SITE CONDITION MONITORING OF ATLANTIC SALMON SACs

Report by the SFCC to Scottish Natural Heritage, Contract F02AC608

J.D.Godfrey

2005

SITE CONDITION MONITORING OF ATLANTIC SALMON SACs Report No: Contractor: Scottish Fisheries Co-ordination Centre BACKGROUND The Scottish Fisheries Co-ordination Centre (SFCC) was commissioned by Scottish Natural Heritage (SNH) to investigate the possibility of using data collected by SFCC members on juvenile salmonid populations in Scottish rivers to generate information useful for conservation decision-making. In particular, the SFCC were asked to help SNH meet their statutory obligation, under the EC Habitats Directive and the EC Water Framework Directive, to monitor and evaluate the status of Atlantic salmon (Salmo salar L) populations in Special Areas of Conservation (SACs) and Candidate SACs (cSACs). This report represents the first stage of the condition assessment for the Atlantic salmon. SNH sought three outputs from the report, which the SFCC undertook to deliver as part of an 18-month contract: 1. An assessment of the possibility of using SFCC data as input into the

Environment Agency’s HABSCORE model (Barnard et al. 1995; Milner et al. 1995, 1998), and to determine the usefulness of this approach.

2. The development of a Scottish version of HABSCORE that will aid the prediction of salmon populations based on habitat characteristics.

3. The development of a Scottish National Fisheries Classification Scheme. 4. An assessment of the current status of Scottish SACs. MAIN FINDINGS • SFCC data are not currently compatible with necessary inputs to the HABSCORE

model for England and Wales • It is not recommended that more resources are allocated to collect data in

Scotland that would enable SFCC data to be used with the HABSCORE model. This is because the HABSCORE model was determined empirically rather than specified biologically, and so may not be a useful predictive tool outwith the geographical area of its derivation. In any case, HABSCORE is in the process of being replaced by the EA with a GIS-based approach.

• After correction and organisation of SFCC data, and of sourcing and refining additional data, two sets of predictive models of juvenile salmon population density in Scotland were developed. These were based on (a) 545 sites with Zippin densities, and (b) 1638 sites with one-run minimum population density estimates that had been electrofished by SFCC members (1997-2002). In both cases sites were selected on criteria of free access for salmon, and absence of pollution and stocking.

• The models explained variation in 17.1 & 17.2% of salmon fry, and 17.8 & 24.2% of salmon parr population density.

• Using estimates of biomass rather than population density allowed more variation to be explained: up to 25.8 & 18.2% for salmon fry, and 30.9 & 19.5% for salmon parr.

• The most important factors predicting population density were Salmon Fishery Region, Channel Stability, Local Landuse and River Level, while key covariates were Substrate, Depth and Flow characteristics, Stream Width, Altitude and Day of Year.

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• A Fisheries Classification Scheme for salmonids was developed using the minimum population density data, providing a national database against which individual sites can be judged. The scheme follows that of the NRA (1995) National Fisheries Classification Scheme in setting out a simple system for grading river sites on the basis of their salmonid populations. The present scheme differs from that of the NRA in one important respect: the regional variation in salmonid population density within Scotland is addressed by generating a grading system for each available Salmon Fishery region (8 of 11).

• A mixed monitoring scheme for the SACs, with both depletion (at established sites) and timed electrofishing (at semi-randomly selected sites) in each of the SACs was adopted, designed to combine high-quality data from a few fixed sites, with sufficiently wide spatial coverage to include the entire SACs.

• Monitoring effort was weighted with SAC area, and the numbers of sites chosen to be electrofished ranged from 6 depletion and 9 timed sites on the smallest SAC to 16 depletion and 25 timed sites on the largest.

• Monitoring work on the SACs was carried out during August-October 2004 and 2005 by SFCC-trained staff. Adequate data were obtained for 16 of the 17 SACs and is presented herein; for the Borgie SAC only a single site was electrofished.

• All the SACs had juvenile fry and parr salmon present at the majority of sites, and overall fry were present at 93.3% and parr at 95.0% of depletion sites.

• Variation in mean population densities between SACs varied over an order of magnitude. Mean SAC fry density per 100m2 ranged from 13.5±s.d.8.4 in North Harris to 144.5±s.d.93.5 on the South Esk. Mean SAC parr density per 100m2 ranged from 5.0±s.d.3.8 on the Endrick to 57.4±s.d.18.3 on the South Esk.

• When compared with the Fisheries Classification Scheme for salmonids there was no evidence to suggest that juvenile salmon numbers in the SACs as a whole varied markedly either above or below that expected from Scottish rivers in general.

• Randomly selected timed fishing sites yielded similar results to the fully-quantitative fishings, suggesting that the pre-established fully-quantitative sites did not give a notably biased picture of the SAC.

• Overall fry were caught at 91.2% of timed sites, and parr at 83.7%, though some SACs had more patchily distributed fish than others.

• Should the survey be repeated, the number of depletion sites sampled in the monitoring programme was adequate to detect either a 50% decrease or a 100% increase in parr population density for most individual SACs at the conventional power level, but the sample sizes were inadequate to detect the same size of population change amongst fry.

• An analysis of post 1952 rod-catch data for adult salmon populations found that the spring sub-population had declined in 9, remained stable in 6, and increased in none of the 15 SACs for which data were available. The summer-running fish had declined in none, remained stable in 11, and increased in 5 of 16 SACs, while the autumn-running fish had declined in 2, remained stable in 8, and increased in 6 of 16 SACs.

• Based on previous data we reasoned that if the declines in spring adult numbers were sufficiently marked as to affect juvenile populations, then it would be evident in the upper reaches of the SACs. However, relative to SACs with stable spring adult numbers, there was no evidence from our analysis for lower juvenile numbers at higher altitude sites on SACs with declining spring adult numbers

• Using the information gained about juvenile populations and for each of the adult population components of the SACs we take a step toward assigning the Favourability status of the rivers.

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CONTENTS Background Main Findings List of Figures List of Tables List of Maps Map Acknowledgements Acknowledgements Introduction 1 CAN HABSCORE BE USED WITH SFCC ELECTROFISHING DATA?

1.1 Summary 1.2 Introduction 1.3 Required inputs to HABSCORE

2 DEVELOPING MODELS OF JUVENILE SALMON POPULATIONS IN SCOTLAND 2.1 Introduction

2.1.1 Spatial autocorrelation in river systems 2.2 Specifying and assessing the models

2.2.1 Additional data 2.2.1.1 Water quality data 2.2.1.2 Catchment data

2.2.2 Site selection 2.2.3 Ideal site selection 2.2.4 Data structure 2.2.5 The models 2.2.6 Data quality control 2.2.6.1 Exporting data issues 2.2.6.2 Data entry issues 2.2.6.3 Absent data

2.3 Results 2.3.1 Spatial autocorrelation

2.3.2 Principal components analysis 2.3.3 The Zippin models

2.3.3.1 Salmon fry population density 2.3.3.2 Salmon fry biomass 2.3.3.3 Salmon parr population density

2.3.3.4 Salmon parr biomass 2.3.4 The One-Run models

2.3.4.1 Salmon fry population density 2.3.4.2 Salmon fry biomass 2.3.4.3 Salmon parr population density

2.3.4.4 Salmon parr biomass 2.4 Discussion

2.4.1 Spatial autocorrelation 2.4.2 Comparison of Zippin and One-Run models 2.4.3 Regional variation in Scotland 2.4.4 Differences between the models and HABSCORE models 2.4.5 Site selection

2.4.6 Characterising habitat 2.4.7 Despotic and Ideal Free Distributions: predicting populations from habitat features 2.4.8 Model usefulness

2.5 Phase 2 Monitoring strategy

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3 A NATIONAL FISHERIES CLASSIFICATION SCHEME

3.1 Introduction 3.2 Scope and methodology 3.3 Fisheries classification scheme

3.3.1 Absolute national classification 3.3.2 Relative national classification 3.3.3 Absolute regional classification 3.3.4 Relative regional classification

4 SAMPLING PROGRAMME OF SAC JUVENILE SALMON POPULATIONS 4.1 Site selection

4.1.1 Introduction 4.1.2 Depletion site selection 4.1.3 Timed site selection 4.1.4 Electrofishing methodology 4.1.5 Surveillance and monitoring

4.2 Different types of estimates of salmon populations in rivers by electrofishing

4.2.1 Timed electrofishing 4.2.2 Semi-quantitative electrofishing 4.2.3 Fully-quantitative electrofishing 4.2.4 Relationships between the various estimates of density

4.3 The SACs 4.3.1 Berriedale and Langwell

4.3.1.1 Depletion sites 4.3.1.2 Timed sites

4.3.2 Bladnoch 4.3.2.1 Depletion sites 4.3.2.2 Historical data 4.3.2.3 Timed sites

4.3.3 Borgie 4.3.4 Dee

4.3.4.1 Depletion sites 4.3.4.2 Timed sites

4.3.5 Endrick 4.3.5.1 Depletion sites 4.3.5.2 Historical data 4.3.5.3 Timed sites

4.3.6 Grimersta 4.3.6.1 Depletion sites 4.3.6.2 Historical data 4.3.6.3 Timed sites

4.3.7 Little Gruinard 4.3.7.1 Depletion sites 4.3.7.2 Historical data 4.3.7.3 Timed sites

4.3.8 Moriston 4.3.8.1 Depletion sites 4.3.8.2 Timed sites

4.3.9 Naver 4.3.9.1 Depletion sites 4.3.9.2 Timed sites

4.3.10 North Harris 4.3.10.1 Depletion sites

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4.3.10.2 Historical data 4.3.10.3 Timed sites

4.3.11 Oykel 4.3.11.1 Depletion sites 4.3.11.2 Historical data 4.3.11.3 Timed sites 4.3.12 South Esk

4.3.12.1 Depletion sites 4.3.12.2 Historical data 4.3.12.3 Timed sites

4.3.13 Spey 4.3.13.1 Depletion sites 4.3.13.2 Historical data 4.3.13.3 Timed sites

4.3.14 Tay 4.3.14.1 Depletion sites 4.3.14.2 Timed sites

4.3.15 Teith 4.3.15.1 Depletion sites 4.3.15.2 Historical data 4.3.15.3 Timed sites

4.3.16 Thurso 4.3.16.1 Depletion sites 4.3.16.2 Timed sites

4.3.17 Tweed 4.3.17.1 Depletion sites 4.3.17.2 Historical data 4.3.17.3 Timed sites

4.4 Synthesis 4.4.1 Population densities 4.4.2 Comparison of SAC densities with the national classification scheme 4.4.3 Variance in population densities: river saturation 4.4.4 Variance in local habitat densities: site saturation

4.4.4.1 Introduction 4.4.4.2 Results and discussion

4.5 Statistical power of the monitoring programme 5 ADULT ATLANTIC SALMON POPULATION ASSESSMENT OF 17 DESIGNATED SACS

5.1 Introduction 5.2 Salmon population structure 5.3 Adult salmon population assessment options

5.3.1 Fish counters 5.3.2 Fish traps 5.3.3 Redd counts 5.3.4 Fishery catch statistics

5.4 Methods 5.4.1 Catch information 5.4.2 Statistical analyses

5.5 Results 5.5.1 Spring component 5.5.2 Summer component 5.5.3 Autumn component

5.6 Discussion

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6 LINKING ADULT AND JUVENILE SALMON POPULATION DATA

6.1 Introduction 6.2 Methods and analysis 6.3 Results 6.4 Discussion

7 TOWARDS ATTRIBUTING SAC CONDITION STATUS 7.1 Juvenile stages 7.2 Adult population components

8 REFERENCES 9 APPENDICES

A Electrofishing recording sheets, 5mm and 1mm B SFCC General Electrofishing Habitat Survey C SFCC Electrofishing Survey Habitat Definitions D MLURI Land Cover of Scotland Categories E Principal Components Analysis

F Timed Electrofishing Protocol G Timed Fishing Recording Sheets

H Timed Fishing Definitions I Monitoring on the South Esk in 2004

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LIST OF FIGURES Figure 1. Variation in percentage of electrofishing sites correctly assigned to their true locations following the snapping procedure to the SEPA Water Quality River Network Figure 2. Variation in difference in (a) altitude and (b) channel width between sites, with the distance (measured along channel length) between those sites, in the Spey catchment (n=152 sites). Figure 3. Variation in difference in (a) population density and (b) fish size of (i) salmonid fry and (ii) salmonid parr between sites with the distance (measured along channel length) between those sites, in the Spey catchment (n=152 sites). Figure 4. National expectations for salmonid population density measured by one-run electrofishing events. Figure 5. Distribution of juvenile salmonid densities in Scotland, showing variation with river width: (a) salmon fry, (b) salmon parr, (c) trout fry, (d) trout parr. Figure 6. Proportion of electrofishing events at selected sites throughout Scotland in which zero juvenile salmonids of particular species/age classes were detected by the one-run technique. Figure 7. Variation in population density of juvenile salmonids by Salmon Fishery Statistical Regions, assessed using one-run electrofishing events. (a) salmon fry, (b) salmon parr, (c) trout fry, (d) trout parr. Figure 8. Variation in juvenile salmonid population densities with site river width, Clyde Coast region. (a) salmon fry (b) salmon parr (c) trout fry (d) trout parr Figure 9. Variation in juvenile salmonid population densities with site river width, East region. (a) salmon fry (b) salmon parr (c) trout fry (d) trout parr Figure 10. Variation in juvenile salmonid population densities with site river width, Moray Firth region. (a) salmon fry (b) salmon parr (c) trout fry (d) trout parr. Figure 11. Variation in juvenile salmonid population densities with site river width, North region (a) salmon fry (b) salmon parr (c) trout fry (d) trout parr Figure 12. Variation in juvenile salmonid population densities with site river width, North West region (a) salmon fry (b) salmon parr (c) trout fry (d) trout parr Figure 13. Variation in juvenile salmonid population densities with site river width, Outer Hebrides region (a) salmon fry (b) salmon parr (c) trout fry (d) trout parr Figure 14. Variation in juvenile salmonid population densities with site river width, Solway region (including the border Esk) (a) salmon fry (b) salmon parr (c) trout fry (d) trout parr Figure 15. Variation in juvenile salmonid population densities with site river width, West region (a) salmon fry (b) salmon parr (c) trout fry (d) trout parr Figure 16. Proportion of sites at which one-run electrofishing events detected zero salmonids (for a particular species/age class).

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Figure 17. The relationship between three-run minimum number of fish and the Zippin density estimates associated with them for a) salmon fry and b) salmon parr. Figure 18. Relationship between the density estimates of a) salmon fry and b) salmon parr populations based on the first run of a 3-run fishing event, and those based on all three runs. Figure 19 Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Berriedale and Langwell rivers. Error bars show upper 95% confidence limit. Figure 20. Number of salmon caught per minute during timed electrofishing at sites on the Berriedale & Langwell, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++. Sites are arranged altitudinally, left lowest. Figure 21. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Bladnoch. Error bars show upper 95% confidence limit. Arrows indicate three-run minimum density estimates. Figure 22. Electrofishing time series data for juvenile salmon 1998-2004, Bladnoch SAC. One-run minimum density estimates. Figure 23. Number of salmon caught per minute during timed electrofishing at sites on the Bladnoch, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++. Sites are arranged altitudinally, left lowest. Figure 24. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Dee SAC. Error bars show upper 95% confidence limit. Arrows indicate where three-run minimum estimate is used. Sites are arranged altitudinally. Figure 25. Number of salmon caught per minute during timed electrofishing at sites on the Dee, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++ Sites are arranged altitudinally, left lowest. Figure 26. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Endrick. Error bars show upper 95% confidence limit. Arrows indicate three-run mininimum density estimates. Figure 27. Time series data for juvenile salmon 2003-2004, Endrick SAC. Estimates of numbers are Zippin depletion estimates where available, but otherwise three-run minimum estimates (see y-axis labels). Error bars (Zippin estimates only) show 95% confidence intervals. Some stocking occurred affecting sites LT9, LT13 and LT14 in 2003, and sites LT10 and LT14 in 2004. Figure 28. Number of salmon caught per minute during timed electrofishing at sites on the Endrick, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++. Sites are arranged altitudinally, left lowest.

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Figure 29. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Grimersta SAC. Error bars show upper 95% confidence limit. Arrow indicates where three-run minimum estimate is used. Figure 30. Electrofishing time series data for juvenile salmon 1998-2004, Grimersta SAC. One-run minimum density estimates. Lan03, Lan 04 and Lan21 are three formerly fished sites in the Grimersta catchment that were not part of the SAC monitoring programme, and no information was collected for them for 2004 Figure 31. Number of salmon caught per minute during timed electrofishing at sites on the Grimersta SAC, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++. Sites are arranged altitudinally, left lowest. Figure 32. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Little Gruinard. Error bars show upper 95% confidence limit. Figure 33. Electrofishing time series data for juvenile salmon 1997-2004, Little Gruinard SAC. One-run minimum density estimates for LGD11 and LGD6, zippin estimates for LGD8. Figure 34. Number of salmon caught per minute during timed electrofishing at sites on the Little Gruinard, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++. Sites are arranged altitudinally, left lowest. Figure 35. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Moriston SAC. Error bars show upper 95% confidence limit. Two sites zero densities of salmon. Figure 36. Number of salmon caught per minute during timed electrofishing at sites on the Moriston SAC in August/September 2005. Five minutes fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all juvenile salmon, b) 0+ salmon, and c) 1++ salmon. Sites are arranged altitudinally, left lowest. Figure 37. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Naver SAC. Error bars show upper 95% confidence limit. Arrows indicate where three-run minimum estimate is used. NB sites L01 and AB01 are known to have been recently stocked. Figure 38. Number of salmon caught per minute during timed electrofishing at sites on the Naver, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++ Sites are arranged altitudinally, left lowest. Figure 39. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites in the North Harris SAC. Error bars show upper 95% confidence limit. Arrow indicates where three-run minimum estimate is used. Figure 40. Electrofishing times series data for juvenile salmon 1997-2004, North Harris SAC. One-run minimum density estimates.

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Figure 41. Number of salmon caught per minute during timed electrofishing at sites in the North Harris SAC, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++. Sites are arranged altitudinally, left lowest. NB: scoop nets were used. Some unintentional stocking from commercial hatchery at NHa3. Figure 42. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites in the Oykel SAC. Error bars show upper 95% confidence limit. Arrow indicates where three-run minimum estimates were used. Figure 43. Electrofishing times series data for juvenile salmon 2001-2005, Oykel SAC. Where error bars (95% c.l.) are shown the density estimates are by the Zippin method, otherwise they are three-run minimum density estimates. Figure 44. Number of salmon caught per minute during timed electrofishing at sites on the Oykel SAC (Sept-Nov 2005). Five minutes fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all juvenile salmon, b) 0+ salmon, and c) 1++ salmon. Sites are arranged altitudinally, left lowest. Figure 45. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the South Esk. Error bars show upper 95% confidence limit. N.B. at site SEC the density is estimated from a single fully stop-netted run (see Table 103 for details. Figure 46. Electrofishing time series data for juvenile salmon 1995-2005, for three sites on the South Esk SAC. All data are Zippin estimates with the exception of SEC for which likely Zippin densities have been estimated from a single run (see Table 107). Error estimates are only available from 2004 onwards, and show 95% confidence limits. Further historical data on the South Esk is shown in Appendix I. Data from 2005 collected to different standards than the previous data, and so no direct comparison can be made. Figure 47. Number of salmon caught per minute during timed electrofishing at sites on the South Esk in August 2005. Five minutes fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all juvenile salmon, b) 0+ salmon, and c) 1++ salmon. Sites are arranged altitudinally, left lowest. Figure 48 Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Spey SAC. Error bars show upper 95% confidence limit. Arrow indicates where three-run minimum estimate is used. Figure 49. Electrofishing time series data for juvenile salmon 1996-2004, for various sites in the Spey SAC, one-run minimum density estimates. Figure 50. Number of salmon caught per minute during timed electrofishing at sites on the Spey, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++ Sites are arranged altitudinally, left lowest. Figure 51. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Tay SAC. Error bars show upper 95% confidence limit. Arrows indicate where three-run minimum estimate is used. Figure 52. Number of salmon caught per minute during timed electrofishing at sites on the Tay, 2004. Five minutes of fishing were conducted in each of the three flow

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types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++ Sites are arranged altitudinally, left lowest. NB. Run was not fished at Ta4. Figure 53. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Teith. Error bars show upper 95% confidence limit. Arrows indicate three-run minimum density estimate. Figure 54. Electrofishing time series data for juvenile salmon for available sites in the Teith SAC, 2002-2004. Note that the y-axis scale varies between graphs. Zippin density estimates (no 100m-2) are shown, but where zero fish were caught for a given age class, this has been marked, though, strictly, Zippin estimates of zero are impossible. For the site Teith 8, three-run minimum data is shown. Figure 55. Number of salmon caught per minute during timed electrofishing at sites on the Teith, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++. Sites are arranged altitudinally, left lowest. Figure 56. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Thurso. Error bars show upper 95% confidence limit. Figure 57. Number of salmon caught per minute during timed electrofishing at sites on the Thurso, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++. Sites are arranged altitudinally, left lowest. Figure 58. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Tweed SAC. Error bars show upper 95% confidence limit. Arrows indicate where three-run minimum estimate is used. NB. Error bar for EN 02 1++ is off the scale, see Table 120. Figure 59. Juvenile salmon populations densities estimated by the Zippin method for all sites electrofished on the Tweed in 2004. Sites fished for SAC monitoring are arranged on the left. Where Zippin estimates were not calculable three-run minimum estimates have been used: for 0+ fish his applies to the sites EN02, KE01, OM01, SG03, TL06, TT01 AND BT02; for 1++ fish to sites TW02, RE01, RE03, SG01, SG03, TL06, BK02, BT02 AND BT05. Figure 60. Zippin estimates of salmon fry (0+) and salmon parr (1++) densities at electrofishing sites on the Tweed between 1988 and 2004. The scales of both x and y axes vary, but in each case the last data point is from 2004. Error bars show 95% confidence intervals. The final graph in the series, for site EN 02, shows three-run minimum density estimate. Figure 61. Number of salmon caught per minute during timed electrofishing at sites on the Tweed, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++. Sites are arranged altitudinally, left lowest. Figure 62. a) Mean Zippin density estimates of salmon fry and parr for each SAC b) three-run minimum density estimates for salmon fry and parr c) number of salmon fry and parr caught per minute by timed fishing. Error bars show s.d. Figure 63. Relationship between SAC mean salmon fry density estimates from depletion sites and SAC mean salmon fry numbers caught per minute at timed sites.

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After exclusion of the outlier (Oykel SAC) the relationship is described by the equation , log no. fry min-1 = -1.491 + 0.998 x log Zippin fry density, (d.f. =15, P<0.001, R2=0.78) Figure 64. Comparison of the first run minimum density estimate of the SAC depletion sites with 50th percentile of mixed one-run and first run minimum density estimates for the Salmon Fishery Statistical Region in which the SAC is sited (1997-2002). Only sites where fish were present contribute to the calculation of the 50th percentile, and it is corrected for river width class (see section 3.3.4). No data were available for the North East Region (South Esk & Dee). Figure 65. The mean proportions of a) salmon 0+ and b) salmon 1++ caught in glide, riffle and run habitats in the timed sites on 14 SACs. In general riffles had the highest numbers of both age categories, and glides the lowest. Figure 66. Relationships between mean numbers of parr caught across timed sites in a SAC and the mean proportion of parr caught in the flow-types a) glide, b) run and c) riffle. Proportional habitat use was not related to average population density Figure 67. Plots of standardised catches (annual values divided by the long term mean) including the fitted trend and 95% reference bands by component and by fishery district. Figure 68. Distribution of three-run population densities of salmon fry and parr with altitude in the SACs. The x-axis shows the full altitudinal range of the designated SAC, with the exception of the special case of the North Harris estate (which is not river-based) where the estimated maximum altitude that salmon reach is shown. The altitude range for the Little Gruinard is suspect as channels linking to the loch which forms the highest part of the SAC are not included in the SAC; on this graph an arrow marks the highest river channel included in the SAC. Figure 69. Mean rank of the ratio of lower catchment to upper catchment salmon fry and parr population density in relation to the status of spring adult rod-catch data from the last 50 years. Higher mean ranks indicate relatively low juvenile population density in the upper catchment. The density estimate used for the analyses was the three-run minimum. a) shows the results when upper and lower are divided at the mid altitude point of the SAC, b) shows the result when the dividing point is between the lower two thirds of the SAC’s altitude range and the upper third. Each SAC contributes one rank for each of fry and parr. Sample sizes: a) 8 SACs for declining, 6 for stable, and 1 to unknown (North Harris); b) 6 fot declining, 4 for stable, and 1 for unknown (North Harris). Neither analysis suggests a significant relationship between adult population status and upper catchment juvenile population density.

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LIST OF TABLES Table 1. Data requirements for generating salmonid population density predictions using HABSCORE, together with an assessment of SFCC data compatibility. Table 2. Available variables expected to influence juvenile salmonid population density in Scottish rivers. Table 3. Factors for which no data were available that may influence juvenile salmonid population density in Scottish rivers. Table 4. Summary of Principal Components Axes used in the models Table 5. Summary of between-subjects effects for the general linear model of salmon fry population density (ln no 100m-2) in Scotland, based on electrofishing Zippin estimates. Table 6. Parameter estimates for the general linear model of minimum salmon fry population density (ln no 100m-2) based on Zippin densities from electrofishing events. Table 7. Summary of between-subjects effects for the general linear model of salmon fry biomass (ln g 100m-2) in Scotland, based on Zippin estimates from electrofishing events. Table 8. Parameter estimates for the general linear model of minimum salmon fry biomass (ln g 100m-2) in Scotland, based on Zippin densities from electrofishing events. Table 9. Summary of between-subjects effects for the general linear model of salmon parr population density (ln no 100m-2) in Scotland, based on Zippin estimates from electrofishing events. Table 10. Parameter estimates for the general linear model of salmon parr population density (ln no 100m-2) based on Zippin estimates from electrofishing events. Table 11. Summary of between-subjects effects for the general linear model of salmon parr biomass ((ln(g 100m-2))2) in Scotland, based on Zippin estimates from electrofishing events. Table 12. Parameter estimates for the general linear model of salmon fry biomass (ln g 100m-2) in Scotland, based on Zippin estimates from electrofishing events. Table 13. Summary of between-subjects effects for the general linear model of minimum salmon fry population density (ln no 100m-2) in Scotland, based on one-run electrofishing events. Table 14. Parameter estimates for the general linear model of minimum salmon fry population density (ln no 100m-2) based on one-run electrofishing events. Table 15. Summary of between-subjects effects for the general linear model of minimum salmon fry biomass (ln g 100m-2) in Scotland, based on one-run electrofishing events

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Table 16. Parameter estimates for the general linear model of minimum salmon fry biomass (ln g 100m-2) based on one-run electrofishing events. Table 17. Summary of between-subjects effects for the general linear model of minimum salmon parr population density (ln no 100m-2) based on one-run electrofishing events at sites throughout Scotland Table 18. Parameter estimates for the general linear model of minimum salmon parr population density (ln no 100m-2) based on one-run electrofishing events. Table 19. Summary of between-subjects effects for the general linear model of minimum salmon parr biomass (g 100m-2) based on one-run electrofishing events throughout Scotland Table 20. Parameter estimates for the general linear model of minimum salmon parr biomass (ln g 100m-2) based on one-run electrofishing events at sites throughout Scotland. Table 21. Summary of the explanatory factors (capitalised) and covariates used in the models of Salmon population density and biomass for One-Run and Zippin electrofishing estimates. Table 22. The basic structure of the fisheries classification scheme Table 23. Quintile Ranges for juvenile Salmonid density from 1638 sites on rivers throughout Scotland, based on one-run electrofishing events. Table 24. Summary of juvenile salmonid population densities (number 100m-2) for different classes of river width throughout Scotland, based on one-run electrofishing events. Table 25 Quintile Ranges for juvenile Salmonid density (numbers 100m-2) based on one-run electro-fishing events, for the various Salmon Fishery Statistical Regions. Table 26. Summary of juvenile salmonid population densities (number 100m-2) in different river width classes, based on one-run electrofishing events for the various Salmon Fishery Statistical Regions. Table 27. The number of depletion and timed electrofishing sites in the sampling programme agreed between SNH and the SFCC and the actual number of sites achieved in 2004. Table 28. Linear regression describing the relationship between three-run minimum and depletion density estimates. Table 29. Linear regression equations predicting 3-run minimum density estimates from the first run. Table 30. Details of depletion sites, Berriedale & Langwell SAC. Table 31. Details of depletion electrofishing for 0+ and 1++ salmon, Berriedale & Langwell SAC. Table 32. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Berriedale & Langwell SAC.

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Table 33. Fork length of salmon of different age classes, Berriedale & Langwell SAC. Table 34. Details of timed electrofishing sites, Berriedale and Langwell SAC. Table 35. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Berriedale & Langwell SAC. Each habitat type was fished for five minutes. Table 36. Presence/absence of salmon year classes, and of trout at timed sites, Berriedale & Langwell SAC. Table 37. Details of depletion sites, Bladnoch SAC. Table 38. Details of depletion electrofishing for 0+ and 1++ salmon, Bladnoch SAC. Table 39. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Bladnoch SAC. Table 40. Fork length of salmon of different age classes, Bladnoch SAC. Table 41. Details of timed electrofishing sites, Bladnoch SAC. Table 42. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Bladnoch SAC. Each habitat type was fished for five minutes. Table 43. Presence/absence of salmon year classes, and of trout at timed sites, Bladnoch SAC. Table 44. Details of the timed electrofishing site, Borgie SAC. Table 45. Salmon CPUE in glide, run and riffle habitats at a timed electrofishing site on the Borgie SAC. Each habitat type was fished for five minutes. Table 46. Presence/absence of salmon year classes, and of trout at the timed site, Borgie SAC. Table 47. Details of depletion sites, Dee SAC. Table 48. Details of depletion electrofishing for 0+ and 1++ salmon, Dee SAC. Table 49. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Dee SAC. Table 50. Fork length of salmon of different age classes, Dee SAC. Table 51. Details of timed electrofishing sites, Dee SAC. Table 52. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Dee SAC. Each habitat type was fished for five minutes. Table 53. Presence/absence of salmon year classes, and of trout at timed sites, Dee SAC. Table 54. Details of depletions sites, Endrick SAC.

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Table 55. Details of depletion electrofishing for 0+ and 1++ salmon, Endrick SAC. Table 56. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Endrick SAC. Table 57. Fork length of salmon of different age classes, Endrick SAC. Table 58. Details of timed electrofishing sites, Endrick SAC. Table 59. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Endrick SAC. Each habitat type was fished for five minutes. Table 60. Presence/absence of salmon year classes, and of trout at timed sites, Endrick SAC. Table 61. Details of depletion sites, Grimersta SAC. Table 62. Details of depletion electrofishing for 0+ and 1++ salmon, Grimersta SAC. Table 63. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Grimersta SAC. Table 64. Fork length of salmon of different age classes, Grimersta SAC. Table 65. Details of timed electrofishing sites, Grimersta SAC. Table 66. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Grimersta SAC. Each habitat type was fished for five minutes. Table 67. Presence/absence of salmon year classes, and of trout at timed sites, Grimersta SAC. Ageing of 1+ and 2+ parr was tentative. Table 68. Details of depletion sites, Little Gruinard SAC. Table 69. Details of depletion electrofishing for 0+ and 1++ salmon, Little Gruinard SAC. Table 70. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Little Gruinard SAC. Table 71. Fork length of salmon of different age classes, Little Gruinard SAC. Table 72. Details of timed electrofishing sites, Little Gruinard SAC. Table 73. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Little Gruinard SAC. Each habitat type was fished for five minutes. Table 74. Presence/absence of salmon year classes, and of trout at timed sites, Little Gruinard SAC. Table 75. Details of depletion sites, Moriston SAC. Table X1. Details of depletion electrofishing for 0+ and 1++ salmon, Moriston SAC.

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Table 76. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Moriston SAC. Table 77. Fork length of salmon of different age classes, Moriston SAC. Table 78. Details of timed electrofishing sites, Moriston SAC, 2005. Table 79. Salmon cpue in glide, run and riffle habitats at timed electrofishing sites on the Moriston SAC, 2005. Each habitat type was fished for five minutes. Table 80. Presence/absence of salmon year classes, and of trout at timed sites, Moriston SAC, 2005 Table 81. Details of depletion sites, Naver SAC. Table 82. Details of depletion electrofishing for 0+ and 1++ salmon, Naver SAC. Table 83. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Naver SAC. Table 84. Fork length of salmon of different age classes, Naver SAC. Table 85. Details of timed electrofishing sites, Naver SAC. Table 86. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Naver SAC. Each habitat type was fished for five minutes. Table 87. Presence/absence of salmon year classes, and of trout at timed sites, Naver SAC. Table 88. Details of depletion sites, North Harris SAC. Table 89. Details of depletion electrofishing for 0+ and 1++ salmon, North Harris SAC. Table 90. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, North Harris SAC. Table 91. Fork length of salmon of different age classes, North Harris SAC. Table 92. Details of timed electrofishing sites, North Harris SAC. Table 93. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the North Harris SAC. Each habitat type was fished for five minutes. Table 94. Presence/absence of salmon year classes, and of trout at timed sites, North Harris SAC. Table 95. Details of depletion sites, Oykel SAC. Table 96. Details of depletion electrofishing for 0+ and 1++ salmon, Oykel SAC. Table 97. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Oykel SAC.

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Table 98. Fork length of salmon of different age classes, Oykel SAC. Table 99. Details of timed electrofishing sites, Oykel SAC, 2005. Table 100. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Oykel SAC, 2005. Each habitat type was fished for five minutes. Table 101. Presence/absence of salmon year classes, and of trout at timed sites, Oykel SAC, 2005. Table 102. Details of depletion sites, South Esk SAC. Table 103. Details of depletion electrofishing for 0+ and 1++ salmon, South Esk SAC in 2005. Table 104. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, South Esk SAC. Table 105. Fork length of salmon of different age classes, South Esk SAC. Table 106. Details of timed electrofishing sites, South Esk SAC, 2005. Table 107. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the South Esk SAC, 2005. Each habitat type was fished for five minutes. Table 108. Presence/absence of salmon year classes, and of trout at timed sites, South Esk SAC, 2005. Table 109. Details of depletion sites, Spey SAC. Table 110. Details of depletion electrofishing for 0+ and 1++ salmon, Spey SAC. Table 111. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Spey SAC. Table 112. Details of timed electrofishing sites, Spey SAC. Table 113. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Spey SAC. Each habitat type was fished for five minutes. Table 114. Presence/absence of salmon year classes, and of trout at timed sites, Spey SAC. Table 115. Details of depletion sites, Tay SAC. Table 116. Details of depletion electrofishing for 0+ and 1++ salmon, Tay SAC. Table 117. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Tay SAC. Table 118. Fork length of salmon of different age classes, Tay SAC. Table 119. Details of timed electrofishing sites, Tay SAC.

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Table 120. Salmon cpue in glide, run and riffle habitats at timed electrofishing sites on the Tay SAC. Each habitat type was fished for five minutes. Table 121. Presence/absence of salmon year classes, and of trout at timed sites, Tay SAC. Table 122. Details of depletion sites, Teith SAC. Table 123. Details of depletion electrofishing for 0+ and 1++ salmon, Teith SAC. Table 124. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Teith SAC. Table 125. Fork length of salmon of different age classes, Teith SAC. Table 126. Details of timed electrofishing sites, Teith SAC. Table 127. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Teith SAC. Each habitat type was fished for five minutes. Table 128. Presence/absence of salmon year classes, and of trout at timed sites, Teith SAC. Table 129. Details of depletion sites, Thurso SAC. Table 130. Details of depletion electrofishing for 0+ and 1++ salmon, Thurso SAC. Table 131. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Thurso SAC. Table 132. Fork length of salmon of different age classes, Thurso SAC. Table 133. Details of timed electrofishing sites, Thurso SAC. Table 134. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Thurso SAC. Each habitat type was fished for five minutes. Table 135. Presence/absence of salmon year classes, and of trout at timed sites, Thurso SAC. Table 136. Details of depletion sites, Tweed SAC. Table 137. Details of depletion electrofishing for 0+ and 1++ salmon, Tweed SAC. Table 138. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Tweed SAC. Table 139. Fork length of salmon of different age classes, Tweed SAC. Table 140. Details of timed electrofishing sites, Tweed SAC. Table 141. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Tweed SAC. Each habitat type was fished for five minutes.

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Table 142. Presence/absence of salmon year classes, and of trout at timed sites, Tweed SAC. Table 143. Summary of depletion and timed fishings at 14 SACs. Sample sizes can be found in preceding sections covering individual SACs. Table 144. Comparison of regional percentage of electrofishing sites with zero salmon 0+ and sites with zero salmon 1++ estimated from a one-run fishings and first-run fishings with the first run of the SAC depletion fishings. Table 145. Coefficients of variation from depletion density estimates and from three-run minimum estimates together with the percentage of sites with no fish caught in 0+ and 1++ age categories. Table 146. Coefficients of variation and percentage of sites with no fish caught in 0+ and 1++ age categories from numbers caught in timed fishings. Table 147. Depletion site sample sizes required to detect a 50% decline (with constant coefficient of variation) in juvenile salmon populations (0+ and 1++ age classes) on the SACs based on observed variation and for three levels of statistical power, with α held at 0.05 throughout. To achieve the power indicated the each survey year requires the number of sample sites indicated. Table 148 Depletion site sample sizes required to detect a 50% decline from the actual data (with constant coefficient of variation) in juvenile salmon populations (0+ ans 1++ age classes) on the SACs based on observed variation and for three levels of statistical power, with α held at 0.05 throughout. Table 149. Depletion site sample sizes required to detect a 100% increase (with constant coefficient of variation) in juvenile salmon populations on the sacs based on observed variation and for three levels of statistical power, with α held at 0.05 throughout. To achieve the power indicated the each survey year requires the number of sample sites indicated Table 150. Depletion site sample sizes required to detect a 100% increase from the actual data (with constant coefficient of variation) in juvenile salmon populations (0+ and 1++ age classes) on the sacs based on observed variation and for three levels of statistical power, with α held at 0.05 throughout. Table 151. The power to detect a 50% decline in juvenile salmon numbers assuming a repeat of the sampling effort of 2004/2005. Table 152. The power to detect a 100% increase in juvenile salmon numbers assuming a repeat of the sampling effort of 2004/2005. Table 153. The 17 SACs and the associated fishery districts from which catch information was used in the adult population assessment. Table 154. Results of F-test to determine whether the trend lines fitted to the catch data were significantly different to a straight line through the mean value. Table 155.The n-fold change and direction between recorded catch at the beginning (1952) and end (2002) of the time series considered.

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Table 156. Relationships between salmon fry and parr and altitude in the SACs. Table 157. Assessment of the condition status of Atlantic salmon SACs on the basis of juvenile populations. Separately for fry and parr stages favourable status was conferred on those SACs with a median grade of C when the zero densities were included in the 0-20 percentile range (see accompanying text). Table 158. Favourable condition status for Atlantic salmon SACs on the basis of changes in adult populations (estimated from rod catch data) since the date of SAC designation. Each SAC’s condition status is defined as Favourable (Y) or Not favourable (N)

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LIST OF MAPS Map 1. Distribution of SFCC quantitative electrofishing sites with associated habitat data available at the time of analysis. Map 2. The Salmon Fishery Statistical regions of Scotland. Map 3. Distribution of depletion and timed electrofishing sites on the Berriedale and Langwell SAC. Map 4. Distribution of depletion and timed electrofishing sites on the Bladnoch SAC. Map 5. Location of the single timed electrofishing site on the Borgie SAC Map 6. Distribution of depletion and timed electrofishing sites on the Dee SAC. Map 7. Distribution of depletion and timed electrofishing sites on the Endrick SAC. Map 8. Distribution of depletion and timed electrofishing sites on the Grimersta SAC. Map 9. Distribution of depletion and timed electrofishing sites on the Little Gruinard SAC. Map 10. Distribution of depletion and timed electrofishing sites on the Moriston SAC. Map 11. Distribution of depletion and timed electrofishing sites on the Naver SAC. Map 12. Distribution of depletion and timed electrofishing sites in the North Harris SAC. Map 13. Distribution of depletion and timed electrofishing sites in the Oykel SAC. Map 14. Distribution of depletion and timed electrofishing sites on the South Esk SAC. Map 15. Distribution of depletion and timed electrofishing sites on the Spey SAC. Map 16. Distribution of depletion and timed electrofishing sites on the Tay SAC. Map 17. Distribution of depletion and timed electrofishing sites on the Teith SAC. Map 18. Distribution of depletion and timed electrofishing sites on the Thurso SAC. Map 19. Distribution of depletion and timed electrofishing sites on the Tweed SAC.

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MAP ACKNOWLEDGEMENTS SAC extent - JNCC Catchment rivers - CEH, derived from OS 1:50,000 Panorama DTM Catchment lochs - Land Cover of Scotland 1:25,000 (MLURI,1993) SFSR boundaries - Fisheries Research Services Catchment rivers displayed in maps are based on digital spatial data licensed from the Centre for Ecology and Hydrology, © CEH. Data include material based on Ordnance Survey 1:50,000 maps with the permission of the controller of Her Majesty's Stationery Office © Crown copyright. ACKNOWLEDGEMENTS I would like to thank the following representatives (or former representatives) of the Scottish Fisheries Co-ordination Centre for their participation in the electrofishing monitoring programme and/or for making available previous electrofishing surveys: Helen Bilsby, Mark Bilsby, Colin Bull, Ronald Campbell, Peter Cunningham, Adrian Hudson, Marshall Halliday, James Hunt, Bob Laughton, Simon McKelvey, Iain McMyn, Jamie Ribbens, David Summers, Willie Shearer and Willie Yeomans, together with other staff at Clyde River Foundation, Conon DSFB, Dee DSFB, Esk DSFB, Forth Fisheries Foundation, Galloway Fisheries Trust, Kyle of Sutherland DSFB, Spey Research Trust, Tay DSFB, Tweed Foundation, Wester Ross Fisheries Trust and Western Isles Fisheries Trust. In addition thanks are due to staff (or former staff) at the Fisheries Research Services Freshwater Laboratory, in particular Hilary Anderson (SFCC), John Armstrong, Malcolm Beveridge, Ross Gardiner, Julian Maclean, Joe Thorley and Alan Youngson, who all made a significant contribution to the development of this report. Finally I would like to acknowledge Colin Bean (SNH) for his patience and encouragement.

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INTRODUCTION Under European legislation (Council Directive 92/43 EEC, Habitats Directive adopted 1992) member states are required to maintain habitats and populations of species listed in Annex II of the directive. This list includes the Atlantic salmon (Salmo salar L.). In Scotland 11 Special Areas of Conservation (SACs) have been designated that include salmon as a primary qualifier, and there are a further six SACs where salmon are regarded as a secondary qualifier to the designation for another Annex II species. A key part of the SAC process for both species and habitats is to monitor target populations/habitats to form an assessment of their condition. The aim of the monitoring exercise is to be able to define the population as one of the following four categories: Favourable; Unfavourable (with sub-categories of Declining, Maintained, Recovering); Partially Destroyed; and Destroyed. Scottish Natural Heritage (SNH) asked the Scottish Fisheries Co-ordination Centre (SFCC) to provide an assessment of salmon populations in SACs, based upon data for juvenile (pre-marine stage) salmon. In the first three chapters of this report, we will examine data on juvenile salmon populations from the full range of rivers in which they have been collected and collated by the SFCC. This is hoped to provide the necessary background for understanding and assessing the particular status of the populations in SAC rivers, which will form the focus of chapters 4 to 6. Scottish rivers are undoubtedly a stronghold of the Atlantic salmon in Europe. Populations of salmon in Scotland are of both economic value and conservation concern, and as a consequence, have been the subject of considerable research. However, difficulties inherent in the study of a wide-ranging aquatic animal have left many questions about how salmon populations function unanswered. The two distinct life-stages of the salmon, freshwater and marine have been difficult to connect, and in this report we shall concentrate on the juvenile salmon populations of Scottish rivers. Whilst juvenile salmonid data are the most tractable for the purpose of analysis, it should be noted at the outset that any assessment based solely on juvenile populations cannot be taken to represent a complete assessment of, and may not even be the most important component of, true population status. We briefly examine adult populations on the SACs in chapter 5. Despite extensive electrofishing surveys carried out over many years, there is limited published information on the relationship between juvenile salmon density and habitat features in Scotland. This in part is a consequence of the complex conceptual and analytical framework that any investigation involving river networks must entail, part due to the great complexity of interacting biotic and abiotic habitat features important to salmonids (Armstrong et al. 2003), and part due to the piecemeal nature of much of the data. Before the SFCC was formed, electrofishing data were collected and held in isolation by a variety of District Salmon Fishery Boards. Recently most of the data from individual districts have been entered into centrally-based databases, into which SFCC members now add all new electrofishing records. At the time of the instigation of this work, data were available up to and including the year 2002. This dataset represents a huge investment in time and effort by SFCC members, and is a unique resource for understanding the relationship between riverine habitat and juvenile salmonid populations. However, although direct links between habitat features and population densities have certainly never been explored on this scale in Scotland before, the development of the model HABSCORE (Milner et al. 1993, Wyatt et al. 1995) represented an equivalent task for England and Wales. HABSCORE is an empirically-based model

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that is used to predict salmonid densities based on local habitat features. Several habitat features were identified as significant predictors of salmon fry numbers. The positive predictors were total instream cover for a >10cm fish; link number of reach; cobble substrate with shallow flow; and gravel substrate with turbulent flow. The negative predictors for fry were conductivity; degree of substrate embeddedness; substrate diversity; cobble substrate; cobble substrate with shallow, smooth flow; cobble substrate with shallow, turbulent flow; gravel substrate with shallow, smooth flow; and gravel substrate with deep, turbulent flow. For Salmon parr (1++) positive predictors were distance from principal source; site altitude; link number of reach; and cobble substrate with shallow, smooth flow. The negative predictors were cross-sectional area and conductivity. Much can be predicted from various smaller scale studies of salmonid habitat preferences from around the world. Several excellent reviews of these studies are available (Armstrong et al. 2003; Heggenes 1990; EU Life in Rivers Project 2001), detailing the ranges of conditions which are used by various stages of the life-cycle. Heggenes (1990) identifies depth, current, substrate and cover as the key features of habitat that influence salmonid population density and distribution. Armstrong et al. (2003) review studies that have quantified the use of these features. Salmon fry use water velocities typically within the range 10-40cms-1; water depth typically within the range 5-65cm; and substrate size within the range 16-256mm (pebbles and cobbles). A wide variety of cover types were identified, including deep/turbulent water, undercut banks, fallen logs, submerged or overhanging vegetation, rocks and other submerged objects. Salmon parr seem to use slightly faster water velocities, slightly deeper water (20-70cm), and slightly larger substrate size (64-512+mm). Clearly cover will be provided from the same sources as those for 0+ fish, except that the smallest types of cover may be inadequate. Even if true representations of salmon preferences, the features that tend to be used may have only a slight influence on salmon population density, and the size of this influence may vary with the degree to which the carrying capacity of the environment has been reached (Armstrong et al. 2003). Nevertheless, the information currently available gives a firm basis for the specification of a model based on known, or deduced, aspects of salmon biology.

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1 CAN HABSCORE BE USED WITH SFCC ELECTROFISHING DATA? 1.1 Summary HABSCORE is an empirical model for predicting salmonid population density using habitat variables, based on reference sites in England and Wales. Its use for predicting salmonid densities in Scottish rivers, though of interest, is therefore of somewhat dubious value. Furthermore, the habitat data collected by the SFCC for its electrofishing sites is not compatible with HABSCORE’s required inputs. Even an extensive site re-survey program for the necessary habitat data, together with the gleaning of some new data from GIS sources, would still render less than a third of the current SFCC records useable. It appears therefore that the effort involved in collecting data compatible with HABSCORE would be greater than the rewards would merit, and that the most appropriate use of the available data is to develop an alternative predictive model for and from Scottish rivers. 1.2 Introduction HABSCORE is a model developed by the former National Rivers Authority (NRA) and the Environment Agency (EA) as a guide to the quality status of sites monitored for salmonid populations by electrofishing (Barnard et al. 1995). The model was constructed using electrofished sites in England and Wales. Sites with known and identifiable environmental impacts were removed from the database, so that the reference population (in all 602 sites) could be regarded as “notionally pristine”. Fish density and habitat data were collected over a two year period at these sites, and five best-fit multiple regression models were developed (for five different species/age classes), using a range of habitat variables to explain population densities. All significant main effects were included in the models, regardless of theoretical underpinning, but no first or higher order interactions were fitted. The models are intended to be used to predict ‘ideal’ population densities at other sites based on habitat variables. This is an end in itself, but the main purpose of the model is to use the discrepancy between predicted and actual populations at such sites to evaluate their status. The limitations of this approach are discussed in section 2, nevertheless the HABSCORE models account for a large proportion of the variation in salmonid population densities for the sites from which it was developed (43-47% for 3 different age/size classes of trout, 41% for 0+ salmon and 29% for >0+ salmon). The models accounted for between 45 and 87% of the total spatial variation in the dataset. Part of the remit of this report is to determine whether SFCC data could be used in conjunction with HABSCORE to develop predictions of salmonid populations for Scottish rivers. It is acknowledged that predictions based on samples entirely outwith the target population is a dubious exercise (Fausch et al. 1990; Cowx 2002, Draft), yet the SFCC dataset seems to provide an ideal opportunity to make use of HABSCORE, for comparative purposes. The SFCC has overseen, and collated, a rigorous, standardised collection of both habitat and salmonid population density data across large areas of Scotland. However, if habitat-based predictions of salmonid density are to be applied from HABSCORE to SFCC sites, then there must be a very high degree of compatibility between the two habitat data collection protocols. There must also be consistent methods of estimating population density between the two datasets if the SFCC population densities are to be meaningfully compared with HABSCORE predictions.

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1.3 Required inputs to HABSCORE Outlined briefly below are the data input requirements for the latest HABSCORE model (Oct 2000). The input data is divided into three forms: HABform (detailing local habitat features), MAPform (information on catchment characteristics), and FISHform (the fish population density data). The latter is not essential for making predictions of expected population levels, but is necessary for assessment of site-status relative to expectations. The variables required in the three forms are collated in Table 1, together with an assessment of the extent to which the SFCC data are compatible with them. Table 1. Data requirements for generating salmonid population density predictions using HABSCORE, together with an assessment of SFCC data compatibility. Variables in italics are not essential for model use. HABSCORE DATA REQUIREMENTS SFCC DATA COMPATIBLE? HABform Site identification: various: YES Riparian Shading: YES Migratory Access: YES Substrate embeddedness: Partially recorded Flow conditions at time: Partially recorded Upstream land-use: NOT RECORDED* Potential Impacts: Partially recorded Reach dimensions: YES Width and depth profile at stop nets: NO Section dimensions: YES Substrate: NO Flow type: Partially recorded Sources of cover for >10cm trout: NO MAPform Site identification: YES Distance of site from principal source: NOT RECORDED* Distance from tidal limit: NOT RECORDED* Link number: NOT RECORDED* Downstream link number NOT RECORDED* Site Altitude: YES River Discharge Code: NOT RECORDED Mean Conductivity: YES but rarely recorded Catchment Gradient (1085 slope): NOT RECORDED* Site Gradient: NOT RECORDED* FISHform† Various: YES † data required for comparing predicted and actual salmonid densities * potential for data to be obtained using maps Table 1 indicates that many essential variables are either not recorded in the SFCC protocol (reach dimensions, section dimensions, distance from principal source, distance from tidal limit, link number, downstream link number, river discharge code, catchment gradient and site gradient) or are recorded in a non-compatible way

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(substrate embeddedness, width and depth profile at stop nets, substrate, flow type, sources of cover for >10cm trout). While several of these missing variables could be obtained using GIS, there would remain significant absences in the HABform section, rendering the use of HABSCORE impossible. Table 1 does not highlight the most important difference between the two systems: where the SFCC protocol uses estimates of overall averages of habitat variables throughout a site, HABSCORE requires a division of a contiguous site into a number of 10-metre sections that each have independent estimates for the various habitat variables (and fish density). In other words, the HABSCORE model requires a finer level of detail than the SFCC data provides. Nor would it be possible to use repeated input of the SFCC average values in to each of the 10-metre sections in the HABSCORE software, because the variation within a site is used to derive some of the model parameters. To enable SFCC data to be used with HABSCORE would entail, as a minimum, revisits to each site of interest (total number of sites=1638) to obtain section dimensions, width and depth profiles at stopnets, substrate type, substrate embeddedness, and sources of cover. Many sites are in any case revisited annually, but a new protocol would have to be developed and disseminated, and the SFCC member biologists consulted before such work might be undertaken. Even if this were done, conductivity measurements, though included in the SFCC protocol, have been recorded rather rarely and cannot be recorded in retrospect, but are an essential input to the HABSCORE, so that only a small proportion (less than a third) of the historical records could be used. The effort involved in making it possible for the SFCC data to be used with the HABSCORE model would appear to outweigh its advantages. Instead, it seems more appropriate to develop a predictive model for Scottish salmonid populations based on the available Scottish data. However, specific future sites of interest (for example sites in SACs for salmon) might be deemed worthy of being approached with both the HABSCORE and SFCC protocols in mind, should sufficient resources be available.

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2 DEVELOPING MODELS OF JUVENILE SALMON POPULATIONS IN SCOTLAND 2.1 Introduction A major required output of this report is the development of a model which closely predicts Habitat Quality Scores and Habitat Utilisation Indices (sensu HABSCORE, Milner et al. 1998) for Scottish river systems. Habitat Quality Scores (HQSs) are a measure of the salmonid densities that a given site is expected to support, based on habitat characteristics, whereas Habitat Utilisation Indices (HUIs) are a measure of the relationship between observed and expected salmonid density. We view the modelling exercise as an approach to assessing the “condition” of Atlantic salmon in SACs, and to establishing the range of conditions which may be regarded as “favourable” or otherwise. At this early stage of the development of the SAC rivers monitoring program, there is little sound information to deploy, save for measures of species population density and length. These on their own are not regarded as sufficient for designation of “favourable condition” on SAC sites, since they provide no information regarding what population densities should be expected under truly favourable conditions at these sites. One approach to improving this understanding is the attempt to account for the effect of habitat variables on salmonid population size. The success of any modelling approach, particularly when it is correlative in nature, as here, relies on the quality of data, but also on the most appropriate explanatory variables having been recorded. The data collected under the aegis of the SFCC represents the product of considerable experience of the likely influence of habitat on salmonid populations. It consists of two concomitant parts: 1. electofishing surveys 2. riverine habitat surveys. These have been collected by SFCC members in most regions of Scotland, providing a broad coverage of Scottish rivers. However, currently there are some important omissions (the Tay and Dee catchments). Data from the SFCC members are submitted to a central database held by SFCC at the Fisheries Research Services Freshwater Laboratory in Pitlochry. The survey techniques have been standardised since 1997, and while some areas had been collecting similar data for many years previously, these electrofishing events are regarded as non-conformant with subsequent SFCC data (SFCC 2001a), and are consequently excluded from most analyses. The standard data-recording sheets are shown in Appendices A and B with habitat definitions in Appendix C. Further details concerning the data collection protocol are available in the SFCC Electrofishing and Habitat Survey training manuals (SFCC 2001b and 2001c). Salmonid populations are expected to vary from site to site due to a variety of influences existing in different spatial and temporal scales. Among these are local habitat features (eg substrate, depth, cover), catchment-wide habitat features (land-use, geology), and stochastic climatic events (floods, freezing conditions). The SFCC habitat surveys collect data only on the first of these. In seeking to elucidate relationships between juvenile salmonids and riverine habitat, we have attempted to account for variation due to these other sources as well, by obtaining data relating to catchment-wide effects, but were unable to obtain appropriate information of stochastic events. Instead the typical magnitude of stochastic influences may be

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deduced from the size of between year variation at sites with more than one population survey. We set out to develop a series of models of salmonid population density. One approach is simply to use all the available data to describe features that are associated with particular salmonid densities. Such models could be used to predict salmonid densities where habitat data was available, but no electrofishing surveys had been undertaken. In addition, since they can incorporate some catchment-wide data, they can give variance estimates of the relative significance of large scale and small-scale features. The success of this second approach relies on the assumption that the selection of pristine or low-impact sites does, in fact, represent “ideal” salmonid populations i.e. populations at the carrying capacity of the natural environment. To truly determine the carrying capacity of a site would require experimental manipulations of population size, and even the results of such experiments would need to be interpreted carefully. An alternative approach to understanding carrying capacity, though still requiring manipulation, is to consider which habitat features are important at different levels of population saturation. In the absence of an experimental determination of carrying capacity, this study proceeded on the premise that rivers selected to be SACs had healthy salmon stocks that saturated the habitat. 2.1.1 Spatial autocorrelation in river systems Methods of analysing spatial data have recently undergone rapid development, and this new branch of statistics has been called Geostatistics, due to its emergence in the field of geology. However, spatial data is an important component of many biological studies that has frequently been overlooked. Samples at sites closer together are more likely to be similar than samples from sites further apart, and unless all the factors that determine the similarity can be accounted for (which cannot be known), treating all the samples as independent violates the assumptions inherent in almost all statistical tests (including non-paramatric tests). The result is an increase in the risk of Type 1 errors occurring through pseudoreplication (Hurlbert 1984), potentially leading to erroneous conclusions (eg see Randall et al. 1995 and Nash et al. 1999). Where environmental conditions and population densities are both autocorrelated there is a tendency for the significance of covariates to be exaggerated (Gumpertz et al. 1997). These errors apply particularly to broad geographic scale data, such as the dataset analysed in this report, where variation amongst clustered samples are analysed with respect to local details of habitat which themselves are unlikely to be randomly distributed. For example, rock strata with a particular angle of bedding plane may generate a particular type of instream habitat. A number of samples on a river sharing the same bedding plane, and hence having similar instream habitat, may all have similarly high (or low) salmonid densities. A simple analysis of these data could generate an erroneously significant correlation between those local habitat variables and population density, when in fact, it might be that the high population densities were a result of the chemical composition of the water derived from the underlying geology, or due to the particular flow and temperature conditions that had prevailed in the catchment, or due to the numbers of returning salmon that had entered the river the previous year, or to any other factor that jointly affected sites in the same locale. This type of problem was highlighted in the field of aquatic biology as long ago as 1988 (Legendre & Trousellier 1988), and can be resolved by weighting samples with respect to their spatial separation from other samples. However, the problem is

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slightly more complex when the analysis involves river networks, because the spatial autocorrelation between sites may be of two kinds: the first the simple straight line distance (Euclidean distance) between sites, which would account for variation due to, for example, geology and weather, and the second the distance between sites along the river network, accounting for variation due to shared upstream catchment characteristics (eg being downstream of a pollution source), shared genetic history, and to the physical dispersion of individuals. This type of “as the fish swims” distance (Network distance) has been used in the analysis of fish populations in estuaries (Little et al. 1997), where it explained slightly more variation than autocorrelation measured by Euclidian distance. The results of this type of investigation of spatial autocorrelation are generally presented as correlograms, which represent autocorrelation graphically, with distance on the X-axis, and average difference in the measured variable (eg salmon population density) for pairs of sites that fall in the distance class in question. A typical correlogram shows increasing average difference with distance apart. There are two key features of a correlogram. First, the nugget, which is the point on the Y-axis where the line of the mean differences crosses it, measuring the average difference between sites with a nominal value of zero-distance between them. The nugget therefore indicates the extent of differences between sites that are not related to their distance apart, and which can thus be entirely attributed to local site differences, random error, and measurement error. The second point of note on the correlogram is the point where further increases in distance make no additional increases in average difference. This point indicates the distance between sites that makes them truly independent samples of local site details. The correlogram is on its own informative, but the process also allows weightings for site distances to be applied to other analyses to account for the non-independence of sites without disregarding the data. We attempted to match all electrofishing sites to a Digital River Network (SEPA), and used the matched co-ordinates to measure Network distance between points. However, the very large numbers of sites involved required specialised computing facilities and skills, and a full analysis of spatial autocorrelation was thought to be beyond the scope of this study. We have nevertheless conducted analysis of spatial variation on a catchment basis, generating correlograms for Network distance indicating the extent of spatial autocorrelation of salmon population densities within catchments, though unfortunately this procedure does not provide a means for weighting data points for use in a national scale predictive model. 2.2 Specifying and assessing the models An empirical approach was used in the development of the EA’s HABSCORE model (Barnard et al. 1995). Under this approach all variables are fitted to the model, and removed sequentially only if failing to reach a certain probability criterion (although HABSCORE included a few conventionally non-significant (ie p>0.05) variables to maximise the variance explained, whilst first-order interactions were not included). The final model contains all variables that contribute ‘significantly’ to the explanation of variance in the response variable. This empirical approach to model selection is common in biology, but is regarded as of dubious value by some authors (Burnham & Anderson 1998), and HABSCORE’s developers were aware of this (Milner et al. 1998). The difficulty with the empirical approach is that while it gives the best fit of the data to the model, it does not necessarily give the best model for predictive use. The goal of a model should be to maximise its inferential power, not its fit. A model constructed in an interactive way (using statistical package routines that test all

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possible models) may be over-fitted, and unstable. In other words, a second modelling exercise with another sample of data from the same population would be unlikely to generate the same model. Such models may be much poorer predictors than the confidence intervals they claim would suggest (Chatfield 1996). Attaching true significance levels to such models could be approached by using Bonferroni corrections (Sokhal & Rohlf 1995), with adjustments required for every model tested. If the statistical procedure assessed 100 models in finding the best fit, then the standard level of α (0.05) at which variables should be accepted as ‘significant’ should be adjusted to 0.0005. The fit of any model can be improved by including more parameters, yet the principal of parsimony demands that the model should have “the smallest possible number of parameters for adequate representation of the data” (Box & Jenkins 1970). The principal of parsimony represents the attempt to balance the trade-off between bias and variance. Too many parameters in a model lead to low bias, but high variance (ie uncertainy). Too few parameters lead to low variance but high risk of bias. The best approximating model (since there can be no true model) is one that minimises the function of these two risks, and achieves confidence intervals that are close to the nominal values, and that have a narrow width. The difficulty is to determine where this optimal trade-off lies, and there is no standard solution. Burnham and Anderson (1998) have argued that under-fitting (too few parameters) may be a more frequent problem for inference in biological models. An alternative approach to model selection is through information theory. Here the aim is to develop a maximal model based on biological considerations alone, without ‘data-dredging’, and to use the Akaike Information Criterion (Akaike 1973) to distinguish between this and reduced parameter versions of itself. A readable account of the theory and derivation of the Akaike Information Criterion can be found in Burnham and Anderson (1998). We will adopt this approach here on the grounds that it deploys a more parsimonious approach to model selection, and is likely to specify a more robust model. Table 2 sets out the factors and co-variates that were available, and that we predicted would have an impact on salmonid population density. Table 2 also gives the principal biological reasons for the inclusion of the variables. This table represents the maximal model. There are a number of variables we would like to have included in our analysis, but were unable to obtain data of sufficient quality. These included flow rate, predator population density measures, exploitation of adults, data on soils, geological data, and data on climate (Table 3). This superior modelling exercise has not yet been completed and is not included in this report. In any case, we are mindful that whilst biologically-derived models judged by the Akaike Information Criterion may represent an improvement on the HABSCORE approach, nevertheless a more direct comparison between Scottish salmon populations on the one hand and English and Welsh populations on the other may be advantageous. To this end we derive here a series of general linear models (where HABSCORE relied on multiple regression modelling), using the empirical stepwise deletion method employed by HABSCORE’s developers. It must be borne in mind however that these models do not represent a truly direct comparison, due to differences in the nature of the data available. Nevertheless it should be possible to determine whether similar influences determine populations of salmon.

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2.2.1 Additional data In order to extend the local scope of the SFCC dataset, other data were obtained from various sources. 2.2.1.1 Water quality data The Scottish Environment Protection Agency (SEPA) aims to classify all river courses in Scotland that drain a catchment of ≥10km2. Some details of the methodology SEPA have adopted can be found at http://www.sepa.org.uk/data/classification/classification_scheme_rivers_2000.htm. Separate classifications pertain to chemical status (with classifications for dissolved oxygen, biological oxygen demand, ammonia, iron and pH), biological status (with classifications based on laboratory and bankside analyses), aesthetic status (based on the presence of various gross litter items), nutrient status, and toxicity status. For each category, the sampling site and associated river reach are assigned to one of five categories (A1, A2, B, C, D), with various boundaries between grades defined on the website given above. A “default based” Overall category is also attached to each reach i.e. it is assigned the poorest of the various grades recorded for the chemistry, biology, aesthetic and toxicity assessments. We use the SEPA data here by adopting the grades from a reach that contains an SFCC quantitative electrofishing site. However, we modify it slightly, by excluding the aesthetic grade from the derivation of the Overall grade, in view of the likely trivial impact of the features contributing to this category on salmonid populations.

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Table 2. Available variables expected to influence juvenile salmonid population density in Scottish rivers. Factors/Covariates Effect on, or correlation with Predicted Effect on

Population Density Catchment Average gradient Channel morphology, flow, substrate ? Land-use (PCA) Water chemistry (nutrients/contaminants), sediment

load ?

Catchment area (km2) Water flow volume and characteristics ? Longitude and Latitude of river mouth Genetic variation in anadromous populations ?

Coastal fish farms Genetic stock, recruitment ? Site Stream Order Flow characteristics, distance to sea/source ? River width Flow characteristics, chemistry, cover. ? Substrate measures (PCA) Flow speed, food availability, cover, spawning sites factor Depth measures (PCA) Predation risk, food availability, temp variation various (age classes) In-stream Cover Predation risk, overwinter survival + (diff age classes) Bankside Cover (PCA) Predation risk, sediment load + (diff age classes) Tree cover Water temp, food source ? Altitude Temp, water chemistry, flow characteristics, climate. - Competitors Density-dependent effects (food, space) - Flow type (PCA) Flow speed, food availability, cover complex Conductivity Water chemistry, food ? range-dependent Local land-use Predators, water chemistry, sediment load factor Nearby lochs absent/up-/down-stream Flow, sediment load, food factor Date Survival, temperature, food availability factor Latitude, Longitude Climate ? Water Quality Food, hatching success, survival ? range-dependent Gradient Channel morphology, flow, substrate ? Channel Stability Channel morphology, flow, spawning sites + Bed Compacted Food availability, cover, spawning sites ? Silting Food availability, cover, spawning sites - Table 3. Factors for which no data were available that may influence juvenile salmonid population density in Scottish rivers. Variable Effect on/correlated with Predicted effect

Geology (base poor base rich) Water chemistry, channel morphology, food levels + Predation Direct on juvenile salmonid numbers ? Climate Water temp, flood events/low flows, hatching success complex Flow volume and speed Food availability, DO, hatching success, channel

morphology ?

Soils Water chemistry, channel morphology factor Degree of accessibility to adults Number of eggs + over low range Spatial & temporal variation in adult mortality.

Breeding population size ?

SEPA regard river reaches with the grade • A1 as “Sustainable salmonid population, natural ecosystem.” • A2 as “Sustainable salmonid population, ecosystem may be modified by human

activity.” • B as “Sustainable coarse fish populations. Salmonids may be present. Impacted

ecosystem.” • C as “Fish sporadically present, impoverished ecosystem.” • D as “Cause of nuisance, fauna absent or seriously restricted.”

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Using GIS ‘snapping’ techniques, we used the six figure grid reference for each electrofishing site to associate it with the nearest part of the SEPA Water Quality River Network (WQRN), so that the water quality recorded by SEPA for the reach of river that the site occupied could be assigned to it. In most cases the mismatch between the site grid reference and the river network was small (<100m). However, since some SFCC sites are situated on streams too small to feature in the SEPA river water quality scheme, some sites were ‘snapped’ to more distant rivers. This work was undertaken by Dave Tulett and Julia Jackson (FRS Marine Laboratory). In order to avoid associating SFCC sites with rivers other than the one they were truly sited on, a sample of the snapped sites was checked (Figure 1). For each snapped distance class, 25 sites were sampled. All sites with snapped distances of less than 50m were correctly assigned, 96% of sites between 50-60m and 92% of sites from 60-70m were correctly assigned. The percentage decreased with snapped distance so that those sites with snapped distances of 90-100m had only a 68% chance of being correctly assigned. In all cases the incorrect association of sites occurred where a site on a small stream (not on the WQRN) was snapped to the next order stream of which it was a tributary. In most cases it would be reasonably safe to assume that these rivers shared the principal aspects of water quality with their neighbours, however this could not be demonstrated. Unfortunately a large number of sites (267) was snapped at a distance of between 50 and 70m. However, since such sites had a 94% chance of being correctly assigned, and since there was a reasonable chance that even the 6% that were incorrectly assigned did, in fact, have the water quality characteristics that they were assigned to, we decided to retain the SEPA water quality data for all sites with a snapped distance of <70m. Those with snapped distances of greater than 70m were rejected (excepting those we had already determined were correctly assigned during the sampling procedure described above). In all, of the 4734 electrofishing events selected for analysis, 2089 (44.1%) had water quality data associated with them. Figure 1. Variation in percentage of electrofishing sites correctly assigned to their true locations following the snapping procedure to the SEPA Water Quality River Network.

Variation in percentage of electrofishing sites correctly assigned to their true locations following the snapping

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2.2.1.2 Catchment data To generate catchment data for each individual SFCC electrofishing site we produced an Arc/Info AML program to calculate the catchment above each site grid reference on a river, using a raster dataset derived from the Ordnance Survey 1:50,000 Panorama Digital Terrain Model (DTM) data. Once the catchment boundary had been created, the same dataset was used to generate river and contour lines for the site’s catchment. The catchment boundary was also used to clip out land cover information from the most recent available dataset: the Land Cover of Scotland data produced by the Macaulay Land Use Research Institute (LCS88, MLURI 1993). The procedure provided information for each site on catchment area, minimum and maximum catchment altitude, area of upstream lochs and the percentage of a variety of land cover categories, detailed in Appendix D. This work was undertaken by Hilary Anderson (SFCC). 2.2.2 Site selection In developing our models, we aimed at predicting juvenile salmonid populations expected under reasonably natural conditions for the given local habitat, we sought to follow the established methodology of HABSCORE, used in England and Wales. HABSCORE predictions are based on a reference population of sites selected as “notionally pristine.” It is not entirely apparent what constitutes pristine-ness, but here we select only sites that are deemed to have full access to salmonids (following local river surveys), that are free of significant pollution, and that are not known to have been stocked (determined by SFCC biologists). No attempt was made to determine the pristine-ness of the catchment as a whole, but instead our methodology relies on the land-cover data and water quality data to flag human influences on catchments if these are significant to salmonid populations. One aspect of pristine-ness that we have not at this stage been able to address is the possible influence of salmon farms on wild salmonid populations. 2.2.3 Ideal site selection A true model for predicting ideal fish population density for given conditions of natural habitat would use only those sites known to be at carrying-capacity as the reference population. To this end an extension of selection criteria beyond the three already described was envisaged, to obtain a selection of “pristine” sites for analysis. There are two possible approaches to selecting “pristine” sites, which can be characterised as theory-based and empirical (data-based) respectively. The first is an assessment of the impact humans are likely to have had on salmonid populations at a site, without reference to the populations themselves. Since no catchments can be regarded as entirely un-impacted, this must necessarily entail a series of assumptions about which anthropogenic effects have the greatest impact. Nor are these assumptions necessarily obvious. For example, a large area of non-native forestry in a catchment is likely to cause a catchment to be regarded as heavily impacted, whereas a large extent of semi-natural moorland may not. However, it is possible that the deforestation that allowed the establishment of the moorland may have had, and may continue to have as great an effect on salmonid populations as subsequent afforestation. Without testing the many assumptions involved in an assessment of the degree of impaction, any such assessment must be regarded as highly subjective. This is more the case since sufficient knowledge of SFCC sites is not held by any one individual, so that different individuals assessing sites in different regions may have used subtly different criteria. Nevertheless, an attempt was made to standardise assessments by reference to a series of possible impacts and their

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intensity. The SFCC biologists were asked to select sites within their particular regions that were least impacted in terms of four further criteria: • the presence of alien species • canalisation • flow regulation • catchment land-use An alternative approach is a retrospective empirical assessment of pristine-ness based on the populations of salmonids and other fish actually found at a site. This has the advantage that objective and repeatable criteria can be applied. Maitland sets out a system for defining the ecological status of rivers based on the fish communities they contain (Maitland 2002). However, the apparent objectivity of these criteria relies on prior information regarding expected values, against which the actual populations can be judged, and scored. Given that a major aim here was to determine the impact of local habitat features on population size, it is apparent that this approach would involve a degree of logical circularity. A more simple retrospective approach would be to apply a cut-off point for salmonid population density below which sites are excluded from the reference population. This approach however risks the possibility that only the most productive habitats would be selected, severely restricting the ability of any model based on such a reference population to be informative about the range of riverine habitats encountered. We therefore concluded that the assessment of pristine-ness, based upon knowledge of the catchment, whilst inherently flawed, at least involves no element of logical circularity, and provides the best approach to avoiding bias in the reference population. There was considerable variation between areas in the proportion of electrofishing sites that were regarded by SFCC biologists as of “low-impact” status. In central eastern Scotland, the Firth of Forth catchment area, only 3 of 88 sites were selected. Conversely, in the Wester Ross area, 95 of 157 sites were selected as being of low impact status. The result of this “ideal site” selection process is available for modelling, but time was too short to include the analysis in this report. 2.2.4 Data structure We used two datasets for the modelling analyses. The SFCC dataset contains multiple-run and single run electrofishing data. Whilst the multiple-run events represent very high quality data, allowing accurate Zippin estimates (Zippin 1958) of true population size, they are rather few in number (n=545 sites, not all associated with complete habitat data). Conversely, whilst the one-run electrofishing data represent less high quality data, allowing minimum population density estimates only, they are more plentiful in number (n=1638 sites). The two sets of data can complement each other, with the Zippin estimates representing the definitive data, whilst the one-run minimum population density estimates allow the exploration of relationships which small sample sizes in the definitive dataset preclude. No attempt has been made to estimate the true population density from the one-run data, and it must be borne in mind that these represent a varying proportion of true population density, and so can at best be regarded as a minimum population density.

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The Zippin method cannot produce reliable estimates at zero or very low densities, thus these are absent from the Zippin analysis of the Zippin data. In the one-run data zero estimates could arise from sampling error of a few fish, or from zero fish due to habitat, or from zero fish due to other reasons. Since these situations are not distinguishable, since the inclusion of zero densities introduced more noise, and since their inclusion would also prevent a direct comparison between the Zippin and one-run models, it was thought best to follow the methodology of HABSCORE (Barnard et al. 1995) and exclude zero estimates from the analysis. While a considerable amount of variation in salmonid population density is temporal, the six years of data do not yield any pattern in temporal variation, but simply indicate differences between years. In developing a predictive model, therefore, that applies past information to future estimates of salmonid density, individual year effects are not relevant, and thus mean cross-year estimates should be used. The data available for sites varies between a single electrofishing event, and five visits to a site in five separate years. The data used in the models below avoid pseudoreplication by using single mean estimates of site characteristics and population density. Amongst the available variables, we tested for significant co-linearity and where possible we used principal components analysis to combine correlated variables into single useable measures, for example, the various percentages of substrate types. Where this was not possible, we retained one of the correlated predictors whilst discarding the rest according to: assessment of probable ultimate causality higher or highest number of observations for the variable assessment of data quality for the variable 2.2.5 The models We develop two sets of four models, one set using the definitive Zippin densities, the other using one-run minimum population density estimates (see 2.2.4) relating salmon populations to habitat features. These models have as their dependent variables 1. salmon fry population density (no 100m-2) 2. salmon fry biomass (g 100m-2) 3. salmon parr (1++) population density (no 100m-2) 4. salmon parr (1++) biomass (g 100m-2) Biomass was calculated from the fork length of salmon fry recorded by the SFCC according to the equation

Mass (g) = 2.8087x10-6 x Fork Length (mm)3.3016 (P. Shackley, unpublished data, Shelligan burn) and multiplied by population density (no 100m-2) giving biomass as g100m-2 2.2.6 Data quality control Pre-processing of the data from the SFCC database in preparation for analysis highlighted a number of issues relating to database structure, storage, data entry and data export. The database managers are currently working towards solving these for future use, but meanwhile errors were corrected in database exports. Many corrections had to be conducted manually, and proved time-consuming. Much help was received from other SFCC staff, particularly Hilary Anderson, and affiliated staff in this work.

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2.2.6.1 Exporting data issues There were a number of difficulties concerning export from the database, these included • inappropriate null values • internal calculations of variance • isolated run data inconsistencies • incorrect size calculations often requiring manual correction and recalculation. 2.2.6.2 Data entry issues To allocate fish to age classes it is necessary to define all the lower and upper size-limits (or breakpoints) for each age class. Where these were absent the database assigned fish to an un-aged class. In many cases incorrect entry of breakpoints led to many fish being un-aged when it was, in fact, possible to age them. The system for entering age-classes was counter-intuitive and, as many were incorrectly entered, all sites where un-aged fish were present had to be corrected manually. 2.2.6.3 Absent data Site gradient. Gradient is not currently recorded by the SFCC members for electrofishing sites, but was an important predictor in HABSCORE models, and was deployed by the NRA in its National Fisheries Classification Scheme. We spent quite a long time trying to obtain average site gradients from digitised data, however, due to mismatch between digitised river networks and digitised contour networks, it proved impossible to find an automatic method to calculate gradient effectively. Eventually, SFCC members calculated site gradients in their areas manually, using 1:50,000 Ordnance survey maps, and measuring the distance between contours, for all their sites. Accessibility of sites to salmonids is not currently included in the SFCC database. Linking this accessibility data to the main export was time-consuming. Conductivity was a key input to HABSCORE, and is likely to be an important measure of salmonid habitat quality. Unfortunately, for a variety of reasons mostly relating to equipment failure, conductivity was more often not recorded than recorded during SFCC electrofishing visits. In the end the scarcity (and bias) of conductivity measures necessitated its exclusion as an independent variable from the modelling exercise.

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Map 1. Distribution of SFCC quantitative electrofishing sites with associated habitat data available at the time of analysis.

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2.3 Results 2.3.1 Spatial autocorrelation The spatial autocorrelation of measures of altitude and stream width from 152 sites in the Spey catchment are presented. The mean difference in altitude between sites shows a typical relationship Figure 2a with the distance measured along the stream channel between sites. A steep increase in dissimilarity between sites occurs over the first 20km, levelling off until no further increase in difference is detectable after about 70km. In terms of altitude then, sites are independent estimates of true mean altitude only if they are 70km or further apart. By contrast, Figure 2b, shows an entirely different pattern of spatial autocorrelation for river width. Here the relationship is less clear, though it is evident that the difference between the nugget (variation in width where the difference between sites is zero) and the smallest difference in distance class for river width (2.5km) is greater than any subsequent increases in the difference between width with distance. The slope of change thereafter is shallow, if indeed it represents a true slope at all. Figure 2. Variation in difference in (a) altitude and (b) channel width between sites with the distance (measured along channel length) between those sites, in the Spey catchment (n=152 sites).

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18

Figure 3 shows the relationship of aspects of salmonid populations with distance between sites at which they were sampled. Salmon fry show much less variation in population density than trout fry, and this is true to a lesser extent for parr also. However, the spatial autocorrelation for population density for both groups is hard to interpret. For salmon fry an initial steep increase in population density difference over the first 10km gives way to a plateau. A similar relationship is seen for salmon parr, but in this case a second, unexpected, increase in difference is seen after 70km. For trout fry a steep change in difference is detectable over the first 100km, with a sudden decline in difference thereafter. In terms of difference in the size of salmonid fry and parr, it appears that little difference is detectable after the first 10km between sites, although, again, for fry there is an unexpected increase in difference after 100km. In general, significant spatial autocorrelation is restricted to sites within 10km of each other (along the river network), and even there its extent is rather small compared to the nugget effect (representing variation within a site between years). Figure 3. Variation in difference in (a) population density and (b) fish size of (i) salmonid fry and (ii) salmonid parr between sites with the distance (measured along channel length) between those sites, in the Spey catchment (n=152 sites). (a) (i) (ii)

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19

2.3.2 Principal components analysis Much of the SFCC electrofishing habitat data is in the form of competing percentages, as with the percentages of pools, glides, runs, riffles and torrents making up the flow characteristics of a single site. These percentages are necessarily correlated with each other. This presented a problem in terms of retaining all the information such data provides in a model with acceptable residual characteristics. We used principal components analysis in an attempt to summarize collections of related (and correlated data) into single usable measures, the principal component axes. Details of the various principal components axes are presented in Appendix E, whilst a summary of the interpretation of the axes used is presented (Table 4). Principal Components axes were derived for flow type characteristics (Flow), site depth characteristics (Depth), bankside cover (Bank), substrate characteristics (Substrate), and catchment land use characteristics (Land). Table 4. Summary of Principal Components Axes used in the models. Component Interpretation

Flow PCA1 Negatively correlated with run, riffle and torrent flow types.

Flow PCA2 Associated with deep glide and deep pool type flows, and a scarcity of run type flow.

Depth PCA1 Positively correlated with moderately deep water (20-50cm), and negatively with shallow water (<20cm).

Depth PCA2 Associated with high proportions of both very shallow (<10cm) and deep water (>40cm), and negatively associated with moderately shallow water (10-30).

Bank PCA1 Negatively associated with bare banks, and positively with draped and undercut banks.

Bank PCA2 Strongly correlated with marginal type bankside vegetation.

Substrate PCA1 Negatively correlated with the abundance of large substrate size, and positively related to sand, gravel and pebble sizes.

Substrate PCA2 Correlated with smaller substrate sizes (silt, sand and high organic substrate), and strongly negatively associated with pebble and cobble abundance.

Land PCA1 Negative association with heather moor, peat and freshwater habitats. Weaker positive correlation with rough/improved grass, arable, and coniferous woodlands.

Land PCA2 Positive association with arable, improved land, and urban habitats. Negative association with coniferous plantations, and recent woodland fellings/plantings.

Land PCA3 Associated with all types of tree cover, and negatively associated with rough grassland.

20

2.3.3 The Zippin models 2.3.3.1 Salmon fry population density Four parameters were fitted to a general linear model of salmon fry population density, explaining 17.1% of variation (Table 5), and their coefficients are shown in Table 6. Salmon Fishery Region (Map 2) was the only significant factor accepted in the model, indicating an important geographical variation in salmon populations. Multiple pairwise comparisons showed that the Clyde Coast region, with the lowest fitted mean, had significantly lower population densities than both East Region (with the highest fitted mean, P<0.001) and Solway (including the Border Esk) region (P<0.026). The North West region was also associated with lower densities than the East Region (P<0.001) and the Solway Region (P<0.018). West Region was also associated with lower densities than East Region (P<0.027). Of the significant covariates, Substrate PCA2 was the most important predictor of population density (the negative slope indicating that high population densities were associated with pebbles and cobbles, and negatively linked with silts, sands and high organic substrates). A weaker negative association with Substrate PCA1 suggested a further contribution from the larger, boulder substrate size to high population densities. Day of Year was negatively related to fry population density during the course of the electrofishing period (June to November). Table 5. Summary of between-subjects effects for the general linear model of salmon fry population density (ln no 100m-2) in Scotland, based on electrofishing Zippin estimates. Source Sum of

Squaresdf Mean

SquareF Sig.

Corrected Model 83.655 10 8.365 7.199 .000Intercept 62.951 1 62.951 54.175 .000SF REGION 27.780 7 3.969 3.415 .002Substrate PCA1 4.563 1 4.563 3.927 .048Substrate PCA2 19.259 1 19.259 16.574 .000Day Of Year 4.838 1 4.838 4.163 .042Error 336.980 290 1.162 Total 5003.134 301 Corrected Total 420.635 300 R2 = .199 (Adjusted R2= .171)

Table 6. Parameter estimates for the general linear model of minimum salmon fry population density (ln no 100m-2) based on Zippin densities from electrofishing events. See also Table 5. Parameter Coefficient S. E. t Sig. 95% C. I. Power Lower Upper Intercept 4.788 .747 6.410 .000 3.318 6.259 1.000

Clyde Coast -.565 .494 -1.143 .254 -1.538 .408 .207East .627 .282 2.226 .027 .07262 1.182 .602

Moray Firth .08595 .366 .235 .815 -.635 .806 .056

SF REGION

North .474 .443 1.070 .286 -.398 1.347 .187North West -.04246 .266 -.160 .873 -.566 .481 .053

Outer Hebrides .321 .586 .548 .584 -.832 1.475 .085Solway .485 .288 1.684 .093 -.08207 1.053 .389

West 0 . . . . . .

Substrate PCA1 -.158 .080 -1.982 .048 -.316 -.00108 .506Substrate PCA2 -.325 .080 -4.071 .000 -.482 -.168 .982Day Of Year -.00557 .003 -2.040 .042 -.0194 -.00020 .529

21

Map 2. The Salmon Fishery Statistical Regions of Scotland.

22

2.3.3.2 Salmon fry biomass Just three parameters were retained in the general linear model of salmon fry biomass, which explained 18.2% of the variance in the data, representing a very slight improvement over the population density (Tables 7 and 8). Salmon Fishery Region was the dominant predictor. Clyde Coast and North West Regions were associated with low fry biomass levels and East and Solway regions with high biomass. Pairwise comparisons showed that both East and Solway Regions had significantly higher fry biomass levels than either Clyde Coast, North West, or West Regions (P<0.005 in six instances). Water Clarity contributed to further variation in fry biomass, with clear water being associated with significantly higher levels than coloured water (P<0.014). The only significant covariate predicting fry biomass was Substrate PCA1, with the negative slope suggesting high biomass levels were associated with cobbles and boulders. Table 7. Summary of between-subjects effects for the general linear model of salmon fry biomass (ln g 100m-2) in Scotland, based on Zippin estimates from electrofishing events. Source Sum of

Squaresdf Mean

SquareF Sig.

Corrected Model 84.989 10 8.499 7.634 .000Intercept 297.603 1 297.603 267.318 .000SF REGION 81.956 7 11.708 10.517 .000WATER CLARITY 9.298 2 4.649 4.176 .016Substrate PCA1 4.610 1 4.610 4.141 .043Error 321.741 289 1.113 Total 5876.216 300 Corrected Total 406.730 299 R2 = .209 (Adjusted R2= .182)

Table 8. Parameter estimates for the general linear model of minimum salmon fry biomass (ln g 100m-2) in Scotland, based on Zippin densities from electrofishing events. See also Table 7. Parameter Coefficient S. E. t Sig. 95% C. I. Power Lower Upper Intercept 3.261 .341 9.551 .000 2.589 3.933 1.000

Clyde Coast -.425 .461 -.921 .358 -1.333 .483 .151East .893 .239 3.730 .000 .422 1.364 .961

Moray Firth .194 .350 .556 .579 -.494 .883 .086

SF REGION

North .113 .433 .260 .795 -.740 .966 .058North West -.315 .249 -1.262 .208 -.806 .176 .242

Outer Hebrides .151 .571 .264 .792 -.973 1.275 .058Solway .836 .276 3.024 .003 .292 1.380 .854

West 0 . . . . . .

Clear .649 .262 2.475 .014 .133 1.166 .694Intermediate -.195 .588 -.332 .740 -1.353 .962 .063

CLARITY

Coloured 0 . . . . . .Substrate PCA2 -.159 .078 -2.035 .043 -.314 -.00524 .527

23

2.3.3.3 Salmon parr population density Rather more of the variation in salmon 1++ population density was attributable to the available explanatory variables than was the case for fry. Five parameters were fitted, together contributing 24.2% of the variation (Tables 9 and 10). Salmon Fishery Region was the only factor fitted, and showed a similar, but not identical, influence of geographical area on parr population density as on fry. Clyde Coast was again associated with the lowest population density levels, but the Moray Firth Region had the highest levels. High mean levels for North and Outer Hebrides Regions may have been randomly related to small sample sizes for these regions. In any case the only significant differences between regions in population densities detected by pairwise comparisons were the Moray Firth greater than East (P<0.001), North (P<0.005), Solway (P<0.004), and West (P<0.024) together with the Clyde Coast having lower densities than all the other regions (all P<0.01). Substrate PCA1 was the single most important predictor, with a negative relationship indicating an association of high salmon parr densities with a preponderance of cobbles and boulders. Day of the Year was negatively related to parr population density, suggesting significant parr mortality or migration through the fishing period (June to November). Stream width was negatively correlated with parr population density. A rather smaller amount of variation was explained by Flow PCA2, with the negative slope suggesting that a relative scarcity of deep pools and glides but an abundance of run type flows were associated with high population densities of parr. Table 9. Summary of between-subjects effects for the general linear model of salmon parr population density (ln no 100m-2) in Scotland, based on Zippin estimates from electrofishing events. Source Sum of

Squaresdf Mean

SquareF Sig.

Corrected Model 62.426 11 5.675 9.888 .000Intercept 57.573 1 57.573 100.315 .000SF REGION 16.562 7 2.366 4.123 .000Log Width 5.840 1 5.840 10.176 .002Substrate PCA1 18.037 1 18.037 31.427 .000Flow PCA2 3.038 1 3.038 5.294 .022Day Of Year 6.085 1 6.085 10.602 .001Error 169.308 295 .574 Total 2647.525 307 Corrected Total 231.734 306 R2 = .269 (Adjusted R2= .242)

24

Table 10. Parameter estimates for the general linear model of salmon parr population density (ln no 100m-2) based on Zippin estimates from electrofishing events. See Table 9. Parameter Coefficient S. E. t Sig. 95% C. I. Power Lower Upper Intercept 4.589 .508 9.030 .000 3.589 5.589 1.000

Clyde Coast -1.064 .327 -3.254 .001 -1.707 -.420 .900East .00638 .198 .032 .974 -.383 .395 .050

Moray Firth .554 .238 2.326 .021 .08525 1.023 .640

SF REGION

North .109 .317 .343 .732 -.515 .733 .064North West -.104 .180 -.577 .564 -.459 .251 .089

Outer Hebrides .440 .475 .927 .355 -.494 1.374 .152Solway -.09984 .209 -.479 .633 -.510 .311 .076

West 0 . . . . . .

Substrate PCA1 -.343 .061 -5.606 .000 -.464 -.223 1.000Log Width -.594 .186 -3.190 .002 -.961 -.228 .889Flow PCA2 -.143 .062 -2.301 .022 -.264 -.02061 .631Day Of Year -.005689 .002 -3.256 .001 -.009127 -.00225 .901

2.3.3.4 Salmon parr biomass The biomass model for Salmon 1++ represented an improvement, in terms of variance explained, on the 1++ population density model. Five parameters were fitted which together explained 30.9% of the variation in the data. Salmon Fishery Region was important again, with East Region being associated with high biomass levels, whilst Clyde Coast, North West and West Regions were associated with low biomass levels. Pairwise comparisons showed that East Region had significantly higher biomass levels than Clyde Coast, (P<0.002), West Region (P<0.001) and North West Region (P<0.001), whilst Moray Firth had significantly higher levels than the North West (P<0.007). The North West had significantly lower levels than both North (P<0.008) and Solway (P<0.001) Regions. Local Landuse again appeared in the model: here pairwise comparisons showed that Broadleaved/Mixed woodland (P<0.002), Scrub (P<0.001) and Improved Grassland (P<0.008) were all linked with higher parr biomass levels than Rough Pasture, while Scrub was also linked to higher levels than Heather Moorland (P<0.013). Clear water was associated with higher biomass levels than coloured water. As in the salmon 1++ population density model river width was negatively associated with biomass. By far the most important linear predictor, however, was Substrate PCA1, the negative slope indicating an association between salmon 1++ biomass and the abundance of cobble and boulder substrate at a site.

25

Table 11. Summary of between-subjects effects for the general linear model of salmon parr biomass ((ln(g 100m-2))2) in Scotland, based on Zippin estimates from electrofishing events. Source Sum of Squares df Mean Square F Sig.

Corrected Model 8395.25 23 365.01 6.768 .000Intercept 6100.32 1 6100.32 113.115 .000SF REGION 2871.74 7 410.25 7.607 .000LOCAL LANDUSE 1 1561.38 11 141.94 2.632 .003WATER CLARITY 815.79 3 271.93 5.042 .002Log Width 257.96 1 257.96 4.783 .030Substrate PCA1 2803.06 1 2803.06 51.976 .000Error 14776.85 274 53.93 Total 237400.71 298 Corrected Total 23172.10 297 R2 = .362 (Adjusted R2= .309)

Table 12. Parameter estimates for the general linear model of salmon parr biomass ((ln(g 100m-2))2) in Scotland, based on Zippin estimates from electrofishing events. See Table 11. Parameter Coefficient S.E of t P 95% C. I.

Coeff Lower Upper

Intercept 38.672 8.400 4.604 .000 22.136 55.209Clyde Coast -1.897 3.226 -.588 .557 -8.248 4.453

East 6.971 1.804 3.864 .000 3.419 10.522Moray Firth 4.338 2.505 1.732 .084 -.594 9.270

SF REGION

North 5.813 3.110 1.869 .063 -.309 11.936North West -1.671 1.839 -.909 .364 -5.292 1.949

Outer Hebrid 6.607 4.706 1.404 .161 -2.657 15.870Solway 4.099 2.090 1.961 .051 -.01547 8.213

West 0 Clear 4.164 1.957 2.128 .034 .311 8.017CLARITY

Coloured 0 unrecorded -14.425 8.283 -1.742 .083 -30.730 1.881

BL -14.845 8.083 -1.837 .067 -30.758 1.068CP -14.735 8.207 -1.795 .074 -30.892 1.421GA -21.852 9.517 -2.296 .022 -40.587 -3.117IG -15.287 8.041 -1.901 .058 -31.117 .544IN -4.583 10.903 -.420 .675 -26.046 16.881

MH -17.228 8.126 -2.120 .035 -33.226 -1.230RD -10.225 9.557 -1.070 .286 -29.039 8.590RP -19.363 8.059 -2.403 .017 -35.228 -3.497SC -10.909 8.348 -1.307 .192 -27.343 5.525TH -15.422 8.166 -1.888 .060 -31.498 .655

LOCAL LANDUSE 1

TL 0 Subtrate PCA1 -4.350 .603 -7.209 .000 -5.538 -3.162Log Width(m) -4.035 1.845 -2.187 .030 -7.667 -.403

26

2.3.4. The One-Run models 2.3.4.1 Salmon fry population density Eleven parameters were significantly associated with minimum salmon fry population density (detailed in Tables 13 and 14), with Salmon Fishery region, local land use, and Depth PCA1 being the most important. Overall only 17.2% of the variance could be accounted for by the significant parameters. Salmon Fishery regions with high densities were East Region, Moray Firth, and Solway, whilst sites in West Region, Outer Hebrides and Clyde Coast had low densities when controlling for other parameters in the model. While overall Local Landuse was related to population density, the relatively small sample sizes meant that estimates of the significance of individual landuse categories exceeded P=0.05, nevertheless RS (rock and scree), IG (improved/semi-improved grassland) and GA (gardens) seem to be associated with high densities, whilst OW (open water), WL (wetland) and MH (moorland heath) were associated with low densities of fry. A strong negative association with Depth PCA1 was found, indicating an association of high fry densities and shallow water (<20cm) (see Table 4 and Appendix E). Flow PCA2 was negatively related to fry density, indicating that a scarcity of deep pools and glides but an abundance of run type flows were associated with high population densities. Unstable channels were associated with low densities, stable channels with high densities and mixed stability (sites that were reported as stable in some years and unstable in others) falling in between. High River Levels (Height) were associated with higher density estimates than low flow levels. Site altitude was positively associated with fry density, whilst local gradient (estimated from the distance between contour lines above and below the site) was negatively related to density, as was the average gradient of the upstream catchment, instream vegetation levels and % overhanging boughs were both rather weakly negatively related to population density. Table 13. Summary of Between-Subjects Effects for the general linear model of minimum salmon fry population density (ln no 100m-2) in Scotland, based on one-run electrofishing events.

Source Sum of Squares df Mean Square F Sig.

Corrected Model 279.062 35 7.973 6.161 .000 Intercept 18.733 1 18.733 14.476 .000

CHANNEL STABILITY 11.649 3 3.883 3.001 .030 RIVER LEVEL 11.815 2 5.908 4.565 .011

SF REGION 37.803 7 5.400 4.173 .000 LOCAL LANDUSE2 50.590 16 3.162 2.443 .001 Instream Vegetation 7.183 1 7.183 5.551 .019

Log Altitude (m) 10.080 1 10.080 7.789 .005 Log Local Gradient 10.010 1 10.010 7.735 .006

Log Catchment Gradient 8.171 1 8.171 6.314 .012 Overhanging Boughs % 5.427 1 5.427 4.194 .041

Flow PCA2 7.154 1 7.154 5.528 .019 Depth PCA1 24.610 1 24.610 19.018 .000

Error 1080.562 835 1.294 Total 7055.221 871

Corrected Total 1359.624 870 R2 = 0.205 (Adjusted R2= 0.172)

27

Table 14. Parameter estimates for the general linear model of minimum salmon fry population density (ln no 100m-2) based on one-run electrofishing events. See also Table 13. Parameter Coefficient S.E. t Sig. 95% C.I. Power Lower Upper

Intercept .690 .626 1.102 .271 -.538 1.918 .196Unstable -.374 .126 -2.975 .003 -.621 -.127 .844

Mixed -.156 1.146 -.136 .892 -2.406 2.093 .052CHANNEL STABILITY

Stable 0 . . . . . .

High .653 .318 2.055 .040 .029 1.277 .537Low .209 .085 2.463 .014 .043 .376 .691

RIVER LEVEL

Medium 0 . . . . . .

Clyde Coast .331 .202 1.638 .102 -.066 .728 .373East 1.149 .284 4.049 .000 .592 1.706 .981

Moray Firth .781 .202 3.870 .000 .385 1.176 .972

SF REGION

North .475 .254 1.868 .062 -.024 .975 .462North West .456 .184 2.476 .013 .095 .818 .696

Outer Hebrides .162 .224 .724 .469 -.277 .601 .112Solway .525 .189 2.784 .005 .155 .895 .794

West 0 . . . . . .

Unrecorded .606 .698 .868 .386 -.764 1.975 .139BL .144 .550 .262 .793 -.935 1.224 .058CP .314 .573 .548 .584 -.810 1.437 .085GA 1.574 .973 1.619 .106 -.335 3.483 .366IG .588 .555 1.059 .290 -.501 1.676 .185IN 1.356 .959 1.414 .158 -.526 3.238 .293

MH -.117 .542 -.216 .829 -1.181 .947 .055NC .706 .855 .826 .409 -.972 2.385 .131OW -.555 .655 -.848 .397 -1.841 .730 .135RD .267 .561 .477 .634 -.833 1.368 .076RP .295 .544 .542 .588 -.773 1.363 .084RS 1.355 .743 1.823 .069 -.104 2.813 .445SC .477 .620 .769 .442 -.740 1.694 .120SU .489 .747 .654 .513 -.978 1.956 .100TH .458 .551 .832 .406 -.623 1.539 .132TL .445 .980 .455 .649 -1.477 2.368 .074

LOCAL LANDUSE 2

WL 0 . . . . . .

Instream Vegetation -.006 .003 -2.356 .019 -.011 -.001 .653Log Altitude (m) .246 .088 2.791 .005 .073 .419 .796Log Local Gradient -.249 .089 -2.781 .006 -.424 -.073 .793Log Catchment Gradient -.177 .070 -2.513 .012 -.315 -.039 .709Overhanging boughs % -.003 .002 -2.048 .041 -.006 -.0001 .534Flow PCA2 -.122 .052 -2.351 .019 -.224 -.020 .651Depth PCA1 -.217 .050 -4.361 .000 -.315 -.120 .992

28

2.3.4.2 Salmon fry biomass A total of 15 parameters were fitted in the general linear model of minimum salmon fry biomass (ln g 100m-2) (Tables 15 and 16). These accounted for 25.8% of the variation in biomass, representing a substantial improvement over the one-run population density model. Key factors were identical to the salmon fry density model. Again there was significant variation amongst the Salmon Fishery regions though less marked than in the density model, East region being associated with the highest levels of biomass (significantly greater than those from Clyde Coast (P<0.018), Outer Hebrides (P<0.002), Solway (P<0.010) and West (P<0.001). Intermediate levels of biomass were associated with the Moray Firth region (significantly higher than Outer Hebrides (P<0.002) and West Region (P<0.008)), the North Region (significantly greater than Outer Hebrides (P<0,006)) and North West (significantly greater than Outer Hebrides (P<0.001)). Low levels of biomass were found in the West, Clyde Coast and Outer Hebrides. Channel stability was important, with stable channels supporting higher stock biomass than unstable ones. The fitted influence of river level at the time of electrofishing was very similar to the influence in the fry density model, underlining the fact that this response was artifactual. Local Landuse (within 50m of banktop) appeared to be an important determinant of salmon fry biomass. Land use types associated with high fry biomass levels were Improved Grassland (IG), Rock and Scree (RS) and Roads (RD), intermediate biomasses were linked with Rough Pasture (RP) and Tall Herbs (TH), whilst Heather Moorland (HM), BroadLeaf/mixed woodland (BL), Open Water (OW) and Coniferous Plantations (CP) were associated with low biomass levels. Improved Grassland was linked to significantly higher fry biomass levels than MH (P<0.001), BL (P<0.012). Rock and Scree was associated with significantly higher levels of biomass than MH (P<0.013), BL (P<0.033) CP (P<0.046) and OW (P<0.037), whilst Heather Moorland was linked with lower biomasses than RD (P<0.013), RP (P<0.002) and TH (P<0.005). Covariates with a similar association for salmon fry population density and biomass were local gradient, catchment gradient, Depth PCA1, Flow PCA2, and the % overhanging boughs. Covariates with a significant association with salmon fry biomass, but not population density were Stream Width (negative), Substrate PCA1 and Substrate PCA2 (together indicating higher biomass levels at sites with a high proportion of substrate sizes from pebbles through to boulders). Upstream Catchment Area (positive), and Northing (negative) were amongst the strongest predictors in the model. The single most important predictor of fry biomass however, was Day of Year (positive), indicating that individual fry growth over the electrofishing period (June to November) was not exactly matched by decline in population size.

29

Table 15. Summary of between-subjects effects for the general linear model of minimum salmon fry biomass (ln g 100m-2) in Scotland, based on one-run electrofishing events. Source Sum of

Squaresdf Mean

SquareF Sig.

Corrected Model 540.495 40 13.512 9.652 .000Intercept 5.225 1 5.225 3.732 .054CHANNEL STABILITY 23.299 3 5.825 4.161 .002RIVER LEVEL 14.384 2 7.192 5.137 .006LOCAL LANDUSE2 42.014 16 2.626 1.876 .019SF REGION 45.955 7 6.565 4.689 .000Log Width 10.499 1 10.499 7.499 .006Log Local Gradient 7.164 1 7.164 5.117 .024Log Catchment Gradient 9.027 1 9.027 6.448 .011Log upstream catchment area (m2) 12.543 1 12.543 8.959 .003Catchment Landuse PCA2 8.391 1 8.391 5.994 .015Substrate PCA1 11.615 1 11.615 8.297 .004Substrate PCA2 13.142 1 13.142 9.387 .002Depth PCA1 9.937 1 9.937 7.098 .008Flow PCA2 9.094 1 9.094 6.496 .011Day Of Year 21.448 1 21.448 15.320 .000Northing 11.129 1 11.129 7.949 .005Error 973.427 830 1.173 Total 9975.476 874 Corrected Total 1455.063 873 R2 = .288 (Adjusted R2= .258)

30

Table 16. Parameter estimates for the general linear model of minimum salmon fry biomass (ln g 100m-2) based on one-run electrofishing events. See also Table 15. Parameter Coefficient S. E. t Sig. 95% C. I. Power Lower Upper Intercept 1.911 1.17 1.633 .103 -.386 4.207 .37

Mixed -1.288 1.20 -1.078 .281 -3.633 1.056 .19Unstable -.472 .120 -3.931 .000 -.708 -.237 .98

CHANNEL STABILITY

Stable 0 . . . . . .

High .564 .276 2.045 .041 .023 1.104 .53Low .226 .084 2.702 .007 .062 .390 .77

RIVER LEVEL

Medium 0 . . . . . .

Unrecorded -.325 .570 -.570 .569 -1.443 .794 .09BL -.469 .570 -.822 .411 -1.587 .650 .13CP -.447 .595 -.751 .453 -1.616 .721 .12GA .434 1.01 .429 .668 -1.549 2.416 .07IG -0.178 .575 -.031 .975 -1.146 1.111 .05IN .828 .998 .830 .407 -1.130 2.787 .13

MH -.659 .566 -1.165 .244 -1.770 .451 .21NC -.376 .889 -.423 .672 -2.121 1.369 .07OW -.714 .684 -1.043 .297 -2.057 .629 .18RD -.203 .581 -.349 .727 -1.343 .938 .06RP -.264 .565 -.467 .641 -1.374 .845 .08RS .698 .773 .903 .367 -.819 2.215 .15SC -.213 .642 -.331 .741 -1.473 1.048 .06SU .406 .775 .523 .601 -1.115 1.927 .08TH -.213 .571 -.373 .709 -1.334 .908 .07TL .530 1.02 .520 .603 -1.471 2.531 .08

LOCAL LANDUSE 2

WL 0 . . . . . .

Clyde Coast .358 .232 1.540 .124 -.09832 .814 .34East 1.031 .290 3.560 .000 .463 1.599 .95

Moray Firth .508 .193 2.639 .008 .130 .886 .75

SF REGION

North .576 .320 1.801 .072 -.0517 1.204 .44North West .530 .221 2.399 .017 .0965 .964 .67

Outer Hebrides -.106 .282 -.378 .705 -.659 .446 .07Solway .289 .247 1.169 .243 -.196 .775 .22

West 0 . . . . . .

Catchment Landuse PCA2 .092 .038 2.448 .015 .01839 .167 .69Substrate PCA1 -.139 .048 -2.880 .004 -.233 -.0442 .82Substrate PCA2 -.149 .048 -3.064 .002 -.244 -.0534 .87Log Local Gradient -.204 .090 -2.262 .024 -.380 -.02698 .62Log Catchment Gradient

-.174 .069 -2.539 .011 -.309 -.03954 .72

Depth PCA1 -.140 .053 -2.664 .008 -.244 -.03700 .76Log upstream catchment area (m2)

.238 .079 2.993 .003 .0819 .394 .85

Log Width -.482 .176 -2.739 .006 -.828 -.137 .78Flow PCA2 -.130 .051 -2.549 .011 -.231 -.02999 .72Day Of Year 6.12 x10-3 .002 3.914 .000 3.05 x10-3 9.19 x10-3 .97Northing -3.13 x10-6 .000 -2.819 .005 -5.32 x10-6 -9.54 x10-7 .80

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2.3.4.3 Salmon parr population density The available measures of habitat proved, as with salmon fry, to be rather poor predictors of salmon parr population density. Nine significant parameters were fitted, accounting for just 17.8% of the variation in density (Tables 17 and 18). The model is similar to that derived for fry, with Salmon Fishery Region, local land use being the principal explanatory factors, but different covariates predominate (Stream width and Substrate PCA1). Amongst the Salmon Fishery regions Moray Firth has the highest population densities for fry, with East region also high. The West, and particularly the Clyde Coast are associated with low parr population densities. While overall local land use was related to population density, the relatively small sample sizes meant that confidence in the influence of land use types is low, nevertheless BL (broad leaved/ mixed woodland) and SU (suburban/urban development) seem to be associated with high densities of parr, whilst FW (felled woodland) and SC (scrub, brambles, gorse) were associated with low densities. As with fry, stable channels had higher densities than unstable channels. In contrast to fry, low river heights during electrofishing were associated with higher recorded densities of parr than high flows. Amongst the covariates, Altitude varied positively, and river width varied negatively with parr density. Instream cover positively associated with density, whilst Substrate PCA1 was strongly negatively associated with density (indicating a positive association with cobbles and boulders). Flow PCA2 was negatively related to density (suggesting that a relative scarcity of deep pools and glides but an abundance of run type flows were associated with high population densities of parr, just as with fry). Table 17. Summary of between-subjects effects for the general linear model of minimum salmon parr population density (ln no 100m-2) based on one-run electrofishing events at sites throughout Scotland.

Source Sum of Squares

df Mean Square

F Sig.

Corrected Model 215.240 28 7.687 9.320 .000 Intercept 13.278 1 13.278 16.098 .000 CHANNEL STABILITY 16.039 2 8.019 9.723 .000 SF REGION 53.611 7 7.659 9.285 .000 RIVER LEVEL 7.029 2 3.514 4.261 .014 LOCAL LANDUSE1 35.520 12 2.960 3.589 .000 Log Altitude (m) 8.951 1 8.951 10.852 .001 Log Width (m) 16.869 1 16.869 20.452 .000 Substrate PCA1 17.688 1 17.688 21.446 .000 Flow PCA2 10.091 1 10.091 12.234 .000 Instream Cover % 9.240 1 9.240 11.202 .001 Error 863.571 1047 .825 Total 4606.247 1076 Corrected Total 1078.811 1075 R2= .200 (Adjusted R2 = .178)

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Table 18. Parameter estimates for the general linear model of minimum salmon parr population density (ln no 100m-2) based on one-run electrofishing events. See also Table 17. Parameter Coefficient S.E of t P 95% C. I. Power

Coeff Lower Upper

Intercept 1.128 .506 2.230 .026 .136 2.120 .606Mixed .309 .645 .479 .632 -.957 1.575 .077

Unstable -.371 .085 -4.365 .000 -.538 -.204 .992CHANNEL STABILITY

Stable 0 . . . . . .

Clyde Coast

-.242 .130 -1.866 .062 -.497 .0125 .462

East .520 .195 2.673 .008 .138 .902 .761Moray Firth .596 .125 4.753 .000 .350 .842 .997

SF REGION

North .315 .175 1.797 .073 -.0290 .658 .435North West .370 .113 3.263 .001 .147 .592 .903

Outer Hebrides .208 .141 1.475 .141 -.0688 .486 .314Solway .395 .116 3.413 .001 .168 .621 .926

West 0 . . . . . .

High .0421 .201 .210 .834 -.351 .436 .055Low .176 .060 2.912 .004 .0573 .294 .829

RIVER LEVEL

Medium 0 . . . . . .

unrecorded .0275 .469 .059 .953 -.893 .948 .050BL .0383 .465 .082 .934 -.874 .951 .051CP -.247 .488 -.506 .613 -1.205 .711 .080FW -1.075 1.020 -1.054 .292 -3.077 .926 .184IG -.109 .468 -.232 .816 -1.028 .810 .056

MH -.382 .469 -.814 .416 -1.303 .539 .129NC -.204 .654 -.313 .754 -1.487 1.078 .061RD -.129 .591 -.219 .827 -1.289 1.030 .056RP -.388 .466 -.833 .405 -1.303 .526 .132SC -.564 .531 -1.063 .288 -1.607 .478 .186SU .765 .791 .967 .334 -.787 2.316 .162TH -.00127 .478 -.003 .998 -.939 .937 .050

LOCAL LANDUSE 1

TL 0 . . . . . .

Log Altitude (m) .216 .066 3.294 .001 .0873 .345 .908Log Width(m) -.496 .110 -4.522 .000 -.712 -.281 .995Substrate PCA1 -.177 .038 -4.631 .000 -.252 -.102 .996Flow PCA2 -.123 .035 -3.498 .000 -.193 -.0542 .938Instream Cover % .160 .048 3.347 .001 .0661 .253 .917

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2.3.4.4 Salmon parr biomass Unlike the situation for salmon fry, including an estimate of the mass of parr, rather than just their number, did not lead to a substantial increase in the amount of variation that habitat features could explain. The model derived could account for 19.5% of the variance (Tables 19 and 20), less than 2% improvement over the population density model. In general the model was very similar to the parr population density model. The same four factors were fitted (Salmon Fishery Region, River Level, Local Landuse 1 and Channel Stability). Ten parameters were fitted in all, with Flow PCA2 and Instream Cover being dominant predictors, along with Stream width. Salmon Fishery Region contributed significantly to variation in parr biomass, East and Solway regions had high levels, whilst North, North West, West and Outer Hebrides regions had low biomass of parr. It was notable that the Moray Firth (predominant in terms of parr numbers) had only moderate biomass levels. Pairwise comparisons showed that both East Region and Solway had significantly higher biomass levels than all the other regions excepting each other (all between P<0.001 and P<0.004), with no other significant differences between any of the other regions. Channel stability again emerged as an important predictor, with unstable areas being associated with low biomass, whilst low River Levels were again associated with higher reported biomass, emphasising the need to take account of river levels when electrofishing is conducted. Local Landuse 1 (predominant land use within 50m of the bank top) results showed that Broadleaved Woodland, Improved Grassland and Tall Herbs were associated with high biomass levels, whereas Heather Moorland, Scrub and Rough Pasture were linked with low biomass levels. Pairwise comparisons revealed that Heather Moorland was associated with significantly lower biomass levels than Broadleaved Woodland (P<0.001) and Improved Grassland (P<0.002). Similarly low levels of biomass were associated with Scrubland when compared with Improved Grassland (P<0.039) and Broadleaved Woodland (P<0.023). Tall Herbs were associated with signigicantly higher parr biomass levels than Heather Moorland (P<0.06), Rough Pasture (P<0.025) and Scrub (P<0.035). The presence of Roads was also associated with high levels of biomass compared with Heather Moorland (P<0.031) and Scrub (P<0.032). Lowest marginal mean biomass levels were linked with Felled Woodland, though the sample size was small and differences were P>0.05). There was one fitted parameter in the biomass model that was not a significant predictor in the population density model: Depth PCA1 was positively related to parr biomass (suggesting an association of high biomass with moderately deep water (20-50cm)). Otherwise the covariates were similar to those for the parr population density model (positive association with Altitude and Instream Cover, and a negative association with Flow PCA2). This latter suggested that a relative scarcity of deep pools and glides but an abundance of run type flows were associated with high parr biomass. A negative relationship with this parameter was a feature of all four one-run models. A summary of the factors and covariates that were fitted in the four one-run models as well as the four Zippin density models is given in Table 21.

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Table 19. Summary of between-subjects effects for the general linear model of minimum salmon parr biomass (g 100m-2) based on one-run electrofishing events throughout Scotland. Source Sum of Squares df Mean Square F Sig.

Corrected Model 249.498 30 8.317 9.218 .000Intercept 23.914 1 23.914 26.507 .000SF REGION 46.892 7 6.699 7.425 .000CHANNEL STABILITY 7.973 2 3.987 4.419 .012LOCAL LANDUSE1 27.306 12 2.275 2.522 .003RIVER LEVEL 13.972 2 6.986 7.743 .000Log Width (m) 8.233 1 8.233 9.126 .003Log Altitude (m) 6.195 1 6.195 6.867 .009Log upstream catchment area (m2)

5.991 1 5.991 6.640 .010

Flow PCA2 15.199 1 15.199 16.847 .000Depth PCA1 4.856 1 4.856 5.382 .021Instream Cover % 16.542 1 16.542 18.336 .000Error 892.259 989 .902 Total 20245.603 1020 Corrected Total 1141.756 1019 R2= 0.219 (Adjusted R2= 0.195)

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Table 20. Parameter estimates for the general linear model of minimum salmon parr biomass (ln g 100m-2) based on one-run electrofishing events at sites throughout Scotland. See also Table 19. Parameter Coefficient S.E. of t Sig. 95% C. I. Power

coeff Lower Upper

Intercept 2.024 .638 3.172 .002 .772 3.276 .887Clyde Coast -.025 .145 -.169 .866 -.308 .259 .053

East .744 .217 3.435 .001 .319 1.169 .929Moray Firth .171 .139 1.236 .217 -.101 .443 .235

SF REGION

North .031 .184 .166 .868 -.330 .391 .053North West .067 .123 .544 .586 -.174 .307 .085

Outer Hebrides -.109 .156 -.699 .485 -.415 .197 .108Solway .632 .128 4.953 .000 .382 .883 .999

West 0 . . . . . .

Mixed .901 .676 1.333 .183 -.426 2.227 .265Unstable -.238 .091 -2.611 .009 -.418 -.059 .742

CHANNEL STABILITY

Stable 0 . . . . . .

Unrecorded .234 .442 .529 .597 -.634 1.102 .083BL .388 .438 .887 .375 -.471 1.248 .144CP .078 .465 .168 .867 -.835 .992 .053FW -.686 1.046 -.656 .512 -2.739 1.367 .100IG .321 .442 .727 .467 -.546 1.189 .112

MH -.027 .443 -.062 .951 -.896 .842 .050NC -.060 .651 -.092 .927 -1.337 1.217 .051RD .716 .581 1.233 .218 -.424 1.855 .234RP -.002 .439 -.004 .997 -.864 .860 .050SC -.307 .520 -.590 .555 -1.327 .713 .091SU .899 1.047 .858 .391 -1.156 2.953 .138TH .300 .456 .658 .511 -.595 1.196 .101

LOCAL LANDUSE 1

TL 0 . . . . . .

High .110 .222 .497 .619 -.325 .546 .079Low .263 .067 3.935 .000 .132 .395 .976

RIVER LEVEL

Moderate 0 . . . . . .

Log Width (m) -.435 .144 -3.021 .003 -.717 -.152 .855Log Altitude (m) .185 .071 2.620 .009 .047 .324 .745Log upstream catchment area (m2)

.163 .063 2.577 .010 .039 .287 .731

Flow PCA2 -.164 .040 -4.104 .000 -.243 -.086 .984Depth PCA1 .091 .039 2.320 .021 .014 .167 .640Instream Cover % .217 .051 4.282 .000 .117 .316 .990

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Table 21. Summary of the explanatory factors (capitalised) and covariates used in the models of Salmon population density and biomass for One-Run (OR) and Zippin (ZP) electrofishing estimates. Blank cells indicate the factor/covariate is not in the particular model.

salmon 0+ population

density

salmon 0+ biomass

salmon 1++ population

density

salmon 1++ biomass

OR ZP OR ZP OR ZP OR ZP CHANNEL STABILITY Yes Yes Yes Yes SF REGION Yes Yes Yes Yes Yes Yes Yes Yes RIVER LEVEL Yes Yes Yes Yes LOCAL LANDUSE1 Yes Yes Yes LOCAL LANDUSE2 Yes Yes WATER CLARITY Yes Yes Log Altitude (m) +ve +ve +ve Log Local Gradient -ve -ve Log Catchment Gradient -ve -ve Log Upstream Catchment area (m2)

+ve

Log Width -ve -ve -ve -ve -ve Depth PCA1 -ve -ve +ve Flow PCA2 -ve -ve -ve -ve -ve Substrate PCA1 -ve -ve -ve -ve -ve -ve -ve Substrate PCA2 -ve -ve Catchment Landuse PCA2 +ve Instream Vegetation % -ve Instream Cover +ve +ve % Overhanging Boughs -ve Banktop Vegetation Complexity Day Of Year -ve +ve -ve Northing -ve -ve

Variance explained (%) 17.2 17.1 25.8 18.2 17.8 24.2 19.5 30.9

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2.4 Discussion 2.4.1 Spatial autocorrelation A thorough incorporation of spatial effects between sites was not possible, however the analysis of spatial autocorrelation between sites in the Spey catchment suggested that the proximity of sites within a catchment was likely to be reflected in a tendency for a similarity in the salmonid populations present. Part of this similarity can be accounted for by the independent influence of similar habitat variables in closely situated sites. Indeed features such as site altitude seem to be much more closely related to Network distance between sites than population density. River width, an important determinant of salmonid population density, appears to vary in a similar way with Network distance between sites as does population density. In each case the analysis suggests that, after the first 10km of distance between sites there is very little sign of a consistent influence of distance between sites on site characteristics. Even within the first 10km, the influence is slight on population density, and given its similarity to the difference in physical variables, may be very largely accounted for by the genuine independent influence of the physical site characteristics. This, coupled with the absence of any indication of patterns amongst model residuals, suggests that there is little cause for concern about the models presented here being significantly influenced by the distribution of the sampling points, even though approximately 15% of site distance comparisons may fall within the range of 10km distance from other sites. 2.4.2 Comparison of Zippin and One-Run models The Zippin models fitted here had fewer parameters than their one-run counterparts, with four explanatory variables for the two salmon fry models, and five for the two salmon parr models. By contrast, the one run models had 11 and 15 variables for fry and 9 and 10 for parr. This difference probably reflects the greater statistical power of the one-run models, consequent on their larger sample sizes, though it might be that the one-run variables reflect efficiency of capture. More data might lead to further parameterisation of the Zippin models (which may perhaps be regarded as under-fitted (Burnham & Anderson 1988)), but would be unlikely to lead to a substantial increase in the amount of variance explained, since, by definition, the more important factors will be fitted at smaller sample sizes. The Zippin models give a view of salmon populations in which geographical region is important for both fry and parr (with Salmon Fishery Region appearing in all four models). Beyond that, substrate is the next most important predictor, with an apparent use of sites with high proportions of pebble and cobble substrate (negative relationship with Substrate PCA1 was fitted in all four models), with an additional indication of use of sites where cobbles and boulders were predominant for fry (Substrate PCA2 fitted to fry density model only). This suggests that the juvenile salmonid distribution is centred around the cobble-size substrate, which is consistent with previous work (Armstrong et al. 2003 and references therein). Flow conditions appeared to be significant for parr, with the models suggesting greater levels of occupation at sites where run-type flow was more common than average and where deep pools tended to be scarce, but flow conditions apparently had little impact on fry distribution. Stream width was negatively associated with parr density and biomass, but was not a significant predictor for fry. This probably reflects the greater proportion of cover provided by bank features in smaller streams, since

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the ratio of bank length to stream surface area is inversely proportional to stream width. High levels of water clarity seemed to be associated with higher biomass levels for both fry and parr, perhaps suggesting that clear water aids feeding efficiency, or that coloured water is associated with low levels of nutrients, or adversely affects the reliability of electrofishing estimates. Finally, local land use had an impact on parr biomass, with higher levels being associated with Broadleaved/Mixed Woodland, Improved Grassland, and Scrub in comparison to lower levels associated with Rough Pasture and Heather Moorland. The distribution of parr biomass relative to these land use types suggest that higher growth rates are associated with higher nutrient imput types. Conversely, these land use types did not appear to influence parr survival, since density was not influenced by local landuse in the Zippin models. Date was a negative predictor of both fry and parr numbers, but did not feature in the density models, suggesting that significant fry mortality occurred through the electrofishing period. The one-run models include a greater variety of explanatory variables, with features such as depth, instream cover, instream vegetation, and over-hanging boughs all functioning as predictors in at least one of the four models, as well as local gradient, catchment gradient and site altitude. Local landuse and Channel Stability were also fitted to all the one-run models. In general though these features were fitted in addition to, rather than instead of, the important predictors of the Zippin models (i.e. Salmon Fishery Region and Substrate PCA1). This suggests that the one-run models can be regarded as informative additional models. Only water clarity (present in two of the Zippin models) was entirely absent from the one-run models. Since coloured water was a negative predictor of Zippin biomass, it seems unlikely that Water Clarity is absent from one-run models as a consequence of inefficient fishing due to poor fish visibility. 2.4.3 Regional variation in Scotland The Zippin models give a picture of regional distribution of juvenile salmon density in Scotland in which salmon fry and parr are more abundant in the East and Solway Regions, and less abundant in the Clyde Coast, West and North West regions. The Zippin models represent the most high quality data, but suffer somewhat from a non-even distribution of sites throughout Scotland, with rather few sites in the South West, the North East, and Outer Hebrides, making it difficult to detect variation particularly from North and Outer Hebrides regions. However, this general picture is supported by the well-distributed but lower quality data from the one-run electrofishings in which both fry and parr are more abundant (and have a higher standing biomass) in the East and Solway Regions, are less abundant in the West, North West and Clyde Coast Regions, whilst the North Region and Moray Firth are intermediate in terms of both density and biomass. There is a risk that the efficiency of one-run electrofishings vary with region (due, for example, to varying conductivity) whilst Zippin densities, and Zippin-based estimates of biomass, should not be affected by variation in fishing efficiency. There may be many reasons for this regional variation in juvenile salmon populations. It may reflect differences with a northwest-southeast axis, such as rainfall, and geology, which we were not able to include in our analysis. Secondly there is a possibility that differences between Salmon Fishery Statistical Regions (SFSRs) may be generated by differences between the teams and individuals that have carried out the electrofishing in them. However, the SFCC has standardised

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the methodology between districts and all members of staff have attended the same electrofishing training courses, and in any case the SFSR boundaries do not accord with the boundaries of the individual fishery boards that contribute data to the SFCC (with the exception of the Outer Hebrides). Furthermore, the use of Zippin densities should remove variation due to team differences. One controversial factor potentially affecting much of western Scotland’s fisheries is salmon farming. It is notable that the SFSRs most remote from the influence of fish farms (Solway, East, and Moray Firth) tended to have higher population densities of salmon than those on the western seaboard. Having recently obtained data on the proximity of active and former fish farms to river mouths, we are now in a position to perform analyses that bear more directly on this issue. 2.4.4 Differences between the models and HABSCORE models The most notable feature of the Scottish data on salmonid population density analysed here is that it contains more noise in relation to habitat variables than the dataset used for HABSCORE. Where HABSCORE explained 41% and 29% of the population density of salmon fry and parr respectively, the Zippin models presented here account for 17% of fry variation and 24% of parr variation. Some of the discrepancy may be due to differences in data (for example Conductivity was an important predictor in HABSCORE but was not available here), data structure, or modelling technique. These were sufficiently similar to be unlikely to make up the difference, and it is probable that a real difference exists. This could be between (a) the sort of sites selected for inclusion in the modelling exercise (b) the quality of the data collected (c) the range of habitat types represented by the sites or (d) a true difference between the influence of habitat on salmon population density. One source of differences between HABSCORE and the present models is that the number of years over which sites were sampled was lower for HABSCORE (principally 1987-88 for Wales and 1992-93 for England, but from 1997-2002 for the Scottish sites). Habitat models of fish population density based on data from a single year tend to ‘explain’ high levels of variance (Fausch et al. 1988), but this arises because there is no inclusion of temporal variance due to stochastic events, and such models give misleadingly precise predictions of density when applied to other years. Analysis of the SFCC data on an annual basis (not presented here) showed considerable annual variability in the variance in salmon population density accounted for by habitat features. It is therefore the case that, in general, the more years of data included in a model, the less variance it will appear to explain, because a greater degree of temporal variance has been introduced. While for some purposes excluding ‘noise’ due to annual variation might be an advantage, for a model purporting to predict future salmonid populations, or providing a standard against which to judge future population estimates at sites, including more years in the reference population (as here) should provide a more realistic estimate of the true amount of spatial variance that the data can explain. Given that the present models were based on data collected over a longer period than HABSCORE, we should therefore expect lower levels of explained variance. It is notable in this regard that the latest models from the Environment Agency, based on many years of data, explain much less variance (18%) in the population density of salmon fry in England and Wales (Coley 2003), though these are based on GIS derived variables alone. Conversely, using the models based on SFCC data for the year 2000, general linear models were able to account for 26% and 31% of the variation in population density of fry and parr respectively (SFCC unpublished data).

40

The difference in the predictability of fry numbers is particularly marked between Scotland and England and Wales (17 vs 41%), with similar variance explained for 1++ fish (24 vs 29%). The relative difference of fry-fry and parr-parr predictions between HABSCORE and the present models suggests a biological component to differences between the two sets of models, because most of the artifactual reasons for differences might be expected to influence both parr and fry equally. This need not be the case however, if stochastic factors influence fry population density more heavily than parr (perhaps acting on the egg stage) and if such factors acted more strongly in Scotland than in England and Wales. It does not seem improbable that extreme flood events, or extremes of temperatures at critical times were more common in Scotland. Alternatively, the difference between fry and parr could simply reflect the different parameters that were available in the development of HABSCORE and for the present models. Where direct comparisons of parameters can be made there is little similarity between the parameters fitted to the HABSCORE models and to our own. In fact our Zippin models share no predictors in common with HABSCORE, and our one-run models very few. For salmon fry, the Zippin model fitted date (not significant for HABSCORE (Barnard et al. 1995)), and two Substrate PCA axes, together indicating higher densities where pebbles, cobbles and boulders were abundant (HABSCORE used a different approach to substrate analysis, but the presence of Cobble substrate was, overall, a negative predictor of fry density). HABSCORE fitted a negative relationship between stream width and fry density, whereas this was not a significant predictor in either the Zippin or one-run models here (although it was a negative predictor in our one-run biomass model). Similar but not identical measures of stream-bed compaction were used, and were fitted for HABSCORE, but were not significant here. In the one-run model for fry density altitude (positive), local gradient (negative), catchment gradient (negative) were all fitted, but though available to HABSCORE, were not significant (nor were they significant in our Zippin models). Comparison of the models presented here for salmon 1++ and HABSCORE salmon 1++ models show little similarity. Altitude was a positive predictor for HABSCORE, and for our one-run model, but was not significant in our Zippin model. Similar measures of upstream catchment area were used, and this was a positive predictor for HABSCORE, but not in our parr density models (though it did feature in the one-run biomass model). Stream width was fitted here in both one-run and Zippin parr density models though this was not significant in HABSCORE. Cobble sized substrate was a positive predictor of salmon parr density in our models, but was not fitted in HABSCORE. Date was a negative predictor of parr population density in our Zippin model, but was not significant in HABSCORE. The lack of similarity between our models and those of HABSCORE, despite a similar approach and many similar variables, suggests that genuine biological differences exist between the sites and populations on which they were based. Using biomass as the dependent variable instead of population density (by including an estimate of average mass along with fish numbers) raised explained variance levels from 17% & 18% for fry and parr to 24% & 31% respectively. If salmon were approaching carrying capacity in the dataset analysed here, self-thinning (of numbers) might be expected approximately to match growth, although the slope of the relationship, the ‘thinning slope’ should differ depending on whether it is space or energy that is limiting (Grant & Kramer 1990, Bohlin et al. 1994). In either case an inverse relationship between numbers and mean weight is expected, and that biomass should not vary with, or at most be very slightly influenced by, day of year. Amongst salmon parr in this study this situation may be the case because day of

41

year did not contribute to the variation in biomass. Amongst fry, however, there was a positive relationship between day of year and biomass, indicating an effect of individual growth on population biomass, itself suggestive of spare capacity at a site during the earlier part of the season, or of changing capacity through the season. It should however, be noted that a relationship consistent with a thinning gradient may occur coincidentally rather than be caused by a density-dependent process, so that the approach to carrying capacity cannot be reliably inferred (Armstrong 1997). 2.4.5 Site selection Any model is critically dependent on the data from which it is constructed. A source of difference between all habitat models of salmonid populations that is very hard to quantify is the site-selection process. Here we excluded all sites where access for salmon was dubious, all sites where pollution was regarded as an issue, and all sites where stocking either by salmon or trout was suspected or known to have occurred. The designation of sites as polluted, or stocked, or of dubious access is a somewhat subjective exercise however, and despite efforts to maintain a common standard of data recording it is possible that SFCC staff may approach these decisions somewhat differently, so that site selection might vary between areas and between years. The site selection process for HABSCORE was not directly comparable with ours. Fewer sites were used (602 throughout England and Wales compared with up to1638 in Scotland in the present study), and they were selected on the basis of a belief that there were no artificial constraints on the population and that recruitment was not limiting (Barnard et al. 1995). Whether this represents a more or less stringent selection process than the one used here is unknowable, and it is not unlikely that differences in the site selection process contribute to some of the differences between our models and those of HABSCORE. As an alternative to the models presented here we aimed to present ideal site models, in which a further reduction in the number of sites used was made. Instead of attempting to account for variation on a catchment scale by measuring certain parameters (including anthropomorphic influences such as landuse) this approach would aim to select only those sites with little human influence, and thus to see the natural influence of local habitat features on salmon density. Any modelling exercise using this further refinement would clearly represent a trade-off between sample-size and data quality. While being likely to lead to higher levels of explained variance, there would be a concomitant risk of increased bias. 2.4.6 Characterising habitat Within a site, salmonid distribution is non-random, yet the dependent variable analysed here (and in other models) was the average distribution over the whole site, while the independent variables are often average measures for the whole site. This presents a problem interpreting the data, because it is not unlikely that small areas of habitat contribute asymmetrically to the numbers of salmon found at a site, while average descriptors can mask the importance of those small areas. HABSCORE models attempted to avoid this difficulty by including the percentage cover of the various individual substrate and flow type combinations. The inclusion of so many non-independent variables in a model should probably be accompanied by a reduction in the level of α at which significance is accepted. Furthermore the inter-correlation, often negative, of such variables may lead to a situation in which a

42

significant relationship with one automatically, but erroneously leads to a relationship with another. An inadequate but statistically sound alternative would be to summarise depth data, for example, by using mean depth and depth variance as inputs to the model. Such an approach would only permit the linear influence of depth to be accommodated. Our approach to the problem was to use principal components analysis (PCA) to summarise the data. This allows for example the substrate type that, on average, is rather rare, to contribute equally to the summary as the substrate type which is, on average, dominant. The PCA approach also allows for non-linear effects of stream variables to be incorporated in the models. The PCA axes used here were correlated with abundance of intermediate depths, or substrate sizes. The problem of incorporating possible non-linear affects in the models for non-summarised data remained, but inspection of graphical relationships detect no strong non-linear (u- or n- shaped) effects. 2.4.7 Despotic and Ideal Free Distributions: predicting populations from habitat

features If animals are distributed according to the Ideal Free Distribution (Fretwell 1972) then we may anticipate a significant relationships between habitat variables and population density at both high and low populations levels. This is because all animals are free to move and to occupy the area of habitat that provides them with the highest return of, for example, food. At very low population density levels only the best patches would be occupied. Not all distributions are free however, and Fretwell (1972) coined the termed ‘Despotic’ for any distribution of animals that is influenced by aggression. In this situation there may be little scope to predict population density from habitat features, particularly if population levels are approaching carrying capacity. This situation arises if aggressive territory holders maintain larger resource bases and occupy the best habitat whilst poorer competitors maintain smaller resource bases in poorer habitat, so that territories of similar sizes occur across the habitat. Thus there is only a limited amount of variation of population density that can be explained by habitat features even in a perfectly non-stochastic environment. Viewed in these terms simple models that can explain 20-30% of variation in population by reference to habitat variables alone have performed well. 2.4.8 Model usefulness A feature of the models developed here is the incorporation of a geographical variable within the national scheme. A drawback of any modelling exercise based on post hoc analysis is that the causative nature of relationship between the independent variables and the dependent variable is unknown. This uncertainty is of limited concern where the model is only to be applied within the strict bounds of the reference population, since it can be inferred that, causative or coincidental, the relationships are likely to remain reasonably consistent. There are two main areas where the causative/correlative nature of the relationship become important for model application: differences in time (see section 2.4.2) and differences in space between the model’s source and its intended prediction. The application of HABSCORE to Scotland has rightly been regarded as a dubious exercise (Cowx 2002), because the range of conditions is likely to be different, and the underlying processes cannot be inferred. What the present modelling exercise showed is that even within Scotland there is significant regional variation in the connection between habitat and population density. All models include Salmon Fishery Regions (SFRs) (Map 2) as important

43

predictors of salmon populations. Failure to include this regional variation would result in lower explained variance, and poorer predictive power, but it is arguable that separate models for each of these regions might further improve predictive power. In using SFR as a factor in a predictive model a risk is being run. Firstly there is the possibility that rivers as yet unsampled within an SFR to which predictions are applied may be unlike other rivers in the SFR. This could be the case if the similarity within SFRs and the difference between SFRs was due to average geological differences between regions, and that the target river happened to have a non-typical catchment geology. Serious discrepancies between predicted and observed salmon populations at sites in a ‘new’ river in a SFR might suggest a cursory examination of the catchment for possible features distinguishing it from others in the region. In general the models presented here make reasonable predictors of salmon population density, but with wide confidence intervals. Predictive power is much improved if the size of the fish as well as their number can be collected so that biomass models can be used. However, the accuracy of the models is such that only the broadest scale approach to prediction can be encompassed, with only very poor or very good sites likely to be convincingly identified when predicted and observed results are compared. Nevertheless, models that can predict up to 31% of variation in populations from habitat variables alone are rare in biology, and this analysis represents a simple starting point from which more complex analyses and further work can proceed.

44

2.5 Phase 2 monitoring strategy • Three possible approaches to a monitoring strategy for juvenile Atlantic salmon in

SAC rivers are outlined below, each with its advantages and disadvantages. These approaches are: a limited number of high quality fully quantitative electrofishings at fixed sites; a larger number of timed electrofishings; and a mixture of fully quantitative and timed electrofishings.

• Fully quantitative fishings are desirable for direct comparisons between SACs, and if repeated on a yearly basis allow for definitive temporal comparisons. However, logistically it will be possible to fish only a few sites in this way (n= between 10 and 25 for each of the 17 SAC rivers, with a total of up to 300 sites).

• A large number of timed electrofishing events would provide better spatial coverage of the SAC rivers, but at the cost of the precision and accuracy of the data obtained.

• A mixed strategy could provide both high quality and wide-ranging data, but at the potential cost of maximising neither.

• The most appropriate strategy depends in part upon the likely future funding for monitoring SAC rivers, in part upon assumptions made, and in part on the exact nature of the desired outputs

• If it is assumed that SACs are presently pristine, with salmon saturating the habitat, and distributed in approximate accordance with the Ideal Free Distribution, then the high quality, low number strategy may be appropriate.

• If no assumptions are made regarding the current status of SACs, nor about the distribution of salmon within a river, then a broad scale approach, yielding information on the patchiness of salmon distribution, may be more useful than a small number of high quality sites in determining the status of the population. This is because, under certain conditions, salmon populations may remain constant in the best habitats even while numbers in the river as a whole fluctuate widely. However, timed electrofishing efficiency is likely to vary considerably with local and meteorological conditions, so that comparison between years, between rivers and even between sites on the same river may be unreliable.

• The mixed strategy seems to provide a more amenable alternative, allowing for a limited number of index sites that can be directly compared for temporal and spatial variation, but simultaneously allowing the patchiness of the salmon distributions to be assessed in order to double-check that assumptions are being met. Accordingly it is the mixed strategy that we adopt in section 4.

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3 A NATIONAL FISHERIES CLASSIFICATION SCHEME 3.1 Introduction The SFCC were asked to develop a national river classification scheme for Scottish rivers, conceived as similar to the National Rivers Authority River Classification Scheme (1995). The NRA’s scheme attempts to determine the status of a fishery with reference to the population density and diversity of the fishes it contains. The classification structure is two-fold: an ‘Absolute’ classification based on percentiles derived from a notionally representative reference population (based on 949 sites throughout England and Wales. A second ‘Relative’ classification structure attempts to account for broad-scale habitat variation in fishery expectation, using gradient and river width to modify expectations of fish populations. Again fisheries are graded according to their performance against the established percentiles from the reference population. The NRAs scheme incorporates a variety of measures either not available for, or not relevant to, Scottish inland fisheries. Most notably these relate to coarse fish populations and diversity, for which little data is available for Scotland, whilst in any case salmonids dominate the fisheries scene in Scotland. Accordingly we concentrate on salmonid populations only. We regard the principal goals of such a classification to be the provision of a framework for assessing and comparing river fisheries throughout Scotland, whilst allowing for comparison with English and Welsh fisheries. 3.2 Scope and methodology We adopt a similar approach to the NRA scheme (though including data on salmonids only). ‘Absolute’ quintile ranges of salmonid densities are based on all SFCC sites with free access for salmonids, and where stocking is not known to have occurred. This allows for an instant comparison of fishery performance against a nationally based reference point. Furthermore it will be possible to compare the absolute values of the Scottish quintile ranges with those established in England and Wales. As with the NRA’s scheme, we treat salmonid fry and parr separately, but make no attempt to distinguish between different parr ages. Results from the modelling exercises carried out as part of SECTION B indicate a marked variety of salmonid population density between areas. An established system for dividing Salmon fisheries already exists: the Salmon Fishery Statistical Regions (Map 2), and these alone can account for up to 10% of the variation in salmonid population density. By contrast, the variance in population density explained by gradient, and even width in the SFCC dataset is very much less. This strongly suggests that a finer scale approach to Scottish fisheries classification might also have utility, giving a more realistic set of expectations for local performance. To this end we will also develop quintile gradings for fishery performance based on the Statistical Region in which they occur. At present this can provide classification for seven of the eight mainland regions, while we hope to be able to provide data for the eighth, the North East, in the future. Data for two of the three island regions (Orkney and Shetland) are presently outwith the aegis of the SFCC. In addition we adopted the NRA’s attempt to account for broad-scale river habitat types by developing a second series of ‘Relative’ quintile ranges for given classes of river width, following the NRA’s classification scheme (four width classes, <4m, 4-6m, 6-9m and >9m). Because of their being few rivers in the widest width class in the Outer Hebrides, and because of a generally small sample size in the North region, we have, in these cases combined river width classes rather than publish benchmarks for each width class based on inadequate sample sizes.

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The NRA’s ‘Relative’ scheme included classifications based on gradient as well as width. In an attempt to follow this system the SFCC recently measured gradients for all the sites for which electro-fishing data are available, following the methodology described in the NRA scheme. However, in contrast to the situation in England and Wales, gradient had a trivial and non-consistent effect on salmonid population densities, and we therefore did not include it as a habitat descriptor. Nor, indeed, did any other single and widely available broad-scale measure of habitat. We therefore have confined our classification scheme to one based on region and river width alone. Quintile estimates were calculated using the back-transformed logarithmic mean of one-run minimum estimate electrofishing event(s) at 1638 sites, selected for having free access to salmon and trout, unstocked status and absence of known polluting factors, spread throughout Scotland. Estimates of zero population densities were excluded from the quintile ranges, but the proportion of sites with zero estimates (for particular age/species classes, river widths and areas) is recorded. We adopt this approach for several reasons. Firstly, although no issues with access or pollution are known to exist, nevertheless access may be restricted, or local pollution may have occurred. Secondly, it is possible to estimate what the likely equivalent three-run electrofishing estimate would have been based on the one-run estimate data provided here, but only where a non-zero result is recorded. Thus by treading the one-run zero estimates separately, we allow for a wider comparison with other sorts of data. Table 22. The basic structure of the classification scheme.

One Run estimate comparison with relevant percentile range

Classification

> 80th percentile Class A

>60th percentile <80th percentile Class B

>40th percentile <60th percentile Class C

>20th percentile <40th percentile Class D

>zero <20th percentile Class E

zero Unclassified*

*National/local likelihood of obtaining zero population density enables assessment of the Unclassified status It is envisaged that the 80th percentile figure for population density be regarded as the national (or where appropriate local) minimum standard for a class A river or site, the 60th percentile representing the minimum for a B classification, and so on (Table 16). A one-run estimate of zero will yield an Unclassified status, which can be regarded as the lowest possible denomination. It should be noted, however, that in certain circumstances, zero is the most likely one-run population density estimate amongst the reference population. Thus the significance of the Unclassified status must be assessed for each circumstance (which can be readily achieved by reference to Tables 23 to 29).

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3.3 Fisheries classification scheme Data are presented both graphically and in table form. The 100th percentile (or maximum density recorded) is reported for interest in the tables, but is not shown graphically because it is of little value in classifying a river or site. This is because the maximum reported score is necessarily dependent on the number of samples it is drawn from, and is not therefore directly comparable between widths/regions. 3.3.1 Absolute national classification These provide a broad approach to the Scottish fisheries, perhaps for comparison with other national fisheries. Table 23. Quintile Ranges for juvenile Salmonid density from 1638 sites on rivers throughout Scotland, based on one-run electrofishing events. Quintile ranges are calculated from those sites with densities greater than zero, the proportion of sites with zero density is indicated. Population Density (number 100m-2) Salmon 0+ Salmon 1++ Trout 0+ Trout 1++ Min 0.2 0.3 0.2 0.220th percentile 4.7 2.6 2.5 1.640th percentile 10.3 5.1 5.3 3.160th percentile 20.3 9.1 12.4 5.680th percentile 42.1 15.8 30.3 10.4Max 497.7 119.1 415.7 204.4Proportion zero density 27.7% 23.3% 14.0% 18.7% Figure 4. National expectations for salmonid population density measured by one-run electrofishing events, based on data in Table 23.

National Salmonid Population Density

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3.3.2 Relative national classification These offer a refinement of the absolute national classes, by taking account of the influence of river width on salmonid population density expectations (Table 24, Figures 5 and 6). Table 24. Summary of juvenile salmonid population densities (number 100m-2) for different classes of river width throughout Scotland, based on one-run electrofishing events. Minimum, maximum and quintile points are shown. Quintile ranges are calculated from those sites with densities greater than zero, the percentage of sites with zero density is indicated.

Width Class <4m 4-6m 6-9m >9m

Salmon 0+ 0th percentile 0.2 0.5 0.5 0.3 20th percentile 4.3 5.1 5.2 4.2 40th percentile 8.7 11.0 12.2 10.7 60th percentile 15.2 26.6 21.5 18.7 80th percentile 35.2 49.2 41.2 38.9 100th percentile 497.7 290.0 295.9 252.1 Percent zero density 40.0 19.1 22.8 14.1

Salmon 1++

0th percentile 0.7 0.4 0.4 0.3 20th percentile 2.5 2.8 3.2 2.3 40th percentile 5.1 5.1 6.2 4.1 60th percentile 8.3 9.6 10.6 8.2 80th percentile 15.8 16.8 16.8 14.2 100th percentile 79.0 51.4 119.1 50.4 Percent zero density 36.9 16.0 17.4 6.0

Trout 0+

0th percentile 0.6 0.5 0.5 0.2 20th percentile 4.5 3.3 2.2 1.1 40th percentile 11.0 6.9 4.0 1.8 60th percentile 22.9 13.7 5.7 3.3 80th percentile 49.9 32.2 12.9 7.1 100th percentile 415.7 221.4 160.8 100.5 Percent zero density 12.9 10.1 12.0 24.0

Trout 1++

0th percentile 0.7 0.4 0.5 0.2 20th percentile 4.5 2.0 1.3 0.7 40th percentile 5.0 3.4 2.1 1.0 60th percentile 8.3 6.4 3.6 1.8 80th percentile 15.3 10.3 6.2 2.7 100th percentile 174.2 67.4 204.4 10.1 Percent zero density 15.2 12.4 16.1 37.8

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Figure 5. Distribution of juvenile salmonid densities in Scotland, showing variation with river width: (a) salmon fry, (b) salmon parr, (c) trout fry, (d) trout parr. Percentile densities derived from mean densities at sites estimated by one-run electrofishing episodes.

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Figure 6. Proportion of electrofishing events at selected sites throughout Scotland in which zero juvenile salmonids of particular species/age classes were detected by the one-run technique. Total number of sites =1638 (<4m, n=683; 4-6m, n=356; 6-9m, n=326; >9m, n=283)

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3.3.3 Absolute regional classification A regional breakdown of fishery classification, taking account of spatial variation in salmonid population densities, using the Salmon Fishery Statistical Regions (see Map 2) as its basis (Table 25, Figure 7). Table 25 Quintile Ranges for juvenile salmonid density (numbers 100m-2) based on one-run electrofishing events, for the various Salmon Fishery Statistical Regions. Quintile ranges were calculated from those sites with densities greater than zero, the percentage of sites with zero density is indicated. a) Clyde Coast region, n=151 sites

salmon 0+ salmon 1++ trout 0+ trout 1++ Percent zero density 27.8% 27.8% 7.94% 17.9% Min 0.33 0.26 0.44 0.25 20th percentile 5.04 1.56 2.33 1.84 40th percentile 10.66 3.06 4.69 3.29 60th percentile 18.88 5.06 8.65 5.22 80th percentile 47.66 9.17 20.66 7.60 Max 210.61 36.96 145.47 42.95

(b) East region, n=183 sites

salmon 0+ salmon 1++ trout 0+ trout 1++ Percent zero density 12.0% 10.4% 3.3% 10.4% Min 0.69 0.69 0.85 0.30 20th percentile 6.89 3.05 4.31 1.86 40th percentile 21.54 6.30 11.94 3.39 60th percentile 43.38 10.16 26.21 7.46 80th percentile 104.58 19.07 72.10 13.85 Max 497.70 51.42 292.95 70.81

(c) Moray Firth region, n=226 sites

salmon 0+ salmon 1++ trout 0+ trout 1++ Percent zero density 19.9% 11.5% 16.8% 16.4% Min 0.67 0.67 0.29 0.57 20th percentile 7.37 3.74 2.21 1.60 40th percentile 15.49 9.49 4.52 2.89 60th percentile 29.78 14.53 8.67 5.57 80th percentile 55.04 23.10 18.25 11.29 Max 196.36 119.10 94.63 80.64

(d) North region, n=50 sites

salmon 0+ salmon 1++ trout 0+ trout 1++ Percent zero density 24.0% 18.0% 12.0% 28.0% Min 0.51 1.01 0.51 0.57 20th percentile 5.45 2.18 1.79 1.09 40th percentile 10.70 6.36 4.16 2.72 60th percentile 14.79 9.49 5.10 4.37 80th percentile 29.37 16.28 10.07 7.61 Max 67.36 27.66 98.49 14.73

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Table 25 (continued) (e) North West region, n=392 sites

salmon 0+ salmon 1++ trout 0+ trout 1++ Percent zero density 35.7% 29.6% 15.6% 28.3% Min 0.78 0.66 0.44 0.22 20th percentile 4.42 2.58 1.99 1.52 40th percentile 8.00 4.67 4.26 2.72 60th percentile 14.15 8.04 8.25 4.31 80th percentile 26.05 13.09 15.80 8.58 Max 121.51 37.34 102.51 47.47

(f) Outer Hebrides region, n=160 sites

salmon 0+ salmon 1++ trout 0+ trout 1++ Percent zero density 30.0% 31.9% 35.0% 26.3% Min 0.50 0.71 0.16 0.17 20th percentile 2.86 2.37 1.74 1.00 40th percentile 5.58 5.33 3.22 2.14 60th percentile 9.53 9.26 6.55 3.75 80th percentile 15.55 14.15 11.89 7.07 Max 167.34 40.44 56.26 38.09

(g) Solway region, n=291 sites

salmon 0+ salmon 1++ trout 0+ trout 1++ Percent zero density 28.9% 21.0% 7.2% 8.6% Min 0.22 0.38 0.38 0.35 20th percentile 5.21 2.86 4.14 2.27 40th percentile 12.68 5.87 12.09 4.71 60th percentile 25.28 9.12 26.63 8.25 80th percentile 46.53 15.03 56.49 16.28 Max 221.41 50.40 415.72 174.16

(h) West region, n=185 sites

salmon 0+ salmon 1++ trout 0+ trout 1++ Percent zero density 45.4% 33.0% 15.7% 16.8% Min 0.58 0.51 0.24 0.49 20th percentile 2.44 1.93 1.99 1.59 40th percentile 6.05 3.64 5.53 3.05 60th percentile 14.59 5.81 17.29 5.28 80th percentile 26.58 11.27 50.40 8.36 Max 172.43 40.45 181.27 66.69

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Figure 7. Variation in population density of juvenile salmonids by Salmon Fishery Statistical Regions, assessed using one-run electrofishing events. Quintiles based on mean densities at 1638 sites throughout Scotland (a) salmon fry, (b) salmon parr, (c) trout fry, (d) trout parr.

b) Salmon 1++ population density

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3.3.4 Relative regional classification A refinement of the absolute regional classes that take account of the influence of river width on salmonid population density expectations (Table 26, Figures 8 to 16). Table 26. Summary of juvenile salmonid population densities (no 100m-2) in different river width classes, based on one-run electrofishing events. Minimum, maximum and quintile points are shown. Quintile ranges are calculated from those sites with densities greater than zero, the percentage of sites with zero density is indicated. (a) Clyde Coast region (n=151 sites)

Width Class <4m 4-6m 6-9m >9m

salmon 0+ 0th percentile 0.7 0.7 1.5 0.3 20th percentile 5.5 8.5 4.5 7.4 40th percentile 11.2 15.6 5.5 9.7 60th percentile 19.1 25.4 17.7 16.5 80th percentile 53.3 50.4 41.5 30.0 100th percentile 115.6 210.6 89.1 62.8 % zero density 35.2 34.3 23.1 10.5

salmon 1++ 0th percentile 0.7 0.7 0.4 0.3 20th percentile 1.6 1.6 1.6 1.1 40th percentile 3.0 3.9 3.1 2.2 60th percentile 4.6 5.6 6.0 4.4 80th percentile 6.9 9.2 12.6 6.9 100th percentile 19.3 24.0 20.5 37.0 % zero density 32.4 31.4 30.8 5.3

trout 0+ 0th percentile 0.9 0.6 0.5 0.4 20th percentile 5.0 2.8 1.8 1.4 40th percentile 9.2 4.4 2.7 2.1 60th percentile 15.8 6.8 4.2 2.7 80th percentile 28.8 16.7 5.3 4.6 100th percentile 87.4 145.5 40.0 8.6 % zero density 8.5 5.7 7.7 10.5

trout 1++ 0th percentile 0.9 0.6 0.6 0.2 20th percentile 2.5 1.4 1.5 0.8 40th percentile 4.8 3.8 2.1 1.2 60th percentile 6.1 5.9 3.4 2.1 80th percentile 8.5 9.9 5.3 2.7 100th percentile 29.7 42.9 8.6 4.1 % zero density 14.1 17.1 15.4 36.8

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Table 26 (b) East region (n=183)

Width Class <4m 4-6m 6-9m >9m

salmon 0+ 0th percentile 0.9 0.9 0.7 2.5 20th percentile 5.5 7.1 12.5 5.6 40th percentile 20.5 21.5 22.5 17.1 60th percentile 53.8 37.2 45.2 37.3 80th percentile 124.0 63.6 90.9 79.8 100th percentile 497.7 290.0 295.9 252.1 % zero density 16.1 16.7 7.3 5.3

salmon 1++ 0th percentile 0.7 1.2 0.7 0.7 20th percentile 3.0 3.2 4.1 2.3 40th percentile 6.3 6.3 8.1 5.3 60th percentile 10.6 8.9 12.6 9.9 80th percentile 20.3 16.7 22.0 15.5 100th percentile 40.9 51.4 48.9 37.3 % zero density 14.3 10.4 9.8 5.3

trout 0+ 0th percentile 1.5 0.9 1.0 0.9 20th percentile 17.4 9.0 4.1 1.7 40th percentile 32.9 16.8 6.6 3.9 60th percentile 70.2 42.6 13.2 6.1 80th percentile 108.9 89.7 26.5 12.2 100th percentile 292.9 164.0 95.6 59.1 % zero density 1.8 2.1 2.4 7.9

trout 1++ 0th percentile 0.9 0.9 0.5 0.3 20th percentile 4.4 2.7 1.8 0.5 40th percentile 8.9 4.7 2.9 0.8 60th percentile 14.1 7.5 3.7 1.6 80th percentile 20.4 13.2 9.4 3.0 100th percentile 70.8 32.5 16.8 9.4 % zero density 3.6 2.1 14.6 26.3

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Table 26 (c) Moray Firth region (n=226)

Width Class <4m 4-6m 6-9m >9m

salmon 0+ 0th percentile 1.5 1.0 0.7 0.9 20th percentile 8.6 7.7 11.2 4.0 40th percentile 22.6 27.5 18.7 9.9 60th percentile 35.8 42.6 26.8 15.1 80th percentile 86.8 77.3 40.4 32.3 100th percentile 186.8 196.4 97.5 114.4 % zero density 36.2 13.8 16.7 18.0

salmon 1++ 0th percentile 1.2 1.0 0.7 0.9 20th percentile 5.3 3.7 4.9 3.0 40th percentile 11.7 10.8 9.2 6.7 60th percentile 18.9 18.4 12.4 12.1 80th percentile 30.9 25.3 22.8 16.0 100th percentile 79.0 40.9 119.1 33.4 % zero density 23.4 12.1 10.0 3.3

trout 0+ 0th percentile 1.1 0.5 0.8 0.3 20th percentile 5.9 2.9 3.1 1.2 40th percentile 14.3 7.0 4.5 1.6 60th percentile 21.0 10.4 6.0 3.3 80th percentile 39.0 26.4 9.3 5.4 100th percentile 94.6 64.7 83.9 37.3 % zero density 17.0 8.6 18.3 23.0

trout 1++ 0th percentile 1.4 1.0 0.6 0.6 20th percentile 3.9 2.3 1.3 1.0 40th percentile 9.1 5.2 2.3 1.7 60th percentile 13.7 7.2 4.0 1.9 80th percentile 18.1 13.3 6.1 2.7 100th percentile 80.6 23.6 46.1 8.9 % zero density 6.4 17.2 6.7 31.1

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Table 26 (d) North region (n=50)

Width Class <6m >6m

salmon 0+ 0th percentile 1.0 0.5 20th percentile 7.1 4.5 40th percentile 9.3 13.1 60th percentile 12.7 28.4 80th percentile 20.1 32.7 100th percentile 48.9 67.4 % zero density 34.5 9.5

salmon 1++ 0th percentile 1.2 1.1 20th percentile 1.7 4.4 40th percentile 4.6 7.0 60th percentile 8.5 13.3 80th percentile 13.0 19.1 100th percentile 21.3 27.7 % zero density 24.1 9.5

trout 0+ 0th percentile 1.0 0.5 20th percentile 4.4 0.8 40th percentile 5.2 1.9 60th percentile 8.5 2.9 80th percentile 12.6 4.2 100th percentile 98.5 5.5 % zero density 6.9 19.0

trout 1++ 0th percentile 1.2 0.6 20th percentile 3.0 0.6 40th percentile 4.4 0.9 60th percentile 7.1 1.1 80th percentile 8.6 1.6 100th percentile 14.7 3.6 % zero density 20.7 38.1

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Table 26 (e) North West region (n=392)

Width Class <4m 4-6m 6-9m >9m

salmon 0+ 0th percentile 0.8 1.0 0.8 1.0 20th percentile 4.4 4.5 2.7 5.5 40th percentile 7.0 10.6 5.5 11.4 60th percentile 11.5 20.8 8.7 14.2 80th percentile 23.0 33.1 17.8 28.6 100th percentile 121.5 70.1 73.7 79.8 % zero density 49.4 24.7 34.6 17.3

salmon 1++ 0th percentile 0.7 0.7 0.7 0.7 20th percentile 2.6 2.4 2.5 2.9 40th percentile 4.9 3.7 5.5 4.3 60th percentile 7.9 8.0 9.0 8.0 80th percentile 13.9 13.7 12.5 11.8 100th percentile 31.8 37.3 24.0 22.4 % zero density 47.0 17.8 25.6 8.0

trout 0+ 0th percentile 0.9 0.7 0.7 0.4 20th percentile 4.4 2.2 1.9 1.1 40th percentile 8.8 4.3 2.9 1.4 60th percentile 15.8 5.9 4.9 8.3 80th percentile 29.7 11.5 8.6 3.1 100th percentile 102.5 30.3 28.8 14.3 % zero density 10.2 13.7 11.5 33.3

trout 1++ 0th percentile 1.1 0.7 0.8 0.2 20th percentile 2.6 1.1 1.2 0.7 40th percentile 4.1 2.1 1.8 0.8 60th percentile 7.2 3.3 2.8 4.3 80th percentile 12.6 5.6 4.6 2.4 100th percentile 47.5 25.5 24.8 10.1 % zero density 16.3 23.3 25.6 62.7

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Table 26 (f) Outer Hebrides region (n=160)

Width Class <4m 4-6m >6m

salmon 0+ 0th percentile 1.2 0.5 0.9 20th percentile 4.1 1.9 1.5 40th percentile 7.4 2.7 2.8 60th percentile 12.4 5.3 3.6 80th percentile 18.7 8.2 7.2 100th percentile 167.3 15.8 10.9 % zero density 36.7 5.3 0.0

salmon 1++ 0th percentile 1.0 0.7 1.0 20th percentile 3.1 3.9 1.7 40th percentile 6.8 5.0 2.0 60th percentile 10.1 7.2 3.7 80th percentile 17.2 10.2 7.5 100th percentile 40.4 13.5 13.2 % zero density 38.3 10.5 0.0

trout 0+ 0th percentile 0.6 1.1 0.2 20th percentile 2.1 1.9 0.3 40th percentile 3.5 2.2 0.5 60th percentile 6.8 4.8 0.9 80th percentile 13.1 9.0 2.5 100th percentile 56.3 11.8 8.5 % zero density 28.9 57.9 69.2

trout 1++ 0th percentile 0.7 0.4 0.2 20th percentile 1.6 0.6 0.2 40th percentile 2.8 0.7 0.3 60th percentile 4.9 1.9 0.5 80th percentile 8.4 3.7 1.3 100th percentile 38.1 5.7 2.1 % zero density 28.1 10.5 30.8

60

Table 26 (g) Solway region (n=291)

Width Class <4m 4-6m >6m >9m

salmon 0+ 0th percentile 0.2 1.0 1.7 0.7 20th percentile 3.0 6.1 11.7 7.1 40th percentile 8.4 16.4 19.3 11.7 60th percentile 19.7 33.9 32.8 22.0 80th percentile 37.3 54.9 48.4 38.9 100th percentile 221.4 167.3 125.2 120.3 % zero density 31.7 10.5 13.2 4.8

salmon 1++ 0th percentile 0.8 0.4 0.8 0.5 20th percentile 2.5 2.9 3.9 2.8 40th percentile 5.1 5.7 8.2 6.0 60th percentile 7.8 10.4 11.4 8.8 80th percentile 11.1 15.3 17.3 13.6 100th percentile 36.2 33.8 30.6 50.4 % zero density 32.5 11.8 9.4 4.8

trout 0+ 0th percentile 0.7 0.5 0.8 0.4 20th percentile 5.6 6.4 4.0 1.4 40th percentile 19.9 18.4 7.4 3.4 60th percentile 48.4 32.4 21.8 9.7 80th percentile 94.6 51.3 32.6 24.0 100th percentile 415.7 221.4 160.8 100.5 % zero density 11.7 2.6 5.7 4.8

trout 1++ 0th percentile 0.7 1.2 0.5 0.3 20th percentile 4.0 3.2 1.7 0.7 40th percentile 8.4 5.8 3.5 1.1 60th percentile 11.6 8.1 5.6 2.1 80th percentile 23.1 15.3 10.0 4.5 100th percentile 174.2 67.4 204.4 8.8 % zero density 10.0 1.3 7.5 19.0

61

Table 26 (h) West region (n=185)

Width Class <4m 4-6m >6m >9m

salmon 0+ 0th percentile 1.3 1.6 0.8 0.6 20th percentile 2.4 3.5 1.6 2.7 40th percentile 5.3 6.0 10.4 8.1 60th percentile 10.7 14.0 14.0 15.9 80th percentile 17.2 35.5 21.1 45.1 100th percentile 92.8 55.1 172.4 83.9 % zero density 60.0 27.3 44.7 29.4

salmon 1++ 0th percentile 1.4 0.8 0.5 0.5 20th percentile 2.3 2.0 1.9 1.7 40th percentile 3.3 5.0 4.4 3.2 60th percentile 6.9 6.6 5.9 4.2 80th percentile 12.2 10.8 10.9 6.6 100th percentile 30.9 40.4 22.0 24.0 % zero density 48.8 24.2 26.3 11.8

trout 0+ 0th percentile 1.4 0.7 0.5 0.2 20th percentile 9.9 3.0 1.1 0.8 40th percentile 28.5 5.0 1.8 1.5 60th percentile 44.7 12.4 2.7 2.6 80th percentile 74.4 19.0 5.3 4.0 100th percentile 181.3 103.5 94.6 9.8 % zero density 5.0 12.1 18.4 41.2

trout 1++ 0th percentile 0.9 0.9 0.8 0.5 20th percentile 3.9 2.3 1.5 0.7 40th percentile 5.6 3.3 2.1 0.9 60th percentile 7.6 5.4 3.2 1.5 80th percentile 12.1 8.4 4.9 1.8 100th percentile 66.7 30.3 10.8 6.0 % zero density 13.8 12.1 18.4 26.5

62

Figure 8. Variation in juvenile salmonid population densities with site river width, Clyde Coast region. Data shown are mean quintile distributions for sites based on one-run electro-fishing samples, excluding zeros. Total number of sites=151. (a) salmon fry (b) salmon parr (c) trout fry (d) trout parr

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63

Figure 9. Variation in juvenile salmonid population densities with site river width, East region. Data shown are mean quintile distributions for sites based on one-run electro-fishing samples, excluding zeros. Total number of sites=183. (a) salmon fry (b) salmon parr (c) trout fry (d) trout parr

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64

Figure 10. Variation in juvenile salmonid population densities with site river width, Moray Firth region. Data shown are mean quintile distributions for sites based on one-run electro-fishing samples, excluding zeros. Total number of sites=228 (a) salmon fry (b) salmon parr (c) trout fry (d) trout parr.

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65

Figure 11. Variation in juvenile salmonid population densities with site river width, North region. Data shown are mean quintile distributions for sites based on one-run electro-fishing samples, excluding zeros. Total number of sites=50. (a) salmon fry (b) salmon parr (c) trout fry (d) trout parr

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66

Figure 12. Variation in juvenile salmonid population densities with site river width, North West region. Data shown are mean quintile distributions for sites based on one-run electro-fishing samples, excluding zeros. Total number of sites=392. (a) salmon fry (b) salmon parr (c) trout fry (d) trout parr

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67

Figure 13. Variation in juvenile salmonid population densities with site river width, Outer Hebrides region. Data shown are mean quintile distributions for sites based on one-run electro-fishing samples, excluding zeros. Total number of sites=160. (a) salmon fry (b) salmon parr (c) trout fry (d) trout parr

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68

Figure 14. Variation in juvenile salmonid population densities with site river width, Solway region (including the border Esk). Data shown are mean quintile distributions for sites based on one-run electro-fishing samples, excluding zeros. Total number of sites=291. (a) salmon fry (b) salmon parr (c) trout fry (d) trout parr

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69

Figure 15. Variation in juvenile salmonid population densities with site river width, West region. Data shown are mean quintile distributions for sites based on one-run electro-fishing samples, excluding zeros. Total number of sites=185. (a) salmon fry (b) salmon parr (c) trout fry (d) trout parr

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Figure 16. Proportion of sites at which one-run electrofishing events detected zero salmonids (a particular species/age class). Some river width classes combined in North and Outer Hebrides regions to ensure sample sizes greater than 15.

(b) Clyde Coast, n=151

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71

4. SAMPLING PROGRAMME OF SAC JUVENILE SALMON POPULATIONS 4.1 Site selection 4.1.1 Introduction Perhaps the ideal site selection for monitoring populations should be random allowing an unbiased view of the river and maximising the number of questions to which the resultant data can be applied. However the present monitoring exercise was constrained from such an approach by both financial necessities and output requirements. The approach adopted for reporting the site condition for SACs requires that some assessment of the population dynamics of the species is made. Presently the state of knowledge of juvenile salmon is not in a position to achieve this end convincingly for salmon (eg from habitat data or age-structure alone) without recourse to historical information. The sampling programme was designed to give information on the present population levels of salmon at given sites within the SAC, on historical trends in population density at those sites, on the spatial distribution of salmon throughout the SAC, and on the distribution of salmon amongst flow types in the SAC. For both the depletion and timed electrofishing programs the goals were two-fold. The depletion fishing programme sought 1) to set the present juvenile salmon population levels within their historical context

and 2) to set up a large collection of high quality population estimates as a benchmark

for future monitoring Given this dual role, depletion sites were selected to maximise the value of current historical data consistent with a reasonable geographical spread of sites throughout the SAC. The timed fishing programme was aimed at 1) creating a larger number of samples to assess the spatial status of salmon

populations within SACs on a larger scale (as well as giving CPUE estimates for given conditions)

2) investigating habitat saturation on a finer scale with reference to the Ideal Free Distribution (Fretwell & Lucas 1979) and the Ideal Despotic Distributions in relation to juvenile salmon population densities in three different flow types: glide, run and riffle.

A number of sites in the sampling programme for each SAC was agreed between SNH and the SFCC (Table 27), and the sampling was intended to take place in August/early September 2004. A very wet August in many parts of Scotland, together with a number of unforeseen local difficulties meant a substantial disruption to the programme of work, with many sites not fished until October, and still other sites not able to be fished at all (Table 27). Affected in particular were the Oykel, the Borgie, the Moriston and the Tay. These SACs were revisited in 2005, together with the South Esk (about which some concerns regarding the quality of the electrofishing data had been raised (see section 4.3.12).

72

Table 27. The number of depletion and timed electrofishing sites in the sampling programme agreed between SNH and the SFCC and the actual number of sites achieved in 2004 and, in parentheses, 2005. SAC Agreed no.

Depletion Actual no. Depletion

Agreed no.Timed

Actual no. Timed

Berriedale&Langwell 6 6 9 9 Bladnoch 6 6 9 9 Borgie 6 0 9 1 Dee 8 8 14 14 Endrick 6 6 9 9 Grimersta 7 5 11 8 Little Gruinard 7 7 11 11 Moriston 6 0(6) 9 0(9) Naver 7 6 11 8 North Harris 7 8 11 8 Oykel 7 2 (5) 11 0(7) South Esk 7 9 (7) 11 11 (10) Spey 11 11 18 16 Tay 15 9(3) 25 8(7) Teith 7 7 11 11 Thurso 7 7 11 11 Tweed 10 10 16 16 4.1.2 Depletion site selection We adopted a series of revisits to sites on the SACs for which previous fully-quantitative or semi-quantitative electrofishing estimates of salmon densities were available (if any), and set out to obtain current (2004) fully quantitative population density estimates. It should be noted that the selection of pre-existing sites, by Fishery Trust biologists, was not subject to centralised control, and data from such sites may reflect individual differences in site selection. Accordingly direct comparisons between different SAC rivers may be slightly compromised. New depletion sites were used where existing sites did not adequately cover the spatial extent of the SAC, or where there were no pre-existing sites. The general location of the sites was allocated centrally, but in most cases the specific site was determined by local Fisheries Trust biologists. 4.1.3 Timed site selection Timed sites were selected centrally, being located on line maps of the SAC (with no details other than the river network) in a way intended to maximise the spatial distribution of sites within the SAC. The grid reference of the location marked on the line maps was then determined as accurately as possible using O/S maps. Electrofishing teams were asked locate this spot on the ground, and move upstream from the location until the first run, glide or riffle was found (see section 4.1.4). This sampling programme could be described as a stratified semi-random, although in a few cases logistical concerns of the electrofishing teamson the ground led to a change in the location of the timed site from that allotted centrally, and thus to a reduction in the true randomness of the sampling strategy.

73

4.1.4 Electrofishing methodology The electofishing protocol for depletion sites followed the SFCC protocol for 3-run depletion electrofishing as closely as possible (SFCC 2001b, APPENDICES A & B), including the collection of habitat data. In a few cases not all the habitat data was collected. The timed fishing protocol followed a new Timed Electrofishing Protocol developed with participation from the SFCC Electrofishing Review Group. Teams moved upstream from the site location conducting 5 minutes worth of electrofishing in each of three flow types (glide, run and riffle, as determined according to SFCC definitions, APPENDIX C), as and when they arose. The Timed Electrofishing Protocol is given in full in APPENDICES F and G. In a few cases there was insufficient habitat for the full 5 minutes of timed fishing in a run or glide or riffle (the shortest of these was three minutes 10 seconds) and the data present on catch rates per minute has been adjusted accordingly. On none of these occasions was zero fish caught. 4.1.5 Surveillance and monitoring For the purposes of SAC condition monitoring, a distinction is made between surveillance and monitoring (Anon 1998). Surveillance is a generalised assessment of population status, whereas monitoring compares the population with some predetermined standard. Given the chief conclusion of Section 2, that the predictive power of habitat modelling is fairly weak, and that greater than 75-80% of variability in juvenile salmon population density derives from unexplained or stochastic factors, it would be counterproductive to define ‘expected’ population size at this stage in the process. Accordingly, the focus of this section will be on surveillance, in the hope and expectation that further accumulation of data may lead to improved understanding and eventually toward the formulation of standards for population levels. In the interests of putting SAC river juvenile salmonid populations levels within the context of Scottish rivers as a whole however, a comparison of the current data with the National River Classification Scheme developed in Section 3 is made. 4.2 Different types of estimates of salmon populations in rivers by electro-fishing By necessity, there are a series of different types of estimates of salmon density used in this report. These are described here for the sake of economy. 4.2.1 Timed electrofishing This represents a time rather than area limited approach, so that the resultant figure is catch per unit effort (CPUE), where the unit of effort is time. These estimates are semi-quantitative only, and differences will accrue from variation in operator skill, speed, habitat type, flow, water turbidity, and ight levels as well as from true variation in fish density. Many of the problems can be minimised with appropriate-training, common-protocol and tools and the restriction of the fishing to particular conditions, but their effects remain unquantifiable.

74

4.2.2 Semi-quantitative electrofishing This is the least rigorous area-based estimate of fish population density. Frequently it is simply determined by a single ‘run’ or ‘pass’ of the electrofishing team through the delineated area of fishing. The density is then calculated from this figure, and the resulting estimate of density is known as a one-run minimum density estimate (or a single-pass minimum density estimate). It is a ‘minimum density estimate, because there is no means of incorporating the fish that were uncaught in this single run. A slight improvement on the one run minimum estimate is the three-run minimum density estimate. As the name suggests this is derived from three success passes of the team through the area. Fish are NOT returned to the stream at the end of each pass, but are stored in holding tanks on the bank. While these yield a minimum density estimate nearer to the true density, it still allows for no estimation of the true density. Semi-quantitative electrofishings are likely to be influenced by differences in weather and flow conditions as well as habitat types and operator skill. 4.2.3 Fully-quantitative electrofishing Also known as a depletion estimate and Zippin density (after Zippin 1954). These are derived from the same method electrofishing method as the three-run minimum depletion estimates with the difference being that the distribution of fish caught with each succeeding run allows for a statistical estimate of the total number of fish present in the area, and for the attachment of confidence limits to the estimate (Zippin 1954). These estimates rely on the assumption of constant effort and constant catchability of individual fish. 4.2.4 Relationships between the various estimates of density The chief drawback with fully quantitative/Zippin estimates is that they often cannot be calculated where numbers of fish caught are very low, and clearly never where no fish are caught. Hence at times in this report, to avoid biasing analysis against low density sites, 3-run minimum estimates are used in place of Zippin estimates. Where this has been the case attention is always drawn to the fact in the text, figures and tables. Figure 17 shows the close correspondence between 3 run minimum and Zippin density estimates in the data collected for the SACs in 2004, with Zippin estimates generally being a few percent higher than the 3-run minimum on which the Zippin estimate is based. Clearly Zippin estimates can never be lower than the 3-run minimum. Table 28 gives the regression equations for the relationships between three-run minimum estimates and the depletion estimates associated with them for salmon fry and parr. These explain a great deal of the variance (r2=0.97 for fry, 0.94 for parr after the exclusion of an obvious outlier), but, as seen in Figure 17, Zippin estimates occasionally vary more markedly above the 3-run minimum. These Zippin estimates are invariably those that are associated with large confidence intervals. Table 28. Linear regression describing the relationship between three-run minimum and depletion density estimates. See Figure 17. For parr the obvious outlier (Figure 17b) was excluded from the regression.

slope intercept R2 n P< salmon fry 1.128±0.021 1.70±1.74 0.971 88 0.000001 salmon parr 1.080±0.029 0.98±0.70 0.941 87 0.000001

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Figure 17. The relationship between three-run minimum number of fish and the Zippin density estimates associated with them for a) salmon fry and b) salmon parr. a) b)

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Slightly more problematic is the relationship between 3-run and 1-run minimum density estimates. This is because comparisons between the two can only be made where 3-run estimates have been made (i.e. comparing the first run of a three with all three runs). However, single runs are frequently made without the intention of making further runs, and it is not known how this may affect the thoroughness of the single-run when compared with the first of multiple runs. While this caveat does not apply to the data collected on the SACs in 2004, all being three-run estimates, it does apply to comparisons with previous SFCC data. However, even on the basis of the available comparison, which is likely to reduce the true variation, there is considerable scatter (Figure 18). Linear regression can aid prediction of likely 3-run estimates from 1-run estimates, and as a rough rule of thumb for both fry and parr the three-run minimum estimate can be estimated as 1.5 x the one-run minimum estimate (Table 29). Table 29. Linear regression equations predicting 3-run minimum density estimates from the first run. See Figure 18.

slope intercept R2 (%) n P< Salmon fry 1.53 ±0.03 2.97 95.3 108 0.000001 Salmon parr 1.45 ±0.04 1.53 92.7 108 0.000001

Figure 18. Relationship between the density estimates of a) salmon fry and b) salmon parr populations based on the first run of a 3-run fishing event, and those based on all three runs. a) b)

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n m

inim

um e

stim

ate

Salmon parr densities

010203040506070

0 10 20 30 40 50 60 70

1-run minimum estimate

3-ru

n m

inim

um e

stim

ate

76

We provide details of both Zippin depletion estimates and three-run minimum estimates. The former improve our understanding of numbers at individual sites, but where some sites cannot have depletion estimates made for them, it is not prudent to rely on them alone for summaries of the data across sites. This is because Zippin estimates cannot be calculated if no fish are caught, or if the distribution of fish caught between the runs is uneven. Since the likelihood of uneven declines (or even increases) of fish numbers between subsequent runs is higher where fewer fish are present, it follows that use of Zippin estimates to summarise collections of data where some data points could not be calculated entails a bias towards higher fish numbers. If population declines begin patchily rather than generally across a catchment, then relying on Zippin densities alone might delay detection of the decline. Therefore, where not all Zippin estimates could be calculated for a collection of sites we give both Zippin and 3-run minimum means in the text. Where all sites had Zippin estimates calculated we give only Zippin means. 4.3 The SACs We deal with each of the SACs individually, in each case providing some details of sites and electrofishings. These are necessarily summaries of the data that were collected, and full details of all the sampling and the sites are provided as electronic copies submitted to SNH with this report. 4.3.1 Berriedale and Langwell The Berriedale and Langwell SAC in Caithness is the second smallest of the SACs designated for salmon, covering an area of just 0.576km2. It incorporates the mainstems of the rivers Langwell and Berriedale which share a common confluence about 100m from the sea. This river is not presently part of the SFCC affiliation, and there is no available historical information on juvenile salmon densities. The Berriedale and Langwell were electrofished for the SAC monitoring exercise by the nearby Conon District Salmon Fishery Board. Six depletion sites and nine timed sites were fished (Map 3). No stocking was known to have taken place in the SAC. The rivers rise in upland sheep-grazing land and moorland, whilst there is broadleaved woodland in the lower reaches. 4.3.1.1 Depletion sites Site details, a summary of electrofishing results, and the presence/absence of salmon year classes and of trout, and mean sizes of the age classes for the six depletion sites are tabulated (Tables 30, 31, 32, 33). Almost all sites produced Zippin estimates for both fry and parr, with narrow confidence intervals. Mean Zippin density for fry was 29 100m-2 (range 7-58). Mean parr Zippin density was 23 (range 15-35) with one site having numbers too low for Zippin calculation (Figure 19). Salmon fry and parr were found at all the sites, with most sites having 1+ and 2+ fish. No older fish were caught. 1++ trout were found at all the sites, with trout fry being present at only two.

77

Map 3. Distribution of depletion and timed electrofishing sites on the Berriedale and Langwell SAC.

Table 30. Details of depletion sites, Berriedale & Langwell SAC.

Site Code

Easting Northing Altitude (m)

Channel name Principal local landuse

BD1 311600 923300 25 Berridale Broadleaved woodland LW1 309700 922200 50 Langwell Broadleaved woodland LW2 304100 924800 140 Langwell Heath/Moorland BD2 306800 930600 160 Berridale Broadleaved woodland LW3 300700 926150 210 Langwell Heath/Moorland BD3 298450 931500 255 Feith Gaineimh Mhor Heath/Moorland Table 31. Details of depletion electrofishing for 0+ and 1++ salmon, Berriedale & Langwell SAC. Site

Code Date Area

(m2) Mean wet width (m)

Zippin density 0+ (no 100m-2) +95% c.l.

3-run min 0+

(no 100m-2)

Zippin density 1++ (no 100m-2) +95% c.l.

3-run min S1++

(no 100m-2)

BD1 06/09/04 124.8 6.2 30.3+3.2 28.8 31.0+4.3 28.8LW1 05/09/04 81.5 3.3 7.4+0.4 7.4 18.4+0.4 18.4LW2 05/09/04 136.8 6.8 46.7+1.6 46.1 34.5+5.4 31.4BD2 06/09/04 123.2 6.2 16.7+1.7 16.2 17.2+0.8 17.0LW3 01/09/04 87.4 4.2 58.3+2.7 57.2 14.9+0.2 14.9BD3 22/08/04 110.0 5.5 15.1+1.9 14.5 N/a 0.9Mean 29.1 28.4 23.2 18.6s.d. 18.2 17.9 7.9 10.0

78

Table 32. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Berriedale & Langwell SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3++ 0+ 1++

BD1 YES YES YES no no YES LW1 YES YES YES no YES YES LW2 YES YES YES no no YES BD2 YES YES YES no no YES LW3 YES YES no no no YES BD3 YES no YES no YES YES Table 33. Fork length of salmon of different age classes, Berriedale & Langwell SAC. Site Code 0+ mean±s.d.

fork length (mm) no 0+ 1+ mean±s.d.

fork length (mm) no 1+ 2+ mean±s.d.

fork length (mm) no 2+

BD1 61.0±5.3 36 100.1±4.9 31 129.2± 5LW1 71.5±3.3 6 103.8±4.6 14 122.0 1LW2 62.4±3.5 63 101.2±8.4 38 128.6±4.8 5BD2 65.5±3.9 20 106.3±6.2 12 128.0±7.1 9LW3 56.5±3.9 50 99.7±7.2 13 n/a 0BD3 68.4±3.5 16 n/a 0 127.0 1 Figure 19. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Berriedale and Langwell rivers. Error bars show upper 95% confidence limit.

Berridale & Langwell SAC

0

10

20

30

40

50

60

70

BD1 LW1 LW2 BD2 LW3 BD3site name

num

ber (

100m

-2)

0+

1++

4.3.1.2 Timed sites Nine timed sites were fished in late August and early September, four on each of the Langwell and Berriedale Waters and one at their confluence. Details of the sites are shown in Table 34 with details of the catch per unit effort (CPUE) in Table 35.

79

Salmon fry were caught at all sites with 8/9 having 1+ fish and 6/9 having 2+ fish. Trout were present at all the sites (Table 36). Salmon, particularly fry, were caught at notably higher rates in the riffles. There was little obvious difference between capture rates in run and glide habitats, though very few fish were caught in the runs of the three uppermost sites. Figure 20 shows the distribution of fry and parr across sites and across flow types. Table 34. Details of timed electrofishing sites, Berriedale and Langwell SAC. Site Code Easting Northing River Altitude

(m) Principal Local Landuse

B&L5 311900 923800 B/L confluence 1 Broadleaved woodland B&L6 309200 922700 Langwell 65 Rough pasture B&L1 311300 927000 Berriedale 80 Broadleaved woodland B&L7 306100 923000 Langwell 120 Heath/Moorland B&L2 308800 929600 Berriedale 145 Rough pasture B&L3 304600 931300 Berriedale 190 Heath/Moorland B&L8 302600 924700 Langwell 200 Heath/Moorland B&L9 299700 925800 Langwell 225 Rough pasture B&L4 299400 931000 Berriedale 245 Heath/Moorland Table 35. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Berriedale & Langwell SAC. Each habitat type was fished for five minutes. Site code Survey date Salmon 0+ min-1 Salmon 1++ min-1

Glide Run Riffle Glide Run Riffle B&L5 05.09.04 0 0.2 1 0 1.4 1.6 B&L6 01.09.04 1 0.4 1.4 1 0.8 1 B&L1 06.09.04 2.2 1.8 6.6 1.2 1.6 1.6 B&L7 01.09.04 0.6 0.4 2.6 1.8 1.6 2.6 B&L2 22.08.04 1.6 1.6 4.4 0.2 0.8 0.4 B&L3 22.08.04 0 0 0.2 0.25 0.4 0.6 B&L8 01.09.04 1.6 0 4.2 2 1 2.4 B&L9 01.09.04 1 0 2.8 0.8 0.8 0.8 B&L4 22.08.04 1 0.2 1.8 0 0 0 Mean 1.00 0.51 2.78 0.81 0.93 1.22 s.d. 0.69 0.65 1.88 0.71 0.51 0.84 Table 36. Presence/absence of salmon year classes, and of trout at timed sites, Berriedale & Langwell SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3+ B&L5 YES YES YES no YES B&L6 YES YES YES no YES B&L1 YES YES no no YES B&L7 YES YES YES no YES B&L2 YES YES no no YES B&L3 YES YES YES no YES B&L8 YES YES YES no YES B&L9 YES YES YES no YES B&L4 YES no no no YES

80

Figure 20. Number of salmon caught per minute during timed electrofishing at sites on the Berriedale&Langwell, 2004. Five minutse of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++. Sites are arranged altitudinally, left lowest. a)

0

2

4

6

8

B&L5 B&L6 B&L1 B&L7 B&L2 B&L3 B&L8 B&L9 B&L4

all s

alm

on m

in-1

Glide

Run

Riff le

b)

0

2

4

6

8

B&L5 B&L6 B&L1 B&L7 B&L2 B&L3 B&L8 B&L9 B&L4

salm

on fr

y m

in-1

Glide

Run

Riff le

c)

0

2

4

6

8

B&L5 B&L6 B&L1 B&L7 B&L2 B&L3 B&L8 B&L9 B&L4

salm

on p

arr m

in-1

Glide

Run

Riff le

81

4.3.2 River Bladnoch The River Bladnoch SAC in South West Scotland covers an area of 3.0km2, and falls within the aegis of the Galloway Fisheries Trust, whose staff undertook the electrofishing of six depletion sites, and nine timed sites (Map 4). The major tributaries are the Tarf, the Water of Malzie, the Beoch Burn and the Black Burn (on both of which rivers spring-running fish are known to spawn). The river rises in the Galloway hills where extensive afforestation is thought to have adversely affected river acidity, particularly in parts of the Tarf and the upper mainstem. Some sections of the river have recently been stocked, and these were avoided in the site selection process, whilst others are somewhat canalised and unsuitable for electrofishing. In its lower sections the river flows through agricultural land. 4.3.2.1 Depletion sites Site details, a summary of electrofishing results, and the presence/absence of salmon year classes and of trout, and mean sizes of the age classes for the six depletion sites are tabulated (Tables 37, 38, 39, 40) Salmon were present at five of the six sites, although only one individual was caught at one of those five. Trout were present at five sites, being absent from SACB1 in which salmon were abundant. Densities of salmon fry ranged from 0-267 per 100m2, and from 0-56 per 100m2 for 1++ fish. Mean Zippin density for fry was 122 per 100m2, one of the highest recorded in this monitoring exercise, but this figure excludes the two sites with no, or very few, salmon, and the mean three-run minimum 80 per 100m2 estimate probably gives a truer picture (Table 38, Figure 21). Mean Zippin parr density across sites was 27 per 100m2 although once again the three-run estimate (18 per 100m2) is a more representative estimate. No salmon older than 1+ were recorded at any of the sites. Table 37. Details of depletion sites, Bladnoch SAC.

Site Code

Easting Northing Altitude (m)

Channel name Principal local landuse

B47 237200 554200 20 Malzie Burn Rough Pasture B45 236000 557800 20 Bladnoch Improved Grassland B30 231400 571400 80 Beoch Burn Conifer plantation SACB2 229200 572100 110 Bladnoch Tall herbs B7 225200 566800 120 Water of Tarf Conifer plantation SACB1 227700 560500 180 Water of Tarf Tall herbs Table 38. Details of depletion electrofishing for 0+ and 1++ salmon, Bladnoch SAC. Site

Code Date Area

(m2) Mean wet width (m)

Zippin density 0+ (no 100m-2) +95% c.l.

3-run min 0+

(no 100m-2)

Zippin density 1++ (no 100m-2) +95% c.l.

3-run min S1++

(no 100m-2)

B47 02/08/04 156.7 4.8 23.0+1.7 22.3 56.4+1.9 55.5B45 02/08/04 187.3 11.6 267.6+4.6 261.7 20.1+1.1 19.8B30 03/08/04 175.2 3.2 56.2+3.0 54.2 14.9+0.3 14.8SACB2 03/08/04 267.9 5.5 n/a 0.4 n/a 0B7 05/08/04 124.7 5.8 n/a 0 n/a 0SACB1 05/08/04 147.3 11.9 142.6+1.6 141.9 18.4+0.4 18.3Mean 122.3 80.1 27.5 18.1s.d. 94.5 94.5 16.8 18.6

82

Map 4. Distribution of depletion and timed electrofishing sites on the Bladnoch SAC.

Table 39. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Bladnoch SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3++ 0+ 1++ B47 YES YES no no YES YES B45 YES YES no no YES YES B30 YES YES no no YES YES SACB2 YES no no no YES YES B7 no no no no YES YES SACB1 YES YES no no no no

83

Table 40. Fork length of salmon of different age classes, Bladnoch SAC. Site Code 0+ mean±s.d.

fork length (mm) no 0+ 1+ mean±s.d.

fork length (mm) no 1+

B47 65±4 35 102±10 87B45 58±5 490 101±9 37B30 60±5 95 114+7 26SACB2 80 1 n/a 0B7 n/a 0 n/a 0SACB1 59±6 209 99±8 27 Figure 21. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Bladnoch. Error bars show upper 95% confidence limit. Arrows indicate three-run minimum density estimates.

Bladnoch SAC sites

0

50

100

150

200

250

300

B47 B45 B30 SACB2 B7 SACB1site name

num

ber (

100m

-2)

0+

1++

4.3.2.2 Historical data Figure 22 shows the available historical data for the sites from the Galloway Fisheries Trust. Only one-run minimum estimates are available for comparison, so they are compared with the first run of the three runs from this years data. In addition site SACB2 (Upper Bladnoch), where no fish were caught this year, has been electrofished informally in previous years, and fish have been either absent or very scarce (J.Ribbens, pers. comm.). Given the short time series, and the inherent variability in one-run estimates, there is little that can be concluded from these data. 4.3.2.3 Timed sites Nine timed electrofishing sites were distributed on the mainstem and tributaries of the system (Table 41, Map 4). Fry were relatively scarce in the glide habitats, and parr most commonly caught in riffles (Table 42). Salmon parr were present at all the sites, with fry absent from only one. Again, no salmon older than 1+ were found (Table 43). There was substantial variation between sites in capture rates (Figure 23), with low numbers (and no fry) at the site on the upper Bladnoch (where acidification is again the likely cause).

84

Figure 22. Electrofishing times series data for juvenile salmon 1998-2004, Bladnoch SAC. One-run minimum density estimates.

GFT/B45

020406080

100120140160180200

2001 2002 2003 2004year

one

run

min

imum

es

timat

e (n

o 10

0m-2)

S0+

S1++

GFT/B47

0

20

40

60

80

100

120

1997 1998 1999 2000 2001 2002 2003 2004year

one

run

min

imum

es

timat

e (n

o 10

0m-2)

S0+

S1++

GFT/B30

0

20

40

60

80

100

120

1997 1998 1999 2000 2001 2002 2003 2004year

one

run

min

imum

es

timat

e (n

o 10

0m-2)

S0+

S1++

GFT/B7

0

2

4

6

8

10

1997 1998 1999 2000 2001 2002 2003 2004year

one

run

min

imum

es

timat

e (n

o 10

0m-2)

S0+

S1++

Table 41. Details of timed electrofishing sites, Bladnoch SAC. Site Code Easting Northing River Altitude

(m) Principal Local Landuse

Bl3 239400 555400 Bladnoch 10 Rough pasture Bl7 234800 559700 Bladnoch 30 Rough pasture Bl2 234500 564700 Bladnoch 50 Rough pasture Bl1 232600 551900 Water of Malzie 70 Conifer plantation Bl5 298400 558700 Water of Tarf 70 Tall herbs Bl8 232300 567200 Black Burn 80 Tall herbs Bl4 232000 570800 Bladnoch 100 Tall herbs Bl6 225450 562600 Water of Tarf 100 Tall herbs Bl9 222300 562200 Drumpail Burn 110 Rough pasture

85

Table 42. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Bladnoch SAC. Each habitat type was fished for five minutes. Site code Survey date Salmon 0+ min-1 Salmon 1++ min-1

Glide Run Riffle Glide Run Riffle Bl3 07/09/04 3.6 1.2 3.8 0.8 2 2.4 Bl7 07/09/04 6 9.6 10.2 0.2 0.8 0.8 Bl2 06/09/04 0.8 3.2 1.6 0.6 0.6 1.4 Bl1 08/08/04 0.8 0.6 0 0.2 0.4 0 Bl5 30/08/04 5.2 4.6 5.6 0.2 1 0.2 Bl8 26/08/04 1.2 6 6.8 0.2 0.6 0.4 Bl4 06/08/04 0 0 0 0 0.4 0.2 Bl6 31/08/04 8 13 11.4 1.8 1.6 2 Bl9 26/08/04 0.2 1.4 0.2 0.4 0.6 1.2 Mean 2.52 3.47 3.64 0.39 0.43 0.71 s.d. 2.76 4.19 4.14 0.52 0.53 0.80 Table 43. Presence/absence of salmon year classes, and of trout at timed sites, Bladnoch SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3+ Bl3 YES YES no no YES Bl7 YES YES no no YES Bl2 YES YES no no no Bl1 YES YES no no YES Bl5 YES YES no no YES Bl8 YES YES no no no Bl4 no YES no no no Bl6 YES YES no no no Bl9 YES YES no no YES

86

Figure 23. Number of salmon caught per minute during timed electrofishing at sites on the Bladnoch, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++. Sites are arranged altitudinally, left lowest. a)

0

2

4

6

8

10

12

14

Bl3 Bl7 Bl2 Bl1 Bl5 Bl8 Bl4 Bl6 Bl9

all s

alm

on m

in-1

Glide

Run

Riff le

b)

0

2

4

6

8

10

12

14

Bl3 Bl7 Bl2 Bl1 Bl5 Bl8 Bl4 Bl6 Bl9

salm

on fr

y m

in-1

Glide

Run

Riff le

c)

0

2

4

6

8

10

12

14

Bl3 Bl7 Bl2 Bl1 Bl5 Bl8 Bl4 Bl6 Bl9

salm

on p

arr m

in-1

Glide

Run

Riff le

87

4.3.3. River Borgie Due in part to time constraints and in part to difficulties with access, the Kyle of Sutherland staff who were asked to fish this river in 2004 and 2005 were able to complete only one, timed, electrofishing site (Map 5). Details of this are given in tables 44, 45 and 46. No further analysis was conducted. Table 44. Details of the timed electrofishing site, Borgie SAC. Site Code Easting Northing River Altitude

(m) Principal Local Landuse

Borg 1 259727 944207 Borgie 117 Heather moorland Table 45. Salmon CPUE in glide, run and riffle habitats at a timed electrofishing site on the Borgie SAC. Each habitat type was fished for five minutes. Site code Survey date Salmon 0+ min-1 Salmon 1++ min-1

Glide Run Riffle Glide Run Riffle Borg 1 17/09/04 0.4 0.6 0.2 0 0.6 1.0 Table 46. Presence/absence of salmon year classes, and of trout at the timed site, Borgie SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3+ Borg 1 YES YES YES no no

88

Map 5. Location of the single timed electrofishing site on the Borgie SAC.

89

4.3.4. River Dee The Dee SAC incorporates all the major tributaries of the Dee, which range in character from montane to agricultural, covering an area of 24.5 km2. Eight depletion sites and 14 timed sites were electrofished (Map 6). The former were distributed throughout the major tributaties, and the latter focused mainly on the mainstem itself, this being too large for depletion fishings. No pollution or stocking events were known to have influenced any of the sites. The SAC sites were fished by staff of the Dee DSFB. 4.3.4.1 Depletion sites Site details and a summary of electrofishing results are tabulated (Tables 47 and 48). Zippin estimates for fry were calculable for six of the eight sites (in one case evidently due to low numbers), and for all of the sites for parr, although confidence limits were wide in some cases (Table 48, Fig 24). For fry Zippin densities ranged from 15-182 per 100m2 (mean 61±s.d.59), while for parr the range was 7-39 per 100m2 (mean 25±s.d.11). Both 0+ and 1+ fish were caught at all sites, with 2+ fish absent only from the site on the Tarland Burn, the lowest lying of the sites, on perhaps the most agricultural of the tributaries, and with the largest 1+ fish (Tables 49 and 50). Map 6. Distribution of depletion and timed electrofishing sites on the Dee SAC.

Table 47. Details of depletion sites, Dee SAC. Site Code Easting Northing Altitude (m) Channel name Principal local landuse 22/16/1 353336 798654 116 Tarland Burn Road 7/4/1 314100 781835 149 Clunie Water Heath/Moorland 27/2/2 352108 790300 255 Water of Feugh Heath/Moorland 10/7/2 322116 793856 295 Feardar Burn Rough pasture 21/4/3 340672 789601 385 Water of Tanar Heath/Moorland 4/7/1 309886 785132 461 Ey Burn Heath/Moorland 9/4/2 317916 800823 502 River Gairn Heath/Moorland 1/3/1 295685 787113 519 Geldie Burn Heath/Moorland

90

Table 48. Details of depletion electrofishing for 0+ and 1++ salmon, Dee SAC.

Site Code

Date Area (m2)

Mean wet

width (m)

Zippin density 0+ (no 100m-2) +95% c.l.

3-run min 0+

(no 100m-2)

Zippin density 1++ (no 100m-2) +95% c.l.

3-run min S1++

(no 100m-2)

22/16/1 27/07/04 58.8 4.6 11.9 17.1+0.9 17.07/4/1 31/08/04 68.9 8.4 14.6+0.8 14.5 27.9+12.7 23.227/2/2 09/02/04 57.3 6.0 30.0+16.0 24.4 39.3+10.8 34.910/7/2 27/08/04 66.7 6.1 181.5+7.0 176.8 39.7+2.7 39.021/4/3 31/08/04 82.5 5.1 32.2+19.7 24.2 7.1+13.2 4.84/7/1 16/08/04 114.7 11.0 0.9 25.9+5.3 23.59/4/2 08/03/04 114.6 11.2 90.2+15.5 76.8 23.5+4.1 21.81/3/1 17/08/04 109.1 10.8 19.2+9.5 15.6 16.0+3.9 14.7Mean 61.3 43.1 24.6 22.4s.d. 59.2 54.8 10.6 10.2 Table 49. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Dee SAC. Site Code Salmon age class present? Trout present?

0+ 1+ 2+ 3++ 0+ 1++ 22/16/1 YES YES no no YES YES 7/4/1 YES YES YES no no YES 27/2/2 YES YES YES no YES YES 10/7/2 YES YES YES no YES YES 21/4/3 YES YES YES no YES YES 4/7/1 YES YES YES no YES no 9/4/2 YES YES YES no YES YES 1/3/1 YES YES YES no no YES Table 50. Fork length of salmon of different age classes, Dee SAC.

Site Code

0+ mean±s.d. fork length

(mm)

no 0+

1+ mean±s.d. fork length

(mm)

no 1+

2+ mean±s.d. fork length

(mm)

no 2+

3+ mean±s.d. fork length

(mm)

no 3+

22/16/1 45.7±1.1 7 98.6±11.5 10 0 0 7/4/1 46.9±3.8 10 87.1±6.5 14 116.5±6.4 2 0 27/2/2 54.6±2.5 14 98.1±6.1 19 120.0 1 0 10/7/2 43.6±3.3 118 75.4±7.0 23 116.3±7.6 3 0 21/4/3 50.7±5.3 20 97.0±8.7 3 128.0 1 0 4/7/1 48.0 1 90.3±5.9 15 120.7±6.6 12 0 9/4/2 36.6±1.9 88 73.9±10.1 17 103.5±5.5 8 0 1/3/1 46.3±2.8 17 76.0±4.6 10 103.3±8.8 6 0

91

Figure 24. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Dee SAC. Error bars show upper 95% confidence limit. Arrows indicate where three-run minimum estimate is used. Sites are arranged altitudinally.

Dee

0

50

100

150

200

22/16/1 7/4/1 27/2/2 10/7/2 21/4/3 4/7/1 9/4/2 1/3/1site

num

ber 1

00m

-2 S0+

S1++

4.3.4.2 Timed sites Salmon were caught at each of the 14 timed sites, but there some gaps in year classes, with 2+ fish absent from the lower reaches of the mainstem. Some sites had very low numbers of fish however, particularly in the uppermost mainstem site, and in the acidic granite-geology of the Muick tributary, and on the Water of Dye where fry were absent (Tables 51, 52, 53). Fry were caught at the highest rates in run habitat, whilst parr were least frequently caught in glides (Figure 25). Table 51. Details of timed electrofishing sites, Dee SAC Site Code Easting Northing River Altitude (m) Principal Local Landuse De12 391829 802923 Dee 3 Broadleaved woodland De13 382863 798671 Dee 15 Scrub De11 375627 795988 Dee 35 Arable De10 363146 795967 Dee 88 Conifer plantation De8 354725 797934 Dee 118 Broadleaved woodland De9 347788 798237 Dee 145 Scrub De7 338683 796550 Dee 183 Improved grassland De1 364593 784018 Water of Dye 198 Heath/Moorland De6 324571 794503 Dee 261 Improved grassland De5 366666 796365 Beltie Burn 287 Broadleaved woodland De14 317853 791751 Dee 315 Improved grassland De3 329064 800425 Gairn 339 Heath/Moorland De2 302627 788667 Dee 400 Heath/Moorland De4 330942 785838 Muick 420 Heath/Moorland

92

Table 52. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Dee SAC. Each habitat type was fished for five minutes. Site code Survey date Salmon 0+ min-1 Salmon 1++ min-1

Glide Run Riffle Glide Run Riffle De12 10.09.04 0.8 3.2 1.6 0 0 0 De13 10.09.04 2 4 2.4 1 0 0.4 De11 10.09.04 2.6 2.6 2.2 0 0 0 De10 10.09.04 2.4 6.4 0.6 0.6 1 1 De8 09.09.04 1 3 3 0.2 0.4 1.6 De9 09.09.04 2.2 3.8 3.2 0.2 1.6 0.8 De7 09.09.04 4.2 2.6 2.8 1.6 0.6 0.6 De1 02.09.04 0 0 0 0 0.4 0.4 De6 09.09.04 2.8 4.8 0.8 1.4 0.8 1.4 De5 08.09.04 0.8 3.8 0.8 0.4 4.6 2.8 De14 09.09.04 3.2 2.6 3 2 1.2 1 De3 08.09.04 4.8 1.4 2.2 0.4 1.8 1.6 De2 17.08.04 0 0.2 0 0 0.2 0 De4 08.09.04 0 0 0 0 0 0 Mean 1.91 2.74 1.61 0.56 0.90 0.83 s.d. 1.49 1.79 1.17 0.65 1.18 0.79 Table 53. Presence/absence of salmon year classes, and of trout at timed sites, Dee SAC. Site Code Salmon age class present? Trout present?

0+ 1+ 2+ 3+ De12 YES YES no no no De13 YES YES no no YES De11 YES YES no no no De10 YES YES YES no no De8 YES YES YES no no De9 YES YES no no no De7 YES YES YES no no De1 no no YES no YES De6 YES YES no no YES De5 YES YES no no YES De14 YES YES no no no De3 no no YES YES YES De2 YES no no no no De4 YES no no no YES

93

Figure 25. Number of salmon caught per minute during timed electrofishing at sites on the Dee, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++ Sites are arranged altitudinally, left lowest. a)

0

2

4

6

8

De12 De13 De11 De10 De8 De9 De7 De1 De6 De5 De14 De3 De2 De4

all s

alm

on m

in-1

Glide

Run

Riff le

b)

0

2

4

6

8

De12 De13 De11 De10 De8 De9 De7 De1 De6 De5 De14 De3 De2 De4

salm

on fr

y m

in-1

Glide

Run

Riff le

c)

0

2

4

6

8

De12 De13 De11 De10 De8 De9 De7 De1 De6 De5 De14 De3 De2 De4

salm

on p

arr m

in-1

Glide

Run

Riff le

94

4.3.5 River Endrick The River Endrick SAC covers an area of 2.4km2, and incorporates only the mainstem of the Endrick itself. The Atlantic salmon is a secondary qualifying species for the SAC designation of the River Endrick. The SAC sites were fished by staff of the Forth Fisheries Foundation. 4.3.5.1 Depletion sites The mainstem of the Endrick was deemed too large for effective depletion electrofishing, thus sites fall in smaller tributaries that are outwith the SAC, and monitoring of the SAC proper is restricted to the Timed fishings (Map 7). Details of the depletion sites, a summary of electrofishing results, and the presence/absence of salmon year classes and of trout, and mean sizes of the age classes for the six depletion sites are tabulated (Tables 54, 55, 56, 57). Both salmon and trout were present at all six of the sites, but numbers varied markedly, and at the highest density site for fry (LT10) stocking was implicated. Densities of salmon fry ranged from 0-218 per 100m2 (mean of Zippin estimates 91±s.d 91, mean of 3-run minimum estimates 39±70 and from 0-10 per100m2 for parr (Zippin mean 5.0±3.8, three-run mean 3.7±3.0). Figure 26 shows the densities of salmon. The presence/absence of age classes shows marked patchiness (Table 56). No fish older than 2+ were caught. Table 54. Details of depletion sites, Endrick SAC.

Site Code

Easting Northing Altitude (m)

Channel name Principal local landuse

LT11 250250 684800 20 Carnock Burn, Blane Water Improved grassland LT12 254550 687700 50 Boquhan Burn Broadleaved woodland LT9 256900 679150 90 Blane Water Improved grassland LT10 244200 683100 90 Catter Burn Improved grassland LT13 258500 687350 100 Balglass Burn Improved grassland LT14 263400 685700 105 Gonachan Burn Rough pasture Table 55. Details of depletion electrofishing for 0+ and 1++ salmon, Endrick SAC. Site

Code Date Area

(m2) Mean wet

width (m)

Zippin density 0+ (no 100m-2 +95% c.l.)

3-run min 0+

(no 100m-2)

Zippin density 1++ (no 100m-2 +95% c.l.)

3-run min S1++

(no 100m-2)

LT11 16/09/04 131.9 4.9 28.7+7.1 25.0 2.3+0.5 2.3LT12 15/09/04 133.3 6.4 N/a 0.0 2.3+0.5 2.2LT9 13/09/04 133.0 3.8 N/a 1.5 N/a 3.0LT10* 16/09/04 99.2 5.1 218.7+19.4* 194.6 N/a 0.0LT13 15/09/04 144.3 3.5 N/a 0.0 N/a 5.5LT14 13/09/04 117.6 4.8 23.9+25.0 15.3 10.5+3.8 9.4Mean 90.5 39.4 5.0 3.7s.d. 90.7 70.0 3.8 3.0

* site stocked with fry

95

Map 7. Distribution of depletion and timed electrofishing sites on the Endrick SAC.

Table 56. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Endrick SAC. Site Code Salmon age class present? Trout present?

0+ 1+ 2+ 3++ 0+ 1++ LT11 YES YES no no YES YES LT12 no YES YES no YES YES LT9 YES YES no no YES YES LT10 YES no no no YES no LT13 no YES no no YES YES LT14 YES YES YES no YES YES Table 57. Fork length of salmon of different age classes, Endrick SAC. Site Code 0+ mean±s.d.

fork length (mm) no 0+ 1+ mean±s.d.

fork length (mm) no 1+ 2+ mean±s.d.

fork length (mm) no 2+

LT11 67.8±5.4 33 109.0±10.4 3 0LT12 0 95.0 1 123.0±1.4 2LT9 72.5±4.9 2 113.5±6.8 8 0LT10 54.2±5.5 193 0 0LT13 0 120.1±7.1 8 0LT14 68.0±4.0 18 109.9±6.5 10 132.0 1

96

Figure 26. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Endrick. Error bars show upper 95% confidence limit. Arrows indicate three-run mininimum density estimates.

Endrick Water

0

50

100

150

200

250

LT11 LT12 LT9 LT10 LT13 LT14site name

num

ber (

100m

-2)

S0+

S1++

4.3.5.3 Historical data Zippin or three-run minimum data from 2003 were available for all the Depletion sites (Figure 27). In all the cases where 95% confidence intervals are present, 2004 appears to have lower population densities than 2003. 4.3.5.4 Timed sites Salmon were caught at all nine of the timed electrofishing sites on the Endrick mainstem (Tables 58, 59, 60), though no parr were caught on the three lower most sites, where the river has a distinctly lowland character; trout were entirely absent from these sites, whilst present in all the others. No salmon older than 1+ were caught. Amongst the six higher sites on the mainstem, capture rates of salmon were very similar (around 4 per minute, Table 59). Both fry and parr were caught at the highest rates in riffle habitat, and lowest rates in the glides (Figure 28). Table 58. Details of timed electrofishing sites, Endrick SAC. Site Code Easting Northing River Altitude (m) Principal Local Landuse En9 248100 687100 Endrick 20 Improved grassland En7 250350 685700 Endrick 25 Improved grassland En8 249300 685900 Endrick 25 Improved grassland En6 252050 687800 Endrick 30 Rough pasture En5 255750 688300 Endrick 50 Rough pasture En4 258200 688500 Endrick 70 Broadleaved woodland En3 260800 687400 Endrick 80 Improved grassland En2 263250 686300 Endrick 100 Improved grassland En1 265700 686300 Endrick 150 Rough pasture

97

Figure 27. Time series data for juvenile salmon 2003-2004, Endrick SAC. Estimates of numbers are Zippin depletion estimates where available, but otherwise three-run minimum estimates (see y-axis labels). Error bars (Zippin estimates only) show 95% confidence intervals. Some stocking occurred affecting sites LT9, LT13 and LT14 in 2003, and sites LT10 and LT14 in 2004.

LT9

0

5

10

15

20

2003 2004

year

3-ru

n m

inim

um e

stim

ate

(num

ber 1

00m

-2)

S0+S1++

LT11

0

50

100

150

2003 2004

year

zipp

in e

stim

ate

(num

ber 1

00m

-2)

S0+S1++

L14

0

10

20

30

40

50

2003 2004

year

zipp

in e

stim

ate

(num

ber 1

00m

-2) S0+

S1++

LT10

0

50

100

150

200

250

2003 2004

year

3-ru

n m

inim

um e

stim

ate

(num

ber 1

00m

-2)

S0+S1++

LT12

0

5

10

15

20

2003 2004

year

3-ru

n m

inim

um e

stim

ate

(num

ber 1

00m

-2)

S0+S1++

LT13

0

5

10

15

20

25

2003 2004

year

3-ru

n m

inim

um e

stim

ate

(num

ber 1

00m

-2)

S0+S1++

98

Table 59. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Endrick SAC. Each habitat type was fished for five minutes. Site code Survey date Salmon 0+ min-1 Salmon 1++ min-1

Glide Run Riffle Glide Run Riffle En9 03.09.04 0.2 0 0.25 0 0 0 En7 03.09.04 2.6 3 1.6 0 0 0 En8 03.09.04 1.2 0 0.6 0 0 0 En6 03.09.04 1.2 2 2.8 1.2 0.2 0.8 En5 03.09.04 1 1.8 2.4 0.4 2 2 En4 23.08.04 0.6 3.2 4 0 0.2 0 En3 23.08.04 1 0.8 3.2 1.2 0.8 0.6 En2 17.08.04 1.2 2.4 4.4 0.4 0.4 1.6 En1 17.08.04 0 0.6 0.8 0 2.6 2.4 Mean 0.49 1.05 1.26 0.40 0.74 0.79 s.d. 0.71 1.16 1.42 0.48 0.90 0.90 Table 60. Presence/absence of salmon year classes, and of trout at timed sites, Endrick SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3+ En9 YES no no no no En7 YES no no no no En8 YES no no no no En6 YES YES no no YES En5 YES YES no no YES En4 YES YES no no YES En3 YES YES no no YES En2 YES YES no no YES En1 YES YES no no YES

99

Figure 28. Number of salmon caught per minute during timed electrofishing at sites on the Endrick, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++. Sites are arranged altitudinally, left lowest. a)

0

2

4

6

8

En9 En7 En8 En6 En5 En4 En3 En2 En1

all s

alm

on m

in-1

Glide

Run

Riff le

b)

0

2

4

6

8

En9 En7 En8 En6 En5 En4 En3 En2 En1

salm

on fr

y m

in-1

Glide

Run

Riff le

c)

0

2

4

6

8

En9 En7 En8 En6 En5 En4 En3 En2 En1

salm

on p

arr m

in-1

Glide

Run

Riff le

100

4.3.6 Grimersta Grimersta SAC, on the Isle of Lewis, is a complex of small, mostly low-gradient channels and lochans dominated by Loch Langavat, with a substantial, though short out-flow known as the Grimersta (Map 8). It covers an area of 14.6 km2, but the majority of this area is contributed by Loch Langavat. No attempt was made to quantify juvenile salmon use of the freshwater bodies. The SAC sites were fished by staff of the Western Isles Fisheries Trust. 4.3.6.1 Depletion sites Five depletion sites were fished. The channels were mostly rather small, and all were low-lying (Table 61) Fry densities ranged from 7-61 per 100m2 (Zippin mean 25.8±s.d.21.4, 3-run minimum estimate 19±17). Parr numbers ranged from 10-33 per 100m2 (Zippin mean 21.0±s.d.7.8 per 100m2). Confidence limits of the Zippin estimates were generally rather wide (Table 62, Fig 29). Salmon were present at all sites, but marked variation in growth rates made ageing of all the fish difficult. At one site the distribution of age classes is uncertain (Lan22) and the mean size of 1+ and 2+ fish at Lan06 could not be determined because of uncertainty about the age of fish (despite a substantial scale sampling effort). It is clear, however, that fry and parr were present at all the depletion sites (Tables 63, 64). Table 61. Details of depletion sites, Grimersta SAC. Site

Code Easting Northing Altitude

(m) Channel name Principal local

landuse Lan12 117599 917472 35 Allt Airigh Os Fid Heath/Moorland Lan14 115361 917562 35 Sandig burn Heath/Moorland Lan22 114773 911847 56 Langadale Heath/Moorland Lan06 117872 927209 60 March Burn between Scaliscro & Grimersta Heath/Moorland Lan24 114473 911016 65 Tributary of Langadale River Rough pasture

Table 62. Details of depletion electrofishing for 0+ and 1++ salmon, Grimersta SAC.

Site Code Date Area (m2)

Mean wet

width (m)

Zippin density 0+ (no 100m-2) +95% c.l.

3-run min 0+

(no 100m-2)

Zippin density 1++ (no 100m-2) +95% c.l.

3-run min S1++

(no 100m-2)

Lan12 08/10/04 86.3 2.7 7.1+1.2 7.0 17.8+1.9 17.4Lan14 08/10/04 85.0 3.9 10.1+7.6 8.2 9.6+1.1 9.4Lan22 08/09/04 193.1 6.1 24.9+14.4 17.6 32.7+20.3 21.8Lan06 18/10/04 49.9 1.7 10.0 19.3+12.4 16.0Lan24 08/09/04 22.7 0.9 61.1+25.8 52.9 25.8+47.9 17.6Mean 25.8 19.1 21.0 16.4s.d. 21.4 17.3 7.8 4.0

101

Map 8. Distribution of depletion and timed electrofishing sites on the Grimersta SAC.

Table 63. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Grimersta SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3++ 0+ 1++ Lan12 YES YES no no YES no Lan14 YES YES no no YES no Lan22 YES YES ? no no YES Lan06 YES YES YES no YES YES Lan24 YES YES no no YES YES

102

Table 64. Fork length of salmon of different age classes, Grimersta SAC.

Site Code 0+ mean±s.d. fork length

(mm)

no 0+

1+ mean±s.d. fork length

(mm)

no 1+

2+ mean±s.d. fork length

(mm)

no 2+

3+ mean±s.d. fork length

(mm)

no 3+

Lan12 36.8±2.3 6 74.2±7.8 9 104.7±13.0 6 0 Lan14 39.9±4.5 7 92.7±15.7 6 134.0±8.5 2 0 Lan22 46.5±2.9 34 n/a n/a n/a n/a 0 Lan06 42.8±1.5 5 n/a n/a n/a n/a 0 Lan24 41.0±3.7 12 74.0±7.6 4 0 0

Figure 29. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Grimersta SAC. Error bars show upper 95% confidence limit. Arrow indicates where three-run minimum estimate is used.

Grimersta

0

20

40

60

80

100

Lan06 Lan12 Lan14 Lan22 Lan24

site name

num

ber (

100m

-2) 0+

1++

4.3.6.2 Historical data Some data was available from previous SFCC fishings dating from 1997. This takes the form of one-run minimum density estimates, and so the first run from the electrofishing surveys detailed above is shown for comparison (Fig 30). Both upward and downward trends can be observed, but given the variability of the data the time series is too short for any conclusions to be drawn. 4.3.6.3 Timed sites Eight Timed sites were electrofished (Table 65). Banner nets were not used for the timed fishing on the Grimersta because of the local health and safety policy of the Western Isles Trust and Board, and band scoop-nets were employed. This may have affected the relative catch-efficiency in the different flow types. For sites Gr1 and Gr2 on the mainstem of the Grimersta, the water was reported as too fast for effective fishing with the equipment in use, and this seems to be reflected in the results (Table 66, Fig 31).

103

Figure 30. Electrofishing time series data for juvenile salmon 1998-2004, Grimersta SAC. One-run minimum density estimates. Lan03, Lan 04 and Lan21 are three formerly fished sites in the Grimersta catchment that were not part of the SAC monitoring programme, and no information was collected for them for 2004.

Lan12

0

10

20

30

40

50

60

1996 1998 2000 2002 2004 2006

year

one-

run

min

imum

es

timat

e

0+1++

Lan06

0

10

20

30

40

50

60

1996 1998 2000 2002 2004 2006

year

one-

run

min

imum

es

timat

e

0+1++

Lan14

0

10

20

30

40

50

60

1996 1998 2000 2002 2004 2006

year

one-

run

min

imum

es

timat

e

0+1++

Lan22

0

10

20

30

40

50

60

1996 1998 2000 2002 2004 2006

year

one-

run

min

imum

es

timat

e

0+1++

Lan24

0

10

20

30

40

50

60

1996 1998 2000 2002 2004 2006

year

one-

run

min

imum

es

timat

e

0+1++

Lan04

0

10

20

30

40

50

60

1996 1998 2000 2002

year

one-

run

min

imum

es

timat

e

0+1++

Lan03

0

10

20

30

40

50

60

1996 1998 2000 2002

one-

run

min

imum

es

timat

e

year

0+1++

104

Lan21

0

10

20

30

40

50

60

1997 1998 1999 2000 2001 2002

one-

run

min

imum

es

timat

e

year

0+1++

Salmon fry were present at all but one of the eight sites, whilst parr were absent from half the sites (Table 67). At the highest altitude site no fish were caught. Numbers of salmon caught per minute were rather low, averaging just over one per minute and there was no indication that fry or parr were more common in any particular flow type (Table 66, Fig 31). Table 65. Details of timed electrofishing sites, Grimersta SAC. Site Code

Easting Northing River Altitude (m)

Principal Local Landuse

Gr1 121102 929244 Grimersta 15 Heath/Moorland Gr2 120645 928523 Grimersta 25 Heath/Moorland Gr6 115258 917560 Sandig Burn 36 Rough pasture Gr7 115006 912132 Langadale 44 Heath/Moorland Gr4 117849 917418 Allt Airigh Os Fid 45 Heath/Moorland Gr5 115251 917494 Garry Burn 47 Rough pasture Gr8 114285 910640 Langadale 70 Heath/Moorland Gr3 117100 926866 Tributary to L Mohal Beag 75 Heath/Moorland Table 66. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Grimersta SAC. Each habitat type was fished for five minutes. Site code Survey date Salmon 0+ min-1 Salmon 1++ min-1

Glide Run Riffle Glide Run Riffle Gr1 18.10.04 0.7 0.6 0.0 0.7 0.8 0.0 Gr2 18.10.04 1.1 0.0 0.3 1.1 0.0 0.3 Gr6 08.10.04 0.6 0.0 0.4 0.8 0.8 0.2 Gr7 08.09.04 0.6 0.6 1.6 0.4 0.4 0.8 Gr4 08.10.04 0.0 0.4 0.0 0.6 1.0 1.2 Gr5 08.10.04 2.0 2.0 1.2 0.7 0.8 0.6 Gr8 08.09.04 0.6 0.6 0.4 0.4 1.4 1.6 Gr3 18.10.04 0.0 0.0 0.0 0.0 0.0 0.0 Mean 0.70 0.53 0.49 0.58 0.65 0.59 s.d. 0.60 0.62 0.56 0.30 0.46 0.54 Table 67. Presence/absence of salmon year classes, and of trout at timed sites, Grimersta SAC. Ageing of 1+ and 2+ parr was tentative. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3+ Gr1 YES no no no no Gr2 YES YES no no no Gr6 YES YES no no no Gr7 YES no no no YES Gr4 YES YES YES no YES Gr5 YES YES YES no YES Gr8 YES no no no YES Gr3 no no no no YES

105

Figure 31. Number of salmon caught per minute during timed electrofishing at sites on the Grimersta SAC, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++. Sites are arranged altitudinally, left lowest. a)

0

1

2

3

4

Gr1 Gr2 Gr6 Gr7 Gr4 Gr5 Gr8 Gr3

all s

alm

on m

in-1

Glide

Run

Riff le

b)

0

1

2

3

4

Gr1 Gr2 Gr6 Gr7 Gr4 Gr5 Gr8 Gr3

salm

on fr

y m

in-1

Glide

Run

Riff le

c)

0

1

2

3

4

Gr1 Gr2 Gr6 Gr7 Gr4 Gr5 Gr8 Gr3

salm

on p

arr m

in-1

Glide

Run

Riff le

106

4.3.7 Little Gruinard The Little Gruinard River, Wester Ross, flows out of the Fionn Loch which is the chief contributor to the 11.8km2 of the SAC. Most tributaries of the Fionn Loch are excluded from the designated area (Map 9) and some of these were fished here, given the few sites which it was possible to fish on the mainstem of the Little Gruinard itself. No pollution or stocking events were known to have affected the sites fished. The SAC sites were fished by the Wester Ross Fisheries Trust. . 4.3.7.1 Depletion sites Fishing efficiency was thought to be good at all seven of the sites electrofished. Sites on the Gruinard mainstem were in river island channels, ranging from 5-130m in altitude. Two smaller channels were also fished (Table 68). Salmon fry and parr were present at all the sites, and Zippin estimates could be calculated for each site, mostly with adequate confidence levels (Table 69, Figure 32). Fry Zippin densities ranged from 16-116 per 100m-2 (mean density 61.7±s.d.36.2), whilst parr ranged from 7-46 per 100m-2 (mean 34.6±s.d.15.5). 1+ fish were absent from one of the smaller channels, but on the mainstem 1+ and 2+ fish were present at all the sites, whilst 3+ fish were present at more than half of the sites (attaining a mean fork length of less than 100mm at the highest site) (Tables 70, 71). Table 68. Details of depletion sites, Little Gruinard SAC. Site

Code Easting Northing Altitude

(m) Channel name Principal local

landuse LGD8 194500 889900 5 Little Gruinard Heath/Moorland LGD13 194250 889150 50 Little Gruinard Heath/Moorland LGD11 194200 886700 95 Little Gruinard Heath/Moorland LGD6 194200 886400 105 Little Gruinard Heath/Moorland LGD4 194200 885400 130 Little Gruinard Heath/Moorland LGD15 194500 877850 170 Lochan Beannach Beag Burn Heath/Moorland LGD14 195300 879300 175 Garbh Allt Heath/Moorland

Table 69. Details of depletion electrofishing for 0+ and 1++ salmon, Little Gruinard SAC. Site

Code Date Area

(m2) Mean wet width (m)

Zippin density 0+ (no 100m-2) +95% c.l.

3-run min 0+

(no 100m-2)

Zippin density 1++ (no 100m-2) +95% c.l.

3-run min S1++

(no 100m-2)

LGD8 08/09/04 112.1 7.8 51.9+4.9 49.1 46.0+3.1 44.6LGD13 08/09/04 81.2 7.3 33.7+4.3 32.0 14.0+10.6 11.1LGD11 06/09/04 61.4 6.7 113.6+13.7 104.2 43.7+10.6 39.1LGD6 06/09/04 93.6 5.2 15.8+2.8 15.0 45.7+7.5 41.7LGD4 13/08/04 115.4 4.8 116.0+63.1 71.1 38.8+34.4 24.3LGD15 24/08/04 65.5 6.6 62.3+8.5 58.0 47.0+6.5 44.3LGD14 18/08/04 70.2 3.6 38.5+30.1 27.1 7.2+0.5 7.1Mean 61.7 50.9 34.6 30.3s.d. 36.2 28.1 15.5 14.9

107

Map 9. Distribution of depletion and timed electrofishing sites on the Little Gruinard SAC.

Table 70. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Little Gruinard SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3++ 0+ 1++ LGD8 YES YES YES YES YES no LGD13 YES YES YES no no no LGD11 YES YES YES no no YES LGD6 YES YES YES YES no YES LGD4 YES YES YES no no YES LGD15 YES YES YES YES no no LGD14 YES no YES YES YES no

108

Table 71. Fork length of salmon of different age classes, Little Gruinard SAC.

Site Code

0+ mean±s.d. fork length

(mm)

no 0+

1+ mean±s.d. fork length

(mm)

no 1+

2+ mean±s.d. fork length

(mm)

no 2+

3+ mean±s.d. fork length

(mm)

no 3+

LGD8 46.0±5.2 55 73.0±7.4 36 98.9±4.8 11 116.7±1.2 3LGD13 45.2±4.4 26 77.6±6.4 8 116.0 1 0LGD11 43.6±3.3 64 63.9±5.6 15 77.8±5.2 9 0LGD6 50.6±5.6 14 65.8±1.5 4 80.4±8.3 31 101.0±3.6 4LGD4 37.5±4.4 82 65.5±3.4 20 86.5±11.7 8 0LGD15 49.3±4.4 38 68.7±4.9 7 84.4±8.1 19 107.0±2.0 3LGD14 50.5±4.0 19 0 94.0 1 98.3±3.2 4 Figure 32. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Little Gruinard. Error bars show upper 95% confidence limit.

Little Gruinard

0

50

100

150

200

LGD4 LGD6 LGD8 LGD11 LGD13 LGD14 LGD15

site name

num

ber (

100m

-2) 0+

1++

4.3.7.2 Historical data Prior data are held by the SFCC for three of the Little Gruinard sites (Figure 33). Previous Zippin density estimates were only available for site, LGD8. Current and previous density estimates for this site have overlapping 95% confidence intervals, giving no indication of any changes in population size for either fry or parr.

109

Fig 33. Electrofishing time series data for juvenile salmon 1997-2004, Little Gruinard SAC. One-run minimum density estimates for LGD11 and LGD6, Zippin estimates for LGD8.

LGD8

01020304050607080

1996 1997 1998 1999 2000 2001 2002 2003 2004year

Zipp

in d

ensi

ty (n

o 10

0m-2

)

S0+S1++

LGD6

01020304050607080

1996 1997 1998 1999 2000 2001 2002 2003 2004year

one

run

min

imum

es

timat

e (n

o 10

0m-2)

S0+S1++

LGD11

01020304050607080

2000 2001 2002 2003 2004year

one

run

min

imum

es

timat

e (n

o 10

0m-2)

S0+S1++

4.3.7.3 Timed sites Timed fishings were conducted at 11 sites on the Little Gruinard, four on the mainstem, and seven on a range of smaller channels (Map 9, Table 72). No salmon were caught at one site (LGr5, outwith the SAC boundaries) and trout were present throughout except the lowest mainstem site (LGR1). At all the other sites both salmon fry and parr were present, with 2+ throughout, 1+ absent from two further sites, and 3+ fish present at the lowest mainstem site (Table 71). Catch rates for salmon averaged at about three per minute for run and riffle habitats, but only at about half that rate in the glides (Table 73, Figure 34).

110

Table 72. Details of timed electrofishing sites, Little Gruinard SAC. Site Code

Easting Northing River Altitude (m)

Principal Local Landuse

LGr1 194250 888550 Little Gruinard 60 Heath/Moorland LGr2 194300 887500 Little Gruinard 80 Heath/Moorland LGr3 194300 886100 Little Gruinard 115 Heath/Moorland LGr4 193960 884500 Little Gruinard 149 Heath/Moorland LGr10 198830 876290 Allt Bruthach an Easain 173 Rough pasture LGr5 192600 882750 Loch na Moine Buige Burn 174 Heath/Moorland LGr9 199300 875500 Allt a' Chiadhain 174 Rough pasture LGr11 195250 880750 Allt Glac Chaol 174 Rough pasture LGr8 193700 877750 Loch an Doire crionaich Burn 175 Heath/Moorland LGr7 193400 877800 Loch nan Clach Dubha Burn 185 Heath/Moorland LGr6 194350 876300 Strathan Buidhe Burn 195 Heath/Moorland Table 73. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Little Gruinard SAC. Each habitat type was fished for five minutes. Site code Survey date Salmon 0+ min-1 Salmon 1++ min-1

Glide Run Riffle Glide Run Riffle LGr1 08.09.04 0.8 2.6 4.6 0.4 1.8 1.4 LGr2 06.09.04 0.8 0.4 0 0.8 0.8 0.6 LGr3 13.08.04 2.6 1.8 1.4 0 0.8 1.2 LGr4 13.08.04 0.2 1.4 3 0.8 0.8 2.2 LGr10 18.08.04 0.6 1.4 0.4 0.6 0 0.2 LGr5 18.08.04 0 0 0 0 0 0 LGr9 18.08.04 1.8 3.4 1.4 0.2 0.2 0.8 LGr11 18.08.04 2.6 3.4 2.6 0.8 1 0.6 LGr8 24.08.04 1.8 4.8 4.4 0 0 0.2 LGr7 24.08.04 1 3 3.4 0.2 0.2 0 LGr6 24.08.04 0 3.4 2 1.8 1.8 1.6 Mean 1.11 2.33 2.11 0.51 0.67 0.80 s.d. 0.91 1.39 1.57 0.51 0.64 0.69 Table 74. Presence/absence of salmon year classes, and of trout at timed sites, Little Gruinard SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3+ LGr1 YES YES YES YES no LGr2 YES YES YES no YES LGr3 YES YES YES no YES LGr4 YES YES YES no YES LGr10 YES no YES YES YES LGr5 no no no no YES LGr9 YES YES YES no YES LGr11 YES YES YES no YES LGr8 YES no YES no YES LGr7 YES YES YES no YES LGr6 YES YES YES no YES

111

Figure 34. Number of salmon caught per minute during timed electrofishing at sites on the Little Gruinard, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++. Sites are arranged altitudinally, left lowest. a)

0

2

4

6

8

LGr1 LGr2 LGr3 LGr4 LGr10 LGr5 LGr9 LGr11 LGr8 LGr7 LGr6

all s

alm

on m

in-1

Glide

Run

Riff le

b)

0

2

4

6

8

LGr1 LGr2 LGr3 LGr4 LGr10 LGr5 LGr9 LGr11 LGr8 LGr7 LGr6

salm

on fr

y m

in-1

Glide

Run

Riff le

c)

0

2

4

6

8

LGr1 LGr2 LGr3 LGr4 LGr10 LGr5 LGr9 LGr11 LGr8 LGr7 LGr6

salm

on p

arr m

in-1

Glide

Run

Riff le

112

4.3.8 Moriston Too little information was obtained on the Moriston in 2004 to be worth commenting on. Accordingly the SFCC agreed to sample the Moriston SAC again in the late summer/early autumn of 2005, and the results from this second survey are reported here. The Moriston, a tributary of the Ness catchment, is a regulated river, with the SAC boundaries including only the mainstem from its outflow at Loch Ness up to the dam below Loch Cluanie (Map 10). There are two further dams within the SAC: a small dam some 4km kilometres below Loch Cluanie at Ceannacroc, which is thought to be impassable to salmon in all but exceptional flows (Colin Campbell pers. comm.) but is currently being removed; and the Dundreggan Reservoir dam (with a functioning fish pass), approximately 8km upstream of Loch Ness. The Moriston SAC covers an area of 1.9km2, draining a catchment that is principally mountain-moorland in character, with considerable coniferous afforestation. Moriston SAC sites were fished by staff of the Conon DSFB. No previous electrofishing data from the Moriston is held by the SFCC. 4.3.8.1 Depletion sites Six depletion sites were fished, but the size of the River Moriston made effective fishing impossible at all but two sites along its length, with the remaining sites being located on small tributaries of the river just outwith the SAC boundaries (Map 10, Table 74). These latter sites were all located close to the mainstem, and the channels separating the sites from the SAC boundary (ie the mainstem of the Moriston) were checked (by walk-over survey) to ensure that there were no physical barriers to returning adult salmon or sea trout. The two sites on the mainstem were both situated a sites where islands formed a channel small enough to fish. The 0+, 1+ and 2+ age-classes of salmon were present at four of the six sites (including the two located on the mainstem), but salmon were absent at the remaining two sites (Table 76). Where present, there was relatively little variation amongst densities of 1++ fish (mean of Zippin density estimates = 17.0±5.8 100m-2), similarly 1+ and 2+ fish at all sites were of a similar size (Table 75 and 77). There was typical variance amongst 0+ population densities across sites (mean of Zippin density estimates = 75.1±69.0 100m-2 (Table 75)), with one site (Mackenzie, on the main stem) having notably higher fry densities than the others (Fig 35). Table 74. Details of depletion sites, Moriston SAC.

Site Code Easting Northing Altitude (m) Channel name Principal local landuse Mor/Pho 232500 813700 115 Allt Phocaichain Rough Pasture Mackenzie 223700 811300 120 Moriston Broadleaved woodland Mor/Eoin 224975 811550 130 Allt an Eoin Rough Pasture Mor/Baile 227400 813000 130 Allt Baile nan Carne Rough Pasture Caena 222800 810800 140 Moriston Broadleaved woodland Mor/Bhlaraidh 238000 816400 170 Allt Bhlaraidh Broadleaved woodland

113

Table 75. Details of depletion electrofishing for 0+ and 1++ salmon, Moriston SAC.

Site Code Date Area (m2)

Mean wet

width (m)

Zippin density 0+ (no 100m-2) +95% c.l.

3-run min 0+

(no 100m-2)

Zippin density 1++ (no 100m-2) +95% c.l.

3-run min S1++

(no 100m-2)

Mor/Pho 22/08/05 84.80 4.24 20.3+10.8 16.5 20.3+10.8 16.5Mackenzie 31/08/05 126.00 6.30* 193.2+9.5 181.7 8.8+0.4 8.7Mor/Eoin 31/08/05 99.20 4.96 50.6+10.3 44.4 24.1+2.8 23.2Mor/Baile 22/08/05 81.60 4.08 0.0 0.0Caena 03/09/05 74.40 3.72* 36.3+28.4 25.5 15.0+1.3 14.8Mor/Bhlaraidh 22/08/05 97.50 3.90 0.0 0.0Mean 75.1 44.7 17.0 10.5s.d. 69.0 63.2 5.8 8.6

* sites located on part of main stem of the Moriston where it divides into several channels Map 10. Distribution of depletion and timed electrofishing sites on the Moriston SAC.

114

Table 76. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Moriston SAC.

Site Code Salmon age class present? Trout 0+ 1+ 2+ 3++ 0+ 1++

Mor/Pho YES YES YES no YES YES Mackenzie YES YES YES no YES no Mor/Eoin YES YES YES no YES YES Mor/Baile no no no no YES YES Caena YES YES YES no YES no Mor/Bhlaraidh no no no no no YES

Table 77. Fork length of salmon of different age classes, Moriston SAC. Site Code 0+

mean±s.d. fork length

(mm)

no 0+

1+ mean±s.d. fork length

(mm)

no 1+

2+ mean±s.d. fork length

(mm)

no 2+

3+ mean±s.d. fork length

(mm)

no 3+

Mor/Pho 58.7 14 89.1 12 112.5 2 n/a 0 Mackenzie 53.3 229 96.2 5 117.0 6 n/a 0 Mor/Eoin 56.4 44 89.7 20 109.7 3 n/a 0 Mor/Baile n/a 0 n/a 0 n/a 0 n/a 0 Caena 60.4 19 90.0 8 120.3 3 n/a 0 Mor/Bhlaraidh n/a 0 n/a 0 n/a 0 n/a 0

Figure 35. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Moriston SAC. Error bars show upper 95% confidence limit. Two sites had zero densities of salmon. Sites are arranged altitudinally, left lowest.

Moriston SAC

0255075

100125150175200

Mor/Pho

Macke

nzie

Mor/Bail

e

Mor/Eoin

Caena

Mor/Bhla

raidh

Site name

num

ber (

100m

-2) S0+

S1++

115

4.3.8.2 Timed sites Timed sites were distributed as evenly as possible along the length of the mainstem of the Moriston, all falling within the SAC boundaries (Map 10, Table 78). CPUE was generally rather low (mean for 0+ = 1.2 min-1, mean for parr 0.3 min-1 (Table 79)), but fish were caught at higher rates in riffle habitat (Fig 36). Sites Mor 8 and Mor 9 were upstream of the man-made barrier at Ceannacroc, and the absence of fish at these sites indicates that the barrier probably was impassable (Table 80). Table 78. Details of timed electrofishing sites, Moriston SAC, 2005. Site Code Easting Northing River Altitude

(m) Principal Local Landuse

Mor 1 242000 816500 Moriston 40 Broadleaved woodland Mor 2 239000 816975 Moriston 50 Coniferous plantation Mor 3 236175 815600 Moriston 90 Coniferous plantation Mor 4 232400 814200 Moriston 115 Rough Pasture Mor 5 231050 813550 Moriston 120 Broadleaved woodland Mor 6 227300 812600 Moriston 121 Broadleaved woodland Mor 7 225300 811800 Moriston 130 Rough Pasture Mor 8 221650 810000 Moriston 140 Coniferous plantation Mor 9 219000 809800 Moriston 170 Rough Pasture

Table 79. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Moriston SAC, 2005. Each habitat type was fished for five minutes. Site code Survey date Salmon 0+ min-1 Salmon 1++ min-1

Glide Run Riffle Glide Run Riffle Mor 1 03/09/2005 0 0 0 0.4 1 1.2Mor 2 03/09/2005 0 0 0.4 0.4 0 0.4Mor 3 03/09/2005 0.4 0 1 1.2 0.4 0.2Mor 4 03/09/2005 3 0.8 2.2 0.2 0 0.8Mor 5 03/09/2005 0.8 0 1.4 0.2 0.6 0.4Mor 6 03/09/2005 2.4 3 1.6 0 0 0Mor 7 22/08/2005 1 4 10.8 0.2 0 0.4Mor 8 23/08/2005 0 0 0 0 0 0Mor 9 23/08/2005 0 0 0 0 0 0

Mean 0.84 0.87 1.93 0.29 0.22 0.38s.d. 1.06 1.45 3.22 0.35 0.35 0.38 Table 80. Presence/absence of salmon year classes, and of trout at timed sites, Moriston SAC, 2005. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3+ Mor 1 no YES YES no YES Mor 2 YES no YES no No Mor 3 YES YES YES no YES Mor 4 YES YES YES no No Mor 5 YES YES no no YES Mor 6 YES no no no No Mor 7 YES YES YES no no Mor 8 no no no no YES Mor 9 no no no no YES

116

Figure 36. Number of salmon caught per minute during timed electrofishing at sites on the Moriston SAC in August/September 2005. Five minutes fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all juvenile salmon, b) 0+ salmon, and c) 1++ salmon. Sites are arranged altitudinally, left lowest. a)

0

2

4

6

8

10

12

Mor1 Mor2 Mor3 Mor4 Mor5 Mor6 Mor7 Mor8 Mor9

all s

alm

on m

in-1

Glide

Run

Riff le

b)

0

2

4

6

8

10

12

Mor1 Mor2 Mor3 Mor4 Mor5 Mor6 Mor7 Mor8 Mor9

salm

on fr

y m

in-1 Glide

Run

Riff le

c)

0

2

4

6

8

10

12

Mor1 Mor2 Mor3 Mor4 Mor5 Mor6 Mor7 Mor8 Mor9

salm

on p

arr m

in-1 Glide

Run

Riff le

117

4.3.9 Naver The Naver SAC, Sutherland, includes all the major tributaries but its areal extent of 10.7km2 is dominated by Loch Naver and Loch Choire (Map 11). No attempt has been made to characterise juvenile salmon use of these large freshwater bodies. The SFCC holds no previous information on juvenile salmon populations in the Naver catchment. There is no SFCC membership for the Naver, and no previous data of electrofishings is held by the SFCC. The SAC sites were fished by Kyle of Sutherland DSFB staff. 4.3.9.1 Depletion sites Since the size of the main river Naver precludes effective electrofishing all six depletion sites in the Naver SAC were arranged on the tributaries (Map 11, Table 81). Fry and 1+ salmon were present at all the sites, with 2+ fish absent from the highest altitude site on the River Vagastie (Table 83). Fry densities ranged from near to zero to 138 per 100m2 (mean Zippin density 67.2±s.d.46.4, three-run minimum mean 38±s.d.41). The range of parr densites was 11-45 (mean Zippin density 29.6±s.d.10.3) (Table 82, Figure 37). Table 81. Details of depletion sites, Naver SAC.

Site Code Easting Northing Altitude (m) Channel name Principal local landuse N/S/01 274199 954257 84 Skelpick Burn Heath/Moorland N/L/01 268331 944697 95 Langdale Burn Heath/Moorland N/MD/01 252336 936272 104 Meadie Burn Heath/Moorland N/AB/01 256360 934718 117 Altnaharra Burn Rough pasture N/MT/01 266899 931953 164 Mallart Heath/Moorland N/V/01 254520 930369 169 Vagastie Heath/Moorland

Table 82. Details of depletion electrofishing for 0+ and 1++ salmon, Naver SAC.

Site Code Date Area (m2)

Mean wet

width (m)

Zippin density 0+ (no 100m-2) +95% c.l.

3-run min 0+

(no 100m-2)

Zippin density 1++ (no 100m-2) +95% c.l.

3-run min S1++

(no 100m-2)

N/S/01 09/07/04 118.6 6.2 75.6+12.1 65.8 44.7±8.2 39.6N/L/01 09/07/04 111.2 5.6 44.3+18.0 34.2 32.7±7.6 28.8N/MD/01 09/08/04 114.8 6.6 N/a 0.9 23.1±3.3 21.8N/AB/01 09/08/04 136.7 6.4 11.4+1.7 11.0 33.4±11.3 27.1N/MT/01 09/10/04 143.4 9.3 137.3+18.7 115.1 11.2±4.1 9.8N/V/01 09/08/04 109.5 7.5 N/a 0.9 32.4±6.4 29.2Mean 67.2 38.0 29.6 26.0s.d. 46.4 41.3 10.3 9.0

118

Map 11. Distribution of depletion and timed electrofishing sites on the Naver SAC.

Table 83. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Naver SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3++ 0+ 1++ N/S/01 YES YES YES no YES no N/L/01 YES YES no no YES no N/MD/01 YES YES YES no YES YES N/AB/01 YES YES YES no YES YES N/MT/01 YES YES YES no YES YES N/V/01 YES YES YES no no YES

119

Table 84. Fork length of salmon of different age classes, Naver SAC.

Site Code 0+ mean±s.d. fork length

(mm)

no 0+

1+ mean±s.d. fork length

(mm)

no 1+

2+ mean±s.d. fork length

(mm)

no 2+

3+ mean±s.d. fork length

(mm)

no 3+

N/S/01 47.8±3.5 78 n/a n/a n/a n/a 0 N/L/01 49.1±5.6 38 84.5±7.2 32 0 0 N/MD/01 52.0 1 75.2±5.9 18 105.3±7.7 7 0 N/AB/01 42.3±3.9 15 71.0±8.7 28 103.4±5.3 9 0 N/MT/01 43.9±3.7 165 85.5±8.2 11 115.3±3.1 3 0 N/V/01 52.0 1 n/a n/a n/a n/a 0

Figure 37. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Naver SAC. Error bars show upper 95% confidence limit. Arrows indicate where three-run minimum estimate is used. NB sites L01 and AB01 were known to have been recently stocked.

Naver SAC

0

20

40

60

80

100

120

140

160

S01 L01 MD01 AB01 MT01 V01

Site name

Num

ber (

100m

-2) S0+

S1++

4.3.9.2 Timed sites Given the unavailability of depletion electrofishing as an option on the Naver itself, the timed sites were focused on the mainstem. Eight sites were fished (Table 85) Catch rates were over 2 per min in the riffles, but around 1 per min in the glides and runs (Table 86, Figure 38). Salmon fry and 1+ fish were caught at all the sites, whilst 2+ fish were recorded at all but the two lowermost mainstem sites (Table 87). No older salmon were reported. Trout, by contrast were absent from five of the sites.

120

Table 85. Details of timed electrofishing sites, Naver SAC. Site Code Easting Northing River Altitude (m) Principal Local Landuse Na1 271494 957394 Naver 6 Rough pasture Na2 272338 950649 Naver 30 Rough pasture Na3 271498 946802 Naver 43 Rough pasture Na4 269479 943825 Naver 53 Rough pasture Na5 267744 938838 Naver 67 Heath/Moorland Na7 256552 933443 Naver 96 Improved grassland Na6 266800 931850 Naver 156 Heath/Moorland Na8 254566 930700 Naver 175 Rough pasture Table 86. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Naver SAC. Each habitat type was fished for five minutes. Site code Survey date Salmon 0+ min-1 Salmon 1++ min-1

Glide Run Riffle Glide Run Riffle Na1 14/09/04 1 0.2 1.2 0.6 0.2 0 Na2 13/09/04 0.6 0.4 2.8 0 0.2 0.6 Na3 13/09/04 0.2 0 1.2 0.6 0.2 0.4 Na4 13/09/04 1 1.2 2.2 0.8 1.4 0.8 Na5 13/09/04 0.2 1.2 3.2 0 0.8 0.6 Na7 15/09/04 0 0 0.2 0.2 0 1 Na6 09/09/04 3.8 2 1.2 0.2 0.4 1.8 Na8 15/09/04 0.4 0 0.2 0 0.2 0.2 Mean 0.90 0.63 1.53 0.30 0.43 0.68 s.d. 1.15 0.70 1.04 0.30 0.43 0.52 Table 87. Presence/absence of salmon year classes, and of trout at timed sites, Naver SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3+ Na1 YES YES no no no Na2 YES YES no no no Na3 YES YES YES no no Na4 YES YES YES no YES Na5 YES YES YES no no Na7 YES YES YES no YES Na6 YES YES YES no YES Na8 YES YES YES no no

121

Figure 38. Number of salmon caught per minute during timed electrofishing at sites on the Naver, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++ Sites are arranged altitudinally, left lowest. a)

0

1

2

3

4

5

Na1 Na2 Na3 Na4 Na5 Na7 Na6 Na8

all s

alm

on m

in-1

Glide

Run

Riff le

b)

0

1

2

3

4

5

Na1 Na2 Na3 Na4 Na5 Na7 Na6 Na8

salm

on fr

y m

in-1

Glide

Run

Riff le

c)

0

1

2

3

4

5

Na1 Na2 Na3 Na4 Na5 Na7 Na6 Na8

salm

on p

arr m

in-1

Glide

Run

Riff le

122

4.3.10 North Harris North Harris is unique amongst SACs designated for salmon in that it is not a single catchment, but an entire estate with multiple catchments (Map 12). The principal rivers are the Meavaig, the Leosaid, the Ulladale and the Resort. Its remoteness presents health and safety issues and particular sampling difficulties, with access by boat often the most practicable. As a result the intended sampling programme was somewhat adjusted in the light of logistical considerations. The SAC sites were fished by staff of the Western Isles Fisheries Trust. 4.3.10.1 Depletion sites Site details, a summary of electrofishing results, and the presence/absence of salmon year classes and of trout, and mean sizes of the age classes for the eight depletion sites are tabulated (Tables 88, 89, 90, 91). Fry densities ranged from 1-30 per 100m2 (mean Zippin estimate 13.5±8.4), whilst parr ranged from 3-31 per 100m2 (mean Zippin estimate 18.9±s.d.9.7, mean 3-run estimate 15.8±s.d.9.5). In general confidence in the estimates was good, particularly for parr, but was very poor at two sites for fry (Mea02 and Leo07, see Table 89 and Figure 39). Large variation in growth rates presented problems in ageing fish, despite extensive scale-reading effort, and in some cases the age distributions at sites are uncertain (Table 90, 91). However, 0+ and 1+ fish were present at all the sites, with 2+ fish caught in at least half of the sites. Table 88. Details of depletion sites, North Harris SAC. Site

Code Easting Northing Altitude

(m) Channel name Principal local

landuse Hal01 103444 908431 15 Halladale Heath/Moorland Hal02 102900 908903 26 Halladale Heath/Moorland Mea04 109823 908339 45 Meavaig Heath/Moorland Leo04 105650 908990 50 Leosaid Heath/Moorland Hou04 108244 913914 57 Un-named trib. to Loch Ulladale Heath/Moorland Mea02 110263 910350 65 Meavaig Heath/Moorland Res04 110877 913334 77 Gleann Stuladail River, Resort Heath/Moorland Leo07 104524 910452 140 Leosaid Heath/Moorland

Table 89. Details of depletion electrofishing for 0+ and 1++ salmon, North Harris SAC. Site

Code Date Area

(m2) Mean wet width (m)

Zippin density 0+ (no 100m-2) +95% c.l.

3-run min 0+

(no 100m-2)

Zippin density 1++ (no 100m-2) +95% c.l.

3-run min S1++

(no 100m-2)

Hal01 10/09/04 76.9 3.3 17.0+0.5 16.9 18.3+0.9 18.2Hal02 10/09/04 89.7 2.3 29.6+8.9 25.6 26.3+2.3 25.6Mea04 26/10/04 135.2 5.3 5.3+0.6 5.2 7.1+1.7 6.7Leo04 10/09/04 206.1 4.6 1.1+0.7 1.0 3.2+1.2 2.9Hou04 09/10/04 68.0 2.5 16.7+12.7 13.2 19.3+1.1 19.1Mea02 11/10/04 78.3 2.9 18.8+58.8 8.9 26.9+6.8 24.3Res04 11/10/04 100.6 3.6 7.5+7.0 6.0 31.3+9.2 26.8Leo07 09/09/04 67.6 2.9 12.4+28.8 7.4 N/a 3.0Mean 13.5 10.5 18.9 15.8s.d. 8.4 7.3 9.7 9.5

123

Map 12. Distribution of depletion and timed electrofishing sites in the North Harris SAC

Table 90. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, North Harris SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3++ 0+ 1++ Hal01 YES YES ? no YES YES Hal02 YES YES ? no YES YES Mea04 YES YES YES no no YES Leo04 YES YES YES ? YES YES Hou04 YES YES YES no YES YES Mea02 YES YES YES ? no YES Res04 YES YES no no YES YES Leo07 YES YES no no YES YES

124

Table 91. Fork length of salmon of different age classes, North Harris SAC.

Site Code

0+ mean±s.d. fork length

(mm)

no 0+

1+ mean±s.d. fork length

(mm)

no 1+

2+ mean±s.d. fork length

(mm)

no 2+

3+ mean±s.d. fork length

(mm)

no 3+

Hal01 67.2±4.3 13 n/a n/a n/a n/a 0 Hal02 46.0±8.2 23 n/a n/a n/a n/a 0 Mea04 46.3±5.9 7 71.0±7.5 5 110.3±11.9 4 0 Leo04 58.0±8.5 2 n/a n/a n/a n/a n/a n/a Hou04 43.2±7.0 9 73.4±12.2 9 109.8±3.2 4 0 Mea02 59.9±10.2 7 n/a n/a n/a n/a n/a n/a Res04 45.2±8.0 6 83.9±10.4 17 106.5±5.9 10 0 Leo07 57.2±9.4 5 104.5±3.5 2 0 0 Figure 39. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites in the North Harris SAC. Error bars show upper 95% confidence limit. Arrow indicates where three-run minimum estimate is used.

North Harris SAC

0

10

20

30

40

50

60

70

80

Hal01 Hal02 Mea04 Leo04 Mea02 Hou04 Res04 Leo07

site name

num

ber (

100m

-2)

S0+

S1++

4.3.10.2 Historical data Limited previous one-run minimum density estimates were available for four of the sites. These are included here and are compared with the first run of the SAC samples for the sake of completeness (Figure 40). Variation in the data is too great and the time series too short for any conclusions to be drawn.

125

Figure 40. Electrofishing times series data for juvenile salmon 1997-2004, North Harris SAC. One-run minimum density estimates.

Housay04

0

5

10

15

1998 2000 2002 2004 2006

year

one-

run

min

imum

es

timat

e

S0+S1++

Meavaig02

0

5

10

15

1998 2000 2002 2004 2006

year

one-

run

min

imum

es

timat

e

S0+S1++

Leosaid04

0

1

2

3

4

5

1996 1998 2000 2002 2004 2006

year

one-

run

min

imum

es

timat

e

S0+S1++

Leosaid07

0

1

2

3

4

5

1996 1998 2000 2002 2004 2006

year

one-

run

min

imum

es

timat

e

S0+S1++

4.3.10.3 Timed sites Because of the local health and safety policy operated by the Western Isles Fisheries Trust and Fishery Board banner nets were not used in the North Harris estate, and hand-held scoop nets were employed instead. This may have affected the relative catch-efficiency in the different flow types. Site NHa3 on the Leosaid suffered from unintentional stocking from a commercial hatchery, and site NHa4 may have been affected by pollution from this hatchery (M.Bilsby, pers. comm.). It is not known to what extent this may have affected results. All the sites were relatively low-lying (Table 92) and surrounded by moorland. Salmon were present at all the sites. Once again, ageing salmon proved problematic because of overlapping sizes of year classes. However, 1+ salmon were present at all sites, and 2+ salmon at least six of the eight sites (Table 94). Salmon of 3+ were only found at one site, NHa8, on the Resort. Parr dominated the juvenile salmon population (Table 93, Figure 41) being caught at more than three times the rate of fry. Overall capture rates were 1.6 fish per minute, with most caught in the runs and fewest in the glides.

126

Table 92. Details of timed electrofishing sites, North Harris SAC. Site Code Easting Northing River Altitude (m) Principal Local Landuse NHa7 103066 912102 Ghlinne 5 Heath/Moorland NHa3 105315 907844 Leosaid 20 Heath/Moorland NHa2 109855 908703 Meavaig 45 Heath/Moorland NHa5 108612 915005 Ulladale 45 Heath/Moorland NHa4 105650 908465 Leosaid 50 Heath/Moorland NHa8 110665 913895 Resort 55 Heath/Moorland NHa6 107593 913928 Ulladale 70 Heath/Moorland NHa1 110296 910430 Uisleitir 80 Heath/Moorland Table 93. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the North Harris SAC. Each habitat type was fished for five minutes. Site code Survey date Salmon 0+ min-1 Salmon 1++ min-1

Glide Run Riffle Glide Run Riffle NHa7 09.09.04 0 1.2 1.0 0.8 0.2 0.4 NHa3 10.09.04 0.2 1.0 0.315 0.6 1.4 0.631 NHa2 26.10.04 0 0.2 0.421 1.263 2.2 1.684 NHa5 09.10.04 0.6 0.4 0.2 1.8 2.0 3.0 NHa4 10.09.04 0.6 0.6 0.4 2.6 2.6 2.0 NHa8 11.10.04 0.2 0.2 0.6 0.8 1.6 1.0 NHa6 09.10.04 0 0.6 0 0.2 0.6 0.2 NHa1 11.10.04 0.4 0.4 0.2 0.4 1.2 0.8 Mean 0.25 0.58 0.39 1.06 1.48 1.21 s.d. 0.24 0.34 0.28 0.75 0.75 0.89 Table 94. Presence/absence of salmon year classes, and of trout at timed sites, North Harris SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3+ NHa7 YES YES no no YES NHa3 YES YES YES no YES NHa2 YES YES YES no YES NHa5 YES YES YES no no NHa4 YES YES YES no YES NHa8 YES YES YES YES YES NHa6 YES YES ? no YES NHa1 YES YES YES no YES

127

Figure 41. Number of salmon caught per minute during timed electrofishing at sites in the North Harris SAC, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++. Sites are arranged altitudinally, left lowest. NB: scoop nets were used. Some unintentional stocking from commercial hatchery at NHa3. a)

0

1

2

3

4

NHa7 NHa3 NHa2 NHa5 NHa4 NHa8 NHa6 NHa1

all s

alm

on m

in-1

Glide

Run

Riff le

b)

0

1

2

3

4

NHa7 NHa3 NHa2 NHa5 NHa4 NHa8 NHa6 NHa1

salm

on fr

y m

in-1

Glide

Run

Riff le

c)

0

1

2

3

4

NHa7 NHa3 NHa2 NHa5 NHa4 NHa8 NHa6 NHa1

salm

on p

arr m

in-1

Glide

Run

Riff le

128

4.3.11 Oykel Only two sites were fished on the Oykel SAC in 2004. Accordingly the SFCC agreed to sample a further four on the Oykel in the late summer/early autumn of 2005. The results of both 2004 and 2005 are reported here. The River Oykel drains much of eastern Sutherland and flows into the Dornoch Firth via the Kyles of Sutherland. The SAC comprises all the major tributaries of the Oykel system and has an area of 9.64km2. The catchments it drains are principally moorland and bog in character, though extensive afforestation has occurred in parts. The SAC sites were fished by staff of the Kyle of Sutherland DSFB. 4.3.11.1 Depletion sites Six depletion sites were fished, distributed amongst the headwaters of the system. (Map 13, Table 95). A summary of electrofishing results, and the presence/absence of salmon year classes and of trout, and mean sizes of the age classes for the eight depletion sites are tabulated (Tables 96, 97, 98). Fry densities ranged from 0-85 per 100m2 (mean Zippin estimate 49.9±33.5, mean 3-run estimate 27.4±s.d.21.9), whilst parr ranged from 0-33 per 100m2 (mean Zippin estimate 21.4±s.d.10.4, mean 3-run estimate 15.0±s.d.9.1). With the exception of one site confidence limits in the density estimates for parr were tight, but confidence limits about fry density estimates were rather larger see (Table 96 and Figure 42). Table 95. Details of depletion sites, Oykel SAC.

Site Code Easting Northing Altitude (m)

Channel name Principal local landuse

CM/01 239389 912846 89 Abhainn Gleann na Muic Heather moorland OAS/01/05 231167 909576 150 Allt Strath Seasgaich Heather moorland OER/01 227433 898673 175 Rappach Heather moorland RO/02 232609 914197 196 Oykel Heather moorland OEM03 229604 892102 236 Mulzie Rough pasture CS02 235026 921637 241 Cassley Heather moorland OEM02 229807 889662 300 Mulzie Rough pasture

Table 96. Details of depletion electrofishing for 0+ and 1++ salmon, Oykel SAC.

Site Code Date Area (m2)

Mean wet

width (m)

Zippin density 0+ (no 100m-2) +95% c.l.

3-run min 0+

(no 100m-2)

Zippin density 1++ (no 100m-2) +95% c.l.

3-run min S1++

(no 100m-2)

CM/01 04/11/05 83.60 2.71 85.4+51.1 56.2 31.3+6.2 28.71OAS/01/05 31/10/05 47.33 3.33 82.6+82.5 50.7 18.4+6.3 16.90OER/01 03/11/05 200.70 11.28 3.0 6.9+1.5 6.48RO/02 01/11/05 188.72 8.86 29.6+25.3 18.0 33.1+53.3 15.37OEM03 09/09/04 120.56 5.48 4.3+1.1 4.1 9.7+4.9 8.29CS02 04/11/05 92.96 8.30 18.0+29.6 10.8 3.23OEM02 04/09/04 87.48 10.54 79.8+59.2 49.2 29.0+6.5 26.29Mean 49.9 27.4 21.4 15.0s.d. 33.5 21.9 10.4 9.1

129

Table 97. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Oykel SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3++ 0+ 1++ CM/01 YES YES no no YES YES OAS/01/05 YES YES no no YES no OER/01 YES YES YES no YES no RO/02 YES YES YES no no YES OEM03 YES YES no no YES YES CS02 YES YES YES no YES YES OEM02 YES YES YES no YES YES Map 13. Distribution of depletion and timed electrofishing sites in the Oykel SAC

130

Table 98. Fork length of salmon of different age classes, Oykel SAC.

Site Code 0+ mean±s.d. fork length

(mm)

no 0+

1+ mean±s.d. fork length

(mm)

no 1+

2+ mean±s.d. fork length

(mm)

no 2+

3+ mean±s.d. fork length

(mm)

no 3+

CM/01 46.8±5.9 47 86.1±10.1 24 N/a 0 N/a 0 OAS/01/05 56.0±5.9 24 101.6±7.8 8 N/a 0 N/a 0 OER/01 50.5±9.8 6 85.8±8.8 12 114.0 1 N/a 0 RO/02 49.4±10.9 34 86.3±12.2 25 116.0±4.2 4 N/a 0 OEM03 51.4±11.6 5 94.4±7.8 10 N/a 0 N/a 0 CS02 58.8±7.0 10 99.5±10.6 2 118.0 1 N/a 0 OEM02 47.4±4.0 43 100.7±11.8 22 128.0 1 N/a 0

Figure 42. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites in the Oykel SAC. Error bars show upper 95% confidence limit. Arrow indicates where three-run minimum estimates were used.

Oykel SAC

0

25

50

75

100

125

150

175

CM/01

OAS/01/05

OER/01

RO/02

OEM03CS02

OEM02

Site name

num

ber (

100m

-2)

0+1++

4.3.11.2 Historical data Population density estimates from a single previous electrofishing visits (in 2001 or 2002) were available for four of the sites, being a mixture of Zippin density estimates and three-run minimum estimates (see Fig 41). At all four sites the direction of change in population density was the same for both fry and parr. Populations were lower in 2005 than the previous estimate at three of the sites, but at the fourth site they were higher. No inferences can be drawn from these data.

131

Figure 43. Electrofishing times series data for juvenile salmon 2001-2005, Oykel SAC. Where error bars (95% c.l.) are shown the density estimates are by the Zippin method, otherwise they are three-run minimum density estimates.

OER/01

0102030405060708090

2001 2002 2003 2004 2005year

dens

ity e

stim

ate

(no

100m

-2)

S0+

S1++

CS02

0102030405060708090

2000 2001 2002 2003 2004 2005year

dens

ity e

stim

ate

(no

100m

-2)

S0+

S1++

CM/01

0102030405060708090

2001 2002 2003 2004 2005year

dens

ity e

stim

ate

(no

100m

-2)

S0+

S1++

RO/02

0102030405060708090

2001 2002 2003 2004 2005year

dens

ity e

stim

ate

(no

100m

-2)

S0+

S1++

4.3.11.3 Timed sites Seven timed sites were distributed throughout the Oykel catchment, (Map 13, Table 99). The numbers of fish that were caught were strikingly low at all sites and there is some concern about the comparability of these data with timed fishings on the other SACs (given that the depletion fishings do not seem to indicate that low numbers are typical of the Oykel system). Mean CPUE for fry and parr were 0.11 and 0.18 fish min-1 respectively (Table 100). Many gaps appear in the age classes found (Table 101), but these gaps may simply be the consequence of the very low number of individuals captured. At one site, Oyk 4, on the River Eileag, there were no salmon recorded. This site was also the only timed site where trout were reported (although these were present at all the depletion sites in the SAC). Table 99. Details of timed electrofishing sites, Oykel SAC, 2005. Site Code Easting Northing River Altitude (m) Principal Local Landuse Oyk 1 246189 904470 Cassley 51 Rough pasture Oyk 2 234601 903946 Oykel 65 Rough pasture Oyk 3 230949 898388 Rappach 140 Rough pasture Oyk 4 230716 907207 Eileag 151 Rough pasture Oyk 5 232754 912918 Oykel 162 Rough pasture Oyk 6 231922 894369 Mulzie 179 Rough pasture Oyk 7 237196 919801 Cassley 197 Heather moorland

132

Table 100. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Oykel SAC, 2005. Each habitat type was fished for five minutes. Site code Survey date Salmon 0+ min-1 Salmon 1++ min-1

Glide Run Riffle Glide Run Riffle Oyk 1 03.11.05 0 0 0 0 0.2 0Oyk 2 13.10.05 0.2 0.4 0.4 0 0.4 0.6Oyk 3 04.11.05 0 0.2 0.4 0.2 0 0Oyk 4 24.10.05 0 0 0 0 0 0Oyk 5 16.09.05 0.2 0.2 0.4 0.2 0.4 0.6Oyk 6 21.09.05 0 0 0 0.2 0.2 0.2Oyk 7 16.09.05 0 0 0 0.2 0.4 0Mean 0.06 0.11 0.17 0.11 0.23 0.20s.d. 0.09 0.15 0.20 0.10 0.17 0.26 Table 101. Presence/absence of salmon year classes, and of trout at timed sites, Oykel SAC, 2005. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3+ Oyk 1 no no YES no no Oyk 2 YES YES YES no no Oyk 3 YES no YES no no Oyk 4 no no no no YES Oyk 5 YES YES YES no no Oyk 6 no YES no no no Oyk 7 no YES YES no no

133

Figure 44. Number of salmon caught per minute during timed electrofishing at sites on the Oykel SAC (Sept-Nov 2005). Five minutes fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all juvenile salmon, b) 0+ salmon, and c) 1++ salmon. Sites are arranged altitudinally, left lowest. a)

0

1

2

Oyk1 Oyk2 Oyk3 Oyk4 Oyk5 Oyk6 Oyk7

all s

alm

on m

in-1

Glide

Run

Riff le

b)

0

1

2

Oyk1 Oyk2 Oyk3 Oyk4 Oyk5 Oyk6 Oyk7

salm

on fr

y m

in-1

Glide

Run

Riff le

c)

0

1

2

Oyk1 Oyk2 Oyk3 Oyk4 Oyk5 Oyk6 Oyk7

salm

on p

arr m

in-1

Glide

Run

Riff le

134

4.3.12 South Esk The SAC of the South Esk includes all the major, and some of the secondary tributaries of the South Esk system, occupying a total area of 4.79km2 (Map 14). The lower reaches run through agricultural land to the Montrose Basin, whilst the headwaters rise in the eastern Grampians. The SAC sites were initially fished by South Esk DSFB staff in 2004, but staff did not operate to full SFCC standards, and due to concerns about the commensurality of the data with data from other SACs, the river was electrofished a second time in August and September 2005 by fully accredited electrofishing teams (comprising staff from the Esk DSFB, the Clyde River Trust and FRS). Because the 2004 fishings were conducted following the tradition of electrofishing at the sites concerned however, these fishings still represent a continuum with the historical data on the South Esk, and so are included in the report as Appendix I. 4.3.12.1 Depletion sites Data on juvenile densities has been collected yearly by the South Esk Salmon Fishery Board since 1995 at five sites on the South Esk system, since 2001 at three further sites. We adopted as many of those sites that were concordant with SFCC protocols here however, of the 9 sites, only 3 were deemed fishable, and at one of those rising water meant that the fishing had to be abandoned after a single-pass (See Table 102 and Appendix I). A further 4 sites were selected on fishable channnels spread amongst the tributaries (Map 14). Fry and parr were present at all sites. Zippin fry densities ranged from 40 to 282 per 100m2 (Zippin mean 144.5±s.d.93.5), while parr densities ranged from 31 to 87 per 100m2 (Zippin mean 57.4±s.d.18.3) (Table 103, Figure 45). If the likely densities at site SEC (predicted from mean depletion rates) were included in the calculation of the mean these values dropped slightly (see footnote Table 103). 0+, 1+ and 2+ salmon age classes were present at all seven depletion sites, with 3+ salmon being additionally present at M1, the highest altitude site on the South Esk mainstem, where fish were notably slow growing. (Tables 104, 105). Table 102. Details of 2005 depletion sites, South Esk SAC.

Site Code Easting Northing Altitude (m) Channel name SEN1 352450 758500 43 Noran Water SEC 340100 759400 141 South Esk SEM1 338750 762350 177 Moy Burn SEU1 334150 762870 200 Uig Burn M1 328100 778100 282 South Esk SEP1 329250 767850 288 Prosen Water PW 325800 769900 391 Prosen Water

135

Map 14. Distribution of depletion and timed electrofishing sites on the South Esk SAC in 2005.

136

Figure 45. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the South Esk. Error bars show upper 95% confidence limit. N.B. at site SEC the density is estimated from a single fully stop-netted run (see Table 103 for details.

South Esk SAC

0

50

100

150

200

250

300

350

SEN1 SEC SEM1 SEU1 M1 SEP1 PW

site name

num

ber (

100m

2 ) 0+

1++

Table 103. Details of depletion electrofishing for 0+ and 1++ salmon, South Esk SAC in 2005. Site

Code Date Area

(m2) Mean wet width (m)

Zippin density 0+ (no 100m-2) +95% c.l.

3-run min 0+

(no 100m-2)

Zippin density 1++ (no 100m-2) +95% c.l.

3-run min S1++

(no 100m-2)

SEN1 27.09.05 52.5 5.2 263.6±16.0 249.4 49.5±0.4 49.5 SEC* 08.08.05 273.6 11.4 (31.0)* (20.5*) (29.8*) (21.0*) SEM1 27.09.05 47.9 6.1 106.7±5.7 104.4 71.8±7.0 68.9 SEU1 22.09.05 46.1 3.5 282.0±33.7 247.2 30.6±1.5 30.4 M1 08.08.05 240.8 7.1 40.3±17.8 27.4 45.8±18.2 32.0 SEP1 22.09.05 77.2 9.5 102.6±3.5 101.0 59.6±5.5 57.0 PW 07.08.05 135.7 5.9 71.6±31.6 49.4 87.0±5.5 82.5 Mean** 144.5 130.2 57.4 53.4 s.d. 93.5 88.5 18.3 18.7

*Only a single stop-netted run was available for SEC, values shown are estimated from average South Esk depletion rates using regression (R2 values of 97% for fry and 84% for parr). Single run densities (no 100m-2) were 13.2 and 11.0 for 0+ and 1++ respectively. ** The mean shown was calculated excluding site SEC. If SEC estimates are included then the 0+ Zippin density mean is 128.2±95.3 and the 1++ Zippin density mean is 53.4±19.5

137

Table 104. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, South Esk SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3++ 0+ 1++ SEN1 YES YES YES no YES YES SEC YES YES YES no YES YES SEM1 YES YES YES no YES YES SEU1 YES YES YES no YES YES M1 YES YES YES YES YES YES SEP1 YES YES YES no YES YES PW YES YES YES no YES YES Table 105. Fork length of salmon of different age classes, South Esk SAC.

Site Code

0+ mean fork

length±s.d. (mm)

no 0+

1+ mean fork

length±s.d. (mm)

no 1+

2+ mean fork

length±s.d. (mm)

no 2+

3+ mean fork

length±s.d. (mm)

no 3+

SEN1 54.8±4.8 131 94.1±6.6 18 114.4±7.5 8 0 SEC 50.7±3.9 36 94.3±8.4 28 121.5±3.5 2 0 SEM1 58.0+5.6 50 97.4±6.6 31 115.0±0 2 0 SEU1 52.4±4.8 115 93.3±9.5 13 114.0 1 0 M1 31.2±2.58 67 55.0±5.9 64 92.1±7.2 12 112.0 1 SEP1 53.1±3.6 78 90.0±8.7 39 117.6±6.5 5 0 PW 37.9±4.0 67 77.4±7.0 100 113.6±5.0 12 0 4.3.12.2 Historical data Figure 46 shows previous annual Zippin density estimates at three of the SAC sites, dating back to the mid 1990s. Data collected prior to 2005 were not collected in full concordance with SFCC protocols (in particular stop nets were not used) but are thought to have been collected using a constant methodology. Up till 2004 significant negative slopes can be fitted for both fry (P<0.006) and parr (P<0.05) at site SEC, Two further linear trends are suggested: a negative slope for parr at PW (P<0.1), and a positive slope (P<0.1) for fry at M1. In general noise was greater amongst fry. The data from 2005, collected to SFCC standards, appears to contrast markedly with data collected previously, with in general, higher numbers of fish being recorded than previously. This change is particularly marked amongst parr, and can perhaps be attributed to parr being more likely to escape from a non-netted depletion site than fry. It is clear that no direct comparison can be made between the data collected in 2005 and the earlier data.

138

Figure 46. Electrofishing time series data for juvenile salmon 1995-2005, for three sites on the South Esk SAC. All data are Zippin estimates with the exception of SEC for which likely Zippin densities have been estimated from a single run (see Table 103). Error estimates are only available from 2004 onwards, and show 95% confidence limits. Further historical data on the South Esk is shown in Appendix I. Data from 2005 collected to different standards than the previous data, and so no direct comparison can be made.

site M1

0

20

40

60

80

100

year

zipp

in d

ensi

ty (n

o100

m-2)

0+1++

site SEC

0

20

40

60

80

100

year

zipp

in d

ensi

ty (n

o100

m-2)

0+1++

site PW

0

20

40

60

80

100

120

year

zipp

in d

ensi

ty (n

o100

m-2)

0+1++

139

4.3.12.3 Timed sites Ten timed sites were fished on the South Esk, focusing principally on the large mainstem that could not be sampled in any other way (Table 106), and including a sampling site on less favourable agricultural burn within the SAC boundaries. Juvenile salmon were present at all but one of the sites (on the Noran Water), whilst 1+ fish were absent at a further site (where a 2+ individual was caught). 2+ salmon were recorded at half of the sites (Table 108). The absence of fish at site SEs2 on the Noran Water is notable given the large number of salmon, particularly fry, caught in the depletion site, SEN1, lower down the same river (Fig 45). No salmon were caught at SEs2 when it was fished in 2004. No known obstacles to salmon migration exist between SEs2 and SEN1, and the habitat at the site appears to be suitable for salmon. However SEs2 is not far downstream of impassable falls, and it may be that there is not suitable spawning habitat upstream. Overall throughout the South Esk catch rates were high, with the average rate lowest in glides (3.44 salmon min-1) compared with the average rates of 7.08 and 8.46 salmon min-1 in the runs and riffles respectively (Table 107, Figure 47). These high levels of fish caught in the timed fishings contrast very markedly with the low levels caught in 2004 (see Appendix I) Table 106. Details of timed electrofishing sites, South Esk SAC, 2005. Site Code Easting Northing River Altitude (m) Principal Local Landuse SEs10 364180 758240 South Esk 4 Conifer plantation SEs9 356780 758720 South Esk 26 Improved grassland SEs8 349930 756770 South Esk 56 Arable SEs1 345100 754500 Lemno Burn 60 Arable SEs11 342090 757880 South Esk 84 Tall herbs SEs2 346510 760940 Noran Water 140 Scrub SEs7 337360 765100 South Esk 206 Improved grassland SEs6 333870 764260 Prosen Water 208 Improved grassland SEs3 332560 772780 South Esk 230 Arable SEs5 327220 768810 Prosen Water 326 Rough pasture Table 107. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the South Esk SAC, 2005. Each habitat type was fished for five minutes. Site code Survey date Salmon 0+ min-1 Salmon 1++ min-1

Glide Run Riffle Glide Run Riffle SEs10 06.08.05 6 15 23.6 0 0.2 1.2SEs9 06.08.05 9.6 19.6 16.4 1.6 1 0.2SEs8 06.08.05 1.6 7.6 5.2 0.8 0.8 3.4SEs1 06.08.05 0 0.6 0.8 0 0 0.4SEs11 07.08.05 1 7.8 3 0 0.4 0.4SEs2 07.08.05 0 0 0 0 0 0SEs7 07.08.05 0.8 3.8 8.4 1.2 1 1.6SEs6 07.08.05 6.8 3.4 5.4 0.4 0.2 2.2SEs3 07.08.05 2 2 4.2 0.2 1.6 2.6SEs5 07.08.05 0 0.8 0.8 2.4 5 4.8Mean 2.78 6.06 6.78 0.66 1.02 1.68s.d. 3.42 6.60 7.61 0.83 1.49 1.58

140

Table 108. Presence/absence of salmon year classes, and of trout at timed sites, South Esk SAC, 2005. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3+ SEs10 YES YES no no no SEs9 YES YES YES no YES SEs8 YES YES no no YES SEs1 YES no YES no YES SEs11 YES YES no no YES SEs2 no no no no YES SEs7 YES YES YES no YES SEs6 YES YES no no YES SEs3 YES YES YES no no SEs5 YES YES YES no YES

141

Figure 47. Number of salmon caught per minute during timed electrofishing at sites on the South Esk in August 2005. Five minutes fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all juvenile salmon, b) 0+ salmon, and c) 1++ salmon. Sites are arranged altitudinally, left lowest. a)

0

5

10

15

20

25

SEs10 SEs9 Ses8 SEs1 SEs11 SEs2 SEs7 SEs6 SEs3 SEs5

all s

alm

on m

in-1

Glide

Run

Riff le

b)

0

5

10

15

20

25

SEs10 SEs9 Ses8 SEs1 SEs11 SEs2 SEs7 SEs6 SEs3 SEs5

salm

on fr

y m

in-1

Glide

Run

Riff le

c)

0

5

10

15

20

25

SEs10 SEs9 Ses8 SEs1 SEs11 SEs2 SEs7 SEs6 SEs3 SEs5

salm

on p

arr m

in-1

Glide

Run

Riff le

142

4.3.13 Spey The Spey SAC incorporates all the major tributaries and a number of smaller burns, giving an overall area of 57.3km2, the second largest of the SACs designated for salmon (Map 15). No pollution or stocking events were known to have affected any of the sites fished. The SAC sites were fished by staff of the Spey Research Trust. 4.3.13.1 Depletion sites Eleven depletion sites were fished in August and September 2004, located throughout the major tributaries of the Spey (Map 15, Table 109). Although not mainstem sites, many of these sites are on substantial channels, even at high altitudes (Table 110). The range of fry densities recorded was 0-189 per 100m2 (Zippin mean density 54.3±s.d.57.9, three-run minimum mean 35.2±sd49.5). Parr densities ranged from around 5 to 50 per 100m2 (Zippin mean 28.7±sd18.4, three-run minimum mean 21.0±sd16.6) (Table 110). Confidence limits for the Zippin estimates varied from good to very poor (Figure 48). Salmon fry were present at all of the sites. 0+ fish were absent from one site, but 1+ and 2+ fish were present throughout, whilst 3+ fish were found at four of the sites (Table 111). Table 109. Details of depletion sites, Spey SAC. Site Code Easting Northing Altitude (m) Channel name Principal local landuse F3 336150 839800 190 Fiddich Broadleaved woodland A2 323500 824800 275 Avon Livet Broadleaved woodland Tr1 267600 791400 285 Truim Rough pasture Fe2 285250 801300 290 Feshie Allt Ruadh Conifer plantation N2 302100 814450 310 Nethy Natural conifers T7 276600 793750 320 Tromie Heath/Moorland Dr2 298450 808450 360 Druie Allt Mor Natural conifers A23 316300 811800 365 Avon Heath/Moorland C2 265000 798400 373 Calder Rough pasture A13 315500 807450 460 Avon Loin Burn Heath/Moorland D9 276600 812200 480 Dulnain Heath/Moorland Table 110. Details of depletion electrofishing for 0+ and 1++ salmon, Spey SAC.

Site Code

Date Area (m2)

Mean wet

width (m)

Zippin density 0+ (no 100m-2) +95% c.l.

3-run min 0+

(no 100m-2)

Zippin density 1++ (no 100m-2) +95% c.l.

3-run min S1++

(no 100m-2)

F3 31/08/04 153.5 11.0 36.9+4.9 33.9 47.7+6.6 43.0A2 13/09/04 106.4 10.1 188.5+10.7 176.7 60.7+3.1 59.2Tr1 07/09/04 188.1 17.1 1.2+0.8 1.1 14.0+0.8 13.8Fe2 06/09/04 89.6 6.4 N/a 3.3 16.9+11.1 13.4N2 24/08/04 84.8 5.9 42.0+10.4 36.5 49.6+41.0 31.8T7 18/08/04 206.6 23.0 1.5+0.3 1.5 21.5+106.8 6.3Dr2 01/09/04 85.5 5.7 N/a 0.0 42.7+41.0 26.9A23 14/09/04 110.8 15.8 13.1+4.2 11.7 14.5+3.0 13.5C2 09/09/04 89.6 7.2 68.1+11.8 60.3 7.9+0.9 7.8A13 14/09/04 138.2 7.7 83.0+38.4 55.0 11.0+0.8 10.9D9 25/08/04 157.0 13.1 N/a 7.0 N/a 3.8Mean 54.3 35.2 28.7 21.0s.d. 57.9 49.5 18.4 16.6

143

Map 15. Distribution of depletion and timed sites on the Spey SAC.

Table 111. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Spey SAC. Site Code Salmon age class present? Trout present?

0+ 1+ 2+ 3++ 0+ 1++ F3 YES YES YES no YES YES A2 YES YES YES no YES YES Tr1 YES YES YES YES YES YES Fe2 YES YES YES no YES YES N2 YES YES YES no YES YES T7 YES YES YES no YES YES Dr2 no YES YES no YES YES A23 YES YES YES YES no YES C2 YES YES YES no YES YES A13 YES YES YES YES YES YES D9 YES YES YES YES no YES

144

Figure 48. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Spey SAC. Error bars show upper 95% confidence limit. Arrow indicates where three-run minimum estimate is used.

Spey SAC

0

25

50

75

100

125

150

175

200

F3 A2 Tr1 Fe2 N2 T7 Dr2 A23 C2 A13 D9Site name

Num

ber (

100m

-2) S0+

S1++

4.3.13.2 Historical data All the depletion sites had been previously fished on either three or four occasions dating back to around 1997, but in all cases only one-run minimum density estimates were available, and thus these were compared with the first run of the present fishings (Figure 49). On the basis of these data, it appeared that relatively low numbers of salmon parr were caught in 2004. Compared to the first data point in each series, the 2004 value is lower in all eleven cases, having also declined from the 2003 value in 10 of 11 cases. For fry 10 of eleven sites had lower densities than was reported in the last occasion the sites were fished. While 2004 thus looks like a ‘bad’ year in terms of juvenile population densities, it is not yet possible to determine whether this represents a general temporal decline in juvenile salmon numbers on the Spey, or merely a single poor year. 4.3.13.3 Timed sites Sixteen of the programmed 18 timed sites were surveyed, with fishings lasting into October, having been affected by high flow levels. Sites were spread throughout the mainstem (two not fished), major tributaries and some of the smaller, lower-lying channels (Map 15, Table 112). Mean catch rates of salmon per minute were 0.99 min-1 in the glides, and at 1.94 and 1.93 min-1 in the runs and riffles respectively (Table 113), but there was considerable variation in catch rates between the sites (Fig 50). Salmon fry were present at all 16 sites, whilst parr were present at 14 of the 16 fished (1+ at 13, and 2+ at eight sites). No 3+ fish were caught (Table 114).

145

Figure 49. Electrofishing time series data for juvenile salmon 1996-2004, for various sites in the Spey SAC, one-run minimum density estimates.

site A13

010

2030

4050

6070

8090

100

year

one

run

min

imum

es

timat

e

0+1++

site A2

0

20

40

60

80

100

120

140

year

one

run

min

imum

es

timat

e

0+1++

site A23

0

10

20

30

40

50

year

one

run

min

imum

es

timat

e

0+1++

site C2

0

10

20

30

40

50

year

one

run

min

imum

es

timat

e0+1++

site Dr2

0

10

20

30

40

50

year

one

run

min

imum

es

timat

e

0+1++

site D9

0

5

10

15

20

25

year

one

run

min

imum

es

timat

e

0+1++

146

Figure 49 (continued)

site F3

0

50

100

150

200

250

year

one

run

min

imum

es

timat

e

0+1++

site Tr1

0

5

10

15

20

25

year

one

run

min

imum

es

timat

e

0+1++

site Fe2

0

10

20

30

40

50

year

one

run

min

imum

es

timat

e

0+1++

site N2

0

10

20

30

40

50

year

one

run

min

imum

es

timat

e0+1++

site T7

0

5

10

15

20

25

year

one

run

min

imum

es

timat

e

0+1++

147

Table 112. Details of timed electrofishing sites, Spey SAC. Site Code Easting Northing River Altitude

(m) Principal Local Landuse

Sp4 317482 837729 Pitchroy Burn 140 Broadleaved woodland Sp10 318578 830290 Livet 190 Broadleaved woodland Sp3 305249 829078 Milton Burn 195 Rough pasture Sp1 300456 821544 Allt Mhor (Nethy) 210 Broadleaved woodland Sp5 275978 799801 Spey 225 Rough pasture Sp2 287845 810840 Allt na Criche 230 Broadleaved woodland Sp6 255225 793926 Spey 245 Heath/Moorland Sp8 334808 836389 Fiddich 260 Rough pasture Sp11 302232 816344 Nethy 290 Natural conifers Sp12 285422 820253 Dulnain 300 Rough pasture Sp13 295100 810400 Luineag 310 Natural conifers Sp16 265191 797264 Truim 330 Heath/Moorland Sp7 317529 819133 Conglass 335 Rough pasture Sp15 275229 792167 Tromie 340 Heath/Moorland Sp9 316315 814221 Avon 345 Rough pasture Sp14 284850 794150 Feshie 345 Natural conifers Table 113. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Spey SAC. Each habitat type was fished for five minutes. Site code Survey date Salmon 0+ min-1 Salmon 1++ min-1

Glide Run Riffle Glide Run Riffle Sp4 12/10/04 0 0.8 1.2 0.4 0.4 0.8 Sp10 15/09/04 2 4 2.4 1.2 0.2 0.4 Sp3 12/10/04 0 0.4 0.6 0.2 0.6 1 Sp1 20/10/04 0.6 0.8 1.8 0 0.6 1 Sp5 29/09/04 2.8 3.6 3.6 0.2 0.2 0.2 Sp2 11/10/04 0 0.4 0.4 0 0 0 Sp6 29/09/04 0 0.2 0 0 0 0 Sp8 31/08/04 2.2 3.4 3.2 0 1.6 3.2 Sp11 24/08/04 0.4 1.2 0.4 0 0.2 0.6 Sp12 01/09/04 0.2 1.2 0.8 0.8 1.2 0.6 Sp13 01/09/04 0.6 1 0.4 0 0.4 1.78 Sp16 16/09/04 1 1.4 1.2 0 0.2 0.4 Sp7 14/10/04 1.4 4.8 2.2 0.4 0.4 0.4 Sp15 18/08/04 0.2 0.4 0.4 0.2 0 0.2 Sp9 14/09/04 0.2 0.8 0.8 0.4 0 0 Sp14 10/09/04 0.2 0.2 0.2 0.2 0.4 0.6 Mean 0.74 1.54 1.23 0.25 0.40 0.70 s.d. 0.87 1.46 1.07 0.33 0.43 0.79

148

Table 114. Presence/absence of salmon year classes, and of trout at timed sites, Spey SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3+ Sp4 YES YES YES no YES Sp10 YES YES YES no YES Sp3 YES YES no no YES Sp1 YES YES YES no YES Sp5 YES YES no no no Sp2 YES no no no YES Sp6 YES no no no no Sp8 YES YES YES no YES Sp11 YES YES YES no YES Sp12 YES YES no no no Sp13 YES YES no no no Sp16 YES no YES no YES Sp7 YES YES YES no YES Sp15 YES YES no no YES Sp9 YES YES no no YES Sp14 YES YES YES no YES

149

Figure 50. Number of salmon caught per minute during timed electrofishing at sites on the Spey, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++ Sites are arranged altitudinally, left lowest. a)

0

2

4

6

8

Sp4 Sp10 Sp3 Sp1 Sp5 Sp2 Sp6 Sp8 Sp11 Sp12 Sp13 Sp16 Sp7 Sp15 Sp9 Sp14

all s

alm

on m

in-1

Glide

Run

Riff le

b)

0

2

4

6

8

Sp4 Sp10 Sp3 Sp1 Sp5 Sp2 Sp6 Sp8 Sp11 Sp12 Sp13 Sp16 Sp7 Sp15 Sp9 Sp14

salm

on fr

y m

in-1

Glide

Run

Riff le

c)

0

2

4

6

8

Sp4 Sp10 Sp3 Sp1 Sp5 Sp2 Sp6 Sp8 Sp11 Sp12 Sp13 Sp16 Sp7 Sp15 Sp9 Sp14

salm

on p

arr m

in-1

Glide

Run

Riff le

.

150

4.3.14 Tay The River Tay is the largest of the SACs designated for salmon, covering an area of almost 95km2, and accordingly our sampling programme allocated more sites to the Tay than any other SAC. We aimed to fish 15 depletion sites and 25 timed sites, but significant flooding throughout August 2004, and later in the season, disrupted the work programme so that we achieved only nine depletion sites and just eight timed sites (Map 16). Previous electrofishing on the Tay has not followed SFCC protocols fully and we were unable to make comparisons with historical data. The SAC sites were fished by staff of the Tay DSFB. As a result of the low numbers of electrofishing sites achieved in 2004, further sites were fished in 2005, including some revisits to sites. Combined data from 2004 and 2005 is analysed here, with the most recent data being used where a site was fished in 2004 and 2005. 4.3.14.1 Depletion sites Sites were distributed amongst major tributaries and low-lying burns (Map 16, Table 115). Salmon were caught at all the sites, with densities for fry ranging from 38 to 577 100m-2 (Zippin mean 143.7±sd161.6) and for parr from 5 to 48 100m-2 (Zippin mean 27.5±sd14.9, three-run minimum mean 23.4±sd14.8) (Table 116). Some of the Zippin estimates had wide confidence limits (Fig 51). Some of the fishings had only two runs, and three-run minimums were estimated from these using simple extrapolation based on the assumption of a constant proportional capture rate. Salmon 0+ and 1+ were present at all sites, while the 2+ age class was only absent at half of the sites, including at a fairly high altitude site on the River Cononish where the mean size of 1+ fish was notably large (Tables 117, 118). Table 115. Details of depletion sites, Tay SAC 2004/5. Site Code Easting Northing Altitude (m) Channel name Principal local landuse LUN1 318100 740100 35 Lunan Burn Tilled land DEAN1 338600 748500 55 Dean Water Improved Grassland SHO1 306600 729700 55 Shochie Burn Tilled land KER1 341600 747000 58 Kerbet Water Tilled land LOC1 253900 735300 140 Lochay Broadleaved woodland SHO2 299900 733800 190 Shochie Burn Broadleaved woodland ERR3 276600 763700 200 Errochty Water Improved Grassland FEAR1 304900 763700 255 Fearnach Water Improved Grassland CON1 231100 728600 260 Cononish Rough pasture ALM3 279700 733400 290 Almond Rock/Scree BRE1 300400 763400 290 Brerachan Water Heather moorland SHEE2 309700 770800 348 Shee Water Rough pasture

151

Table 116. Details of depletion electrofishing for 0+ and 1++ salmon, Tay SAC 2004/5.

Site Code

Date Area (m2)

Mean wet

width (m)

Zippin density 0+ (no 100m-2) +95% c.l.

3-run min 0+

(no 100m-2)

Zippin density 1++ (no 100m-2) +95% c.l.

3-run min S1++

(no 100m-2)

LUN1 21/09/05 134.0 7.1 167.5+16.1 161.1 10.1+3.9 9.7DEAN1 19/09/05 105.6 5.9 386.4+388.1 144.9 15.8+26.1 9.5SHO1 26/09/05 58.3 5.3 143.3+7.9 142.5 N/a 10.3KER1 20/09/05 45.6 3.8 577.3+60.3 548.9 N/a 4.4LOC1 09/10/04 112.9 8.1 42.3+4.6 39.8 4.6+1.2 4.4SHO2 26/09/05 74.3 5.5 48.5+11.5 46.7 28.7+5.4 28.3ERR3 22/09/05 80.3 7.3 119.6+42.3 104.6 39.1+1.9 38.7FEAR1 07/10/05 117.6 14.7 48.4+4.8 47.9 18.8+0.4 18.7CON1 09/10/04 145.0 14.5 38.1+11.4 31.0 N/a 33.8ALM3 03/10/05 83.3 9.8 57.9+9.5 56.4 39.7+8.3 38.4BRE1 07/10/05 92.4 5.6 49.4+4.2 49.1 43.4+21.0 39.0SHEE2 05/10/05 74.0 7.4 46.1+8.6 41.9 47.7+4.3 45.9Mean 143.7 117.9 27.5 23.4s.d. 161.6 137.5 14.9 14.8 Table 117. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Tay SAC 2004/5. Site Code Salmon age class present? Trout present?

0+ 1+ 2+ 3++ 0+ 1++ LUN1 YES YES no no YES YES DEAN1 YES YES YES no YES YES SHO1 YES YES no no no no KER1 YES YES no no YES no LOC1 YES YES no no no YES SHO2 YES YES YES no YES YES ERR3 YES YES YES no YES no FEAR1 YES YES YES no YES YES CON1 YES YES no no YES YES ALM3 YES YES YES no YES no BRE1 YES YES no no YES YES SHEE2 YES YES YES no YES no

152

Map 16. Distribution of depletion and timed electrofishing sites in the Tay SAC.

Table 118. Fork length of salmon of different age classes, Tay SAC 2004/5.

Site Code

0+ mean±s.d. fork length

(mm)

no 0+

1+ mean±s.d. fork length

(mm)

no 1+

2+ mean±s.d. fork length

(mm)

no 2+

3+ mean±s.d. fork length

(mm)

no 3+

LUN1 49.0±5.6 199 97.3±8.7 12 0.0 0 0 DEAN1 57.3±6.9 153 104.7±9.1 9 134.0 1 0 SHO1 65.2±7.8 81 97.5±6.0 6 0.0 0 0 KER1 64.8±8.0 228 141.5±2.1 2 0.0 0 0 LOC1 66.9±5.2 45 121.4±10.0 5 0.0 0 0 SHO2 49.3±4.0 32 82.6±5.5 16 102.8±3.6 4 0 ERR3 48.6±4.6 72 83.1±9.2 29 105.5±2.1 2 0 FEAR1 59.9±4.9 54 96.1±9.4 21 117.0 1 0 CON1 67.4±4.9 45 147.0±10.9 4 0.0 0 0 ALM3 48.4±3.7 44 83.5±9.2 29 139.0 1 0 BRE1 59.0±4.2 44 93.1±8.4 31 0.0 0 0 SHEE2 59.6±3.8 31 88.7±9.7 23 116.6±11.6 11 0

153

Figure 51. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Tay SAC, 2004. Error bars show upper 95% confidence limit. Sites are arranged altitudinally, lowest leftmost.

Tay SAC

0

100

200

300

400

500

600

700

800

LUN1

DEAN1SHO1

KER1LO

C1SHO2

ERR3

FEAR1CON1

ALM3

BRE1

SHEE2

site name

num

ber (

100m

-2)

0+

1++

4.3.14.2 Timed sites The programme of 25 timed sites was severely disrupted by flow conditions in 2004, and only 8 sites were fished. Surveys of the original programme of sites were made to some sites in 2005, with some of revisits. Details of the timed sites and electrofishing surveys from 2004 and 2005 are tabulated in Tables 119, 120, 121. Fry were present at all sites, and 1+ fish present at all but two of the sites, while 2+ fish were present at four of the eight sites. Capture rates were high, particularly in the riffles where mean catch rates for fry and parr were respectively 8.5 and 1.4 per minute. In the runs mean catch rate was 5.6 for fry and 1.1 for parr, whilst in the glides overall salmon catch rate was just 2.8 per minute (Table 120, Figure 48). At one site, LYO1, no run habitat was fished. Table 119. Details of timed electrofishing sites, Tay SAC 2004. Site Code Easting Northing River Altitude (m) Principal Local Landuse TAY1 313400 739700 Tay 30 Arable ERI1 322700 743600 Ericht 35 Improved grassland ISL1 329900 747600 Isla 40 Orchard TAY2 300700 742600 Tay 45 Garden GLA1 338900 747900 Glamis 55 Improved grassland L.TUM1 296700 754300 Tummel 65 Improved grassland TUM1 290700 759900 Tummel 110 Rough pasture GAR1 283800 765800 Garry 135 Improved grassland TUM2 275400 759400 Tummel 155 Rough pasture ERR2 278100 763800 Errochty 190 Improved grassland LYO1 254800 745900 Lyon 215 Improved grassland FIL1 235800 728200 Fillan 215 Improved grassland TUM3 246800 757000 Gaur 225 Rough pasture LYO10 250900 742100 Lyon 280 Rough pasture SHE1 314500 763400 Shee 295 Improved grassland

154

Table 120. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Tay SAC. Each habitat type was fished for five minutes.

Site code Survey date

Salmon 0+ min-1 Salmon 1++ min-1

Glide Run Riffle Glide Run Riffle TAY1 09.10.05 1.4 2.4 6.3 0.0 0.0 0.0ERI1 05.10.05 2.8 not fished 14.0 0.0 not fished 0.4ISL1 20.09.05 11.2 27.4 29.2 1.4 4.2 3.2TAY2 09.10.05 1.0 7.0 6.6 0.0 0.6 0.2GLA1 19.09.05 20.0 not fished 16.6 3.6 not fished 0.2L.TUM1 08.10.05 1.8 7.4 12.0 0.0 0.8 0.0TUM1 29.09.04 0.0 1.4 5.4 0.2 0.8 1.8GAR1 08.10.05 2.8 5.8 4.3 0.2 1.2 0.0TUM2 22.09.05 1.8 8.6 11.2 0.4 1.6 1.0ERR2 22.09.05 3.1 5.4 12.8 0.1 0.7 0.6LYO1 08.10.04 3.0 not fished 15.8 0.0 not fished 5.0FIL1 09.10.04 2.2 2.2 4.7 0.6 1.6 0.8TUM3 29.09.04 0.6 1.7 2.0 0.0 0.0 0.0LYO10 23.09.05 0.4 2.0 3.4 0.0 1.3 1.6SHE1 05.10.05 0.3 2.5 3.2 0.3 2.3 1.4Mean 3.49 6.15 9.83 0.45 1.26 1.08s.d 5.11 6.85 7.00 0.91 1.09 1.36

Table 121. Presence/absence of salmon year classes, and of trout at timed sites, Tay SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3+ TAY1 YES no no no YES ERI1 YES YES no* no no* ISL1 YES YES no no YES TAY2 YES YES no no YES GLA1 YES YES ? no YES L.TUM1 YES YES ? no no TUM1 YES YES YES no no GAR1 YES YES ? no YES TUM2 YES YES ? no YES ERR2 YES YES no no YES LYO1 YES YES YES no no* FIL1 YES YES no no YES TUM3 YES no no no YES LYO10 YES YES YES no YES SHE1 YES YES YES no YES • Run not fished.

155

Figure 52. Number of salmon caught per minute during timed electrofishing at sites on the Tay, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++ Sites are arranged altitudinally, left lowest. NB. Run was not fished at ERI1, GLA1 and LYO1. a)

0

5

10

15

20

25

30

35

TAY1ERI1

ISL1

TAY2GLA

1

L.TUM1

TUM1

GAR1TUM2

ERR2

LYO1

FIL1TUM3

LYO10

SHE1

all s

alm

on m

in-1

Glide

Run

Riff le

b)

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

TAY1ERI1

ISL1

TAY2GLA

1

L.TUM1

TUM1

GAR1TUM2

ERR2

LYO1

FIL1TUM3

LYO10

SHE1

salm

on fr

y m

in-1 Glide

Run

Riff le

c)

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

TAY1ERI1

ISL1

TAY2GLA

1

L.TUM1

TUM1

GAR1TUM2

ERR2

LYO1

FIL1TUM3

LYO10

SHE1

salm

on p

arr m

in-1 Glide

Run

Riff le

156

4.3.15 River Teith The Atlantic salmon is a secondary qualifying species for the Teith SAC. The SAC is comprised of some of the major tributaries of the upper system, and a few of the smaller low-lying streams. Several lochs are included in the designation, and these contribute to the majority of the 13.1km2 designated (Map 17). No attempt has been made here to assess the status of the lochs in the system. The SAC sites were fished by Forth Fisheries Foundation staff. 4.3.15.1 Depletion sites Seven sites were selected for depletion fishings, comprised of established sites and new sites on previously unsampled tributaries (Table 122). Salmon were somewhat patchily distributed in amongst the sites with fry densities ranging from 0 to 321 per 100m2 (Zippin mean163.3±sd122.8, three-run minimum mean 79.8±106.5) and parr densities in the range 0-55 (Zippin mean 25.3±sd18.8, three-run minimum mean 13.9±sd17.9) (Table 123). Confidence limits of the estimates were generally quite narrow (Fig 53). Fry were absent at two sites and very scarce at another whilst parr were absent from one and scarce at two sites. 1+ fish were absent at three sites, two of which had 2+ fish present (Tables 124, 125). No older fish were caught. Table 122. Details of depletion sites, Teith SAC.

Site Code

Easting Northing Altitude (m)

Channel name Principal local landuse

Teith2 270300 703300 55 Annet Burn, Broadleaved woodland Teith6 250300 706300 90 Achray Water Broadleaved woodland Teith4 265400 707900 90 Brackland Burn Rough pasture Turk1 253200 706900 100 River Turk Broadleaved woodland Teith1 274500 705500 160 Ardoch Burn Rough pasture Teith8 252900 717500 210 Calair Burn Broadleaved woodland Larig1 238500 716450 280 River Larig Heath/Moorland Table 123. Details of depletion electrofishing for 0+ and 1++ salmon, Teith SAC. Site

Code Date Area

(m2) Mean wet width (m)

Zippin density 0+ (no 100m-2) +95% c.l.

3-run min 0+

(no 100m-2)

Zippin density 1++ (no 100m-2) +95% c.l.

3-run min S1++

(no 100m-2)

Teith2 05/08/04 119.8 6.5 320.6+22.1 283.8 4.2+0.3 4.2Teith6 03/08/04 142.8 7.7 N/a 0.7 N/a 0.7Teith4 05/08/04 130.6 5.4 237.8+28.1 196.1 55.3+4.0 52.8Turk1 03/08/04 123.3 12.3 8.2+0.4 8.1 N/a 0.0Teith1 05/08/04 141.9 6.9 N/a 0.0 17.4+4.5 15.5Teith8 04/08/04 118.7 11.9 N/a 0.0 N/a 0.8Larig1 04/08/04 138.6 4.2 86.5+18.1 70.0 24.4+3.0 23.1Mean 163.3 79.8 25.3 13.9s.d. 122.8 106.5 18.8 17.9

157

Map 17. Distribution of depletion and timed electrofishing sites on the Teith SAC.

Table 124. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Teith SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3++ 0+ 1++ Teith2 YES YES no no YES YES Teith6 YES no YES no YES YES Teith4 YES YES YES no YES YES Turk1 YES no no no YES YES Teith1 no YES YES no YES YES Teith8 no no YES no YES YES Larig1 YES YES YES no YES YES

158

Table 125. Fork length of salmon of different age classes, Teith SAC. Site Code 0+ mean±s.d.

fork length (mm) no 0+ 1+ mean±s.d.

fork length (mm) no 1+ 2+ mean±s.d.

fork length (mm) no 2+

Teith2 50.8±5.2 340 98.2±6.9 5 0Teith6 62.0 1 0 151.0 1Teith4 44.4±5.7 256 88.6±8.5 63 112.8 6Turk1 60.3±5.3 10 0 0Teith1 0 114.7±7.6 21 142.0 1Teith8 0 0 122.0 1Larig1 39.3±2.8 97 78.7±8.3 31 120.0 1 Figure 53. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Teith. Error bars show upper 95% confidence limit. Arrows indicate three-run minimum density estimate.

Teith SAC

0

50

100

150

200

250

300

350

Teith2 Teith4 Teith6 Turk1 Teith1 Teith8 Larig1Site name

Num

ber (

100m

-2) S0+

S1++

4.3.15.2 Historical data Zippin estimates from previous fishings in 2002 and 2003 were available for five of the SAC sites (Fig 54). These show that both fry and parr densities vary significantly between years at most sites, in some cases to a very large degree, but no overall pattern can be discerned. 4.3.15.3 Timed sites With the mainstem of the Teith being too large for depletion fishings, the timed sites were focused on the Teith itself, with three further tributaries sampled, comprising 11 sites in total (Map 17, Table 126). All sites were fished in August 2004. Salmon were present at all sites, though represented by just one individual at two sites (Table 128, Figure 55). Only 0+ and 1+ salmon age-classes were found, with the exception of the highest site on the mainstem, where a single 3+ fish was caught (Te11). This latter site is not accessible to salmon in all years and had been stocked. Catch rates per minute tended to decline with altitude on the mainstem (Figure 55), but were mostly fairly high, with average capture rates of 3.1 fish per minute in the glides, 3.8 in the riffles and 3.9 in the runs (Table 127).

159

Figure 54. Electrofishing time series data for juvenile salmon for available sites in the Teith SAC, 2002-2004. Note that the y-axis scale varies between graphs. Zippin density estimates (no 100m-2) are shown, but where zero fish were caught for a given age class, this has been marked, though, strictly, Zippin estimates of zero are impossible. For the site Teith 8, three-run minimum data is shown.

Teith 1

0

20

40

60

80

100

120

2001 2002 2003 2004 2005

year

zipp

im e

stim

ate

0+1++

Teith 2

050

100150200250300350400

2001 2002 2003 2004 2005

year

zipp

in e

stim

ate

0+1++

Teith 4

0

50

100

150

200

250

300

350

2001 2002 2003 2004 2005

year

zipp

in e

stim

ate

0+1++

Teith 6

02468

10121416

2001 2002 2003 2004 2005

year

zipp

in e

stim

ate

0+1++

Teith 80+ data three-run minimum estimate

0

2

4

6

8

10

12

14

2001 2002 2003 2004 2005

year

zipp

in e

stim

ate

0+1++

160

Table 126. Details of timed electrofishing sites, Teith SAC. Site Code Easting Northing River Altitude

(m) Principal Local Landuse

Te7 276100 697100 Teith 10 Rough pasture Te5 270750 702200 Teith 30 Broadleaved woodland Te6 275300 703400 Teith 50 Rough pasture Te4 264400 705100 Teith 60 Broadleaved woodland Te10 260300 706950 Teith 80 Improved grassland Te2 256300 704700 Drunkie 90 Broadleaved woodland Te3 265300 707850 Keltie 90 Broadleaved woodland Te8 255900 716800 Teith 130 Broadleaved woodland Te9 258600 709400 Teith 130 Broadleaved woodland Te1 243700 718000 Farig 150 Rough pasture Te11 251300 717100 Teith 280 Rough pasture Table 127. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Teith SAC. Each habitat type was fished for five minutes. Site code Survey date Salmon 0+ min-1 Salmon 1++ min-1

Glide Run Riffle Glide Run Riffle Te7 02.08.04 10.6 12.8 7.4 0 0 0 Te5 02.08.04 4.2 4.6 8.8 0.8 2 0 Te6 02.08.04 5.4 12.2 6.6 1.6 1.6 1.8 Te4 02.08.04 4.4 4.2 3 0.2 0.6 3.4 Te10 04.08.04 0.4 4.8 1.8 0 0 0 Te2 03.08.04 0 0 0 0 0 0.2 Te3 02.08.04 5 7.6 6.4 1.8 1.8 2.2 Te8 03.08.04 2.2 5.8 8.2 0.2 0.8 1 Te9 03.08.04 4.8 2 3.8 0 0 0 Te1 04.08.04 0.6 4.4 1.6 0.4 2.2 1.6 Te11 04.08.04 0 0 0 0 0 0.2 Mean 2.53 3.12 2.87 0.52 0.79 0.96 s.d. 3.07 4.04 3.12 0.63 0.87 1.11 Table 128. Presence/absence of salmon year classes, and of trout at timed sites, Teith SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3+ Te7 YES no no no YES Te5 YES YES no no YES Te6 YES YES no no YES Te4 YES YES no no YES Te10 YES no no no YES Te2 no YES no no YES Te3 YES YES no no YES Te8 YES YES no no no Te9 YES no no no no Te1 YES YES no no YES Te11 no no no YES YES

161

Figure 55. Number of salmon caught per minute during timed electrofishing at sites on the Teith, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++. Sites are arranged altitudinally, left lowest. a)

0

2

4

6

8

10

12

14

Te7 Te5 Te6 Te4 Te10 Te2 Te3 Te8 Te9 Te1 Te11

all s

alm

on m

in-1

Glide

Run

Riff le

b)

0

2

4

6

8

10

12

14

Te7 Te5 Te6 Te4 Te10 Te2 Te3 Te8 Te9 Te1 Te11

salm

on fr

y m

in-1

Glide

Run

Riff le

c)

0

2

4

6

8

10

12

14

Te7 Te5 Te6 Te4 Te10 Te2 Te3 Te8 Te9 Te1 Te11

salm

on p

arr m

in-1

Glide

Run

Riff le

162

4.3.16 River Thurso The Thurso SAC occupies an area of 3.5km2, and is comprised of all the major streams in the catchment (Map 18). Most of the catchment and length of the channels is ’Flow Country’ characterised by low-gradients, and with significant afforestation, whilst in the lower reaches the river passes through agricultural and urban environments. The SFCC has no affiliation with the river, and the sampling programme was carried out by the Conon District Salmon Fishery Board. 4.3.16.1 Depletion sites No previous information on juvenile populations is held by the SFCC, and all the sites were selected for the SAC monitoring alone. They were located in each of the upper tributaries and in two small, lower-lying burns and a single site on the main river was also sampled (Table 129). All sites were fished in September. Densities of fry were strikingly constant (Figure 56), all in the range 32-90 per 100m2 (Zippin mean 71.7±sd10.1). Parr densities ranged from 4.1 to 28.5 per 100m2 (Zippin mean 13.5±sd7.8) (Table 130). Salmon fry were present at all the seven sites, with 1+ and 2+ fish present at six of the sites. No 3++ fish were recorded. (Table 131, 132). Table 129. Details of depletion sites, Thurso SAC.

Site Code

Easting Northing Altitude (m)

Channel name Principal local landuse

TH1 311000 965000 30 Geise Burn Broadleaved woodland TH2 314100 959550 30 Sibster Burn Rough pasture TH3 313050 951800 55 Thurso Rough pasture TH4 317050 947050 80 Little River Rough pasture TH5 303900 944500 130 Sleach Water Conifer plantation TH6 298900 940800 155 Rumsdale Water Heath/Moorland TH7 300100 937800 160 Glutt Water Heath/Moorland Table 130. Details of depletion electrofishing for 0+ and 1++ salmon, Thurso SAC. Site

Code Date Area

(m2) Mean wet width (m)

Zippin density 0+ (no 100m-2) +95% c.l.

3-run min 0+

(no 100m-2)

Zippin density 1++ (no 100m-2) +95% c.l.

3-run min S1++

(no 100m-2)

TH1 10/09/04 79.8 2.7 32.0+2.4 31.3 7.3+5.2 6.3TH2 27/09/04 99.6 4.0 78.0+4.5 75.3 9.7+6.2 8.0TH3 09/09/04 95.2 4.1 89.5+2.8 88.2 28.5+0.8 28.4TH4 27/09/04 94.4 4.7 70.5+4.9 67.8 12.4+6.3 10.6TH5 08/09/04 98.0 4.9 58.0+3.7 56.1 4.1+0.5 4.1TH6 07/09/04 106.0 5.3 63.7+4.2 61.3 17.4+1.7 17.0TH7 07/09/04 102.0 5.1 70.4+4.7 67.6 9.0+1.2 8.8Mean 71.7 69.4 13.5 12.8s.d. 10.1 10.3 7.8 7.9

163

Map 18. Distribution of depletion and timed electrofishing sites on the Thurso SAC.

Table 131. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Thurso SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3++ 0+ 1++ TH1 YES YES YES no YES no TH2 YES YES YES no YES YES TH3 YES YES YES no YES YES TH4 YES YES YES no YES no TH5 YES no YES no YES no TH6 YES YES YES no YES YES TH7 YES YES no no YES YES

164

Table 132. Fork length of salmon of different age classes, Thurso SAC. Site Code 0+ mean±s.d.

fork length (mm) no 0+ 1+ mean±s.d.

fork length (mm) no 1+ 2+ mean±s.d.

fork length (mm) no 2+

TH1 66.2±3.9 25 105.0±1.4 2 105.0 3TH2 70.4±5.9 75 87.7±1.4 7 125 1TH3 61.8±5.2 84 106.0±7.3 26 123 1TH4 55.7±4.9 64 106.3±6.8 8 128.5 2TH5 58.7±6.1 55 0 124 4TH6 57.8±5.3 65 102.8±6.2 16 130.5 2TH7 52.3±4.2 69 106.9±4.5 9 0 Figure 56. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Thurso. Error bars show upper 95% confidence limit.

Thurso SAC

0102030405060708090

100

TH1 TH2 TH3 TH4 TH5 TH6 TH7

Site name

num

ber (

100m

-2)

0+

1++

4.3.16.2 Timed sites Eleven timed sites were fished, 4 in the lower mainstem, 3 in the upper mainstem and 4 on the upper tributaries (Table 133). All sampling took place in September Overall mean salmon catch rates were 5.5 per minute in the riffles, 2.6 in the glides and 2.7 in the runs (Table 134, Figure 57). Salmon fry were present at all sites, while both 1+ and 2+ fish were present at all sites bar two at which no parr were caught. No 3+ fish were recorded (Table 135).

165

Table 133. Details of timed electrofishing sites, Thurso SAC. Site Code Easting Northing River Altitude

(m) Principal Local Landuse

Th1 311700 966550 Thurso 15 Rough pasture Th2 314200 962200 Thurso 20 Rough pasture Th3 312200 957700 Thurso 45 Rough pasture Th4 312600 953400 Thurso 50 Rough pasture Th5 311650 948100 Thurso 100 Heath/Moorland Th6 306000 943550 Thurso 140 Heath/Moorland Th7 301900 940300 Thurso 150 Heath/Moorland Th8 300600 945450 Sleach Water 150 Wetland Th9 307700 942600 Backlass 140 Heath/Moorland Th10 299500 940700 Rumsdale Water 155 Heath/Moorland Th11 299700 936400 Glutt Water 195 Heath/Moorland Table 134. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Thurso SAC. Each habitat type was fished for five minutes. Site code Survey date Salmon 0+ min-1 Salmon 1++ min-1

Glide Run Riffle Glide Run Riffle Th1 09.09.04 2.6 4 5.6 1.8 2.2 2.4Th2 10.09.04 6 3.2 7.4 1.6 1.2 3.4Th3 09.09.04 3.4 2.2 5.2 0.8 0.6 0.2Th4 09.09.04 1 1 3.2 0 0 0Th5 08.09.04 5.8 3.4 6 1.8 1.4 0.6Th6 08.09.04 3.6 2.6 3.2 0 0.2 0.4Th7 08.09.04 5.6 0.4 6 0.4 0 0.6Th8 08.09.04 0.6 1.6 6.2 0 0 0Th9 08.09.04 0 0.6 0 0.2 0.4 0Th10 07.09.04 1.8 2.6 4.8 0.2 1.4 0.4Th11 07.09.04 2.4 0.4 3.8 0.2 1.6 0.8Mean 2.98 2.00 4.67 0.64 0.82 0.80s.d. 2.02 1.22 1.94 0.71 0.74 1.04 Table 135. Presence/absence of salmon year classes, and of trout at timed sites, Thurso SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3+ Th1 YES YES YES no YES Th2 YES YES YES no no Th3 YES YES YES no no Th4 YES no no no no Th5 YES YES YES no YES Th6 YES YES YES no YES Th7 YES YES YES no YES Th8 YES no no no YES Th9 YES YES YES no YES Th10 YES YES YES no YES Th11 YES YES YES no YES

166

Figure 57. Number of salmon caught per minute during timed electrofishing at sites on the Thurso, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++. Sites are arranged altitudinally, left lowest. a)

0

2

4

6

8

10

12

Th1 Th2 Th3 Th4 Th5 Th6 Th9 Th7 Th8 Th10 Th11

all s

alm

on m

in-1

Glide

Run

Riff le

b)

0

2

4

6

8

10

12

Th1 Th2 Th3 Th4 Th5 Th6 Th9 Th7 Th8 Th10 Th11

salm

on fr

y m

in-1

Glide

Run

Riff le

c)

0

2

4

6

8

10

12

Th1 Th2 Th3 Th4 Th5 Th6 Th9 Th7 Th8 Th10 Th11

salm

on p

arr m

in-1

Glide

Run

Riff le

167

4.3.17 Tweed The Tweed SAC contains all the major and many of the lower order tributaries of the system, occupying a total area of 40.0km2 (Map 19). Given the extent of the Tweed catchment, the sites it was possible to fish during this sampling programme were perhaps too few in number to reflect the full range of the habitat types. No pollution or stocking events were known to have affected the SAC sites. Electrofishing was conducted by staff of the Tweed Foundation, generally with flows at high-medium levels. 4.3.17.1 Depletion sites The Tweed Foundation has an extensive range of pre-existing electrofishing sites throughout the catchment that are fished in rotation. We adopted a selection from these, covering the catchment as evenly as possible, and maximising the historical record. Ten sites were fished, ranging in altitude from 40 to 320m (Table 136). Fry densities ranged between >18 and 230 per 100m2 (Zippin mean 127.8±sd66.6, three-run minimum mean 89.7±36.0), whilst reported parr densities varied between 2.9 and 129 per 100m2. This maximum figure however is unreliable due to extremely wide confidence limits (Table 137). Mean Zippin density for fry was 33.9±sd36.0 per 100m2 (three-run minimum mean 18.9±10.3). Figure 58 shows the fishing results for the SAC sites, and, for comparison, the full range of sites fished in 2004 on the Tweed is shown in Figure 59, with the SAC sites arranged on the left. Both 0+ and 1+ salmon were present at all the sites, and no older fish were found (Table 138). Table 136. Details of depletion sites, Tweed SAC. Site Code Easting Northing Altitude (m) Channel name Principal local landuse EN 02 371800 637300 40 Eden Water Tall herbs LR 05G 357900 635400 80 Leader Water Broadleaved woodland KE 02 377715 619685 130 Teviot Tall herbs AN 01 347450 607500 170 Teviot Rough pasture LE 04 318500 640550 180 Upper Tweed Tall herbs AE 01 343900 618800 220 Teviot Rough pasture WR 01 366800 663300 220 Whiteadder Water Heath/Moorland HT 02 338323 652073 260 Gala Water Rough pasture TW 02 305631 620781 280 Upper Tweed Rough pasture EK 08 331800 615800 320 Ettrick Water Heath/Moorland Table 137. Details of depletion electrofishing for 0+ and 1++ salmon, Tweed SAC.

Site Code

Date Area (m2)

Mean wet

width (m)

Zippin density 0+ (no 100m-2) +95% c.l.

3-run min 0+

(no 100m-2)

Zippin density 1++ (no 100m-2) +95% c.l.

3-run min S1++

(no 100m-2)

EN 02 27/08/04 93.3 4.7 18.2 129.1+907 23.6LR 05G 29/06/04 174.2 15.8 172.2+30.6 130.3 47.9+13.4 37.9KE 02 29/07/04 115.3 5.8 230.1+30.7 188.2 26.9+2.4 26.0AN 01 17/08/04 90.3 6.0 138.7+11.4 128.5 6.7+0.3 6.6LE 04 30/08/04 179.2 8.5 186.4+30.8 141.7 11.7+5.8 9.5AE 01 25/08/04 163.8 7.6 56.3+22.3 40.3 23.5+5.2 20.8WR 01 27/08/04 122.8 10.2 26.3+10.9 21.2 28.6+8.3 24.4HT 02 24/08/04 198.0 7.3 46.0+14.7 34.8 28.2+4.0 25.8TW 02 30/08/04 113.3 11.3 170.0+43.1 124.4 11.5EK 08 25/08/04 176.0 8.8 123.9+67.8 69.3 2.9+0.2 2.8Mean 127.8 89.7 33.9 18.9s.d 66.6 57.0 36.0 10.3

168

Map 19. Distribution of depletion and timed electrofishing sites on the Tweed SAC.

Table 138. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites, Tweed SAC. Site Code Salmon age class present? Trout present?

0+ 1+ 2+ 3++ 0+ 1++ EN 02 YES YES no no YES YES LR 05G YES YES no no YES YES KE 02 YES YES no no YES YES AN 01 YES YES no no YES YES LE 04 YES YES no no YES YES AE 01 YES YES no no YES YES WR 01 YES YES no no YES YES HT 02 YES YES no no YES YES TW 02 YES YES no no YES YES EK 08 YES YES no no YES YES

169

Table 139. Fork length of salmon of different age classes, Tweed SAC.

Site Code

0+ mean±s.d. fork length

(mm)

no 0+

1+ mean±s.d. fork length

(mm)

no 1+

2+ mean±s.d. fork length

(mm)

no 2+

3+ mean±s.d. fork length

(mm)

no 3+

EN 02 68.7±8.4 17 117.7±9.1 22 0 0 LR 05G 49.3±3.0 227 103.7±10.0 66 0 0 KE 02 56.5±6.6 217 113.8±8.2 30 0 0 AN 01 57.8±6.9 116 107.5±10.0 6 0 0 LE 04 60.7±7.5 254 122.2±10.2 17 0 0 AE 01 65.2±7.9 66 101.3±7.2 34 0 0 WR 01 67.9±5.8 26 112.5±8.5 30 0 0 HT 02 61.6±4.8 69 100.9±9.0 51 0 0 TW 02 55.8±6.8 141 101.0±6.6 13 0 0 EK 08 64.4±7.6 122 112.5±7.1 5 0 0 Figure 58. Juvenile salmon population density estimated by the Zippin method for the SAC monitoring sites on the Tweed SAC. Error bars show upper 95% confidence limit. Arrows indicate where three-run minimum estimate is used. NB. Error bar for EN 02 1++ is off the scale, see Table 139.

Tweed cSAC Sites

0

50

100

150

200

250

300

EN 02 LR 05G KE 02 AN 01 LE 04 AE 01 WR 01 HT 02 TW 02 EK 08

site name

num

ber 1

00m

-2

0+

1++

4.3.17.2 Historical data The most extensive historical information held by the SFCC for any of the SACs is that held on the Tweed. Most sites have at least three previous electrofishing events, with Zippin density estimates dating back, in some cases, as far as the 1980s. The available data for the SAC sites are complied in Figure 60. The overall picture is one of remarkable constancy amongst parr densities, with significant, but apparently patternless variation in fry densities between years.

170

Figure 59. Juvenile salmon populations densities estimated by the Zippin method for all sites electrofished on the Tweed in 2004. Sites fished for SAC monitoring are arranged on the left. Where Zippin estimates were not calculable three-run minimum estimates have been used: for 0+ fish his applies to the sites EN02, KE01, OM01, SG03, TL06, TT01 AND BT02; for 1++ fish to sites TW02, RE01, RE03, SG01, SG03, TL06, BK02, BT02 AND BT05.

All sites Tweed 2004

0

100

200

300

400

500

600

700

EN02

LR05G

KE02

AN01

LE04

AE01

WR01

HT02

TW02

EK08

JD01

JD02N

JD02S

JD03

KE01

KE03

LR05F

OM01

OM02

OM03

OM04

OM05

RE01

RE02

RE03

SG01

SG02

SG03

TL01

TL02

TL03

TL04

TL05

TL06

TL07

TT01

TT02

TT03

TT04

AE02

AE03

AN02

BK01

BK02

BK03

BT01

BT02

BT04

BT05

HE01

HE02

site name

num

ber 1

00m

-2

0+1++

4.3.17.3 Timed sites Sixteen timed sites were fished, on the mainstem and on some tributaries not sampled in the depletion sites (Table 140). The altitudinal range of the sites was 36-240 m. Catch rates were high for fry (mean 6.1 fish min-1), but rather low for parr (1.2 fish min-1). Overall catch rate means were highest in the riffles (8.0 fish min-1) and lowest in the glides (4.8 min-1) with runs intermediate at 6.2 fish min-1 (Table 141, Figure 61). Fry were present at all of the sites, and 1+ fish at all but two of the sites. No older fish were caught (Table 142).

171

Figure 60. Zippin estimates of salmon fry (0+) and salmon parr (1++) densities at electrofishing sites on the Tweed between 1988 and 2004. The scales of both x and y axes vary, but in each case the last data point is from 2004. Error bars show 95% confidence intervals. The final graph in the series, for site EN 02, shows three-run minimum density estimate.

AE 01

0

20

40

60

80

100

1990 1995 2000 2005

year

zipp

in d

ensi

ty

0+1++

AN 01

0

50

100

150

200

1985 1990 1995 2000 2005

year

zipp

in d

ensi

ty

0+1++

EK 08

0

50

100

150

200

1995 2000 2005

year

zipp

in d

ensi

ty

0+1++

HT 02

020406080

100120140160180

1995 2000 2005

year

zipp

in d

ensi

ty

0+1++

LR 05G

050

100150200250300350400

2000 2001 2002 2003 2004 2005

year

zipp

in d

ensi

ty

0+1++

TW 02(I++ is one-run minimum estimate)

0

50

100

150

200

250

1985 1990 1995 2000 2005

year

zipp

in d

ensi

ty

0+1++

172

Figure 60 (continued)

WR 01

0

20

40

60

80

100

1995 2000 2005

year

zipp

in d

ensi

ty

0+1++

LE 04

050

100150200250300350400450

1995 2000 2005

year

zipp

in d

ensi

ty

0+1++

EN 02

05

10152025303540

1975 1985 1995 2005

year

3-ru

n m

inim

um0+1++

KE 02

0

50

100

150

200

250

300

1990 1995 2000 2005

year

zipp

in d

ensi

ty

0+1++

Table 140. Details of timed electrofishing sites, Tweed SAC. Site Code Easting Northing River Altitude

(m) Principal Local Landuse

Tw9 370684 631587 Teviot 36 Scrub Tw1 361098 631573 Tweed 62 Tall herbs Tw10 357022 618937 Teviot 69 Tall herbs Tw2 348940 632366 Tweed 98 Improved grassland Tw12 366507 615922 Jed Water 106 Broadleaved woodland Tw14 349445 636069 Gala Water 109 Suburban Tw3 338270 637664 Tweed 127 Tall herbs Tw11 353483 625593 Ale Water 131 Broadleaved woodland Tw4 330745 637544 Tweed 142 Tall herbs Tw8 372842 660029 Whiteadder Water 164 Scrub Tw5 316708 635644 Tweed 186 Improved grassland Tw15 333659 621105 Ettrick Water 207 Tall herbs Tw16 334592 626381 Yarrow Water 207 Garden Tw7 316109 646932 Lyne Water 215 Tall herbs Tw6 311281 626955 Tweed 222 Broadleaved woodland Tw13 350776 654492 Leader Water 240 Tall herbs

173

Table 141. Salmon CPUE in glide, run and riffle habitats at timed electrofishing sites on the Tweed SAC. Each habitat type was fished for five minutes. Site code Survey date Salmon 0+ min-1 Salmon 1++ min-1

Glide Run Riffle Glide Run Riffle Tw9 30.08.04 0.8 1.8 5.2 0.4 0.4 0.4 Tw1 30.08.04 0.8 3.2 2.8 1.2 1.2 2.4 Tw10 31.08.04 23.8 20.2 19.2 1 0 0.6 Tw2 25.08.04 0 6.6 5.6 0 0.2 1.2 Tw12 03.08.04 0.2 7.6 9.2 0 0.8 0.8 Tw14 26.08.04 1.4 0.6 3.4 0.2 0.2 1.4 Tw3 23.08.04 9 6.8 6.8 0.4 0 0.4 Tw11 31.08.04 10.2 8.6 18 0.2 0 0.4 Tw4 23.08.04 9.8 14.8 9 0.2 0.2 0.2 Tw8 18.08.04 0.4 3.8 5 0 0.4 0.6 Tw5 24.08.04 5 3.8 4 0 0 0 Tw15 25.08.04 4.8 6.4 10.6 0.4 0.6 0.4 Tw16 19.08.04 0.6 1 6 0.2 0 0.8 Tw7 27.08.04 1.6 3 4.8 0 0 0 Tw6 24.08.04 1.2 1.4 1.4 0.2 0.2 0.2 Tw13 26.08.04 2 5.4 6.8 0.4 0.4 0.2 Mean 4.48 5.94 7.36 0.30 0.29 0.63 s.d. 6.06 5.06 4.85 0.34 0.33 0.60 Table 142. Presence/absence of salmon year classes, and of trout at timed sites, Tweed SAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3+ Tw9 YES YES no no YES Tw1 YES YES no no YES Tw10 YES YES no no no Tw2 YES YES no no YES Tw12 YES YES no no YES Tw14 YES YES no no YES Tw3 YES YES no no YES Tw11 YES YES no no YES Tw4 YES YES no no YES Tw8 YES YES no no YES Tw5 YES no no no YES Tw15 YES YES no no YES Tw16 YES YES no no YES Tw7 YES no no no YES Tw6 YES YES no no YES Tw13 YES YES no no YES

174

Figure 61. Number of salmon caught per minute during timed electrofishing at sites on the Tweed, 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. a) all salmon b) salmon 0+ and c) salmon 1++. Sites are arranged altitudinally, left lowest. a)

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4.4 Synthesis This section of the report draws together data from the various SACs. 4.4.1 Population densities There was significant variation in mean Zippin fry (Anova, F15,82=1.83, P<0.044), and parr densities (F15,85=2.22, P<0.012) among the SACs. Southern and Eastern rivers tended to have higher densities of juveniles: the Teith had the highest mean fry densities and the South Esk had the highest mean parr densities. In general there are relatively higher proportions of parr to fry in the more northerly rivers, reflecting the different age-structure of the parr population (Table 143). There are recognised problems with the timed fishing method as a quantification tool. Since there are no nets to prevent fish escaping, fish too large to find cover may escape before they can be drawn into the electric field. This is likely to reduce parr capture rates relative to fry. Another difficulty is that the time taken in handling the fish caught reduces the time available for fishing itself, so that differences in densities between sites will tend to be underestimated by the timed method. Nevertheless, the timed and depletion electrofishing results showed some marked similarities in this study (Figure 62 a, b and c). There was a striking correspondence between mean fry numbers estimated by timed and depletion fishings for a SAC. Mean SAC Zippin density explained 48% of the variance in mean SAC fry number caught per minute, and as much as 78% of the variance if the obvious outlier (the River Oykel) was excluded (log-log linear regression, d.f.=15, log no. fry min-1 = -1.491 + 0.998 x log Zippin fry density, P<0.001, Figure 63). The equivalent relationship for parr was positive, but non-significant. This may reflect the greater variance in parr escape rates between sites, or could be simply a consequence of lower variation in parr numbers than in fry numbers. Given that timed sites were not simply a different set of sites to the depletion sites (being selected in a different, semi random way, and often focused on different sections of the catchment) this encourages the belief that the pattern of depletion fishing results (and timed results) do not simply describe juvenile populations at the site itself, but also reflect the character of the catchment as a whole. Timed fishings would appear to yield information of more value than simple presence/absence, giving a semi-quantitative picture of fry salmon populations.

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Figure 62. Mean measures of abundance of salmon fry and parr for each SAC a) Zippin density estimates b) three-run minimum density estimates c) number of salmon fry and parr caught per minute by timed fishing. Error bars show s.d.

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Table 143. Summary of depletion and timed fishings at 14 SACs. Sample sizes can be found in preceding sections covering individual SACs.

Depletion sites Timed sites SAC Fry Zippin

density mean±sd

Parr Zippin density

mean±sd

Fry 3-run density

mean±sd

Parr 3-run density

mean±sd

Fry min-1 mean±sd

Parr min-1 mean±sd

B&L 29.1±18.2 23.2±7.9 28.4±17.9 18.6±10.0 1.43±1.02 0.99±0.63 Bladnoch 122.3±94.5 27.5±16.8 80.1±94.5 18.1±18.6 3.89±3.57 0.78±0.57 Dee 61.3±59.2 24.6±10.6 43.1±54.8 22.4±10.2 2.09±1.15 0.76±0.70 Endrick 90.5±90.7 5.0±3.8 39.4±70.0 3.7±3.0 1.59±0.90 0.62±0.61 Grimersta 25.8±21.4 21.0±7.8 19.1±17.3 16.4±4.0 0.57±0.51 0.61±0.32 L.Gruinard 61.7±36.2 34.6±15.5 50.9±28.1 30.3±14.9 1.85±1.05 0.66±0.53 Moriston 75.1±69.0 17.0±5.8 44.7±63.2 10.5±8.6 1.21±1.66 0.30±0.28 Naver 67.2±46.4 29.6±10.3 38.0±41.3 26.0±9.0 1.02±0.72 0.47±0.27 N.Harris 13.5±8.4 18.9±9.7 10.5±7.3 15.8±9.5 0.41±0.17 1.25±0.74 Oykel 49.9±33.5 21.4±10.4 27.4±21.9 15.0±9.1 0.11±0.14 0.18±0.14 S.Esk 144.5±93.5 57.4±18.3 130.2±88.5 53.4±18.7 5.21±4.34 1.12±1.16 Spey 54.3±57.9 28.7±18.4 35.2±49.5 21.0±16.6 1.17±1.08 0.45±0.39 Tay 143.7±161.6 27.5±14.9 117.9±137.5 23.4±14.8 6.08±5.20 0.85±0.75 Teith 163.3±122.8 25.3±18.8 79.8±106.5 13.9±17.9 4.35±3.07 0.74±0.72 Thurso 71.7±10.1 13.5±7.8 69.4±10.3 12.8±7.9 3.22±1.44 0.75±0.73 Tweed 127.8±66.6 33.9±36.0 89.7±57.0 18.9±10.3 5.93±5.00 0.40±0.35 Figure 63. Relationship between SAC mean salmon fry density estimates from depletion sites and SAC mean salmon fry numbers caught per minute at timed sites. After exclusion of the outlier (Oykel SAC) the relationship is described by the equation , log no. fry min-1 = -1.491 + 0.998 x log Zippin fry density, (d.f. =15, P<0.001, R2=0.78)

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4.4.2 Comparison of SAC densities with the national classification scheme Section 3.3.4 of this report presents a regional description of expected one-run minimum densities of salmonids partially corrected for variation in densities due to channel size, based on all the qualifying data held by the SFCC from 1997-2002. These were developed only using sites where at least some salmon were caught and Figure 16 shows the regional expectation for zero densities. We compare these expectations with the first-run of the SAC depletion fishings in Figure 64. These show a varied picture, with all SACs having some sites with populations both above and below the regional 50th percentile. Where no fish were caught sites appear at 100% below the 50th percentile. The Endrick and Moriston sites tended to fall below the 50th percentile, (though in both these cases most were necessarily located on channels outwith the SAC), while the Little Gruinard sites tended to fall above, but otherwise there was little sign of the SACs having either notably higher or notably lower than their regional expectation, particularly in view of the low precision associated with one-run fishings, and a possible bias in comparing the first-run of a depletion fishing with a single run fishing. Eleven of 14 SACs had lower than the regional rate of sites with absent salmon fry and parr (Table 144), the exceptions being the Teith (for both fry and parr), the Moriston (for both fry and parr), the Bladnoch (for parr) and the Naver (for fry). The number of sites at the SACs was too small for these to be regarded as representative values. In the case of the Bladnoch, forestry related acidification is implicated in the sites where zero salmon were caught. Table 144. Comparison of regional percentage of electrofishing sites with zero salmon 0+ and sites with zero salmon 1++ estimated from a one-run fishings and first-run fishings with the first run of the SAC depletion fishings.

SAC (n sites)

Salmon 0+ Salmon 1++ Statistical Region

Regional % zero density

SAC % zero density

Regional % zero density

SAC % zero density

Clyde Coast Endrick (n=6) 27.8 17 27.8 17 East Tay (n=12) 12.0 0 10.4 0 East Teith (n=7) 12.0 29 10.4 14 East Tweed(n=10) 12.0 0 10.4 0 Moray Spey(n=11) 19.9 9 11.5 0 Moray Moriston (n=6) 19.9 33 11.5 33 North B&L(n=6) 24.0 0 18.0 0 North Naver(n=6) 24.0 33 18.0 0 North Oykel (n=7) 24.0 0 18.0 0 North Thurso(n=7) 24.0 0 18.0 0 North East Dee(n=8) N/a 13 N/a 0 North East S.Esk(n=8) N/a 0 N/a 0 North West L.Gruinard(n=7) 35.7 0 29.6 0 Outer Hebrides Grimersta(n=5) 30.0 0 31.9 0 Outer Hebrides N.Harris(n=8) 30.0 0 31.9 0 Solway Bladnoch(n=6) 28.9 17 21.0 33

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Figure 64. Comparison of the first run minimum density estimate of the SAC depletion sites with 50th percentile of mixed one-run and first run minimum density estimates for the Salmon Fishery Statistical Region in which the SAC is sited (1997-2002). Only sites where fish were present contribute to the calculation of the 50th percentile, and it is corrected for river width class (see section 3.3.4). No data were available for the North East Region (South Esk & Dee).

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Figure 64 (continued)

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4.4.3 Variance in population densities: river saturation Population density at carrying capacity is often regarded as an indicator of habitat quality. However it can be a misleading one (Van Horne 1983) if, for example, areas with high population density are prone to stochastic extinctions. Variance in population sizes through time and space are other key measures. The limited evidence available for temporal variation on SACs only indicates that longer data sets are required. Spatial variation, however, can be more readily examined. High spatial variation in population density could be an early indicator of population decline, even while high quality habitat remains saturated. If the kinds of sites that have been selected for depletion fishings by biologists represent high quality habitat, then a range of such sites might be the very last areas of a river to indicate population decline. The coefficents of variation (CV) (s.d/mean) for fry and parr populations from depletion fishings are presented in Table 145 alongside the equivalent data for three-run minimum estimates. The three-run estimates tend to have higher CVs because, unlike the Zippin estimates, they do not exclude the variation from very low and zero densities, which are of particular interest, thus the CVs based on minimum density estimates are the most informative. Fry numbers had higher variance than parr numbers, probably reflecting the smoothing effect of the density dependent factors that have had longer to act on parr. The Teith and the Bladnoch stand out as having high CVs for parr (with an apparent high value for the Tweed being generated by one doubtful zippin estimate, based on minimum density estimate the Tweed had moderately CV for parr). In the case of the Bladnoch, this can be readily attributable to the acidification of parts of the upper catchmnets post-afforestation. The Grimersta, South Esk and Naver SACs had low CVs for parr density, indicating reasonably constant densities throughout the sampled sites. Table 145. Coefficients of variation from depletion density estimates and from three-run minimum estimates together with the percentage of sites with no fish caught in 0+ and 1++ age categories. SAC Depletion

Coeff. Variation Three-run minimum

Coeff. Variation % sites with salmon

age class absent 0+ 1++ 0+ 1++ 0+ 1++ B&L 0.63 0.34 0.63 0.54 0 0 Bladnoch 0.77 0.61 1.18 1.03 17 33 Borgie N/a N/a N/a N/a N/a N/a Dee 0.97 0.43 1.27 0.46 0 0 Endrick 1.00 0.76 1.78 0.80 33 17 Grimersta 0.83 0.37 0.90 0.24 0 0 L.Gruinard 0.59 0.45 0.55 0.49 0 0 Moriston 0.92 0.34 1.41 0.82 33 33 Naver 0.69 0.35 1.09 0.35 0 0 N. Harris 0.62 0.51 0.70 0.60 0 0 Oykel 0.67 0.49 0.80 0.61 0 0 S. Esk 0.65 0.32 0.68 0.35 0 0 Spey 1.07 0.64 1.41 0.79 9 0 Tay 1.12 0.54 1.17 0.79 0 0 Teith 0.75 0.74 1.33 1.29 28 14 Thurso 0.14 0.58 0.15 0.62 0 0 Tweed 0.52 1.06 0.63 0.55 0 0

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If the CVs reflect the status of the catchment, then we should anticipate a correspondence between with the CVs of the timed fishing numbers for each SAC. Table 146 shows the coefficients of variation for timed fishing numbers. There was a no significant relationship between CVs of 3-run and timed fishings for fry (P<0.4) nor for parr, though there was a weak trend towards a positive correlation in this latter case (P<0.1) Amongst the timed fishings (in contrast to depletion estimates) it was notable that the CVs of parr density were not significantly lower than the CVs of fry density (as predicted by density dependent population effects. It is likely that this results from a lower capture efficiency for parr using the timed fishing method. High variance in population density amongst sites, particularly in parr, could indicate high variation in the carrying capacity of the sites. If this were the case stable parr populations within sites across years would be anticipated (as seen in the historical data presented above for the Tweed). Alternatively, high variance in populations could indicate lack of habitat saturation, in which case variation within sites across years should be more variable. Finally high variance in between site density could reflect a natural, patchy distribution of spawning sites. In such cases a particulary big difference between fry and parr CVs could be anticipated, as shown by the Dee and the Grimersta. Table 146. Coefficients of variation and percentage of sites with no fish caught in 0+ and 1++ age categories from numbers caught in timed fishings. SAC Timed Fishings 0+ CV 1++ CV % 0+ absent % 1++ absent B&L 0.71 0.63 0 11 Bladnoch 0.92 0.73 11 0 Borgie N/a N/a N/a N/a Dee 0.55 0.92 14 14 Endrick 0.57 0.98 0 33 Grimersta 0.89 0.52 13 50(43) L.Gruinard 0.57 0.81 9 9 Moriston 1.37 0.93 33 22 Naver 0.71 0.58 0 0 N. Harris 0.41 0.59 0 0 Oykel 1.27 0.78 57 14 S. Esk 1.00 1.00 10 10 Spey 0.93 0.86 0 13 Tay 0.86 0.88 0 0 Teith 0.71 0.98 18 36 Thurso 0.45 0.97 0 18 Tweed 0.84 0.87 0 14 4.4.4 Variance in local habitat densities: site saturation 4.4.4.1 Introduction Just as variance between sites can be informative about river saturation, so, on a smaller spatial scale, variance within sites can be informative about habitat saturation. Apart from regional variation, and variation due to stream size and time of year, the key explanatory variables from salmon population density models in Section 2 were substrate and flow-type. Density was positively correlated with boulder-cobble size substrate, and with run and riffle flow types. This was not unexpected given previous

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research into salmon habitat preferences (Armstrong et al. 2003; Heggenes 1990; EU Life in Rivers Project 2001). There is particular evidence supporting the view that riffle-type flow represents preferred habitat, with most parr territories being located in riffles (Okland et al. 2004), although other habitats are used. Given a range of habitat types of varying profitability, the distribution of animals within the overall habitat can be informative. Where saturation of the habitat is high all habitat types are expected to be occupied, whereas low overall population densities may lead to the less-preferred habitat types being unoccupied. The Ideal Free Distribution (IFD) (Fretwell & Lucas 1979) is one in which each individual is able to locate itself wherever its most profitable position is. Such a situation would, at low overall densities, lead to the less profitable habitat types being empty, but lead, with increasing densities to a situation in which even less preferred habitats were used, albeit at lower densities than the favoured habitat. However, where territorial behaviour is present, distributions of animals vary away from the IFD toward the Ideal Despotic Distribution (IDD), under which subdominant animals may be forced into sub-optimal habitat even where overall population densities are low. The flexibility of territorial behaviour in salmonids is debatable, but Okland et al. (2004) have reported considerable overlap of territories in Atlantic salmon and flexibility in habitat use, suggesting that an IDD distribution is an unrealistic expectation. Bult et al (1999) have shown that pool- use by salmon was relatively higher at higher population levels, suggesting that the pattern of distribution of salmon in streams does indeed change with population density. The conclusion from the foregoing is that where populations are saturated sub-optimal habitat types will be occupied, and but where populations are not saturated, and declining, such areas are likely to become empty first, possibly before changes in density become apparent in more favoured habitats. We sought to quantify the approximate use of habitat features thought to be important to salmon. We used flow type rather than substrate type because the former is more easily distinguished prior to getting into the river. We sought to determine whether salmon in the SACs were distributed according to the expectations of previous research (namely lower densities in glides and higher densities in riffle and runs) by examining population density in adjacent stretches of glide, run and riffle flow types. If variation between population densities in these three flow types is found to exist we assume that this reflects habitat suitability, and use this to test a hypothesis regarding habitat saturation by salmon populations. We reason that the degree of departure away from population saturation will tend to be reflected in overall populations density, so that where densities are lower we expect to find a proportionally lower use of the sub-optimal habitat. 4.4.4.2 Results and discussion The mean proportions of salmon fry and parr caught in the three flow types are shown in Figure 63. There was a consistent pattern of capture across the rivers, particularly for parr, in which salmon were least commonly caught in glides and most frequently caught in riffles. The only striking exception to this general trend for parr was on the Borgie and this was probably merely an consequence of the small sample size (only 6 fry and 8 parr were caught at the single site surveyed). Two further slightly unusual distributions, those for North Harris and the Grimersta, may have been related to the use of scoop nets rather than banner nets at these sites. The more variable distributions for fry, may reflect their subdominance to parr (and to trout).

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Figure 65. The mean proportions of a) salmon 0+ and b) salmon 1++ caught in glide, riffle and run habitats in the timed sites on 14 SACs. In general riffles had the highest numbers of both age categories, and glides the lowest. The data for Borgie are less reliable, being based on one site only. a)

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We rejected the notion that the distribution of salmon amongst the flow-types might simply be an artefact of ease of capture by examining the equivalent capture rates for trout, and of the number of fish reported as seen but not captured. A total of 1023 trout were caught: 304 in glides, 394 in runs and 325 in riffles (the equivalent figures for salmon were glide 1747, run 2474, riffle 2962. A total of 1094 fish were seen but not caught: 349 in glides, 369 in runs, and 376 in riffles. Together these data suggest that features other than catchability influence the distribution of fish caught in the

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three flow types. Given that the number of fish seen and not caught was highest in riffles and lowest in glides (where fish were probably respectively hardest and easier to see), the figures we collected here may understate the true difference in the use of these habitat types by salmon. Ideally, to address the issue of habitat saturation influencing the relative use of sub-optimal habitat (glides) we would analyse the proportional use of each site with regard to the total numbers at the site. However, where fish numbers are low, the reliability of proportional data declines, and, in this case, exclusion of the unreliable estimates of flow-type use would leave only the highest density individual sites, thus removing the ability to detect the relationship of interest. Instead we adopted a SAC mean approach, totalling the numbers of parr and fry for all the sites in a SAC and calculating the mean proportional use of each of the flow types. We then compared this with the mean number of fry and parr in the sites in the SAC. While losing degrees of freedom, this approach avoids any risk of pseudo-replication, while at the same time weighting the analysis in favour of the sites with the most reliable estimates. There was no significant relationship between the proportional use by salmon fry or parr of glide, run or riffle and mean fry numbers (Figure 66), nor were the proportions used by fry influenced by mean parr numbers. Most importantly the key relationship predicted if habitat is unsaturated, a positive relationship between glide use and mean numbers, did not emerge (P<0.47 for fry, P<0.91 for parr). Accordingly our results support the view that glide flow-type areas are not favoured by juvenile salmon while riffle flow-types are, but they do not provide any evidence to support the view that the rivers and sites here with low densities are necessarily performing below habitat saturation levels for salmon.

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Figure 66. Relationships between mean numbers of parr caught across timed sites in a SAC and the mean proportion of parr caught in the flow-types a) glide, b) run and c) riffle. Proportional habitat use was not related to average population density a) b) c)

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4.5 Statistical power of the monitoring programme A key output of any preliminary monitoring scheme must be an assessment of the ability of the scheme to detect future changes, and to advise on any excess or shortfall in the sampling effort. We give here a power analysis of the data collected at the depletion sites on the SACs. Traditionally, biologists have regarded Type I Errors, α, (the false rejection of a null hypothesis) as more serious than Type II Errors, β, (the false acceptance of a null hypothesis), and hence much emphasis has been placed on the P value (a measure of the confidence we have in rejecting the null hypothesis) that a statistical test generates. This emphasis on not falsely rejecting a null hypothesis (though at the cost of frequently falsely accepting a null hypothesis) has perhaps been accepted because it appears to mirror the rigorous approach of logical positivism: hypotheses can only be disproved, not proved. In ecology however, most hypothesis-testing is statistical rather than scientific (Quinn & Dunham 1983), and false acceptance of a null hypothesis may be just as serious a concern as false rejection (Toft & Shea (1983). Failure to recognise a large change in salmon populations would be disastrous for a conservation monitoring programme, whereas false detection of a non-real change might merely be expensive. The avoidance of Type II errors is a question of statistical power. Because of the emphasis on P levels (α), statistical power (1-β) is often overlooked, and there is no equivalent in the biological literature to the universally accepted value to the 0.05 value for α, although many authors regard 0.20 as the conventional value for β (Cohen 1980). In effect this is a tacit acceptance that Type II errors are four times less important than Type 1 errors, which is an assumption that should be examined in each particular case. The statistical power of tests is principally influenced by the sample size, the variance in the sample, and the size of difference between two means (the effect size) that is required to be detected. Given an agreed effect size and a knowledge of inherent variation in the measurements, the number of samples (in this case, monitoring sites) that are required to determine a ‘genuine’ (α=0.05) difference (ie the pre-determined effect size of interest) or a ‘genuine’ absence (β=0.20) of difference. Table 147 shows the likely numbers of samples required between two years to detect a 50% decline in (ie halving of) mean population density, assuming that the coefficient of variation remains constant, for three power levels, β=0.5 (representing a 50% chance of failure to detect the 50% population decline), β=0.2 (the conventional level at which statisticians accept Type II Error) and β=0.05 (setting the acceptance of Type II Error at the conventional rate at which biologists accept Type I Error). There is considerable variation in the sampling requirements consequent on the different levels of between-site variation in the SACs. What is evident, however is that reducing the risk of a Type II Error to the level at which Type I Errors are accepted is unrealistic for many of the SACs. On the other hand, achieving the conventional level of power, β=0.2 is a realistic prospect, particularly for parr. If the between site variation observed in the current report are assumed to be a relatively constant feature of the SAC, then SACs can be targetted according to this sort of analysis: Berriedale & Langwell, Little Gruinard, Moriston, Naver and South Esk all require slightly fewer depletion sites than were fished to detect a 50% decline in parr populations at β=0.20, whereas most other SACs would require more sites, particularly the Tweed the Endrick and the Teith.

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Table 147. Depletion site sample sizes required to detect a 50% decline (with constant coefficient of variation) in juvenile salmon populations (0+ and 1++ age classes) on the SACs based on observed variation and for three levels of statistical power, with α held at 0.05 throughout. To achieve the power indicated the each survey year requires the number of sample sites indicated. Number of sites required SAC β=0.50 β=0.20 β=0.05 0+ 1++ 0+ 1++ 0+ 1++ Berriedale&Langwell 8 3 16 5 26 8Bladnoch 12 8 24 15 39 25Dee 18 4 36 8 61 13Endrick 20 12 40 23 66 38Grimersta 14 3 27 6 45 9Little Gruinard 7 3 14 6 23 11Moriston 17 3 34 5 55 8Naver 10 3 19 5 31 8North Harris 8 6 18 11 26 18Oykel 9 5 18 10 30 16South Esk 9 2 17 4 28 7Spey 22 8 44 16 74 27Tay 25 6 50 12 83 20Teith 11 11 22 22 37 37Thurso 1 7 1 14 2 22Tweed 6 22 11 44 18 74 Table 148. Depletion site sample sizes required to detect a 50% decline from the actual data (with constant coefficient of variation) in juvenile salmon populations (0+ ans 1++ age classes) on the SACs based on observed variation and for three levels of statistical power, with α held at 0.05 throughout. SAC Number of

sites 2004/2005

Number of sites required in subsequent year

β=0.50 β=0.20 β=0.05 0+ 1++ 0+ 1++ 0+ 1++ Berriedale&Langwell 6 250 1 ∞ 3 ∞ ∞ Bladnoch 6 ∞ 28 ∞ ∞ ∞ ∞ Dee 8 ∞ 2 ∞ 6 ∞ ∞ Endrick 6 ∞ ∞ ∞ ∞ ∞ ∞ Grimersta 5 ∞ 1 ∞ 9 ∞ ∞ LittleGruinard 7 6 2 ∞ 16 ∞ ∞ Moriston 6 ∞ 1 ∞ 3 ∞ ∞ Naver 6 ∞ 1 ∞ 3 ∞ ∞ North Harris 6 ∞ 4 ∞ ∞ ∞ ∞ Oykel 8 14 2 ∞ 25 ∞ ∞ South Esk 7 20 1 ∞ 2 ∞ 6 Spey 11 ∞ 4 ∞ ∞ ∞ ∞ Tay 12 ∞ 2 ∞ 11 ∞ ∞ Teith 7 ∞ ∞ ∞ ∞ ∞ ∞ Thurso 7 1 6 1 ∞ 1 ∞ Tweed 10 2 ∞ 15 ∞ ∞ ∞

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Given that in many cases the present sampling programme did not achieve the required number of sites, the actual sampling effort required to detect a 50% decline in population density given the number of sites that were fished in 2004/2005 is shown in Table 148. Again it is evident that detecting changes of this size amongst fry is unrealistic at a reasonable level of power for a given SAC. Even for parr at some of the SACs (Bladnoch, Endrick, North Harris, Spey, Teith and Tweed) at the conventional power level it is likely to be impossible to detect a 50% decline in stocks. Table 149. Depletion site sample sizes required to detect a 100% increase (with constant coefficient of variation) in juvenile salmon populations on the SACs based on observed variation and for three levels of statistical power, with α held at 0.05 throughout. To achieve the power indicated the each survey year requires the number of sample sites indicated Number of sites required SAC β=0.50 β=0.20 β=0.05 0+ 1++ 0+ 1++ 0+ 1++ Berriedale&Langwell 8 3 16 5 26 8Bladnoch 12 8 24 15 39 25Dee 18 4 37 8 61 13Endrick 20 11 40 23 66 37Grimersta 14 3 28 6 45 9LittleGruinard 7 4 14 8 23 13Moriston 17 3 34 5 55 8Naver 10 3 19 5 31 8North Harris 8 6 16 11 25 18Oykel 9 5 18 10 30 16South Esk 9 2 17 4 28 7Spey 22 9 44 17 74 28Tay 25 6 50 12 82 20Teith 11 11 23 22 37 36Thurso 1 7 1 14 2 22Tweed 6 22 11 45 18 73 Detection of a 100% increase in numbers would require a very similar sampling effort, (Table 149), and detection of an increase in population density as small as 50% is unrealistic. However, the failure to reject a null hypothesis where a population is increasing is a less serious concern than a failure to detect a decreasing population. Here the β level of 0.5 might be regarded as acceptable, in which case the present number of sites would be adequate in the majority of cases to detect large changes in parr population density (Table 150).

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Table 150. Depletion site sample sizes required to detect a 100% increase from the actual data (with constant coefficient of variation) in juvenile salmon populations (0+ and 1++ age classes) on the SACs based on observed variation and for three levels of statistical power, with α held at 0.05 throughout. SAC Number of

sites 2004/2005

Number of sites required in subsequent year

β=0.50 β=0.20 β=0.05 0+ 1++ 0+ 1++ 0+ 1++ Berriedale&Langwell 6 9 2 26 5 140 9 Bladnoch 6 15 8 85 24 ∞ 105 Dee 8 26 4 350 8 ∞ 14 Endrick 6 44 14 ∞ 66 ∞ ∞ Grimersta 5 23 3 ∞ 7 ∞ 11 LittleGruinard 7 7 4 18 9 50 17 Moriston 6 29 2 ∞ 5 ∞ 9 Naver 6 11 3 40 6 ∞ 9 North Harris 6 8 5 25 13 114 32 Oykel 8 9 5 26 10 88 20 South Esk 7 9 2 25 4 97 7 Spey 11 30 8 192 20 ∞ 44 Tay 12 33 5 230 12 ∞ 23 Teith 7 13 13 49 46 ∞ ∞ Thurso 7 1 7 1 17 2 46 Tweed 10 3 31 11 320 22 ∞ Table 151. The power to detect a 50% decline in juvenile salmon numbers assuming a repeat of the sampling effort of 2004/2005. SAC 1-β % 0+ 1++ Berriedale&Langwell 42.0 89.4Bladnoch 29.4 43.6Dee 25.9 83.5Endrick 19.4 30.2Grimersta 23.1 76.8Little Gruinard 52.4 75.1Moriston 22.2 89.5Naver 35.5 88.1North Harris 41.6 56.3Oykel 46.8 74.0South Esk 44.7 96.0Spey 28.6 64.1Tay 28.0 81.2Teith 35.0 35.4Thurso 100.0 52.9Tweed 77.7 26.4 A simple way of increasing the level of power of a statistical test is to increase the level of α at which we reject the null hypothesis. Changing the level of α from 0.05 to 0.1 in effect doubles the statistical power of a test. This might be regarded as outrageous by some, but there is no theoretical underpinning of the conventional value of α: it is simply a balance that has to be made, and the balance should be flexible in the light of the relative seriousness of falsely accepting or falsely rejecting the null hypothesis. It is clear, however, that without such an adjustment, the level of

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sampling in the present study delivers, in the majority of cases, inadequate power to detect a 50% decline in populations between years (Table 151). Only on the Thurso for fry, and the Berriedale & Langwell, the Dee, Moriston, Naver, South Esk and Tay for parr, and can the conventional level of β be expected to be achieved (with several other SACs approaching close to the conventional power). Similarly, to detect a 100% increase in population density at the individual SAC level, a repeat of the current sampling programme would be likely to have power at the conventional level for same set of rivers (Table 152). Table 152. The power to detect a 100% increase in juvenile salmon numbers assuming a repeat of the sampling effort of 2004/2005. SAC 1-β % 0+ 1++ Berriedale&Langwell 41.5 89.3Bladnoch 29.4 43.0Dee 25.8 83.2Endrick 19.4 30.7Grimersta 22.5 77.2Little Gruinard 52.3 75.5Moriston 22.2 89.5Naver 35.4 87.8North Harris 42.3 56.9Oykel 47.0 74.0South Esk 44.8 96.0Spey 28.5 62.2Tay 28.1 81.6Teith 35.0 35.8Thurso 100 53.5Tweed 77.4 26.6 If population declines take the form of increased patchiness rather than general reduction in density, then the number of Zippin estimates that could be calculated would similarly decline, effectively reducing the sample size and so requiring further increases in site numbers. Under these circumstances population monitoring might be better served by greater numbers of lower intensity sites, yielding greater spatial coverage, akin to the timed sites in the present study. Use of the Carle & Strubb (1978) method of depletion calculation rather than Zippin would generate estimates for all sites, but at the cost of increased uncertainty in the mean value. High confidence intervals about depletion estimates will necessarily entail higher variance about the estimated average densities. Part of the reason for the high number of sites required to achieve given power levels for parr on the Tweed (Table 147, 148) is due to the low confidence associated with one of the Zippin estimates. The evidence from historical data on juvenile salmon population sizes is that inter-annual variation at sites can be large, particularly for fry, and is certainly so large that the short time-series presently available is inadequate to detect the next scale of population change. Whether this reflects inherent annual variation more than sampling error is uncertain, particularly so given that many of the estimates are only semi-quantitative. Instituting annual fully-quantitative monitoring sites would go some way toward addressing the concerns about sampling error, but could not eradicate them entirely.

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The analysis of rod-catch data indicates the value of long-term data sets, but there are concerns that in the future rod-catch statistics will become increasingly compromised as a continuous time-series due to the effects of the introduction and adoption of catch and release schemes. This focuses attention on a crucial part of any long-term monitoring effort: the need to ensure that methodologies are constant both in time and space. To this end it may be that increased effort should be devoted to determining variability between individual monitoring staff and equipment. While much effort has been expended into ascertaining effects of electrofishing on fish, both physiological (Schreer et al 2004, Schnyder 1995, Thompson et al 1997) and behavioural (Mesa & Schreck 1989, Nordwall 1999,Young & Schmettering 2004), very little has been done to investigate the reliability and repeatability of estimates of population size from electrofishing. In part this is because the research into the effects of electrofishing on fish has demonstrated that repeat fishings at a site are inadequate to test the repeatability of electro-fishing estimates, due to changes in fish behaviour and distribution post-electroshock. Thus only a controlled experimental environment can properly address the question of the quality of electrofishing population estimates. However, what is much more problematic in the present analysis is to determine both the timescale and the number of samples along that time-scale that are necessary before a statistical difference detected between years becomes meaningful. The power calculations above cannot inform these considerations. Here the driving issues are firstly the timescale over which action (whether reportage or direct) is expected, and secondly the underlying noise inherent in salmon population densities. Inter-annual variation in reported population size is a near-given in biology, reflecting either observer error or stochastic variability. Generally the next scale at which trends across years are discernible is regarded as a true population change. However, there may be trends of increase or decrease on a larger scale that are part of inherent population dynamics of a species, rather than a cause for concern. Here strategic and political considerations must play a driving role in the design of sampling strategies.

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5 ADULT ATLANTIC SALMON POPULATION ASSESSMENT OF 17 DESIGNATED SACS. Authors: J.C. MacLean and J.L. Thorley 5.1 Introduction We will first review our current understanding of salmon population structure and then consider the types of assessment information that are both (a) available and (b) appropriate. 5.2 Salmon population structure The term “population” is now widely, and loosely, used to describe various groupings of individuals. Salmon assessment biologists use the following definition of populations “A group of interbreeding individuals which possess a common gene pool and which are reproductively isolated (temporally or spatially) from other groups of interbreeding individuals” (Ricker, 1975; ICES, 1996). Genetic studies have demonstrated population structuring in Atlantic salmon (Salmo salar L.) at sub-catchment scales (Jordan et al. 1992; Jordan et al., 1997; Garant et al. 2000). Structuring is maintained by homing which was shown to be precise within several kilometres for a substantial proportion of Atlantic salmon captured at a tributary site in the River Dee in Scotland (Youngson et al., 1994). Studies of this type are few but similar precision was reported for the Pacific salmon species, Oncorhynchus nerka L., in Illamna lake, Alaska and lake Washington, Washington (Quinn et al. 1999). Migratory behaviour differs for fish returning to different natal locations. Run-timing (the date on which adult salmon return to fresh water) is a heritable trait that varies among rivers (Hansen and Jonsson, 1991) and among sub-catchment populations (Quinn et al. 2000; Stewart et al. 2002, Stewart et al. submitted). Within river catchments, run-timing correlates with the spatial distribution of salmon at spawning time. This was first demonstrated for the Northwest Miramichi catchment by Saunders (1967) using sequential fish-traps and confirmed in separate studies of several Scottish rivers using radio-tracking (Laughton and Smith 1992; Walker and Walker 1992; Webb and Campbell 2000). As a general rule, earlier running fish within both the 1SW and 2SW sea-age groups travel greater distances up-river, to spawn at higher elevation locations more distant from the sea. The relationships between run-timing and spawning location can therefore be considered to link run-timing with membership of sub-catchment populations. Thus, any adult salmon assessment must be based in the context of the within-river population structure that drives the productivity and diversity of the resource. 5.3 Adult salmon population assessment options There are several adult population assessment techniques currently used in Scotland, each with its own advantages and disadvantages and these are summarised below. All provide indicators that will vary, to some degree with abundance. Ideally, any indicator of abundance would be compared to other indicators but this is seldom possible. We have restricted ourselves to assessment methods concerned with adult fish although we acknowledge that indicators at other stages of the life cycle, for example, juvenile density estimates, can also be informative.

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5.3.1 Fish counters Several types of fish counter are available and these include resistivity, infra-red and hydro-acoustic examples. The most common type utilised in Scotland is the resistivity counter followed by infra red counters (Thorley et al. submitted). Fish counters can provide good information and are capable of operating throughout the year. In essence they provide a count of adult salmon for the area above the counter site. Resistivity counters are generally deployed on a fixed, purpose built weir and have the disadvantage of being expensive to install. The scope for installing infra red counters is restricted as they require migrating adults to be constrained to a narrow channel and therefore are best deployed in existing structures such as fish ladders and on small spawning burns. Currently there are 29 fish counters deployed in Scotland and thus the national coverage is patchy (Simpson, 2003) and, more relevant in the context of this report, they do not provide information for all the SAC areas. 5.3.2 Fish traps Fish traps are operated in some locations in Scotland and provide reliable counts of fish movement. While they are usually cheaper, in terms of capital cost, than fish counters they are labour intensive in terms of running costs. Again the national coverage is sparse, with only 21 being deployed in total (Simpson, 2003), and further they do not provide information for all the SAC areas. 5.3.3 Redd counts Redd counts are a traditional assessment method. Records exist for many spawning tributaries in Scotland and they have the advantage that the cost of collection is low. Unfortunately there are several disadvantages with this assessment method the major problem being that the relationship between redd number and the number of females producing the redds varies and is not one to one (Taggart et al. 2001). 5.3.4 Fishery catch statistics Fishery catch statistics are also a source of assessment information and have the advantage that they have been systematically and comprehensively documented since 1952. Throughout the time series the netting industry, which is restricted to fixed localities on the coast or in estuaries has been in decline. In contrast, the rod and line fishery continues to be pursued across all river catchments that support salmon populations. Thus the rod and line fishery catch resource has the advantage that it provides good geographic coverage of the country and further, it is collected at a fine scale level both temporally (by month) and spatially (by fishing beat), that corresponds to our current understanding of salmon population structure. There are however some limitations in the use of rod catch statistics. Firstly, catch will vary with exploitation, which in turn will be dependent on the effort expended. Unfortunately, no effort data is available and given that the type of effort deployed is strategic, rather than passive, and that the efficiency of effort will vary within and among fisheries, the derivation of a useable index for the future appears remote. Secondly, there is the possibility of misreporting which may arise due to a number of unsubstantiated factors.

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The usefulness of rod catch statistics has been previously explored by several authors. For example, Youngson et al (2002) analysed the rod catch, in the early months of the season, from seven major Scottish east coast rivers. The similarities in trends across both spatial and temporal scales led to the conclusion that the most likely factor driving catches was indeed abundance. Other studies have directly assessed the value of rod catch data at selected sites through comparison with fish counter data (e.g. Beaumont et al., 1991; Crozier and Kennedy, 2001) and have shown that the two abundance indicators are closely related. More recently, Thorley et al. (submitted) have shown the trends in the district-level rod catches to be in broad agreement with the trends in the automatic fish counters at 11 of 12 sites. Thus, the rod and line catch database has therefore been used to assess the adult salmon populations in the 17 designated SACs. This study describes the trends in seasonal rod catches for each of the 17 SACS and interprets the results to provide a population assessment on three separate seasonal run-timing groups of salmon. 5.4 Methods 5.4.1 Catch information

Data analyses are based on reported rod and line catches. A national database of the proprietors of individual fisheries in Scotland is maintained by Fisheries Research Services. Catches are reported by the proprietors/occupiers of the three legal types of salmon fishery, namely: fixed engine, net-and-coble and rod and line. At the end of the fishing season each year, individual proprietors are mailed a request, now under the terms of the Salmon and Freshwater Fisheries (Consolidation) (Scotland) Act 2003, for the data that they have compiled on a monthly basis for the completed season. Information from individual fisheries is amalgamated and stored in 109 fishery districts. Consequently, catch information for defined areas other than the fishery districts is not readily available. Therefore, the catch information used to assess the SACs is the relevant fishery district. Table 153 shows the fishery district appropriate for assessment of each SAC. Note that the River Borgie and River Naver SACs both lie within the Naver fishery district and consequently, the Naver fishery district catch has been used to assess both these SACs.

Catch and release was not a strong feature of the Scottish sports fisheries in the past. However, in recent years (since the mid 1990s), catch and release has been strongly advocated by angling and conservation groups, increasingly practised voluntarily and, for some fisheries, formally adopted as local policy. Proprietors/occupiers have been providing information on the number of fish caught and released since 1994. Catch and release was initially directed towards the early season fisheries as it became increasingly evident this sector of the catch was in decline but has now become common throughout the fishing season. For the purposes of this report, those fish released have been summed with those retained.

Salmon catch information lends itself for adult population assessment as it has been systematically collected, is available for all 17 SACs and has been shown to relate to other indicators of abundance. However there are also some disadvantages, for example, misreporting and misclassification of grilse as salmon. This latter problem is of particular concern when both grilse and salmon occur in the catches at the same time (June onwards) and has yet to be resolved. Therefore the trend analyses presented here make no distinction between the two age categories and one sea-winter (1SW) and multi sea-winter (MSW) salmon are combined.

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Due to the small number of salmon reported in some months in some fishery districts the analyses were performed on three seasonal components of the catch. The spring component was defined as those fish caught in the months January to May, the summer component as those fish caught in the months June to August and the autumn component as those fish caught in the months September and October. Note that no analysis was possible in the Resort and Fincastle fishery districts (North Harris SAC) for the spring component as fish were reported in only a few years over the period considered.

5.4.2 Statistical analyses

Catch data in general tend to follow a Poisson rather than a normal distribution. In such distributions the mean is equal to the variance. To normalise the variance (ie. so that the mean is independent of the variance) the catch data sets were square root transformed (Sokal and Rohlf, 1995; Chatfield, 1996).

A cubic smoothing trend line with three degrees of freedom was fitted to each time series of catch data (the three seasonal components for each of the 16 fishery districts representing the 17 SACs). The exact curvature of the smoother can be adjusted by varying the degrees of freedom used in the fitting procedure. Using three degrees of freedom, for each catch series, had the desired outcome of capturing the underlying trend whilst leaving negligible autocorrelation (Chatfield, 1996) in the residuals (which could be taken as independently and normally distributed with constant variance).

An F-test was performed to determine whether the fitted trend line was significantly different from a straight line through the mean. A reference band, in this case an approximate 95% point-wise reference band (Bowman & Azzalini, 1997), was superimposed on the trend line to indicate both the timing and nature of significant differences. As a general rule, where the fitted trend line is outside the reference band there is a significant difference. To aid interpretation and ensure the confidentiality of the catch returns, the time series, trend lines and reference bands where back-transformed to the original scale and then divided by the mean prior to plotting. Finally, a comparison between the catch levels at the start of the time series (1952) was made with the catch level at the end of the series (2002) to provide an overview of the direction and magnitude of any change in catch over the period.

5.5 Results

Results of the F-test to determine whether the trends were significantly different to a straight line through the mean are given in Table 154. Of the 47 comparisons (three seasonal components for 16 districts with the exception of the North Harris spring component) only six were not significant. This clearly indicates that trends exist in most of the data sets as opposed to catch values fluctuating around a mean value.

Reference to Figure 67 provides information on the nature of the trends and further, highlights the location(s) in the time series where the trend line is significantly different from the long-term mean.

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Table 155 shows the results of a comparison of magnitude and direction of change in catches in a comparison between the values at the beginning of the time series (1952) with those at the end (2002).

The results of the analyses provide a description of changes in catch over time and also permit an assessment of the current status of each seasonal group in each district in relation to the long term mean. The current status of the populations can be inferred from the position of the trend line in relation to the 95% reference bands in the later years of the time series. If the trend line lies within the reference band the current status may be described as stable, if the trend line lies above the reference bands the current status is judged to be above the long term mean and if the trend line lies below the reference bands the current status is determined to be below the long term mean. 5.5.1 Spring component Significant trend lines were observed in 13 of the 15 datasets examined, the exceptions being Berriedale and Clyde. The location of the significant differences varied among datasets but in all cases present catch level is less than that at the beginning of the time series. The current status of the catch in comparison to the long term mean can be described as follows: Above: None Stable: Berriedale, Bladnoch, Clyde, Forth, Gruinard, Thurso Below: Dee, Kyle, Loch Roag, Naver, Ness, South Esk, Spey, Tay, Tweed 5.5.2 Summer component Significant trend lines were observed in 12 of the 16 datasets examined, the exceptions being Bladnoch, Clyde, Dee and Thurso. The location of the significant differences varied among datasets but in 11 of these datasets present catch level is greater than that at the beginning of the time series. The current status of the catch in comparison to the long term mean can be described as follows: Above: Berriedale, Forth, Kyle, Tay, Tweed Stable: Bladnoch, Clyde, Dee, Gruinard, Loch Roag, Naver, Ness, Resort & Fincastle, South Esk, Spey, Thurso Below: None 5.5.3 Autumn component Significant trend lines were observed in all 16 datasets examined. The location of the significant differences varied among datasets and in 14 cases the present catch level is greater than that at the beginning of the time series. The current status of the catch in comparison to the long term mean can be described as follows: Above: Bladnoch, Dee, Forth, Kyle, South Esk, Tweed Stable: Clyde, Gruinard, Loch Roag, Ness, Resort & Fincastle, Spey, Tay, Thurso Below: Berriedale, Naver

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Table 153. The 17 SACs and the associated fishery districts from which catch information was used in the adult population assessment. SAC name SAC code Fishery district

Berriedale & Langwell Waters UK0030088 Berriedale River Bladnoch UK0030249 Bladnoch River Borgie UK0012995 Naver Endrick Water UK0019840 Clyde River Dee UK0030251 Dee River Teith UK0030263 Forth Little Gruinard River UK0030183 Gruinard River Oykel UK0030261 Kyle Grimersta UK0030255 Loch Roag River Naver UK0030260 Naver River Moriston UK0030259 Ness North Harris UK0012935 Resort & Fincastle River South Esk UK0030262 South Esk River Spey UK0019811 Spey River Tay UK0030312 Tay River Thurso UK0030264 Thurso River Tweed UK0012691 Tweed Table 154. Results of F-test to determine whether the trend lines fitted to the catch data were significantly different to a straight line through the mean value.

Fishery district

Spring component

Summer component

Autumn component

Berriedale NS <.001 <.01 Bladnoch <.001 NS <.0001 Clyde NS NS <.05 Dee <.0001 NS <.0001 Forth <.0001 <.0001 <.0001 Gruinard <.0001 <.0001 <.0001 Kyle <.05 <.0001 <.0001 Loch Roag <.0001 <.001 <.01 Naver <.0001 <.05 <.0001 Ness <.0001 <.05 <.0001 Resort & Fincastle NA <.05 <.01 South Esk <.0001 <.05 <.0001 Spey <.0001 <.0001 <.0001 Tay <.0001 <.0001 <.0001 Thurso <.0001 NS <.05 Tweed <.0001 <.0001 <.0001

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Table 155. The n-fold change and direction between recorded catch at the beginning (1952) and end (2002) of the time series considered.

Fishery district

Spring component

Summer component

Autumn component

Berriedale -1 11 -1 Bladnoch -3 1 23 Clyde -1 -1 3 Dee -6 -1 1 Forth -2 4 8 Gruinard -12 2 2 Kyle -1 2 10 Loch Roag -20 -1 -1 Naver -3 1 1 Ness -1 1 2 Resort & Fincastle NA 2 2 South Esk -3 1 4 Spey -4 1 2 Tay -1 8 9 Thurso -2 1 1 Tweed -4 2 12 5.6 Discussion Major differences exist in the current status of catches, and by inference in the underlying populations, in each of the three seasonal components analysed. For the spring component, most datasets revealed current catches to be below the long term mean, some were at similar values and none were above the long term mean. In contrast, for the summer component, most datasets showed that current catch levels were consistent with the long term mean, a few were above and none were below. A similar pattern of categorisation was evident for the autumn component although in this case two datasets were found to be significantly below the long term mean. The categorisation of current catch levels into three groups (above, stable, below) shows no obvious geographic (e.g. east:west) pattern for any of the three run-timing components. The results of the rod catch analysis need to be interpreted with caution. In the case of the spring component, catch information does not allow any assessment of fish entering the rivers prior to the opening of the various fishing seasons. However, given the patterns in the Scottish rod catch shown by Youngson et al (2002), whereby steeper declines in the earlier months were demonstrated, our best assumption would be that these very early running spring salmon would also, in general, show a decrease in abundance in recent years. Further, the rod catch analysis and the associated inferences on the abundance of the underlying populations need to be considered in a wider context. There is evidence from monitored sites that marine survival has decreased in the last two decades (MacLean et al, 2000). As a consequence the commercial net fisheries have decreased their effort and have reported reduced catches thus allowing a greater proportion of the returning adults to enter Scottish rivers and to be available for rod exploitation. Essentially the reduction in net catches has acted as a buffer to the rod fishery with the result that rod catches do not fully indicate the downward trend in

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marine survival. However, the net industry has declined to such an extent (Anon, 2003) that this buffer for rod catches and (more importantly in the present context) for spawning escapement is almost exhausted. Therefore changes in rod catch levels in the coming years and, where possible, escapement, need to closely monitored. We have assessed the current level of salmon abundance with respect to longer term historical levels using rod catch as a proxy for abundance and have shown, in general, that the spring component is below and the summer and autumn components are the same as or above historical means. However, a critical question remains: Does the current level of adult abundance result in the juvenile carrying capacity of the freshwater habitats being attained? The answer to this will require comparisons of adult abundance and juvenile surveys at the appropriate spatial and temporal scales.

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Figure 67. Plots of standardised catches (annual values divided by the long term mean) including the fitted trend and 95% reference bands by component and by fishery district.

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6 LINKING ADULT AND JUVENILE SALMON POPULATION DATA. 6.1 Introduction On the rivers for which evidence is available, it is apparent that the spring salmon represent genetically distinct sub-populations (see section 5.2 for refs). Furthermore this sub-population is also spatially distinct (maintained by homing (Youngson et al 1994)) with spring-running adults tending to spawn in the upper reaches of catchments (Webb & Campbell 2000). This appears to be true for both large eastern and small western Scottish catchments (Laughton & Smith 1992, Walker & Walker 1992). Section 5 reports on the best available information on adult salmon catches for the SAC rivers. This takes the form of rod catch data from the past 50 years. This analysis indicates that the most severe evidence for decline in adult populations is amongst the spring running component. Accordingly, if adult numbers have declined to sufficiently low levels that juvenile populations are numerically compromised, it is amongst this sub-population that the results are most likely to be detected. However, the decline in spring-running adults is only apparent for some of the SACs (Borgie, Dee, Grimersta, Moriston, Naver, Oykel, South Esk, Spey, Tay and Tweed), with stable spring numbers in the remaining SACs (Berriedale & Langwell, Bladnoch, Endrick, Little Gruinard, Teith and Thurso) from the time-series analysis. No evidence was available for the North Harris SAC area. Accordingly, we anticipate that, if the adult numbers have declined to sufficiently low levels that juvenile numbers are affected, then lower juvenile numbers will be found amongst the upper reaches of those rivers with declining adult spring-running populations relative to those where there is no evidence of such a decline. Furthermore we anticipate that such an effect should be more marked amongst fry than amongst parr, because of density dependent survival. Our null hypothesis is that there is no difference in the relative abundance of juvenile salmon in the upper sections of SACs with Declining and Stable spring-running adults numbers. 6.2 Methods and Analysis The upper altitudinal limit of SACs is dependent on prior knowledge about the distribution of salmon populations in the rivers. Accordingly we determined upper limits using GIS, by overlaying SAC boundaries with OS Panorama contours and CEH/OS rivers, and using the limit as the basis for defining the expected zone in which spring-salmon spawn. We divided each catchment into two sections: the lower-middle (lowest two thirds of the altitudinal range of the SAC), and upper (upper third of the altitudinal range) sections. We then allocated each depletion site in an SAC to one of those sections, depending on its altitude. The altitudinal distributions of sites for the 15 SACs for which we had adequate information are shown in Figure 68. We encountered two problems. Firstly the distribution of sites where Zippin estimates were not calculable severely reduced the number of SACs for which estimates of density were available in the upper third of the catchment. In many cases this was where very few or zero fish had been caught. We therefore adopted the use of the three-run minimum estimates. Secondly, even when we adopted the three-run minimum density estimates there were no data points in the upper sections of the Endrick, Tay, Teith, and Tweed SACs. So that these could be included in the analysis, and to maximise the power to detect any effect of decline in the upper

210

catchment, we generated a second definition of upper and lower SAC sections, this time using the mid point of the SACs altitudinal range as the dividing point. This still left us without an estimate for the Tay, so in this case we obtained direct information about which sites were likely to be in areas of spring salmon spawning (David Summers, pers. comm.). For each method we calculated the mean density for both fry and parr in the lower and upper altitudinal ranges. To correct for variation in numbers between catchments we used the ratio of lower-middle:upper (or lower:upper) densities. Thus low ratios <1 indicate lower mean population in the lower reaches of the SAC, while ratios >1 indicate lower population densities in the upper SAC. We then ranked the ratios and used non-parametric statistics to assess the significance of the relationship between the status of spring adult populations and juvenile populations density. 6.3 Results Strong relationships between altitude and juvenile populations were scarce (Table 156); 0nly on the Tay was a significant (negative) relationship between fry and altitude observed, and amongst 1++ fish only two significant correlations were detected, one negative (Spey) and one positive (Tay) (both rivers with declining spring stocks), though only the relationship between parr and altitude on the Tay was significant following Bonferroni corrections for non-independent contrasts. Six of 16 correlations for 0+ and five of 16 correlations for 1++ fish were positive. There was no indication that negative relationships were more common amongst those SACs with declining adult spring salmon populations (Fisher’s Exact Probability Tests, all P >0.3). Table 156. Relationships between salmon fry and parr and altitude in the SACs. SAC Spring Adult Status Fry Parr Relationship

with altitude P< Relationship

with altitude P<

Berridale&Langwell Stable +ve 0.65 -ve 0.11 Bladnoch Stable -ve 0.68 -ve 0.24 Endrick Stable +ve 0.79 +ve 0.33 Little Gruinard Stable -ve 0.99 -ve 0.63 Teith Stable -ve 0.31 +ve 0.91 Thurso Stable +ve 0.95 -ve 0.89 North Harris Not known -ve 0.25 -ve 0.38 Dee Declining +ve 0.89 -ve 0.56 Grimersta Declining +ve 0.20 +ve 0.35 Moriston Declining -ve 0.39 -ve 0.32 Naver Declining +ve 0.75 -ve 0.21 Oykel Declining -ve 0.64 -ve 0.69 South Esk Declining -ve 0.25 +ve 0.31 Spey Declining -ve 0.63 -ve 0.04 Tay Declining -ve 0.04 +ve 0.001 Tweed Declining -ve 0.65 -ve 0.09 The mean rank of the ratios of lower-middle:upper (Fig 69 (a)) and of lower:upper (Fig 69 (b)) mean juvenile population densities are shown. There was no indication that upper catchment juvenile population densities were relatively lower on SACs with declining spring adult populations (determined from rod-catch statistics).

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Figure 68. Distribution of three-run population densities of salmon fry and parr with altitude in the SACs. The x-axis shows the full altitudinal range of the designated SAC, with the exception of the special case of the North Harris estate (which is not river-based) where the estimated maximum altitude that salmon reach is shown. The altitude range for the Little Gruinard is suspect as channels linking to the loch which forms the highest part of the SAC are not included in the SAC; on this graph an arrow marks the highest river channel included in the SAC. Arrows on the Tay graph indicate sites where spring salmon are thought to spawn (D.Summers, pers. comm.)

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Figure 68 (cont).

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213

Figure 69. Mean rank of the ratio of lower catchment to upper catchment salmon fry and parr population density in relation to the status of spring adult rod-catch data from the last 50 years. Higher mean ranks indicate relatively low juvenile population density in the upper catchment. The density estimate used for the analyses was the three-run minimum. a) shows the results when upper and lower are divided at the mid altitude point of the SAC, b) shows the result when the dividing point is between the lower two thirds of the SAC’s altitude range and the upper third. Each SAC contributes one rank for each of fry and parr. Sample sizes: a) 8 SACs for declining, 6 for stable, and 1 to unknown (North Harris); b) 6 for declining, 4 for stable, and 1 for unknown (North Harris). Neither analysis suggests a significant relationship between adult population status and upper catchment juvenile population density. a) b)

0

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6.4 Discussion The absence of evidence for a relationship between spring adult declines and juvenile population density meant that we could not reject our null hypothesis, that decline in adult spring populations has resulted in decline in juvenile populations of this component of the population. However, our analyses were based on small sample sizes, particularly for the upper sections of the SACs, and cannot be regarded as firm evidence for no effect of declining spring adult numbers on juvenile densities. Since there may be numerous local complicating factors in the distribution of spring spawners, such as the well-known favouring of particular tributaries in the Tweed system, it is likely that a crude analysis of this sort could detect only a very major effect. Furthermore, our analyses only considered numbers, and did not assess potential impacts on the age-structures of juvenile populations, which might be a more sensitive initial indicator. The simpler hypothesis, anticipating a more marked decline in juvenile population density along an altitudinal gradient within individual rivers where spring running salmon are in decline, could not be firmly formulated. This is because any effect of the decline in spring adult numbers may be ongoing and thus it is not possible to use previous SFCC data to correct for the independent effect of altitude on numbers. Furthermore, variation in the degree of access to upper reaches of rivers is likely to have a strong inter-annual component. For example, adult penetration to the upper reaches of many rivers may have varied markedly between the dry summer of 2003 and the wet summer of 2004.

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7 TOWARDS ATTRIBUTING SAC CONDITION STATUS Authors: J. D. Godfrey and J.C. Maclean 7.1. Juvenile stages To help SNH assign a condition status to each SAC we compared juvenile salmonid densities in the SACs with the National River Classification scheme (developed in Chapter 3 of this report). There were two options, to make the comparison with the National classification (correcting for channel size (3.32)) and/or with the Regional classification (3.3.3). Comparing each SAC with its regional average may appear advantageous, but there were a number of problems with this approach. Firstly, because of an absence of prior data there was no available Regional classification for some rivers (Dee, South Esk, Tay). Since the data collected for this report are the only regional data with which to form a regional classification it follows automatically (and with entirely circular logic) that using this system the Dee, South Esk and Tay would be classified at the median grade. In the cases of some other SACs another circularity of logic would arise because the regional scheme may be based entirely, or almost entirely, on previous data collected on the SAC itself, leading merely to a comparison of the year of survey with the average of the period from 1997-2002. While this data is informative about present as opposed to previous status (See section 4.4.2), using this method to develop a classification of ‘favourable’ status would be misleading because it would simply be establishing whether population density in an SAC was improving (or getting worse). Thus a very favourable SAC could easily score worse than a very unfavourable SAC using this approach. Another problem with the Regional classification scheme is that in some cases it is based on rather few previous electrofishings (Section 3) and so the percentile bands will have more noise, leading to inappropriate classification, than those of the National classification. Accordingly we chose to compare SAC densities with those in the National Classification scheme (Table 157). Comparison with the National Scheme is pleasingly simple, but it is not known how meaningful it is to compare data from a river in, say, the far north west with national median density data. Schemes are descriptions of average juvenile population levels, and hence are useful for suggesting expectations about population size or serving as a yardstick. However, since there is likely to be genuine between-catchment variation in juvenile densities (due to differing catchment characteristics such as climate and geology) even in a pristine state, this system is an inherently weak way to determine whether a particular site/river is 'good' or 'bad' in terms of juvenile numbers. Chapter 2 of this report explored the possibility of using a “Scottish Habscore” to overcome this problem, but established that local habitat characteristics explained only a small amount of variation in population density. This is likely due to near-random things like the relative proximity of the electrofishing site to a spawning location, the flow conditions affecting the ability of adults to reach upper parts of the catchment and the sea survival of adults. The parr stage should be more stable in the face of this type of stochastic event firstly because they generally represent more than a single year’s progeny and secondly because their numbers have had more time to respond to density-dependent effects. Accordingly more weight might be given to the classification of favourable status based on parr than on fry densities in Table 15 (though it should be noted that local habitat explained only marginally more of the variation in parr population density than it did for fry (see Chapter 2)).

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Table 157. Assessment of the condition status of Atlantic salmon SACs on the basis of juvenile populations. Separately for fry and parr stages favourable status was conferred on those SACs with a median grade of C or above when the zero densities were included in the 0-20 percentile range (see accompanying text).

SAC Salmon Age Class

No sites

No of sites with densities in Percentile Range (Scotland average, accounting for width) 0-20

21-40

41-60

61-80

81-100

Zero fish

(E) (D) (C) (B) (A)

Median Grade

Median grade with zeros as 0-20 percentile

Favourable?

0+ 3 1 2 D+ D+ N Berrie & Langwell 1++ 1 2 3 B+ B Y

0+ 1 1 1 3 A C Y Bladnoch 1++ 2 1 3 A B Y 0+ n/a n/a n/a n/a n/a n/a n/a n/a n/a Borgie 1++ n/a n/a n/a n/a n/a n/a n/a n/a n/a 0+ 1 2 3 2 C C Y Dee 1++ 1 5 2 B B Y 0+ 2 1 1 1 1 D+ D+ N2 Endrick 1++ 2 2 2 E+ E2 N2 0+ 2 2 1 D D N Grimersta 1++ 1 2 2 C C Y 0+ 1 1 4 1 B B Y L.Gruinard 1++ 1 1 1 4 A A Y 0+ 2 1 2 1 C D N3 Moriston 1++ 2 2 2 C+ C Y4 0+ 2 1 1 1 1 C+ D+ N Naver 1++ 1 2 3 B+ B+ Y 0+ 3 1 2 1 D D N Oykel 1++ 1 2 1 1 2 C C Y 0+ 4 2 2 E+ E+ N N.Harris 1++ 2 1 4 1 B B Y 0+ 1 4 2 3 1 B D N Spey 1++ 1 2 3 3 2 C C Y 0+ 3 4 A A Y S.Esk 1++ 2 5 A A Y 0+ 1 5 6 B+ B+ Y Tay 1++ 3 2 1 6 B+ B+ Y 0+ 2 1 1 1 2 D D N Teith 1++ 1 2 1 1 1 1 D+ D N 0+ 5 2 B B Y Thurso 1++ 3 2 1 1 C C Y 0+ 2 2 1 5 B+ B+ Y Tweed 1++ 1 2 1 4 2 B B Y

1 See Table 24

2 All depletion sites were outwith SAC, however, timed sites within cSAC suggest patchiness and lowish densities for parr, but no particular problem for fry. 3 Some depletion sites outside the SAC, grade based on those within the SAC is C and hence favourability status Y 4 Some depletion sites outside the SAC, grade based on those within the SAC is B+ and hence favourability status Y

216

Most of the data in the classification scheme are derived from single-fishings, with a few from the first run of three-run fishings. By contrast the data collected for the SACs are all based on the first run of three run fishings. We do not know how first-run of three run and single run fishings compare. There is a risk of bias, in this case, possibly towards giving an overly-negative view of the SACs, since three-run fishing may be conducted in conditions less effective for single-run fishing, given that subsequent runs can be relied on to account for efficiency, whilst single-run fishings must be conducted in the best conditions. The National Classification Scheme (3.3.2) is based only on sites where some salmon were caught. This was because there was uncertainty about whether there was salmonid access to some of the zero density sites. Accordingly there are two columns giving a median grade in the Table 157, the first one using only SAC sites with >0 densities, the second placing the zero density sites in the 0-20 percentile range. This second scheme introduces bias leading to an overly-negative view of the SACs in comparison to the National Classification Scheme. However, since SAC boundaries were defined with areas of salmon access in mind this system is preferred given that it allows, for example, the effect of acidification in upland Galloway, to be taken into consideration in determining the favourable status. It is thus that the Favourable/Unfavourable column is based on the median scores including zero density sites. Particularly effected by the scoring system including zero density sites is the Spey which scores ‘B’ for fry when excluding the zero density sites, but D when the zero density sites are included. Similarly the score for the Naver SAC falls from B- to C- for fry (Table 157). “Favourable” status was awarded to those sites which for 0+/1++ which achieve C or above (ie equal to or higher than the Scottish average). The rationale for using the C grade is not entirely clear, given that one might expect special areas of conservation for salmon to hold better than average juvenile population densities (perhaps making grade B a better standard). However, since two ways in which the scoring system is likely to be biased toward a negative view of the SACs have been identified above, and none that bias it toward a positive view, grade C seemed a fairer choice. However, it must be recognised that this system for defining status is somewhat arbitrary and unsatisfactory. An example of this is that the River Bladnoch SAC obtains favourable status for both fry and parr, even though it is clear that there are parts of the upper SAC area that are definitely not currently favourable for juvenile salmon, with a particular anthropogenic cause clearly implicated. Additionally, given that variation in adult marine mortality is likely to be an important factor in determining the distribution and density of juvenile populations, most especially of fry, it may be risky to define an SAC on the basis of a single year. Furthermore in the absence of adequate time series it is difficult to justify the comparison of a small set of sites with an average level (since by chance sites far from (or near to) good spawning sites may have been selected, leading to bias. Nevertheless, given the resources available this approach is the best available. Furthermore it is envisaged that future monitoring of the SACs will allow a more robust system of attributing favourability status via the development of a time series that could detect trends (as opposed to single year fluctuations) in SAC populations and so highlight SACs which have populations of potential concern. At this stage of data collection, difficulties with defining SAC condition status are unavoidable, because the data-set on which to base such definitions is still inadequate, being as yet only a snap shot in time. An alternative method for assessing favourability could be developed around the concept of patchiness (discussed in Section 4.4), but for this, too, the site condition

217

monitoring is at too early a stage. The extent of juvenile distribution and the variability in densities within an SAC could be more informative about returning adults and habitat quality than the mean density values alone. In section 4.4 some coefficients of variation of juvenile densities are presented (measuring patchiness), but in the absence of knowing what the coefficient of variation should be in a pristine environment (and accepting that it must vary between rivers just as the distribution of potential spawning sites must vary between rivers) all that can be done at this stage is to identify which SACs have the greatest patchiness, and to establish the first point of a time series. Again, with repeated monitoring of sites eventually a sufficient time series could be established to allow the coefficients of variation to become informative of SAC condition. 7.2 Adult population components Categorisation as favourable/unfavourable was based on the following criteria as supplied by SNH:

• Favourable: the average rod catch in the years since the site was designated as an SAC is greater than the catch in the year of designation.

• Unfavourable: the average rod catch in the years since the site was designated as an SAC is less than the catch in the year of designation.

Thus, for each SAC, the rod catch in the year of designation was compared with the average catch in subsequent years up to and including 2004. The favourability status thus defined is shown in Table 158 for each of the adult components at each of the SACs. The extent to which any component in any SAC is favourable/unfavourable is elaborated upon in Figures 70, 71 and 72. A full description of the rod catch data sets used to assess the SACs can be found in Section 5. Table 158. Favourable condition status for Atlantic salmon SACs on the basis of changes in adult populations (estimated from rod catch data) since the date of SAC designation. Each SAC’s condition status is defined as Favourable (Y) or Not favourable (N) SAC Date of

designation Spring component

Summer component

Autumn component

Berriedale&Langwell 26-Jan-01 Y Y Y Grimersta 16-Mar-01 Y N Y Little Gruinard 16-Mar-01 Y N N Bladnoch 20-Jul-01 Y N Y Dee 10-May-02 Y Y Y Naver 16-Mar-01 N N N South Esk 16-Mar-01 N Y Y Spey 04-Jun-99 Y Y N Tay 10-May-02 Y Y Y Thurso 16-Mar-01 Y Y N Tweed 30-Nov-01 N Y Y Borgie 20-Dec-00 N N N Endrick 20-Jan-01 N N N Moriston 29-Jan-01 Y N Y North Harris 20-Dec-00 n/a Y Y Oykel 16-Mar-01 N N N Teith 16-Mar-01 Y N N

218

Figure 70. Percentage change in rod catch since year of cSAC designation for the spring salmon component. For those cSACs where a change greater than +/- 50% is recorded the value of the change is labelled on the plot.

-50.00-40.00-30.00-20.00-10.00

0.0010.0020.0030.0040.0050.00

% c

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eeN

averSouth EskSpeyTayThursoTw

eedBorgieEndrickM

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Teith

inf inite133%106%

-62%

Figure 71. Percentage change in rod catch since year of cSAC designation for the summer salmon component. For those cSACs where a change greater than +/- 50% is recorded the value of the change is labelled on the plot.

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137%

219

Figure 72. Percentage change in rod catch since year of cSAC designation for the autumn salmon component. For those cSACs where a change greater than +/- 50% is recorded the value of the change is labelled on the plot.

-50.00-40.00-30.00-20.00-10.00

0.0010.0020.0030.0040.0050.00

% c

hang

e

Berridale & Langwell

Grim

erstaLittle G

ruinardBaldnochD

eeN

averSouth EskSpeyTayThursoTw

eedBorgieEndrickM

oristonN

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Oykel

Teith

625% 63% 200%

7.3 Future assessment of SACs It is recognised that we are still at an early stage of the development of a monitoring system for Atlantic salmon SACs, particularly for juveniles. The Atlantic salmon has a complex life history, making it a particularly difficult species to monitor effectively, particularly given that the status of the salmon population in an SAC may be largely dependent on conditions outside the SAC, namely in the North Atlantic. It is because of fluctuations in marine mortality outside the SAC that the population within an SAC on a particular year cannot be regarded as truly representative of the SAC itself. Accordingly only the establishment of time series data can provide information regarding the status of individual SACs themselves in the context of changes in marine survival that may affect all the SACs similarly. The length of time series before it becomes truly informative cannot be known, since it will depend on as yet unknown levels of variation, but it is likely to be greater than 10 years (or sets of data points). Only time can allow the development of a robust classification tool for Atlantic salmon. Another possible method for assessing favourability could be developed around the concept of patchiness (discussed in Section 4.4), but for this, too, the site condition monitoring is at too early a stage. The extent of juvenile distribution and the variability in densities within an SAC could be more informative about returning adults and habitat quality than the mean density values alone. In section 4.4 some coefficients of variation of juvenile densities are presented (measuring patchiness), but in the absence of knowing what the coefficient of variation should be in a pristine environment (and accepting that it must vary between rivers just as the distribution of potential spawning sites must vary between rivers) all that can be done at this stage is to identify which SACs have the greatest patchiness, and to establish the first point of a time series. Again, with repeated monitoring of sites eventually a sufficient time series could be established to allow the coefficients of variation to become informative of SAC condition.

220

It may be that these approaches orientated towards long time-scales are regarded too slow for the required purposes of SAC condition monitoring. It might be thought essential that a future monitoring event can produce a definitive answer in terms of whether juvenile population density has increased or decreased since the period reported here. In this case the analysis of the power of the present monitoring system (Section 4.5) and the recommended number of monitoring sites on each SAC to achieve a given power should be taken into consideration. Simply revisiting the sites fished for this report would be likely to be insufficient in almost all cases to be able to determine with 95% confidence whether, for example, a 50% decrease in juvenile populations had taken place. For adults there is already an established historical record, which provides at least qualitative information about changes in adult salmon populations in rivers. These data show that components of the adult population undergo both significant annual and decadal changes. Given that there is concordance between annual changes in adult populations among rivers it follows that assessment of the current status of adult populations should not be dependent on the year that a particular SAC was designated (Table 158). Instead it is suggested that the rules regarding comparison of current population status with population status at designation date should be relaxed, and that a fixed reference year (or the average population of a common set of years) should be chosen as a historical reference point for comparison with present population levels. Changes in netting and angling practices over the last decade are also making it harder to regard current rod-catch data as commensurate with older records. Accordingly their value as a tool for future assessment may be increasingly compromised. An alternative assessment method would involve the provision of fish counters and smolt traps on each of the SACs, since these could then provide direct information on the outcome of the critical population processes both inside and outside the SAC’s boundaries. Capital investment and staffing costs however would be of an order of magnitude greater than the continuation of the current monitoring programme of juvenile electro-fishing and adult rod-catch data, and would similarly require a number of year’s data before a robust classification system could be developed. Fixed smolt traps can assess river performance on for small channels and so suffer from a limited spatial coverage (while gaining the advantage of sampling the entire channel, as opposed to a the few hundred square meters sampled by electrofishing sites). The new and relatively inexpensive rotary screw traps that are currently being used in a few locations in Scotland may represent a compromise, in that they can sample larger spatial extents (though with less precision). However it is not yet know how effective these traps are at assessing smolt production.

221

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APPENDIX A.1 SFCC 5MM. ELECTROFISHING RECORDING SHEET Easting:_ _ _ _ _ metres Northing: _ _ _ _ _ metres Site code:............. Altitude:............ metres River:......................................................................................................................................................... Site situation:............................................................................................................................................ Access/permission:.......................................................................................................…. Date:.............

Instream cover: None / Poor / Moderate / Good / Excellent

Salmon Trout Mm 1 2 3 4 mm 1 2 3 4 30-34 30-34 35-39 35-39 40-44 40-44 45-49 45-49 50-54 50-54 55-59 55-59 60-64 60-64 65-69 65-69 70-74 70-74 75-79 75-79 80-84 80-84 85-89 85-89 90-94 90-94 95-99 95-99 100-104 100-104 105-109 105-109 110-114 110-114 115-119 115-119 120-124 120-124 125-129 125-129 130-134 130-134 135-139 135-139 140-144 140-144 145-149 145-149 150-154 150-154 155-159 155-159 160-164 160-164 165-169 165-169 170-174 170-174 175-179 175-179 180-184 180-184 185-189 185-189 190-194 190-194 195-199 195-199 200-204 200-204 205-209 205-209 210-214 210-214 215-219 215-219 220-224 220-224 225-229 225-229 230-234 230-234 235-239 235-239 240-244 240-244 245-249 245-249 250-254 250-254 255-259 255-259 260-264 260-264 265-269 265-269 270-274 270-274 275-279 275-279 >279 >279

Scales:........................................................................................................................................... Other species:.............................................................................................................................. Site notes:.....................................................................................................................................

APPENDIX A.2 SFCC 1MM. ELECTROFISHING RECORDING SHEET

Easting:_ _ _ _ _ metres Northing: _ _ _ _ _ metres Site code:............. Altitude:............ metres River:......................................................................................................................................................... Site situation:............................................................................................................................................ Access/permission:............................................................................................ Date:.............................

Instream cover: None / Poor / Moderate / Good / Excellent SALMON mm 1 2 3 4 mm 1 2 3 4 mm 1 2 3 4 mm 1 2 3 4 30 90 150 21031 91 151 21132 92 152 21233 93 153 21334 94 154 21435 95 155 21536 96 156 21637 97 157 21738 98 158 21839 99 159 21940 100 160 22041 101 161 22142 102 162 22243 103 163 22344 104 164 22445 105 165 22546 106 166 22647 107 167 22748 108 168 22849 109 169 22950 110 170 23051 111 171 23152 112 172 23253 113 173 23354 114 174 23455 115 175 23556 116 176 23657 117 177 23758 118 178 23859 119 179 23960 120 180 24061 121 181 24162 122 182 24263 123 183 24364 124 184 24465 125 185 24566 126 186 24667 127 187 24768 128 188 24869 129 189 24970 130 190 >71 131 191 24972 132 19273 133 19374 134 19475 135 19576 136 19677 137 19778 138 19879 139 19980 140 20081 141 20182 142 20283 143 20384 144 20485 145 20586 146 20687 147 20788 148 20889 149 209 Scales:........................................................................................................................................... Other species:.............................................................................................................................. Site notes:.....................................................................................................................................

APPENDIX B SFCC GENERAL ELECTROFISHING HABITAT SURVEY Easting:_ _ _ _ _ _ metres Northing: _ _ _ _ _ _ metres Site code:................ Date:.................... Widths (m) At Wet width Bed width Bank width

A - Upst. 0 metres B C Site length: D E ...........metres F G H I

J - Downst. Depths (cm) <10 11-20 21-30 31-40 41-50 >50 Percent Substrate HO SI SA GR PE CO BO BE OB Percent Instream veg:..........% Silted?: Y / N Substrate: Stable / Unstable & Compacted / Partly / Uncompacted

Substrate notes:.........................................................................................................................................................

Flow SM DP SP DG SG RU RI TO Percent Flow notes:.................................................................................................................................................…………

Bankside (%) UC DR BA MA LB RB

Total LB fish cover:....................% Total RB fish cover:....................%

LB bankface veg.: Bare / Uniform / Simple / Complex RB bankface veg.: Bare / Uniform / Simple / Complex

LB banktop veg.: Bare / Uniform / Simple / Complex RB banktop veg.: Bare / Uniform / Simple / Complex

LB overhang. boughs: .............% RB overhang. boughs: ..............% Canopy cover: ...............%

Bankside Notes:.........................................................................................................................................................

Landuse: AR / BL / CP / FW / GA / IG / IN / MH / NC / OR / OW / RD / RP / RS / SC / SU / TH / TL / WL

Equipment Type: GEN / BACK Volts:.......... Amps:..........SMOOTH / PULSED Effective fishing?: Y / N

Cond:........μScm-1 Temp:........oC Time:............

Stopnet: UP / DO / BO / NO Water: LO / ME / HI & CLR / COL

Team leader:........................................ No of staff:................ Photo taken & IDS?: Y .............................. / N

Stocking? Y / N Pollution? Y / N

SP Notes:....................................................................................................…………………………………………

AccessSal?: Y / N / S / ? AccessTrt?: Y / N / S / ? Purpose: M / I

Access Notes:...................................................................................……………………………………………….

APPENDIX C SFCC ELECTROFISHING SURVEY HABITAT DEFINITIONS Width (taken at right angles to the midline of the river): Wet width - width across the wetted part of the river channel Bed width - width of the river bed between the foot of the two bank faces, including any exposed bed or bars Bank width - width between the two bank tops (level with the lower bank top if the banks are different heights) Substrate (% of survey stretch area): HO - High organic: very fine organic matter, incl peat substrate and thick leaf cover on the bed SI - Silt: fine, sticky, mostly inorganic material, individual particles invisible SA - Sand: fine, inorganic particles, <= 2mm diameter, individual particles visible GR - Gravel: inorganic particles 2-16mm diameter PE - Pebble: inorganic particles 16-64mm diameter CO - Cobble: inorganic particles 64-256mm diameter BO - Boulder: inorganic particles >256mm diameter BE - Bedrock: continuous rock surface OB - Obscured: wood, sheets of iron, barrels etc. obscuring river bed which cannot be moved for inspection. Only includes areas covered by instream vegetation roots; other instream vegetation can usually be moved - incl in other categories. Substrate recorded from the point of view of cover for fish, not spawning suitability. Instream veg (% of survey stretch area) : % of the survey stretch stream bed covered by instream vegetation. Includes ALL types of vegetation (including algae), providing vegetation serves as cover for fish. Thin layer of algae/mosses that cover the surface of rocks does not count as cover. Silted?: Y / N Refers to silt covering the surface of the bed and NOT to silt in the stream bed matrix.

Substrate stability and compactedness: Stable / Unstable - 'Unstable' used to identify stretches where stream mobility is extreme – may be indicated by braided channels and gravel bars. Uncompacted - beds move when digging into the stream bed with feet Compacted - should be obviously cemented Fully compacted stream bed is unlikely to be ‘Unstable’. Bedrock is never classed as compacted. Partly - beds contain both uncompacted and compacted patches Flow (% of survey stretch area): SM - Still marginal: <10cm deep, still/eddy, no waves behind 2-3cm wide rule, smooth surface, silent DP - Deep pool: >= 30cm deep, flow slow, eddy, no waves behind 2-3cm wide rule, smooth surface, silent SP - Shallow pool: <30cm deep, flow slow, eddy, no waves behind 2-3cm wide rule, smooth surface, silent DG - Deep glide: >=30cm deep, flow moderate/fast, waves form behind 2-3cm wide rule, smooth surface, silent SG - Shallow glide: <30cm deep, flow moderate/fast, waves form behind 2-3cm wide rule, smooth surface, silent RU - Run: water flow fast, unbroken standing waves at surface, water flow is silent RI - Riffle: water flow fast, broken standing waves at surface, water flow is audible TO - Torrent: white water, chaotic & turbulent flow, noisy, difficult to distinguish substrate

Fish Cover Type (% of Left and Right bank length): UC - Undercut: cover provided from undercut banks. DR - Draped: cover from vegetation rooted on the river bank and draping on to the water surface BA - Bare: no cover or fish cannot get to cover due to lack of water MA - Marginal: cover provided by plants rooted in the stream bed, excluding fully aquatic vegetation Total fish cover (% of Left and Right bank length) : % of bank length (water/land boundary) within survey stretch that provides cover for fish. ‘Cover’ = physical cover for fish, not secondary cover related to shading.

Bankface and banktop vegetation (Left and Right bank): Bare - predominantly bare ground (or buildings/concrete). <50% vegetation cover Uniform - predominantly one vegetation type, but lacking scrub or trees Simple - predominantly 2-3 vegetation types, with/without scrub or trees, including tall or short herbs. Complex - four or more vegetation types which must include scrub or trees Type of vegetation does not mean different species, but structural complexity i.e. number of different canopy layers (e.g. short grass vs. long grass/nettles vs. shrubs vs. taller trees).

Overhanging boughs (% of Left and Right bank length) : % of bank length (water/land boundary) within survey stretch where branches from trees and shrubs rooted in the riparian zone overhang the survey stretch. Total Canopy cover (% of survey stretch area) : % of the survey stretch wetted area covered by overhanging branches. Landuse (50m from the banktop) : AR - Arable OW - Open water BL - Broadleaf/mixed woodland RD - Road CP - Conifer plantations RP - Rough pasture FW - Felled woodland RS - Rock and scree GA - Garden SC - Scrub IG - Improved/semi-improved grass SU - Suburban/urban development IN - Industrial TH - Tall herbs/rank vegetation MH - Moorland/heath TL - Tilled land NC - Natural/semi-natural conifers WL - Wetland OR - Orchard Stop net: UP - upstream stop net used only DO - downstream stop net used only BO – stop nets used both up and downstream NO - no stop nets used Water level and clarity: LO - Low: summer level or below ME - Medium: slightly higher than summer level due to rain but not not bursting banks HI - High: flood conditions, bursting banks

CLR - Clear: water clear, fish easily visible COL - Coloured: water coloured, stunned fish difficult to see Accessible to Salmon and Trout?: Y - Yes N - No S - Sometimes, likely to be species/adult size or flow dependent ? - Unsure

APPENDIX D LAND COVER OF SCOTLAND CATEGORIES Land Cover of Scotland, Macaulay Land Use Research Institute, 1993. Data based on aerial photography flown at 1:25,000 across Scotland in 1988 / 89. Original land cover classes reclassified into 18 broad classes.

LCS1 Arable LCS2 Improved grassland LCS3 Good rough grassland LCS4 Poor rough grassland LCS5 Heather moorland LCS6 Peatland LCS7 Scrub LCS8 Felled woodland LCS9 Recent planting LCS10 Conifers LCS11 Mixed woodland LCS12 Broad-leaved woodland LCS13 Freshwater LCS14 Urban LCS15 Other mosaics LCS16 Missing/obscured LCS17 Tidal waters LCS18 Bracken

APPENDIX E PRINCIPAL COMPONENTS ANALYSIS 1. Flow Type For data structure see Appendix A, for definitions see Appendix C Total Variance Explained by Flow principal components axes Initial Eigenvalues

Component Total % of Variance Cumulative % 1 1.666 20.8 20.8 2 1.568 19.6 40.4 3 1.169 14.6 55.0 4 1.027 12.8 67.9 5 .995 12.4 80.3 6 .794 9.9 90.2 7 .769 9.6 99.9 8 .011 0.1 100.0

Flow PCAs and flow type percentage correlation matrix Flow Type PCA1 PCA2 PCA3 PCA4 SM .369 -.088 .233 -.066 SP .219 .120 .523 .331 DP -.159 .323 .223 .557 SG .474 .085 -.097 -.314 DG -.046 .418 -.527 .049 RU -.091 -.572 -.173 .342 RI -.381 .042 .389 -.575 TO -.103 -.002 .104 -.029 No single axis dominates the variance structure, with both the first two axes explaining about 20% of the variance in the flow type data. The third and fourth axes contribute around 14% each. Overall the analysis is not particularly successful in summarising the data. Flow PCA1 is not easily interpreted, but is generally negatively correlated with run, riffle and torrent flow types. Flow PCA2 represents deep glide and deep pool type flows, and a scarcity of run type flow. Further axes are not easily interpreted, and are not used in the analysis.

2. Stream depth For data structure see Appendix A, for definitions see Appendix C Total Variance Explained by Depth principal components axes Initial Eigenvalues

Component Total % of Variance Cumulative % 1 2.517 42.0 42.0 2 1.504 25.1 67.0 3 .947 15.8 82.8 4 .656 10.9 93.7 5 .375 6.3 100.0

Depth PCAs and depth class correlation matrix Depth class (cm) PCA1 PCA2 <11 -.273 .371 11-20 -.259 -.243 21-30 .169 -.521 31-40 .327 -.053 41-50 .294 .275 >50 .183 .344 The first two axes contain 67% of all the variance in the data, with the first alone contributing over 40%, offering a useful summary of the data. Depth PCA1 is positively correlated with moderately deep water, and negatively with shallow water Depth PCA2 is associated with high proportions of both very shallow and very deep water, and negatively associated with moderately shallow water

3. Bank fish cover For data structure see Appendix A, for definitions see Appendix C Total variance explained by Bank fish cover principal components axes Initial Eigenvalues

Component Total % of Variance Cumulative % 1 2.192 54.8 54.8 2 1.048 26.2 81.0 3 .502 12.5 93.5 4 .258 6.4 100.0

Bank PCAs and Bank cover type abundance correlation matrix Bank cover type PCA1 PCA2 Bare -.413 -.138 Marginal .116 .904 Marginal .116 .904 Draped .385 -.130 The first two axes provide a good summary of the data, contributing 55% and 26% of the variance respectively, and offer clear correlations with bankside fish cover. Bank PCA1 is negatively associated with bare banks, and positively with draped and undercut banks, whilst Bank PCA2 is strongly correlated with marginal type bankside vegetation.

4. Substrate For data structure see Appendix A, for definitions see Appendix C Total variance explained by Substrate principal components axes Initial Eigenvalues

Component Total % of Variance Cumulative % 1 2.134 26.7 26.7 2 1.451 18.1 44.8 3 1.104 13.8 58.6 4 .913 11.4 70.0 5 .877 11.0 81.0 6 .794 9.9 90.2 7 .653 8.2 98.4 8 .124 1.6 100.0

Substrate PCAs and substrate percentage correlation matrix Substrate Type PCA1 PCA2 PCA3 High Organic .067 .275 .409 Silt .191 .301 .318 Sand .245 .272 .186 Gravel .339 .002 -.216 Pebble .271 -.411 -.151 Cobble -.255 -.357 .419 Boulders -.329 .323 -.130 Bedrock -.075 .220 -.584 The first two axes account for 45% of the variance in the substrate data. Substrate pca1 is negatively correlated with the abundance of large substrate size, and positively related to sand, gravel and pebble sizes. Pca2 is correlated with smaller substrate sizes (silt, sand and high organic substrate), and strongly negatively associated with pebble and cobble abundance. The pca33 explains little variance, and is not easily interpreted and was therefore not included in the modeling exercise.

5. Catchment landuse Data represent combined categories from MLURI land cover data summarized in Appendix D. Total variance explained by Landuse principal components axes. Initial Eigenvalues Component Total % of Variance Cumulative %

1 2.229 24.8 24.8 2 1.203 13.4 38.1 3 1.070 11.9 50.0 4 1.038 11.5 61.5 5 .937 10.4 72.0 6 .878 9.8 81.7 7 .826 9.2 90.9 8 .753 8.4 99.3 9 .067 0.7 100.0

Land PCAs and Land use categories correlation matrix Catchment land use type PCA1 PCA2 PCA3 PCA4 Arable and improved grassland .197 .473 .025 -.173 Rough grassland .262 .012 -.597 .076 Recent felling or planting .171 -.376 .261 .258 Coniferous and mixed woodlands .220 -.390 .461 -.211 Broadleaved woodlands and scrub .053 .336 .425 .313 Heather moor and peatland -.424 .028 .005 .054 Freshwater -.264 -.007 .163 .018 Urban habitats .078 .406 .291 -.378 Bracken .075 .188 .070 .757 The first axis accounts for 25% of the data variance, but the following 4 axes each contribute about 10%, and overall the PCA is rather unsuccessful at summarizing the data. Land PCA1 is negatively associated with heather moorland, peatland and freshwater habitats, with weaker positive association with rough and improved grassland, arable, and coniferous woodlands, suggesting a negative association with upland and ‘wild’ type catchments. Land PCA2 has strong positive associations with arable and improved land, together with urban habitats, and negative associations with coniferous plantations, and recent woodland fellings and plantings. Land PCA3 is associated with all types of tree cover, and negatively associated with rough grassland.

APPENDIX F TIMED ELECTROFISHING PROTOCOL SAC monitoring SFCC / SNH contract: Timed Fishing Method 1. “Site” to consist of the three major habitats: glide, riffle and run. 2. Total of 5 minutes fishing in each habitat type (i.e. total of 15 minutes fishing). Results

from the three habitat types to be recorded separately. 3. “Site” need not be continuous, but 5 minutes of each habitat type to be sampled, as and

when it occurs moving in an upstream direction from the agreed site. Site identified by its downstream grid reference.

4. Backpack electrofishing gear smooth DC current preferred. 5. Team of two people: anode operator and net person (with slung ‘bucket’, preferably a

columnar-type bottle adapted with a funnel feeding into the lid, to allow fish to be put in without removing lid). Alternatively three-person team in which third person contributes to fishing only by holding bucket (ie does not attempt to net fish).

6. Net person to use banner net. Only sites which can be efficiently fished with a banner net to be sampled.

7. Anode operator with hand net or sieve to transfer fish from the banner net to bucket only 8. Anode sweeps fish into banner net using full arm length sweeps. 9. Fishing in an upstream direction. 10. Fishing a shallow 5 metre wide section (where appropriate) out from the bank up to knee

depth (50cm). 11. Same method of working through the section as for quantitative fishing (out from bank, 2

paces upstream, in to bank etc). 12. Information recorded on fish and habitat largely as in quantitative fishing (some

unnecessary fields excluded and some additions). 13. Numbers for all species found. 14. Lengths of salmon and trout to 1mm. 15. Scales taken from sub-set of fish as per review group guidance note. 16. Photographs taken of the site to aid its subsequent identification: including photos of each

starting point, and the three habitats sampled 17. Additional fields (for each sample area):

Flow type; Width of river (estimate wet, bed and bank widths); Percentage of the channel fished; Mean depth; Approximate area fished; Predominant substrate; Estimate of number of fish missed; SNH survey identifier. Any information useful in helping correctly pinpoint the areas sampled for use when the site is revisited.

APPENDIX G TIMED FISHING RECORDING SHEETS

SFCC / SNH TIMED ELECTROFISHING RECORDING SHEET (1 of 3)

Easting:……….……….. Northing:……..………….. Sitecode:........….....…. Date:..........….......…. River:.......................................................................................................................... Altitude: ………….(m) Site situation:................................................................ Access/permission:....................................................... SALMON

mm Glide Run Riffle mm Glide Run Riffle mm Gl Ru Ri mm Gl Ru Ri 30 90 150 210 31 91 151 211 32 92 152 212 33 93 153 213 34 94 154 214 35 95 155 215 36 96 156 216 37 97 157 217 38 98 158 218 39 99 159 219 40 100 160 220 41 101 161 221 42 102 162 222 43 103 163 223 44 104 164 224 45 105 165 225 46 106 166 226 47 107 167 227 48 108 168 228 49 109 169 229 50 110 170 230 51 111 171 231 52 112 172 232 53 113 173 233 54 114 174 234 55 115 175 235 56 116 176 236 57 117 177 237 58 118 178 238 59 119 179 239 60 120 180 240 61 121 181 241 62 122 182 242 63 123 183 243 64 124 184 244 65 125 185 245 66 126 186 246 67 127 187 247 68 128 188 248 69 129 189 249 70 130 190 71 131 191 72 132 192 73 133 193 74 134 194 75 135 195 76 136 196 77 137 197 78 138 198 79 139 199 80 140 200 81 141 201 82 142 202 83 143 203 84 144 204 85 145 205 86 146 206 87 147 207 88 148 208 89 149 209

> 249

Salmon Scales: ........................................................................... Site Notes: ………………………………………………………

Photo IDs Notes Glide Run Riffle

SFCC / SNH TIMED ELECTROFISHING RECORDING SHEET (2 of 3)

Easting:……….……….. Northing:……..………….. Sitecode:........….....…. Date:..........….......…. TROUT

mm Glide Run Riffle mm Glide Run Riffle mm Gl Ru Ri mm Gl Ru Ri 30 90 150 210 31 91 151 211 32 92 152 212 33 93 153 213 34 94 154 214 35 95 155 215 36 96 156 216 37 97 157 217 38 98 158 218 39 99 159 219 40 100 160 220 41 101 161 221 42 102 162 222 43 103 163 223 44 104 164 224 45 105 165 225 46 106 166 226 47 107 167 227 48 108 168 228 49 109 169 229 50 110 170 230 51 111 171 231 52 112 172 232 53 113 173 233 54 114 174 234 55 115 175 235 56 116 176 236 57 117 177 237 58 118 178 238 59 119 179 239 60 120 180 240 61 121 181 241 62 122 182 242 63 123 183 243 64 124 184 244 65 125 185 245 66 126 186 246 67 127 187 247 68 128 188 248 69 129 189 249 70 130 190 71 131 191 72 132 192 73 133 193 74 134 194 75 135 195 76 136 196 77 137 197 78 138 198 79 139 199 80 140 200 81 141 201 82 142 202 83 143 203 84 144 204 85 145 205 86 146 206 87 147 207 88 148 208 89 149 209

> 249

Trout Scales:.................................................................................... Other Species Notes: ……………………………………… OTHER SPECIES

Species Number Species Number Species Number Species Number Salmonid Hybrids Minnow Eels Stickleback (3) Stickleback (10) Stone Loach Rudd Chub Zander Rainbow Trout Dace Powan Lamprey Larvae Brook Lamprey River Lamprey Sea Lamprey Common Bream Tench Ruffe Allis Shad Roach Common Carp Barbel Twaite Shad Pike Mirror Carp Grayling Sparling Perch Arctic Charr Gudgeon Flounder

SFCC / SNH TIMED ELECTROFISHING RECORDING SHEET (3 of 3)

Easting:……….……….. Northing:……..………….. Sitecode:........….....…. Date:..........….......…. Glide Run Riffle DIMENSIONS INSTREAM Site Upstream Easting Instream Cover N/P/M/G/E N/P/M/G/E N/P/M/G/E Site Upstream Northing

Instream Veg % Site Length (m)

Silted? Yes / No Yes / No Yes / No Glide Run Riffle

Av Wet Width (m) Substrate % HO Av Bed Width (m)

SI Av Bank Width (m) SA Flow Stretch % GR PE % Depth (cm) <10 CO 11-20 BO 21-30 BE 31-40 OB 41-50

>50 Substrate Stable? S / U S / U S / U Subst Compacted? C / P / U C / P / U C / P / U Time Fished

No. Areas Fished % Channel Fished No. Missed Fish

Instream Notes:

OTHER BANKS

Survey Purpose I / M / MSt / SAC / WFD Banks Fished? L/ R / B/ N L/ R / B/ N L/ R / B/ N Equipment Type Backpack / Generator

Left Bank % UC Volts DR Amps BA Current Smooth / Pulsed MA

Cond. μScm-1 Right Bank % UC Temperature oC

DR Time BA Water Level Low / Medium / High MA Water Visibility Clear / Coloured

LB Fish Cover % Team Leader RB Fish Cover % No. of Staff LB Bankface Veg B / U / S / C B / U / S / C B / U / S / C RB Bankface Veg B / U / S / C B / U / S / C B / U / S / C

Survey Notes:

LB Banktop Veg B / U / S / C B / U / S / C B / U / S / C Stocked Salmon? Yes / No / Unknown RB Banktop Veg B / U / S / C B / U / S / C B / U / S / C Stocked Trout? Yes / No / Unknown

LB Over Bough % RB Over Bough %

Canopy Cover %

Stocking Notes:

Pollution? Yes / No Landuse1 * Landuse2

Pollution Notes:

Access Salmon? Yes / No / Sometimes / Unknown

Access Trout? Yes / No / Sometimes / Unknown

Bankside Notes:

* Landuse1 / Landuse2: AR / BL / CP / FW / GA / IG / IN / MH / NC / OR / OW / RD / RP / RS / SC / SU / TH / TL / WL

Accessibility Notes:

APPENDIX H TIMED FISHING DEFINITIONS

SFCC / SNH TIMED ELECTROFISHING RECORDING DEFINITIONS (Page 1 of 2)

Note: Definitions as for SFCC quantitative surveys (see TeamLeader manual) except new fields in blue, clarification / slight definition differences in red.

Flow Types

Glide / Gl moderately fast; smooth surface apppearance; silent Run / Ru fast; unbroken surface waves; silent Riffle / Ri fast; broken surface waves: audible

INSTREAM Instream Cover (MUST be recorded prior to electrofishing) (Include fished areas only)

N None: No cover; stream bed composed entirely of fine uniform particles (e.g. silt, sand, gravel, pebbles) or continuous hard surfaces (bedrock, concrete) P Poor: Little cover; stream bed composed predominantly of fine to medium particles (e.g. gravel, pebbles and cobbles), little or no cover from aquatic vegetation M Moderate Moderate substrate cover and/or with some aquatic vegetation cover G Good: Good cover; stream composed predominantly of medium to large size substrate

(e.g. pebbles, cobbles and boulders) and/or with some aquatic vegetation cover E Excellent: Excellent cover; stream composed predominantly of large size substrate (e.g. cobbles and boulders) and/or with extensive aquatic vegetation cover

Substrate % (percentages of the following categories per flow type within the fished areas) HO High Organic: very fine organic matter SI Silt: fine, mostly inorganic material, individual particles invisible SA Sand: fine, inorganic particles <=2mm, individual particles visible GR Gravel: inorganic particles 2-16mm PE Pebble: inorganic particles 16-64mm CO Cobble: inorganic particles 64-256mm BO Boulder: inorganic particles >256mm BE Bedrock: continuous rock surface OB Obscured: immoveable wood, barrels etc; incl. substrate invisible from water depth / colour

Substrate Stable? (within the fished areas) S Stable U Unstable

Substrate Compacted? (within the fished areas) C Compacted P Partly compacted U Uncompacted

BANKS Banks Fished?

L Left bank only (on the left when facing downstrean) R Right bank only B Both left and right banks N Neither bank

Left and Right Bank % (adjacent to the fished areas) UC Undercut: undercut banks DR Draped: vegetation rooted in riparian zone; branches/leaves touch or almost touch surface BA Bare: no cover or fish can’t get to cover due to lack of water MA Marginal: vegetation rooted in stream bed/bank incl. tree roots; excl. fully aquatic vegetation

Left and Right Bank Fish Cover % (adjacent to the fished areas) percentage of the total left or right bank length providing cover for fish

Left and Right Bankface / Banktop Vegetation (adjacent to the fished areas) B Bare: predominantly bare ground (or buildings / concrete), <50% vegetation cover U Uniform: predominantly one vegetation type, lacking scrub or trees S Simple: predom. 2-3 vegetation type, with/without scrub or trees, incl. tall/short herbs C Complex: four or more vegetation types, including trees

SFCC / SNH TIMED ELECTROFISHING RECORDING DEFINITIONS (Page 2 of 2) Left and Right Bank Overhanging Boughs % (adjacent to the fished areas)

percentage of the total left or right bank length with overhanging boughs Canopy Cover% (adjacent to the fished areas) percentage of the total stretch area with overhanging boughs Landuse1 / Landuse2 (Predominant) (adjacent to the fished areas)

AR Arable MH Moorland/heath SC Scrub BL Broadleaved/mixed woodland NC Natural/semi-natural conifers SU Suburban CP Conifer plantation OR Orchard TH Tall herbs FW Felled woodland OW Open water TL Tilled land GA Garden RD Road WL Wetland IG Improved/semi-improved grass RP Rough pasture IN Industrial RS Rock/scree

DIMENSIONS Site Upstream Easting six figure easting for the site’s upstream point Site Upstream Northing six figure northing for the site’s upstream point Site Length (m) Approximate length of the site between grid reference locations Av Wet Width (m) Average wet width across 1+ areas per flow type (estimate for wide rivers) Av Bed Width (m) Average bed width across 1+ areas per flow type (estimate for wide rivers) Av Bank Width (m) Average bank width across 1+ areas per flow type (estimate for wide rivers) Flow Stretch % Estimated total percentage per flow type of the full site stretch

(including areas not fished) % Depth (cm) Percentages of each depth category per flow type within the fished areas Time Fished Total number of minutes fished per flow type No. Areas Fished Number of areas per flow type required to complete the fishing time % Channel Fished Estimated percentage per flow type of the channel fished No. Missed Fish Estimated number of fish per flow type seen to escape while fishing OTHER Survey Purpose

I Investigating M Monitoring MSt Monitoring Stocking SAC Special Area of Conservation (for SNH) WFD Water Framework Directive (for SEPA)

Survey Notes Notes on any of the preceding fields under DIMENSIONS or OTHER Access Salmon? / Trout? Whether the survey area is accessible to Salmon or Trout Accessibility Notes Notes on fish accessibility

APPENDIX I MONITORING ON THE SOUTH ESK IN 2004 Additional Electrofishing Data for the South Esk, Collected in 2004 A number of sites were electrofished on the South Esk cSAC in 2004, by Esk DSFB staff. Staff were not trained to full SFCC standards, and due to concerns about the commensurality of the data with data from other cSACs, the river was electrofished a second time in August and September 2005 by fully accredited electrofishing teams (see section 4.3.12). Because the 2004 fishings were conducted following the tradition of electrofishing at the sites concerned these fishings still represent a continuum with the historical data on the South Esk, and so are included here. Depletion sites 2004. Data on juvenile densities has been collected yearly by the South Esk Salmon Fishery Board since 1995 at five sites on the South Esk system, since 2001 at three further sites, and since 2003 for another. We adopted these sites here (Appendix I Table 1). Seven are situated on the mainstem of the river, with further sites on the Prosen and White Waters. Fry and parr were present at all sites. Zippin fry densities ranged from 11 to 93 per 100m2 (Zippin mean 40.6±s.d.25.7), while parr densities ranged from less than one to 21 per 100m2 (Zippin mean 8.3±s.d.7.1, three-run minimum estimate 5.6±s.d.6.2) (Appendix I Table 2, Appendix I Figure 1). The five lowermost sites had only 1+ parr present, whilst the four uppermost had 2+ salmon. Site BR had 2+ but no 1+ fish (Appendix I Table 2, Appendix I Table 3). Appendix I Table 1. Details of 2004 depletion sites, South Esk cSAC.

Site Code Easting Northing Altitude (m) Channel name LK 364200 758200 9 South Esk FN 349900 756800 40 South Esk SEC 340100 759400 141 South Esk RL 336400 768600 223 South Esk DR 336300 769800 230 South Esk BR 330500 774200 236 South Esk WW 328000 776000 261 White Water M1 328100 778100 282 South Esk PW 325800 769900 391 Prosen Water

Historical data. Appendix I Figure 2 shows previous annual Zippin density estimates at six of the cSAC sites, most dating back to the mid 1990s, while Appendix I Figure 3 shows cSAC sites for which only one-run minimum density estimates are available, dating from 2001. Five of the Zippin sites have more than seven points in the time series. Significant linear slopes can be fitted to some of these time series, but most have no significant linear component. Significant negative slopes can be fitted for both fry (P<0.006) and parr (P<0.05) at site SEC, and for parr at WW (p<0.009). Two further linear trends are suggested: a negative slope for parr at PW (P<0.1), and a positive slope (P<0.1) for fry at M1. In general noise is greater amongst fry. These data provide the beginnings of a useful data set, but at present are probably too limited for inference about significant changes in juvenile salmon populations on the South Esk.

Appendix 1 Map 1 Distribution of depletion and timed electrofishing sites on the South Esk cSAC in 2004.

Appendix I Table 2. Details of depletion electrofishing for 0+ and 1++ salmon, South Esk cSAC in 2004. Site

Code Date Area

(m2) Mean wet width (m)

Zippin density 0+ (no 100m-2) +95% c.l.

3-run min 0+

(no 100m-2)

Zippin density 1++ (no 100m-2) +95% c.l.

3-run min S1++

(no 100m-2)

LK 05/08/04 592.0 24.6 24.3+5.8 18.8 1.4+0.1 1.4FN 02/09/04 152.0 5.9 92.8+3.5 90.1 1.4+1.0 1.3SEC 02/09/04 155.0 6.1 11.0+0.2 11.0 3.2+0.2 3.2RL 01/09/04 355.0 13.4 30.8+5.1 26.2 N/a 0.3DR 01/09/04 136.0 6.1 70.1+6.8 64.7 N/a 4.4BR 01/09/04 372.0 13.3 11.3+1.6 10.5 N/a 0.5WW 31/08/04 220.0 6.7 28.7+4.2 25.9 13.4+0.9 13.2M1 31/08/04 337.0 10.0 46.0+7.9 37.7 9.8+7.1 6.8PW 02/09/04 228.0 6.8 50.7+3.1 48.2 20.8+2.7 19.3Mean 40.6 37.0 8.3 5.6s.d. 25.7 25.1 7.1 6.2

Appendix I Table 3. Presence/absence of salmon year classes, and of trout 0+ and 1++ at depletion sites in 2004, South Esk cSAC. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3++ 0+ 1++ LK YES YES no no no no FN YES YES no no YES n/a SEC YES YES no no YES no RL YES YES no no YES YES DR YES YES no no no no BR YES no YES no YES YES WW YES YES YES no YES YES M1 YES YES YES no YES no PW YES YES YES no YES YES Appendix I Table 4. Fork length of salmon of different age classes, South Esk cSAC in 2004.

Site Code

0+ mean fork length

(mm)

no 0+

1+ mean fork length

(mm)

no 1+

2+ mean fork length

(mm)

no 2+

3+ mean fork length

(mm)

no 3+

LK 57 111 109 8 0 0FN 50 137 93 2 0 0SEC 54 17 97 5 0 0RL 42 93 75 1 0 0DR 45 88 93 6 0 0BR 44 39 0 115 2 0WW 45 57 88 24 120 5 0M1 33 129 65 21 95 2 0PW 41 110 87 33 112 11 0 Appendix I Figure 1. Juvenile salmon population density estimated by the Zippin method for the cSAC sites on the South Esk in 2004. Error bars show upper 95% confidence limit. Arrows indicate three-run minimum estimate used.

South Esk

0

20

40

60

80

100

120

LK FN SEC RL DR BR WW M1 PWsite

num

ber 1

00m

-2

S0+

S1++

Appendix I Figure 2. Electrofishing time series data for juvenile salmon 1995-2004, for various sites in the South Esk cSAC, Zippin density estimates. Error estimates are only available for 2004, and show 95% confidence limits. Significant negative slopes can be fitted for fry (P<0.006) and for parr (P<0.05) at site SEC, and for parr at WW (p<0.009), whilst a further negative slope approaches significance at PW (P<0.1) for parr, and a positive slope (P<0.1) is suggested for fry at M1.

site SEC

0

20

40

60

80

100

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

year

zipp

in d

ensi

ty (n

o100

m-2)

0+1++

site WW

0

20

40

60

80

100

120

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

yearzi

ppin

den

sity

(no1

00m

-2)

0+1++

site M1

0

20

40

60

80

100

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

year

zipp

in d

ensi

ty (n

o100

m-2)

0+1++

site LK

0

10

20

30

40

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

year

zipp

in d

ensi

ty (n

o100

m-2)

0+1++

site PW

0

20

40

60

80

100

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

year

zipp

in d

ensi

ty (n

o100

m-2)

0+1++

site FN

0

20

40

60

80

100

2002 2003 2004

year

zipp

in d

ensi

ty (n

o100

m-2)

0+1++

Appendix I Figure 3. Electrofishing times series data for juvenile salmon 1992-2004, for various sites in the South Esk cSAC, one-run minimum density estimates.

site DR

0

25

50

75

100

125

2001 2002 2003 2004 2005

year

one-

run

min

imum

(no

100m

-2)

0+1++

site BR

0

2

4

6

8

10

2000 2001 2002 2003 2004

year

one-

run

min

imum

(no

100m

-2)

0+1++

Timed sites 2004. Eleven timed sites were fished on the mainstem and tributaries of the South Esk (Appendix I Table 5). Salmon were absent at four sites: the lowermost mainstem site, on the Lemno burn, the Noran Water and on one further mainstem site, where trout were also absent. Fry were caught at all the remaining sites, and 1+ fish were present at all but one of these. 2+ fish were found only at the highest altitude site (Appendix I Table 7) Overall catch rates were low (1.43 fish per minute) with the lowest capture rates in the glides. (Appendix I Table 6, Appendix I Figure 4). Appendix I Table 5. Details of timed electrofishing sites, South Esk cSAC in 2004. Site Code Easting Northing River Altitude (m) Principal Local Landuse SEs10 364180 758240 South Esk 4 Conifer plantation SEs9 356780 758720 South Esk 26 Improved grassland SEs8 349930 756770 South Esk 56 Arable SEs1 345100 754500 Lemno Burn 60 Arable SEs11 342090 757880 South Esk 84 Tall herbs SEs2 346510 760940 Noran Water 140 Garden SEs7 337360 765100 South Esk 206 Improved grassland SEs6 333870 764260 Prosen Water 208 Improved grassland SEs3 332560 772780 South Esk 230 Arable SEs4 327440 779210 South Esk 290 Rough pasture SEs5 327220 768810 Prosen Water 326 Rough pasture

Appendix I Table 6. Salmon cpue in glide, run and riffle habitats at timed electrofishing sites on the South Esk cSAC in 2004. Each habitat type was fished for five minutes. Site code Survey date Salmon 0+ min-1 Salmon 1++ min-1

Glide Run Riffle Glide Run Riffle SEs10 22.09.04 0 0 0 0 0 0 SEs9 21.09.04 1.2 4.8 3.4 0 0 0.4 SEs8 21.09.04 2.6 2.4 3 0.4 0.2 0.2 SEs1 15.09.04 0 0 0 0 0 0 SEs11 20.09.04 1.8 5.4 3.8 0 0.2 0 SEs2 16.09.04 0 0 0 0 0 0 SEs7 21.09.04 0.4 2.2 1.8 0.2 0.4 0.2 SEs6 20.09.04 1.8 1 1.4 0 0 0 SEs3 16.09.04 2.2 0 2.6 1 0.2 0.2 SEs4 16.09.04 0 0 0 0 0 0 SEs5 20.09.04 0 0.6 0.8 0 0.2 0.2 Mean 0.91 1.49 1.53 0.15 0.11 0.11 s.d. 0.98 1.90 1.41 0.30 0.13 0.13 Appendix I Table 7. Presence/absence of salmon year classes, and of trout at timed sites, South Esk cSAC in 2004. Site Code Salmon age class present? Trout

0+ 1+ 2+ 3+ SEs10 YES YES no no no SEs9 YES YES no no YES SEs8 YES YES no no no SEs1 no no no no YES SEs11 YES YES no no no SEs2 no no no no YES SEs7 YES YES no no YES SEs6 YES no no no YES SEs3 YES YES no no no SEs4 no no no no no SEs5 YES YES YES no YES

Appendix I Figure 4. Number of salmon caught per minute during timed electrofishing at sites on the South Esk in 2004. Five minutes of fishing were conducted in each of the three flow types, glide, run and riffle, at each site. A) all salmon b) salmon 0+ and c) salmon 1++ sites are arranged altitudinally, left lowest. a)

0

2

4

6

SEs10 SEs9 SEs8 SEs1 SEs11 SEs2 SEs7 SEs6 SEs3 SEs4 SEs5

all s

alm

on m

in-1

Glide

Run

Riff le

b)

0

2

4

6

SEs10 SEs9 SEs8 SEs1 SEs11 SEs2 SEs7 SEs6 SEs3 SEs4 SEs5

salm

on fr

y m

in-1

Glide

Run

Riff le

c)

0

2

4

6

SEs10 SEs9 SEs8 SEs1 SEs11 SEs2 SEs7 SEs6 SEs3 SEs4 SEs5

salm

on p

arr m

in-1

Glide

Run

Riff le