UK Biodiversity Indicators in Your Pocket 2013

This documents supports

C4a. Status of threatened species – status of priority species

For further information on C4a. Status of priority species visit http://jncc.defra.gov.uk/page-4238

For further information on BIYP visit http://www.jncc.gov.uk/page-1824

Indicator C4a. Status of priority species – Technical background report – August 2013

Prepared by the Species Indicator Initiative working group:Jeremy Biggs (Pond Conservation), Tom Brereton (BC), David Brooks (Rothamsted Research), Fiona Burns (RSPB), Natasha Chick (Defra), Mark Eaton (RSPB), Richard Gregory (RSPB), Karen Haysom (BCT), Nick Isaac (BRC - CEH), David Noble (BTO), Deborah Procter (JNCC), Mark Stevenson (Defra), James Williams (JNCC).

1. Introduction

The adjustments to the UK biodiversity indicators set as a result of the adoption of the Strategic Plan for Biodiversity (including the Aichi Targets) at the 10th Conference of Parties of the Convention on Biological Diversity mean there is a need to report progress against Aichi Target 12:

Target 12: By 2020 the extinction of known threatened species has been prevented and their conservation status, particularly of those most in decline, has been improved and sustained.

Previously, the UK biodiversity indicator for threatened species used lead partner status assessments on the status of priority species from three-yearly UK Biodiversity Action Plan (UK BAP) reporting rounds. As a result of the devolution of biodiversity strategies to the UK's four nations, there is no longer a current list of UK priority species, or associated reporting. In order to assess progress towards international biodiversity targets at a UK level, and to improve species’ conservation prospects, a robust system of analysis and reporting for threatened species in the UK is needed. This should also help to meet the reporting requirements of the individual countries.

Although it would be possible to develop indicators separately in each of the four countries and use these for UK reporting (with or without amalgamation), this process would be inefficient because:

A. Most of the available datasets are UK wide and so each country would need to separately negotiate with each data provider to develop and update any indicator.

B. Many datasets are likely to be too small to produce reliable trends at country level.

C. The methods for compiling the indicator at UK level would only need to be developed once (rather than four times).

D. If different, bespoke approaches are used to develop indicators at a country level their construction and interpretation may vary in a way that makes compilation at the UK level difficult

In addition, there are a number of species, for example, those listed in the Annexes of the Habitats Directive, where a degree of UK coordination is either already required or where coordination is likely to be beneficial to each country.

This paper presents the first iteration of a new indicator to provide a robust measure of the status of threatened species in the UK, with 'species identified as conservation priorities' being

taken as a proxy for 'threatened species'. Although biodiversity monitoring in the UK may be as good as anywhere else in the world, and a wide range of data and novel analytical approaches have been used, it should be recognised from the outset that any indicator on the status of priority species will be hampered by short comings in the availability of data.

2. Species List

The UK BAP list has been superseded by the biodiversity lists of the four UK countries (Section 41 of the Natural Environmental and Rural Communities (NERC) Act 2006 in England, Section 42 of the NERC Act in Wales, Northern Ireland priority species list in Northern Ireland and the Scottish biodiversity list in Scotland). As a result, there is no single list of species that represents the UK’s species of conservation priority. The criteria for inclusion in each of the four biodiversity lists are derived from those used to identify the UK BAP priority species list, most recently in 2007, but there has been some divergence in approaches, see Table 1. For example, the Scottish biodiversity list and the Northern Ireland priority species list both have criteria based on rarity alone, whereas the UK BAP criteria did not consider rarity; rare species were only listed if they were considered threatened or declining.

For the purposes of this indicator, an inclusive approach has been taken, whereby any species on one or more of the country biodiversity lists has been considered. A species only has to be included in one of the country lists to be included on the combined list. The Scottish Biodiversity list has a final criterion based on the importance of species to people, however, species designated under this criterion were not considered here. The taxonomic composition of the combined four country list is shown in Table 2.

Some countries have included a small number of taxa below the species level (i.e. sub-species) on their biodiversity lists. Such infra- specific taxa were only retained on the combined four country biodiversity list if the associated species was not included. For example, a sub-species of the willow tit (Poecile montanus) is included on the Welsh list but it is a full species on the Scottish Biodiversity list, thus on the combined list only the full species was retained.

Table 1: the biodiversity lists of the four countries of the UK

Country Number of Taxa

Criteria for species inclusion

England (S41) 943 On the 2007 UK BAP list

Hen Harrier

Northern Ireland (NI) priority species list

481 1: On the 2007 UK BAP list

2: Rapid decline of >= 2% per year

3: Decline of >=1 % per year and NI holds >= 50% of Irish, or >=20 % of UK population or Irish/UK population restricted to NI

4: Rare in NI (1-2 sites) and NI holds >=50% of Irish, or >=20% of UK population or Irish/UK population restricted to NI

5: >=20 % of a well recognised sub-species in NI

6: Irish Red data book species

7: Red list Birds of Conservation concern Ireland or UK

Scottish Biodiversity 2,090 S1:On the 2007 UK BAP list

Country Number of Taxa

Criteria for species inclusion

List

S2:International obligation

S3:Species defined as 'nationally rare' in GB/UK (<15 10km2), which are present in Scotland

S4: Species present in <= 5 km2 or sites in Scotland

S5: Decline of >= 25% in 25 years in Scotland

S6a: Endemic

S6b: Endemic subspecies if also meets another criterion

Wales (S42) 567 International importance, IUCN Global Red List or Red listed in >=50% of EU countries where data is available or other source indicating international threat or decline

International responsibility >=25% of EU/Global population in Wales and decline >=25% in 25 years in Wales

Decline in Wales >=50% in 25 years

Other for example decline and very restricted range

UK (combined four country list)

2,890

Table 2: Taxonomic breakdown of combined four country biodiversity list

Group Number of Species

Invertebrates

insect - beetle (Coleoptera) 191

insect - butterfly 25

insect - dragonfly (Odonata) 4

insect - hymenopteran 103

insect - moth 174

insect - orthopteran 6

insect - other 4

insect - riverfly 8

insect - true bug (Hemiptera) 15

insect - true fly (Diptera) 94

other Invertebrate 233

Vertebrates

Amphibian 4

Bird 127

Group Number of Species

Fish 57

marine Mammal 22

terrestrial Mammal 26

Reptile 10

Plants and fungi

Vascular plants 409

Alga 254

Stonewort 15

Lichen 546

Bryophytes 301

Fungi 262

Grand Total 2890

3. Data Sources

Robust population time series for as many species on the combined four country biodiversity list as possible were sought by the project team. The majority of these data have previously been published and many are currently used as part of the UK biodiversity indicator set. Population time series of two major types were collated, the first measuring changes in relative species abundance and the second measuring changes in relative frequency of species occurrence. The analysis underlying the time series was in general conducted by the data providers; however, the time series of frequency of species occurrence were generated by the Biological Records Centre (BRC), part of the Centre for Ecology and Hydrology. Details of these analyses and the rules for species inclusion into the data sets are given in the following sections.

3.1. Time series in relative abundance

Tables 3 and 4 provide a summary of the relative abundance datasets included in the indicator. They show the analytical methods used to generate the species time series in each dataset. Although these vary in detail, the underlying method is similar. These datasets are generated largely from data collected by national monitoring schemes. In these schemes data are collected in a robust and consistent manner and the geographical coverage is good, with statistical approaches used to correct for biases in coverage. These datasets are ideal for producing population time series for widespread species; however, in some cases the sample size is insufficient to generate time series for rarer or more range restricted species. Each scheme has a set of criteria to determine whether time series can be generated for each species and if they are sufficiently robust to be included in the published results of the scheme. Table 5 gives an overview of the quality of the data derived from each scheme. Further information about each monitoring scheme and the data analysis and results can be found in the references given at the end of this paper.

Bird time series are well documented and several data sources are available (Table 3). Some bird species are represented in more than one dataset. The order of the rows in Table 3 shows

the hierarchy used, from top to bottom, to ensure that the most appropriate and robust data for each species was included in the indicator.

The majority of species time series start around 1970 and the date of the last available update is 2011. The Rothamsted moth data starts in 1968, but to avoid over representing these time series in the overall indicator, data were only used from 1970 onwards, and the time series were expressed as a proportion of the 1970 value. Some datasets begin later than 1970, for example the butterfly time series begin in 1976. The method of incorporating this variation in time period into the indicator is discussed in the Indicator method section (4) below. Some datasets do not continue until 2010, for example, the Rothamsted moth dataset has currently only been analysed to 2007 and indices for seven bird species surveyed by periodic national surveys end at various points between 2002 and 2008. For these species where the time series did not continue until 2010, the annual estimate was held at the value of the final data point for all years from the end of the time series to 2010. Thus, the 2007 estimate in each Rothamsted moth time series was used as the estimate for 2008, 2009 and 2010.

The steep decline in many moth species has an effect on the indicator as a whole. The last moth data in the indicator is for 2007, and the final values for moth species are then held constant in the overall index until 2010. The impact of this on the assessment has been considered: if moths are excluded from the indicator the short term decrease between 2005 and 2010 is not significant, and the indicator would be assessed as ‘no change’. Over ten years, from 2000 to 2010, the indicator without the moth data would be slightly positive, but not sufficiently so to be assessed as an increase.

Table 3: Summary of the analysis methods and criteria for species selection for bird datasets

Birds Time period (Sample size)

Data Type Species selection method Analysis method

Time series used in current bird indicator - C5

Various (45 – split shown in blue below)

Unsmoothed index Various, depending on the original dataset, all those used are described below

Statutory Conservation Agency and RSPB Annual Breeding Bird Scheme (SCARRABS)

Various (7, 5)

Population estimates from two or more national surveys

These surveys are designed to be in depth surveys for a particular species and so have sufficient data to allow population trends to be robustly estimated.

Linear interpolation was used to estimate annual values for years between national surveys.

Common Bird Census/Breeding Bird Survey (BBS) joint trends;

1970-2011 (1, 28)

Smoothed index

Smoothed population time series were generated by fitting a smoothed curve to the data directly using a generalised additive model (GAM) (Fewster et al. 2000). Thus the model is: log (count) = site effect + smooth (year) where smooth year) represents a smoothing function of the year effect (BTO 2013a).

BBS 1995-2011 (4, 5)

Unsmoothed index

Data from the BBS surveys were only included for species recorded in on average over 40 BBS squares in each year of the survey period.

Unsmoothed time series are estimated using a similar procedure to the CBC/BBS joint trends described above simply without the smoothing parameter, year is taken as a factor (BTO 2013a).

Rare Breeding Birds Panel

Various, largely 1970 - 2010 (29, 1)

Annual estimate

Species where data were known to be biased were excluded (low quality data: RBBP 2010), as were those where individuals were only infrequently present in the UK (taken as species where the maximum count was 10 or less and the median was 3)

Linear interpolation was used to estimate any missing data.

Seabird Monitoring Panel (SMP) and Seabird censuses

1986-2011 (6)

Unsmoothed index

Very small colonies and colonies where counting error is known, or suspected, to exceed 5% are excluded from SMP time series. The accuracy of time series obtained using the SMP sample was assessed by comparing them with data from two complete censuses of all breeding seabirds in the UK. A time series was rejected as inaccurate where a discrepancy of more than 15% occurred between the SMP estimate and the census figure

For the majority of species a combination of SMP and census data is used. The two census estimates are used, with linear interpolation for the intervening years. The SMP time series is anchored to the 2nd census estimate and used in all subsequent years. For a small number of species the census data alone is used.

Birds Time period (Sample size)

Data Type Species selection method Analysis method

(Thompson et al. 1997).

Wetland Bird Survey (WeBS)

1970-2011 (12)

Unsmoothed index

There is a system of observer recorded quality of visit (visibility, areas missed) within WeBS, which excludes poor quality site visits. Only sites that have a good overall level of coverage are used (at least 50% of possible visits undertaken) (BTO 2013b, Maclean and Ausden 2006).

As for BBS time series

Table 4: Summary of the analysis methods and criteria for species selection for other taxonomic groups

Group Dataset and provider

Time period and Data Type

Species selection method Analysis method

Moths Rothamsted Insect Survey (Rothamsted Research)

1968-2007, TRIM annual index.

Time series were estimated for species where >500 individuals had been captured over the sampling period. Only sites that operated for a minimum of 48 weeks a year, with at least one year of data (411 sites ) were used, and all but one species were analysed using a subset of sites (214) with at least five years data (Conrad et al. 2004, 2006; Fox et al. 2013)

Site x year Log-linear Poisson regression models in TRIM (Pannekoek and van Strien 1996) were used. One species was analysed using all 411 sites to ensure model convergence, otherwise only sites with five years data were used to estimate time series. To test for biases due to site turnover linear change estimates from sites running for >=5 years (N=199) were compared with those estimated from sites running a >= 20 years (N=41) over a 35 year period from 1968-2002. The estimates are significantly correlated (r = 0.90, df = 336, p < 0.001) (Conrad et al. 2004).

Moths Butterfly Conservation (BC)

~2000-2011. TRIM annual index.

Expert opinion (Mark Parsons – Butterfly Conservation) was used to judge whether the number of sites monitored was sufficient to represent the national time series, given each species’ distribution.

Site x year Log-linear Poisson regression models in TRIM (Pannekoek and van Strien 1996) were used.

Bats National Bat Monitoring Programme (Bat Conservation Trust)

1997-2011. Unsmoothed index.

A power analysis determined that across all surveys, a sample size of 30-40 repeat sites (surveyed for more than one year) would give sufficient data to calculate robust species time series. This would provide 90% power to detect a decline of 25% over 25 years (0.1 sig. level). Borderline cases are judged based on the quality of the time series, primarily from the confidence limits (Walsh et al. 2001, Bat Conservation Trust 2013).

As BBS time series. In addition, mixed models are used to investigate factors that could influence time series (e.g. bat detector make, temperature). Over dispersion is a problem for bat detector surveys, where a single bat repeatedly flying past the observer may give rise to a large count of bat passes. Based on the results of simulations a binomial model of the proportion of observation points on each survey where the species was observed is used.

Dormice National dormouse monitoring

1995-2011. Unsmoothed index.

As BBS time series. Time series are estimated monthly. The data for June are used following advice from PTES.

scheme (PTES)

Butterflies UK Butterfly Monitoring Scheme (BRC)

1976-2011. TRIM annual index.

Indices are calculated for butterfly species that have been recorded from five or more sites per year. The wider countryside butterfly survey has only three counts during summer and requires twice as many monitored sites to achieve comparable precision to the 26-week butterfly monitoring scheme. 430 monitoring sites on average are required to achieve 80% power (5% significance level) for detecting a 25% decline in abundance over 10 years.

Site x year Log-linear Poisson regression models in TRIM (Pannekoek and van Strien 1996) are used. For years where a transect site has not been recorded, the model imputes an estimated site index that allows for the general conditions of the year in question and how favourable the site is.

Table 5: Assessment of robustness of monitoring schemes – Data quality = Red > Amber > Green

Dataset Effort Survey design Field method

Moths Rothamsted moth survey (1968-) 80 Consistent, Non-random Light trap

Butterflies Wider countryside butterfly survey (2007-) 750 Consistent, Random Transect

UK butterfly monitoring scheme (1976-) 1000 Consistent, Non- random Transect

Mammals

National Dormouse Survey (1993-) 300 Consistent, Known sites Nest box search

Breeding bird survey (1995-) 2400 Consistent, Random Transect

National Bat monitoring scheme (1997-) 1300 Consistent, Random Various, field/ roost counts

Birds Breeding bird survey (1995-) 3200 Consistent, Random Transect

Common bird census (1970-2000) 300 Consistent, Non-random Territory mapping

Seabird monitoring programme, (1986 -) seabird censuses (1969 ,85,00)

Species specific

Consistent, Non-random or Total Colony counts

Wetland bird survey (1970-) 3000 Consistent, Non-random Site counts

Rare birds breeding panel (1970-) Species specific

Some variation over time, all or most known sites

Site counts and individual re-cords

SCARRABS (1974-) Species Consistent, stratified ran- Various, tran-

specific dom sects

3.2. Time series in Frequency of Occurrence, derived from general geological recording

In addition to the time series showing changes in relative species abundance, similar time series showing changes based on general biological recording, were collated. Biological records are observations of species in a known place in space and time. Most records are made by volunteer recorders and whilst these data may be collected following a specific protocol, the majority of records in these datasets are opportunistic. The intensity of recording varies in both space and time (Isaac 2012, Isaac et al. 2013), which is a challenge for estimating robust quantitative trends. Fortunately, a range of methods now exist for producing such trends using unstructured biological records data (e.g. Szabo et al 2010, Hill 2011). In effect these methods identify long-term changes in species distributions; the term ‘frequency of occurrence’ is however technically more accurate, and is therefore used in this technical document. .

The frequency of occurrence data have been generated by the Biological Records Centre (BRC), using novel techniques for analysing biological recording data. As part of this work BRC have been using computer simulations to compare different statistical techniques for reducing the influence of biases (such as spatial or temporal variation in observer effort) in recording datasets (Isaac 2012). Analysis is ongoing and therefore robust time series were only available for a sample of taxonomic groups in time for inclusion in the indicators presented here; it is anticipated more will be available for future updates of this indicator, broadening its taxonomic scope.

The datasets included in the indicator have been generated using the ’well-sampled sites model’ (Roy et al. 2012). The input data for each species is a table of all the site visits between 1970 and 2009 for the taxonomic group in question (table 5), with data on the list length (the number of species recorded) and whether the focal species was recorded (1) or not (0). A site visit is defined as a unique combination of date and 1km2 grid cell. These data were then filtered for data quality, first removing all visits with list lengths shorter than the median for the taxonomic group in question. At the second filtering step, grid cells that had visits in less than three years were excluded. The time series for each species was then estimated from a generalised linear mixed effects model, with year as the covariate and grid cell as a random effect (following Roy et al. 2012). This approach has emerged from the simulation study as the most robust and powerful of the available methods (Isaac et al, manuscript in prep).

The annual index for each species is based on the fitted values from the well-sampled sites model for that species. Technically, these fitted values are the probability that the focal species was recorded on an average visit in the year in question. A key assumption of the well-sampled sites model is that species’ detectability has not changed over time. The relevant recording schemes were therefore consulted, and species excluded from the indicator for which this assumption is unsupportable. For example, the speckled bush cricket (Leptophyes punctatissima) was excluded because a large proportion of records come from using bat-detectors, which have only recently been adopted by the community of Orthopteran recorders. The consultation is ongoing, and there may be small changes in future years’ publication as a result.

The frequency of occurrence time series end in 2009. In order to make a direct comparison with the abundance indicator, the series were extended by one year using the same method as for the abundance time series that ended prior to 2010; the 2009 value was held over to 2010.

The following organisations contributed data for this analysis: BWARS (Bees, Wasps and Ants Recording Society), British Dragonfly Society, Butterfly Conservation, andHoverfly Recording Scheme, and the Orthoptera Recording Scheme.

4. Indicator Methods

The two types of population data, abundance and frequency of occurrence were first investigated separately and then the feasibility of combining these two datasets was investigated. The methods of indicator creation were the same regardless of the dataset under consideration. Table 6 gives a summary of the relationship

between the number of species on the combined four country biodiversity list (FCL) and the number of these for which population time series are available.

As far as possible, previously published methods of indicator creation were used, both because these are well-established, are likely to have undergone peer review and allow comparison of this indicator with existing species indicators for birds (C5), butterflies (C6) and bats (C8). These methods are described briefly below and references are given for further information.

Table 6: Summary of species time series included in the Species Indicator

 Group Data Type Species with data

Species on FCL

Species on FCL with data and meeting criteria

Birds Abundance 198 126 99

Butterflies 56 26 21

Mammals 13 26 11

Moths 355 174 79

Total (Abundance) 210

Moths Frequency of Occurrence 

743 174 105 (overlap of 72 with Abundance dataset)

Ants 30 10 2

Bees 198 60 37

Wasps 201 33 23

Hoverflies 209 29 2

Dragonflies 39 4 2

Grasshoppers 31 6 3

Total (Frequency of Occurrence) 174

Total 312 (384 – 72 overlap)

The majority of species time series had values estimated for each year. In the few cases where a species year combination was missing, these values were estimated using log-linear interpolation (Collen et al. 2008). Time series were not extrapolated before the first year or after the last. Where time series ended prior to 2010 they were extended by holding the final data value constant in all subsequent years. Since the indicator is focussed on threatened species some of these species are rare and a few time series contained zero counts for one or more years. This was largely in the Rare Breeding Birds Panel data. As the composite indicator is calculated using the geometric mean it is not possible to include zero values. This issue was addressed by adding 1% of the average value of the time series to the whole series of those species’ time series containing zeros (Loh et al. 2005).

Each time series was expressed as a proportion of the first year of the time series, so that the first year equals one hundred. Extremely large or small index values can have a disproportionate influence on composite indicators. Following the methods used in the current wild bird index (C5); any index value greater than 10000 or less than one was set to these values until the index dropped below 10000 again or above one (Noble et al. 2004). One species had a time series that went above 10000 and eight species had time series that dropped below one, these are specified in the species list in Appendix 1.

The period 1970 to 2010 represents the core period covered by the majority of species time series (Figure 1). Fewer than half of the species time series begin before or extend beyond this period and to include these outlying years would mean that the index values estimated for these years would largely reflect data availability rather than biological change.

Each species in the indicator was weighted equally. When creating a species indicator weighting may be used to try to address biases in a dataset, for example if one taxonomic group is represented by far more species than another, the latter could be given a higher weight so that both taxonomic groups contribute equally to the overall indicator. Complicated weighting can, however, make the meaning and communication of the indicator less transparent. Groups with many species on the FCL could be considered more threatened than others and therefore should contribute more to the overall indicator. Although there was some variation between taxonomic groups in the proportion of species on the list for which data were available, this proportion was substantial for all groups where at least some data were available. The main bias on the data is that some taxonomic groups are not represented at all, which cannot be addressed by weighting. For this reason, and to ensure clarity of communication, equal weighting was used.

Figure 1: Number of species contributing to the headline indicator in each year, 1970 to 2010

To create the composite index for a group (by data type or taxonomy) or overall, the geometric mean was calculated from the species time series data (Figure 2). Different species time series had different start dates. This was taken into consideration with the method currently used for the wild bird index (indicator C5); for species time series entering the indicator after the first year, their first year is set to the geometric mean of those species time series already in the indicator. Confidence intervals for each composite indicator were created using bootstrapping (Buckland 2005, Freeman et al. 2001); in each iteration (n = 100) a random sample of species were selected with replication and the geometric mean calculated.

4.1 Headline Indicator - C4ai

The headline indicator (C4ai) was generated by combining 210 time series charting changes in relative species abundance using the methods described in the preceding section. In addition, bars showing the proportion of species showing increases or decreases (of any magnitude, and with no consideration of statistical

significance) have been provided. These cover two time periods – ‘long-term’, from 1970 to 2010, and ‘short-term’, from 2005 to 2010.

Figure 2: Change in the relative abundance of priority species in the UK, 1970 to 2010

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4.1.2 Assessment of change – headline indicator

The assessment is based on a test of statistical significance by comparing the change and 95 per cent confidence intervals between first and last date of the long and short term changes respectively. The overall indicator shows a consistent downward trajectory over its 40 years duration. The final value of the indicator in 2010 is 42 per cent (95% confidence intervals (CI): 30, 50) suggesting that on average those priority species represented in the indicator have declined by more than a half since 1970. To calculate the short-term trend, a change statistic for the 2005 to 2010 period was calculated and the data re-sampled to provide confidence intervals on that change statistic (not shown in Figure 2), and the proportional change for each species over the most recent five and ten years was calculated. The geometric mean of the species level change was calculated and 95% confidence intervals were estimated using bootstrapping. In 2010 the relative abundance of the 210 species included in the indicator had declined by seven per cent relative to their 2005 levels (95% CI: 87,99). The equivalent change between 2000 and 2010 was a five per cent decline (95% CI: 87, 104).

If the confidence interval is entirely below 100 the time series would be assessed as decreasing, if it was entirely above 100 the indicator would be assessed as increasing, if the confidence interval spanned 100 the indicator would be assessed as no significant change. Therefore, both the long-term change (1970 to 2010) and the short-term change (2005 to 2010) were assessed as decreases. There was no change in the indicator between 2000 and 2010.

The steep decline in many moth species has an effect on the indicator as a whole. The last moth data in the indicator is for 2007, and the final values for moth species are then held constant in the overall index until 2010. The impact of this on the assessment has been considered: if moths are excluded from the indicator the short term decrease between 2005 and 2010 is not significant, and the indicator would be assessed as ‘no change’. Over ten years, from 2000 to 2010, the indicator without the moth data would be slightly positive, but not sufficiently so to be assessed as an increase.

This assessment of change over time is currently based upon unsmoothed annual estimates of relative abundance. This means that the percentage change over time can vary substantially depending on the time period assessed. One way to reduce this variation is to make the assessment based on smoothed time series based on generalised additive models (Freeman et al. 2001). These dampen the inter-annual variation in the time series and thus aid the interpretation of important patterns of change. At present this type of information is not available for all the species in the indicator presented here, however, it is hoped it will be possible to work towards generating these data and using this methodology in future iterations of the indicator.

4.2 Change in frequency of occurrence time series

An equivalent indicator was created using the 174 time series of changes in frequency of species occurrence (Figure 3).

Figure 3: Change in priority species (frequency of occurrence time series), with 95 per cent confidence intervals, 1970 to 2010

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This measure also shows a downward trajectory over its 40 years duration. The final value of the indicator in 2010 is 49 per cent (95% CI 39, 61) suggesting that on average the frequency of occurrence of those priority species represented in the indicator has declined by around a half since 1970. At present these time series are estimated assuming a monotonic rate of change over the full 40 year period, which means it is not possible to disentangle short and long-term change.

4.3 Comparing and combining the two data types

Both types of data give a similar trajectory of change (Figure 4). Depending on the life history, frequency and distribution of a species either type of data may be the most appropriate way to measure changing species status and time series, as each data type for a single species may tell a different story. If these two types of data were combined it would allow measures of change in status for as many species, over as broad a spectrum of taxonomic groups as possible. It is the direction of time series that is most important here, rather than the precise slope of the indicator. Pooling the two types of data would allow provision of a clear, simple measure of change, which is vital as the prime purpose of biodiversity indicators is as communication tools. If the indicator is declining the status of threatened species is, on average, continuing to degrade, and if the indicator is stable or increasing species status is, on average, stabilising or improving. An indicator based on both the time series of relative abundance and those of frequency of species occurrence (312 species) is shown in Figure 5. The only group for which there are time series in both relative abundance and frequency of species occurrence is the moths; 72 species have time series in both data types. Where both abundance and frequency of occurrence data are available abundance trends were used in preference to frequency of occurrence trends.

Figure 4: Change in priority species – comparing Abundance and Frequency of Occurrence data, 1970 to 2010

Note: the number of species included in each line is shown in brackets.

Figure 5: Change in priority species - time series with both data types combined, 1970 to 2010.

Note: the number of species included is shown in brackets.

4.4 Treatment of species with time series in both abundance and frequency of occurrence

For the species where a time series in abundance and a time series in frequency of occurrence were both available the abundance date were used in the composite indicator. In order to investigate the influence of this decision on the indicator two further indices for this group of species were estimated: first, a measure based on the abundance time series for each species and second, a measure using the frequency of occurrence time series for each species. Figure 6 shows a strong correlation between the annual index values of these two indicators, showing they exhibit a similar pattern of change. The frequency of occurrence index is somewhat higher over the whole time period assessed than the abundance index. This is similar to the pattern shown in Figure 4 comparing the overall time series for the two data types. Figure 7 shows a comparison between the abundance indicator (Figure 2) and the same indicator but giving precedence to the frequency of occurrence data for those species where both data types were available. There is a strong correlation between the two options, with the latter option exhibiting a shallower decline over time.

Figure 6: Comparison between the annual index values for measures derived from abundance time series and frequency of occurrence time series for those moth species where both are available.

Figure 7: Indicator giving precedence to either abundance or frequency of occurrence time series where duplication occurs, 1970 to 2010.

4.5 Change in priority species by taxonomic group

The headline indicator (Figure 2) masks variation within and between taxonomic groups. Figures 8 and 9 show indicators for each taxonomic group separately. These were generated using the same methods as the overall indicator.

Figure 8: Change in relative species abundance, by taxonomic group, 1970 to 2010

0

20

40

60

80

100

120

140

160

1970 1975 1980 1985 1990 1995 2000 2005 2010

Inde

x (1

970

= 10

0)B

utte

rflie

s (1

976

= 10

0) M

amm

als

(199

3 =

100)

Mammals (11)

Birds (99)

Butterflies (21)

Moths (79)

United Kingdom

Note: the number of species included in each line is shown in brackets.

This index for birds has remained roughly stable since the 1970s. There are several possible explanations for this. Birds have benefited from more investment in their conservation than other groups and, as a result, some species are increasing due to this. This includes some species increasing rapidly from small numbers, like the marsh harrier (Circus aeruginosus) and the red kite (Milvus milvus) as well as species that have benefited from changes in legislation, like geese which are now protected from hunting. Additionally, the definition of priority species, as provided by the four Country lists, includes all species for which there is specific international obligation for conservation action (owing to the use of this as a criterion for the Scottish priority list). This has resulted in a large number of waterbird species within the indicator, many of which occur in the UK as wintering populations and which have shown substantial increases since the 1970s. The overall stable time series for birds masks some species which are still rapidly declining; for example, turtle dove (Streptopelia turtur) has declined by 97% over the time period assessed.

Mammals are mainly represented here by bats and the composite mammal time series closely resembles indicator C8 (mammals of the wider countryside (bats)). The steep initial increase in the index is driven by an increase in mountain hare (Lepus timidus) and Natterer’s bat (Myotis nattereri). Although the species composition is somewhat different, the butterfly composite index resembles the Habitat Specialist line of indicator C6i (butterflies of the wider countryside), with the steep initial drop in the indicator thought to be attributable to a severe drought in 1976.

Similar variation is seen between composite time series for taxonomic groups with frequency of occurrence data (Figure 9). The majority of groups show on average a decline over the period assessed. Bees, wasps

and ants have been subject to fewer declines on average, however, within this group bee species are on average declining whereas wasps are on average increasing.

Figure 9: Change by taxonomic group, frequency of occurrence datasets, 1970 to 2010

0

20

40

60

80

100

120

1970 1975 1980 1985 1990 1995 2000 2005 2010

Inde

x (1

970

= 10

0)

Bees, wasps and ants (62)

Moths (105)

Other Insects (7)

United Kingdom

Note: the number of species included in each line is shown in brackets.

5 Future developments

The indicator of relative abundance will be refined in future as further data become available. The basis of assessment, particularly for the short-term change, may also be refined, for example, by investigating statistical smoothing to detect underlying trends and reduce the impact of particularly high or low values at the start or end of a time series.

It is anticipated that the general approach of the indicator developed for reporting in 2013 will be retained into the future, however, it is likely that the work will be refined and expanded. Work is currently being undertaken to derive trends from distribution data (general biological recording) for more species using data collected by national recording schemes. Time series should become available for a larger suite of taxonomic groups and therefore more species should be included in the indicator in future years, improving representativity. In addition, analysis will be undertaken to seek to understand the impact of different priority-listing criteria in the UK’s four nations. At present the occurrence time series assume monotonic change over the 40 year time period, in the future it is hoped to be able to assess change over shorter time periods, perhaps by decades.

As the sample size increases it should become possible to investigate other ways to break down the indicator; possibilities include, by countries, upland/lowland, ecosystems/habitats, traits/life history strategies and or by trophic level.

Regardless of advances in statistical techniques there are species on the priority species lists for which monitoring data are sparse. This is for a variety of reasons, including species rarity, difficulty of detection, or those species for which monitoring methods are unreliable or unavailable. In order for the indicator to be representative of all types of species on the biodiversity lists, a method of assessing the changing status of a sample of these remaining data-poor species will need to be considered.

References

Bat Conservation Trust (2013) http://www.bats.org.uk/pages/detecting_population_change.html.

British Trust for Ornithology (2013a) http://www.bto.org/about-birds/birdtrends/2012/methods/statistical-methods-alerts.

British Trust for Ornithology (2013b) http://www.bto.org/sites/default/files/u18/downloads/publications/wituk_methods_0910.pdf.

Buckland, S.T., Magurran, A.E., Green, R.E. and Fewster, R.M. (2005) Monitoring change in biodiversity through composite indices. Philosophical Transactions of the Royal Society of London. Series B, 360, 243–254.

Collen, B., Loh, J., Whitmee, S., McRae, L., Amin, R. and Baillie, J. (2008) Monitoring Change in Vertebrate Abundance: the Living Planet Index. Conservation Biology, 23, 317-327.

Conrad, K.F.,Woiwod, I.P., Parsons, M., Fox, R., Warren, M.S. (2004) Long-term population trends in widespread British moths, Journal of Insect Conservation, 8: 119–136.

Conrad, K.F., Warren, M.S., Fox, R., Parsons, M.S., Woiwod, I.P. (2006) Rapid declines of common, widespread British moths provide evidence of an insect biodiversity crisis, Biological Conservation, 132: 279-291.

Freeman, S.N., Baillie, S.R. and Gregory, R.D. (2001) Statistical analysis of an indicator of population trends in farmland birds, BTO Research Report no. 251, Thetford. http://www.bto.org/sites/default/files/u196/downloads/rr251.pdf.

Fewster, R.M., Buckland, S.T., Siriwardena, G.M., Baillie, S.R. and Wilson, J.D (2000). Analysis of population trends for farmland birds using generalized additive models. Ecology 81: 1970-1984

Fox, R., Parsons, M.S., Chapman, J.W., Woiwod, I.P., Warren, M.S. and Brooks, D.R. (2013) The State of Britain’s Larger Moths 2013. Butterfly Conservation and Rothamsted Research, Wareham, Dorset, UK.

Hill, M.H., (2011) Local frequency as a key to interpreting species occurrence data when recording effort is not known. Methods in Ecology and Evolution, 3 (1), 195-205.

Isaac, N. J., B. (2012) Extracting trends from biological recording data. National Biodiversity Network Conference. London. doi:10.6084/m9.figshare.428369.

Isaac, N. J. B., August, T. A., Harrower, C. and Roy, D.B. (2013) Trends in the Distribution of UK native species 1970-2010. Preliminary report to JNCC. JNCC Report No 488. http://jncc.defra.gov.uk/pdf/488_Web.pdf .

Loh, J., Green, R. E., Ricketts, T., Lamoreux, J., Jenkins, M., Kapos, V. and Randers, J. (2005) The Living Planet Index: using species population time series to track trends in biodiversity. Philisophical Transactions of the Royal Society B 360, 289-295.)

Maclean, I.M.D. and Austin, G.E. 2006. Wetland Bird Survey Alerts 2004/05: Changes in numbers of wintering waterbirds in the Constituent Countries of the United Kingdom, Special Protection Areas (SPAs) and Sites of Special Scientific Interest (SSSIs). BTO Research Report 458, British Trust for Ornithology, Thetford.

Noble, D. G., Newson, S. E. and Gregory, R. D. (2004) Approaches to dealing with disappearing and invasive species in the UK’s indicators of wild bird populations. A report by the BTO and RSPB under contract to Defra (Wild Bird Indicators).

Pannekoek,. J., and van Strien, A. J. ( 1996) TRIM – trends and indices for monitoring data. Research paper no. 9634. Statistics Netherlands.

Roy, H. E., Adriaens, T., Isaac, N. J. B., Kenis, M., Martin, G. S., Brown, P. M. J. and Hautier, L., et al. (2012) Invasive alien predator causes rapid declines of native European ladybirds. Diversity and Distributions, 18, 717-725.

Szabo, J.K., Vesk, P.A., Baxter, P.W.J., and Possingham, H.P (2010) Regional avian species declines estimated from volunteer-collected long-term data using List Length Analysis. Ecological Applications, 20, 2157–2169.

Thompson, KR, Brindley, E and Heubeck, M (1997) Seabird numbers and breeding success in Britain and Ireland, 1996. JNCC, Peterborough, (UK Nature Conservation No. 21).

van Strien et al. (1997) The statistical power of two butterfly monitoring schemes, JAE, 34: 817-

Walsh, A., et al. (2001) The UK's National Bat Monitoring Programme - Final Report 2001, the Bat Conservation Trust, London. http://www.bats.org.uk/pages/nbmp_reports.html.

Musgrove, A. J., Austin, G.E., Hearn, R.D., Holt, C.A., Stroud, D.A., Wotton, S.R, (2011), Overwinter population estimates of British waterbirds, British Birds, 104: 364–397.

Appendix 1 – Species List

Scientific_Name Common_Name Group Datatype England S41

Wales S42

Scotland biodiversity

list

NI priority species

list

Capped at.10000

Halted at 1

Accipiter gentilis Northern goshawk birds abundance N N N Y NA NA

Acrocephalus palustris marsh warbler birds abundance Y N N N NA NAAcrocephalus scirpaceus reed warbler birds abundance N N Y N NA NA

Alauda arvensis skylark birds abundance Y Y Y Y NA NA

Alcedo atthis kingfisher birds abundance N N Y N NA NA

Anas acuta pintail birds abundance N N N Y NA NA

Anas clypeata shoveler birds abundance N N N Y NA NA

Anas querquedula garganey birds abundance N N Y Y NA NAAnser albifrons subsp. albifrons

European white-fronted goose birds abundance Y N Y N NA NA

Anser albifrons subsp. flavirostris

Greenland white-fronted goose birds abundance N Y Y Y NA NA

Anthus trivialis free pipit birds abundance Y Y Y Y NA NA

Apus apus swift birds abundance N N Y Y NA NA

Aquila chrysaetos golden eagle birds abundance N N Y Y NA NA

Aythya ferina pochard birds abundance N N Y Y NA NA

Aythya fuligula tufted duck birds abundance N N N Y NA NA

Botaurus stellaris great bittern birds abundance Y Y Y Y NA NABranta bernicla subsp. bernicla

dark-bellied brent goose birds abundance Y Y N N NA NA

Branta bernicla subsp. Hrota

Nearctic light-bel-lied brent goose birds abundance N N N Y NA NA

Branta leucopsisSvalbard barnacle goose birds abundance N N Y N NA NA

Bucephala clangula goldeneye birds abundance N N N Y NA NA

Burhinus oedicnemus stone-curlew birds abundance Y N N N NA NA

Calidris alpina dunlin birds abundance N N Y Y NA NA

Calidris canutus knot birds abundance N N N Y NA NA

Caprimulgus europaeus nightjar birds abundance Y Y Y Y NA NA

Carduelis cabaret lesser redpoll birds abundance Y Y Y Y NA NA

Carduelis cannabina linnet birds abundance Y Y Y Y NA NA

Carduelis spinus siskin birds abundance N N Y N NA NA

Charadrius hiaticula ringed plover birds abundance N Y N N NA NA

Circus aeruginosus marsh harrier birds abundance N N Y N Y NA

Circus cyaneus hen harrier birds abundance Y Y Y Y NA NA

Corvus cornix hooded crow birds abundance N N Y N NA NA

Coturnix coturnix quail birds abundance N N N Y NA NA

Crex crex corncrake birds abundance Y Y Y Y NA NA

Cuculus canorus cuckoo birds abundance Y Y Y Y NA NA

Cygnus columbianus Bewick's swan birds abundance Y Y Y Y NA NA

Cygnus cygnus whooper swan birds abundance N N Y Y NA NADendrocopos minor subsp. comminutus

lesser spotted woodpecker birds abundance Y Y N N NA NA

Emberiza calandra corn bunting birds abundance Y Y Y N NA NA

Emberiza cirlus cirl bunting birds abundance Y N N N NA NA

Emberiza citrinella yellowhammer birds abundance Y Y Y Y NA NA

Emberiza schoeniclus reed bunting birds abundance Y Y Y Y NA NA

Falco columbarius merlin birds abundance N N Y N NA NA

Falco peregrinus peregrine falcon birds abundance N N Y N NA NA

Scientific_Name Common_Name Group Datatype England S41

Wales S42

Scotland biodiversity

list

NI priority species

list

Capped at.10000

Halted at 1

Falco subbuteo hobby birds abundance N N Y N NA NA

Falco tinnunculus kestrel birds abundance N Y Y N NA NA

Ficedula hypoleuca pied flycatcher birds abundance N Y N N NA NA

Gavia arctica black-throated diver birds abundance N N Y Y NA NA

Gavia stellata red-throated Diver birds abundance N N Y N NA NA

Haliaeetus albicilla white-tailed eagle birds abundance N N Y Y NA NA

Jynx torquilla wryneck birds abundance N N Y N NA NA

Lagopus lagopus red grouse birds abundance Y Y Y Y NA NA

Lanius collurio red-backed shrike birds abundance N Y Y N NA Y

Larus argentatus herring gull birds abundance Y Y Y Y NA NA

Limosa lapponica bar-tailed godwit birds abundance N Y Y N NA NA

Limosa limosa black-tailed godwit birds abundance Y N Y Y NA NA

Locustella luscinioides Savi's warbler birds abundance Y N N N NA NA

Locustella naeviagrasshopper Warbler birds abundance Y Y Y Y NA NA

Lullula arborea woodlark birds abundance Y Y N N NA NA

Melanitta nigra common scoter birds abundance Y Y Y Y NA NA

Milvus milvus red kite birds abundance N N Y N NA NA

Motacilla flava yellow wagtail birds abundance Y Y Y Y NA NA

Muscicapa striata spotted flycatcher birds abundance Y Y Y Y NA NA

Numenius arquata curlew birds abundance Y Y Y Y NA NA

Pandion haliaetus osprey birds abundance N N Y N NA NA

Panurus biarmicus bearded tit birds abundance N N Y N NA NA

Passer domesticus house sparrow birds abundance Y Y Y Y NA NA

Passer montanus tree sparrow birds abundance Y Y Y Y NA NA

Perdix perdix grey partridge birds abundance Y Y Y N NA NA

Pernis apivorus honey buzzard birds abundance N N Y N NA NA

Phalaropus lobatusred-necked phalarope birds abundance N N Y Y NA NA

Philomachus pugnax ruff birds abundance N N Y N NA NA

Phylloscopus sibilatrix wood warbler birds abundance Y Y Y Y NA NA

Pluvialis apricaria golden plover birds abundance N Y Y Y NA NA

Podiceps auritus slavonian grebe birds abundance N N Y N NA NA

Podiceps nigricollis black-necked grebe birds abundance N N Y Y NA NA

Poecile montanus willow tit birds abundance Y Y Y N NA NAPoecile palustris subsp. palustris/dresseri marsh tit birds abundance Y Y Y N NA NA

Porzana porzana spotted crake birds abundance N N Y N NA NA

Prunella modularis dunnock birds abundance Y Y Y Y NA NA

Pyrrhocorax pyrrhocorax chough birds abundance N Y Y Y NA NA

Pyrrhula pyrrhula bullfinch birds abundance Y Y Y Y NA NA

Scolopax rusticola woodcock birds abundance N N Y N NA NA

Stercorarius parasiticus Arctic skua birds abundance N N Y Y NA NA

Sterna dougallii roseate tern birds abundance Y Y Y Y NA NA

Sterna hirundo common tern birds abundance N N Y N NA NA

Sterna paradisaea Arctic tern birds abundance N N Y N NA NA

Sterna sandvicensis sandwich tern birds abundance N N Y N NA NA

Sternula albifrons little tern birds abundance N N Y Y NA NA

Streptopelia turtur turtle dove birds abundance Y Y Y Y NA NA

Sturnus vulgaris starling birds abundance Y Y Y Y NA NA

Scientific_Name Common_Name Group Datatype England S41

Wales S42

Scotland biodiversity

list

NI priority species

list

Capped at.10000

Halted at 1

Tetrao tetrix black grouse birds abundance Y Y Y N NA NA

Tetrao urogallus capercaillie birds abundance N N Y N NA NA

Tringa glareola wood sandpiper birds abundance N N Y N NA NA

Tringa totanus redshank birds abundance N N N Y NA NATroglodytes troglodytes subsp. fridariensis Fair Isle wren birds abundance N N Y N NA NA

Turdus iliacus redwing birds abundance N N Y Y NA NA

Turdus philomelos song thrush birds abundance Y Y Y Y NA NA

Turdus pilaris fieldfare birds abundance N N N Y NA Y

Vanellus vanellus lapwing birds abundance Y Y Y Y NA NA

Argynnis adippe high brown fritillary butterfly abundance Y Y N N NA NA

Aricia artaxerxesNorthern brown ar-gus butterfly abundance Y N Y N NA NA

Boloria euphrosynepearl-bordered fritil-lary butterfly abundance Y Y Y N NA NA

Boloria selenesmall pearl-bordered fritillary butterfly abundance Y Y Y N NA NA

Coenonympha pamphilus small heath butterfly abundance Y Y Y Y NA NA

Coenonympha tullia large heath butterfly abundance Y Y Y Y NA NA

Cupido minimus small blue butterfly abundance Y Y Y Y NA NA

Erynnis tages dingy skipper butterfly abundance Y Y Y Y NA NA

Euphydryas aurinia marsh fritillary butterfly abundance Y Y N Y NA NA

Hamearis lucinaDuke of Burgundy fritillary butterfly abundance Y N N N NA NA

Hipparchia semele grayling butterfly abundance Y Y Y Y NA NA

Lasiommata megera wall brown butterfly abundance Y Y Y Y NA NA

Leptidea sinapis wood white butterfly abundance Y Y N N NA NA

Limenitis camilla white admiral butterfly abundance Y Y N N NA NA

Maculinea arion large blue butterfly abundance Y N N N NA NA

Melitaea athalia heath fritillary butterfly abundance Y N N N NA NA

Plebejus argus silver-studded blue butterfly abundance Y Y N N NA NA

Pyrgus malvae grizzled skipper butterfly abundance Y Y N N NA NA

Satyrium w-albumwhite-letter hair-streak butterfly abundance Y Y N N NA NA

Thecla betulae brown hairstreak butterfly abundance Y Y N N NA NA

Thymelicus acteon Lulworth skipper butterfly abundance Y N N N NA NA

Ammophila sabulosared banded sand wasp bwa

frequency of occurrence N N Y N NA NA

Ancistrocerus parietum wall mason wasp bwafrequency of occurrence N N Y N NA NA

Andrena cineraria grey mining bee bwafrequency of occurrence N N Y N NA NA

Andrena coitana a bee bwafrequency of occurrence N N N Y NA NA

Andrena denticulata a bee bwafrequency of occurrence N N N Y NA NA

Andrena fuscipes a bee bwafrequency of occurrence N N N Y NA NA

Andrena helvola a mining bee bwafrequency of occurrence N N Y N NA NA

Andrena marginata a mining bee bwafrequency of occurrence N N Y N NA NA

Andrena nigroaenea a bee bwafrequency of occurrence N N N Y NA NA

Andrena praecox a bee bwafrequency of occurrence N N N Y NA NA

Andrena ruficrus a mining bee bwafrequency of occurrence N N Y N NA NA

Anoplius concinnusa spider-hunting wasp bwa

frequency of occurrence N N Y N NA NA

Scientific_Name Common_Name Group Datatype England S41

Wales S42

Scotland biodiversity

list

NI priority species

list

Capped at.10000

Halted at 1

Anthidium manicatum wool-carder bee bwafrequency of occurrence N N Y N NA NA

Anthophora furcatafork tailed flower bee bwa

frequency of occurrence N N Y N NA NA

Bombus humilisbrown-banded carder-bee bwa

frequency of occurrence Y Y N N NA NA

Bombus muscorum moss carder bee bwafrequency of occurrence Y Y Y Y NA NA

Bombus ruderariusred-shanked carder-bee bwa

frequency of occurrence Y Y Y N NA NA

Cerceris quadricincta a wasp bwafrequency of occurrence Y N N N NA NA

Cerceris quinquefasciata a wasp bwafrequency of occurrence Y N N N NA NA

Ceropales maculataa spider-hunting wasp bwa

frequency of occurrence N N Y N NA NA

Colletes daviesanus a bee bwafrequency of occurrence N N Y N NA NA

Colletes fodiens a bee bwafrequency of occurrence N N Y N NA NA

Crabro peltarius a solitary wasp bwafrequency of occurrence N N Y N NA NA

Crossocerus megaceph-alus a digger wasp bwa

frequency of occurrence N N Y N NA NA

Crossocerus quad-rimaculatus

4-spotted digger wasp bwa

frequency of occurrence N N Y N NA NA

Diodontus tristismelancholy black wasp bwa

frequency of occurrence N N Y N NA NA

Dipogon subintermediusa spider-hunting wasp bwa

frequency of occurrence N N Y N NA NA

Dipogon variegatusa spider-hunting wasp bwa

frequency of occurrence N N Y N NA NA

Ectemnius cephalotes a digger wasp bwafrequency of occurrence N N Y N NA NA

Ectemnius continuus a digger wasp bwafrequency of occurrence N N Y N NA NA

Epeolus variegatus a cuckoo bee bwafrequency of occurrence N N Y N NA NA

Eucera longicornis long-horned bee bwafrequency of occurrence Y Y N N NA NA

Evagetes crassicornisa spider-hunting wasp bwa

frequency of occurrence N N Y N NA NA

Formica aquilonia Scottish wood ant bwafrequency of occurrence N N N Y NA NA

Formica fusca negro ant bwafrequency of occurrence N N Y N NA NA

Hedychridium ardens a ruby-tailed wasp bwafrequency of occurrence N N Y N NA NA

Hylaeus brevicornis a bee bwafrequency of occurrence N N Y Y NA NA

Hylaeus hyalinatus a bee bwafrequency of occurrence N N N Y NA NA

Lasioglossum angusti-ceps a bee bwa

frequency of occurrence Y N N N NA Y

Lasioglossum fulvicorne a mining bee bwafrequency of occurrence N N Y N NA NA

Lasioglossum nitidiuscu-lum a bee bwa

frequency of occurrence N N N Y NA NA

Lasioglossum rufitarse a solitary bee bwafrequency of occurrence N N N Y NA NA

Lasioglossum smeath-manellum a mining bee bwa

frequency of occurrence N N Y N NA NA

Lasioglossum villosulum shaggy mining bee bwafrequency of occurrence N N Y N NA NA

Lindenius albilabris a digger wasp bwafrequency of occurrence N N Y N NA NA

Mutilla europaea large velvet ant bwafrequency of occurrence N N Y N NA NA

Nomada errans a bee bwafrequency of occurrence Y N N N NA Y

Nomada fabricianaFabricius' nomad bee bwa

frequency of occurrence N N Y N NA NA

Nomada goodeniana a bee bwa frequency of N N N Y NA NA

Scientific_Name Common_Name Group Datatype England S41

Wales S42

Scotland biodiversity

list

NI priority species

list

Capped at.10000

Halted at 1

occurrence

Nomada leucophthalma a nomad bee bwafrequency of occurrence N N Y N NA NA

Nomada obtusifrons a nomad bee bwafrequency of occurrence N N Y N NA NA

Nomada striata a bee bwafrequency of occurrence N N N Y NA NA

Odynerus melanoceph-alus a mason-wasp bwa

frequency of occurrence Y Y N N NA NA

Osmia aurulentagold-fringed mason bee bwa

frequency of occurrence N N Y N NA NA

Oxybelus uniglumiscommon spiny dig-ger wasp bwa

frequency of occurrence N N Y N NA NA

Pompilus cinereus leaden spider wasp bwafrequency of occurrence N N Y N NA NA

Priocnemis schioedteia spider-hunting wasp bwa

frequency of occurrence N N Y N NA NA

Sphecodes ferruginatus a bee bwafrequency of occurrence N N N Y NA NA

Sphecodes gibbus a bee bwafrequency of occurrence N N Y Y NA NA

Sphecodes pellucidus a solitary bee bwafrequency of occurrence N N N Y NA NA

Stelis punctulatissima a cuckoo bee bwafrequency of occurrence N N Y N NA NA

Tachysphex pompili-formis

a spider-hunting wasp bwa

frequency of occurrence N N Y N NA NA

Lepus europaeus brown hare mammals abundance Y Y Y N NA NA

Lepus timidus mountain hare mammals abundance Y N Y Y NA NAMuscardinus avel-lanarius dormouse mammals abundance Y Y N N NA NA

Myotis daubentonii Daubenton's bat mammals abundance N N Y N NA NA

Myotis nattereri Natterer's bat mammals abundance N N Y N NA NA

Nyctalus noctula noctule mammals abundance Y Y Y N NA NA

Pipistrellus pipistrellus pipistrelle bat mammals abundance N Y Y N NA NA

Pipistrellus pygmaeus soprano pipistrelle mammals abundance Y Y Y Y NA NA

Plecotus auritusbrown long-eared bat mammals abundance Y Y Y Y NA NA

Rhinolophus fer-rumequinum

greater horseshoe bat mammals abundance Y Y N N NA NA

Rhinolophus hippos-ideros

lesser horseshoe bat mammals abundance Y Y N N NA NA

Coleophora tricolorbasil thyme case-bearer moths abundance Y N N N NA NA

Eustroma reticulatum netted carpet moths abundance Y Y N N NA NAHydraecia osseola subsp. hucherardi marsh mallow moths abundance Y N N N NA NAIdaea ochrata subsp. cantiata bright wave moths abundance Y N N N NA NAPyropteron chrysidi-formis fiery clearwing moths abundance Y N N N NA NA

Siona lineata black-veined moth moths abundance Y N N N NA NA

Thalera fimbrialis sussex emerald moths abundance Y N N N NA NA

Acronicta psi grey dagger moths both Y Y Y Y NA NA

Acronicta rumicis knot grass moths both Y Y Y Y NA NA

Agrochola helvola flounced chestnut moths both Y Y Y Y NA NA

Agrochola litura brown-spot pinion moths both Y Y Y Y NA NA

Agrochola lychnidis beaded chestnut moths both Y Y Y Y NA NA

Allophyes oxyacanthaegreen-brindled crescent moths both Y Y Y Y NA NA

Amphipoea oculea ear moth moths both Y Y Y Y NA NA

Amphipyra tragopoginis mouse moth moths both Y Y Y Y NA NA

Apamea anceps large nutmeg moths both Y Y Y N NA NA

Scientific_Name Common_Name Group Datatype England S41

Wales S42

Scotland biodiversity

list

NI priority species

list

Capped at.10000

Halted at 1

Apamea remissa dusky brocade moths both Y Y Y Y NA NA

Arctia caja garden tiger moths both Y Y Y Y NA NA

Asteroscopus sphinx the sprawler moths both Y Y N Y NA NA

Atethmia centragocentre-barred sal-low moths both Y Y Y Y NA NA

Blepharita adusta dark brocade moths both Y Y Y Y NA NA

Brachylomia viminalis minor shoulder-knot moths both Y Y Y Y NA NA

Caradrina morpheus mottled rustic moths both Y Y Y Y NA NA

Celaena haworthii Haworth's minor moths both Y Y Y Y NA NA

Celaena leucostigma the crescent moths both Y Y Y Y NA NA

Chesias legatella the streak moths both Y Y Y Y NA NA

Chesias rufata broom-tip moths both Y Y Y N NA NA

Chiasmia clathrata latticed heath moths both Y Y Y Y NA NA

Cymatophorima diluta oak lutestring moths both Y Y Y N NA NA

Dasypolia templi brindled ochre moths both Y Y Y Y NA NA

Diarsia rubi small square-spot moths both Y Y Y Y NA NA

Diloba caeruleocephala figure of eight moths both Y Y Y Y NA NA

Ecliptopera silaceata small phoenix moths both Y Y Y Y NA NA

Ennomos erosaria September thorn moths both Y Y Y N NA NA

Ennomos fuscantaria dusky thorn moths both Y Y N N NA NA

Ennomos quercinaria August thorn moths both Y Y Y Y NA NA

Entephria caesiatagrey mountain car-pet moths both Y Y Y Y NA NA

Epirrhoe galiata galium carpet moths both Y Y Y Y NA NA

Eugnorisma glareosa autumnal rustic moths both Y Y Y Y NA NA

Eulithis mellinata the spinach moths both Y Y Y N NA NA

Euxoa nigricans garden dart moths both Y Y Y Y NA NA

Euxoa tritici white-line dart moths both Y Y Y N NA NA

Graphiphora augur double dart moths both Y Y Y Y NA NAHemistola chryso-prasaria small emerald moths both Y Y Y N NA NA

Hepialus humuli ghost swift moths both Y Y Y Y NA NA

Hoplodrina blanda the rustic moths both Y Y Y Y NA NA

Hydraecia micacea rosy rustic moths both Y Y Y Y NA NA

Idaea dilutaria silky wave moths both Y Y N N NA NA

Lycia hirtaria brindled beauty moths both Y Y Y Y NA NA

Macaria wauaria the v-moth moths both Y Y Y N NA NA

Malacosoma neustria the lackey moths both Y Y Y N NA NA

Melanchra persicariae dot moth moths both Y Y Y Y NA NA

Melanchra pisi broom moth moths both Y Y Y Y NA NA

Melanthia procellata pretty chalk carpet moths both Y Y N N NA NA

Mesoligia literosa rosy minor moths both Y Y Y Y NA NA

Mythimna commashoulder-striped wainscot moths both Y Y Y Y NA NA

Orthonama vittata oblique carpet moths both Y Y Y Y NA NA

Orthosia gracilis powdered quaker moths both Y Y Y Y NA NA

Pelurga comitata dark spinach moths both Y Y Y Y NA NA

Perizoma albulata grass rivulet moths both Y Y Y Y NA Y

Rhizedra lutosa large wainscot moths both Y Y Y N NA NAScopula margine-punctata mullein wave moths both Y Y Y Y NA NAScotopteryx chenopodi- shaded broad-bar moths both Y Y Y Y NA NA

Scientific_Name Common_Name Group Datatype England S41

Wales S42

Scotland biodiversity

list

NI priority species

list

Capped at.10000

Halted at 1

ata

Spilosoma lubricipeda white ermine moths both Y Y Y Y NA NA

Spilosoma luteum buff ermine moths both Y Y Y Y NA NA

Stilbia anomala the anomalous moths both Y Y Y Y NA NA

Tholera cespitis hedge rustic moths both Y Y Y Y NA NA

Tholera decimalis feathered gothic moths both Y Y Y Y NA NA

Thumatha senexround-winged muslin moths both N N Y N NA NA

Timandra comae blood-vein moths both Y Y Y N NA NA

Trichiura crataegi pale eggar moths both Y Y Y Y NA NA

Tyria jacobaeae cinnabar moths both Y Y Y Y NA NA

Watsonalla binaria oak hook-tip moths both Y Y Y N NA NA

Xanthia gilvago dusky-lemon sallow moths both Y Y Y N NA NA

Xanthia icteritia the sallow moths both Y Y Y Y NA NA

Xanthorhoe decoloraria red carpet moths both Y Y Y Y NA NA

Xanthorhoe ferrugatadark-barred twin-spot moths both Y Y Y Y NA NA

Xestia agathina heath rustic moths both Y Y Y Y NA NA

Xestia castaneaneglected or grey rustic moths both Y Y Y Y NA NA

Adscita statices forester mothsfrequency of occurrence Y Y Y Y NA NA

Aleucis distinctata sloe carpet mothsfrequency of occurrence Y N N N NA NA

Anarta cordigerasmall dark yellow underwing moths

frequency of occurrence N N Y N NA Y

Catocala promissalight crimson under-wing moths

frequency of occurrence Y N N N NA NA

Chortodes brevilinea Fenn's wainscot mothsfrequency of occurrence Y N N N NA NA

Chortodes extrema concolorous mothsfrequency of occurrence Y N N N NA NA

Cosmia diffinis white-spotted pinion mothsfrequency of occurrence Y Y N N NA NA

Cossus cossus goat moth mothsfrequency of occurrence Y Y Y N NA NA

Cyclophora pendularia dingy mocha mothsfrequency of occurrence Y Y N N NA NA

Cyclophora porata false mocha mothsfrequency of occurrence Y N N N NA NA

Dicycla oo heart moth mothsfrequency of occurrence Y N N N NA NA

Endromis versicolora Kentish glory mothsfrequency of occurrence N N Y N NA NA

Entephria flavicinctatayellow-ringed car-pet moths

frequency of occurrence N N N Y NA NA

Eriogaster lanestris small eggar mothsfrequency of occurrence N N N Y NA NA

Hadena albimacula white spot mothsfrequency of occurrence Y N N N NA NA

Heliothis maritimashoulder-striped clover moths

frequency of occurrence Y N N N NA Y

Lithostege griseata grey carpet mothsfrequency of occurrence Y N N N NA NA

Macaria carbonarianetted mountain moth moths

frequency of occurrence N N Y N NA NA

Minoa murinata drab looper mothsfrequency of occurrence Y Y N N NA NA

Noctua orbonalunar yellow under-wing moths

frequency of occurrence Y Y Y N NA NA

Paracolax tristalis clay fan-foot mothsfrequency of occurrence Y N N N NA NA

Parasemia plantaginis wood tiger mothsfrequency of occurrence N N N Y NA NA

Pechipogo strigilata common fan-foot mothsfrequency of occurrence Y N N N NA NA

Scientific_Name Common_Name Group Datatype England S41

Wales S42

Scotland biodiversity

list

NI priority species

list

Capped at.10000

Halted at 1

Perizoma blandiata pretty pinion mothsfrequency of occurrence N N N Y NA NA

Polia bombycina pale shining brown mothsfrequency of occurrence Y Y N N NA Y

Rheumaptera hastata argent and sable mothsfrequency of occurrence Y Y Y Y NA NA

Scotopteryx bipunctaria chalk carpet mothsfrequency of occurrence Y Y N N NA NA

Shargacucullia lychnitis striped lychnis mothsfrequency of occurrence Y N N N NA NA

Trichopteryx poly-commata barred tooth-striped moths

frequency of occurrence Y N Y N NA NA

Trisateles emortualis olive crescent mothsfrequency of occurrence Y N N N NA NA

Tyta luctuosa four-spotted moth mothsfrequency of occurrence Y N N N NA NA

Xestia ashworthii Ashworth’s rustic mothsfrequency of occurrence N Y N N NA NA

Xylena exsoleta sword-grass mothsfrequency of occurrence N Y Y Y NA NA

Aeshna isosceles Norfolk hawkerother in-sects

frequency of occurrence Y N N N NA NA

Anasimyia transfuga a hoverflyother in-sects

frequency of occurrence N N Y N NA NA

Cheilosia chrysocoma a hoverflyother in-sects

frequency of occurrence N N Y N NA NA

Coenagrion mercuriale Southern damselflyother in-sects

frequency of occurrence Y Y N N NA NA

Decticus verrucivorus wart-biterother in-sects

frequency of occurrence Y N N N NA NA

Metrioptera brachyptera bog bush-cricketother in-sects

frequency of occurrence N N Y N NA NA

Stethophyma grossumlarge marsh grasshopper

other in-sects

frequency of occurrence Y N N N NA NA