Research and Development s6

DEPARTMENT for ENVIRONMENT, FOOD and RURAL AFFAIRS CSG 15 Research and Development Final Project Report (Not to be used for LINK projects)

Two hard copies of this form should be returned to: Research Policy and International Division, Final Reports Unit DEFRA, Area 301 Cromwell House, Dean Stanley Street, London, SW1P 3JH. An electronic version should be e-mailed to [email protected]

Project title AGRI-ENVIRONMENT SCHEMES AND BUTTERFLIES: RE-ASSESSING THE IMPACTS AND IMPROVING DELIVERY OF BAP TARGETS

DEFRA project code BD1446

Contractor organisation Butterfly Conservation, Manor Yard, East Lulworth, Wareham. Dorset BH20 and location 5QP

Total DEFRA project costs £ 169,967

Project start date 01/08/03 Project end date 31/07/05

Executive summary (maximum 2 sides A4)

1. AIMS & OBJECTIVES . This study builds on the work of BD1427, which collated data from a large number (535 sites) of butterfly monitoring transects in England in order to identify the impact of agri-environment schemes on butterfly populations. 2. The objectives of the current study were to: (1) Improve the statistical power to detect population trends, by adding three more years of data (from 2001-3) and extra sites, and improving statistical techniques; (2) Re-assess the impacts of agri-environment schemes on butterfly populations (including BAP priorities and on SSSIs); (3) Assess the potential of using volunteers to monitor site habitat condition and management; (4) Acquire detailed habitat and management data to assess scheme prescriptions and to develop generic prescriptions for target species; (5) Provide additional feedback to Defra staff on the effectiveness of scheme prescriptions and other key results; (6) Promote technology transfer through publications, talks and other media. 3. METHODS . Trends were calculated using the time effects model of TRIM (Trends and Indices for Monitoring Data) Timed count data was included for some very rare species, collected separately by BC researchers. The performance of species assemblages was assessed from composite indices using methods developed by the RSPB/BTO for the headline indicator for birds (Gregory et al, 2002). 4. The precision of trend estimation was improved by the use of Generalised Additive Models (GAMs) and Generalised Estimating Equations (GEEs), developed with the help of researchers at St. Andrew University. 5. RESULTS . Following development work, the dataset grew to 820 sites (an increase of >50% since BD1427), of which 371 (45%) were entered into schemes. The rapid data collation network also grew considerably and now involves 40 volunteer co-ordinators and over 1500 recorders. This development work also allowed trends to be calculated for 40 species (6 more than in BD 1247, mostly additional BAP Priority Species). 6. The overall results show that there has been a significant decline in mean species abundance of 30% over the 10 last years, with the majority of species having declined significantly. The declines have been across the board,

CSG 15 (9/01) 1 Project DEFRA BD1446 title AGRI-ENVIRONMENT SCHEMES AND BUTTERFLIES: RE- project code ASSESSING THE IMPACTS AND IMPROVING DELIVERY OF BAP TARGETS including at scheme and non scheme sites, SSSIs and non SSSIs, and in the wider countryside highlighting the acute problems butterflies face in the English landscape. 7. Butterflies have also declined significantly on scheme sites, at a rate of - 22.5% over the last 10 years, compared to a non-significant decline of - 15% detected for 1994-2000 through BD1427. The result suggested a possible acceleration in species decline over the last three years, though the difference was not statistically significant. Among conservation priorities, four of the eight (50%) BAP Priority butterflies had declined significantly on scheme sites over the last ten years, as well as 6 of the 10 candidate BAP species 8. The decline was lower at scheme sites compared to non-scheme sites (mean decline per annum -2.95%, p<0.05 vs -3.77%, p<0.05), though the difference was not statistically significant (t=0.48, d.f. 76, p=0.63). For habitat specialists (n=19), there was a significant decline in mean abundance at scheme and non -scheme sites (-4.66% p.a. vs -6.75%), though again the difference was not significant (t=0.97, d.f. 38, p=0.34). 9. Trends for all sites (scheme and non-scheme) also showed a significant decline in mean abundance of BAP Priority Species (n=8) from 1994-2003, though the mean rate of decline per BAP Priority species was significantly reduced by more than half at scheme sites (mean decline p.a. -3.94% ±3.85%CL, compared to -11.89% ±3.85%CL at non scheme sites, t=2.40, d.f. 7, p=0.04). Of the eight BAP Priority species six (75%) had improved trends at scheme sites compared to non scheme sites, including significant improvements for Adonis Blue, High Brown Fritillary, Heath Fritillary and Silver-studded Blue. 10. The species benefiting most from schemes are mainly those associated short and medium turf conditions, such as Silver-spotted Skipper and Adonis Blue. Species least benefiting from schemes included those associated with ranker grass, variable turf and scrub edge/mosaics, including Small Blue and Duke of Burgundy (mean decrease -6.97% p.a. on scheme sites, p<0.05 vs -1.06%, n.s., t=-3.91, d.f. 5 p=0.01). 11. Considering just lowland calcareous grassland, the mean species trend was very similar at scheme and non-scheme sites (-2.16% p.a. vs -2.02%, n.s.) (t=-0.07, d.f. 40, p=0.94). The mean annual trend of 12 habitat specialists was roughly stable at scheme sites (-1.55%, n.s.), but in significant decline at non-scheme sites (-3.3%, p<0.05). 12. Short/medium turf habitat specialists were stable at both scheme and non scheme sites (-0.31% pa, n.s. vs -3.34%, n.s; t=1.5, d.f. 16, p=0.15), but the trends of six specialists requiring habitat mosaics was significantly worse at scheme sites compared to non scheme sites (mean decline -7.1% pa, n=6, p<0.05 vs –1.45%, n.s.; t=-3.11, d.f. 10, p=0.01). These data provide further evidence that the drive to restore generic (‘favourable’) habitat conditions as defined by homogenous NVC communities is impacting on non BAP Priority species requiring habitat heterogeneity. 13. Trends were examined on 60 ‘ordinary’ farmland transects for six farmland indicator species that breed in hedgerows, grasslands and field margins. Although sample sizes were small, these species had a worse trend on farmland between 1990-2003 compared to other sites (-53% vs -15%, t=-2.49, d.f. 4, p<0.05). These results are of great concern and highlight the acute problems 'common species' are facing in the general countryside. 14. Of concern on the 60 farmland transects, six of eight farmland species had worse mean trends at scheme sites, though the difference was not statistically significant (-36% vs -20.5% over 14 years, t=-0.83, d.f. 6, p=0.43). There is also a need for a more wide-ranging analysis of scheme arable and hedgerow options on butterflies. 15. In a separate study of four CSS field margin treatments on three farms (Dawson, 2004), butterfly diversity was highest in the wildflower margins, and lowest in the 6m margin, though the overall results were not statistically

significant (butterfly abundance F(3)(45)=1.06, p= 0.38, species richness (F(3)(45)=1.13, p= 0.35). However, the unsown margins supported more species and a greater abundance of butterflies than the 2m and 6m margin treatments, and were the most important habitat for Wall Brown, a candidate BAP Priority Species. The research provided further research evidence to highlight the positive impact of wildflower margins on butterfly diversity in arable farmland areas and the relatively low value/potential negative impact of certain types of 6m margin. 16. Of the eight BAP Priority species on SSSIs, six had declined significantly over the last decade, whilst two increased significantly (Adonis Blue and Silver-spotted Skipper). There was no overall difference in mean trend on SSSIs vs non-SSSIs, though four Priority Species had improved trends at SSSIs and sample sizes were low for four species. The results for habitat specialists on SSSIs were also mixed: six out of thirteen species with adequate sample sizes had improved trends at SSSIs compared to non SSSIs, but there was no difference in mean abundance (t=-0.19, d.f. 24, p=0.84). In summary, no strong evidence was available to detect an overall difference in trends of BAP Priority and habitat specialists between SSSIs and non SSSIs. 17. Within SSSIs, the mean decline of BAP Priority Species was highly significantly lower at scheme sites compared to non-scheme sites (-31% over 10 years, n.s. vs -68%, p<0.05) (t=3.88, d.f. 7, p<0.001). Seven of 8 BAP Priority Species had significantly improved trends on SSSIs in schemes compared to non-scheme SSSIs (Yates corrected χ2=6.25, d.f. 1, p=0.01). However, no differences were detected between scheme and non-scheme sites for all-species or habitat specialists. Species requiring mosaic habitats fared worse on SSSIs (-7% at scheme sites, compared to -1.%

CSG 15 (9/01) 2 Project DEFRA BD1446 title AGRI-ENVIRONMENT SCHEMES AND BUTTERFLIES: RE- project code ASSESSING THE IMPACTS AND IMPROVING DELIVERY OF BAP TARGETS p.a., at non scheme sites, n=6 species, t=-3.16, d.f. 5 p=0.01). These data indicate that schemes are a key mechanism helping to halt the decline of BAP Priority species on SSSIs, but not other species. Mosaic habitat specialists fared worse on SSSIs while short turf species benefited. 18. Following an initial analysis of 1700 separate trends from 450 sites, details of habitat management were obtained from over 100 sites, to identify what management regimes had benefited 11 key species or habitat specialist assemblages. Management success was to a large degree determined by outcome-focussed (adaptive, targeted, species-specific) judgements made by well informed and experienced land managers who (1) had a clear idea of the target habitat conditions they were seeking to maintain/restore; (2) carefully targeted management in time and space based on local knowledge; (3) modified (‘fine-tuned’) management as required when habitat conditions necessitated a change (e.g. to prevent over and undergrazing); (4) had sufficient control and resources to modify management. 19. Common reasons why butterflies declined at sites were related to the lack of sufficient fine-tuning of prescriptions, and included: (1) lack of knowledge of species occurrence or understanding of the habitat requirements of the species being managed for; (2) lack of control of rabbit grazing; (3) inappropriate (in time and space) bracken or scrub cutting regimes; (4) overgrazing in summer during drought years; (5) insufficient grazing in years of high grass growth 20. Two pilot studies were conducted to test how well volunteers can conduct basic habitat condition monitoring. In 2003, 32 volunteers took 20,000 turf height measurements at 37 sites, and in 2004, 37 volunteers conducted 100 habitat surveys at 47 sites. Volunteers generally preferred the drop-disc method of measuring turf height compared to sward stick, and valuable baseline data was collated. Both surveys confirmed that there is great potential to use volunteers in the future monitoring of habitat condition, and considerably advanced methodology. 21. CONCLUSIONS.  Because butterflies are widely accepted as good indicators of ecosystem health, the overall decline of butterflies (30% in 10 years) is an alarming result with important implications for other insects and biodiversity.  Agri-environment schemes are playing a positive role in helping to significantly slow and in some cases reverse the declines of BAP Priority species, especially short/medium turf species.  However, the positive effect of schemes was not evident for all species combined or all habitat specialists. This suggests that general conservation measures aimed at conserving birds (on ordinary farmland) and improving SSSIs and other semi-natural habitats have not been sufficient to halt butterfly declines. Moreover, for some species types they may have exacerbated declines, notably habitat mosaic species. This is of wider concern, as scrub and habitat mosaics are critically important for threatened insects (e.g. 352 RDB/BAP species).  Examples of successful management were found for all species, proving it is technically possible to manage effectively for even the most threatened and specialised butterfly species.  The new agri-environment scheme in England, Environmental Stewardship (ES) has the potential to be a big step forward as it addresses many of the concerns highlighted in this research  There is a pressing need for the great wealth of information generated on habitat management for specialist butterflies collected under BD1446 to effectively reach the land managers and advisers. A series of seminars are recommended for RDS Project Officers to highlight the opportunities and issues related to conserving butterflies, especially under Higher Level ES.  The results clearly demonstrate why it is now more important than ever to have butterflies as a Headline Governmental biodiversity indicator, to complement the existing suite (SSSI condition, farmland birds) and to continue to broadly assess the effectiveness of agri-environment schemes, SSSIs and other policy and land management in conserving biodiversity.

CSG 15 (9/01) 3 Project DEFRA BD1446 title AGRI-ENVIRONMENT SCHEMES AND BUTTERFLIES: RE- project code ASSESSING THE IMPACTS AND IMPROVING DELIVERY OF BAP TARGETS

Scientific report (maximum 20 sides A4) 1. INTRODUCTION

The scope of this project is large and covers four main areas, related to agri-environment schemes, SSSIs and butterfly populations in England: (1) the impacts of agri-environment schemes at national, regional and local scales on butterflies and interrelationships with SSSIs; (2) site habitat management for butterflies – what works?; (3) monitoring the condition of butterfly features on sites; and (4) technology transfer of the results. The scientific, biodiversity conservation and policy context of this work is discussed below.

There have been large-scale declines in farmland biodiversity due to agricultural intensification since the Second World War (Robinson & Sutherland, 2002). To counter these biodiversity losses and associated changes in landscape quality, the UK Government is one of 26 European Countries to have developed an agri-environment programme. Two main schemes, currently administered by Defra have operated in England, Environmentally Sensitive Areas (ESAs) and the Countryside Stewardship Scheme (CSS). In both schemes farmers enter into 10-year agreements to manage their land to provide environmental benefits, including the maintenance and restoration of biodiversity. During the 1990s Defra and other environmental bodies have funded a number of detailed environmental research and monitoring programmes for these schemes, focussing on botanical communities and birds. Since 1998, two Defra-funded research projects (BD1427 and BD1446) have added to this programme by assessing population impacts of CSS and ESA management on a high profile and flagship invertebrate group: the butterflies.

The other main mechanism operating to conserve biodiversity in England is the protected area network, of which the national sites are Sites of Special Scientific Interest (SSSIs). Biodiversity losses have been substantial on SSSIs, with agricultural management highlighted as the main land use causing unfavourable condition of SSSIs (Defra, 2003). A baseline assessment completed in 2003, showed that approximately 50% of sites were in unfavourable condition in biodiversity terms. To address this problem, the English Government has adopted a Public Service Agreement (PSA) target to have 95% of SSSIs in a favourable condition by 2010. SSSI condition is also a Headline Indicator of sustainable development under the Government’s Biodiversity strategy for England (Defra, 2002). Agri-environment schemes are a key mechanism through which measures to restore SSSIs to favourable condition can be instigated. SSSI condition monitoring is chiefly assessed on the integrity of plant communities with reference to the National Vegetation Classification. Monitoring the status of butterflies on SSSIs is potentially a vital addition to current monitoring, by (1) providing an independent measure of the changing biodiversity condition of SSSIs, and (2) determining the effects of agri-environment scheme management on the condition of SSSIs.

Butterflies are widely accepted as ecological indicators of ecosystem health (Thomas, 2005; Thomas et al., 2004; Swaay et al., in press) and meet a number of the criteria for selecting indicator species. In particular, their high breeding rates and short life cycles allow butterflies to respond rapidly to environmental changes. Butterflies are relatively easy to identify at the species level and a standard validated procedure, the butterfly transect, has been developed for monitoring them, which has been widely adopted (by more than 1500 recorders in 2005). Moreover, many butterflies breed in grassland habitats that have been a major target of agri-environment schemes and, because they are sensitive to vegetation structure, they are highly responsive to grazing regimes. Their populations are thus likely to react more rapidly than many other groups currently being monitored. Recent analyses of distribution data have also shown that butterflies are declining more rapidly than either birds or plants in Britain (Thomas et al., 2004), emphasising their potential role as indicators and the value of this research.

Research project BD1427 was highly successful in developing a system (including software, co-ordination network, analytical procedure, feedback mechanisms) for assessing the overall effect of agri-environment schemes on butterfly populations as well as changes on individual sites. A very large dataset on trends of butterflies on over 550 sites, including 200 entered into schemes was collated, and a rapid data collation network involving 33 volunteer co-ordinators and over 1000 recorders was established. The research carried out under BD1427 indicated that schemes were improving conditions for the majority of BAP and other habitat specialist butterflies associated with target habitat conditions (including favourable SSSI condition) though there were local concerns for a small number of habitat specialists associated with scrub edge/mosaic conditions. However, the research was carried out over a short time period, and many of the results were not quite statistically significant, in-part because of the time delay required for an overall effect. A further ca.150 sites were identified under BD1427 that had the potential to be collated, subject to further resources being

CSG 15 (9/01) 4 Project DEFRA BD1446 title AGRI-ENVIRONMENT SCHEMES AND BUTTERFLIES: RE- project code ASSESSING THE IMPACTS AND IMPROVING DELIVERY OF BAP TARGETS made available, whilst three additional years (2001-2003) had been recorded since the analysis. A substantial body of data collated in BD1427 was not used, because the data was too sparse to generate annual indices under the current analysis procedure of site-based index calculation. Recent statistical techniques, including the application of Generalised Additive Models (GAMs) and Generalised Estimating Equations (GEEs) (Paradis & Claude, 2002) give the potential to model data across sites and calculate more indices from existing data, which in turn will increase the precision (lower standard error) of trend estimates.

 The main aim of the current research was therefore to build on the network developed and with extra sites, extra years of data and improved statistical techniques, to more fully determine the impacts of agri- environment schemes and SSSIs on butterflies and to identify the main habitat management factors causing change.

A key finding of conservation concern from BD1427 was that there was an overall decline in the abundance of habitat specialist butterflies on SSSIs and other semi-natural habitats, with four (of thirteen) habitat specialists including one BAP Priority species, declining statistically significantly on scheme sites over the 1990s. Halting the decline of butterfly populations at individual sites requires a thorough understanding of the specific ecological requirements of species and implementation of appropriate management prescriptions. The detailed ecology of the majority of habitat specialists is now well known through autecological research and general management recommendations have been documented for some habitats (BUTT, 1986). However, there have been few quantitative studies identifying the detailed habitat management prescriptions (e.g. timing of mowing, type of stock animal, timing and intensity of grazing etc) that have maintained strong populations of habitat specialist species at individual sites. BD1427 demonstrated the potential of linking butterfly population changes with habitat and management data to identify the management practices causing wide-scale butterfly population changes across whole landscapes. Under the current project this approach will be developed further by examining the dataset in far more detail and gathering site information (habitat, management, conservation status and ownership) on a range of sites where butterflies have done relatively well, or poorly.

 An important secondary aim of this research is therefore to identify beneficial management prescriptions for BAP Priority and other habitat specialist butterflies on land subject to agri-environment schemes.

Additionally, assessment will be made of the extent to which generic management prescriptions for individual butterfly species and species assemblages can be advocated within agri-environment schemes. The research should make a substantial contribution to the development of the science base underpinning conservation management for butterflies, and will also provide insight into other invertebrate groups.

Over the course of projects BD1427 and BD1446, agri-environment schemes in England have been subject to review, linked to Government plans to address the future sustainable development of the farming industry. In 2005, CSS and ESAs were replaced by a new scheme, Higher Level Environmental Stewardship (HLES), though existing CSS/ESA agreements will continue to run for a full ten years. One of the main differences from CSS/ESAs is that in HLES there is greater emphasis is placed on the results of farm management (i.e. have the features of conservation value been maintained/restored), with less emphasis on land managers having to adhere to rigid management prescriptions (i.e. a scheme focussed on ‘outcomes’ rather than the process of management). Under HLES, butterflies are prominent ‘features’, for which farmers and other landowners can receive payments for positive management works (Defra, 2005). Of the 21 species comprising the ‘Uncommon Invertebrates’ feature SI01 in HLES, 13 (60%) are habitat specialist butterflies, underlying the importance of managing sites for butterflies in the new scheme. As part of HLES, performance indicators (‘indicators of success’) are set to monitor the outcomes of scheme management at the agreement level. Very basic ‘Indicators of Success’ have been developed as part of HLES, though for important butterfly sites, more detailed habitat condition assessment is required to determine whether butterfly features have achieved favourable condition. Currently, there are no standardised methods of monitoring the condition of butterfly habitats, and very few recorders monitor anything other than butterfly abundance at their transect sites.

 A tertiary aim of the project was to develop and test rapid, simple and cost-effective approaches to monitoring habitat condition for individual BAP species and species assemblages/habitats, and to assess the potential for the work to be carried out by volunteers.

Generating reliable information on the condition of butterfly habitats is also potentially of high value in the management of butterfly populations as it can: (1) provide a baseline of target habitat conditions; (2) enable identification of early

CSG 15 (9/01) 5 Project DEFRA BD1446 title AGRI-ENVIRONMENT SCHEMES AND BUTTERFLIES: RE- project code ASSESSING THE IMPACTS AND IMPROVING DELIVERY OF BAP TARGETS signs of habitat deterioration; (3) identify the particular nature of a habitat problem; (4) identify sites with restoration potential; and (5) enable monitoring of species with low detectability.

In research contract BD1427 a gap was identified between information gathered on butterfly distribution and habitat requirements, and conservation practitioners who can use the information to deliver biodiversity gain. Also, a wealth of information on butterfly trends on individual scheme sites was obtained, which could be used to give feedback to Defra and Project Officers.

 An important aspect of this research proposal will be to make this data and new results obtained available to Defra Project Officers and Ecologists, to enable more effective delivery of butterfly conservation through agri- environment scheme agreements.

OBJECTIVES

1. To improve the statistical power to detect population trends, by maintaining the data collation network, adding three more years of data, adding extra sites and datasets and through a feasibility study to address sampling biases. 2. To re-assess the impacts of agri-environment schemes on butterfly populations, including assessment of the performance of butterflies on scheme sites by BAP priority habitat type and by region, and comparison of the impact of schemes on SSSIs and non SSSIs. 3. To assess the potential of using volunteers to monitor site condition by recording (1) habitat and management changes, and (2) sward and vegetation structure (e.g. comparing drop disc data with photographic categories). 4. To acquire detailed habitat and management data on a range of monitored sites, thereby identifying good (and bad) practice, (1) to enable assessment of differing scheme prescriptions, and (2) to develop generic management prescriptions for habitat specialist and Priority BAP butterflies. 5. To provide additional feedback to Defra (e.g. to policy staff, ecologists, project officers) on the effectiveness of scheme prescriptions and management recommendations in conserving butterflies and on the other key results generated through BD1427 and the current research. 6. To promote technology transfer by publishing results in refereed journals, giving presentations to scientific conferences, and via the Internet.

2. METHODS

2.1 Butterfly abundance data The main body of butterfly abundance data used in the research was derived from butterfly transects. The method involves weekly butterfly counts along set site routes in standardised recording conditions. The weekly counts and interpolated missing week values at each transect site are summed to generate annual indices of abundance that can be analysed over time to detect population trends (Pollard and Hall 1986).

The transect method is labour intensive, and more rapid methods have been developed to generate abundance indices for habitat specialists, especially where: (1) species distribution is dynamic in time and space; (2) recorder density is low; (3) butterfly detectability is low; and (4) where the climate is less hospitable. Timed counts were the main additional form of scientifically validated (Warren et al, 1984) annual abundance data collected, especially for fritillary species in western England. Timed Counts measure the population size and area occupied by a butterfly species based on 1-2 visits and with reference to local transect data, which enables data to be corrected to an index at the peak flight period. Timed count data was collected for the following species: Heath Fritillary, High Brown Fritillary, Marsh Fritillary, Pearl-bordered Fritillary, and Small Pearl-bordered Fritillary. Additionally, a small amount of butterfly egg count (Brown Hairstreak), larval web (Marsh Fritillary) and maximum record (Duke of Burgundy, Chalkhill Blue, Silver-studded Blue) data were used, where coverage by transects was poor/absent. The criteria for use of this data were that it was: (1) recorded to a high standard; (2) regionally validated; and (3) scientifically robust.

Further validation work was completed to confirm that non-transect monitoring data gave similar trends to transect data, and thus that the non-transect monitoring data was a reliable surrogate. Examples of validation include, in the south-west CSG 15 (9/01) 6 Project DEFRA BD1446 title AGRI-ENVIRONMENT SCHEMES AND BUTTERFLIES: RE- project code ASSESSING THE IMPACTS AND IMPROVING DELIVERY OF BAP TARGETS where there was no significant difference in the High Brown Fritillary trend on timed count and transect sites (Wald-Test = 0.18, d.f. 1, p=0.667). Similarly, in the example illustrated below, the decline in the Marsh Fritillary across England was very similar at transect and larval web count sites (Figure 2.1). Moreover, combining both data sets gave more precise trends estimates (see Section 3.2.3).

1.6 Transect Larval Web 1.4 Linear trend (Transect) Linear trend (Larval Web) 1.2 x e

d 1 n i

n 0.8 o i t a

0 1990 1992 1994 1996 1998 2000 2002 Figure 2.1. National Trends for Marsh Fritillary; transect data vs larval web data

2.2 Data collation Data was collated for the period 1990 to 2003. Only sites with current/potential for agricultural use in England were used in the analysis. The target dataset included an estimated 150 additional transect sites identified through BD1427, whilst three years of extra years of data for 2001-2003 was collated from existing sites and new sites established over the period. Data from independent transect sites was collated by Butterfly Conservation, through a network of volunteer co- ordinators and provision of bespoke data entry software (Transect Walker). Butterfly Monitoring Scheme (BMS) transect data was obtained from the Centre for Ecology and Hydrology (CEH). Under the current research project, the data gathering network was further strengthened with more than 40 co-ordinators established, and over 1500 recorders contributing data each year in 2002 and 2003. Transect Walker was again made freely available to enable recorders to supply electronic data. An advanced version of Transect Walker 2.0 was developed over the course of BD1446.

For each new transect/non-transect monitoring site collated under BD1446, the following data were collected: butterfly abundance data, weather/recorder details from each visit, site habitat and management data and a map of the monitoring route. Information on the statutory protected status (in/outside of an SSSI or NNR) of sites, and whether they had been entered into CSS or ESA agri-environment agreements was obtained from the Geographical Information (GI) Unit of Defra RDS South West in Bristol. For each scheme site, the year of entry and holding number of scheme transects was obtained from the Bristol GI Unit. Habitat information, management details, maps of individual agreements were obtained from regional Defra Service Centres and by use of Defra’s GENIE GIS data system. Considerable efforts were made to obtain further detailed habitat and management information through liaison with transect recorders, landowners and site mangers. The nature reserve status of sites was obtained from site managers or butterfly recorders. Nature reserves were defined as those specifically named as a nature reserve either through statutory designation by English Nature (NNRs and Local nature Reserves (LNRs) or by voluntary conservation bodies (the Wildlife Trusts) and in some instances Local Authorities. Non transect monitoring data was collated from volunteer recorders via regional species action groups (e.g. South West Fritillary Action Group, Cumbria Fritillary Action Group), BC regional staff, CCW staff, and specific single species surveys organised by BC.

CSG 15 (9/01) 7 2.3 Data storage Electronic butterfly transect data supplied by co-ordinators was combined into a secure, single MS Access database at the Head Office of Butterfly Conservation. Transect Walker datasets were converted into MS Access via a bespoke program National Co-ordinator. Timed count data was stored in a separate MS Access database 2.4 Abundance indices and trends Overall population trends were analysed by modelling year and site effects using a loglinear model with Poisson errors incorporating adjustments for overdispersion and serial correlation, written in the freeware program TRIM (Trends and Indices for Monitoring Data) (Pannekoek and van Strien 1996). Trends were calculated in TRIM using the time effects model (a stricter model than that generally used in BD1427), allowing for over dispersion and serial correlation. The time effects model estimates parameters for each separate year and therefore generates collated indices for each year with standard error bars. For some species (High Brown, Heath and Pearl-bordered Fritillaries), the national trend was generated by combining transect and timed count data. This is acceptable in TRIM, as all the indices are scaled comparatively (to 1 in the start year), as part of the Poisson regression algorithm. A Wald-Test (Hosmer & Lemeshow, 1989) was used to determine whether there were statistically significant differences between trends over the 1990s according to co-variate categories including SSSI status, agri-environment scheme status and region.

In TRIM, the species trend (Slope ± SE) is expressed as a mean % increase or decrease per year over the monitoring period. For example, for species j, over a seven year period from 1994-2000, where the slope (trend) = 1.05 [SE 0.02]. This represents a significant positive trend, as the lower 95% confidence limits does not drop below 1.0 (slope range 1.01- 1.08). The slope of 1.05, can either be expressed as a mean annual increase of +5% per year, or (using compound increase) equivalent to a +65% increase over 10 years.

A study was completed into feasibility of data weighting to generate more representative national indices and trends. Spatial datasets were not available for Butterfly Conservation to complete this, but in any case professional advice received was that this was (1) not necessary for habitat specialists (existing coverage largely representative), or (2) undesirable for wider countryside species, due to the large scale extrapolation that would be required to generate nationally representative indices. The professional recommendation from various statisticians was the need to develop a new methodology and scheme to more effectively monitor wider countryside species. Investigation was made into the use of the chord distance (Orlóci, 1967), to compare butterfly trends and beta diversity at scheme and non-scheme sites. This was found to be an inappropriate approach, due the large number of missing values within and between years at individual transect sites.

2.5 Impacts of agri-environment schemes and SSSIs on butterflies

2.5. 1. Site, year and species selection To assess butterfly trends at sites entered into agri-environment scheme/non scheme sites and SSSIs, filtering of the butterfly abundance dataset was required. The majority of sites used in the analysis were from semi-natural lowland grassland, heathland and wetland habitats in middle and southern England, though an increasing number of ordinary farmland transects were collated. The subset included post-industrial sites with semi-natural vegetation.

Species trends at scheme and non-scheme sites were calculated for 39 of the 58 regular English butterflies. As in project BD1427 migrants, rarities with low sample sizes, and woodland species were excluded. The species, by type are listed below:  BAP Priority: Adonis Blue, High Brown Fritillary, Heath Fritillary, Marsh Fritillary, Northern Brown Argus, Pearl-bordered Fritillary, Silver-spotted Skipper, Silver-studded Blue  BAP SCC: Brown Hairstreak, Chalkhill Blue, Duke of Burgundy, Lulworth Skipper, Small Blue, Small Pearl-bordered Fritillary  BAP Prop. (species recommended as BAP Priority Species as part of the UK BAP Review and not currently listed in the BAP): Dingy Skipper, Grayling, Grizzled Skipper, Small Heath, Wall Brown (Bourn et al., 2005)  Non-BAP habitat specialists: Dark Green Fritillary, Green Hairstreak,  Common/widespread species: Brimstone, Brown Argus, Comma, Common Blue, Gatekeeper, Green-veined White, Holly Blue, Large Skipper, Large White, Marbled White, Meadow Brown, Orange-tip, Ringlet, Small Tortoiseshell, Small Copper, Small White, Small/Essex Skipper, Speckled Wood. Note that habitat specialists include all the BAP species mentioned above excluding Wall and Small Heath.

TRIM can become unstable when comparing trends by co-variate type (e.g. agri-environment scheme status), if the covariate status of a site changes category through time (for example a site may change from being not in a scheme to being entered in a scheme, during the study period). To avoid this problem, a discrete ten-year time period (three more years than under BD1427) from 1994 to 2003 was selected for the bulk of analyses, and only those sites that remained either in a scheme or outside of a scheme for the whole period were used. For scheme sites, only those that entered between 1991 and 1993 were used. This gave samples of 141 scheme and 303 non-scheme sites. Project MAFF BD1446 title AGRI-ENVIRONMENT SCHEMES AND BUTTERFLIES: RE- project code ASSESSING THE IMPACTS AND IMPROVING DELIVERY OF BAP TARGETS

For a limited number of analyses, a less rigorous definition of scheme sites was used, enabling assessment of trends over a longer period from 1990-2003. For these analyses, sites were classified as in a scheme for the whole duration, regardless of the year of entry. This gave samples of 371 scheme and 311 non-scheme sites. Cross validation work determined that 1994-03 and 1990-03 species trends were broadly similar hence 1994-03 trends were used preferentially where possible.

2.5.2. Composite indices To asses the performance of species assemblages, composite indices were calculated using methods developed by the RSPB/BTO for the UK Government’s headline indicator for birds (Gregory et al, 2001). This approach standardises species trends and creates a simple (geometric) mean index across selected species. For each year separately, the log of each species index value was taken, then averaged across selected species and the exponential of the result calculated. Composite indices were developed for a range of species assemblages including: (1) all ‘farmland’ butterflies; (2) habitat specialists; (3) BAP Priority species; and (4) short, medium rank and variable turf specialists. Composite indices were disaggregated to compare trends by covariate type, especially at scheme and non-scheme sites.

2.5.3 Impacts of CSS on arable farmland butterflies Transect sample size for ordinary farmland was low (Section 3.1) and a separate study was completed in Dorset in 2004 by Kathryn Dawson of the University of East Anglia, to compare butterfly species richness and abundance under four arable field margin treatments established under CSS. The four treatments were: (1) No margin; (2) 2m margin; (3) 6m margin; and (4) Wildflower mix margin (pollen and nectar). Regression analyses were used to identify key environmental and vegetation elements influencing butterfly distribution and abundance in each margin type.

2.6 Statistical research to improve analytical procedures Statistical research was carried out by the Centre for Ecological and Environmental Modelling (CREEM), St Andrews University in partnership with CEH to develop (1) new and improved methods of calculating indices and modelling trends, and (2) appropriate software to run the modelling procedure. Investigation was made into the application of General Additive Models (GAMs), to estimate missing values and indices by modelling data across sites as a smooth non- linear function of time. GAMs rely on the assumption of independence between counts, yet counts on the same site can be correlated. Consequently, the application of Generalised Estimating Equations (GEEs) was also tested, as they have the flexibility of GAMs, but take into account any correlation between successive counts. The set of covariates tested, which were likely to influence the number of butterflies seen, included (1) data from the count day (date, time of day, wind speed, temperature, sunshine), and (2) site attributes (latitude, longitude, altitude, habitat, region). Following testing of the model on selected species, work was carried out to develop a bespoke software function that would calculate site, regional and national indices for user-defined species and time periods.

2.7 Habitat management- what works? Detailed analysis of site trend data for selected species was undertaken to identify beneficial and detrimental management practices and the causes of population changes. Trends were analysed between 1990 and 2003, covering the main period of agri-environment schemes in England and the drive to restore favourable condition on SSSIs through management. The longer time period was used to increase the chance of trend detection, and because the principal aim was to investigate habitat management rather than scheme/non scheme effects. Species selected for analysis (‘key species’) were of three types: (1) BAP Priority species; (2) Habitat specialists regarded as indicators of favourable habitat condition for a wide diversity of invertebrates and plants (Chalkhill Blue and Dark Green Fritillary); and (3) species thought to be being negatively impacted at some sites through scheme and SSSI management (evidence obtained through Defra contract BD1427) including the Duke of Burgundy and Small Blue. Data from Wales was used for this part of the analysis for relevant species (e.g. Marsh Fritillary), where the habitat and management results could be applied to England.

For each key species national indices for each year and a 14-year trend were calculated. For each site supporting one or more key species, two analyses were completed for each species: (1) a linear trend over time by correlating the site index with year, and (2) the level of correlation of the site trend over the monitoring period with the national trend (with a deviation indicating a site-specific habitat/management effect). A limitation of this approach is that it assumes the transect index is representative of the whole site, which may not necessarily be the case in a small number of instances. Site- specific trends were generated in STATISTICA identified by determining Pearson’s parametric linear correlation coefficient (r) (Falk and Well 1997) of annual abundance index with year.

9 Project MAFF BD1446 title AGRI-ENVIRONMENT SCHEMES AND BUTTERFLIES: RE- project code ASSESSING THE IMPACTS AND IMPROVING DELIVERY OF BAP TARGETS

For each species, key sites were identified where status (population size and trend) fitted one of the following categories:  Colonisation (a positive index following five successive index values of 0)  Extinction (a positive index preceding five successive index values of 0)  Significant increase [(r) of index over time, P<0.05),  Presumed increase [(r) of index over time, P>0.05, but anecdotal evidence suggests increase]  Significant decrease [(r) of index over time, P<0.05),  Presumed decrease [(r) of index over time, P>0.05, but anecdotal evidence suggests decrease]  Current large, stable population [2003 index falls within top 25% of monitored sites, (r) of index over time P>0.05]  Current medium, stable population [2003 index falls within top 50-75%, (r) of index over time P>0.05]  Current large population, trend unknown (2003 index falls within top 25%, <5 years data) The numbers of sites in each of the categories was tabulated for each species. Note that typically, a substantial proportion of sites were not classed as key sites. These included where: (1) the population was small/medium and there was insufficient data to detect a trend; (2) the population was small and stable; or (3) where the butterfly was recorded only sporadically (>50% indices 0, and maximum value typically <10)

Site habitat and management data was obtained from key sites. Data was obtained from a diverse range of sources (in part to corroborate data from a few sites where only verbal records remained) including site conservation advisers (English Nature, Defra RDS), site managers, farmers/local graziers and butterfly recorders. Data collected included information on timing, extent and intensity of scrub clearance; rabbit distribution, rabbit grazing pressure (three subjective categories; light, moderate or heavy), rabbit trends and control measures; mowing regimes; and stock grazing. Information collected on stock grazing included grazing system (continuous/free-range or rotational/paddock), seasonal (max number per day over grazing period) and annual stocking density, timing of grazing, broad stock type and breed, number of animals, and area stock grazed (hectares). Stocking densities were defined as the number of livestock units per hectare per year (LUHaYr) using standard livestock units described in the 2003 Countryside Stewardship Handbook (and for additional stock types in Nix, 1999).

2.8 Monitoring habitat condition Habitat condition pilot studies were carried out in 2003 and 2004, utilising volunteer recorders. In 2003, the focus of the ‘entry level’ study was to assess the potential to involve volunteers for the first time in monitoring sward height and structure (two vital components which determine habitat condition) at butterfly monitored sites. All recorders who currently walk a butterfly transect were invited to carry out surveys of the sward height and structure of their butterfly monitored sites twice during the year (peak and end of growing season), by two rapid methods; the sward stick and drop disk. A training session was organised for participants. Full details are given in the project report (Brereton & Stewart, 2004). Along with turf data and site photographs, volunteers were asked to send in a completed TR4 form (site map and meta-data) and a TR12 form that documents annual changes at sites (e.g. habitat and management changes). Survey work was carried out in a range of early successional (open) habitats including grassland, heathland, marsh (wet grassland) and bracken.

The 2004 pilot study developed monitoring habitat condition beyond sward structure to include the full range of attributes considered to be of importance to individual species. Habitat condition survey methods were devised for each species, due to the wide variety of differing habitat attributes required by each. The aim was to devise robust habitat condition survey methods that could be completed quickly and easily by volunteer recorders with minimal training or experience in botanical survey methods. The target butterfly species for the pilot survey included BAP Priority species; BAP SCC and widespread grassland species indicative of generic favourable habitat condition for target biodiversity including Small Heath and Common Blue. The study focused on open semi-natural habitats subject to agricultural management, especially grazing and scrub control. Field testing was carried out by volunteer recorders at a range of butterfly transect sites, mainly in England. Survey design followed JNCC’s Common Standards Monitoring Framework and the approach adopted by English Nature (EN) for condition assessment of SSSIs in England. Habitat condition survey methods for each species were drawn up with reference to research publications and in consultation with species experts.

The range of condition indicators (attributes) selected for recording (n=18 across all species) were of three broad types: (1) population measures (e.g. area occupied); (2) key adult resources (e.g. larval foodplants in a particular vegetation structure); and (3) positive/negative indicators of habitat change (e.g. levels of Rabbit and stock grazing). For recorders who wanted to take part in the survey, but who did not have BAP species on their monitored sites, generic habitat

10 Project MAFF BD1446 title AGRI-ENVIRONMENT SCHEMES AND BUTTERFLIES: RE- project code ASSESSING THE IMPACTS AND IMPROVING DELIVERY OF BAP TARGETS condition survey forms were generated for species assemblages of widespread habitat types, including amenity grassland and hedgerows. Following methodology development, standardised proformas were drawn up for each species and habitat. Full details are given in the project report (Brereton, Brooks & Hobson, 2005). Recorders were invited to take part in the pilot surveys through advertisements at the National Recording meeting, the BD1446 Annual newsletter to recorders, via the UK Transect eforum, and through a letter sent to (a) all recorders in the CEH/JNCC Butterfly Monitoring Scheme and (b) on Butterfly Conservation’s butterfly transect address list database. In this preliminary study, it was not possible to devise full condition assessment forms, as there were insufficient research data to enable key attributes to be identified and generic target levels to be set. Instead, the key objective of this study was to test a range of potentially important attributes for each species across a wide range of sites, in order to identify key attributes, set generic attribute target levels and enable standardised condition assessment protocols to be developed in the future. In total, 16 species survey forms and three habitat survey forms were devised, with reference to research information and in consultation with species experts.

3. RESULTS

3.1 Additional butterfly monitoring data collected under BD1446

3.1.1 Butterfly Transect Data Butterfly abundance data were collated for 535 transects under Defra contract BD1427. Through BD1446, data from a further 285 transects in England was collated, an increase of over 50%. One hundred and ninety four new transects were established from 2001-2003, with 2003 being a record year for establishment of new sites (n=84).

 The record increase in the numbers of new transects set up in 2003 highlighted the benefit of a high-profile project in supporting the development of butterfly monitoring in the UK.

80 70 p u

t 60 e s 50 s t

c 40 e s

n 30 a r t 20 w e

N 10 0 1990 1992 1994 1996 1998 2000 2002

Figure 3.1.1. Increasing number of new butterfly transects established over period of schemes (closed circles), and number of agri- environment scheme sites monitored by transects (open circles).

Of the transect sites added, 90 were in SSSIs, 84 monitored one or more BAP Species, including 36 which monitored BAP Priority species. A large proportion (45%) of the additional transects sampled land entered into agri-environment schemes, with 94 in CSS and 11 in ESAs (Table 3.3.1). Thirty of these additional transects sampled ordinary farmland; representing a 157% increase in the number of ordinary farmland monitored sites compared to BD1427.

3.1.2 Non-Transect Monitoring Data In addition to new transect sites, annual abundance data from timed counts, larval web counts (for Marsh Fritillary only) and egg counts were collated from 180 sites (Figure 3.1.2). Again, this data was of high value to the project aims. All of the sites monitor one or more BAP species, whilst are third are entered into schemes in England (n=29 in CSS and 36 in ESA). (Table 3.1.2). Forty of the sites have more than 10 years of data, and in some cases this runs back as far as 1984.

Table 3.1.2. Additional data collated under BD1446

Method No. new sites added Transect 232 Timed count 68 Maximum record/Peak count 30 Larval web count 80 Egg count 2

Figure 3.1.2. Location of additional monitoring sites collated under BD1446 (285 Transect & 180 Non-Transect)

3.1.3 Value of additional data  The additional data collected under BD1446 enabled a more powerful and wide-ranging analysis of the impacts of schemes on butterfly populations.  National scheme site trends were calculable for 39 species under BD1446, compared to 34 under BD1427.

The additional species included four BAP Priority species, High Brown Fritillary, Heath Fritillary (regional-only trend in BD1427), Northern Brown Argus and Pearl-bordered Fritillary, and two BAP SCC, Brown Hairstreak and Lulworth Skipper.

 For all of the 32 comparable species analysed under BD1446, the scheme site trend was more precise (lower standard error) than that generated under BD1427.

 The extra data meant that for some rare species, regional as well as national trends could be generated for the first time.

For example, collation of timed count data for the High Brown Fritillary improved monitoring coverage in two key areas, south west England (26 sites) and Wales (10 sites). This was important, given that there were regional differences in trends for this species (Table 3.1.3).

Table 3. 1.3 High Brown Fritillary regional trends 1990-2003 calculated using transect and timed count data

Region No. sites Trend slope +/- SE Mean annual % change Trend South West 37 0.81 +/- 0.07 -19 Sig. Dec. Midlands 5 0.81 +/- 0.04 -19 Sig. Dec. North West 33 0.99 +/- 0.02 -0.8 Stable Wales 10 0.86 +/- 0.04 -14 Sig. Dec.

3.2 Value of CREEM statistical development work A software function programmed in R (Dalgaard, 2002) was developed to model butterfly transect data at the regional, country and national level, and tested for four species; Silver-spotted Skipper, Chalkhill Blue, Small Heath and Common Blue. The GAM/GEE method was used for regions that had 50 or more non-zero counts across the year and in these cases, any within-transect correlation was incorporated into model standard errors. For regions with less than 50 non-zero observations in total, a GAM method (which does not incorporate within-transect correlation) was used. Since this method does not assume any within-transect correlation, the upper and lower limits for these indices should be treated with caution. Transect-level indices were estimated for each day of the sampling season by setting any environmental variables in the model at typical (i.e. median) transect level values and making predictions for each day in the sampling season. These predictions for each day were then summed for each day across the designated sampling season to provide an annual transect level index. The GEE standard errors (when available) were then used to obtain upper and lower 95% confidence limits for these indices. For regions with few transect visits, GAM standard errors were used instead. Regional indices were estimated by averaging the predicted transect indices within a region; the upper and lower limits for these regional indices were obtained using the GEE standard errors (when available). National indices were obtained by averaging the predicted regional indices within the UK. Full details are given in the report by Brewer (2004). In the software function, a procedure was developed to transform annual indices so that historical data could be incorporated into the time modelling of trends.

The major advantages of this approach over the existing approach are: (1) increased flexibility; (2) more realistic index ranges; (3) precision estimates (standard errors) for site indices; (4) regional level model formulation and fitting; and (5) the ability to calculate transect indices for sites with missing counts. Each of these issues will be discussed in turn. The first major advantage of this approach is that the butterfly indices (per metre) are modelled in a very flexible way that permits multiple brooding behaviour within sites to be modelled across time. Additionally, brooding behaviour is permitted to vary across regions. Specifically, Generalised Additive Models (GAMs) allow the relationship between each covariate (e.g. day, sun, wind etc) and the index to be non-linear on the link scale, to enable multiple brooding behaviour to be accommodated. The former approach employed a less flexible method (Generalized Linear models (GLMs)) which required the relationship between day and the butterfly index to be linear on the log scale. This does not allow for multiple brooding behaviour that occurs in many butterfly species throughout the UK. The second major advantage of this approach is that the upper and lower 95% confidence limits for national, regional and transect-level indices are based on more realistic assumptions. For instance, butterfly counts within a transect over time are likely to be more similar than butterfly counts collected from different transects and this similarity (or correlation) must be acknowledged if upper and lower confidence limits for any indices are to be believed. In particular, positive within-transect autocorrelation (which is often present for counts within transects through time) can lead to substantial underestimation of parameter uncertainty, which can result in index limits that are too narrow.

Incorporating within-transect autocorrelation helps ensure fluctuations in butterfly indices that are within the natural bounds of sampling variation are not misinterpreted as real changes in butterfly abundance. This approach utilises Generalized Estimating Equations (GEEs) that permit correlation within transect counts over time and adjust the upper and lower index limits accordingly. The former approach attempted to account for any within-transect correlation using a bootstrap method. While bootstrap methods have been shown to work well for uncorrelated data, little work has been done on the ability of this method to provide realistic indices for repeated-measures data. In particular, the utility of bootstrap methods for data sets with small numbers of transects or transects with few visits is highly questionable; the bootstrap method is not recommended for small sets of independent data and it is likely this is also the case for data sets with small numbers of transects. A further advantage of this approach is that the GAM/GEE method is fitted at the regional level while transect level indices are calculated using transect level covariate information. This level of model fitting allows the brooding behaviour and covariate effects to differ across regions within and across years. This new approach also allows transect indices to be calculated for sites with few visits. In the past, missing counts were

13 Project MAFF BD1446 title AGRI-ENVIRONMENT SCHEMES AND BUTTERFLIES: RE- project code ASSESSING THE IMPACTS AND IMPROVING DELIVERY OF BAP TARGETS interpolated (by averaging counts from neighbouring weeks) to give a full set of counts across time for each transect and when counts were missing for more than two consecutive weeks a site level index could not be calculated.

 In summary, the modelling work has developed a procedure to calculate a greater number of more realistic (not biased low), validated indices from existing data, which will increase the ability to detect real species trends over time.

Unfortunately, the work was completed too late in the day due to technical problems to enable re-analysis of all the abundance data, though it is likely to be an important tool for future trend analyses and monitoring of scheme and SSSI impacts in future projects (e.g. the UK-BMS BD1453).

3.3. Butterfly monitored sites: location, species, scheme status, SSSI status, habitat & ownership Of the 820 sites monitored for butterflies collated under BD1446 (Figure 3.3.1a) 371 were located on sites entered into agri-environment schemes, including 67 in ESA agreement and 309 in CSS (Table 3.3.1, Figure 3.3.31b). BAP Priority species are monitored on 337 sites (Table 3.3.2), and the number of monitored scheme sites with BAP priority species has almost doubled since BD1427. The number of non-scheme transect sites with priority species has reduced since 2000, which reflects the continued entry of new sites with BAP species into schemes.

Figure 3.3.1 a) (left plot) Location of butterfly transects in England that have been collated by Butterfly Conservation and; b) (right plot) Location of agri-environment scheme transects 1990-2003 (black circles = ESA agreement transects, grey circles = CSS transects)

Table 3.3.1 Agri-environment scheme status of butterfly transects in England 1990-2003

Total no. Total on Total scheme Non scheme Non scheme Scheme status CSS ESA transects agric. land* (CSS+/or ESA) (agric. land)* (woodland) unconfirmed Index data collated 820 667 371 309 67 311 130 18 *= grassland, heathland and other habitats which have the potential for agricultural use

Table 3.3.2 Transects sampling BAP species between 1990 and 2003

Scheme Non Scheme  Priority species 167 127  Species of Conservation Concern 221 222  Proposed BAP species* 324 355 *=Bourn et al 2005(UK BAP review)

Over half of the collated transects (444) occur on SSSIs, of which 231 are in scheme and 138 are on equivalent non scheme sites, i.e. grassland, heathland or wetland (Table 3.3.3). Geographic coverage of monitored scheme sites has improved under BD1446, with the addition of transects in North East England and Yorkshire meaning all Defra regions are now covered (Appendix 3.3.1).

Table 3.3.3. The protected status (SSSI) of scheme and non scheme transects

Scheme Non-scheme (Grass/heath/wet) SSSI 231 138 Non SSSI 136 146

A wide range of UK BAP broad habitats are monitored by transects (Appendix 3.3.2), with calcareous grassland the most heavily sampled (277 sites, 34% of the total). The number of monitored scheme sites in this, the most important habitat for butterflies, has increased by almost 50% under BD1446 (from 122 to 170). Scheme sites are monitored by transects on at least fifteen different BAP Priority habitat types (Appendix 3.3.3) and again, lowland calcareous grassland accounts for a large proportion (42%). As found in BD1427, the majority of transects (>50%) at scheme and non scheme sites are owned by conservation and land management bodies, with the bulk of the remainder in private or nature reserve ownership (Appendix 3.3.4).

Table 3.4 Trends in grass/heath/wetland butterflies at agri-environment schemes sites over the period 1990-2003 (n=371 transects)

BD1427 BD1427 BD1446 BD1446 BD1446 BD1446 BD1427 BD1446 BD1446

94-00 94-00 94-03 94-03 90-03 90-03 94-00 94-03 90-03

Species Status Sward requirement % PA 95%CL % PA 95%CL % PA 95%CL Trend* Trend* Trend* change change change Adonis Blue BAP Priority Short + bare ground 7.12 6.27 4.58 4.96 9.13 3.78 Inc Stable Inc Heath Fritillary BAP Priority Variable turf -10.34 21.95 -8.99 5.61 Dec Stable Dec High Brown Fritillary BAP Priority Variable turf +/- scrub -1.44 5.08 -14.66 5.90 ? Stable Dec Marsh Fritillary BAP Priority Variable turf -26.23 3.53 -6.29 2.76 -4.21 3.76 Dec Dec Dec Northern Brown Argus BAP Priority Medium to tall -8.04 3.74 -6.42 2.69 Dec Dec Pearl-bordered Fritillary BAP Priority Variable turf +/- scrub -7.9 3.57 -5.67 1.96 ? Dec Dec Silver-spotted Skipper BAP Priority Short+ bare ground 25.4 11.19 3.21 5.59 12.08 3.23 Inc Stable Inc Silver-studded Blue BAP Priority Variable ±bare ground -4.78 6.13 -5.28 4.39 1.56 5.70 ? Dec Stable Dingy Skipper BAP Prop. Variable ±bare ground -9.71 5.08 -5.33 2.37 -2.73 1.23 Dec Dec Dec Grayling BAP Prop. Bare ground 4.09 8.58 3.73 4.70 -2.81 2.16 Stable Stable Dec Grizzled Skipper BAP Prop. Variable ±bare ground -0.05 6.76 -4.03 4.17 -3.53 1.65 Stable Stable Dec Small Heath BAP Prop. Short or variable turf -7.47 4.16 -4 1.98 -4.89 1.12 Dec Dec Dec Wall Brown BAP Prop. Variable + bare ground -2.83 5.31 -1.61 2.45 -5.39 1.22 Stable Stable Dec Brown Hairstreak BAP SCC Scrub -22.88 7.55 -7.44 5.59 Dec Dec Chalkhill Blue BAP SCC Short-medium 11.35 3.82 -0.7 2.70 -1.5 1.98 Inc Stable Stable Duke of Burgundy BAP SCC Medium to tall +/- scrub -7.16 6.39 -7.93 4.43 -10.69 1.72 Dec Dec Dec Lulworth Skipper BAP SCC Tall 3.91 4.51 2.84 3.18 Stable Inc Small Blue BAP SCC Variable +/- scrub -9.79 7.08 -9.51 6.21 -7.19 2.69 Dec Dec Dec Small Pearl-bord. Frit. BAP SCC Medium to tall -10.06 12.49 -14.08 4.70 -6.48 2.21 Stable Dec Dec Brown Argus Variable turf -10.96 3.65 -9.01 2.18 0 1.31 Dec Dec Stable Common Blue Short-medium -10.3 2.96 -5.54 1.55 -1.62 0.86 Dec Dec Dec Dark Green Fritillary None-Hab spec. Medium 16.9 11.21 5.81 5.64 9.9 2.67 Inc Inc Inc Brimstone No pref. ± scrub 4.79 2.63 2.9 1.59 0.58 0.63 Inc Inc Stable Comma Scrub edge 13.73 4.55 9.2 2.55 3.48 1.02 Inc Inc Inc Gatekeeper Scrub edge -1.44 2.55 -1.69 1.47 -2.69 0.73 Stable Dec Dec Green Hairstreak None-Hab spec. Variable +/- scrub -3.62 4.47 -5.97 2.94 -2.11 1.51 Stable Dec Dec Green-veined White Medium 6.13 3.35 0.46 1.76 1.23 0.86 Inc Stable Inc Holly Blue Scrub/trees 13.11 7.76 -5.2 1.61 ? Inc Dec Large Skipper Medium to tall+/- scrub -8.44 3.33 -5.51 1.71 -2.12 0.96 Dec Dec Dec Large White None 3.95 3.82 2.45 1.84 -3.12 0.92 Inc Inc Dec Marbled White Medium to tall 3.45 2.88 -4.45 1.78 -0.15 1.04 Inc Dec Stable Meadow Brown Medium 9.6 3.37 0.88 1.59 -0.68 0.71 Inc Stable Stable Orange-tip Medium to tall -1.73 3.04 -2.08 1.80 -3.68 0.80 Stable Dec Dec Peacock None 4.49 3.72 Inc Red Admiral None 5.22 4.23 Inc Ringlet Medium to tall+/- scrub 6.27 2.57 2.86 1.67 1.96 0.88 Inc Inc Inc Small Copper Variable -14.07 3.90 -8.27 2.39 -5.06 1.14 Dec Dec Dec Small Tortoiseshell None -9.97 4.29 -1.48 1.92 -2.99 1.04 Dec Stable Stable Small White None -13.6 3.02 -6.55 1.65 -1.51 0.98 Dec Dec Dec Small/Essex Skipper Tall -15.61 2.67 -16.86 1.90 -7.08 1.12 Dec Dec Dec

Speckled Wood Scrub edge 2.56 2.69 8.78 2.18 3.71 0.92 Stable Inc Inc PA= Per annum. *Trends: Inc=Significant increase, Dec=Significant decrease

3.4 Butterfly abundance trends at scheme sites On average, species declined at a significant mean annual rate of 2.55% per annum (22.5% over 10 years) for the period 1994-2003, compared to a non-significant decline of 15% (15% over 10 years) detected for 1994-2003 through BD1427. The result suggested a possible acceleration in species decline over the last three years, though the difference was not statistically significant. More than half of species declined significantly over the period up to 2003 (51% of species 1994- 2003, 60% 1990-2003), whilst around a fifth increased significantly (18% 1994-2003, 23% 1990-2003). The trends for each species are given in Table 3.4.

 In summary, of the BAP Priority butterflies monitored at schemes sites, half declined significantly over the last ten years, representing a similar result to that identified in the previous project (n=4 of 8 species BD1446, compared to n=2 of 4 under BD1427).

The declining species were Marsh Fritillary, Northern Brown Argus, Pearl-bordered Fritillary and Silver-studded Blue. The Heath Fritillary, which was reported to have declined significantly from 1994-2000, was stable over the period 1994- 2003, indicating a recent recovery. Conversely the Silver-spotted Skipper and Adonis Blue, which increased significantly from 1994-2000, had stable trends 1994-2003 possibly suggesting a recent reversal in fortunes for these species. However, both species increased significantly at scheme sites from 1990-2003, indicating that the longer-term pattern is still up.

For the period 1994-2003, four of the six BAP SCC species decreased whilst two had stable trends. Of the Proposed BAP Priority species, two decreased whilst three were stable. Results were worse for the period 1990-2003, as nine of the eleven BAP SCC/Proposed BAP Priority species decreased significantly, whilst only one species, the Lulworth Skipper increased.

 In summary, trends in BAP SCC and proposed BAP Priority species up to 2003, were in the main similar to those described under BD1427, with if anything the extra data detecting changes for the worse rather than for the better (e.g. change in trend from increase to stable or from stable to a decrease).

Of the other species, including common grassland specialists and wider countryside generalists, ten species decreased significantly, seven increased and three had stable populations at scheme sites. The majority of species which increased were either mobile generalists (e.g. Large White), or species which were known (Asher et al., 2001) to be increasing nationally in range and abundance (e.g. Comma, Ringlet, Speckled Wood), though the list did include Brimstone, a scrub/hedgerow species and Dark Green Fritillary, a medium-turf semi-natural grassland specialist.

3.5 Comparison of butterfly abundance trends between scheme and non scheme sites

3.5.1 Species types

 For All-Species (n=39) there was a significant decline in mean species abundance of 30% at both scheme and non-scheme sites in the ten years from 1994-2003, highlighting the acute problems butterflies face in the English Countryside. The declines of the majority of species (>50%) were statistically significant.

The decline was lower at scheme sites compared to non-scheme sites (mean decline p.a. -2.95%, p<0.05 vs -3.77%, p<0.05), though the difference was not statistically significant (t=0.48, d.f. 76, p=0.63). For habitat specialists (n=19), there was a significant decline in mean abundance at scheme and non-scheme sites (mean decline p.a. -4.66% vs -6.75%), though again the greater mean decline at non-scheme sites was not significant (t=0.97, d.f. 38, p=0.34).

There was also a significant decline in mean abundance of BAP Priority Species (n=8) at scheme and non-scheme sites from 1994-2003.

 However, the mean rate decline per BAP Priority species was significantly reduced by more than half at scheme sites (mean decline p.a. -3.94% ±3.85%CL, compared to -11.89% ±3.85%CL at non-scheme sites, t=2.40, d.f. 7, p=0.04).

 Of the 8 BAP Priority species, six (75%) had improved trends at scheme sites compared to non-scheme sites.

The difference in trend between scheme and non-scheme sites was significant for four of the six species. These were the Adonis Blue, High Brown Fritillary, Heath Fritillary and Silver-studded Blue.

Composite indices of annual butterfly abundance were generated for All-Species, habitat specialists and BAP Priority Species at scheme and non-scheme sites between 1994 and 2003. No differences were detected in the linear trend over time in the composite index for All-Species (stable) and habitat specialists (significant decline) at scheme and non- scheme sites. However, for BAP Priority species (Figure 3.5.1) a significant linear decline in the composite index at non- scheme sites (r=-0.84, n=10, p=0.02) was not evident at scheme sites (r=-0.48, n=10, p=0.16).

 The improved trend in BAP Priority species at scheme sites was particularly noticeable since 2000 (r=0.92, n=4, p=0.079), suggesting that the decline in BAP Priority Species is currently being at least halted, and to some extent reversed. This recent recovery was not evident at non-scheme sites (r=-2.11, n=4, p=0.786).

160 Scheme 160 Scheme

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Figure 3.5.1: Mean index for n=39 All-Species (left plot) and n=8 BAP Priority Species (right plot) scheme and non scheme 1994-2003

3.5.2 “Winners & losers” at scheme and non-scheme sites A further measure of the performance of butterfly species at scheme sites was made by comparing differences in trends (magnitude differences) for each species between scheme and non-scheme sites. The ten ‘winners’ and ‘losers’ are illustrated in Appendix 3.5.2. The results were not as clear-cut as under BD1427, but there was some evidence to confirm that as described in BD1427, species benefiting from schemes included those associated with short and medium turf conditions, including Silver-spotted Skipper, Adonis Blue and Dark Green Fritillary. Species least benefiting from scheme sites included those associated with ranker grass, variable turf and scrub edge/mosaics, including Small and Essex Skipper, Lulworth Skipper, Small Blue and Duke of Burgundy.

3.5.3 Comparison of butterfly trends between scheme and non-scheme sites – by habitat structure Trends in butterfly populations at scheme and non-scheme sites were further assessed in relation to the sward requirements of monitored species. This was an important analysis as there were concerns raised through results in BD1427, that on grassland sites schemes were benefiting short-medium turf species associated with generic favourable habitat conditions, unwittingly at the expense of species requiring habitat mosaic and ‘undesirable levels’ of habitat attributes such as scrub and bare ground. This issue was inspected further in BD1446, where trends in selected short/medium-turf grassland species and mosaic species assemblages were compared within and between scheme and non-scheme sites from 1994-2003. The six mosaic species were Brown Argus, Dingy Skipper, Duke of Burgundy, Green Hairstreak, Grizzled Skipper and Small Blue, whilst the nine short/medium turf species were Adonis Blue, Marsh Fritillary, Silver-spotted Skipper, Chalkhill Blue, Common Blue, Dark Green Fritillary, Green-veined White, Meadow Brown and Small Heath. The Bracken fritillaries were excluded from the analysis, as they were more likely being managed specifically for and because they are not strictly grassland species.

There was a significant mean decline in abundance of All-Species combined (n=32) at both scheme and non-scheme sites. In contrast, short/medium -turf habitat specialists were stable at scheme and non-scheme sites (mean annual change -0.2% vs -2.81, both n.s.), with the species suite performing significantly better (at the 10% level) at scheme sites (t=-1.87, d.f. 5, p=0.09). Each of the 6 species requiring mosaic habitats had a worse trend at scheme sites compared to non-scheme sites. At scheme sites, the mean annual rate of decline of habitats specialists requiring habitat mosaics was significantly higher than at non-scheme sites (-6.97% p.a., p<0.05, compared to -1.06% per annum, n.s. at non-scheme sites, t=-3.91, d.f. 5, p=0.01).

Composite indices of annual butterfly abundance for mosaic and short-turf habitat specialist species were plotted for scheme and non-scheme sites between 1994 and 2003 (Figure 3.5.3). The plots illustrate the relative improvement in the fortunes of short/medium turf species since the late 1990s and the relative downturn in mosaic species. These changes are linked to the policy drive over the same period to restore generic favourable habitats conditions at SSSIs and other semi- natural sites, through schemes and other conservation management mechanisms.

 These data provide further strong evidence to indicate that overall, scheme management is benefiting BAP Priority and short/medium turf habitat specialists associated with generic target habitat conditions, at the expense of other specialist species requiring mosaics and habitat heterogeneity at a different spatial scale.

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Figure 3.5.3 Mean index for n=9 short/medium turf S (left plot) and n=6 mosaic (right plot) grassland habitat specialists, scheme and non-scheme 1994-2003

3.5.4 Comparison of trends between scheme and non-scheme sites – by region and BAP Priority habitat Selected analyses were completed to show the potential of the data to detect species trends at scheme and non-scheme sites at the regional scale and by BAP Priority Habitat. The Marsh Fritillary (Figure 3.5.4.1) was found to be declining significantly at scheme and non-scheme sites in both Purple Moor Grass and Rush pastures in western England, and Lowland Calcareous grassland in central southern England. However, the decline was significantly greater at non-scheme sites in Purple Moor Grass and rush pastures (65% over 10 years, compared to 43-54%).

Schem e Schem e 1.4 Non-Sche m e 2.5 Non-Sche m e 1.2 2 1 1.5 x

0.8 x e e d d n n I 0.6 I 1 0.4 0.5 0.2

0 0 1994 1996 1998 2000 2002 1994 1996 1998 2000 2002

Figure 3.5.4.1 Trends in abundance of the Marsh Fritillary in Lowland Calcareous grasslands (left plot) and Purple Moor Grass and Rush pasture (right plot) scheme and non-scheme sites 1994-2003. Linear trendlines are added for clarity.

The High Brown Fritillary performed significantly better at scheme sites, than non-scheme sites in both north west and south west England (Figure 3.5.4.2). In north west England the butterfly was roughly stable at scheme sites compared to a significant decline at non-scheme sites (-16% decline over 10 years vs -50% decline, p<0.05) whilst in the south-west the severe declines were more acute at non-scheme sites (77% scheme sites, 94% non-scheme sites).

 The results demonstrate that schemes have played a particularly important role in helping to reverse the decline in the High Brown Fritillary through concerted effort in recent years.

Schem e 10000 Sche m e 1000 Non-Schem e Non-Schem e

) 1000 ) e e l l 100 a a c c s s

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e 10 d d n n I

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Figure 3.5.4.2 Trends in abundance of the High Brown Fritillary in south west England (left plot) and north west England (right plot) at scheme and non-scheme sites 1994-2003.

3.5.5 Comparison of butterfly trends between scheme and non scheme sites – lowland calcareous grassland A separate habitat analysis was carried out for lowland calcareous grassland, as this is the main BAP habitat type sampled by transects (n=170 scheme and n=102 non scheme sites 1994-2003). Twenty-one species were included in the analysis, adopting the species selection approach in BD1427, with three BAP priority Species (Adonis Blue, Marsh Fritillary, Silver-spotted Skipper), nine other habitat specialists (Brown Argus, Chalkhill Blue, Dingy Skipper, Duke of Burgundy, Grayling, Grizzled Skipper, Small Blue, Green Hairstreak, Dark Green Fritillary) and nine common grassland breeding butterflies (Common Blue, Large Skipper, Marbled White, Meadow Brown, Ringlet, Small/Essex Skipper, Speckled Wood, Small Heath and Wall Brown)

For all-species over the period 1994-2003, there was no overall change in mean abundance at scheme or non-scheme sites (mean annual change per species -2.16%, n.s. vs -2.02%, n.s.), with the mean species trend very similar at scheme and non-scheme sites (t=-0.07, d.f. 40, p=0.94). For the 12 habitat specialists, the mean species trend was stable at scheme sites (-1.55% p.a., n.s.), but in significant decline at non-scheme sites (-3.3% p.a., p<0.05). Though this result suggested an overall benefit of scheme management for habitat specialist butterflies at lowland calcareous grassland sites, it is

19 Project MAFF BD1446 title AGRI-ENVIRONMENT SCHEMES AND BUTTERFLIES: RE- project code ASSESSING THE IMPACTS AND IMPROVING DELIVERY OF BAP TARGETS important to note that seven of the 12 habitat specialists had a more positive trend at non-scheme sites. Two the three BAP Priority species had more positive trends at scheme sites.

 In summary, there was no clear-cut evidence to demonstrate that habitat specialists were performing better overall at scheme sites than non scheme sites in lowland calcareous grassland habitats.

At lowland calcareous grassland sites, the mean annual trend of habitat specialists requiring habitat mosaics was significantly worse at scheme sites compared to non-scheme sites (t=-3.11, d.f. 10, p=0.01). Each of the six species requiring mosaic habitats had a worse trend at scheme sites where the mean annual trend was in decline (mean decline per annum -7.1%, p<0.05), whilst the mean trend at non-scheme sites was stable (-1.45 %, n.s.). In contrast short/medium turf habitat specialists were stable at both scheme and non-scheme sites (mean decline -0.31% vs -3.34% p.a., both n.s.), with the difference in mean trend not significant (t=1.5, d.f. 16, p=0.15).

These data provide further evidence to support the conclusion highlighted in BD1427, that the drive to restore generic (‘favourable’) habitat conditions on sites as defined by homogenous NVC communities is impacting on Non BAP Priority species requiring habitat mosaics and habitat heterogeneity at a different spatial scale.

3.5.6 Comparison of butterfly trends between scheme and non-scheme sites on ‘ordinary’ farmland Abundance trends of six ordinary farmland indicator species that breed in hedgerows, grasslands and field margins were compared at transects on 60 ‘ordinary’ farmland sites versus elsewhere. The species were Brimstone, Common Blue, Green-veined White, Orange-tip, Large Skipper and Small Copper. As sample size was comparatively low, trends were examined over the period 1990-2003. All six species had a more negative trend at ordinary farmland sites compared to elsewhere, with the mean rate of decline significantly greater at ordinary farmland sites (-53% vs -15% elsewhere over 14 years, t=-2.49, d.f. 4, p<0.05).

Though sample sizes were low, the research provides new evidence to suggest, as feared, that selected 'common species' are facing acute problems in the general countryside.

Trends in farmland butterflies on the 60 farmland transects were also compared for scheme and non-scheme sites, with two additional species included in the analysis (Marbled White and Meadow Brown). Of concern, six of eight species had worse mean trends at scheme sites, though the difference was not statistically significant (-36% vs -20.5% on non-scheme farmland over 14 years, t=-0.83, d.f. 6, p=0.43). Information on the management carried out at the scheme sites was not collected, though work is likely to have included creation of field margin habitat and hedgerow management. The fact that no positive impact on butterflies on ordinary farmland butterflies was detectable at schemes, highlight the need for a more wide-ranging analysis of scheme arable and hedgerow options on butterflies

3.5.7 Impacts of CSS on arable farmland butterflies in Dorset Forty six (125m) transects were walked at three farms, covering four field margin treatments (CSS 2m, CSS 6m, CSS wild flower mix and unsown control), each less than three years old. Fourteen butterfly species were recorded with butterfly density low in each of the four treatments. Two measures of butterfly diversity (number of species and mean number per transect) were highest in the wildflower margins, and lowest in the 6m margin, though the overall results were not statistically significant (butterfly abundance F(3)(45)=1.06, p= 0.38, species richness (F(3)(45)=1.13, p= 0.35). However, there were significant results for individual species and species assemblages grouped by butterfly family. The unsown margins supported more species and a greater abundance of butterflies than the 2m and 6m margin treatments, and were the most important habitat for Wall Brown. The 6m margins were characterised by a relatively low herb cover and dense grass cover, and may have reduced habitat quality of margins for butterflies in some instances. The importance of hedgerow quality as a positive factor determining butterfly diversity on margins was demonstrated. Hedgerow presence was found to have positive impact, increasing butterfly diversity along field edges, especially the abundance of shade tolerant species such as the Speckled Wood. Specie-rich hedges were found to be important for butterflies for connectivity, as food resources and for shelter. This appeared to apply particularly when herb diversity was low within the margins (unmodified and modified). The full results of the study are presented in Dawson (2004).

 The research provided further research evidence to highlight the positive impact of wildflower margins on butterfly diversity in arable farmland areas and the relatively low value/potential negative impact of certain types of 6m margin.

3.5.8 The effect of year since entry on population trend The effects of year since entry into an agri-environment scheme over the period 1991-2003 was investigated for both Chalkhill Blue and Adonis Blue; both species that appear to have benefited from agri-environment scheme management. A similar analysis under Defra contract BD1427 for Chalkhill Blue only (1991-2000, n=61 transects) suggested that populations tend to decline in the first few years after entry into scheme (during a restoration phase), and subsequently increase as management takes effect. This effect is less clear-cut for Chalkhill Blue 1991-2003 (Figure 3.5.8, n=96 transects), with an overall declining trend (slope 0.96 +/- 0.01), but there does appear to be a recovery in population index over a longer time period.

130 600 120 110 500 x x e 100 e d d 400 n n i

e 80 e 300 t t a a l

70 l l l o 60 o 200 C C 50 100 40 30 0 0 1 2 3 4 5 6 7 8 9 10 11 12 0 1 2 3 4 5 6 7 8 9 10 11 12 Year since entry Year since entry Figure 3.5.8 Population trends in the Chalkhill Blue (n=96 transects) (left) and the Adonis Blue (n=48 transects) (right) following entry into agri-environment schemes

The effect of year since entry on Adonis Blue populations appears to be more immediate (Figure 3.5.8, n= 48 transects), with a considerable upward trend with increasing time since entry (slope 1.12 +/- 0.02). This suggests that the very short turf conditions required by this species can be restored even over a short time period.

3.5.9. Species trends at scheme sites before and after entry The impact on butterfly abundance of site entry into an agri-environment scheme was further assessed by comparing population trends before and after entry at a selection of sites with long data runs. For 20 sites entered into scheme in 1991 or 1992, population trends before and during entry (seven year period 1986-1992) were compared with trends some time after entry (nine year period 1995-2003). 20 non-scheme sites with long data runs were used as control and differences in mean population trends between scheme and non-scheme, and between time periods, were compared using Analysis of Variance (ANOVA). The subset of species were grouped into the following (non-exclusive) covariate categories: 1) short/medium turf species (Adonis Blue, Chalkhill Blue, Common Blue, Dark Green Fritillary, Green- veined White, Meadow Brown, Silver-spotted Skipper, Small Heath), 2) mosaic species (Brown Argus, Dingy Skipper, Duke of Burgundy, Green Hairstreak, Grizzled Skipper, Small Blue, and 3) BAP/proposed BAP species (Adonis Blue, Chalkhill Blue, Dingy Skipper, Duke of Burgundy, Grizzled Skipper, Silver-spotted Skipper, Small Heath).

There was no significant differences in the mean population trend between scheme and control (non-scheme) sites for any of the species groups (p>0.47). This might be due to the fact that sites with long data runs (both scheme and non-scheme) tend to be Nature Reserves that are managed for their butterfly interest. These sites are therefore unlikely to make dramatic management changes after entering agri-environment schemes. Many of the more recently established transects on scheme sites are not biased in this way, sampling land that has not been managed for conservation in the past. Comparing butterfly trends before and after scheme entry for these restoration sites may give a clearer indication of scheme impact. Further ANOVA revealed that time effects were more significant than scheme effects on this small subset of sites over the monitored period.

3.6 Impacts of SSSIs and inter-relationship with scheme sites

Six of eight BAP Priority species declined significantly on SSSIs from 1994-2003, whilst two increased significantly (Adonis Blue and Silver-spotted Skipper). Four of the eight BAP Priority species had improved trends at SSSIs compared to non-SSSIs, whilst no overall difference in mean trend for BAP Priority species was detected between SSSIs and non- SSSIs. However, sample sizes were low for four of the BAP Priority species at SSSIs and caution must be used in interpreting the results. Trends were more variable at non-SSSIs, in part due to smaller sample sizes. The results for all habitat specialists between SSSIs and non-SSSIs were also mixed. Six of 13 habitat specialists (with adequate sample sizes) had improved trends at SSSIs but no difference was detectable in the mean trend per species for habitat specialists (t=-0.19, d.f. 24, p=0.84).

 In summary, no strong evidence was available to detect an overall difference in trends of BAP Priority and habitat specialists between SSSIs and non SSSIs.

Mosaic species (n=6) were found to be in significant decline at both SSSIs and non-SSSIs (mean -4.1% p.a., p<0.05 vs -5%, p<0.05 non-SSSIs), whereas no difference was apparent in the mean rate of decline for all species (t=0.5 d.f. 10 p=0.62 ). Short/medium turf species (n=8) were broadly stable at both SSSIs and non SSSIs (mean annual change +0.02%, n.s. vs +2.7%, n.s.) (t=-0.37, d.f. 14, p=0.71).

However, on SSSIs entered into schemes, 7 of 8 BAP Priority species had significantly improved trends compared to non- scheme sites (Yates corrected χ2=6.25, d.f. 1, p=0.01). Additionally, the mean decline of BAP Priority Species on SSSIs was highly significantly lower at scheme sites compared to non-scheme sites (31% over 10 years, n.s. vs 68%, p<0.05) (t=3.88, d.f. 7, p>0.001). In contrast, no difference was detected between scheme and non-scheme sites on SSSIs for All- Species or habitat specialists.

 These data indicate that schemes are a key mechanism helping to halt the decline of BAP Priority species on SSSIs.

At SSSI scheme sites, the mean annual decline of mosaic habitat specialists was significantly higher than at non scheme sites (-7% vs -1.%, n=6 species, t=-3.16, d.f. 5 p=0.01). Each of the 6 species requiring mosaic habitats had a worse trend at SSSI scheme sites compared to SSSI non-scheme sites. In contrast specialist species requiring short/medium turf conditions were stable at SSSI scheme sites (+1.003% PA, n.s.), whilst at SSSI non scheme sites there was a significant decline in the species assemblage (-3.2%, p<0.05) and the mean trend difference between scheme and non-scheme sites was close to significant (t=1.53, d.f. 16, p=0.145).

 These data provided yet further evidence to indicate that the drive (through scheme management) to restore generic target habitat conditions on SSSIs defined by homogenous NVC communities is impacting on non-BAP Priority species requiring habitat mosaics.

Specific examples of the negative impacts of generic habitat management on mosaic species included the Small Blue at Park Bottom, the Duke of Burgundy at Levin Down, and the Dingy and Grizzled Skipper at Fairmile Bottom.

3.7 Habitat management – what works? A total of 1700 separate trends were calculated and examined from 450 sites, covering 11 key species between 1990 and 2003. From this analysis more than 200 key sites were identified (Appendix 3.7.1), where management data was sought. The emphasis was on obtaining detailed management data from successfully managed sites, preferably where large populations were maintained and on understanding the likely causes of decline at failing sites. Collecting management data proved extremely time consuming, though in the time available data were collected from more than 130 sites, with examples of successful management obtained for all key species. Two main analyses were completed: (1) identification of sites where management has benefited a range of BAP Priority species and habitat specialist assemblages, and (2) selected management results for BAP Priority and other key species. The results are summarised below and in far greater detail in Appendix 3.7.2.

Management success was to a large degree determined by outcome-focussed (adaptive, targeted, species-specific) judgements made by well informed and experienced land managers who  had a clear idea of the target habitat conditions they were seeking to maintain/restore

 carefully targeted management in time and space based on local knowledge  modified (‘fine-tuned’) management as required when habitat conditions necessitated a change (e.g. to prevent over and undergrazing)  had sufficient control and resources (including available stock and adjacent grazing land) to modify management

Common reasons why butterflies declined at sites, were related to the lack of sufficient fine-tuning of prescriptions, and included  lack of knowledge of species occurrence or understanding of the habitat requirements of the species being managed for  lack of control of rabbit grazing  inappropriate (in time and space) bracken and scrub cutting regimes  overgrazing in the summer during drought years  insufficient grazing in years of high grass growth

The available data indicated that the main benefits of agri-environment schemes to butterflies were that they provided resources to enable managers to restore grazing, better control stock and rabbit grazing, and implement scrub/bracken clearance and rotational management. All of the site managers contacted (n=140) over the course of the project, commented that agri-environment scheme made a real difference in their ability to manage sites more effectively, though our data shows this did not always translate to measurable positive results on the ground.

Stock grazing was found to be an essential part of management for many species especially Adonis Blue, Chalkhill Blue, High Brown Fritillary, Heath Fritillary, Marsh Fritillary, Northern Brown Argus and Small Blue. A wide range of stock grazing regimes were found to be beneficial both between and within species. ‘Year-round’ (i.e. during/post growing season grazing) cattle grazing on large (>100 hectares) calcareous grassland sites was singled out as particularly beneficial to a wide range of species, including Adonis Blue, Chalkhill Blue, Dingy Skipper, Duke of Burgundy, Glanville Fritillary, Grayling, Grizzled Skipper, High Brown Fritillary, Northern Brown Argus and Silver-spotted Skipper. As a rough rule of thumb, a stocking level on southern calcareous grasslands of ca1LUHaYr was likely to create a variable turf under this regime, whilst a stocking level of ca. 2LUHaYr, would create more uniformly short sward conditions. Examples of year-round cattle grazed sites of high importance for butterflies included Cerne Abbas Giant, Brook Down, Mere Down, Rodborough Common and Whitbarrow.

There was no evidence to indicate that complex rotational (paddock) grazing was essential and examples were highlighted for all species studied where continuous (free range) worked well.

No requirement was found for native cattle breeds on lowland calcareous grassland in southern England, though in the more extreme terrain of north-west England, hardy breeds were essential. Popular hardy breeds on well managed sites included Dexter, Galloway, Belted Galloway, North Devon and Red Poll. No strong association was found between individual native sheep breeds and well grazed sites, and many good sites were grazed by cross breeds. However, native breeds were found to play a vital role in scrub control, with effective Bramble browsers including Hebridean, Wiltshire Horn and Herdwick.

Rabbit grazing was a feature of every single calcareous grassland site where management data was obtained (n=ca100 sites) and thus its value can not be underestimated. Rabbit grazing was a vital element at many sites where BAP species had large, stable population trends. For some species, including Dark Green Fritillary, Silver-spotted Skipper, Duke of Burgundy and Small Blue, nationally important populations were maintained solely by rabbit grazing, though at other sites overgrazing by rabbits lead to declines of the same species. Effective rabbit control is the key to success. For management prescriptions, stocking levels must be set in relation to the level of rabbit grazing if they are to have any meaning. In the case of the Adonis Blue, stocking levels as low as <0.1LuhaYr were sufficient at heavily rabbit grazed sites, whilst at lightly rabbit grazed sites typical stocking levels at good sites were in the region of 0.8LUHaYr worked well.

Abandoned calcareous grassland, comprised of medium to rank tall grassland and scrub was an important butterfly habitat, supporting nationally important populations of Dark Green Fritillary, Small Blue and Duke of Burgundy at some

23 Project MAFF BD1446 title AGRI-ENVIRONMENT SCHEMES AND BUTTERFLIES: RE- project code ASSESSING THE IMPACTS AND IMPROVING DELIVERY OF BAP TARGETS sites. The importance of maintaining representation of lowland calcareous grassland in late successional condition at a landscape scale is emphasised.

Rabbit and stock grazing combinations worked extremely well at many sites, particularly winter stock grazing regimes; with stock playing a vital role in removing litter and grass growth at the end of the growing season, and rabbits creating bare ground and a variable turf through the spring and summer. The value of periodic heavy winter grazing was stressed by a number of site managers in helping to maintain high herb densities in the long term

Pony grazing was uncommon, but where employed created highly suitable habitat for a range of important species including Duke of Burgundy, High Brown Fritillary, Northern Brown Argus, Pearl-bordered Fritillary and Silver-spotted Skipper.

For all 12 species investigated there were examples where scrub clearance (from 25m 2 patches upwards) was demonstrated to have improved habitat quality and increase site carrying capacity, but this did not occur on all occasions by any means.

In addition to clearance, the maintenance and successional management of scrub on rotation was vital to a range of important species especially Dark Green Fritillary, Duke of Burgundy, High Brown Fritillary and Pearl-bordered Fritillary. Gorse cutting on a 2-6 year rotation was an example of a regime benefiting both Dark Green and Pearl-bordered Fritillary. Rotational bracken management was an important tool to maintain suitable habitat conditions for the Dark Green Fritillary, Pearl-bordered Fritillary and High Brown Fritillary. Cutting bracken in strips (<50% per annum) outside the growing season on a 2-5 year rotation worked well for these species at some sites.

Grass cutting, was also found to be an important tool to maintain suitable habitat conditions at sites where grazing could not be restored for practical reasons (e.g. urban fringes sites and regions with few stock animals). Species benefiting from annual mowing (especially autumn flail mowing at 5-10cm blade height) at individual sites included Chalkhill Blue, Dark Green Fritillary, Duke of Burgundy (in combination with scrub management), Heath Fritillary and Marsh Fritillary. Other species which have also been known to benefit from mowing include Dingy Skipper and Grizzled Skipper. Annual mowing was also widely employed to create nectaring habitat for a number of species.

For some species, there were alarming extinction rates and few examples where management had worked. A particular problem was identified in managing bracken dominated grasslands in south west England, where Pearl-bordered Fritillary and High Brown Fritillary are in rapid decline. At a number of sites, where grazing regimes are not thought to have changed, suitable breeding/larval development vegetation (violets growing through exposed, shallow {<15cm deep} Bracken litter in April/May) is becoming rarer (“naturally”). The sites may possibly be changing in relation to external factors such as climate change and atmospheric nitrogen pollution. Further research is urgently required to understand habitat dynamics and identify beneficial management practices.

Some of the most important calcareous grassland sites which supported a wide range of differing species comprised mosaics with high scrub levels (frequently >50%); conditions that were inimical to generic site favourable condition measured in NVC terms. Species frequently associated with these habitat included Dark Green Fritillary, Dingy Skipper, Duke of Burgundy, Green Hairstreak, Grizzled Skipper, High Brown Fritillary, Northern Brown Argus, Pearl-bordered Fritillary and Small Blue. There were concerns that at a number of sites nationally important for butterflies (including Duke of Burgundy and Dark Green Fritillary in some instances), but where flagship BAP butterflies were not present, managers were being required to change the habitat and management of sites (e.g. reduce scrub cover) on generic habitat grounds to the potential detriment of the special butterfly and other invertebrate interest.

The available data indicated that butterflies were more likely to survive on large sites, highlighting the importance of managing at a landscape scale, involving a combination of (1) encouraging linkages between habitat patches and (2) targeting restoration adjacent to known colonies to help create larger sites.

3.8 Habitat Condition Habitat Monitoring Two detailed reports of the 2003 and 2004 habitat condition pilot studies were completed (Brereton & Stewart, 2003; and Brereton, Brookes & Hobson, 2005), with the results summarised below.

3.8.1 2003 pilot study 32 volunteers took part and measured turf height at 37 butterfly transect sites (15 in CSS/ESA agreements), completing around 20,000 measurements. A questionnaire analysis of recorders was carried out and revealed that the main motivation for recorders taking part in surveys was to understand changes in butterfly numbers at sites in relation to habitat management and (2) to do something of value for a conservation body. 90% of recorders found the experience positive and were interested in taking part next year, whilst more than 80% were prepared to monitor sward structure annually over a number of years. The majority of recorders were satisfied with both survey methods and found them easy to use. However, there were some concerns with both methods (e.g. sward stick - which grass blade to measure, drop disk - flattening of vegetation). Given a choice, 61% of respondents said they would prefer to use a drop disk over a sward stick, whilst 27% of surveyors said the reverse was true. Recorders preferred the drop disk because of ease of use and a perception that it gave a better assessment of average sward height. The surveys generated valuable baseline information on sward height and structure at important butterfly sites. More than four-fifths of the sites surveyed recorded one or more BAP butterfly species in recent years, whilst two-thirds of the sites were designated as SSSI and 40% were in schemes. The surveys have also provided valuable new information to enable sward stick/drop disk comparisons in a wider range of early successional habitats than previously studied. The sward height and structure data collected has potential applications for research including identification of sward height preferences for individual species and the relationship between butterfly species richness and sward structure.

3.8.2 2004 pilot study 37 volunteers took part in piloting the survey forms, completing approximately 100 surveys at 47 sites for 15 species and two broad habitat types. The surveys generated an extremely valuable baseline of habitat conditions at some very important BAP butterfly sites. A photographic record of habitat conditions was made at eleven sites. Participation in surveys was encouraging given that: (1) publicity was limited; (2) the survey was primarily about recording vegetation rather than counting butterflies; (3) there was a short lead in time; and (4) no training was offered. In general the surveys were completed to a very high standard, with recorders finding the surveys quick and easy to do (clear and simple proformas were important here) and the majority having no problems following the methodology.

The future role of various attributes recorded on the surveys as key condition indicators in future monitoring was assessed. Key condition indicators were classified as those where between year quantity changes were likely to directly help identify the habitat condition category. It was considered unwise to assess condition without knowing the population trend. Of the potential population measures as condition indicators, inspection of transect data revealed that change in the transect index between years was unlikely to be a reliable measure of condition, as rapid declines/increases may be attributable to the weather. However, one potentially useful statistic which may highlight population vulnerability is the (‘lower level target’) transect index below which extinction could theoretically occur the following year (identified through an analysis of BC/CEH’s all-sites transect database). A more meaningful condition indicator may be the extent to which a site index deviates from the national index between years, as this is more likely to be due to site habitat and management change. For example if the abundance of a BAP butterfly decreases by a greater than 25% deviation from the national trend, this may indicate unfavourable condition.

From 2006, there will be the facility for recorders to obtain national BC/CEH transect indices from the new UK-BMS website (proposed as www.ukbms.org.uk) and carry out this analysis at the site level. There were also problems in using area occupied as a condition indicator - there was evidence from this study (and from previous studies) that recorders may measure extent differently (especially on scrubby sites, or where breeding adults are patchily distributed), leading to potential errors in estimation and reduced power to detect real change over time. A better condition indicator (easier to measure) may be to record the presence of suitable breeding habitat, using the same structured walk methodology (marking breeding habitat on maps rather than adult butterflies). The added advantage here is that recording for this attribute can be made outside the flight period. Of the vegetation attributes, an important finding from the surveys was that scores were highly variable (with frequency often determined as ‘rare’ or ‘occasional’ as well as ‘frequent’ and ‘abundant’) at sites where the butterfly population was in favourable condition (relatively medium or large transect index and a stable population trend over the last decade). This result shows that strong butterfly colonies can be maintained both at sites where suitable breeding habitat is continuous and extensive but also at sites where this vegetation is highly localised and concentrated. A conclusion from this is that it will be difficult to set generic target levels and that site- specific targets for key attributes are recommended (the target levels for which may seem low). For the majority of

25 Project MAFF BD1446 title AGRI-ENVIRONMENT SCHEMES AND BUTTERFLIES: RE- project code ASSESSING THE IMPACTS AND IMPROVING DELIVERY OF BAP TARGETS species, the most important vegetation condition indicator was the frequency of suitable breeding vegetation (frequency of foodplant in a specified sward height range with/without bare ground). Nectar and bare ground was also thought to be an important attribute for some species, but for other attributes the results (in terms of value in recording) were inconclusive. Though proper testing of bias in cover estimation was not carried out, anecdotal evidence indicated there was considerable variability between recorders in how this parameter was estimated. Frequency was considered to be a far more accurate and easier method of recording quantity levels of vegetation attributes. With a structured walk sample size of 20, there was a 50% chance that the frequency score was accurate to within 5%, but could be ‘out’ by up to 15%. A sample size of 60 was found to be more satisfactory, with accuracy estimated to be within 1%. A compromise would be a sample size of 30, (80% chance that the frequency result was accurate to within 5%) or 40 (93% chance of 5% accuracy).

Table 3.8.2: Butterfly Conservation’s approach to condition assessment and progress completed under BD1446

Stages of the research Progress Stage 1 - Identify key habitat attributes (condition indicators) either (1) required for each BAP/key Near completed –limited by butterfly (e.g. bare ground, sward height, foodplant abundance, nectar abundance, ungrazed seed available research data heads etc) or that (2) indicate deteriorating/improving habitat conditions for the butterfly (e.g. grazing level, scrub cover, rank grass cover etc) Stage 2 - Develop condition survey methods ('rapid' and suitable for recorders/land Completed managers with only a limited knowledge of vegetation surveys). Stage 3 - Test condition survey forms (fieldwork by staff and recorders) Completed Stage 4 - Refine survey forms (incorporating recorder comments) Completed Stage 5 - Analyse survey data to identify threshold values/target levels for each habitat Part-completed attribute (e.g. what seasonal sward height range is suitable for species A?). Stage 6 - Identify the habitat condition assessment categories (e.g. favourable, Not completed unfavourable declining - overgrazed, unfavourable improving - overgrazed, etc) Stage 7 - Develop integrated habitat condition survey and assessment forms for each Not completed species and (if feasible) for key habitats (e.g. post industrial sites, chalk grassland etc)

A summary of the habitat condition development work and the stage reached through BD1446 is given in Table 3.8.2. Wider testing was recommended to more fully identify key attributes and recommended target levels, and to enable further progress towards developing habitat condition assessment forms for the BAP species. Plans are underway to carry out BAP species-specific surveys in 2005 through Butterfly Conservation’s network of regional staff. For this work training is recommended, especially in relation to the more accurate recording of % cover and flight area boundaries, particularly on scrubby sites. Repeat surveys are highly recommended as they will enable comparison of habitat changes in relation to butterfly abundance changes.

 In summary, both pilot surveys confirmed that there is great potential to use volunteers in the future monitoring of habitat condition, and helped advance considerably progress in developing habitat condition methods for butterflies and a team of recorders willing and able to do the work.

4. TECHNOLOGY TRANSFER

The results from the project have been, and continue to be, disseminated in a wide number of ways, including: (1) through Butterfly Conservation’s website; (2) involvement in policy development, particularly in relation to the design of Environmental Stewardship; (3) newsletters and popular articles; (4) scientific papers and reports; (5) talks at conferences, meetings and public events; (6) attendance of events for farmers and other land managers; (7) regional seminars to Defra staff; and (8) supply of data to Defra. For the latter, Key summary butterfly transect data (site name, grid reference, species present, recording contact) has been supplied and uploaded to Defra’s GIS system, Genie.

Full details of policy work, events and publications are given in Appendix 4.

5. CONCLUSIONS

 The study found that there has been a serious overall decline in butterfly abundance over the 10 last years of 30%. The declines have been across the board including in common and rare species, and for species with widely

differing habitat requirements. Because butterflies are widely accepted as ecological indicators of ecosystem health, this is an alarming result with important implications for other insects and biodiversity in general.

 Agri-environment schemes are playing a positive role in helping to significantly slow and in some cases reverse the declines of BAP Priority species, especially short/medium turf species. They are also helping to deliver significantly better management on SSSIs for these species. These results are welcome, but more resources and time are required if declines for all BAP species are to be eventually reversed.

 The positive effect of schemes seemed to be restricted to BAP Priority Species and was not evident for all species combined or all habitat specialists. This suggests that general conservation measures aimed at conserving birds (on ordinary farmland) and improving SSSIs and other semi-natural habitats have not been sufficient to halt butterfly declines and for some species types they may have exacerbated declines (see next paragraph).

 A particularly worrying result was the elevated decline of non BAP species associated with habitat mosaics at both scheme sites and SSSIs. This is thought to be directly attributable to generic management linked to the drive to simplify site conservation value/assessment and define favourable conservation status of grassland in terms of homogenous (and largely scrub-free) NVC plant communities. This result was also highlighted in BD1427, and more recently in a study exploring the relationship between SSSI condition status and butterfly population trends (Davies, 2005). The study found that four of eight habitat specialists studied maintained lower populations at SSSIs in favourable condition than at sites in one of the unfavourable condition categories. This is of wider concern, as scrub and habitat mosaics are critically important for threatened insects (e.g. 352 species of RDB/BAP associated species, compared to just 10 species of BAP plants and 13 species of BAP bird, Mortimer et al., 2000).

 The conservation importance of habitat mosaics and maintaining habitat heterogeneity at patch, site and landscape scales for butterflies and other invertebrates can not be overemphasised.

 Examples of successful management were found for all species, proving it is technically possible to manage effectively for even the most threatened and specialised butterfly species. The great wealth of information generated on habitat management for specialist butterflies collected under BD1446 needs to effectively reach the land managers and advisers who’s vital task it is to deliver beneficial conservation management on the ground.

 The new agri-environment scheme in England, Environmental Stewardship (ES) has the potential to be a big step forward as it addresses many of the concerns highlighted in this research including the need to: (1) more fully incorporate species and other site-specific interest features into site management objectives; (2) have an outcome focussed approach when managing habitats; and (3) to monitor success. The devil is in the detail and a series of seminars are recommended for RDS POs to highlight the opportunities and issues related to conserving butterflies, especially under Higher Level ES. A similar series has been organised for birds, and in many respects the case to do this for butterflies is more pressing.

 The results clearly demonstrate why it is now more important than ever to have butterflies as a Headline Governmental biodiversity indicators, to complement the existing suite (SSSI condition, farmland birds) and to continue to broadly assess the effectiveness of agri-environment schemes, SSSIs and other policy and land management in conserving biodiversity.

10. REFERENCES

Asher, J., Warren, M., Fox, R., Harding, P., Jeffcoate, G., & Jeffcoate, S. 2001. The Millennium atlas of butterflies in Britain and Ireland. Oxford University Press. Bourn, N. A. D., McCracken, M. E., Wigglesworth, T., Brereton, T., Fox, R., Roy, D., & Warren, M. S. 2005. Proposed changes to the BAP Priority Species List: Butterflies. Butterfly Conservation report no. SO5-23, Wareham. Brereton, T. & Stewart, K. 2004. Habitat condition monitoring by volunteer butterfly recorders: sward height pilot study 2003. Butterfly Conservation, Wareham.

Brereton, T., , Wareham Brook, S. and Hobson R. 2005. Habitat Condition Monitoring for Butterflies: 2004 pilot study. Report No. SO5-06, Butterfly Conservation. Brewer, C., 2004. Preliminary Report using Generalized Estimating Equations to obtain Indices of Abundance. CREEM contract report to Butterfly Conservation & Defra. Butterflies Under Threat Team 1986. The management of chalk grassland for butterflies. Focus on nature conservation, No. 17, Nature Conservancy Council, Peterborough. Dalgaard, P 2002. Introductory Statistics with R. Springer, Netherlands. Davies, H 2005. The consequences of positive management of protected areas to achieve Government targets - how threatened UK butterflies are faring. Unpublished MSc thesis, University College London. Davies, Z.G., Wilson, R.J., Brereton, T.M., and Thomas, C.D. 2005. The re-expansion and improving status of the silver-spotted skipper butterfly (Hesperia comma) in Britain: a metapopulation success story. Biol. Conserv. 124(2):189-198. Dawson, J. 2004. The diversity and abundance of butterflies on arable field margins in the Countryside Stewardship Scheme. Unpublsihed thesis, University of East Anglia. Defra, 2003. A biodiversity strategy for England. Measuring progress: baseline assessment. Department for the Environment, Food and Rural Affairs, London. Defra 2005. Higher Level Stewardship: Farm Environmental Plans: Guidance. Department for Environment, Food and Rural Affairs, London. (www.defra.gov.uk/erdp/pdfs/es/hls-fep-handbook.pdf). Falk, R. and Well, A. D. 1997. Many Faces of the Correlation Coefficient. Journal of Statistics Education v.5, n.3. Gregory RD, Noble DH, Field RF, Marchant JH and Gibbons DW (2002) Using birds as indicators of biodiversity. Ornis Hungarica 12–13, 11–24. Hosmer, D. W. & Lemeshow S. (1989) Applied logistic regression. Wiley, New York. Mortimer, S. et al 2000. The Nature Conservation Value of Scrub in Britain. JNCC, Peterborough. Nix, J. 1999. Farm Management Pocketbook. Wye College Press, Kent. Orlóci L 1967. An agglomerative method for classification of plant communities. J Ecol 55:193–205. Pannekoek, J. & van Strien, AJ 1996. TRIM – Trends & Indices for Monitoring Data. Research Paper No. 9634, Statistics Netherlands, Voorburg. Paradis, E. & Claude, J. 2002. Analysis of comparative data using generalized estimating equations. J. Theor. Biol. 218: 175–185. Robinson, R. A. & Sutherland, W. J. 2002. Post-war changes in arable farming and biodiversity in Great Britain. Journal of Applied Ecology, 39, 157-176. Swaay, C. A. M. van, Warren. M. S. and Lois, G. (in press). Biotope use and trends of European butterflies. Journal of Insect Conservation, in press. Thomas, J.A. 2005. Monitoring change in the abundance and distribution of insects using butterflies and other indicator groups. Phil. Trans. R. Soc. B 360, 339-357. Thomas, J.A., Telfer, M.G., Roy, D.B., Preston, C., Greenwood, J.J.D., Asher, J., Fox, R., Clarke, R.T. and Lawton, J.H. 2004. Comparative losses of British butterflies, birds, and plants and the global extinction crisis. Science 303, 1879-1881.

APPENDICES (Separate 48-page document)

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