A multi-criteria targeting approach to neutral grassland conservation

A multi-criteria targeting approach to neutral grassland conservation

Julian Bayliss*, Alice Helyar, John T. Lee, Stewart Thompson

Department of Biological and Molecular Sciences Geographical Information Systems and Habitats Research Group, Oxford Brookes University,

Gipsy Lane Campus, Headington, Oxford OX3 0BP, UK

Received 16 August 2002; accepted 6 September 2002

Abstract

Resources for creating and managing rare habitats are limited, and a targeting approach aimed at identifying the most viable sites for

habitat conservation is therefore desirable. This study developed a multi-criteria targeting approach to site conservation for two rare

grassland types, based on a suite of biotic and abiotic factors managed within a Geographical Information System. A number of biotic and

abiotic criteria were assessed to evaluate the biodiversity status of grassland sites. Biotic factors included species diversity, species richness

and species rarity; and abiotic factors included patch area, position in the ecological unit and the influence of surrounding land use. Each

criterion was given equal weighting and a final biodiversity value for each patch was calculated; the patch with the highest cumulative rank

score was deemed the patch with the greatest biodiversity. Each site was then examined in relation to agricultural land under the existing

management prescriptions of the Upper Thames Tributaries Environmentally Sensitive Area (UTTESA). Sites identified with high

biodiversity potential, but currently not included under management prescriptions, were targeted for future inclusion in the ESA scheme. The

targeting approach demonstrated how the national Lowland Meadows habitat action plan creation target of 500 ha could be achieved in the

UTTESA. The fact that this target figure was so easily attained within this study area highlighted the possible underestimation of national

habitat creation targets.

q 2002 Elsevier Science Ltd. All rights reserved.

Keywords: ESA; GIS; Habitat action plans; Mesotrophic grasslands

1. Introduction

This research is undertaken as a contribution to the

growing interest in the conservation of neutral grasslands

in the UK. Although the discussions may at times be

technical the issues are straightforward: how do we choose

those grassland sites to which our limited resources should

be allocated, and are more ambitious conservation targets

achievable within those resources. A targeting approach

has been developed with an existing agri-environment

scheme in mind as the funding mechanism. This is the

environmentally sensitive area (ESA) scheme which is

managed by the Department for Environment, Farming,

and Rural Affairs (DEFRA) in the UK. The work is

supported by the GIS and Habitats Research Group at

Oxford Brookes University, UK.

2. Situation

Lowland mesotrophic ‘neutral’ grasslands are rare and

threatened habitats, specifically the lowland flood meadows

Alopecurus pratensis–Sanguisorba officinalis (hereafter

referred to as type MG4) and old grazed hay meadows

Cynosurus cristatus–Centaurea nigra (hereafter referred to

as type MG5) (Rodwell, 1998). These habitats are listed

under Annex 1 of the European Union’s Directive 92/43/

EEC on the Conservation of Natural Habitats and of Wild

Fauna and Flora (EEC, 1992), commonly known as the

‘Habitats Directive’, as priority habitat requiring special

conservation measures. In the UK these habitats are covered

by a habitat action plan (HAP) with a commitment to

conserve and enhance their distribution in response to

dramatic declines in former ranges (Fuller, 1987; Hopkins,

1990; Jefferson and Robertson, 1996; Young, 2000). For

example, the Lowland Meadows HAP sets a target of 500 ha

of lowland hay meadow to be re-established by 2010 on

carefully targeted sites (Wynne et al., 1995; UK Biodiver-

sity Steering Group, 1999). It is estimated that in the UK

0301-4797/02/$ - see front matter q 2002 Elsevier Science Ltd. All rights reserved.

doi:10.1016/S0301-4797(02)00202-5

Journal of Environmental Management 67 (2003) 145–160

www.elsevier.com/locate/jenvman

* Corresponding author. Tel.: þ44-1865-483269; fax: þ44-1865-

483242.

E-mail address: [email protected] (J. Bayliss).

http://www.elsevier.com/locate/yjema

there has been a loss of 97% of semi-natural lowland

meadow sites between 1938 and 1984, with further national

declines of between 2 and 10% per annum (UK Biodiversity

Steering Group, 1999). These losses are largely due to

agricultural intensification and drainage. The HAP esti-

mates that MG5 grassland currently covers between 5000

and 10 000 ha in England and Wales, whilst MG4 has a total

cover of less than 1500 ha; 10% of which can be found in

Oxfordshire (Stevenson and Liwicki, 1999).

3. Problem statement

This neutral grassland resource is highly fragmented,

being characterised by a number of small isolated patches

and it is generally considered desirable to reduce these

levels of fragmentation with judicious spatial targeting of

both conservation and expansion measures.

4. Goals, targets, hypotheses

If this is to occur it is important first to identify those sites

of high conservation potential (in terms of biodiversity

assessment criteria) to include within the reserve network;

and second, to target expansion around these sites to

encourage re-generation accompanied by appropriate in-site

management. As the majority of lowland neutral grassland

is located in some of the most intensively farmed country-

side in the UK it is logical to enlist the support of land

managers to help achieve the UK HAP targets of the Upper

Thames Tributaries Environmentally Sensitive Area

(UTTESA). This study will consider how much of this

national target can be realistically achieved within the study

area, taking into account the individual requirements of the

biodiversity action plan (BAP) species associated with the

habitat.

5. Materials and methods

5.1. Study area

Introduced in 1987 the ESA scheme aims to protect

countryside of high landscape, wildlife or historic value (i.e.

land that is deemed ‘sensitive’). The ESA initiative is one of

several agri-environment schemes that are designed to

encourage sympathetic agricultural practices; farmers enter

land under specific management prescriptions and receive

payments for farming in an environmentally friendly

manner. There are currently a total of 22 ESA schemes in

England covering 10% of all agricultural land, of which

532 000 ha were under management prescriptions in 2000

(DEFRA, 2001).

The UTTESA, created in 1994, was the last ESA to be

designated in the UK. It covers an area of 27 000 ha and

incorporates the five main tributaries of the Upper Thames

river. These are the rivers Windrush, Evenlode, Glyme,

Cherwell, and Ray (Fig. 1). The majority of the UTTESA is

located within Oxfordshire although parts are also found in

Buckinghamshire, Gloucestershire, and Northamptonshire

(ADAS, 1997, 1998). Generally the land within the

UTTESA is a mosaic of agricultural lands, principally

arable land and improved grasslands, with isolated pockets

of lowland flood meadows (MG4) and old grazed hay

meadows (MG5). The respective land management pre-

scriptions undertaken in the UTTESA are managed through

the Department for Environment, Food and Rural Affairs

(DEFRA).

There are five types of management prescriptions

(known as ‘tiers’) available to farmers in the UTTESA

and these generally relate to the initial state of the habitat.

Tier 1A has to be managed under a permanent grassland

management plan with restrictions on grazing and fertiliser

use. Tier 1B has all the management prescriptions of Tier

1A plus certain restrictions on harvesting dates and stocking

rates. Tier 2 has all the management prescriptions of Tier 1

plus requirements on the maintenance of water levels. Tier

3A prescriptions relate the reversion of arable land to

extensive permanent grassland, and Tier 3B relates to the

reversion of arable land to lowland wet grassland. As of

December 1997 there were 226 land management agree-

ments in the UTTESA (ADAS, 1998).

5.2. GIS and ecology

With a fragmented rural matrix composed of a mosaic of

habitat patches, as is commonly the case in the UK, a spatial

targeting approach to site conservation is desirable. This

approach not only takes into account the biodiversity but

also the spatial dynamics of the focal habitat. To assess the

spatial dynamics of habitats and species within the study

area a geographical information system (GIS) was devel-

oped. GIS are increasingly used as tools to assist in policy

formulation for both inventory purposes and in addressing

wider strategic issues, such as screening of ESA agreement

applications to maximise environmental benefits from

limited financial resources (Swetnam et al., 1998). GIS

development, specifically to identify and target sites for

habitat and species conservation, is increasingly being

employed as a conservation management tool (Pereira and

Itami, 1991; Potter et al., 1993; Veitch et al., 1995; Cook

and Norman, 1996; Bian and West, 1997; Brown et al.,

1998; Lee et al., 2001; Lurz et al., 2001).

6. Methods

The habitat ranking scheme of neutral grassland patch

quality in the UTTESA required the assessment of seven

biotic and abiotic factors (Table 1) incorporated within five

criterion. Four of the main criteria were based on the Ratcliffe

J. Bayliss et al. / Journal of Environmental Management 67 (2003) 145–160146

(1977) criteria of habitat assessment: patch size, diversity

(floral and faunal, and species richness), rarity, and position in

the ecological unit. The fifth criterion, restoration potential,

was developed to assess the feasibility of expanding the site

based on a factor due to surrounding land use.

Species were chosen on the basis of their association

with MG4 and MG5 habitat types (Rodwell, 1998), as well

as their status in the UK BAP and the local biodiversity

action plan (LBAP) (Dodds et al., 1995; ONCF, 1998) in

which they are listed as threatened and have declining

populations. The nine species chosen were skylark (Alauda

arvensis), curlew (Numenius arquata), lapwing (Vanellus

vanellus), reed bunting (Emberiza schoeniclus), reed

warbler (Acrocephalus scirpaceus), snipe (Gallinago

Fig. 1. Location of the UTTESA in the UK.

J. Bayliss et al. / Journal of Environmental Management 67 (2003) 145–160 147

gallinago), redshank (Tringa totanus), yellowhammer

(Emberiza citrinella), and water vole (Arvicola terrestris).

For ease of reference, the 79 neutral grassland sites were

numbered and named according to their location in each

tributary branch listed in numerical order. The branches

were numbered 1–7

1. River Thames A (Buscot GR: SU 230 980 to Newbridge

GR: SP 404 014, at the confluence of the Windrush and

Thames)

2. River Windrush (Bourton-on-the-water GR: SP 173 200

to Newbridge GR: SP 404 014)

3. River Evenlode (Bledington GR: SP 268 205 to

Cassington GR: SP 448 100)

4. River Glyme (Old Chalford GR: SP 345 255 to Bladon

GR: SP 430 142)

5. River Cherwell (Hinton GR: SP 537 524 to Iffley GR: SP

524 028)

6. River Ray (Edgcott GR: SP 680 215 to Islip GR: SP 523

137)

7. River Thames B (Newbridge GR: SP 404 014 to Iffley

GR: SP 524 028).

For example, site 6.10 represents the 10th site on the

River Ray (tributary 6).

6.1. Biotic criteria

6.1.1. Floral diversity

National vegetation classification (NVC) surveys were

obtained for the neutral grassland sites from English Nature

and the local wildlife trust. The vegetation survey data were

then analysed using the MATCH programme (Malloch,

1999), which assesses the similarity between pairs of

vegetation communities. MATCH calculated the simi-

larities between sample data and NVC communities by

means of the Czekanowski similarity coefficient, which

assesses similarity between pairs of communities in terms of

their species composition. MATCH lists the NVC commu-

nities and sub-communities that are most similar to the data

collected. The output was used to assess quality of the

vegetation community in relation to the expected species

composition in the NVC classification system for MG4 and

MG5 communities. Sites were ranked twice, once according

to the NVC MATCH coefficient for type MG4 and again for

type MG5. The site with the highest MATCH similarity

coefficient was ranked highest. Tied scores were not

resolved.

6.1.2. Species richness—fauna

The presence/absence of 9 LBAP target species (Table 2)

on each site were assessed using known distribution records

of individuals between 1995 and 2001. The nine species

were chosen as they are both highly dependent upon the

MG4 and MG5 habitat types for feeding and breeding areas,

and there are nationally agreed targets for their population

expansion (Wynne et al., 1995; UK Biodiversity Steering

Group, 1999). Vector data map layers were created from six

figure UK national grid references accurate to the nearest

100 m, and four figure grid reference points accurate to the

nearest 1000 m, the latter centred in the middle of the grid

square to account for the coarse resolution. Species

distribution on the grassland sites was then scored using

the GIS software package ArcVieww and the number of

species present within the boundaries of each neutral

grassland site recorded to assess the suitability of each

patch to support a range of species. Sites with the most

species were ranked highest. Tied scores were not resolved.

6.1.3. Faunal diversity

In order to assess the species diversity of the neutral

grassland sites the abundance data of each species present

on the patch was used to calculate the Shannon–Wiener

Index of Diversity (Fowler and Cohen, 1995; Sutherland,

1997). Species abundance at each site was calculated as the

mean abundance per year over the number of years the

species had been recorded at the site. If several observations

existed for each site, the mean abundance for each

observation was calculated to give the total abundance on

site. Sites with high species diversity were ranked highest.

Tied scores were not resolved.

6.1.4. Species rarity

Using the species richness data for each site, the rarity of

the species present was scored according to their listing in

the UKBAP and the LBAP, which included the rate of

decline, local rarity, and local distinctiveness. All data were

collected annually in accordance with nation wide agreed

survey techniques, e.g. the British Trust for Ornithology

Table 1

Criteria included in the analysis

Data type Specific Criteria used in

selecting sites

Biotic Species diversity Floral diversity according to

lowland floodplains (code MG4)

and old grazed hay

meadows (code MG5) community

characteristics

Species richness (fauna) of

selected LBAP species

Species diversity (fauna)

Rarity Species rarity (fauna) according

to listings in the

UK BAP and LBAP,

rates of decline, local

rarity and local distinctiveness

Abiotic Patch size Patch area (ha)

Position in the ecological

unit

Minimum nearest neighbour distance

(minNN), edge to edge

Degree of landscape fragmentation

Potential to expand A factor due to

surrounding land use


(BTO) Breeding Bird Survey (BBS) (Bibby et al., 2000).

The species were ranked according to their final rarity score

(Table 2). Local (Oxfordshire) rate of decline over the last

25 years was scored according to species whose range or

numbers were rapidly declining (50–100%), declining (25–

49%), or ‘stable’ (24% decline or a 24% increase) following

the assessment criteria outlined in Oxfordshire’s LBAP

(ONCF, 1998). Local rarity was also assessed on a tetrad

scale (2 km2) in terms of those species that were rare

(occurring in 0.6% tetrads or less in Oxfordshire), those that

were scarce (occurring in 0.6–4.0% of tetrads in Oxford-

shire), and those that were common (occurring in more than

4.0% tetrads in Oxfordshire). Local distinctiveness was

scored according to flagship species (high profile species),

keystone species (ecologically important species), and

typical species (species characteristic within Oxfordshire).

Each site was then scored according to the sum of the

ranked species present; for example, species present may

include curlew (ranked 2), snipe (ranked 8) and water vole

(ranked 9), scoring a total of 19 for this site (refer to

Table 2). Sites were then ranked according to their total

species rarity; those with the greatest cumulative species

rarity were ranked highest. Tied scores were not resolved.

6.2. Abiotic criteria

6.2.1. Patch size

Sites were ranked according to their area, which was

recorded from the attribute database from the vector data

map layer of the neutral grassland sites in the GIS. Landuse

information was obtained from DEFRA. The largest patches

were ranked highest. Tied scores were not resolved.

6.2.2. Position in the ecological unit

Contiguous sites are much more likely to be of greater

conservation value than fragmented sites (Ratcliffe, 1977).

The connectivity of the neutral grassland habitats and their

position in the ecological landscape were assessed using the

spatial analyst programme FRAGSTATSArc (McGarigal

and Marks, 1995). This calculated the minimum nearest

neighbour distance (minNND) of the neutral grassland

patches in the UTTESA. MinNND is defined as the distance

from one patch to another based on edge-to-edge distance

(McGarigal and Marks, 1995). Patches with the highest

minNND, i.e. the most remote patches, were ranked lowest.

Tied scores were not resolved. It was assumed that there

were no suitable habitats between the patches and that patch

colonisation was dependent on the minimum nearest

neighbour distance (Beier and Noss, 1998; Harrison and

Bruna, 1999). For this reason, more isolated patches were

assumed to be less diverse than contiguous patches.

6.2.3. Surrounding land use

Surrounding land use types were assessed for restoration

potential based on the suitability for habitat expansion. The

primary factors involved in this assessment were proximityTab

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to known resources (i.e. other neutral grassland sites), the

size of individual patches, and the degree of shared

perimeter (if any) between patches. The land use GIS

database was divided into nine categories (Table 3), which

were assigned one of four indices of their restoration

potential to neutral grassland: good (G), moderate (M), poor

(P) or impossible (I).

The surrounding land use criterion was calculated from

the length of the shared boundary between each habitat

patch and the adjacent land, and expressed as a percentage

of the total patch perimeter. Water courses were ignored if

they bordered neutral grassland patches and the next

terrestrial landuse was considered. A 100 m buffer of the

adjacent land was included in the calculation to account for

this. As waterways do not present an insurmountable barrier

to the dispersal of many of the target species, this research

assumed that it is possible to restore grassland habitats on

either side of waterways. The 100 m buffer therefore

increased the area of land over which restoration potential

was calculated, accounting for the immediate boundaries.

Each patch was then ranked four times according to the

amount of perimeter it shared with land of good, moderate,

poor or impossible restoration potential. When the patches

were ranked for good and moderate restoration potential,

patches with the greatest shared perimeter were ranked first.

Patches with the greatest shared perimeter with land of poor

or impossible restoration potential were ranked last (Lee

et al., 2001). To account for the importance of sharing a

perimeter with land of high restoration potential and reflect

the difficulty of restoring land of impossible restoration

potential, these ranks were given double weighting.

The total scores were ranked so that neutral grassland

patches adjacent to land of poor and impossible restoration

potential were ranked lowest and patches adjacent to land of

high and moderate restoration potential were ranked highest

(Lee et al., 2001 for a full explanation of the methodology).

Tied scores were not resolved. The four ranks were summed

to rank the sites in order of their overall restoration

potential.

6.3. Final ranking

The seven criteria were summed with equal weight with

the highest scoring, most diverse patch ranked first. Separate

algorithms were developed for MG4 and MG5 scores from

each patch, thereby creating two separate lists of ranked

patches, enabling targeting of sites for conservation and

enhancement based on the community composition for both

grassland types. The final patch rank was assigned based on

the following algorithm

MG4 sites¼floral diversity ðMG4Þþ species richness

þ species diversityþ species rarity

þpatch sizeþminNND

þ expansion potentialðlanduseÞ:

and

MG5 sites¼floral diversityðMG5Þþ species richness

þ species diversityþ species rarityþpatch size

þminNNDþ expansion potentialðlanduseÞ:

The results obtained from the final ranking process were

compared with a list of existing site designations to assess

the effectiveness of the overall methodology. Sites were

selected for enhancement in order of their ranked biodi-

versity value, with the highest ranked site selected first.

Land immediately adjacent to the top ranked sites was

assessed for the suitability of expansion through two

criteria. Firstly the expansion potential based on proximity

to known resources, the size of individual patches, and the

degree of shared perimeter between patches; and secondly

the occurrence of adjacent land under an existing ESA

management prescription. This method identified the most

desirable MG4 and MG5 sites for habitat creation up to the

500 ha target. An algorithm was developed accordingly

(Fig. 2).

7. Results

7.1. Biotic criteria

7.1.1. Floral diversity

Fifty-nine of the 79 neutral grassland patches in the

UTTESA were included in the study as these had NVC

survey data. NVC MATCH similarity coefficients ranged

from 69.9 to 2.0% for MG4 communities and 63.9 to 4.7%

for MG5 communities. Although patches with MATCH

coefficients below 40% were deemed to be a poor goodness

of fit, they were still ranked to provide an indication of the

species composition in relation to MG4 and MG5

communities.

Table 3

Landuse database categories and relative restoration potential

Landuse type Restoration potential

Floodplain grassland Good

Floodplain arable Good

Floodplain margins Moderate

Non agricultural Impossible

Open water Impossible

Other arable Moderate

Other grassland Good

Other margins Poor

Woodland and scrub Poor


7.2. Fauna

7.2.1. Species richness

Table 4 shows the results of the patch ranking using

species richness. Sites with more than one record for each

species indicate that the species was sighted at more than

one location within the patch. Only 20 of the 59 patches

have had target species recorded within their boundaries

since 1995.

7.2.2. Species diversity

The Shannon–Wiener Index of Diversity was calculated

for each patch (Table 4). Sites with only one recorded

species scored a diversity index of 0 indicating a patch

without diversity. However, these sites were more diverse

than patches without any recorded species, which also

scored a diversity of 0. Scoring the species richness

therefore accounted for this difference.

7.2.3. Species rarity

Species rarity was scored to reflect the importance of

species present on the sites. Table 4 shows the site ranking

using species rarity scores. For example site 7.29 was

ranked as the patch with the highest occurrence of rare

species with a score of 43 (out of a possible maximum score

of 48).

7.2.4. Final patch ranking of biotic criteria

The sum of the ranks and the final patch ranking of biotic

criteria for MG4 and MG5 grassland communities are

shown in Table 4. Sites 1.2, 1.6 and 5.6 were ranked as the

top three patches with the highest scoring biotic criteria for

MG4 vegetation communities. Sites 1.2, 1.6, and 6.10 were

ranked as the top three patches with the highest scoring

biotic criteria for MG5 vegetation communities. These sites

consistently had well matched vegetation communities to

MG4 and MG5 characteristics, and high-ranking species

diversity and rarity.

7.3. Abiotic criteria

7.3.1. Patch area

Patches ranged in size from 212.2 to 0.17 ha (Table 5).

The mean patch area was 20.43 ha (Std ¼ 36.6), which is

above the national average as most grassland sites in

England are less than 10 ha (Jefferson and Robertson, 1996).

The large mean patch area was skewed due to the presence

of three extensive large areas of neutral grassland; site 6.10

(212 ha), site 7.29 (165 ha), and site 1.3 (91.7 ha). However,

as 22 additional patches were larger than 10 ha, the large

mean patch size illustrated the importance of the UTTESA

for MG4 and MG5 grasslands.

7.3.2. Position in the ecological unit

Thirty-seven patches were directly contiguous with other

neutral grassland patches and therefore had a minNND of

0 m (Table 5). These patches were treated as separate

patches due to their distinct biotic and abiotic character-

istics. The mean minNND was 649.2 m (Std ¼ 1603.1),

with a maximum of 7920.2 m. The variation in inter-patch

distance reflects the fragmented nature of neutral grassland

habitats. However, the relatively small mean distance

between patches is indicative of the high concentration of

neutral grassland habitats within the UTTESA boundary.

7.3.3. Surrounding landuse

The results of the patch ranking based on the surrounding

land use scores are shown in Table 5. The highest ranked

patch (site 6.1) had high expansion potential as it had the

greatest proportion of adjoining land of good and moderate

restoration potential, being completely surrounded by

grassland and arable land. The majority of patch boundaries

were shared with land of good restoration potential

(mean ¼ 62.2%). Patch boundaries shared with land of

impossible and moderate restoration potential were also

frequent (mean perimeter shared ¼ 22.0% and 14.5%,

respectively); however, shared boundaries with land of

Fig. 2. Algorithm to identify suitable land adjacent to grassland sites to achieve the restoration target of 500 ha.


Table 4

Patch ranking according to biotic criteria: species richness, species diversity (2H), and species rarity

Site Sp richness Sp richness rank 2H 2H rank Sp rarity Sp rarity rank Total rank score

(MG4)

Final rank

(MG4)

Total rank score

(MG5)

Final rank

(MG5)

1.2 3 53 0.8 58 19 55 217 1 221 1

1.6 4 55 1.3 59 12 51 214 2 212 3

5.6 2 51 0.1 51 16 54 210 3 206 5

6.10 8 58 0.2 53 39 57 203 4 216 2

6.9 8 58 0.2 52 39 57 197 5 207 4

7.29 7 57 0.4 56 43 59 195 6 204 6

6.7 3 53 0.3 54 12 51 191 7 187 8

5.2 6 56 0.3 55 32 56 186 8 184 9

2.11 2 51 0.7 57 13 53 183 9 200 7

7.11 1 40 0 1 2 40 140 10 133 11

7.10 1 40 0 1 2 40 136 11 140 10

1.3 1 40 0 1 2 40 134 12 132 12

7.12 1 40 0 1 2 40 128 13 126 13

5.10 1 40 0 1 8 48 121 14 119 14

6.11 1 40 0 1 5 46 104 15 101 17

2.12 1 40 0 1 8 48 101 16 104 16

4.1 1 40 0 1 2 40 97 17 107 15

5.3 1 40 0 1 8 48 92 18 92 18

7.4 1 40 0 1 2 40 90 19 91 19

2.10 1 40 0 1 5 46 88 20 88 20

7.6 0 1 0 1 0 1 61 21 58 22

1.1 0 1 0 1 0 1 59 22 61 21

6.5 0 1 0 1 0 1 59 22 58 22

5.5 0 1 0 1 0 1 55 24 55 25

1.4 0 1 0 1 0 1 53 25 52 26

2.4 0 1 0 1 0 1 51 26 38 35

1.8 0 1 0 1 0 1 49 27 45 30

6.4 0 1 0 1 0 1 48 28 49 27

7.14 0 1 0 1 0 1 47 29 28 41

7.20 0 1 0 1 0 1 46 30 44 31

6.2 0 1 0 1 0 1 45 31 24 44

5.8 0 1 0 1 0 1 44 32 37 36

6.3 0 1 0 1 0 1 43 33 47 28

5.7 0 1 0 1 0 1 42 34 31 39

7.18 0 1 0 1 0 1 41 35 30 40

7.24 0 1 0 1 0 1 40 36 46 29

6.8 0 1 0 1 0 1 39 37 57 24

7.5 0 1 0 1 0 1 37 38 40 32

7.19 0 1 0 1 0 1 34 39 27 42

7.21 0 1 0 1 0 1 32 40 33 38

6.1 0 1 0 1 0 1 31 41 24 44

6.6 0 1 0 1 0 1 30 42 39 34

5.9 0 1 0 1 0 1 29 43 26 43

5.12 0 1 0 1 0 1 28 44 22 47

7.30 0 1 0 1 0 1 26 45 40 32

4.4 0 1 0 1 0 1 24 46 36 37

2.13 0 1 0 1 0 1 23 47 23 46

2.2 0 1 0 1 0 1 21 48 15 51

2.1 0 1 0 1 0 1 18 49 12 53

2.6 0 1 0 1 0 1 17 50 21 48

3.1 0 1 0 1 0 1 16 51 19 49

2.9 0 1 0 1 0 1 14 52 16 50

5.4 0 1 0 1 0 1 13 53 14 52

2.3 0 1 0 1 0 1 11 54 9 56

5.11 0 1 0 1 0 1 10 55 5 59

3.2 0 1 0 1 0 1 9 56 10 55

4.3 0 1 0 1 0 1 8 57 8 57

3.3 0 1 0 1 0 1 7 58 7 58

2.7 0 1 0 1 0 1 5 59 11 51


Table 5

Patch Ranking according to abiotic criteria: patch area, position in ecological unit (minNND) and a factor due to the surrounding landuse

Site Area (ha) Area rank minNND (m) minNND rank Surrounding landuse score Landuse rank Total rank score Final abiotic rank

6.10 212.2 59 0 23 55 56 138 1

6.9 40.9 52 0 23 114 44 119 2

2.2 33.0 49 0 23 107 45 117 3

1.6 31.9 48 0 23 120 42 113 4

6.3 11.7 39 0 23 84 51 113 4

6.2 7.0 32 0 23 43 58 113 4

1.3 91.7 57 1422.2 8 101 46 111 7

5.2 22.9 44 0 23 128 39 106 8

5.3 44.1 54 0 23 157 28 105 9

1.4 45.4 55 2650.5 5 117 43 103 10

7.6 5.8 26 0 23 67 54 103 10

7.5 31.3 47 0 23 148 31 101 12

2.10 12.4 40 1060.7 11 89 50 101 12

3.1 6.0 27 100 21 81 52 100 14

7.10 39.0 50 0 23 170 24 97 15

7.14 28.3 46 0 23 164 27 96 16

2.7 14.2 41 492.4 13 122 41 95 17

2.1 5.7 25 0 23 92 47 95 17

7.29 165.0 58 0 23 208 12 93 19

7.11 42.0 53 0 23 198 16 92 20

2.11 3.7 15 0 23 68 53 91 21

1.8 3.3 13 0 23 64 55 91 21

5.6 40.6 51 0 23 204 14 88 23

6.7 60.1 56 1767.1 6 174 23 85 24

1.1 10.9 38 492.4 13 148 31 82 25

7.4 4.6 21 0 23 134 36 80 26

2.4 4.5 20 4225.2 3 45 57 80 26

5.10 28.0 45 0 23 224 11 79 28

5.5 4.6 22 111.8 20 129 37 79 28

6.1 2.3 10 1110.2 10 42 59 79 28

7.19 7.1 33 0 23 186 21 77 31

4.4 5.6 24 304.1 18 137 35 77 31

6.5 6.3 28 0 23 166 25 76 33

5.7 6.6 30 427.2 17 150 29 76 33

4.3 9.8 37 304.1 18 190 20 75 35

6.4 4.2 18 0 23 141 33 74 36

2.3 8.2 34 0 23 198 16 73 37

6.11 22.9 43 602.1 12 197 18 73 37

2.13 0.3 2 0 23 90 48 73 37

4.1 6.9 31 7920.2 1 126 40 72 40

3.2 9.3 36 100 21 205 13 70 41

7.20 4.8 23 0 23 182 22 68 42

3.3 4.1 17 7800 2 90 48 67 43

5.9 6.5 29 0 23 227 10 62 44

1.2 3.0 12 492.4 13 129 37 62 44

7.12 9.1 35 0 23 264 3 61 46

6.8 4.2 19 0 23 196 19 61 46

2.12 0.4 3 0 23 149 30 56 48

7.30 15.6 42 1297.1 9 252 4 55 49

2.9 1.0 6 0 23 166 25 54 50

6.6 2.7 11 1732.8 7 141 33 51 51

7.18 3.6 14 0 23 245 6 43 52

7.21 1.3 7 0 23 228 9 39 53

5.11 2.2 9 0 23 248 5 37 54

2.6 3.9 16 492.4 13 230 8 37 54

7.24 0.8 5 0 23 244 7 35 56

5.8 0.5 4 0 23 270 2 29 57

5.4 1.6 8 3400 4 204 14 26 58

5.12 0.2 1 0 23 276 1 25 59


poor restoration potential were infrequent (mean perimeter

shared ¼ 1.4%). It is important to note that restoration

potential criteria were selected purely on the ecological and

conservation potential of the land rather than on economic

considerations.

7.3.4. Final patch ranking for abiotic criteria

Sites 6.10, 6.9, and 2.2 were the highest ranked patches;

and sites 5.8, 5.4, and 5.12 were the lowest ranked patches,

for the abiotic criteria (Table 5). Low ranking was largely

attributed to small patch size but also to the poor restoration

potential of the surrounding land use.

7.4. Overall site ranking

Overall patch ranking scores were calculated by sum-

ming the total biotic rank scores with the total abiotic rank

scores. For example the top ten patches for MG4 and MG5

grasslands based on biodiversity criteria are listed in Table 6.

Sites 6.10 and 6.9 are collectively a nationally important

wet grassland area and were ranked first and third as neutral

grassland patches with the greatest biodiversity for both

MG4 and MG5 communities. The sites were large, had high

species richness, diversity and rarity, low minNND, and

were surrounded by land of good restoration potential. The

results of the ranking scheme developed in this investigation

confirm the nature conservation value and status of these

sites, and support the large-scale conservation work

currently being carried out on the sites. Site 1.6 was also

highly ranked (second) reflecting its importance for both

MG4 and MG5 communities.

Consistent with the integral nature of these two habitats,

the overall patch ranking for MG4 and MG5 contained the

same sites although they appeared in a slightly different

order (Table 6). The lowest overall ranking was given to site

5.4, as the patch had no recorded species present, was small,

was isolated and had poor restoration potential.

7.5. Comparison of final output with site designation

Of the top 10 ranked sites of high biodiversity, six are

Sites of Special Scientific Interest (SSSI’s) (sites 6.10,

5.6, 7.29, 5.2, 6.7, and 1.3), three are locally designated

‘Alert Map’ sites (sites 1.6, 6.9, and 2.11), and one (site

1.2) was unofficially designated as a site of nature

conservation interest by a statutory body.

Of particular note were the high ranked sites 7.29,

7.10, 7.11 and 7.6 (ranked 6, 11, 12 and 20,

respectively), which are designated candidate Special

Areas of Conservation (cSACs) under the Habitats

Directive for their high biodiversity value. Site 1.4, a

national nature reserve (NNR), was only ranked 23rd, a

low rank considering its national status. This low rank

can be attributed to a lack of species recorded within the

site boundaries, scoring poorly for species richness,

diversity and rarity.

The highest ranked undesignated patch (i.e. not officially

designated as a site of nature conservation interest) was site

1.2, ranked seventh for MG4 and 8th for MG5 vegetation

community characteristics. The top rank was due to the high

number of species recorded on the site.

7.6. Targeting sites for habitat expansion

The patches targeted for expansion (Table 7) were

selected on the basis of their biodiversity. Sites 6.10 (ranked

first) and 6.9 (ranked third) were excluded from patch

expansion targeting because they already have individual

management plans with separate targets for habitat expan-

sion and enhancement. Fig. 3 shows the areas of land

targeted for habitat enhancement bordering the highest

ranked neutral grassland patches. Site 1.6 was found to have

the largest area of surrounding land (110.4 ha) suitable for

expansion (Table 7).

Land suitable for expansion but not currently under

any ESA agreement was identified (Fig. 4). It is these

areas that are the sites to be targeted for inclusion under

ESA agreements. If they are managed accordingly they

will contribute to the neutral grassland network whilst

Table 6

The 10 highest ranked patches for MG4 and MG5 grasslands based on the

biodiversity criteria

Rank MG4 Sites MG5 Sites

1 6.10 6.10

2 1.6 1.6

3 6.9 6.9

4 5.6 7.29

5 5.2 5.6

6 7.29 2.11

7 1.2 5.2

8 6.7 1.2

9 2.11 6.7

10 1.3 1.3

Table 7

Available land adjacent to neutral grassland patches that could be targeted

for habitat restoration to achieve the UK HAP target of 500 ha

Site Expandable area (ha) Cumulative total area (ha)

1.6 110.4 110.4

5.6 15.6 126

5.2 135.6 261.6

7.29 90.4 352

1.2 90.5 442.5

6.7 34.7 477.2

2.11 27.4 504.6


meeting the UK national HAP habitat creation target of

500 ha of lowland meadow (UK Biodiversity Steering

Group, 1999). Sites 1.6, 5.6, 5.2, 7.29, 1.2, 6.7 are

patches identified for inclusion in the ESA scheme that

would fulfil this target.

7.7. Landscape fragmentation

A comparison was made between the minNND of neutral

grassland patches in the landscape with and without the sites

targeted for enhancement. Table 8 shows the difference

between the median minNND before and after patch

enhancement. There was a significant decrease in the

median minNND between patches with and without

enhancement (Mann–Whitney U-test, P ¼ 0.003). A com-

parison was also made between the mean patch area before

and after patch enhancement (Table 8) and a significant

difference was found (two sample t-test, P ¼ 0.021).

Following enhancement the mean patch area increased,

although the data was found to be skewed and was therefore

normalized. As a result of patch enhancement, the distance

between patches decreased and the patch area increased,

decreasing the overall fragmentation of the landscape as is

expected with an increase in habitat area.

8. Discussion

8.1. Overall ranking scheme

The effectiveness of employing a ranking scheme that

incorporated both biotic and abiotic factors in identifying

Fig. 3. Neutral grassland sites showing areas targeted for restoration within the UTTESA.


the most biologically diverse sites in the UTTESA was

clearly demonstrated. Sites 6.10 and 6.9, ranked first and

third, respectively, were well positioned in the ecological

unit being adjacent to each other and surrounded by land of

good and moderate restoration potential. As a result, sites

6.10 and 6.9 and the surrounding land should be targeted for

enhancement and habitat creation under existing ESA

management prescriptions. Expansion of these sites would

not only increase patch area and species diversity (in

accordance with the species-area relationship), but also

reduce inter-patch distances between these sites and the

neighbouring patches.

Fig. 4. Neutral grassland patches with land targeted for restoration and land currently under agreement within the UTTESA.

Table 8

Comparison between minNN (m), and Area (ha), before and after patch enhancement

Median Mean LogMean Stdev LogStdev Min Max

MinNN before 30.0 426.0 1.9 1306.0 0.7 0.0 7920.0

MinNN after 30.2 249.2 1.8 1068.5 0.6 0.0 7902.5

Area before 4.2 13.8 0.5 30.6 1.0 0.0 212.2

Area after 5.6 16.4 0.8 28.7 0.7 0.2 212.2


Consistent with the theory of island biogeography, where

species diversity increases with patch size (McAurthur and

Wilson, 1967; Schulze and Mooney, 1993; Hubbell, 2001),

the largest patches had relatively high ranking for biotic

factors. However, the highest ranked patch for biotic factors

only, site 1.2, was ranked 47th for patch area and was

therefore an exception to the species-area relationship. As

discussed by Spellerberg (1992), the species-area relation-

ship does not always apply and one must be aware of

exceptions and take note of intrinsic values (other than area)

resulting in high patch diversity. Although grassland

patches such as site 1.2 are viewed as fragmented habitat

islands, they are not surrounded by hostile habitat as

suggested by the island biogeography theory. Instead the

patches are surrounded by other grassland types (e.g. MG6

or MG7) that are also capable of supporting a diverse range

of species.

Of note was site 1.6, ranked second, which only has a

regional site designation. Further investigation may result in

a recommendation to increase the status of this patch, due to

its high biodiversity value, to a nationally important status.

Site 1.6 consistently scored highly for a number of

assessment criteria, especially for site diversity where it

was ranked highest. It was also highly ranked for patch area,

species richness and species rarity and it is adjacent to site

1.8. Sites such as 7.29, 5.6, 6.7, and 5.2, were consistently

ranked highly, as were more than 50% of the SSSI’s. All

cSAC’s ranked within the top 20 sites. Middle to low

ranking patches, however, consisted of a combination of

regionally designated sites, SSSI’s and undesignated sites.

The neutral grassland SSSI’s may have become degraded,

declined in biodiversity quality (English Nature, 2001), and

as a result were ranked low. Regional sites or undesignated

sites of high biodiversity status, as determined by the current

ranking system, have not yet been recognised for their

value. A gap in the data set, particularly of species

distribution from sites of higher designated status, indicated

the necessity for a greater number of surveys, particularly

for BAP species on these patches.

8.2. Patch targeting for habitat enhancement

Generally UK nature conservation policy has focused

on the management of sites of high conservation value

without due consideration to the state of surrounding land

and its potential for habitat expansion (Sheail et al.,

1997). Various targeting mechanisms have been used for

individual site-based evaluations including multi-criteria

methods using biotic and abiotic factors (Ratcliffe, 1977;

Margules, 1984; Rossi and Kuitunen, 1996; Clevenger

et al., 1997). Other approaches have employed iterative

habitat evaluation schemes, using heuristic algorithms or

linear programming techniques, (Kirkpatrick, 1983;

Pressey et al., 1993; Freitag et al., 1997; Csuti et al.,

1997; Sarakinos et al., 2001; Briers, 2002). These aim at

representing the study region’s entire biodiversity in as

few sites as possible to maximise conservation efforts.

Generally there have been few attempts at targeting sites

for habitat creation and even less that have considered the

implications on the wider countryside in fulfilling habitat

expansion objectives.

Land adjacent to neutral grassland patches targeted for

habitat enhancement was selected according to a number

of principles to maximise the benefits attained from the

resources available and from the biodiversity attributes

within the patch. Targeting the surrounding land also

creates buffer zones around the key patches, thus

protecting them from further edge effects and subsequent

habitat degradation, as well as effectively enhancing the

site biodiversity by providing a larger area for species

colonisation.

Land selected for restoration around the periphery of a

neutral grassland patch aimed to minimise the edge effect.

This was achieved by creating a patch that was as large and

circular as possible. Regularly shaped patches have less

edge and larger core areas, therefore land restored around

the patch periphery aimed to restore the habitat circularity

(Laurence and Yensen, 1991). Patch expansion also aimed

to increase the levels of connectivity between patches.

Neutral grasslands are not necessarily isolated habitat

islands surrounded by a landscape of hostile habitats.

They are often linked by a network of floodplain

habitats, such as streams and reed banks, which theoretically

provide wildlife corridors between patches (Beier and Noss,

1998). There are sufficient areas of floodplain grassland

habitats in the UTTESA to potentially link a number of

adjacent patches together, e.g. sites 1.2, 1.1, 5.2, 5.3, 5.6,

and 5.5. Connecting patches reduces their isolation and

minNND as well as decreasing the landscape fragmentation

(Andren, 1994).

8.3. Landscape fragmentation

Restoration and enhancement of neutral grasslands not

only secures a greater area of habitat for associated habitat

specialists but it also protects the remaining resource from

factors such as degradation, fragmentation and edge effects.

Targeting sites for restoration in the UTTESA (Figs. 3 and

4) demonstrated the effect of patch enhancement on the

overall landscape fragmentation. There was a significant

reduction in the minNND between neutral grassland patches

in the UTTESA (Table 8), which indicated a reduction in

habitat isolation and fragmentation of the landscape.

Reducing habitat fragmentation would reverse the general

pattern of biological impoverishment and reduce the impact

of edge effects as described by Bellamy et al. (1996) and

Keyser et al. (1998).

8.4. Conclusion

Fragmentation-related studies have concluded that the

preservation of small remnant areas will not conserve


species diversity (Harrison and Bruna, 1999). However,

small patches are important in promoting the conservation

of larger patches as they can provide valuable habitat,

functioning as stepping stones between larger patches,

facilitating inter patch movement (Semlitsch and Bodie,

1998), and acting as reservoirs for colonisation.

The habitat ranking scheme developed here is a

technique to aid decision makers in directing financial

resources into the conservation of neutral grasslands. The

ranking system enables resource targeting on a strategic

scale, allowing objective decisions to be made according

to the best available scientific information. Fig. 4

identifies the land units to be targeted for restoration,

which are not currently under ESA agreement, on the

basis of the ranking system. This research demonstrates

the benefits of employing a patch ranking system based on

a combination of biotic and abiotic factors for the

targeting of sites for conservation. It can be used to co-

ordinate ESA agreements in order to meet conservation

objectives, maximise environmental benefits and stream-

line resources efficiently. It is, however, recognised that

other environmental variables such as soil type, slope,

aspect could be incorporated into the patch ranking

scheme in order to further refine the process. These are

aspects likely to be in need of address in future research.

Importantly the wildlife conservation and enhancement

objectives of ESA schemes have been readily incorpor-

ated into targets for species and habitats identified as

priorities for biodiversity conservation (Ovenden et al.,

1998). Linking agri-environment schemes closely with

UK BAP processes, as demonstrated by this study, is

crucial in creating a more sustainable agricultural system

and achieving the respective species and HAP targets

(Ovenden et al., 1998). More research is required to

understand the ecological relationships between farming

systems and the requirements of the species they support,

for example interactions between predation rates and

management related changes in the habitat (English

Nature, 2000; Vickery et al., 2001). Farming systems

can then be developed through ESA schemes to maintain

and benefit the ecological characteristics of wildlife

assemblages (McCracken and Bignal, 1998).

The patch ranking scheme for neutral grassland sites in

the UTTESA provided a list of sites, identified via the

GIS in terms of their biodiversity value, for habitat

creation and enhancement to meet the specific objectives

of the UK Lowland Meadows HAP. The process of

habitat restoration inevitably requires high inputs of time

and financial resources, particularly where new habitats

are created. High expenditure on one-off operations is

often required to establish the conditions and vegetation

necessary for the initiation of natural regeneration

processes (Manchester et al., 1999). To maximise

effectiveness, resource-targeting procedures should there-

fore be based on the best information available, enabling

objective rather than subjective site selection. Objective

assessment using quantitative criteria allows comparison

between sites and enables selection of the most ecologi-

cally valuable sites. As the most biologically diverse sites

were targeted for habitat restoration and inclusion under

ESA management agreements, the targeting approach was

shown to be beneficial to conservationists and DEFRA

advisors.

The national Lowland Meadows HAP creation target

of 500 hectares was achieved within the UTTESA

without site suitability becoming a limiting factor, despite

this value referring to the UK as a whole. The actual

figure for habitat creation of lowland meadows (for both

MG4 and MG5) with in Oxfordshire is only 8 ha

(Jefferson, pers. comm.). The rationale behind the

selection of this figure would appear to be proportional

to the existing extent of the particular HAP grassland type

in the county or Natural Area. It seems that the county

figure of 8 ha is particularly low, especially as the

national target of 500 ha was achieved easily, as

demonstrated in this study. We therefore suggest that

both the national and local values, presented in HAP’s,

are in need of revision to adequately reflect the real

potential capacity for habitat restoration and creation in

agricultural landscapes.

Acknowledgements

The authors would like to thank Alistair Helliwell

(DEFRA), Cengiz Philcox (BBOWT), Dan Chamberlain

(BTO), Oxford Ornithological Society, Banbury Ornitholo-

gical Society, Craig Blackwell (Oxfordshire County Ecol-

ogist), and last but not least John Campbell (Oxon

Biological Records Centre) for all their help, support, and

the sharing of data.

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A multi-criteria targeting approach to neutral grassland conservation

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