Post on 15-Jan-2016
DEVELOPMENT OF INDIVIDUAL-BASED MODELS IN SHOREBIRDS
High Water MarkLow Water MarkWASH1972-75Intertidal mudflats and sandflatsProposed fresh-water reservoir
HOW WE THOUGHT ABOUT THE ISSUEDecreasing area Increasing densityIncreasing competitionPercentage starving over winter
EMPIRICAL APPROACH?Increasing densityPercentage starving over winterXX X X X X X X XX??(i) It would be technically very difficult 0 0 0 0 0 00 0 0
Increasing densityPercentage starving over winterHabitat of above average quality is lostHabitat of average quality is lost..and (ii) the function would probably change after habitat loss
THE QUESTION: HOW TO DESCRIBE THE DENSITY-DEPENDENT STARVATION FUNCTION - NOT ONLY AS IT IS AT PRESENT BUT HOW IT WOULD BE IF THE FEEDING ENVIRONMENT WAS CHANGED BY:Habitat loss Disturbance ShellfishingSea-level rise Mitigation measuresetc etc
EVENTUAL ANSWER: develop and test individual-based models using oystercatchers eating mussels on the Exe estuary
MUSSELSLOCAL ISSUE: WOULD HARVESTING MUSSELS AFFECT THE BIRDS?
NO EFFECT EFFECTIncreasing harvest/Decreasing food supply Percentage starving
Before After
DEVELOPMENT OF THE MODEL1976-1996Field work on interference and exploitation competition between oystercatchers for mussels
HOW THE MODEL WORKSMORE DETAILS AT:http://www.dorset.ceh.ac.uk/shorebirds/
Each bird decides each tide where, when and on what prey species it is best to feedhttp://www.dorset.ceh.ac.uk/shorebirds/
Each of the three displaced birds will choose the next best place in which to feedPRINCIPLE: birds in model use optimality decision rules (= fitness maximising) to decide how to respond to a change in their feeding environment just as real birds do
Calibration period for overwinter mortality of adult mussel-feeding oystercatchers on the Exe
Sept 1976 Mar 1980
MORE NATURAL HISTORY WAS NEEDED: eg. feeding in fields over high tide
Predicted (retrospective) and observed increase in mortality 1980 - 1999Calibration period:
CONCLUSION
Winter mortality was density-dependent and the model postdicted it quite well
NO LONGER SO!Applying the model to species other than Oystercatchers: some say that they take too long to parameteriseThe models can usually be built, tested and applied within the time typically taken to conduct an EIA: i.e. 1 3 years
Bird energetics Prey energy content Functional responses Interference functions Food supply, exposure time, weather Human activities eg. fisheryObtained for the site being modelledBuilt into model allometric functionsMODELS CAN NOW BE BUILT AND TESTED VERY QUICKLY AS MOST PARAMETERS ARE IN THE LITERATURE:
Applications to other species: whatwe need to know
Bird energetics Prey energy content Functional response Interference function Food supply, exposure time and weatherAPPLICATION TO OTHER SPECIES - 1
Functional responses of oystercatchers eating musselsA
Chart2
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Data
Fit
Biomass density of mussels > 30mm long(gAFDM/sq m)
Intake rate (mgAFDM/s)
Sheet1
vh=2 dh=1 st=0Site AFDM IR (mgAFDM/s)Days since August 1stMussels >30mm per sq.mSite biomass >30mm (gAFDM30mm (gAFDM/sqm)c6c7fitsc6c7residsc2c5fitsc2c5residsc2c4fitsc2c4residsFMFitBiomc2c5fitFitNumberc2c4fit
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12.20333155.41438.9685.71.77688.42.4811269455-0.71112694552.3917920921-0.18846209212.3568096202-0.153479620207001.602924811214001.638729524
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Sheet1
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Data
Fit
Biomass density of mussels > 30mm long(gAFDM/sq m)
Intake rate (mgAFDM/s)
Sheet2
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(b)
Data
Fit
Biomass density of mussels > 30mm long(gAFDM/sq m)
Intake rate (mgAFDM/s)
Sheet3
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(c)
Data
Fit
Biomass density of mussels > 30mm long(gAFDM/sq m)
Intake rate (mgAFDM/s)
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(a)
Data
Fit
Numerical density of mussels > 30mm long(no./sq m)
Intake rate (mgAFDM/s)
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(b)
Data
Fit
Numerical density of mussels > 30mm long(no./sq m)
Intake rate (mgAFDM/s)
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(c)
Data
Fit
Numerical density of mussels > 30mm long(no./sq m)
Intake rate (mgAFDM/s)
Predicting the asymptote of the functional response in shorebirds from 486 spot estimates of intake rate
Intake rate (i.e. asymptote) depends on:
Body mass of bird Mass of prey
R2 = 75.5% (log transformed data)
Curlew sandpiperKnotRedshankGrey ploverCurlewOystercatcherTEST OF PREDICTIONS FOR ASYMPTOTEy = x
Test of predictions for asymptotes
Observed asymptotes
Predicted asymptote (mgAFDM/s)
Applications to other species: whatwe need to know
Bird energetics Prey energy content Functional response Interference function Food supply, exposure time and weatherAPPLICATION TO OTHER SPECIES - 2
Interference function for stabbing oystercatchers: intake rate (mgAFDM/s) against density of birds
Prey sizeBird sizeHandling timeRunning speedPredicting interference parameters from Stillmans state-dependent behavioural model Interference function
Test of Stillmans behaviour-based model: cockle-eating oystercatchers on the baie de Somme
Predicted and observed interference functions in cereal-feeding cranes. Predictions from Stillmans model. Data: L. M. Bautista, J. C. Alonso & J. Alonso.
Applications to other species: whatwe need to know
Bird energetics Prey energy content Functional response Interference function Food supply, exposure time and weather Human activitiesAPPLICATION TO OTHER SPECIES and SYSTEMS What do we need to measure?
RECENT DEVELOPMENTS Risk of being killed by predators: trade-off between foraging and safety
Multi-species models:up to 9 species in one estuary
Multi-site models:several estuaries across several countries
SOME EXAMPLES OF RECENT APPLICATIONS IN SHOREBIRDSOystercatchersShellfishing, disturbance 8 estuaries 4 countries
Other shorebirds: Disturbance, habitat loss,12 speciesbait-digging, Spartina 10 estuariesencroachment, hunting 4 countriessea-level rise, monitoringestuary quality, mitigation
WildfowlHunting, farming, wind4 speciesfarms >25 estuaries 4 countriesBlue - examples used here
1. OYSTERCATCHERS and SHELLFISHINGHow much shellfish should we leave after shellfish harvesting to ensure that the birds fitness is not reduced?
EXE: oystercatchers eating musselsPrey biomass/bird left over after shellfish harvesting
Mortality Fail to reach target body mass
%%With disturbanceNo disturbanceRange 1976-19990 55 110 165 kg/bird0 55 110 165 kg/bird
CRITICAL THRESHOLD or ECOLOGICAL FOOD REQUIREMENT (food/bird)Critical threshold = 61kgAFDM/birdPercentage starvingEXE ESTUARY
Ecological requirement Multiples of (threshold)kgAFDM/bird Exe Mussel 61 9.13 7.74
Bangor Mussel 50 9.62 6.42 Burry Cockle 44 9.27 5.58
Wash Cockle 20 7.93 2.52
Somme Cockle 33 6.56 5.03
* Taking into account wastage of shellfish flesh (stolen from the birds; winter loss of flesh from the shellfish themselves) Critical threshold or Ecological requirement (E) Physiological requirement (P)kgAFDM/bird kgAFDM/bird * E/P
Because of interference and individual variation in efficiency, just leaving enough shellfish for oystercatchers after harvesting is not enough to ensure they survive in good condition - as Dutch experience confirmsCONCLUSION: ecological requirements are 3-8 times larger than physiological requirements
2.DISTURBANCE: people and raptors
SOMME : DISTURBANCE IN OYSTERCATCHERSACTUAL AMOUNT:1994-951996-971997-981997-98 including raptors
DISTURBANCES PER HOURPERCENTAGE STARVINGSevere winterMild winter
POLICY ADVICE:
IN SEVERE WINTERS, DO NOT ALLOW OYSTERCATCHERS TO BE DISTURBEDBUTIN MILD WINTERS, THEY CAN BE DISTURBED but only up to about ONE disturbance/hour - including raptors
3.SPREAD OF THE GRASS Spartina ON TO UPSHORE MUDFLATS
SOMME: Spartina spreads downshore at 20-40m per year into the feeding areas of dunlin
High Water mark
0ha 100ha 200ha 0 years 5 years 10 yearsDunlin with Spartina spreading at 40m/yearMortality over winter %POLICY ADVICE: get rid of it!
4.HABITAT LOSS and MITIGATION for it
English ChannelR. SeinePORT (105 ha of mudflats)MITIGATION: Convert reed beds into 50 or 100 ha of mudflatsHigh Water MarkPORT DEVELOPMENT: SEINE ESTUARY
5%
0%Mortality %Before PortAfter Port50ha mitigation 100ha mitigationFailing to reach 75% body mass %15%0%DUNLIN in SEINE ESTUARY: Port development and proposed mitigationScenarioScenario
POLICY ADVICE:
The mitigation is needed but should be 100ha if it is to fully effective
TESTS of model predictions:
Distribution and prey choiceImpact on food supplyHours feeding per daylight tide4Mortality of oystercatchers
CONFIDENCE IN MODEL PREDICTIONS?
Percentage of birds1. DISTRIBUTION and PREY CHOICE: proportion of birds eating cockles or mussels in the Burry InletObserved = Predicted =
2. IMPACT ON FOOD: Mussel consumption by oystercatchers on the ExeObservedPredictedPercentExclosure Survey
Chart3
12.1
12.1
11.4
Deadbirds
BirdBirdName$AgeClFeedMethFightAbPropDomPatTypeIFIRBirdAliveIntDay1FESTI
103+S3113.020.13021109.331000.08354350-0.2668136238
132S2117.650.1765152.451300.058772565-0.2052213001
143+S3131.590.3159189.19140-0.015806585-0.1230982019
163+S3132.340.3234182.76160-0.0198191250.0411479945
252S2139.340.3934177.32250-0.0572691450.1232710927
293+S3114.530.14531122.522900.0754645
362S210.850.0085184.883600.1486525
423+S3115.120.1512197.114200.072308
522S216.470.06471101.255200.1185855
553+S310.240.0024186.245500.151916
563+S319.630.09631100.085600.1016795
573+S310.90.009183.25700.148385
593+S312.650.0265187.955900.1390225
623+S3124.120.2412180.296200.024158
701S1134.580.3458185.42700-0.031803
773+S3124.250.24251105.457700.0234625
783+S3132.960.3296195.41780-0.023136
793+S317.620.07621129.37900.112433
802S2111.530.11531100.478000.0915145
923+S3143.340.4334178.92920-0.078669
942S2143.830.4383172.77940-0.0812905
953+S3145.330.4533186.64950-0.0893155
1042S2137.70.377173.411040-0.048495
1073+S319.040.09041103.410700.104836
1253+S313.880.0388190.3412500.132442
1272S2122.240.22241105.1812700.034216
1283+S314.170.0417189.5712800.1308905
1343+S318.160.0816195.9113400.109544
1403+S3113.120.13121108.0214000.083008
1443+S3138.120.3812168.121440-0.050742
1473+S3143.920.4392190.951470-0.081772
1503+S315.560.0556193.7115000.123454
1523+S313.020.0302172.0515200.137043
1633+S319.370.09371104.9316300.1030705
1703+S3129.360.2936189.571700-0.003876
1733+S31530.53176.011730-0.13035
1792S2115.340.15341117.7817900.071131
1883+S3114.130.14131102.2518800.0776045
1893+S3120.110.20111105.318900.0456115
1963+S313.620.0362197.8119600.133833
1993+S3141.540.4154183.171990-0.069039
2103+S3114.150.14151106.9821000.0774975
2193+S3130.170.3017181.662190-0.0082095
2343+S3146.210.4621172.862340-0.0940235
2411S111.760.01761106.7824100.143784
2423+S3140.150.4015159.262420-0.0616025
2453+S319.480.0948183.7224500.102482
2463+S3121.070.21071100.9124600.0404755
2511S1122.330.2233110525100.0337345
2603+S3114.80.1481101.0126000.07402
2653+S311.380.01381103.9226500.145817
2692S2119.920.1992183.0726900.046628
2813+S3113.380.1338194.9228100.081617
2901S1124.330.2433189.6529000.0230345
2943+S3129.690.2969176.952940-0.0056415
2992S2136.420.3642189.472990-0.041647
3003+S3110.80.1081112.9630000.09542
3103+S3115.650.1565172.0731000.0694725
3173+S3124.280.2428188.2231700.023302
3183+S315.860.05861136.4431800.121849
3303+S3114.150.14151107.8333000.0774975
3512S2111.430.1143194.5935100.0920495
3552S2131.780.3178173.683550-0.016823
3883+S3110.770.10771104.0138800.0955805
3932S2143.060.4306181.813930-0.077171
3983+S3130.170.30171113.783980-0.0082095
4093+S3135.480.3548189.124090-0.036618
4133+S3111.40.1141105.2441300.09221
4223+S3119.960.1996192.5842200.046414
4293+S313.860.0386190.3642900.132549
4303+S316.740.06741116.8243000.117141
4352S2129.280.2928180.84350-0.003448
4373+S317.890.0789192.0743700.1109885
4503+S3131.110.3111192.254500-0.0132385
4623+S3137.530.3753190.164620-0.0475855
4663+S3121.720.2172197.3346600.036998
4693+S3156.120.5612165.154690-0.147042
4873+S3125.890.25891104.3648700.0146885
4892S2124.390.2439164.148900.0227135
4923+S3120.880.20881101.949200.041492
4941S1110.650.1065189.9649400.0962225
4973+S3139.760.3976180.134970-0.059516
5003+S319.230.0923181.8650000.1038195
13+S3171.520.7152199.2511-0.229432
62S2136.930.36931109.2161-0.0443755
83+S3161.650.6165183.1881-0.1766275
122S2166.170.6617194.49121-0.2008095
193+S3129.630.29631120.65191-0.0053205
202S2156.810.56811114.96201-0.1507335
213+S3176.420.76421122.28211-0.255647
223+S3150.90.5091117.62221-0.119115
243+S3145.610.45611115.16241-0.0908135
303+S3170.960.7096190.9301-0.226436
323+S3160.420.6042195.5321-0.170047
343+S3124.870.24871126.173410.0201455
353+S3188.850.88851109.98351-0.3221475
373+S3192.750.92751107.15371-0.3430125
433+S3146.580.46581123.31431-0.096003
453+S3176.070.76071116.32451-0.2537745
493+S3184.480.84481102.03491-0.298768
513+S3132.960.32961100.92511-0.023136
613+S3164.670.64671101.92611-0.1927845
643+S3196.960.96961134.31641-0.365536
652S215.150.0515196.046510.1256475
663+S3168.760.6876181.19661-0.214666
713+S3174.590.74591100.08711-0.2458565
723+S3124.190.24191119.387210.0237835
863+S3192.010.92011114.86861-0.3390535
883+S3194.380.94381106.11881-0.351733
913+S3197.20.9721106.78911-0.36682
1033+S3144.640.44641106.761031-0.085624
1053+S3155.520.5552192.451051-0.143832
1082S2157.30.5731121.931081-0.153355
1093+S3177.290.77291106.111091-0.2603015
1103+S3164.490.64491110.71101-0.1918215
1133+S3195.580.9558177.161131-0.358153
1143+S3178.440.7844195.921141-0.266454
1193+S3172.280.72281105.91191-0.233498
1203+S3162.850.62851103.011201-0.1830475
1223+S3144.80.448178.731221-0.08648
1243+S3146.890.4689180.81241-0.0976615
1303+S3187.410.8741187.931301-0.3144435
1313+S3193.580.9358177.291311-0.347453
1323+S3178.450.7845179.81321-0.2665075
1353+S3139.760.3976170.31351-0.059516
1383+S3135.820.35821102.191381-0.038437
1393+S3125.730.25731127.0713910.0155445
1453+S3123.880.23881138.3414510.025442
1573+S3157.980.57981117.281571-0.156993
1663+S3167.510.6751187.231661-0.2079785
1683+S3187.460.8746175.291681-0.314711
1693+S3168.220.68221113.151691-0.211777
1713+S31990.991101.671711-0.37645
1783+S3138.230.38231101.531781-0.0513305
1803+S3135.120.35121114.811801-0.034692
1823+S3177.450.7745196.591821-0.2611575
1832S2143.950.4395191.211831-0.0819325
1863+S3160.520.6052192.851861-0.170582
1953+S3177.620.77621115.341951-0.262067
1973+S3162.030.62031113.971971-0.1786605
2013+S31780.78185.892011-0.2641
2073+S3131.740.31741119.962071-0.016609
2143+S3182.980.8298192.732141-0.290743
2163+S3175.450.75451110.152161-0.2504575
2183+S3199.940.9994186.252181-0.381479
2203+S3135.040.35041108.172201-0.034264
2242S2144.750.4475179.482241-0.0862125
2273+S3123.020.23021122.422710.030043
2333+S3187.590.8759198.922331-0.3154065
2353+S3164.110.64111112.362351-0.1897885
2383+S3166.990.66991108.412381-0.2051965
2393+S3182.40.8241119.982391-0.28764
2433+S3125.160.25161118.1924310.018594
2443+S3176.770.7677198.282441-0.2575195
2473+S3194.410.94411106.432471-0.3518935
2543+S3191.060.91061105.952541-0.333971
2573+S3196.460.96461131.912571-0.362861
2593+S3195.30.9531107.842591-0.356655
2613+S3152.060.5206175.062611-0.125321
2623+S3177.580.77581114.172621-0.261853
2661S1151.530.5153196.442661-0.1224855
2673+S3142.860.4286196.762671-0.076101
2733+S3178.790.7879198.22731-0.2683265
2743+S3187.030.87031115.762741-0.3124105
2793+S3167.10.6711109.152791-0.205785
2833+S3170.420.7042199.052831-0.223547
2843+S3182.010.82011105.272841-0.2855535
2871S1134.760.34761121.072871-0.032766
3022S2151.820.51821106.693021-0.124037
3033+S3178.350.7835195.223031-0.2659725
3043+S3188.250.8825187.183041-0.3189375
3063+S3150.60.506194.763061-0.11751
3113+S3189.810.89811114.453111-0.3272835
3193+S3171.440.7144199.553191-0.229004
3203+S3134.110.34111100.73201-0.0292885
3253+S3175.080.7508187.263251-0.248478
3293+S3184.170.8417172.453291-0.2971095
3353+S3166.80.6681118.473351-0.20418
3423+S31950.95187.853421-0.35505
3453+S3179.010.7901195.823451-0.2695035
3463+S317.510.0751199.6834610.1130215
3473+S3156.710.56711111.273471-0.1501985
3493+S3151.840.51841110.973491-0.124144
3523+S3157.940.5794188.73521-0.156779
3533+S3166.940.6694180.263531-0.204929
3603+S3167.440.67441103.63601-0.207604
3622S2156.970.5697186.723621-0.1515895
3652S2120.040.20041111.2236510.045986
3673+S3186.010.86011125.533671-0.3069535
3743+S3152.610.52611120.483741-0.1282635
3783+S3144.630.4463190.513781-0.0855705
3791S1146.470.46471125.33791-0.0954145
3833+S3155.890.5589189.743831-0.1458115
3913+S3193.20.9321103.553911-0.34542
3923+S3135.990.35991117.963921-0.0393465
4013+S3151.390.51391108.34011-0.1217365
4023+S3174.410.7441193.244021-0.2448935
4063+S3112.420.1242198.840610.086753
4103+S3132.440.32441115.144101-0.020354
4113+S3136.70.3671116.494111-0.043145
4143+S3153.990.5399193.694141-0.1356465
4153+S3186.720.8672187.394151-0.310752
4173+S3152.470.5247195.594171-0.1275145
4233+S3191.430.91431115.484231-0.3359505
4243+S3133.520.33521103.634241-0.026132
4273+S3186.880.8688175.424271-0.311608
4323+S3198.270.9827177.854321-0.3725445
4363+S3163.430.6343195.514361-0.1861505
4383+S3123.350.23351119.9643810.0282775
4393+S3162.530.62531116.554391-0.1813355
4403+S3184.520.8452188.254401-0.298982
4443+S3164.750.64751118.924441-0.1932125
4453+S3158.440.5844196.614451-0.159454
4553+S3168.040.6804194.614551-0.210814
4573+S3168.570.68571103.454571-0.2136495
4603+S3141.90.4191112.464601-0.070965
4682S2133.410.33411120.754681-0.0255435
4713+S3190.350.9035197.964711-0.3301725
4743+S3193.350.93351109.774741-0.3462225
4763+S3174.260.7426175.624761-0.244091
4793+S3133.480.33481102.44791-0.025918
4803+S3168.410.68411109.594801-0.2127935
4813+S3196.530.9653198.84811-0.3632355
4883+S3142.480.4248196.754881-0.074068
4933+S3154.360.5436168.164931-0.137626
Deadbirds
0.083543-0.229432-0.2668136238
0.0587725-0.0443755-0.2052213001
-0.0158065-0.1766275-0.1230982019
-0.019819-0.20080950.0411479945
-0.057269-0.00532050.1232710927
0.0754645-0.1507335
0.1486525-0.255647
0.072308-0.119115
0.1185855-0.0908135
0.151916-0.226436
0.1016795-0.170047
0.1483850.0201455
0.1390225-0.3221475
0.024158-0.3430125
-0.031803-0.096003
0.0234625-0.2537745
-0.023136-0.298768
0.112433-0.023136
0.0915145-0.1927845
-0.078669-0.365536
-0.08129050.1256475
-0.0893155-0.214666
-0.048495-0.2458565
0.1048360.0237835
0.132442-0.3390535
0.034216-0.351733
0.1308905-0.36682
0.109544-0.085624
0.083008-0.143832
-0.050742-0.153355
-0.081772-0.2603015
0.123454-0.1918215
0.137043-0.358153
0.1030705-0.266454
-0.003876-0.233498
-0.13035-0.1830475
0.071131-0.08648
0.0776045-0.0976615
0.0456115-0.3144435
0.133833-0.347453
-0.069039-0.2665075
0.0774975-0.059516
-0.0082095-0.038437
-0.09402350.0155445
0.1437840.025442
-0.0616025-0.156993
0.102482-0.2079785
0.0404755-0.314711
0.0337345-0.211777
0.07402-0.37645
0.145817-0.0513305
0.046628-0.034692
0.081617-0.2611575
0.0230345-0.0819325
-0.0056415-0.170582
-0.041647-0.262067
0.09542-0.1786605
0.0694725-0.2641
0.023302-0.016609
0.121849-0.290743
0.0774975-0.2504575
0.0920495-0.381479
-0.016823-0.034264
0.0955805-0.0862125
-0.0771710.030043
-0.0082095-0.3154065
-0.036618-0.1897885
0.09221-0.2051965
0.046414-0.28764
0.1325490.018594
0.117141-0.2575195
-0.003448-0.3518935
0.1109885-0.333971
-0.0132385-0.362861
-0.0475855-0.356655
0.036998-0.125321
-0.147042-0.261853
0.0146885-0.1224855
0.0227135-0.076101
0.041492-0.2683265
0.0962225-0.3124105
-0.059516-0.205785
0.1038195-0.223547
-0.2855535
-0.032766
-0.124037
-0.2659725
-0.3189375
-0.11751
-0.3272835
-0.229004
-0.0292885
-0.248478
-0.2971095
-0.20418
-0.35505
-0.2695035
0.1130215
-0.1501985
-0.124144
-0.156779
-0.204929
-0.207604
-0.1515895
0.045986
-0.3069535
-0.1282635
-0.0855705
-0.0954145
-0.1458115
-0.34542
-0.0393465
-0.1217365
-0.2448935
0.086753
-0.020354
-0.043145
-0.1356465
-0.310752
-0.1275145
-0.3359505
-0.026132
-0.311608
-0.3725445
-0.1861505
0.0282775
-0.1813355
-0.298982
-0.1932125
-0.159454
-0.210814
-0.2136495
-0.070965
-0.0255435
-0.3301725
-0.3462225
-0.244091
-0.025918
-0.2127935
-0.3632355
-0.074068
-0.137626
Dead
Alive
Discriminant
Feeding Efficiency (%)
STI at the start of the winter
MusselsLost
Exclosures12.1
Estuary-wide12.1
Model prediction11.4
MusselsLost
0
0
0
Percent
Percent of mussels lost over the winter
DisturbanceCosts
NoDist%dead
500499.33333333330.1333333333
1000995.66666666670.4333333333
15001459.66666666672.6888888889
20001882.66666666675.8666666667
3500301014
5000385023
75004693.333333333337.4222222222
100005153.333333333348.4666666667
&R&14&D
DisturbanceCosts
00.13333333330.41.066666666711.0666666667
01.22.33333333337.320.6666666667
04.46.9113.8230.5333333333
07.911.320.8554.3766666667
015.236666666723.6240.096666666763.6666666667
027.733333333337.653.066666666775.3766666667
041.4753.066666666765.1180.0333333333
053.163.566666666772.80
No Disturbance
10% without costs
10% with costs
50% without costs
50% with costs
Initial number of birds
Percent mortality
Costs of disturbance
NoDepletion
0.13333333330.13333333330.13333333330.20.06666666670.40.41
1.13333333330.43333333331.03333333330.93333333331.43333333332.33333333333.97
4.62.68888888894.37666666673.97666666673.75666666676.9112.58
7.98333333335.86666666677.48333333337.257.516666666711.318.8266666667
17.33333333331415.813333333317.523333333315.8123.6240.0566666667
29.33333333332326.266666666725.266666666724.837.660.05
45.333333333337.422222222242.356666666741.641.823333333353.066666666786.8
55.848.466666666753.352.566666666751.033333333363.566666666798.9766666667
Big
NoDist
BigNC
Best10
Worst10
Small
SmallNC
Initial number of birds
Percent mortality
10% of area disturbed or lost
0.66666666670.13333333330.80.66666666670.83.26666666671.0666666667
5.63333333330.43333333333.75.93333333335.611.06666666677.3
12.66666666672.68888888899.513333333312.5810.846666666720.666666666713.82
18.93333333335.866666666714.7518.883333333316.083333333330.533333333320.85
36.28333333331429.6238.7633.426666666754.376666666740.0966666667
49.62340.450.733333333343.463.666666666753.0666666667
62.843333333337.422222222257.3866.933333333360.6275.376666666765.11
69.733333333348.466666666766.375.066666666775.433333333380.033333333372.8
Big
NoDist
BigNC
Best50
Worst50
Small
SmallNC
Initial number of birds
Percent mortality
50% of area disturbed or lost
FileExtAgeFM% in fieldsProportion of time feedingMean mass loss% MortalityInitial NFinal NULDepULNoDep
00a001AllAll4.410.5410.010.250049900.0666666667
00b001AllAll15.230.6420.860.310009970.83333333330.8333333333
00c001AllAll23.20.7223.021.07150014842.88888888892.2444444444
00d001AllAll32.160.7847.442.4200019526.16666666675.3833333333
0.00E+00AllAll58.150.8815.186.573500327015.714285714313.9047619048
00f001AllAll69.090.90817.0911.65000442026.733333333322.8666666667
00g001AllAll78.460.95823.217.077500622046.088888888939.6888888889
00h001AllAll82.240.97243.0623.510000765061.066666666750.8333333333
00i001AllAll82.890.97657.7130.72125008660
00j001AllAll84.550.98173.8237.93150009310
00k001AllAll85.640.982108.0260.35200007930
00l001AllAll88.550.992140.5486.43300004070
500499.6666666667
991.6666666667991.6666666667
1456.66666666671466.3333333333
1876.66666666671892.3333333333
29503013.3333333333
3663.33333333333856.6666666667
4043.33333333334523.3333333333
3893.33333333334916.6666666667
000
000
000
000
000
000
000
000
0
0
0
0
No decline
Depletion
No Depletion
Number of oystercatchers in September
Percent starving by March
500
991.6666666667
1456.6666666667
1876.6666666667
2950
3663.3333333333
4043.3333333333
3893.3333333333
Initial N
3. HOURS FEEDING: oystercatcher (open symbols), little stint, sanderling, dunlin, curlew. Exe estuary, Burry Inlet, Bangor flats, Seine estuary; Cadiz bay.
4. MORTALITY (from autumn to spring) % (se) % (se) N* Predicted ObservedWash*: shellfish abundant 4 0 1.4 (0.3) Wash*: shellfish scarce 3 15.9(4.9) 16.8 (6.4)Exe: low bird density 3 2.3(0.4) 1.7 (0.3)Exe: high bird density 3 3.8(0.1) 3.5 (1.0)Burry Inlet: cockles and mussels: 1 0 ?Bangor mussel beds: 1 0 ?
* Number of years* Assuming upshore intake rates same as on Exe
Basic principles upon which the models are built
1 Well-established behavioural decision rules so that animals in the model are likely to respond to environmental changes as real ones would
2 Include some natural history details because these adaptations can be critical to bird survival
3Calibration may be needed - because we don't know every parameter value precisely
4 Validation of mortality predictions otherwise predictions should not be believed
http://www.dorset.ceh.ac.uk/shorebirds/FIND OUT MORE ON:Co-workers:Richard Stillman Richard Caldow Sarah Durell Andy West
EVEN A SMALL DECREASE IN MORTALITY COULD BE VERY IMPORTANT!!
Equilibrium population size..population size is very sensitive to mortality rate, irrespective of the density-dependence on the breeding groundsWeak density dependence in summer Oystercatcher rangeStrong density dependence in summer
Chart1
161.96473.868
56.34295.504
29.5128.314
18.2360.596
0.5960.102
0.1020.07
0.07
bT = 0.3
bT = 0.7
Adult annual mortality (%)
Sheet1
Adult mortality (%)Stable Population Size
bT = 0.3bT = 0.7
214338641619601433.864161.96
447386856342473.86856.342
6955042951095.50429.51
8283141823628.31418.236
105965960.5960.596
121021020.1020.102
1470700.070.07
1624240.0240.024
Sheet1
00
00
00
00
00
00
0
bT = 0.3
bT = 0.7
Adult mortality (%)
Equilibrium Population Size (000s)
Sheet2
Sheet3
The model had to be able to predict FITNESSMortality rate over the winterBUT ALSO2Fat reserves in springPRINCIPLE: If the FITNESS of the birds in the non-breeding season is maintained, the quality of the estuary for the birds is being maintained