Official Statistics

Indicators of species abundance in England: Response to feedback

Updated 13 October 2025

Applies to England

Last updated: 2025

In May 2024 we published, for the first time, ‘Indicators for Species Abundance in England’ as an official statistic in development. The all-species indicator, once fully developed, will be used to track progress with meeting the statutory biodiversity targets to:

1. Halt the decline in species abundance by 2030

2. Reverse these declines so that by 2042 species abundance is higher than in 2022 and 10% higher than in 2030

Following this publication, we invited feedback on the all-species indicator to help inform further development. To achieve this we:

• Ran two stakeholder engagement workshops in May and June 2024 with eNGOs, local government and landowners, and other interested parties to invite feedback and provide an opportunity to ask questions.
• Published a Defra blog on ‘A call for feedback on the indicators of species abundance in England’ in October 2024.
• Supported the British Ecological Society in running a workshop on the Species Abundance Indicator in mid-October 2024, inviting feedback from a range of experts.
• Met with the Office for Environmental Protection to discuss their feedback.

We received high quality feedback, both written and verbally following this engagement, which we are very grateful for. We also received some feedback on the priority species indicator – more information on updates to this indicator can be found in the 2025 statistical release.

Below we have sought to group and respond to this feedback for the all-species indicator and we have recently published our development plan for the next statistical release to be published in 2026.

The indicator production team are always keen to hear feedback from users, please do continue to get in touch with suggestions or comments: biodiversity@defra.gov.uk.

Trend breakdowns

A common criticism of biodiversity indicators (and any composite trend) is that the loss of granularity (by averaging across large numbers of species) means certain patterns of change might be missed. For example, declines associated with certain species groups, such as those associated with woodland. Stakeholders therefore suggested that we present further breakdowns of the overall trend (e.g. separating data by habitat or region).

We recognise the potential benefits of these more detailed breakdowns and have already included some of these in our indicators of species abundance in England publication. We will also explore alternative options as part of the development plan, which we have outlined below. However, some of these breakdowns may not be available in the 2026 release as classifying species into defined groups can be complex and we need to ensure that the methods used are robust and consistently applied.

Taxonomic breakdown

We already break down the indicator by taxonomic group which can be found in Table 2 and Figure 3 of the indicators of species abundance in England. Defra also publish species abundance indices for Wild bird populations in England, Butterflies in England and Mammals of the wider countryside (bats).

Habitat-level breakdown

Classifying species by the habitats they use is challenging as the classifications that work well for some taxonomic groups may not translate well to other groups. Species can use many different habitat types and these may vary depending on life cycle stage, season, or region.

We will explore options for a habitat classification method that works across taxa. If multiple methods for estimating habitat association are required, we will explore whether using different classifications for each taxa is a robust alternative.

As noted above, Defra also publishes abundance indices for birds and butterflies in the Wild bird populations in England and Butterflies in England publications. In these publications, birds are separated by habitat, and butterflies are separated into habitat specialists and species of the wider countryside.

Functional group breakdown

We will explore options for producing indicator breakdowns around functional groups.

Specialist / generalist

We will explore options for producing indicator breakdowns based on habitat specialists or generalists. As noted above, Defra also publishes abundance indices for birds and butterflies in the Wild bird populations in England and Butterflies in England publications. In these publications indicators are broken down into specialists and generalists.

Landscape / regional / site level breakdown

The indicator uses datasets that estimate the national abundance of species (i.e., for each species, we have a single overall estimate of their abundance in England per year). This means it is not possible to extract data for specific landscapes or regions.

Request for a distribution indicator

We had several requests to develop a distribution indicator. We are pleased to confirm that our development plan includes developing an indicator of all-species distribution in England, which will be published in the England Biodiversity Indicators.

Representativeness of the indicator

The list of species included in the all-species indicator is determined by the species in Schedule 2 of The Environmental Targets (Biodiversity) (England) Regulations 2023.

Species representativeness

There was some concern from stakeholders that the indicator does not include data for all taxonomic groups. Other stakeholders were concerned that we will only be taking actions for species within the indicator or that a handful of species performing well could skew the overall indicator.

The indicator includes a range of species groups which, between them, depend on most habitats found in England. This means that action to deliver the species abundance target will need to focus on the recovery of a broad range of habitats. Improvements to these habitats will benefit all the species that depend on them, including those not included in the indicator. The species listed in Schedule 2 are also not intended to be a priority list for targeting species recovery actions. These are simply the species that we have abundance data for.

Whilst we note that species coverage of the indicator is limited by the availability of abundance data from existing monitoring schemes, it is essential that the datasets included in the indicator meet certain criteria to provide confidence that the trends accurately reflect the national status of each species. Where taxonomic groups are not represented in the indicator, this is because we did not identify datasets that met the criteria for inclusion of those species. More information can be found in the statistics release and published Q&A.

Other biodiversity indicators utilise different types of species and environmental data. These will be used alongside the all-species abundance indicator to help us understand the status of biodiversity in England. This includes the species extinction risk indicator (D5: Conservation status of our native species), which includes data for over 8,200 taxa in England (estimated to be approximately 20% of native terrestrial and freshwater species in England). Several of the taxonomic groups highlighted as being absent from the abundance indicator are well represented in the extinction risk indicator. For example, the extinction risk indicator includes 893 non-vascular plants, 1,464 lichens, and all 13 native amphibian and reptile species in the UK.

We were also asked about the limited number of marine species included in the indicator. The species abundance target (and associated all-species abundance indicator) was developed to cover terrestrial/ freshwater species. Although the indicator contains seabirds and a small number of fish living in coastal waters, we have classified these as coastal species (e.g. those dependent on terrestrial as well as marine habitats), and not as marine species. The indicator therefore does not represent marine species. There are existing abundance indicators for marine species in the UK Marine Strategy and in the OSPAR assessments, and there is a separate target for marine protected areas. We are aware that data may become available for additional species that could be classified as coastal which we will explore further during wider considerations of adding/removing species from the indicator (see below).

Adding / removing species from Schedule 2 and the indicator

We had mixed feedback about whether it would be beneficial to consider adding / removing species from Schedule 2 and the indicator. Some stakeholders highlighted that if new data for species becomes available which meets the data requirements, then we should consider adding them to improve representativeness of the indicator. Other stakeholders were concerned that adding or removing species would contribute to a changing baseline and could lead to ‘gaming’ of the target, e.g. making it easier to meet.

To safeguard the integrity of the target Section 4(1) of the Environment Act requires the Secretary of State to seek advice from independent experts before making changes to Schedule 2. To develop Schedule 2 this took the form of a public consultation. This approach is resource-intensive and impractical for frequent updates, with minimal impact on overall species representation. However, when substantial new data emerges for several species, we will consider expanding Schedule 2 to enhance representativeness.

We propose that we assess annually (in line with the indicator updates), whether there is:

• data for additional species which meet the criteria that could be added to Schedule 2
• potential species on Schedule 2 which no longer meet the data requirements and should be removed from Schedule 2

Consultation on changes to species in the indicator will occur only if a minimum threshold is met, and stakeholder input is invited to define that threshold. Given current monitoring and inclusion criteria, few new species are expected to be able to be added before 2030 and the number of species which no longer meet the data requirements is likely to be very low. Therefore, no public consultation on Schedule 2 changes is planned until after the 2030 assessment.

Temporal and spatial representativeness of the indicator

Some of the feedback received raised issues around the representativeness of the indicator, how that changes over time and how that interacts with the assumptions of the Freeman model. This included the suggestion that we cover other ways of describing representativeness, other than species coverage.

The representativeness of the indicator is reported in multiple sections of the indicator report, but to date has mainly focussed on the species representativeness. For example, the ‘Representativeness of the indicator’ paragraph in the Caveats and limitations section, exclusively discusses the taxonomic coverage of the indicator, how that coverage changes over time and how that relates to the overall goals of the indicator, i.e. average trends across ‘all’ and ‘priority’ species. Figure 9 of the report provides a clear visualisation of the temporal change in taxonomic coverage of the indicator.

We have now extended the ‘representativeness of the indicator’ section, discussing other important areas of representativeness, for example the spatial coverage of the data. We make a key distinction around two forms of representativeness. Firstly, how representative the data are in terms of the target populations of interest, in this case, to what extent do the data reflect the change in status of ‘all’ and ‘priority’ species across their respective ranges within England. Second, within the data, how consistent is that representativeness over time, for example the large changes in the number of species contributing to the indicator over time. These are both discussed in the context of the Freeman method, where we highlight assumptions and areas of concern that require further understanding and investigation.

Understanding and communicating the representativeness of the sample data to the desired population of inference is essential for readers to assess the validity of the conclusions drawn from these indicators. An area for future work is to complete standardised assessments of representativeness across multiple scales (taxonomic, spatial and temporal), where any limitations of the data and models are clearly described. The assumptions of the Freeman method as applied in these indicators should be tested, revealing the likelihood of those assumptions holding for the given indicator. For example, the assumption that “trends among missing species follow the same overall distribution as those with data” can be tested. In reality this assumption that species are missing at random with respect to their trend is known to not be true, however, simple diagnostics can give some insight into how wrong such an assumption is.

Inclusion of ‘undesirable’ species

Some stakeholders were concerned that the all-species indicator includes species which are seen as ‘pests’ (e.g. invasive non-native-species), that are associated with unfavourable habitat quality, have negative interactions with rare and threatened species, or are in some other way undesirable.

There is an argument for the exclusion of these species from the indicator, on the basis that increases in their abundance may not reflect improvements in the status of biodiversity. However, we have considered this question and have retained these species for the following reasons:

1. Any decision about which species are desirable or undesirable to include in the indicator would need to be underpinned by a rigorous process. There is currently no process that could be applied across all species groups in the indicator, meaning that decisions to remove individual ‘undesirable’ species would be subjective and risk undermining confidence in the indicator.
2. The number of potential ‘undesirable’ species is small compared with the much larger number of species in the indicator that are considered to be desirable. This means that, overall, the value of the indicator would generally decrease if habitats were to become degraded (where few species increase but most decrease) and increase if habitat quality were to improve (where most species increase but few decrease).

The exception to the above is invasive non-native species, which were generally excluded from the indicator (as it is possible to apply more consistent criteria for assessment of these species). However, species which established before the year 1500 were included, for example rabbits and fallow deer. The objective cut off point of 1500 was chosen for this indicator because for many of the species which established before this time it is challenging to assess their native status and route of introduction.

All-species abundance indicator methodology

Transparency

In the updated publication, we have addressed several areas of text where we received feedback about a lack of clarity. This includes the Background and methodology section, as well as the Technical annex. Our hope is that the text is now clearer and easier to interpret and understand, enabling further feedback on the methods used to produce these indicators. The code underpinning data cleaning and pre-smoothing of individual species trends will be made available on GitHub at the point at which the statistics are next updated. The code for calculation of smooth multispecies (composite) indices and trends is available on Github.

Smoothing of the indicator

In responses to our question about which smoothing interval would be most appropriate (10 year vs 3 year) we noted no consistent preference on which version of the smoothing is best. For example, some respondents preferred shorter or longer smoothing intervals and some also suggest species-specific smoothing may be useful.

In the current publication, we have retained the two versions of smoothing. A future development goal is to determine which version of smoothing should be used for assessing change in the indicator and carried forward (see Development plan).

In the feedback there were concerns about the interpretation and communication of smoothed trends, particularly about missing important interannual variation.

These indicators are a summary of distinct species-specific times-series. Essentially, they are an average time-series across a set of species and inherently lose the granular detail (species-time-series) in favour of a broader picture of patterns of change. Similarly, statistical smoothing processes necessarily will result in a loss of granularity, meaning that strong fluctuations in inter-annual species- or group-specific abundance values, will be down weighted in favour of a smoothed trend. Smoothing is used here to ensure the indicators reflect long-term patterns of change rather than short-term variation that may be driven by weather, unaccounted for variation in recording behaviour, or other short-term drivers of change. Although a smoothed index is desirable for assessing change over time, as it smooths out some of the impact of between-year fluctuations (e.g. weather patterns), it does mean that it may be difficult to detect notable change between two adjacent years.

Two levels of smoothing are used in the current version of the indicator, a strong and a weak smoother, this allows readers to assess the impact of the amount of smoothing on the resulting patterns of change. The future development plan contains a commitment to an investigation of the appropriate level of smoothing to apply to the these indicators. This is particularly important given the relevance of these indicators to the Environment Act. The future development plan contains a commitment to an investigation of the appropriate level of smoothing to apply to the the indicator.

Concerns about the interpretation of smoothed trends are valid and it is important that the fundamental caveats and assumptions associated with smoothing are clearly communicated. We addressed this in the ‘Smoothing to reveal long-term trends’ section of ‘Caveats and limitations’ of the England Abundance indicator report (see Background and methodology).

Pre-smoothing

In the indicator, following advice from an independent expert review of the methodology by three academics , we applied an additional step of smoothing (pre-smoothing) to the species level data before creating the composite index with the Freeman method (Freeman et al., 2020). The decision to implement pre-smoothing was also partly driven by the cross-validation testing which showed an increase in within-dataset predictive accuracy of the Freeman method when applied to a pre-smoothed dataset compared to an unsmoothed dataset. However, there are some limitations to this approach and we have expanded the ‘Pre-smoothing’ section of the Caveats and limitations of the main indicator report to better reflect these. Other departures from the original implementation of the Freeman method, and consequences thereof, are discussed here and in the indicator report (see section ‘Model specifics’ section of the Technical Annex).

The Freeman method was specifically designed to accommodate unsmoothed input data and any associated short-term variation. The Freeman method is also structured to account for the fact that input data provide an imperfect representation of the true underlying state (abundance per year), meaning that individual species-year index values are supplied alongside an estimate of uncertainty (available here for most species from the given input datasets). This uncertainty is then propagated to the final indicator produced by the Freeman method. The current indicator production method departs from both of these original strengths of the Freeman method, each are discussed separately below, and in the ‘Pre-smoothing’ section of the ‘Caveats and limitations’ and the ‘Model specifics’ section of the indicator report, respectively.

By design the Freeman method contains two forms of ‘smoothing’. Firstly, growth rates (that is species year to year change) are assumed to follow a log normal distribution parameterised by the data, where the impact of outliers is reduced as they are pulled towards the mean growth rate across species. Secondly, the Freeman method applies spline-based smoothing at the community (composite indicator) level, which is specifically designed to smooth short-term fluctuations, meaning the indicator better represents the long-term direction of change. These inbuilt smoothing approaches mean that any additional smoothing of the input data, such as the pre-smoothing step we perform, should be superfluous. Some of the feedback received expressed concern that using additional smoothing steps risks removing biologically meaningful signals, which would reduce the indicator’s accuracy and interpretability.

The caveats of using cross-validation based performance metrics as a reason to use pre-smoothing have now been explained in more detail in the publication text. Cross-validation assessments are done by fitting the model to a subset of the whole dataset, such that the data which it hasn’t been fitted to can be used to test the model’s predictive performance. As the data used in the indicator are pre-smoothed (thereby reducing interannual variation) then it is not surprising that the cross-validation performance is better when using pre-smoothed data compared to the more variable unsmoothed input data. Essentially, the pre-smoothed data are easier for the model to fit, leading inevitably to better performance in cross-validation comparisons.

Given the points above, further development work is required to examine the validity and impact of the methodological departures from the original implementation of the Freeman method. Notably, the addition of pre-smoothing and the lack of species-specific uncertainty propagation. This is now highlighted as an area for future work in the Development plan of the indicator report.

Confidence around the start and end of the time-series

Smoothing an index like the all-species abundance indicator generally produces a trend where the start and the end of the time series have the lowest confidence associated with them and this can impact how well we are able to assess meaningful change over the long and short term. In the all-species abundance indicator, the confidence intervals around the index grows over time, as the indicator is baselined to the first year of the time series (1970) and index values refer to the amount of change since that baseline year. This means we can make reliable comparisons between the index at the start of the time series and how this overlaps with the credible intervals in other years. It is less statistically robust to compare index values between other years of the index. We are currently discussing methods for a more robust approach to assessing change over the short- and medium-term.

Standardising to baseline values in the first year is common practice in biodiversity indicators, and results in the credible interval around the index being smallest in the early years, however this gives the impression that the first (early) years are estimated with more certainty. This is not ideal as data quality and quantity tend to increase over time meaning there is often more certainty around changes in abundance of many species in the more recent years. Uncertainty around the indicator also tends to increase over time when using the Freeman method. This is in part due to the way that randomness is incorporated into the estimates of growth for each species’ population, which causes compounding of uncertainty year after year. Essentially, each year’s estimate depends on the previous year, so uncertainty builds over time. It is possible that as data availability increases in later years, uncertainty overall can decrease as the benefit (reduced uncertainty) of the additional data outweighs the compounding of growth rate uncertainty.

Understanding which areas of uncertainty are captured by the credible interval surrounding the indicator method, and critically assessing the areas of uncertainty that are lost (for example uncertainty around the species-specific index values) is an essential development goal for the indicator. These areas for future development are now highlighted in the future developments section of the indicator report.

Lack of measurement error

The Freeman model (Freeman et al., 2020) does not treat the input data for the different species as perfect, but recognises they arise from a sampling process that is subject to measurement error. This measurement error is currently estimated from the data, but the method does include the ability to provide species-specific estimates for measurement error, if available.

The ability of the Freeman method to incorporate uncertainty around the input indices of abundance is a key ‘strength’, but is not currently implemented in the all-species and priority species abundance indicators. Instead a constant observation variance is estimated globally by the model. This means that uncertainty around the species-specific index estimates is not propagated through to the final indicator plots and assessments.

The use of pre-smoothing inhibits the ability to easily supply uncertainty values as inputs to the Freeman method. A future development goal is to examine the credibility of using pre-smoothing, including an investigation into options for extracting uncertainty values from the pre-smoothed indices. Future iterations of this indicator will include a comparison of the indicator with and without uncertainty values propagated from the input abundance indices. This is crucial to understand the impact of propagating the species-specific uncertainty through to the final indicator.

Options for weighting the indicator

Several responses suggested that we could consider using weightings within the indicator. Currently species-specific trends are amalgamated without weighting, which treats each species 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. The main bias on the data is that some taxonomic groups are not represented at all, which cannot be addressed by weighting. We discuss this further in the Technical annex (see ‘Exploring options for a weighted index’).

We could consider weighting at several different levels, including taxonomic group, functional group or habitat associated grouping. Species-specific weighting has been described in the literature but has often been noted to incorporate a degree of subjectivity that can be difficult to reach a consensus on. Furthermore, it is possible to weight by the level of confidence in the species-specific trends, in other words we can down-weight species where the trends are more vulnerable to bias. However, as with any weighting approach, it is crucial to consider the indicator’s inferential target. Down-weighting species based on bias may result in an indicator that is less representative of the intended population.

Fundamental issue with indicator lines: certain species can be declining while the indicator line is increasing

Indicators are a summary of distinct species-specific times-series. Essentially, they are an average time-series across a set of species and inherently lose the granular detail (species time-series) in favour of a broader picture of patterns of change. The all-species abundance indicator was developed with the aim of summarising trends in abundance for the broadest possible set of species in England. Species in the indicator are equally weighted and the trend is calculated based on geometric mean, which means that a doubling in abundance of one species would be exactly cancelled out by a halving in another species (regardless of whether they are rare or widespread). While it is possible that large increases in some species could mask declines in others, it is not feasible to entirely avoid this risk whilst ensuring that the indicator is as representative as possible of English biodiversity.

We have published additional figures, alongside the overall trend, that allow more detailed understanding of the underlying changes. For example, we produce a chart showing the number of species that have increased, decreased, or shown little change over the short- and long-term (Figure 2). We also produce a breakdown by taxonomic group (Figure 3; Table 2), which would highlight if different trends were occurring across different groups.

What indicators exist in other countries and how does our methodology compare

Many countries collect abundance data for individual taxa, but England is one of few countries to have a nationally representative abundance indicator which incorporates multiple taxonomic groups. Scotland is also developing indicators of species abundance for both marine and terrestrial species, which have been published as experimental official statistics.

Whilst some countries such as Canada and Australia have developed abundance indicators which cover multiple taxonomic groups, these are based on the Living Planet Index methodology. The Living Planet Index methodology is calculated by collating individual population time series data across a region, which are then averaged across a species . This poses a risk that the population data used is not nationally representative. The all-species abundance indicator differs from this methodology as it uses nationally representative population data, rather than averaging time-series of individual populations (except for species for which it is the sole population in England).

How will we communicate the impact of changing the methodology?

As Official Statistics in Development, the methodology for the indicators is likely to undergo changes before it gains Official Statistic status. As with all our statistics, we will indicate anticipated developments in the Development plan for this indicator and explain in the relevant sections where the methodology might have changed for the current publication. Following the feedback we received, we are also publishing this response where we highlight the major changes that have been made to this publication in 2025, along with a Key changes section in the publication itself. Any major changes made to the underlying methodology will also be explored in the Technical annex with a charted comparison to the previous methodology and an explanation of any differences that may arise. This year we have added a ‘Changes since the last publication’ section to the Technical annex, which explores any key differences from the previous year.

Peer review

There were several suggestions that peer review of the complete methodology used would be desirable and will give more confidence in the approach, including the cross-validation work underpinning the indicator development. The indicator methodology was reviewed by an independent panel of three academic experts and we will look to do further peer review of the whole methodology once further developed. The majority of the current indicator methodology and data analysis do use peer-reviewed methods (see References). Any deviations from these methods (for example, the pre-smoothing) are clearly highlighted in the publication, along with justification for their differences. We also highlight areas for future work where the justification needs further clarification. We intend to publish reports relating to the recent development of the indicator, including suggestions and reviews from the expert panel, which should aid with transparency around the decisions taken for this indicator. This page and the main publication will be updated with these links once they become available.

Data

Data Collection

Much of the data on species abundance is collected through volunteer-based recording schemes, many of which are run through partnerships between government bodies, non-governmental organisations (NGOs), and research organisations, or through statutory monitoring schemes. Many of these monitoring schemes rely on citizen scientists, who provide contributions to collecting species data. More information on the schemes contributing data to the indicator is published in the indicators of species abundance in England publication - to find out how to get involved, please contact the schemes directly.

Is it our intention to publish all of the underlying data?

Defra do not own the underlying data used to calculate this indicator. We have added links and references to survey data, species indices and peer-reviewed methodology for each scheme, where available (See Table 6, Technical annex). This also addresses concerns raised around transparency of the provenance of the data and the peer-reviewed science that underpins each scheme.

We are working with data providers and hope to be able to publish the underlying data alongside future updates to the indicator.

Recorder effort

Concerns were raised around the underlying species data used in the indicator and whether we account for bias in the species models due to changing recorder effort and/or change in the spatial pattern of recording over time.

Many of the underlying group-specific species models are designed to handle some of the common forms of bias found in these types of structured surveys datasets. We are aware that even the UK Butterfly Monitoring Scheme, arguably one of the most well-recorded groups has underlying issues of bias: see Boyd et al., 2025, for more detail).

The data sources and the modelling approach used to produce the species specific indices are listed in Table 5 and Table 6, respectively. Understanding the extent to which these methods handle biased data in space and time is challenging, and an evolving field of academic research. A key step towards improving this understanding is clear documentation and communication of the spatial and environmental representation of the sampled data and how these changes over time. As part of the Development plan we intend to produce a clear assessment of the spatial, taxonomic and temporal coverage of data in the next iteration of these indicators.

Species abundance target

Measuring the target to halt the decline in species abundance by 2030 using a comparison between 2029 and 2030

Several stakeholders raised concerns that the target to halt the decline in species abundance by 2030 is based on the difference in the indicator between 2029 and 2030. There was a concern that we will just be comparing two points in time, which does not account for overall trends in the data, and that externalities such as extreme weather events could make the target easier or harder to achieve.

Clause 12 in the Environment Act Regulation requires that:

1. The 2030 species abundance target is to be measured by calculating the difference between the overall relative species abundance index for the years 2029 and 2030 in order to establish whether the overall relative species abundance index for the year 2030 is the same as, or higher than, the overall relative species abundance index for the year 2029.

2. The overall relative species abundance index for a year is derived from the calculation of the geometric mean of the relative species abundance indices for every species listed in Schedule 2 for that year, which is smoothed to reduce the impact of between-year fluctuations in data collected over time.

3. The same methodology must be used to determine the overall relative species abundance index for each year.

The indicator trend that will be used for the 2029 to 2030 comparison will therefore be smoothed to reduce the impact of between-year fluctuations. We are also exploring how a statistical test could be applied to the calculation of the 2029 to 2030 comparison to ensure it most accurately represents general abundance trends and we welcome views from stakeholders on potential options. These two processes will ensure that the method with which we assess whether or not we have met the target is robust.

It is also worth noting that different factors will have different impacts on different species (e.g. more rain could be good for some species, but worse for others). Different species will also respond to adverse weather events on different timescales, and for many species one year of adverse weather conditions would not be enough to materially affect species abundance trends. It is therefore difficult to estimate the cumulative impact of any adverse weather event or other factors on overall species abundance.

To overcome this, we will publish a taxonomic breakdown of the overall trend which will help us to understand changes in different species groups in more detail than just the overall trend. This indicator is also not intended to be looked at in isolation to determine the status of biodiversity in England. It should be considered alongside the wider suite of biodiversity indicators published by Defra, including those reported under the England Biodiversity Indicators and the Outcome Indicator Framework . Taken together, these will help to provide a more holistic picture of the state of nature.

Time-lags in measuring data affecting policy delivery

Stakeholders highlighted that we will not be able to measure the 2030 species abundance target until 2032 due to routine data lags and that this could have implications for policy makers and ambition. However, the target to improve species abundance by 10% by 2042 will still be driving ambitious delivery beyond 2030.

Delivery of the species abundance target

We had various questions around how we will be delivering the species abundance target, and how this relates with other targets such as protecting 30% of land and sea by 2030, Net Zero, etc. More information on this will be included in Defra’s new, statutory plan to protect and restore our natural environment which will be published in the revised Environmental Improvement Plan.

Further suggested developments

In addition to the feedback highlighted here, there were also other suggested developments for the indicator that are too numerous to note here. These suggestions will be kept under review and where possible incorporated into the Development plan.

The indicator production team are always keen to hear feedback from users, please do continue to get in touch with suggestions or comments: biodiversity@defra.gov.uk.