Testing the development of species accounts for measuring...

UNEP-WCMC Technical report

Testing the development of species accounts for

measuring ecosystem condition at EU level

The report has been produced by UNEP-WCMC in collaboration with the European Environment

Agency and European Topic Centre for Biodiversity as part of the integrated system for natural capital

and ecosystem services accounting (KIP INCA) project. Funding for the work has been provide via a

technical support contract managed by the Directorate-General for Environment of the European

Commission.


Acknowledgements This technical report was informed by a two day workshop held at UNEP-WCMCs offices in Cambridge in May 2017, involving UNEP-WCMC, European Environment Agency and the European Topic Centre for Biodiversity. The report has been produced using existing data from a number of sources. The authors would like to acknowledge information kindly provided by André van Kleunen at the Sovon Dutch Centre for Field Ornithology, which has also contributed to the report.

Authors King, S. (UNEP-WCMC), Arnout van Soesbergen (UNEP-WCMC), Claire Brown (UNEP-WCMC), James Vause (UNEP-WCMC), Bálint Czúcz (EEA ETC BD), Daniel Desaulty (EEA), Jan-Erik Petersen (EEA)

Published November 2017

Front cover photo: © Zakharov Aleksey / shutterstock.com

In collaboration with: European Environment Agency, European Topic Centre for

Biodiversity.

Citation: UNEP-WCMC (2017) Developing Ecosystem Condition Accounts for the EU and Member States

Disclaimer: The contents of this report do not necessarily reflect the views or policies of UN Environment, EU, Member States, contributory organisations or editors. The designations employed and the presentations of material in this report do not imply the expression of any opinion whatsoever on the part of UN Environment or contributory organisations, editors or publishers concerning the legal status of any country, territory, city area or its authorities, or concerning the delimitation of its frontiers or boundaries or the designation of its name, frontiers or boundaries. The mention of a commercial entity or product in this publication does not imply endorsement by UN Environment.

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Contents Executive Summary ............................................................................................................ 6

Glossary ............................................................................................................................... 8

1 Introduction ................................................................................................................ 9

2 Biodiversity condition parameters ............................................................................. 11

2.1 Article 17 Reporting.............................................................................................. 12

2.2 Member State bird trends ................................................................................... 13

2.2.1 Article 12 ........................................................................................................ 13

2.2.2 EBCC and National Data .............................................................................. 15

2.3 Key points ............................................................................................................. 15

3 Article 17 Approach .................................................................................................... 17

3.1 Overview of measurement approach .................................................................. 17

3.1.1 Article 17 Species Conservation Status Accounts ........................................... 17

3.1.2 Proposed Structure for Article 17 Species Conservation Status Account ... 19

3.1.3 Getting the data together ............................................................................. 21

3.1.4 Dealing with data gaps ................................................................................. 21

3.2 Key points ............................................................................................................ 22

4 Article 12 Approach ................................................................................................... 24

4.1 Overview of measurement approaches ............................................................. 24

4.1.1 Species Status Accounts .............................................................................. 24

4.1.2 Proposed Structure for Species Status Account ......................................... 26

4.1.3 Species Abundance Accounts...................................................................... 28

4.1.4 Proposed Structure for Species Abundance Account ................................ 30

4.1.5 Getting the data together – Member State Accounts ................................. 31

4.1.6 Getting the data together – EU Level Accounts ......................................... 32

4.2 Key points ............................................................................................................ 32

5 Testing Accounts ....................................................................................................... 34

5.1 Belgium ................................................................................................................ 34

5.1.1 Article 17 ........................................................................................................... 34

5.1.2 Article 12 ....................................................................................................... 36

5.2 Article 17 EU Level Accounts .............................................................................. 44

5.3 Key points ............................................................................................................ 49


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6 Critical Assessment of Species Accounts using Article 12 data ................................ 51

6.1 Article 12 Species Status Accounts ...................................................................... 51

6.2 Article 12 Species Abundance Accounts ............................................................. 51

6.3 Trend indicators .................................................................................................. 52

6.4 Comparison and integration with Belgium Article 17 Species Accounts ......... 54

6.5 Limitations .......................................................................................................... 55

6.6 Key points ............................................................................................................ 56

7 Conclusions ............................................................................................................... 58

7.1 Policy insights from Species Accounts .............................................................. 58

7.2 Species Accounts for Ecosystem Condition Measurement............................... 59

7.3 Data and ecological knowledge constraints ...................................................... 60

7.4 Next Steps ............................................................................................................ 60

References ......................................................................................................................... 63

Appendices ........................................................................................................................ 66

Appendix A: Article 17 and Article 12 based Accounts for Slovakia ............................ 66

Article 17..................................................................................................................... 66

Article 12..................................................................................................................... 67

Appendix B: Spatial Analysis ......................................................................................... 72

Increasing the resolution of bird species habitat links ................................................ 72

Accounting for suitable habitat .................................................................................... 76

Habitat suitability accounting example for Belgium ............................................... 77

Spatial Issues ............................................................................................................. 80

List of figures and tables

Figures

Figure 1: Relationship between thematic accounts and other SEEA-EEA accounts (adapted from Chow 2016) ................................................................................................. 9

Figure 2 Disaggregation of Article 12 data using species and ecosystem linkages ........ 26

Figure 3 Linkages between Article 12 data and accounts at different aggregation levels showing increasing analytical power ............................................................................... 72

Figure 4 Spatial representation of differences in Corine land cover between 2006 and 2012 for MAES (left) and CLC typologies (right) for Belgium ........................................ 73


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Figure 5 Land cover changes between 2006 and 2012 for the CLC typology in Belgium ........................................................................................................................................... 74

Figure 6 Distribution of Acrocephalus palustris in Belgium based on MAES associations (left) and CLC associations (right) for 2012 ................................................ 75

Figure 7 Distribution of Acrocephalus arundinaceus in Belgium based on MAES associations (left) and CLC associations (right) for 2012 ................................................ 76

Figure 8 Percentage change in suitable habitat between 2006 and 2012 for 95 common bird species in Belgium based on Corine land cover classes .......................................... 78

Figure 9 Grid cell specific analysis of suitable habitat changes for common birds in Belgium .............................................................................................................................. 79

Figure 10 Suitable habitat distribution for Acrocephalus palustris in 2006 and 2012 for Belgium using Corine CLC data. Colours indicate the proportion of suitable habitat in the grid cell ........................................................................................................................ 79

Tables

Table 1 EEA Review of biodiversity based ecosystem condition parameters and data .. 12

Table 2 A Proposed Structure for Article 17 Species Conservation Status Account ...... 20

Table 3 Treatment for combing short and long term trend results as an overall trend 25

Table 4 Proposed Structure for Species Status Account ................................................. 27

Table 5 Proposed Structure for Species Abundance Account using Article 12 data ....... 31

Table 6 Account for Belgium using Article 17 Approach .................................................35

Table 7 Species Status Account for Belgium.................................................................... 37

Table 8 Species Abundance Account - all birds for Belgium .......................................... 38

Table 9 Species Abundance Account - EBCC Common Bird Classes for Belgium ........ 40

Table 10 Species Abundance Account - SPA-Trigger Classes for Belgium ..................... 42

Table 11 Species Abundance Account - EU Population Status Classes for Belgium ...... 43

Table 12 Species Status Account for EU ........................................................................... 45

Table 13 Species Abundance Account - Population Status Classes for EU..................... 46

Table 14 Species Abundance Account - all birds for EU ................................................. 47

Table 15 Species Abundance Account - EBCC Common Bird Classes for EU ................ 48

Table 16 Account for Slovakia using Article 17 Approach ............................................... 66


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Table 17 Species Abundance Account using all birds for Slovakia ................................. 67

Table 18 Species Abundance Account using EBCC Common Bird Categories for Slovakia .............................................................................................................................. 68

Table 19 Species Abundance Account using SPA-Trigger Status for Slovakia ............... 69

Table 20 Species Abundance Account using Threat Status Categories for Account for Slovakia .............................................................................................................................. 70

Table 21 Species Status Account for Account for Slovakia ............................................... 71

Table 22 CLC Classes within MAES Wood / Forest Ecosystem Type ............................. 74

Table 23 Ecosystem associations for Acrocephalus palustris and Acrocephalus arundinaceus under MAES and CLC typologies .............................................................. 75


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Executive Summary This report supports work to develop an integrated system for natural capital and ecosystem services accounting in the EU (KIP INCA). It fulfils three main objectives with respect to developing accounts of biodiversity and, by extension, accounting for ecosystem condition via species-level biodiversity metrics. Specifically, it reviews relevant biodiversity data for the EU; tests the compilation of natural capital accounts using selected biodiversity data; and, provides a critical assessment of derived accounting outputs (including from a spatial perspective in Appendix B).

This report has been informed by a two day workshop between UNEP-WCMC, the European Environment Agency (EEA) and the European Topic Centre for Biodiversity (ETC BD). It provides a summary of EEA work to develop ‘Species Accounts’ using data reported under Article 17 of the EU Habitats Directive and a detailed methodology for a novel approach to compiling Species Accounts using data on bird species reported under Article 12 of the EU Birds Directive (the focus of this report).

The report demonstrates it is possible to compile Species Accounts using Article 12 data based on population status, species abundance, species richness and species evenness statistics, all key aspects relevant to biodiversity. A significant current constraint for these accounts is that data is only available for a single reporting period (2008-2012). However, the next reporting cycle is nearing completion (2012-2018) and will allow an update of the accounts in due course. As an interim measure, ‘Status and Trend’ indicators are proposed that draw on population trend data supplied by Member States to provide a temporal aspect to the accounts. This follows a comparable approach using Article 17 data (developed by the EEA).

Among the currently available data sets at the Member State and the EU scales, Species Abundance Accounts using all relevant Article 12 data are believed to provide the best ecosystem coverage and most reliable summary statistics on ecosystem condition when all bird species were considered. The likely exception to this is for cropland, where trends in ‘Common Farmland’ species may provide more accurate signals on the condition of this ecosystem type. A distinct benefit of the Species Abundance Accounts is that they are compiled from numerical data. In theory, this greatly increases the sensitivity of the accounts as barometers of ecosystem condition, as changes in species richness and conservation or population status assessments are likely to be relatively slow to change. However, fundamental to this holding true in practice, is that the abundance data reported by Member States under Article 12 is reliable, updated every reporting period and consistently estimated or measured in meaningful manner over the long-term.

At the EU scale, Species Status Account were considered to provide a useful construct for organising population status assessment by the European Red List of Birds Consortium (2014) from a Mapping and Assessment of Ecosystems and Services (MAES) ecosystem type perspective. Similarly the EU scale Species Abundance Accounts for European Bird Census Council (EBCC) Common Bird species allows the


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Article 12 results to be related to the birds covered by the Pan-European Common Bird Monitoring Scheme to be considered from a MAES ecosystem type perspective.

The Species Accounts presented provide a solid foundation for informing on policy objectives for improved natural capital management and biodiversity in the EU. Important next steps identified include:

Testing the integration of Species Accounts and associated condition parameters within wider ecosystem condition accounts

Comparing information presented in the Article 12 Species Accounts with information on trends presented by the EBCC. This trend data could also support the back casting of Article 12 data to estimate populations for previous reporting periods or to set benchmarks

Refining the distribution of species population estimates across ecosystems and biogeographical regions to increase the specificity of population statistics. For example, using information from the ecosystem extent account, Corine Land Cover preferences and reported distribution data in combination. This could be improved using species distribution modelling approaches

Using geo-referenced national bird species monitoring data to integrate information on biodiversity trends and ecosystem location and trends in a spatially explicit accounting approach

Experimenting with statistics for ecological robustly identified indicator species of ‘good condition’ for specific ecosystem types

Developing the final methodological approach and data processing set-up to be ready for implementation when the next reporting cycle for the data sets used is completed.


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Glossary Biological diversity (Biodiversity): The variability among living organisms from all sources including, inter alia, terrestrial, marine and other aquatic ecosystems and the ecological complexes of which they are part; this includes diversity within species, between species and of ecosystems (CBD, 1992).

Ecosystem asset: A spatial representation of ecosystems as contiguous areas of a single ecosystem type that form the conceptual base for accounting and the integration of relevant statistics (UN et al. 2015).

Ecosystem condition: The effective capacity of an ecosystem to provide services, relative to its potential capacity (MA 2005). In accounting parlance, the condition of an ecosystem asset based on measurements of various characteristics at a given point in time (UN et al. 2014).

Ecosystem Accounting Area: The geographical extent for tabulating species or ecosystem information defined by, for example, sub-region boundaries, protected areas or national boundaries.

Species-level biodiversity: Diversity at the species-level, often combining aspects of species richness, their relative abundance, and their dissimilarity (MA, 2005a).

Species abundance: The total number of individuals of a taxon or taxa in an area, population or community (or, where counts are not feasible, other measures, such as biomass and percentage cover, may be used) (MA, 2005c).

Species evenness: A situation where high evenness occurs is one where when many species have similar abundance, with no single species dominating (Buckland et al., 2005).

Species richness: The number of a species within a given sample, community or area (usually from a particular taxa, e.g. plant species richness) (MA, 2005c).

System of Environmental-Economic Accounting – Experimental Ecosystem Accounting (SEEA-EEA): An experimental, multipurpose, statistical framework that aims to reinforce and quantify the importance of the relationship between people and their environment (UN et al. 2014).

System of National Accounts (SNA): The internationally adopted standard for compiling national statistics on economic activity.

Taxon (plural taxa): A taxonomic category or group, such as phylum, order, family, genus or species.

Threatened species: Any species vulnerable to endangerment in the near future. Comprises the IUCN Red List categories of ‘Vulnerable Species’, ‘Endangered Species’ and ‘Critically Endangered Species’.


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1 Introduction The European Union (EU) has set itself ambitious targets for the preservation and better management of natural capital in the 7th Environmental Action Programme of the EU and the EU Biodiversity Strategy to 2020. To build the knowledge base for achieving these objectives a shared project was set up at EU level to develop an integrated system for natural capital and ecosystem services accounting (KIP INCA). The organisations taking KIP INCA forward are Eurostat, the EU Joint Research Centre (JRC), the Directorate-General for Environment and the Directorate-General for Research and Innovation of the European Commission, and the European Environment Agency. KIP INCA connects to the first phase of the EU initiative on Mapping and Assessment of Ecosystems and Services (MAES), which aims to map and assess ecosystems and their services in the EU, and supports the second phase of MAES, which aims to value ecosystem services and integrate them into accounting and reporting systems by 2020. The key goal for KIP INCA is to establish a system that enables regular ecosystem accounting at EU level.

The methodological starting point of KIP INCA is the UN System of Environmental-Economic Accounting- Experimental Ecosystem Accounts (UN et al. 2014). The SEEA is a multipurpose framework for understanding the interactions between the environment and the economy, thereby extending the established System of National Accounting (SNA) used for the measurement of economic activity and related stocks and flows. The SEEA-EEA extends this framework to consider ecosystems, their condition and the services they provide. This includes accounting for biodiversity, both as a management theme and as an important element in the measurement of ecosystem condition (Remme, Hein and Van Swaay, 2016). The relationship between these accounts is shown in Figure 1.

Figure 1: Relationship between thematic accounts and other SEEA-EEA accounts (adapted from Chow 2016)


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The KIP INCA project aims to develop accounts on the extent and condition of ecosystems present in the EU, as well as accounts for selected ecosystem services from these ecosystems and their contribution to the economy and human well-being. The work presented herein describes methodological approaches to develop thematic accounts for biodiversity for the EU that feed into measuring ecosystem condition. Specifically, approaches are set out to collate and organise data reported by EU Member States under the Nature directives as biophysical accounts of species-level biodiversity. This contributes to operationalising a direct approach to assessing condition via tracking the status of biodiversity, as discussed in the 3rd MAES (2016) report and further developed in the KIP INCA discussion paper by the EEA (2017a) on developing ecosystem condition accounts.

This work focuses on testing methodological options for establishing Species Accounts on the basis of currently available data. It helps us to understand how species accounts could be structured given current data sources and how the data foundation could be improved for establishing regular and solid Species Accounts at EU level. The document also includes initial analysis of the environmental conclusions that can be drawn from species trends as represented via these pilot Species Accounts. In doing so, it aims to make a substantial contribution to the implementation of biodiversity accounting at EU level that can inform on the requirements for parameters of ecosystem condition set out above.

The remainder of this report is structured as follows:

Chapter 2: Provides a summary of biodiversity data that could inform accounting for species and ecosystem condition in the EU

Chapter 3: Sets out an approach to compiling Species Accounts for informing on ecosystem condition using data reported under Article 17 of the Habitats Directive

Chapter 4: Sets out an approach to compiling Species Accounts for informing on ecosystem condition using data reported under Article 12 of the Birds Directive

Chapter 5: Provides a set of pilot Species Accounts using Article 17 and Article 12 reporting data for comparison and analysis for Belgium and the EU as a whole

Chapter 7: Presents the conclusions and recommendations for future implementation of Species Accounts in the EU.

Appendix A provides a set of accounts for Slovakia, which complements the examples provided for Belgium in Chapter 5. Appendix B provides a spatial analysis and critical assessment of the species habitat linkages that can support Species Accounting in the EU.


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2 Biodiversity condition parameters MAES (2013) establishes a typology for ecosystems in the EU for the terrestrial, freshwater and marine realms, comprising of 12 ecosystem types. The terrestrial ecosystems are delineated from the Corine Land Cover classifications and comprise of the following 7 types:

urban systems; cropland; grassland; woodland and forest; heathland and shrub; sparsely vegetated land; and, wetlands.

Freshwater ecosystems comprise solely of a ‘rivers and lakes’ ecosystem type. Whereas the marine realm is subdivided in to the following 4 types:

marine inlets and transitional waters; coastal areas; shelf; and, open ocean.

The second MAES (2014) report provides a summary of information that can be used by Member States to assess the condition of these ecosystems (see Table 3 of MAES, 2014). The ecosystem specific and cross-cutting biodiversity related indicators that are discussed for directly inferring the state (or condition) of ecosystems include:

1. Species richness measures.

2. Abundance and distribution of selected species (in particular farmland and woodland birds for respective ecosystem types).

3. Species threat status (specifically the Red List for European Species) or conservation status (as reported under Article 17).

In the context of developing an approach for ecosystem condition accounting under KIP INCA, the EEA (2017a) developed a discussion paper that provides an evaluation of parameters for both direct and indirect assessment of ecosystem condition within the EU. This was tested in a KIP INCA workshop in 2016. Drawing on these discussions, the following requirements are set out for the Species Accounts in the context of informing on ecosystem condition:

• The condition parameters should match critical pressures on, and changes in, ecosystem condition identified in recent MAES work

• As far as feasible condition parameters should be chosen that are applicable and comparable across all MAES ecosystem types

• Where appropriate or necessary ecosystem-specific condition parameters should be included

• The overall number of condition parameters per ecosystem type should not be too high (e.g. in the range of 3 – 5)

• The condition parameters finally chosen should ideally be underpinned by data sets that allow a reliable quantitative analysis of trends at suitable spatial and temporal scale


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• The condition parameters should be linked to levels of ecosystem service delivery.

Table 1 provides an excerpt of the biodiversity related condition parameters provided by EEA (2017a), which are considered to have the greatest potential for tracking ecosystem condition in ecosystem accounting and wider processes.

Table 1 EEA Review of biodiversity based ecosystem condition parameters and data

Note: Green signifies a very good match of the selected condition parameters with themes (e.g., SEEA EEA), orange a partial match and red is no match

The purpose of the work presented herein, is to test approaches to generating accounts of ecosystem condition using the most promising data identified in Table 1 (i.e., Article 17 reporting and Member State bird trends) and critically assess their fitness for supporting the KIP-INCA programme of work (as per the requirements with respect to ecosystem condition set out above). To focus on EU priority issues, the work aligns with the parameters set out in the second MAES (2014) report and data items relevant to species richness; abundance and distribution; and, threat status.

2.1 Article 17 Reporting

The EU Habitats Directive requires Member States to prepare and submit reports on the conservation status of habitats and species of EU Community interest to the European Commission every six years. The term ‘habitats and species of EU Community interest’ reveals that the species covered are generally those of particular conservation importance (i.e., because they are rare, threatened, endemic or highly characteristic). The EEA-ETC/BD (2013) provides a useful note on the content and characteristics of EU Article 17 data. This identifies the following points that are relevant to the ability of Article 17 data to inform a species accounting processes:

The period from 2001 to 2006 includes the first assessments of the conservation status of species. This covers 1,182 species in total

The second round of reporting for 2007-2012 follows an improved reporting methodology and format. This the foreseen format for future reporting


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Conservation assessments are made at two different scales, at Member State Level and EU level, both by biogeographic / marine region

Where a species occurs within two or more biogeographic regions within a Member State, a conservation assessment for that species is required for each biogeographical region. As a consequence there are 6,064 species assessments at Member State level when aggregated across all of the EU Member States

Conservation status assessment results are symbolised as favourable (FV); unfavourable-inadequate (U1); unfavourable-bad (U2); and, Unknown (XX) status

Conservation status is determined on the basis of four parameters: species range, population, suitable habitat and future prospects (EEA, 2015b)

Given that the conservation assessments are for biogeographical regions at a national scale, downscaling the assessment data to finer scales is unlikely to represent ‘on-the-ground’ reality

In consideration of the above, the Article 17 data has the potential to inform accounts at a national scale (or subnational scale where more than one biogeographic region occurs in the same country) using the conservation assessment results of the set of species within that region. There are now two sets of reporting data on conservation assessment data. This allows a typical asset account type structure to be calculated, with open and closing measures of different assessment results and their associated net changes. Whilst this provides the potential to build on the work of Ivanov et al. (2013), which relied solely on the 2001 to 2006 results, some data manipulations are required to deal with non-genuine changes reported between periods. These may reduce the analytical power of the accounts in certain circumstances and are described further in Section 3.1.3.

2.2 Member State bird trends

2.2.1 Article 12

Article 12 of the Birds Directive requires that Member States provide the European Commission with a composite report on the implementation of national provisions under the Birds Directive (starting from 1981). The report allows an assessment of whether the requisite measures have been taken to maintain the population of all species of naturally occurring birds in a wild state in the Member States’ European territory (N2K Group, 2011). An important development in 2011 to the Article 12 reporting system, was the agreement to improve the quality of reporting and deliver data on the actual state and trends of bird populations. At this point, it was decided to change to a 6 year reporting cycle to align with reporting under Article 17 of the Habitats Directive so that information would be available in policy relevant cycles (N2K Group, 2011; EEA, 2015b). Accordingly, the most recent reporting data under Article 12 of the bird’s directive covers the period 2008 to 2012, with the next reporting period comprising the full six year cycle and the period 2012 to 2018 (the reporting


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deadline for Member States is understood to be 31 July 2019 and it is likely to take a year for reporting data to be assessed and made publically available).

The Article 12 reports prepared by Member States now comprise of two parts, concerning; (a) general information about the implementation of the Directive, (b) the size and trends of individual bird species populations and their distributions (EEA, 2015b). The information on birds’ status, trends and distribution is provided for all species occurring on the Member State’s territory and not sub-divided according to Biogeographical region, as with the Article 17 conservation assessments. For the majority of species, the status and trends are estimated during the breeding season. However, for a selection of bird species the status and trends during the winter seasons are also reported. The reporting format is described in detail by N2K Group (2011) and Roscher et al. (2015).

Article 12 data is available in spatial and tabular format for the reporting period of 2008-2012 from the EEA website (EEA, 2015c). The tabular data includes population sizes, ranges and trends (short and long term) for breeding and wintering populations as part of a Microsoft Access database. Whereas the spatial data provides the breeding range and distribution for targeted species of the directive in GIS format, generally at a spatial resolution of 10 x 10km (Roscher et al., 2015). Unlike the Article 17 reporting requirements, there is no assessment of conservation status undertaken by Member States for Article 12, as the term ‘favourable conservation status’, is not used in the Birds Directive (EEA, 2015b). However, the status of bird species populations has been assessed at the EU level by the European Red List of Birds Consortium (under contract with the European Commission) (EEA, 2015b). This approach is set out in the European Red List of Birds Consortium (2014) and comprises a very different set of criteria to that used in the Article 17 conservation status assessments. Nonetheless, trends both datasets provide information on trends relevant to species status and are considered as comparable indicators for ecosystem condition.

An important associated database has been developed by the EEA (2015a) to link species and habitat types to MAES ecosystems. The database contains the MAES ecosystem associations of all bird species considered for reporting under Article 12 of the Birds Directive (in addition to all species and habitats considered for reporting under Article 17 of the Habitats Directive). As such the database provides the information required to present statistics on bird species from a MAES ecosystem perspective, although it should be noted that specific bird species may associate with more than one ecosystem type and the MAES typology is very broad in comparison with typical habitat typologies (e.g., European Nature Information System (EUNIS) habitat classifications).

In consideration of the above, the Article 12 data has the potential to inform accounts that report on species richness measures, population abundance and distribution and species threat or conservation status by ecosystem type. However, a current constraint is that only one reporting period is available.


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2.2.2 EBCC and National Data

European nations use a variety of methods in their bird monitoring schemes, which ultimately support the Article 12 reporting processes, in addition to informing against national objectives. The European Bird Census Council (EBCC) provides a central coordination point for aggregating this data to infer EU level trends via the Pan-European Common Monitoring Scheme (PECBMS) (EBCC, no date b).

The rationale for the PECBMS is that as common birds are good indicators of the health of the environment, therefore, trends in their status can be used to infer the environmental sustainability of land management in the EU. In 2016, the EBCC (n.d.) produced indices for 167 common bird indicators1, of which 39 were included in the common farmland indicators and 34 in the common forest bird indicators. Given these species are identified as useful indicators of environmental health, focusing on these species would be a sensible way of rationalising the Article 12 monitoring data when developing accounts of ecosystem condition.

Under the PECMBS, trends and indices generated by national schemes are integrated and aggregated using various modelling approaches to plug data gaps, fix spurious observations and generate a trend line at the supranational European scale (EBCC, no date b). As such there is no set of harmonised spatially referenced time-series data on bird counts for the 167 identified common species at the EU level. Nonetheless, as identified by the EEA, the data sets collected under these national schemes could support the construction of a set of spatially referenced biodiversity data relevant to the MAES programme of work. In order to assess the potential for spatial data to inform spatial ecosystem accounting and assessment, an engagement exercise between the EEA and the national organisations responsible for coordinating bird monitoring schemes has been initiated.

2.3 Key points The key points from Chapter 2 comprise:

A set of requirements for Species Accounts for informing on ecosystem condition have been identified

Article 17 reporting data has the potential to inform on accounts of ecosystem condition at the biogeographical region / member state scale. However, non-genuine changes between reporting periods introduce some constraints.

Article 12 reporting data has the potential to inform accounts of ecosystem condition using a range of species diversity metrics at Member State scale. However, there is only one set of reporting data available under the new reporting format.

1The EBCC actually produce indicators for 169 species, Oenanthe cypriaca and Sylvia melanothoraxare

not included in the common bird indicators for Europe since they are endemic species of Cyprus


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National bird monitoring data has the potential to inform a more spatial approach to accounting for ecosystem condition. However, this has not been organised into a harmonised dataset at the European scale at this time.


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3 Article 17 Approach The approach for compiling Species Accounts using Article 17 information is based on the results of conservation assessments and associated trend qualifiers reported by Member States for the species of community interest covered by the Habitats Directive. The approach is summarised below and tested at the Member State scale in Chapter 5.

3.1 Overview of measurement approach

3.1.1 Article 17 Species Conservation Status Accounts

The Article 17 Species Conservation Status Accounts organise information on the results of conservation assessments made by Member States. Under the Habitats Directive, separate conservation assessments are required for any species for each biogeographical region within a country. Therefore, if a Member State lies across two or more regions, a conservation assessment is required for each biogeographical region within the Member State in which a given species occurs (EEA, 2015b). The Article 17 Species Conservation Status Accounts developed are based upon the number of species assessment results in each of the following conservation status classes in each period (as defined in EEA, 2015b):

Favourable (FV): Where the habitat or species can be expected to prosper without any change to existing management or policies;

Unfavourable-inadequate (U1): Where a change in management or policy is required to return the habitat type or species to favourable status, but there is no danger of extinction in the foreseeable future;

Unfavourable-bad (U2): Where a species is in serious danger of becoming extinct

Unknown (XX): Where there is great uncertainty

The Article 17 Species Conservation Status Accounts provide a typical asset type accounting structure, showing the stock (number) of each species in each conservation status class in the opening period (e.g., 2006) and the number in the closing period (e.g., 2012). Net changes over the accounting period are then readily calculated. It should be noted that no weighting of the number of assessments is used in the accounts, thus an assessment result for a species occupying a small area of biogeographic region in a country carries the same weight as an assessment result for a species occupying the entire area of a much larger biogeographic region in a country.

In order to aggregate information on Conservation Status an index is proposed. This Conservation Status Index (CSI) is based on the Red List Index, as described in (Bubb et al., 2009) and is presented below. The CSI varies from zero if all the assessment results are ‘Unfavourable – Bad’ and 100 if all assessments are ‘Favourable’. It should


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be noted that all assessments with an ‘Unknown’ conservation status are omitted from the calculation of the CSI.

0 Favourable

1 Unfavourable - Inadequate

2 Unfavourable - Bad

- Unknown

𝐶𝑆𝐼𝐴𝑅𝑇17 = 100 ∗ [1 − ∑ 𝐶𝑆𝐼𝑛𝑎 ∗ 1 + 𝐶𝑆𝐵𝑎𝑑 ∗ 2

𝐶𝑆𝐹𝑎𝑣+𝐼𝑛𝑎+𝐵𝑎𝑑 ∗ 2]

Where 𝐶𝑆𝐼𝑛𝑎 in the number of assessment with an inadequate CS

Given the definition of ‘Favourable’ status in the habitats directive, changes in overall conservation status require relatively large changes in the underlying conservation status parameters to be apparent (i.e., species range, population, suitable habitat and future prospects, EEA, 2015b). In order to provide a more nuanced understanding of the direction of travel within unfavourable status categories, Member States report a qualifier expressing the trend of conservation status (EEA, 2015b). This allows more subtle changes (improvement or deterioration) within the unfavourable classes to be identified. The four trend qualifiers within the ‘Unfavourable’ status categories comprise:

Improving.

Stable.

Declining.

Unknown.

In order to integrate the information on trends within the Article 17 Species Conservation Status (CS) Accounts, the following indicators are proposed:

‘Art17 condition in CS’ based on the proportion of species of a favourable status or an unfavourable status but with improving trends reported in 2012. The indicator gives an overview of the condition of Article 17 species and varies from 0 (no reported Article 17 species in favourable conservation status2 or in unfavourable conservation status but with improving trends in 2012) to 100 (all reported Article 17 species are of favourable status or unfavourable but show improving trends in 2012)

o (Number of favourable + (unfavourable & improving)) / (Number of species3) * 100.

‘Art 17 trend in CS’ communicates if species conservation status or trends are improving or deteriorating overall. The indicator varies between -100 (all

2 As Member States are not required to report trend qualifiers for species with favourable conservation

status, the number of species of this status need to be included in the numerator as their status is

considered indicative of ‘good’ ecosystem condition. 3 This is all species for which conservation assessments are reported on, including those where the

conservation assessment class and trend qualifiers are reported as ‘Unknown’


19

species have unfavourable conservation status and declining trends) and + 100 (all species have moved to favourable conservation status from unfavourable / unknown or are of unfavourable conservation status but with improving trends reported in 2012).

o (Number of improving – declining + gross increase favourable4) / (Number of species) * 100.

‘Intensity of changes in CS’, this indicator varies between 0 (when no species move to a favourable conservation status class from a different status class or are reported to have improving or declining trends within the unfavourable class) to 100 (when all species are either moving to a favourable conservation status or exhibiting improving or declining trends within the unfavourable status classes). It gives an indication of the % of species that have change during the period.

o (Number of improving + declining + increase favourable) / (Number species) * 100.

‘Coverage of trends in CS’, given Member States often report “unknown” trend qualifiers and conservation status, this indicator is proposed to communicate the proportion of such assessments from the overall set. This indicator varies from 0 (all species assessments results are either unknown conservation status or unfavourable conservation status with unknown trend) to 100 (all species assessments are favourable conservation status or unfavourable conservation status but with reported trends)

o (Number of improving + declining + stable + favourable) / (Number species) * 100.

Finally, the species and MAES ecosystem associations proposed by the EEA (2015a) are used to associate conservation assessment results for species reported under Article 17 of the Habitats Directive with different ecosystem types.

3.1.2 Proposed Structure for Article 17 Species Conservation Status Account

The flexibility exists to organise the Article 17 data to compile Species Accounts in multiple ways, for instance by aggregating assessment results by Member State, MAES ecosystem type, biogeographical region or by species group. Table 2 provides the proposed structure for testing the Article 17 Species Conservation Status Accounts at Member State scale by ecosystem type that aligns with the Article 12 based Species Accounts introduced in Chapter 4. As shown in Table 2, conservation assessment and trend qualifier results are grouped in rows by biogeographical region type. The columns organise this data according to the ecosystem preferences of the assessed species. The final column presents this information at the aggregate national level. It

4 This is the gross number of species moving to a favourable status and not the net change between

favourable and non-favourable status.


20

should be noted that this is not a straightforward aggregation across columns, as a single species may be associated with more than one ecosystem in any given biogeographical region.

Table 2 A Proposed Structure for Article 17 Species Conservation Status Account

Note: The Conservation Status Index (CSI) is not included in Table 2 but could be entered as a row

beneath the ‘Total’ row for each Biogeographical region (Bioregion).

The top section of Table 2 presents the situation in 2001-2006, based on the results of the conservation assessments from the 2001 to 2006 reporting cycle. In the actual compilation of the accounts, it has been necessary to back cast some of the 2012 conservation assessment results in order to inform this section of the account. This procedure is described in Section 3.1.3. The middle section of Table 2 presents the information on the trend qualifiers, together with the number of favourable and unknown conservation assessment results (for which no trend qualifiers are available)

Bioregion 1

Urban

2

Cropland

3

Grassland

4

Forest

5

Heathland

and shrub

6

Sparsely

vegetated

land

7

Inland

wetlands

8

Rivers

and lakes

Total by

CS

Conservation status 2006

FV Favourable

U1 Inadequate

U2 Bad

XX Unknown

Total

FV Favourable

U1 Inadequate

U2 Bad

XX Unknown

Total

Conservation status 2012 and trend in CS

1 Favourable

2 Unfavourable - Improving

3 Unfavourable - Unknown trend

4 Unknown

5 Unfavourable - Stable

6 Unfavourable - Declining

Total

Overall indexes

ART17 condition in CS

ART17 trend in CS

Intensity of changes in CS

Coverage of changes in CS

1 Favourable

2 Unfavourable - Improving

3 Unfavourable - Unknown trend

4 Unknown

5 Unfavourable - Stable

6 Unfavourable - Declining

Total

Overall indexes

ART17 condition in CS

ART17 trend in CS

Intensity of changes in CS

Coverage of changes in CS


FV Favourable

U1 Inadequate

U2 Bad

XX Unknown

Total

FV Favourable

U1 Inadequate

U2 Bad

XX Unknown

Total

Bioregion 2

Bioregion 1

Bioregion 2

Bioregion 1

Bioreion 2

Bioregion 1


21

as reported by Member States in 2012. The middle section of Table 2 also presents the indicators derived from this information, as described above. The bottom section of Table 2 presents the situation in the 2007-2012 period, based on the results of the conservation assessments from the 2007-2012 reporting cycle.

3.1.3 Getting the data together

The EEA (2017) provides a database of Member State Article 17 reporting data as a Microsoft Access file5. Within this database a table is also provided of EU level aggregations of the Article 17 data, where the Member States' reports are aggregated using an agreed methodology (as described in EEA, 2015b). A table is also provided in the database to associate species reported on under Article 17 with their preferred ecosystem type within different biogeographical regions. This is based on the linkages of species to MAES ecosystem types by biogeographical region proposed by the EEA (2015a). This allows the conservation assessment results for species to be organised on the basis of their MAES ecosystem preferences within the Article 17 Species Conservation Status Accounts.

Before compiling the accounts, some pre-processing of the data is required in order to associate the ‘Speciescode’ and ‘Speciesname’ fields for identifying species in the EU and Member State data tables with the ‘Speciesname’ field in the linkages of species to MAES ecosystem type data table. This reflects taxonomy is an evolving field and changes in nomenclature may arise in different data tables (e.g., Barbus comizo is also named Barbus comiza). For the 1,247 species in the EU data table of conservation assessment results in 2012, 1,215 species can be successfully associated with their preferred ecosystem. Of these, only those that are also confirmed for use in Member State level statistics are retained for use in the compilation of the accounts (i.e., the field “USE FOR STAT” is YES in both the Member State and EU level data tables for the species assessment result). This results in the omission of four species assessment results, all associated with Portugal. As such, 1,211 species assessment results from the 2012 Article 17 reporting data are used to compile the accounts, of which various subsets inform the Article 17 Species Conservation Status Accounts at the Member State scale.

3.1.4 Dealing with data gaps

In order to realise a coherent account of changes in conservation status between reporting periods a further manipulation of the data is required. This is because changes in conservation status reported by Member States may be an artefact of improved knowledge, more or less accurate data becoming available, changes in taxonomy or changes in thresholds used for the assessment (EEA, 2015b). As described in the State of Nature Report for the EU (EEA, 2015b), Member States should report where changes in conservation status are due these types of ‘non-genuine’ or unknown reasons and where they are due to genuine improvements or deteriorations (e.g., due to natural reasons or management interventions). These reasons are coded and recorded in the Article 17 database, thus allowing ready qualification of genuine or

5 The European Environment Information and Observation Network also provides a useful web tool for

investigating the Article 17 data, including EU level aggregations of this data (see EIONET, no date b)


22

non-genuine changes in conservation status. In order to eliminate non-genuine changes in conservation assessment results between in 2006 and 2012 from the accounts, the following ‘back casting’ procedure is employed:

Where a change is reported as ‘genuine’ in 2012 (or no change), the conservation assessment result reported in 2006 is retained.

Where a change is reported as ‘non-genuine’ or the reason ‘unknown’ and a qualifier trend is known, the 2012 conservation status assessment result is assigned (or back casted) to 2006 and the original result reported in 2006 discarded.

Where a change is reported as ‘non-genuine’ or the reason ‘unknown’ and the qualifier trend is reported as ‘unknown’, the 2006 conservation assessment result is assigned ‘unknown’ status.

The above treatment implies that changes in the aggregations of the conservation status assessments by biogeographical region should be interpreted with some care. Notably, for accounts where a large number 2012 conservation assessment results have been back cast in 2006, the situation between accounting periods will appear relatively stable. For example, in a biogeographical region with no genuine changes, the results for 2006 will comprise solely of the back-casted assessment results from 2012. This has clear implications for the proposed CSI, such a scenario will result in the same CSI value being reported in 2006 and 2012. In order to provide an insight into the influence of the ‘non-genuine’ changes in the data, a column can be added to the accounts, which indicates the % of genuine changes in conservation status (this should include where there are also no changes recorded). However, this has not been done for the Article 17 based accounts presented herein.

The use of the trend qualifier data from 2012 provides a way of ameliorating the influence of reported non-genuine changes on the Article 17 Species Conservation Status Accounts. Specifically, this is achieved through the use of the ‘Art17 Condition in CS’ and ‘Art 17 trend in CS’ indicators described in Section 3.1.2, which are considered to prove useful potential indicators of ecosystem condition based on the species conservation assessments reported under Article 17 of the Habitats Directive.


It appears feasible to construct accounts of species conservation status using available Article 17 reporting data.

A Conservation Status Index is proposed to aggregate data on conservation status

In order to overcome the relative stability of conservation status (CS) assessment results between periods a set of trend indicators are proposed, comprising: Art 17 condition in CS; Art 17 trend in CS; Intensity of change in CS;


23

and, Coverage of trend in CS. These are calculated using the trend qualifiers reported under Article 17

A ‘back-casting’ procedure is proposed to eliminate non-genuine changes in conservation assessment results between 2006 and 2012


24

4 Article 12 Approach In order to compile accounts that reflect the status of bird species and their diversity in the EU two broad measurement approaches are developed for testing:

Using population status as assessed by the European Red List of Birds Consortium (Species Status Accounts); and,

Using population abundance for bird species (Species Abundance Accounts).

Both approaches are tested in the context of Member State and EU wide accounts of ecosystem condition.

4.1 Overview of measurement approaches

4.1.1 Species Status Accounts

The Species Status Accounts organise information on the number of different species in each population status category (i.e., threatened, secure, not secure6 and unknown – as described by the European Red List of Birds Consortium, 2014). From this information, an aggregated index reflecting the overall threat status at the EU scale of the set of bird species can be derived. This is conceptually aligned with the CSI proposed for the Article 17 data in Section 3.1.1. Again the index (I) is calculated in much the same fashion as a Red List Index (see Bubb et al. 2009), as set out below:

𝐼 = 100 ∗ (1 − (

∑ 𝑊𝐸𝑈 𝐴𝑠𝑠𝑒𝑠𝑠𝑁𝑆=1

𝑊𝐸𝑈 𝑇ℎ𝑟𝑒𝑎𝑡 ∗ 𝑁)) Equation 1

Where 𝑊𝐸𝑈 𝐴𝑠𝑠𝑒𝑠𝑠 is the weight applied to a species population status as follows: Secure = 0. Not Secure = 1, Threatened = 2 and 𝑁 is the number of bird species in these categories indexed over 𝑆. Species with an ‘unknown’ conservation status are not included in the calculation of 𝐼.

Ideally, the accounts would show the opening and closing numbers of each species in the different categories and the value for 𝐼 calculated above. The net changes would reveal the trend in bird species threat status over the accounting period. Assuming the status of birds in MAES ecosystems is correlated with improving or declining condition, 𝐼 (or any other bird status related statistic) can be used as an indicator of ecosystem condition (this assumption is discussed in the conclusions). However, the 2007 to 2012 period represents the first round of Article 12 reporting under the new format and it is not possible to construct accounts with opening and closing measures until the next reporting phase has been completed.

6 Comprising the categories of Near Threatened, Declining and Depleted, as proposed in (European Red

List of Birds Consortium, 2014)


25

To overcome the current lack of a time-series of ‘new format’ Article 12 reporting data, it is proposed to make use of the short (12 years prior to reporting) and long-term (from circa 1980) trends reported for bird species by Member States. These trends are combined to provide an overall trend of species as stable; increasing; declining or unknown using the treatment detailed in

Table 3 Treatment for combing short and long term trend results as an overall trend

Where on trend result is fluctuating Where trend results differ

Short-term Trend

Long-term Trend

Overall Trend

Short-term Trend

Long-term Trend

Overall Result

F F 0 0 + +

F 0 0 0 - -

F + + 0 X 0

F - - - + X

F X X - X -

0 F 0 - 0 -

+ F + + - X

- F - + X +

X F X + 0 +

X 0 0

X - -

X + +

Where: 0 = stable; F = Fluctuating; + = Increase; - = decrease; X = unknown

Using this trend data on individual species, the following indices are calculated for each population status category:

‘Prevailing trends’ of change in population size based on the similar indicator

proposed by Ivanov et al. (2013). This varies between -100 (all species declining)

and +100 (all species either stable or improving, considered indicative of good

condition):

o (No. Species with Stable + Increasing – declining trends) / (Total no.

species) * 100

‘Overall Trend’ is comparable to the ‘Art 17 Trend in CS’ indicator7. This varies

between -100 (all species declining) and +100 (all species increasing)

o (Increase – declining) / (Total no. Species) * 100

‘Intensity of Change’, this varies between 0 (no species increasing or declining)

and 100 (all species either decreasing or declining):

o (Increase + declining) / (Total No. Species) * 100

7 (No. of Improving – declining + increase favourable) / (No. Species) * 100


26

‘Coverage of Trends’, this varies between o (all species have an unknown trend)

and 100 (trend data is available for all species):

o (1 - (No. Unknown / No. Species)) * 100

The use of trend indicators at this stage is considered an interim approach until the next round of Article 12 reporting data becomes available, which will allow a more familiar ‘asset’ account structure of opening and closing stocks to be compiled.

Finally, in order to associate bird species reported under Article 12 with ecosystems, we use the association of species with MAES ecosystems proposed by the EEA (2015a). As described by Roscher et al. (2015), these MAES ecosystem associations are included in the Article 12 database to facilitate statistics from an ecosystem perspective. However, the linkages included in the Article 12 database are based on linkages between species and MAES ecosystem types at an EU level - rather than by biogeographic region as set out in the note by the EEA (2015a). In order to make these associations at the EU level, bird species were limited to three ecosystem type preferences each (comprising the three most commonly referenced across all relevant biogeographic regions) (Roscher et al., 2015). As shown in Figure 2, these associations allow the disaggregation of the national level reporting data to derive subnational accounts, organised by ecosystem type. It should be noted that as some birds have preferences for more than one ecosystem, the status of the same species could be used to inform against the condition of up to three ecosystems, for example both forest and urban ecosystems (where these are relevant preferences).

Figure 2 Disaggregation of Article 12 data using species and ecosystem linkages

4.1.2 Proposed Structure for Species Status Account

Table 4 provides the proposed structure for the Species Status Account. As shown in Table 4, species are grouped in rows by the EU scale population status categories of: Secure; Not Secure; Threatened; and, Unknown. The columns organise the data for the number of species and derived trends according to their preferred ecosystem type. The final column presents this information at the aggregate national level. It should be noted that this is not a straightforward aggregation across columns, as described a single species may have preferences for more than one ecosystem.

The top half of Table 4 presents the situation in 2005-2007, as reported under Article 12 for this period. Given the substantial update to the Article 12 reporting process it


27

has not been possible to harmonise this data with that collated under the 2008 – 2012 reporting period. However, if this were possible this section would contain the number of species in each group for this ‘opening period’ and the derived aggregated threat index. This aggregate index is calculated using Equation 1, the calculation is also provided below Table 4.

The ‘Trends in Status 2008 - 2012’ section of Table 4 presents the indicators described above, calculated from the trends in constituent species of each population status group. These are included at this stage as an interim approach to provide some indication of change in recent years as it has not been possible to determine the number of species in each group for the opening period.

Table 4 Proposed Structure for Species Status Account

The bottom part of Table 4 provides the number of species in each group for the ‘closing period’, as reported under the 2008-2012 Article 12 reporting cycle. The ‘Net

Coastal Cropland Grassland Heathland Shrub Marine Inlets Rivers Lakes

Sparsely

Vegetated Urban Wetlands

Woodland

Forest

Not Secure

Secure

Threatened

Unknown

Aggregate Index

Not Secure

Secure

Threatened

Unknown

Not Secure

Secure

Threatened

Unknown

Not Secure

Secure

Threatened

Unknown

Not Secure

Secure

Threatened

Unknown

Not Secure

Secure

Threatened

Unknown

Aggregate Index

Not Secure

Secure

Threatened

Unknown

Aggregate Index1 This is subject to confirmation and examples of a potential classification system are provided in the above table2 The historic Article 12 reporting format may mean it is not possible to ascertain the situation for 2005-20073 These are the three best measures to be evaluated for use in the accounts4 (Stable + Increasing – decreasing) / (No. species this is all including unknowns) * 1005 (Increase – declining) / (No. Species this is all including unknowns and stable) * 100

NB: The above is analogous to the Overall Trend in CS in the Art 17 approach6 (Increase + declining) / (No. Species) * 1007 (1 - (No. Unknown / No. Species)) * 1008 Where population, threat status or range measures are known the net change between reporting periods should be recorded here

Aggregate index =

Where Secure = 0

Not Secure = 1

Threatened = 2

S = Index for species

N = Total number of species

Situation 2008 - 2012

Number of

Species (S)

Trends in Status 2008 - 2012

Prevailing

Trends4

Overall Trend5

Intensity of

change6

Coverage of

trends7

Net Change8

Number of

Species

Number of

Species (S)

Bird group

classes1

MAES

All

Ecosystems

Situation 2005-20072

∗ −∑ =

∗

𝑊𝐸𝑈 𝐴𝑠𝑠𝑒𝑒𝑠𝑠


28

Change’ section would capture the change between the opening and closing measures in Table 4. It will be possible to calculate these net changes when the next round of Article 12 reporting data becomes available.

The Species Status Account provides a means of communicating the number of species and the population trends within the population status categories within Member States. The accounts will reveal which Member States and ecosystem population trends of species within different population status categories are doing better than elsewhere. However, it is acknowledged that these population status categories have been determined at the EU scale and are, partially, derived from aggregation of the long and short term population trends reported by Member States. Therefore, there is some circularity in this approach and the opening and closing measures of species in different population status categories would: a) require updated EU-wide population status assessments or derivation of national status assessments; and, b) may not show significant change over the short to medium terms.

4.1.3 Species Abundance Accounts

Species abundance provides a more sensitive measure of biodiversity than species richness alone (UNEP-WCMC, 2015). As such, the minimum and maximum population abundance measures reported by Member States for bird species provides a potentially very useful measure of bird species responses to ecosystem degradation.

In addition to considering the populations of all bird species in the accounts, three classification approaches are tested for aggregating bird species data reported under Article 12. The purpose of testing the classification approaches is to establish if different groupings of bird species are feasible and which may be the most useful as indicators of changes in the condition of certain ecosystems. For example, EBCC Common birds are identified as being particularly relevant indicators of environmental health in ordinary landscapes (EBCC, no date b), whereas EU Threatened species may be less likely to be sensitive to changes of condition in broad MAES ecosystem types. As such there is interest in identifying if any consistent or contradictory findings between groupings emerge. The classifications tested comprise:

All species according to European Threat Status: Comprising the EU level Secure, Not Secure, Threatened and Unknown categories developed by the European Red List of Birds Consortium (2014) as used in the Species Status Account.

SPA-Trigger species: species listed in Annex 1 of the Birds Directive and selected migratory species for which Member States should classify Special Protection Areas (SPAs) for their conservation (EEA, 2015b)

EBCC Common Species: Comprising a subset of 1668 species (of which 39 are specific for farmland and 34 for forest and the remainder ‘Other’).

8 The EBCC lists 167 common bird species, however, it was not possible to readily identify the record

relating to Serinus citronella in the Article 12 reports.


29

The availability of abundance estimates greatly increases the biodiversity indicators that can be derived from the Article 12 data. Buckland et al. (2005) and Van Strien et al. (2012) both provide useful synthesis of common indicators of biodiversity. However, as Article 12 data is only available for one period, the use of relative abundance indicators (a common practice in bird surveys) is precluded at this stage. Following Buckland et al. (2005), the three aspects of biodiversity considered of most interest for inferring ecosystem condition comprise: abundance, richness and evenness. As described by Van Strien et al. (2012), few composite indicators exhibit all of the mathematical properties desirable for tracking changes in biodiversity across all three of these aspects. Therefore, the approach at this stage is to develop the following bird species-diversity indicators using the Article 12 data to draw inferences on ecosystem condition:

Total population abundance for a group of bird species (i.e., the total number of individuals).

Species richness for a group of bird species.

Population evenness of a group of bird species (high evenness reflects a more diverse scenario where many species have similar abundance and no single species dominates).

The total abundance is estimated based on the sum of the average populations of bird species reported in that category (this is based on the average of the minimum and maximum population sizes reported by the member states). However, there emerges a significant difference in organising information in the Species Status and Species Abundance Accounts. As a bird species may make use of multiple ecosystems, variations in the condition of these individual ecosystems can influence overall status. However, as a bird can only have one physical manifestation a treatment is needed to disaggregate national abundance measures across preferred ecosystem types. As such the national abundance measures reported under Article 12 are divided equally across all the ecosystems that the bird species use (e.g., if a bird species has preferences for urban and forest ecosystems the national abundance will be split ½ for each ecosystem). This is acknowledged as a simplifying assumption, this treatment does not consider the relative extent of each preferred ecosystem within the ecosystem accounting area or the strength of preference for different ecosystems by species.

The population evenness of a group of bird species is measured using the Shannon’s Index.9 This takes both the number of species and their abundances into account and

9 As described in Buckland et al. (2005) Simpsons index (D) may be more sensitive to changes in

relative abundances due to environmental perturbations (e.g., pollution incidents) than the Shannon’s

Index. However, the Shannon’s Index (𝐻) is favoured as the incorporation of the logarithmic terms

means that the index is more sensitive to changes in populations of rarer species than the Simpsons

Index. Where 𝑝𝑖 is the proportion of the total species abundance attributed to species 𝑖: 𝐻 =

−∑ 𝑝𝑖𝑖 log𝑒(𝑝𝑖). This property is desirable when population abundance estimates for different species

vary by orders of magnitude. It is also expected that some species will naturally have smaller


30

provides low values when a few species dominate and high values when no single species dominates (Van Strien, Soldaat and Gregory, 2012). The Shannon Index varies between zero (when just one species is present in a dataset) and natural log of the number of species in the dataset (when all the species are equally common, with 1 species being a particular case) (Peet, 1975). As such, it potentially conveys more information on biodiversity than a dominance indicator, such as the Simpsons Index, via its sensitivity to species richness. This has utility in a wider accounting context as it integrates information on bird species richness and evenness is a single condition parameter. However, it should be noted that such indices are very much context specific. This allows trends in bird species-level diversity in ecosystem types to be compared between periods and, potentially, track progress in terms of ‘improving’ condition. However, attaining ‘good’ condition requires ecosystem, and likely national or local, reference levels to be determined.

In order to overcome the absence of two time periods for the Article 12 reporting data, the same ‘Prevailing’, ‘Overall’, ‘Intensity of Change’ and ‘Coverage of’ trends are calculated in order to provide the necessary temporal insight into biodiversity condition. These are calculated in exactly the same way as described for the Species Status Account.

4.1.4 Proposed Structure for Species Abundance Account

Table 5 provides the proposed structure for the Species Abundance Account, based on

using all bird species records. The structure follows the row and column format for

Table 4 and can readily be updated to consider EBCC common bird, population status

or SPA-Trigger status as grouping categories. The top part of Table 5 provides the

‘opening measures’ for the overall aggregate abundance of species, the species richness

in this category and the associated Shannon’s Index as measure of both species

richness and evenness. The middle part of Table 5 presents the same trend indicators

as described for the Species Status Account in Table 4. The bottom part of Table 5

presents the ‘closing measures’ for the abundance, number of species and diversity

measure for each common bird category, as reported in the 2008-2012 reporting cycle.

Again, net changes could also be recorded in Table 5 if opening and closing measures

were available. It is anticipated these will be available during the next round of Article

12 reporting, at which point the Status and Trend indicators provided in the middle

section of Table 5 could be removed from the account

populations, for example a larger extent of ecosystem will be required to meet the needs of bird species

with high biomass compared to low biomass. It should be noted, there is no reason why the accounts

could not be readily updated to different indicators (e.g., a Simpsons Index) in the future and this

would be trivial to calculate in historic accounts where the population abundance data was

appropriately organised.


31

Table 5 Proposed Structure for Species Abundance Account using Article 12 data

4.1.5 Getting the data together – Member State Accounts

The EEA (2015c) provides a database of Member State Article 12 reporting data as a Microsoft Access file10. This comprises a total of 7,259 species and sub-species records each assigned to their contributing Member State country (separate country codes are provided for the Gibraltar, Madeira, Azores and Canary island areas). Breeding bird populations are believed to be the more sensitive indicators of ecosystem condition than non-breeding populations (e.g. migrants and wintering species). As such, all records for non-breeding birds as reported by Member States and in the EU level assessment of breeding bird status completed by the European Red List of Birds Consortium are filtered from the data used to create the accounts. The record for Perdix perdix italia is also filtered out as this sub-species became extinct in 2001 (EEA, 2015b). In addition 3 further records are dropped from the dataset due to the absence of both short and long term population trend data. This results in a total of 5,407 records remaining. These are used to construct the Member State Species Status Accounts. It should be noted that this treatment results in the omission of all non-native species except Phasianus colchicus (Ring necked pheasant), which is included is assessed by the European Red Lists of Birds Consortium as ‘Secure’ and is included as a data record in the accounts.

The information on species’ ecosystem preferences is then added to the individual records based on the bird species to ecosystem linkages included in the Article 12

10 The European Environment Information and Observation Network also provides a useful web tool for

investigating the Article 12 data, including the EU level population assessments carried out by the

European Red List Consortium (see EIONET, 2014)

Bird Species Population Based Account Using All Article 12 Data for 2007 and 2012

Coastal Cropland Grassland

Heathland /

Shrub

Marine

Inlets

Rivers /

Lakes

Sparsely


Woodland /

Forest Shelf

Open

Ocean

Total abundance

(No. individuals)

Number of Species

Shannon's Index

Prevailing Trends4

Overall Trend5

Intensity of change6

Coverage of trends7

Total abundance

(No. individuals)

Number of Species

Shannon's Index

Total abundance

(No. individuals)

Number of species

Shannon's Index1 This is subject to confirmation and examples of a potential classification system are provided in the above table2 The historic Article 12 reporting format may mean it is not possible to ascertain the situation for 2005-20073 These are the three best measures to be evaluated for use in the accounts4 (Stable + Increasing – decreasing) / (No. species this is all including unknowns) * 1005 (Increase – declining) / (No. Species this is all including unknowns and stable) * 100

NB: The above is analogous to the Overall Trend in CS in the Art 17 approach6

(Increase + declining) / (No. Species) * 1007

(1 - (No. Unknown / No. Species)) * 100

All

Ecosystems




Net Change8

MAES


32

database (as described in Roscher et al. 2015). Because some birds have preferences for multiple ecosystems this increases the number of records to 10,795. This dataset is used to construct the Species Status Accounts disaggregated by ecosystem type.

There are potentially substantial inconsistencies in the quality of population estimates for bird species reported by Member States. For the Species Abundance Accounts, including populations estimates that are uncertain could impact on their ability to signal when changes in ecosystem condition are impacting on bird species. However, the new Article 12 reporting process allows identification (and exclusion) of those records that suffer the greatest inaccuracy. Accordingly, all records are filtered out where the type of estimate for population is ‘minimum’11; the method is given as ‘Absent Data’; the quality of the estimate Poor (not accurate to within 50%); or, is null. For the Species Abundance Accounts, this results in 4,463 records for Member States (selected from 5,407). For the Species Abundance Accounts disaggregated by ecosystem type this results in 8,974 records (selected from 10,795).

4.1.6 Getting the data together – EU Level Accounts

Generally accounts should allow aggregation of information across different contexts, including spatially. However, in the case of biodiversity there are often constraints associated with spatial aggregation and associated indicators are often scale dependent. For instance, bird species abundance will aggregate readily via the Member State accounts, however, species richness will not as the same species can occur in several countries simultaneously. The process of aggregating trends and evenness measures across ecosystems becomes even more challenging.

However, as described in the State of Nature in the EU report, Member State data has already been combined to produce overall population sizes and trends for each bird taxon (EEA, 2015b). For breeding bird taxa, there is a specific database containing 454 bird species records that includes EU level population estimates and trends, which is included with the Article 12 database (EEA, 2015c). All 454 records are used directly to generate EU level Species Status Accounts and Species Abundance Accounts, thus avoiding the need for complicated aggregation procedures and making the best use of work already completed. The procedure for associating ecosystem preferences with these individual species records generates 1,073 records to use for compiling the Species Status Accounts and Species Abundance Accounts disaggregated by ecosystem type (although 6 species are dropped during this process as linkages to breeding ecosystem preferences could not be made).


It appears feasible to construct Species Status Accounts and Species Abundance Accounts using Article 12 reporting data

11 where insufficient data exists to provide an accurate estimate, but where that given is known to be a

considerable underestimate


33

The proposed Species Status Accounts are based on the number of species in different EU threat status categories

The proposed Species Abundance Accounts are based on species richness, abundance and evenness measures

Four classification approaches are proposed for testing the calculation of Species Abundance Accounts comprising: using all bird data; splitting bird data in European Threat Status categories; using bird data for SPA-Trigger and Non-Trigger species; focusing on EBBC Common Birds

A set of indicators comparable with those proposed in Chapter 3 for the Article 17 approach are proposed to deal with absence of two comparable sets of Article 12 reporting data. These are an interim measure to communicate some information on change in species status until the next round of Article 12 reporting data becomes available (estimated 2019)


34

5 Testing Accounts To test the feasibility of compiling Species Accounts, this chapter presents tables and accounts using the approaches described in the Chapters 3 and 4. In order to evaluate if the different accounting approaches provide a coherent story of ecosystem condition, Species Accounts were compiled for Belgium using the Article 17 and Article 12 datasets and compared. Finally, Species Accounts using the Article 12 data only are presented for the EU as a whole. In addition to the accounts provided for Belgium, Appendix A provides a complementary set of accounts for Slovakia that can inform wider analysis of the proposed accounting methodology.

5.1 Belgium

5.1.1 Article 17

Table 6 provides the Article 17 based Species Account for Belgium based on reported

Conservation Status of species and the trends in Conservation Status between 2006

and 2012. As Table 6 shows, for the period 2007-2012, 60 conservation assessments for

species were completed for the Atlantic biogeographical region, 64 for the continental

and only 3 for the Marine Atlantic biogeographical region. For Forests, Inland

Wetlands and Rivers & Lakes, there are in excess of 20 conservation assessment results

for the two terrestrial biogeographic region. With the exception of 12 conservation

assessments in urban ecosystems for the continental biogeographic region, there are

less than 10 conservation assessments completed in the other ecosystem types in each

biogeographical region (with 5 or less in croplands).

Based on the ‘Art17 condition in CS’ indicator, Table 6 reveals that the condition of

cropland, grassland and urban ecosystems in the Atlantic Bioregion for Belgium are

relatively poor. For the Continental region heathland & shrub is in relatively the worst

condition and rivers & lakes the best. It is not possible to draw any meaningful

conclusions for ecosystems in the Marine Atlantic biogeographical region given the

paucity of conservation assessment results.

The ‘Art17 trend in CS’ indicator reveals conservation status is generally improving for

species in rivers & lakes, stable or showing moderate downward trends in inland

waters, heathland & shrub, forest and grassland and showing substantial deterioration

in cropland and urban ecosystems in the Atlantic bioregion. For the Continental

region, the ‘Art17 trend in CS’ indicator is stable in croplands, forest and rivers and

lakes, and shows small improvements in urban and small deteriorations in grassland,

heathland and shrub and inland wetland ecosystems.

There are no consistently positive ‘Art17 Trend in CS’ results for the same ecosystem in

different biogeographic regions. However, negative ‘Art17 Trend in CS’ results are

observed in forest, grassland and heathland & shrub in both terrestrial biogeographical

regions. Furthermore, the ‘Art17 Trend in CS’ in Table 6 reveals there is no national

overall improvement in conservation status of species in cropland or inland wetlands


35

and no overall deterioration of conservation status of species in sparsely vegetated

land for Belgium.

Table 6 Account for Belgium using Article 17 Approach

Bioregion 1

Urban

2

Cropland

3

Grassland

4

Forest

5

Heathland

and shrub

6

Sparsely

vegetated

land

7

Inland

wetlands

8

Rivers

and lakes

9

Marine Inlets and

transitional waters

11

Marine

coastal

water

12

Marine

shelf

Total by

CS


FV Favourable 2 2 9 2 7 4 14U1 Inadequate 2 4 5 5 13U2 Bad 2 1 5 1 9 10 24XX Unknown 2 3 4 3 1 3 6 9Total 4 2 8 22 6 1 24 25 60FV Favourable 3 1 2 7 2 1 5 7 17U1 Inadequate 4 2 3 2 1 2 2 18U2 Bad 2 1 5 2 1 2 7 8 21XX Unknown 3 1 1 10 3 2 7 7 8Total 12 5 8 22 8 6 21 24 64U1 Inadequate 2 2 2U2 Bad 1 1 1

2 3 1 3


1 Favourable 1 1 5 2 4 2 92 Unfavourable - Improving 3 5 9 123 Unfavourable - Unknown trend 1 3 1 3 1 64 Unknown 1 2 2 1 2 3 75 Unfavourable - Stable 3 1 1 5 4 96 Unfavourable - Declining 2 2 1 8 2 5 6 17Total 4 2 8 22 6 1 24 25 60Overall indexes

ART17 condition in CS 25.0 0.0 12.5 36.4 33.3 0.0 37.5 44.0 35.0

ART17 trend in CS -50.0 -100.0 -12.5 -22.7 -33.3 0.0 0.0 12.0 -8.3

Intensity of changes in CS 50.0 100.0 12.5 50.0 33.3 0.0 41.7 60.0 48.3

Coverage of changes in CS 75.0 100.0 62.5 77.3 66.7 100.0 79.2 84.0 78.3

1 Favourable 4 1 8 1 2 4 7 172 Unfavourable - Improving 3 2 2 3 1 3 3 4 113 Unfavourable - Unknown trend 2 1 1 1 1 4 5 94 Unknown 1 1 5 1 1 2 85 Unfavourable - Stable 1 1 1 1 36 Unfavourable - Declining 1 2 3 4 4 1 8 5 16Total 12 5 8 22 8 6 21 24 64Overall indexes


ART17 trend in CS 16.7 0.0 -12.5 -4.5 -37.5 33.3 -23.8 -4.2 -7.8



1 Favourable

2 Unfavourable - Improving 1 1 13 Unfavourable - Unknown trend 1 1 14 Unknown

5 Unfavourable - Stable 1 1 16 Unfavourable - Declining

Total 2 3 1 3Overall indexes

ART17 condition in CS 50.0 33.3 0.0 33.3

ART17 trend in CS 50.0 33.3 0.0 33.3

Intensity of changes in CS 50.0 33.3 0.0 33.3

Coverage of changes in CS 50.0 66.7 100.0 66.7


FV Favourable 1 1 5 2 4 2 9U1 Inadequate 2 2 1 7 6 12U2 Bad 2 2 3 13 3 11 14 32XX Unknown 1 2 2 1 2 3 7Total 4 2 8 22 6 1 24 25 60FV Favourable 4 1 8 1 2 4 7 17U1 Inadequate 4 3 3 6 4 2 6 5 18U2 Bad 3 2 3 3 2 2 10 10 21XX Unknown 1 1 5 1 1 2 8Total 12 5 8 22 8 6 21 24 64U1 Inadequate 1 2 1 2U2 Bad 1 1 1

2 3 1 3

Atlantic

Continental

Atlantic

Atlantic

Continental

Marine Atlantic

Marine Atlantic

Marine Atlantic

Continental


36

5.1.2 Article 12

In this section, a set of accounts for Belgium are presented using the Article 12 based approaches outlined in Chapter 4. These comprise:

Species Status Account (Table 7)

Species Abundance Account - all birds (Table 8)

Species Abundance Account - EBCC Common Bird Classes (Table 9)

Species Abundance Account - SPA-Trigger Classes (Table 10)

Species Abundance Account - EU Population Status Classes (Table 11)

Species Status Account

Table 7 identifies a total of 184 bird species (comprising 29 Not Secure; 123 Secure; 16 threatened; and, 16 unknown) recorded in the Article 12 data for Belgium, across the same ecosystem types as listed in Table 6. Reference to the National Summary for Article 12 data for Belgium reveals that 185 breeding birds are reported on (EC, 2014). The reason for the discrepancy is that Branta canadensis is dropped for the dataset used to inform Table 7. This is because it is a non-native bird and its population status was not assessed by the European Red List of Birds Consortium (2014).

The Aggregate Index in the bottom row of Table 7, reveals the birds in Belgium generally comprise those with a secure conservation status in the EU (generally the index is around 80). However, grassland ecosystems in Belgium may be of greater relative importance in the EU, as these contain the highest proportion of species of threatened status (the Aggregate Index is less than 70).

The ‘Tends in Status’ section in the middle of Table 7 is calculated in the same way across all four Species Accounts produced for Belgium. However, the classifications or number of data records vary for each different Species Account format, leading to some variation in the ‘Trends in Status’ indicators. With reference to the final column in Table 7, the ‘Prevailing Trend’ and ‘Overall Trend’ indicators reveal similar stories, ‘Not Secure’ species are exhibiting strong negative trends (-37.93 and -48.28, respectively) and ‘Secure’ species strong positive trends (47.97 and 30.08, respectively) in Belgium, an expected result. For ‘Threatened’ species ‘Prevailing Trends’ are positive (6.25) but the ‘Overall Trend’ indicator is negative (-18.75). Whilst this suggests the ‘Overall Trend’ is a more sensitive indicator of ecosystem degradation it may also imply that the ‘Threatened’ species class is a less consistent group of bird species through which to infer ecosystem condition as they may often be the focus of conservation actions, especially when they are rare.


37

Table 7 Species Status Account for Belgium

A general observation is that the ‘Prevailing Trend’ indicator is consistently more positive than the ‘Overall Trend’ indicator. This is expected given the inclusion of species exhibiting stable trends as a positive numerator value in the ‘Prevailing Trends’ indicator. Whilst this may make the indicator less sensitive, it is intuitively appealing to include stable species populations as a positive indicator for ecosystem condition.

At the ecosystem level, the ‘Prevailing Trend’ and ‘Overall Trend’ indicators provides a fairly consistent picture, with ‘Not Secure’ species exhibiting negative trends in most ecosystems and ‘Secure’ species positive. The exceptions to this are for wetlands and rivers & lakes, where ‘Not Secure’ and ‘Secure’ species generally exhibit positive ‘Prevailing Trends’ and ‘Overall Trends’ (the only exception is the Overall Trend of zero for Not Secure species in wetlands). Whilst this suggests these two ecosystems may be in an improving condition, it should be acknowledged that the trend indicators will also respond to a variety of management actions including those of little relevance to broader ecosystem condition (e.g. keeping dogs away from ground nesting birds).

The improvement in rivers & lakes ecosystems in Belgium is also reflected in the ‘Art 17 Trend in CS’ indicator for the Atlantic Biogeographic region presented in Table 6. However, this is the only instance where Overall Trends for Secure and Not Secure species provide the same result.

Bird Species Status and Trends in Status Reported under Article 12 for 2007 and 2012: BelgiumMAES


Heathland /

Shrub Marine Inlets Rivers / Lakes

Sparsely


Woodland /

Forest


Not Secure

Secure

Threatened

Unknown

Aggregate Index


Not Secure - -63.64 -100.00 -100.00 - 33.33 -100.00 -14.29 25.00 -40.00 -37.93

Secure - 65.38 70.59 52.94 - 55.81 66.67 60.87 48.84 36.67 47.97

Threatened - 0.00 16.67 -100.00 - 55.56 40.00 - 30.00 -100.00 6.25

Unknown - 0.00 50.00 0.00 - 50.00 -50.00 - 40.00 50.00 37.50

Not Secure - -72.73 -100.00 -100.00 - 11.11 -100.00 -42.86 0.00 -40.00 -48.28

Secure - 46.15 41.18 17.65 - 39.53 50.00 43.48 32.56 21.67 30.08

Threatened - -50.00 -16.67 -100.00 - 22.22 20.00 - -10.00 -100.00 -18.75

Unknown - 0.00 50.00 -50.00 - 33.33 -50.00 - 20.00 37.50 25.00

Not Secure - 90.91 100.00 100.00 - 77.78 100.00 71.43 75.00 100.00 89.66

Secure - 76.92 52.94 52.94 - 72.09 75.00 69.57 69.77 78.33 72.36

Threatened - 50.00 50.00 100.00 - 66.67 60.00 - 50.00 100.00 68.75

Unknown - 50.00 50.00 50.00 - 66.67 50.00 - 60.00 62.50 62.50

Not Secure - 100.00 100.00 100.00 - 100.00 100.00 100.00 100.00 100.00 100.00

Secure - 96.15 82.35 88.24 - 88.37 91.67 86.96 86.05 93.33 90.24

Threatened - 100.00 83.33 100.00 - 100.00 80.00 - 90.00 100.00 93.75

Unknown - 50.00 50.00 100.00 - 83.33 50.00 - 80.00 75.00 75.00

Net Change8

Not Secure

Secure

Threatened

Unknown


Not Secure 0 11 5 6 0 9 5 7 8 10 29

Secure 0 26 17 17 0 43 24 23 43 60 123

Threatened 0 2 6 2 0 9 5 0 10 3 16

Unknown 0 4 2 2 0 6 2 0 5 8 16

Aggregate Index - 80.77 69.64 80.00 - 77.87 77.94 88.33 77.05 89.04 81.851 This is subject to confirmation and examples of a potential classification system are provided in the above table2 The historic Article 12 reporting format may mean it is not possible to ascertain the situation for 2005-20073 These are the three best measures to be evaluated for use in the accounts4 (Stable + Increasing – decreasing) / (No. species this is all including unknowns) * 1005 (Increase – declining) / (No. Species this is all including unknowns and stable) * 100


Aggregate index =

Where Secure = 0

Not Secure = 1

Threatened = 2



All Ecosystems

Number of Species (S)

Bird group classes1

Number of Species

Prevailing Trends4

Overall Trend5


Coverage of trends7

Number of Species

∗ −∑ =

∗



38

The intensity of change indicator reveals that a maximum of 50% of the species are stable in any one population status category (reflecting the minimum value of 50.0) within a single ecosystem. The ‘Not Secure’ species have particularly unstable population trends in cropland, grassland, heathland & Shrub, sparsely vegetated and woodland and forest ecosystems. This would generally be expected, given that the prevailing trend indicator is highly negative in most of these ecosystems (although Woodland and forest is an anomaly in this regard). The coverage of trends indicators reveals that trend data is available for in excess of 90% of 184 bird species used to inform the account presented in Table 7.

Species Abundance Account using all bird data

Table 8 presents the Species Abundance Account using all species records for which

population estimates meet the criteria discussed in Section 4.1.3. In total this

comprises of 115 species, with species coverage zero for coastal and marine inlet

ecosystems and below 20 for heathland & shrub and urban ecosystems. The total

abundance values provided in Table 8 suggests that most of Belgium’s bird

populations have preferences for woodland / forest ecosystems. However, the

Shannon’s Index is highest in the rivers & lakes and wetland ecosystems, although this

is likely to be influenced by the high number of species with preferences for these

ecosystems (over 50 each).

Table 8 Species Abundance Account - all birds for Belgium

The Prevailing Trends and Overall Trends, generally provide consistent results. Both

identify bird species populations in rivers & lakes have improved, which is also noted

for the ‘Art 17 Trend in CS’ in the Atlantic biogeographical region in Table 6. These

trends are also strongly positive for wetlands (which is not reflected in the overall

trends in Table 6), with modest improvements also observed for sparsely vegetated,

urban and woodland / forest ecosystems. Both indicate negative overall trends for

Population Based Account Using Article 12 Data for 2007 and 2012: Belgium


Heathland /


Sparsely


Woodland /

Forest

Total abundance (No.

individuals)

Number of species

Shannon's Index

Prevailing Trends4 - 23.81 33.33 -14.29 - 55.17 28.57 37.50 47.27 16.22 32.17

Overall Trend5 - 0.00 0.00 -42.86 - 34.48 14.29 12.50 25.45 8.11 13.91

Intensity of change6 - 76.19 57.14 71.43 - 68.97 78.57 62.50 65.45 89.19 74.78

Coverage of trends7 - 100.00 90.48 100.00 - 89.66 92.86 87.50 87.27 97.30 93.04


Number of species

Shannon's Index

Total abundance (No. 0.00E+00 5.82E+04 3.75E+04 1.55E+04 0.00E+00 3.06E+04 3.79E+04 2.78E+04 3.10E+04 3.14E+05 5.52E+05

Number of species 0 21 21 14 0 58 28 8 55 37 115

Shannon's Index - 2.05 1.94 1.53 - 3.06 1.65 0.85 2.92 2.57 3.421 This is subject to confirmation and examples of a potential classification system are provided in the above table2 The historic Article 12 reporting format may mean it is not possible to ascertain the situation for 2005-20073 These are the three best measures to be evaluated for use in the accounts4 (Stable + Increasing – decreasing) / (No. species this is all including unknowns) * 1005 (Increase – declining) / (No. Species this is all including unknowns and stable) * 100

NB: The above is analogous to the Overall Trend in CS in the Art 17 approach6 (Increase + declining) / (No. Species) * 1007 (1 - (No. Unknown / No. Species)) * 100

- No data for calculation

All Ecosystems




MAES

Net Change8


39

heathland & shrub (also noted for the ‘Art 17 Trend in CS’ in Table 6). The ‘Overall

Trend’ is stable (i.e., zero) for Cropland (similar to the trends in Table 6) and

Grassland (Table 6 suggests deterioration in conservation status), whereas the

‘Prevailing Trend’ suggests a moderate improvement in these ecosystems.

Species Abundance Account using EBCC Common Bird Categories

Table 9 presents the Species Abundance Account using EBCC Bird Species categories

for Belgium. In total 66 species (out of the 115 for which population data is available)

have been used to generate the account, comprising of 15 ‘Forest’ common birds, 16

‘Farmland’ and 35 birds which are not farmland or forest specialists (‘Other’ common

birds). Table 9 reveals that common bird species associations with coastal, marine

inlets, sparsely vegetated and urban ecosystems are poor, with less than 10 species

associated with each.

The Shannon’s Index for ‘Other’ common birds is highest for the Rivers and Lakes

ecosystem (2.37) and is also relatively high for wetland (2.24), again indicating these

ecosystems are in relatively good condition. As expected the Shannon’s Index for

‘Forest’ birds is highest for woodland / forest ecosystems (2.09) and for ‘Farmland’

birds in cropland (1.50). The relatively high Shannon’s Index value for woodland /

forest is accompanied by total abundance estimates for Forest birds, which are an

order of magnitude higher in woodland / forest ecosystems than any other ecosystem.

However, with no reference for ‘Good Condition’ for comparison it not possible to

identify which ecosystem is in the, relatively, better condition.

At the ecosystem level, the ‘Prevailing Trend’ and ‘Overall Trend’ indicators provides a

fairly consistent picture, with ‘Farmland’ species exhibiting negative trends in

cropland and ‘Forest’ species stable in woodland / forest. ‘Other’ species exhibit

positive ‘Prevailing Trend’ and ‘Overall Trend’ results in grassland, rivers & lakes and

wetlands. This suggests these ecosystems are in an improving condition, reflecting a

consistent story for rivers & lakes and wetlands in the Atlantic Biogeographical region

of Belgium.

An interesting observation with respect to Table 9, is the ‘Prevailing Trend’ and

‘Overall Trend’ indicators for ‘Other’ and ‘Farmland’ birds in croplands are

contradictory. The trends are both negative for farmland birds in croplands but

positive for ‘Other’. Furthermore, Table 6 reveals the ‘Art 17 Trend in CS’ conservation

status for croplands is negative for the Atlantic and zero for the Continental

biogeographic region (albeit this is based on ≤ 5 assessment results). Consequently,

the trends for the specialist farmland bird class may be identifying a loss of condition

that would not be observed using more aggregated bird classes. As the absolute

abundance of the farmland birds is an order of magnitude higher than the ‘Other’ class

in croplands it may be rational to focus on what is happening to these species for

informing condition accounts. This is in general accordance with a priori expectations

given the research associated with the development of the farmland bird index.


40

Table 9 Species Abundance Account - EBCC Common Bird Classes for Belgium

This inference does not seem not to be as strong for forest birds, although the

prevailing trend is a lower positive number in Table 9 (6.67) for forest birds compared

to ‘Other’ (10.0) (Overall trends are zero for both groups). This second result is in

general accordance with the Article 17 accounts, which indicate negative trends in

conservation status for species in woodland / forest (‘Art 17 trend in CS’ is -22.7 for the

Atlantic and -4.5 for the Continental biogeographical region). There is also a strong

rationale to focus on this group for assessing condition of woodland / forest

ecosystems as they dominate the total abundance of species with a preference for the

ecosystem (i.e., 261,000 reported for Forest Birds in Table 9 and 314,000 for all birds

reported in Table 8).

The ‘Prevailing’ and ‘Overall Trends’ reported for all birds in croplands and woodland

/ forests in Table 8 are consistently more positive than the results for the farmland and

forest bird species in Table 9. Again suggesting, the indicators developed using

specialist species for ecosystems may identify trends in condition that may not be

reflected by the trends in the more generalist bird species. This likely due to the

Common Bird Species Population Based Account Using Article 12 Data for 2007 and 2012: Belgium


Heathland /


Sparsely


Woodland /

Forest

Other

Farmland

Forest

Other

Farmland

Forest

Common (non-

specific)

Farmland

Forest

Other - 60.00 80.00 0.00 - 31.82 -37.50 -100.00 36.84 10.00 25.71

Farmland - -40.00 -18.18 -33.33 - 100.00 100.00 -50.00 -50.00 -33.33 -18.75

Forest - 100.00 - -100.00 - - - 100.00 - 6.67 6.67

Other - 40.00 40.00 -50.00 - 18.18 -37.50 -100.00 21.05 0.00 11.43

Farmland - -50.00 -27.27 -33.33 - 50.00 100.00 -50.00 -50.00 -33.33 -31.25

Forest - 100.00 - -100.00 - - - 100.00 - 0.00 0.00

Other - 80.00 40.00 50.00 - 72.73 87.50 100.00 63.16 80.00 74.29

Farmland - 90.00 81.82 100.00 - 50.00 100.00 50.00 100.00 100.00 81.25

Forest - 100.00 - 100.00 - - - 100.00 - 93.33 93.33

Other - 100.00 80.00 100.00 - 86.36 87.50 100.00 78.95 90.00 88.57

Farmland - 100.00 90.91 100.00 - 100.00 100.00 50.00 100.00 100.00 93.75

Forest - 100.00 - 100.00 - - - 100.00 - 100.00 100.00

Other

Farmland

Forest

Other

Farmland

Forest

Other

Farmland

Forest

Other 0.00E+00 4.76E+03 5.56E+03 1.31E+03 0.00E+00 2.07E+04 2.50E+04 2.13E+04 1.53E+04 2.70E+04 1.21E+05

Farmland 0.00E+00 4.16E+04 2.77E+04 7.39E+03 0.00E+00 3.34E+02 3.50E+03 5.00E+00 8.06E+03 1.96E+04 1.08E+05

Forest 0.00E+00 7.25E+03 0.00E+00 6.75E+03 0.00E+00 0.00E+00 0.00E+00 3.38E+03 0.00E+00 2.61E+05 2.79E+05

Other 0 5 5 4 0 22 8 1 19 10 35

Farmland 0 10 11 6 0 2 1 2 4 3 16

Forest 0 1 0 1 0 0 0 2 0 15 15

Other - 0.23 0.27 0.04 - 2.37 0.57 0.00 2.24 1.82 2.45

Farmland - 1.50 1.49 1.24 - 0.01 0.00 0.67 0.74 0.58 1.89

Forest - 0.00 - 0.00 - - - 0.61 - 2.09 2.181 This is subject to confirmation and examples of a potential classification system are provided in the above table2 The historic Article 12 reporting format may mean it is not possible to ascertain the situation for 2005-20073 These are the three best measures to be evaluated for use in the accounts4 (Stable + Increasing – decreasing) / (No. species this is all including unknowns) * 1005 (Increase – declining) / (No. Species this is all including unknowns and stable) * 100



Shannon's Index

Prevailing Trends4

Overall Trend5

Intensity of

change6

Coverage of

trends7

Total abundance

(No. individuals)

Number of

species

Net Change8

Total abundance

(No. individuals)

Shannon's Index

All Ecosystems




MAES

Shannon's Index

Bird group

classes1

Total abundance

(No. individuals)

Number of

species

Number of

species


41

ability of generalist species to use a wider variety of ecosystem types for residence,

feeding and breeding purposes.

Species Abundance Account using SPA-Trigger Status

Table 10 provides Species Abundance Accounts using SPA-trigger status. The 115 species records for which population data is available are split into two groups, comprising of 86 Non SPA-Trigger Species and 29 SPA Trigger Species to evaluate if this categorisation provides additional insight. The advantage of this approach, as opposed to using the EBCC Common Birds, is that all the available bird species population estimates are used and the 86 Non SPA Trigger Species can be considered a similar group to Common birds, as some may be scarce but dispersed species for which site designation is not appropriate.

Table 10 reveals the number of Non SPA-Trigger species exceed 10 in rivers & lakes, wetlands, sparsely vegetated, cropland, grassland, heathland / shrub and woodland / forest ecosystems, providing reasonable ecosystem coverage. Whereas, the number of SPA-Trigger species only exceed 10 in rivers & lakes, wetlands and sparsely vegetated ecosystems. Table 10 also reveals total populations of Non SPA-Trigger species exceed SPA-Trigger species in abundance by more than a factor of 10 in all ecosystems, an expected result.

The ‘Prevailing’ and ‘Overall Trends’ for both the Non SPA-Trigger and SPA-Trigger

groups are again most positive for the rivers & Lakes and Wetlands ecosystems in

Table 10. It would be interesting to understand if these improvements were associated

with national investment in wetland ecosystems. This could (potentially) support the

integration of information on environmental expenditure with information on the

ecological returns on such investments. The trends for rivers & Lakes and wetlands

and the positive trends reported for sparsely vegetated ecosystems are very similar to

those reported in Table 8 for all bird species. In fact, the ‘Prevailing Trends’ are

consistently positive and ‘Overall Trends’ zero or positive for SPA-Trigger species in all

ecosystems. This is a somewhat counterintuitive result, possibly indicating that

special protection areas are being effective in improving bird species populations in

Belgium since the Birds Directive was established.

The ‘Prevailing Trend’ and ‘Overall Trend’ for Non SPA-Trigger species is negative in

heathland & shrub (-16.67 and -50.00, respectively), similar to the result in Table 8,

where all bird species are considered. The ‘Overall Trend’ for Non-SPA-Trigger species

in cropland is slightly negative (-5.26), which is more aligned with the inferences

drawn from Table 9 for farmland birds (albeit the magnitude of the signal is far lower,

suggesting EBCC Farmland Birds remain the more sensitive indicator). Conversely,

for the woodland / forest ecosystem, Non SPA-Trigger species exhibit very slightly

negative ‘Overall Trends’ (-3.57), very similar to the stable (i.e., zero values) for

‘Overall Trends’ in EBCC Forest Common Birds provided in Table 9


42

Table 10 Species Abundance Account - SPA-Trigger Classes for Belgium

Species Abundance Account using EU Population Status Categories

Table 11 presents Species Abundance Accounts with the 115 bird species organised into

the conservation status categories described by the European Red List of Birds

Consortium (2014), comprising 23 Not Secure, 68 Secure, 16 Threatened and 8

Unknown species. Interestingly, despite the difference in species richness between the

Secure and Not Secure categories, the total abundance for both categories is almost

exactly the same (approx. 240,000). Again, this is somewhat counterintuitive as the

average abundance of each Not Secure species is approximately a factor of 3 higher

than that of the Secure species.

By ecosystem type, the Not Secure species set is less than 10 for each ecosystem and

threatened species only number 10 in wetlands and less in other ecosystems. This may

limit the ability of the categories to infer the condition of ecosystems, given

SPA-Trigger Species Population Based Account Using Article 12 Data for 2007 and 2012: Belgium


Heathland /

Shrub Marine Inlets

Rivers /

Lakes

Sparsely


Woodland /

Forest

Non SPA-Trigger

Species

SPA-Trigger Species

Non SPA-Trigger

Species

SPA-Trigger Species

Non SPA-Trigger

Species

SPA-Trigger Species

Non SPA-Trigger

Species - 15.79 27.78 -16.67 - 56.10 27.78 42.86 45.24 3.57 29.07

SPA-Trigger Species - 100.00 66.67 0.00 - 52.94 30.00 0.00 53.85 55.56 41.38

Non SPA-Trigger

Species - -5.26 0.00 -50.00 - 34.15 16.67 14.29 23.81 -3.57 10.47


Non SPA-Trigger

Species - 78.95 66.67 66.67 - 73.17 83.33 71.43 71.43 89.29 77.91


Non SPA-Trigger

Species - 100.00 94.44 100.00 - 95.12 94.44 100.00 92.86 96.43 96.51


Non SPA-Trigger

Species

SPA-Trigger Species

Non SPA-Trigger

Species

SPA-Trigger Species

Non SPA-Trigger

Species

SPA-Trigger Species

Non SPA-Trigger

Species 0.00E+00 5.67E+04 3.75E+04 1.40E+04 0.00E+00 2.66E+04 3.16E+04 2.78E+04 2.77E+04 3.05E+05 5.27E+05

SPA-Trigger Species 0.00E+00 1.50E+03 5.58E+00 1.50E+03 0.00E+00 4.04E+03 6.30E+03 2.00E+00 3.29E+03 9.02E+03 2.57E+04

Non SPA-Trigger

Species 0 19 18 12 0 41 18 7 42 28 86

SPA-Trigger Species 0 2 3 2 0 17 10 1 13 9 29

Non SPA-Trigger

Species - 1.98 1.94 1.34 - 2.84 1.24 0.85 2.75 2.47 3.28

SPA-Trigger Species - 0.02 0.81 0.02 - 1.55 0.99 0.00 1.14 1.33 2.241 This is subject to confirmation and examples of a potential classification system are provided in the above table2 The historic Article 12 reporting format may mean it is not possible to ascertain the situation for 2005-20073 These are the three best measures to be evaluated for use in the accounts4 (Stable + Increasing – decreasing) / (No. species this is all including unknowns) * 1005 (Increase – declining) / (No. Species this is all including unknowns and stable) * 100



Shannon's Index

Prevailing Trends4

Overall Trend5

Intensity of

change6

Coverage of

trends7

Total abundance

(No. Individuals)

Number of

species

All Ecosystems




MAES

Shannon's Index

Bird group classes1

Total abundance

(No. Individuals)

Total abundance

(No. Individuals)

Shannon's Index

Net Change8

Number of

species

Number of

species


43

preferences tend to be for an average of two ecosystems per bird species. Secure

species number in excess of 10 for cropland, grassland, rivers & lakes, sparsely

vegetated, wetlands and woodland / forest.

Table 11 Species Abundance Account - EU Population Status Classes for Belgium

With respect to ‘Prevailing’ and ‘Overall Trends’, Not Secure species exhibit declining

trends (-30.43 and -39.13, respectively). Conversely, the ‘Secure’ species show

improving trends (58.82 and 38.24, respectively). Whilst this is an expected result it

EU Conservation Status Species Population Based Account Using Article 12 for 2007 and 2012: Belgium


Heathland /

Shrub Marine Inlets

Rivers /

Lakes

Sparsely


Woodland /

Forest

Not Secure

Secure

Threatened

Unknown

Not Secure

Secure

Threatened

Unknown

Not Secure

Secure

Threatened

Unknown

Not Secure - -66.67 -100.00 -100.00 - 33.33 -100.00 0.00 25.00 -33.33 -30.43

Secure - 81.82 72.73 71.43 - 62.86 70.59 75.00 60.61 43.48 58.82

Threatened - 0.00 16.67 -100.00 - 55.56 40.00 - 30.00 -100.00 6.25

Unknown - 0.00 100.00 -100.00 - 40.00 -100.00 - 25.00 100.00 37.50

Not Secure - -66.67 -100.00 -100.00 - 11.11 -100.00 -25.00 0.00 -33.33 -39.13

Secure - 45.45 27.27 14.29 - 45.71 52.94 50.00 45.45 30.43 38.24

Threatened - -50.00 -16.67 -100.00 - 22.22 20.00 - -10.00 -100.00 -18.75

Unknown - 0.00 100.00 -100.00 - 20.00 -100.00 - 0.00 100.00 25.00

Not Secure - 100.00 100.00 100.00 - 77.78 100.00 75.00 75.00 100.00 91.30

Secure - 63.64 45.45 42.86 - 68.57 76.47 50.00 69.70 82.61 70.59

Threatened - 50.00 50.00 100.00 - 66.67 60.00 - 50.00 100.00 68.75

Unknown - 100.00 100.00 100.00 - 60.00 100.00 - 50.00 100.00 75.00

Not Secure - 100.00 100.00 100.00 - 100.00 100.00 100.00 100.00 100.00 100.00

Secure - 100.00 90.91 100.00 - 85.71 94.12 75.00 84.85 95.65 91.18

Threatened - 100.00 83.33 100.00 - 100.00 80.00 - 90.00 100.00 93.75

Unknown - 100.00 100.00 100.00 - 80.00 100.00 - 75.00 100.00 87.50

Not Secure

Secure

Threatened

Unknown

Not Secure

Secure

Threatened

Unknown

Not Secure

Secure

Threatened

Unknown

Not Secure 0.00E+00 3.12E+04 1.31E+04 6.81E+03 0.00E+00 1.14E+04 2.38E+04 2.48E+04 1.14E+04 1.15E+05 2.37E+05

Secure 0.00E+00 1.75E+04 1.26E+04 6.80E+03 0.00E+00 1.14E+04 1.19E+04 3.06E+03 1.09E+04 1.71E+05 2.45E+05

Threatened 0.00E+00 6.02E+03 8.29E+03 1.86E+03 0.00E+00 3.45E+03 2.24E+03 0.00E+00 8.73E+03 1.72E+04 4.78E+04

Unknown 0.00E+00 3.50E+03 3.50E+03 1.33E+00 0.00E+00 4.30E+03 1.33E+00 0.00E+00 4.78E+01 1.10E+04 2.23E+04

Not Secure 0 6 3 4 0 9 5 4 8 9 23

Secure 0 11 11 7 0 35 17 4 33 23 68

Threatened 0 2 6 2 0 9 5 0 10 3 16

Unknown 0 2 1 1 0 5 1 0 4 2 8

Not Secure - 0.88 0.03 0.06 - 1.51 0.34 0.50 1.51 1.09 2.06

Secure - 1.53 1.35 1.19 - 2.80 1.76 0.58 2.78 2.09 2.87

Threatened - 0.14 0.85 0.09 - 1.56 0.91 - 1.03 0.62 1.79

Unknown - 0.00 0.00 0.00 - 0.07 0.00 - 1.09 0.63 1.071 This is subject to confirmation and examples of a potential classification system are provided in the above table2 The historic Article 12 reporting format may mean it is not possible to ascertain the situation for 2005-20073 These are the three best measures to be evaluated for use in the accounts4 (Stable + Increasing – decreasing) / (No. species this is all including unknowns) * 1005 (Increase – declining) / (No. Species this is all including unknowns and stable) * 100



All

Ecosystems




MAES

Total abundance

(No. individuals)

Bird group

classes1

Total abundance

(No. individuals)

Shannon's Index

Coverage of

trends7

Intensity of

change6

Overall Trend5

Prevailing Trends4

Net Change8

Shannon's Index

Shannon's Index

Number of

species

Total abundance

(No. individuals)

Number of

species

Number of

species


44

illustrates that the situation for bird population trends in Belgium is aligned with that

for the EU as a whole. It also highlights the issue of circulatory in using these

categories for organising bird species data and the proposed trend indicators.

The ‘Prevailing’ and ‘Overall Trends’ presented in Table 11, again, confirm the improving trends in bird populations associated with river & lake ecosystems across all population status categories. These trends are also positive for Secure species in wetlands (43.48 and 30.43 for prevailing and overall trends, respectively), however, for ‘Not Secure’ species prevailing trends are positive (25.00) but overall trends are negative (-10.00), albeit there are only 8 species upon which to generate these trends. In fact, ‘Prevailing’ and ‘Overall Trends’ for Secure species are positive in all ecosystems, again implying that the population status assessment at the EU level is very much aligned with the situation at the Member State level for Belgium.

5.2 Article 17 EU Level Accounts In this section, a set of accounts using the Article 12 data for the EU as a whole, as described in Chapter 4, are presented. These comprise:

Species Status Account (Table 12)

Species Abundance Account using population status categories (Table 13)

Species Abundance Account - all birds (Table 14)

Population status for EBCC Common Bird Classes (Table 15)

As species are assigned SPA-Trigger status in some Member States but not in others, this classification system is not consistent for the EU scale and is not tested for the EU accounts. For example, Beucephala clangula is an SPA-Trigger Species in Poland only, despite occurring in 10 other Member States.

Species Status Account for EU

Table 12 presents the Species Status Account for the EU and this is likely to be the most appropriate scale for this analytical construct. The aggregate index in the bottom row of Table 12 provides a useful way of summarising the information compiled by the European Red List of Birds Consortium (2014) by ecosystem type. For example, species with preferences for woodland / forest ecosystems appear to be relatively secure (index 82.68), whereas species with preferences for grassland are relatively more threatened (index = 62.67). This is similar to the scenario observed for Belgium.

With respect to the ‘Prevailing Trend’ and ‘Overall Trend’ indicators, these reflect logical a priori expectations, they are positive for all ‘Secure’ species in all ecosystems and negative for all ‘Not Secure’ and ‘Threatened’ species in all ecosystems (with the exception of the 2 threatened species in urban ecosystems where the overall trends are zero). This reflects that the same underlying trend data has been used to inform the status categories proposed by the European Red List of Birds Consortium (2014) and the ‘Prevailing Trend’ and ‘Overall Trend’ indicators presented in Table 12.


45

Table 12 Species Status Account for EU

Species Abundance Account using Population Status Categories for EU

As the described in Section 4.1.6, population estimates are available for all the species

records used to construct the Species Status Account for the EU. As such, Table 12 can

readily be supplemented with population data for the different population status

categories, as shown in Table 13. This provides some useful additional insights, for

example the high aggregate index for woodland / forest ecosystems presented in Table

12 is also supported by a high abundance of ‘Secure’ birds (402 million) with a high

Shannon’s Index (3.39), compared to ‘Not Secure’ birds (abundance 52 million,

Shannon’s Index 1.78). While the aggregate index for grassland reported in Table 12 is

relatively low, Table 13 identifies the total abundance of Secure (64.5 million), Not

Secure (26.6 million) and Threatened Species (4.55 million) is similar to that found in

heathland & shrub, rivers & lakes, sparsely vegetated and wetland ecosystems.

However, the Shannon’s Index is relatively low within the ‘Not Secure’, ‘Secure’ and

Bird Species Threat Status and Trends in Population Reported under Article 12 for 2007 and 2012: EU


Heathland /

Shrub Marine Inlets

Rivers /

Lakes

Sparsely


Woodland /

Forest Shelf

Open

Ocean

Not Secure

Secure

Threatened

Unknown

Aggregate

Index

Not Secure -40.00 -94.12 -56.25 -72.00 -57.14 -58.82 -43.33 -40.00 -66.67 -31.58 - - -55.88

Secure 54.55 51.22 35.90 40.38 55.00 59.78 56.76 39.39 60.24 55.56 87.50 75.00 55.08

Threatened -100.00 -72.73 -75.00 -40.00 -100.00 -62.96 -52.27 0.00 -68.00 -88.24 -100.00 -100.00 -57.69

Unknown - -21.43 -33.33 -6.67 0.00 0.00 13.33 -25.00 -14.29 4.76 - - 1.39

Not Secure -40.00 -94.12 -56.25 -72.00 -57.14 -58.82 -43.33 -40.00 -66.67 -36.84 - - -57.35

Secure 54.55 26.83 20.51 19.23 45.00 42.39 43.24 18.18 42.17 39.32 87.50 75.00 36.86

Threatened -100.00 -72.73 -75.00 -45.00 -100.00 -70.37 -59.09 0.00 -76.00 -94.12 -100.00 -100.00 -64.10

Unknown - -28.57 -33.33 -13.33 0.00 -5.26 3.33 -25.00 -14.29 -4.76 - - -5.56

Not Secure 80.00 94.12 81.25 88.00 85.71 94.12 76.67 100.00 88.89 78.95 - - 83.82

Secure 81.82 70.73 76.92 73.08 75.00 72.83 83.78 72.73 71.08 70.09 87.50 75.00 72.46

Threatened 100.00 90.91 95.00 85.00 100.00 92.59 90.91 100.00 92.00 94.12 100.00 100.00 89.74

Unknown - 28.57 33.33 13.33 0.00 15.79 16.67 25.00 23.81 14.29 - - 22.22

Not Secure 80.00 94.12 81.25 88.00 85.71 94.12 76.67 100.00 88.89 84.21 - - 85.29

Secure 81.82 95.12 92.31 94.23 85.00 90.22 97.30 93.94 89.16 86.32 87.50 75.00 90.68

Threatened 100.00 90.91 95.00 90.00 100.00 100.00 97.73 100.00 100.00 100.00 100.00 100.00 96.15

Unknown - 35.71 33.33 20.00 0.00 21.05 26.67 25.00 23.81 23.81 - - 29.17

Not Secure

Secure

Threatened

Unknown

Aggregate

Index

Not Secure 5 17 16 25 7 17 30 10 18 19 0 0 68

Secure 22 41 39 52 20 92 74 33 83 117 8 4 236

Threatened 9 11 20 20 10 27 44 2 25 17 5 3 78

Unknown 0 14 6 15 1 19 30 4 21 21 0 0 72

Aggregate

Index8 68.06 71.74 62.67 66.49 63.51 73.90 60.14 84.44 73.02 82.68 61.54 57.14 70.681 This is subject to confirmation and examples of a potential classification system are provided in the above table2 The historic Article 12 reporting format may mean it is not possible to ascertain the situation for 2005-20073 These are the three best measures to be evlauated for use in the accoutns4 (Stable + Increasing – decreasing) / (No. species this is all including unknowns) * 1005 (Increase – declining) / (No. Species this is all including unknowns and stable) * 100


- Insufficient data for calculation8 Where population, threat status or range measures are known the net change between reporting periods should be recorded here

Aggregate index =

Where Secure = 0

Not Secure = 1

Threatened = 2



Number of

Species (S)

Bird group

classes1

MAES

All Ecosystems


Net Change8

Number of

Species (S)


Number of

Species (S)


Prevailing

Trends4

Overall

Trend5

Intensity of

change6

Coverage of

trends7

∗ −∑ =

∗



46

‘Threatened’ populations in grassland (between 1.02 and 1.63), suggesting a few species

may be dominating in this ecosystem.

Table 13 Species Abundance Account - Population Status Classes for EU

Species Abundance Account using All Bird Data for EU

Table 14 presents the Species Abundance Account for the EU using all breeding bird

species records. In total this comprises of 454 species, with species coverage limited

for Open Ocean (7) and shelf (13) ecosystems but reasonable elsewhere (36 in coastal

and higher elsewhere). As with Belgium, the total abundance values in Table 14

suggests reveal woodland / forest ecosystem types has linkages to the largest

abundance of birds in the EU (total abundance 470 million). Woodland / forest also

has the highest Shannon’s Index value (3.66). Interestingly, the second highest

abundance measure is associated with urban ecosystems (309 million). However, the

Shannon’s Index for Urban (2.92) is lower than 5 other ecosystem types, indicating the

high abundance is not indicative of a high diversity (a notion supported by the species

richness of 49 within this ecosystem and often observed by dominance of species

associated with urban areas).

The ‘Prevailing Trends’ and ‘Overall Trends’, generally provide consistent results by ecosystem type, with the only exception being sparsely vegetated ecosystems where the ‘Prevailing Trend’ is slightly positive (5.62) and the ‘Overall Trend’ slightly negative (-3.32). This consistency is also reflected in the values for these trends for the EU as a whole (i.e., in the final column of Table 14). The ‘Overall Trend’ suggests small improvements in bird species populations across the EU for coastal (2.78), rivers & lakes (5.81), urban (2.04), wetlands (0.68) and woodland / forest (12.64). However, the low values may best be interpreted as an indication of stability in these populations. Furthermore, the picture provided by Table 14 is highly aggregated and different bird species in different locations will be doing well and others badly. Nonetheless, one of the purposes of the accounting process is to aggregate information as key indicators and Table 14 demonstrates this is possible.

EU Conservation Status Species Population Based Account Using Article 12 Data for 2007 and 2012: EU


Heathland /

Shrub Marine Inlets

Rivers /

Lakes

Sparsely


Woodland /

Forest Shelf Open Ocean

Not Secure 3.96E+05 1.27E+08 2.66E+07 3.47E+07 4.17E+05 1.81E+06 1.04E+07 1.03E+08 3.26E+06 5.20E+07 0.00E+00 0.00E+00 3.59E+08

Secure 8.21E+05 1.25E+08 6.45E+07 5.62E+07 1.37E+06 2.26E+07 2.53E+07 2.03E+08 1.71E+07 4.02E+08 1.07E+06 2.62E+05 9.19E+08

Threatened 3.04E+05 4.55E+06 3.20E+06 4.68E+06 2.25E+05 8.00E+05 1.28E+06 2.75E+00 3.18E+06 1.27E+07 2.73E+05 3.73E+05 3.16E+07

Unknown 0.00E+00 5.98E+06 1.50E+06 1.65E+06 5.63E+03 1.55E+06 4.51E+06 4.31E+06 6.31E+05 3.62E+06 0.00E+00 0.00E+00 2.38E+07

Not Secure 5 17 16 25 7 17 30 10 18 19 0 0 68

Secure 22 41 39 52 20 92 74 33 83 117 8 4 236

Threatened 9 11 20 20 10 27 44 2 25 17 5 3 78

Unknown 0 14 6 15 1 19 30 4 21 21 0 0 72

Not Secure 0.85 1.67 1.35 1.71 1.04 1.74 1.29 1.23 1.87 1.78 - - 2.44

Secure 2.40 2.55 1.63 2.67 1.78 2.67 2.51 2.75 2.66 3.39 0.81 0.78 3.83

Threatened 1.18 0.97 1.02 1.11 1.73 2.08 2.47 0.47 1.16 1.49 1.02 0.61 2.52

Unknown - 1.29 0.98 1.54 0.00 1.51 1.94 0.63 2.15 2.10 - - 2.76

Shannon's

Index

Number of

species

Total

abundance

(No.

individuals)


All Ecosystems

Bird group

classes1

MAES


47

Table 14 Species Abundance Account - all birds for EU

Species Abundance Account using EBCC Common Bird Categories for EU

Finally, Table 15 presents the Species Abundance Account using EBCC Bird Species

categories for the EU. As described in Section 4.1.6, in total 166 common bird species

have been listed by the EBCC. However, the number of species reported on in Table 15

is 176 as this includes some subspecies of the same common bird species. The species

are organised into 3 groups, comprising: 40 farmland species, 36 forest species and 100

‘other’, non-specialist species. Forest birds are strongly associated with the woodland

and forest ecosystem (Table 15 identifies 40 forest species in this ecosystem type).

Surprisingly, Table 14 identifies more farmland birds in grasslands (31) than cropland

(30), although the total abundance of farmland birds in cropland is higher. Farmland

birds also exhibit preferences for heathland / scrub (23 species). Common bird species

in general have little or no preference for shelf, open ocean and coastal ecosystems.

Bird Species Population Based Account Using All Article 12 Data for 2007 and 2012: EU


Heathland /

Shrub

Marine

Inlets

Rivers /

Lakes

Sparsely


Woodland /

Forest Shelf

Open

Ocean

Total abundance

(No. individuals)

Number of

Species

Shannon's Index

Prevailing 2.78 -7.23 -14.81 -5.36 -7.89 18.06 5.62 16.33 12.24 25.86 15.38 0.00 10.57

Overall Trend5 2.78 -20.48 -22.22 -16.96 -13.16 5.81 -3.37 2.04 0.68 12.64 15.38 0.00 -1.32

Intensity of 86.11 71.08 79.01 70.54 81.58 71.61 73.03 75.51 70.07 66.67 92.31 85.71 27.81Coverage of

trends7 86.11 84.34 86.42 82.14 86.84 83.87 82.02 89.80 81.63 79.89 92.31 85.71 81.06

Total abundance

(No. individuals)

Number of

Species

Shannon's Index

Total abundance

(No. individuals) 1.52E+06 2.63E+08 9.58E+07 9.73E+07 2.02E+06 2.68E+07 4.15E+07 3.09E+08 2.42E+07 4.70E+08 1.34E+06 6.35E+05 1.33E+09

Number of

species 36 83 81 112 38 155 178 49 147 174 13 7 454

Shannon's Index 2.76 2.93 2.32 3.13 2.46 3.12 3.14 2.92 3.22 3.66 1.35 1.36 4.181 This is subject to confirmation and examples of a potential classification system are provided in the above table2 The historic Article 12 reporting format may mean it is not possible to ascertain the situation for 2005-20073 These are the three best measures to be evaluated for use in the accounts4 (Stable + Increasing – decreasing) / (No. species this is all including unknowns) * 1005 (Increase – declining) / (No. Species this is all including unknowns and stable) * 100


- Insufficient data for calculation

All

Ecosystems




Net Change8

MAES


48

Table 15 Species Abundance Account - EBCC Common Bird Classes for EU

As shown in Table 15, the Shannon’s Index for Farmland Birds is highest for cropland (2.64) and is also high for grassland (2.27), particularly when compared to ‘Other’ common birds (0.83). This is due to the relatively higher number of farmland bird species (31) compared to other common bird species (12) that have preferences for grassland ecosystems. A similar scenario exists for heathland & shrub, where the Shannon’s Index for farmland birds marginally exceeds that for other common birds (although the species richness and total abundance of ‘other’ birds is higher).

For woodland / forest ecosystems, Table 15 confirms the Shannon’s Index is highest for forest birds (2.95), although for ‘Other’ common birds it is also high (2.93). However, given the higher abundance and species richness of the ‘Other’ category, the ‘Forest’ common bird species must exhibit a higher population evenness. Thus, they may provide a better indicator of relative degradation from the current state.

Common Bird Species Population Based Account Using Article 12 Data for 2007 and 2012: EU


Heathland /

Shrub

Marine

Inlets

Rivers /

Lakes

Sparsely


Woodland /

Forest Shelf

Open

Ocean

Other

Farmland

Forest

Other

Farmland

Forest

Other

Farmland

Forest

Other -100.00 54.17 41.67 20.00 -15.38 17.50 13.04 41.67 16.67 35.19 - - 26.00

Farmland - -66.67 -54.84 -43.48 -100.00 -100.00 -41.67 -55.56 -100.00 -100.00 - - -57.50

Forest - 100.00 - 50.00 - 100.00 100.00 -33.33 0.00 38.46 - - 36.11

Other -100.00 25.00 8.33 8.00 -23.08 -15.00 -4.35 20.83 -9.52 18.52 - - 3.00

Farmland - -73.33 -61.29 -52.17 -100.00 -100.00 -41.67 -55.56 -100.00 -100.00 - - -65.00

Forest - 50.00 - 0.00 - 100.00 100.00 -33.33 0.00 15.38 - - 16.67

Other 100.00 58.33 58.33 80.00 84.62 50.00 73.91 70.83 61.90 62.96 - - 63.00

Farmland - 86.67 87.10 78.26 100.00 100.00 75.00 100.00 100.00 100.00 - - 85.00

Forest - 50.00 - 50.00 - 100.00 100.00 33.33 100.00 61.54 - - 66.67

Other 100.00 87.50 91.67 92.00 92.31 82.50 91.30 91.67 88.10 79.63 - - 86.00

Farmland - 93.33 93.55 86.96 100.00 100.00 75.00 100.00 100.00 100.00 - - 92.50

Forest - 100.00 - 100.00 - 100.00 100.00 33.33 100.00 84.62 - - 86.11

Other

Farmland

Forest

Other

Farmland

Forest

Other

Farmland

Forest

Other 4.40E+05 1.42E+08 4.71E+07 4.35E+07 1.49E+06 2.16E+07 2.04E+07 2.32E+08 1.58E+07 3.26E+08 0.00E+00 0.00E+00 8.50E+08

Farmland 0.00E+00 1.13E+08 4.68E+07 3.30E+07 1.42E+04 2.25E+06 8.09E+06 6.68E+07 5.97E+06 1.95E+07 0.00E+00 0.00E+00 2.96E+08

Forest 0.00E+00 1.61E+06 0.00E+00 1.86E+07 0.00E+00 1.12E+05 1.16E+06 2.48E+06 2.40E+05 1.17E+08 0.00E+00 0.00E+00 1.41E+08

Other 3 24 12 25 13 40 23 24 42 54 0 0 100

Farmland 0 30 31 23 1 4 12 9 6 4 0 0 40

Forest 0 2 0 4 0 1 1 3 2 39 0 0 36

Other 0.99 1.77 0.83 2.18 1.67 2.64 1.86 2.40 2.68 2.93 - - 3.29

Farmland - 2.64 2.27 2.41 0.00 0.13 1.60 1.86 1.20 1.15 - - 3.01

Forest - 0.54 - 0.78 - 0.00 0.00 0.79 0.69 2.95 - - 2.931 This is subject to confirmation and examples of a potential classification system are provided in the above table2 The historic Article 12 reporting format may mean it is not possible to ascertain the situation for 2005-20073 These are the three best measures to be evaluated for use in the accounts4 (Stable + Increasing – decreasing) / (No. species this is all including unknowns) * 1005 (Increase – declining) / (No. Species this is all including unknowns and stable) * 100


- Insufficient data for calculation

Shannon's Index

Prevailing

Trends4

Overall Trend5

Intensity of

change6

Coverage of

trends7

Total abundance

(No. individuals)

Number of

species

All

Ecosystems




Shannon's Index

Shannon's Index

Bird group

classes1

Total abundance

(No. individuals)

Net Change8

Number of

Species

Total abundance

(No. individuals)

Number of

Species

MAES


49

The ‘Prevailing Trend’ and ‘Overall Trend’ for farmland birds in Table 15 is negative across all ecosystems, both in aggregate and individually. This is as expected given the negative trends in common farmland birds under the PECBMS (EBCC, 2015) but supports the notion that the accounting logic is consistent with the wider assessment processes for common birds in the EU under the PECBMS. The trends for Forest birds in Table 15 are generally positive. For woodland / forest ecosystems in particular, the ‘Prevailing Trend’ is 38.46 and the ‘Overall Trend’ is 16.67. In comparison, the PECBMS results suggest that woodland bird populations are stable (EBCC, 2015). This again supports the notion that the ‘Overall Trend’ indicator is the more sensitive indicator of changes in condition. Nonetheless, there remains logic in retaining stable populations in the prevailing trend indicator as these do reflect that condition (or pressures) is not ‘worsening’ for multiple species.

With the exception of marine and coastal ecosystems, the ‘Prevailing Trends’ for ‘Other’ common bird species reported in Table 15 are positive (across all ecosystems 26.0). However, the ‘Overall Trends’ are negative for these species in rivers & lakes, sparsely vegetated and wetlands and across all ecosystems is almost zero (or 3.00 as reported in Table 15). This is likely to be in general accordance with the PECMBS, which demonstrates an overall negative trend in all common bird species but one that is heavily influenced by the deterioration in farmland species particularly (see EBCC 2015).


The accounting tables presented demonstrate the feasibility of constructing Species Abundance and Species Status Accounts using Article 12 reporting data at Member State and EU scale

The Species Abundance Accounts were successfully calculated using all relevant Article 12 records and disaggregated by European Population Status; and, EBBC Common Bird Categories at EU and Member State scale

The Species Accounts for Belgium suggest an improvement in the condition of rivers & lakes and wetlands for supporting biodiversity and a decline in the condition of heathland & shrub. The trends in EBBC farmland birds suggest a deterioration in the condition of cropland for supporting biodiversity in Belgium.

The Species Accounts for the EU suggest condition for supporting biodiversity is improving (slightly) in rivers & lakes and woodland / forest ecosystems and declining (slightly) in cropland, grassland and heathland and shrub. The trends in farmland birds more strongly support the notion that the condition of cropland and grassland ecosystems for supporting biodiversity are declining in the EU.


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SPA-Trigger status was found to be inconsistently applied to bird species between Member States. As such Species Abundance Accounts using SPA-Trigger status categories were only be calculated at Member State scale

The Prevailing Trend and Overall Trend indicators provide a fairly consistent picture, although the Prevailing Trend indicator is always more positive

EBBC common farmland bird species may be the most sensitive indicator of cropland ecosystem condition

Comparison between the Species Accounts calculated using Article 17 and Article 12 data in Belgium was difficult given that it is not possible to disaggregate the Article 12 data by biogeographical region. However, both accounts suggest that biodiversity tends are positive in River & Lake ecosystems in Belgium

Ecosystem coverage is best when all bird species are used but remains poor for urban and marine MAES ecosystem types


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6 Critical Assessment of Species Accounts using Article 12 data

The set of Species Accounts presented in Sections 5.1 and 5.2 clearly demonstrate that

accounts of species status, abundance, richness and evenness can be compiled at both

Member State and EU scales using the Article 12 database. This chapter provides a

critical assessment of the different accounting constructs and ways of organising the

Article 12 data, together with comparisons with Article 17 based Species Accounts.

6.1 Article 12 Species Status Accounts The Species Status Accounts were calculated using population status categories

developed for the EU as a whole. At the Member State scale, understanding the

number of species transitioning between these population status categories would be

useful for identifying in which countries, and their ecosystems, species of EU

importance for conservation reside. However, there appears little logic in using

species transitions between population status categories at the EU scale to infer

condition of ecosystems in Member States locally. At the EU scale the Species Status

Accounts are considered to provide a useful construct for organising the population

status assessment by the European Red List of Birds Consortium (2014) from a MAES

ecosystem type perspective (albeit similar information is provided in the State of

Nature for the EU report, EEA, 2015b).

There are some further concerns with compiling the Species Status Accounts at

Member State scale, due to the same data being used to determine status categories

and to calculate proposed trend indicators. The ‘Prevailing’ and ‘Overall Trends’ that

emerge will reflect the assumptions inherent in this categorisation process by the

European Red List of Birds Consortium (2014). These Species Status Accounts also

require that the EU scale assessment is repeated every reporting period.

It is possible to compile the Species Status Accounts by deriving population status

categories for each Member State using the same approach set out in European Red

List of Birds Consortium (2014) at the national scale. This approach could be tested

when the next set of Article 12 reporting data becomes available.

6.2 Article 12 Species Abundance Accounts At the Member State scale, the Species Abundance Accounts are likely to provide greater insight into condition (compared to Species Status Accounts), as they provide an opportunity to evaluate bird species diversity from the perspectives of abundance, richness and evenness statistics compiled from numerical data. The use of Shannon’s index also allows conflation of species richness and evenness into a single parameter that could help streamline any condition accounting process.


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It is noted the cost of this analytical advantage is a reduction in the number of records,

due to population abundance estimates failing quality criteria (i.e., for Belgium only

115 records out 184 meet this criteria). This cost is minimised by adopting an

accounting approach that uses all 115 bird species in a single category. There is

intuitive appeal in this approach as the maximum sample size is expected to provide

the maximum confidence in any derived summary statistics. However, there are

potential ecological reasons for focusing on particular bird species grouping.

The main exception for using all bird species was for cropland, where trends in Pan-

European Common Bird Monitoring Scheme (PECBMS) Common Farmland Bird

species may provide more accurate signals on the condition of this ecosystem type.

This would be supported by the EBCC's targeted choice of farmland species that are

widely and reliably monitored. It is also considered that common birds, or at least

those not targeted for conservation action (e.g., via particular management action,

such as provision of bird breeding boxes), are likely to be more sensitive indicators of

changes in ecosystem condition. In addition, the suitability of SPA-Trigger and EU

Population status were evaluated as ways of grouping bird species data. However,

these groupings provided the similar signals (or trends) as using all birds, but suffered

from poor ecosystem coverage (i.e., less bird species records per ecosystem type).

Furthermore, the SPA designations were not consistent across Member States, limiting

comparability.

With respect to the EU Population Status, organising information on species

abundance into these categories does not provide any clear cut additional insights.

Using the population status categories is also undesirable, as the categorisation

process is based on the same data as that used to calculate the trend indicators used in

the accounts (as discussed above). In addition, the mean abundances for the less

threatened species groups are actually found to be lower than for those of a higher

threat status (e.g., see Table 13, where 68 Not Secure species comprise 359 million

individuals with a mean abundance of 5.28 million individuals per species and the 236

Secure species comprise 919 million with a mean abundance 3.89 million).

6.3 Trend indicators In order to overcome the absence of Article 12 reporting data for two periods,

‘Prevailing Trend’ and ‘Overall Trend’ indicators were calculated based on the short

and long term trends of bird species reported by Member States. The trend indicators

are consistently constructed over both the Species Status Accounts and the Species

Abundance Accounts.

The ‘Overall Trend’ indicator is considered to provide a more sensitive indicator of

marginal changes in bird-species diversity and, potentially, of changes in ecosystem

condition. Whereas, the ‘Prevailing Trend’ indicator may be preferable as it

communicates when condition is not ‘worsening’ for multiple species, as stable

populations positively contribute to this index. There remains logic in retaining stable

populations in the prevailing trend indicator, as these do reflect that condition (or


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pressures) is not ‘worsening’ for multiple species (i.e., species whose population trend

is stable contribute positively to the indicator value).

In a majority of instances the ‘Overall Trend ‘ and ‘Prevailing Trend’ indicators reveal

consistent stories with respect to ecosystem condition. However, due to the positive

impact of stable species, the ‘Prevailing Trends’ were often more positive than ‘Overall

Trends’. This resulted in the two trend indicators occasionally having the opposite

signs when their absolute values were close to zero.

The ‘Intensity of Change’ index is around 70 in all the Article 12 accounts for Belgium

(indicating 70% of the species trends are either increasing or declining). The

‘Coverage of Trends’ indicator is also consistently around 90, indicating that

information on species trends is available for nearly all bird species. This is

substantially higher than reported in the Article 17 based accounts (78.3 for the

Atlantic and 73.4 for the continental biogeographical regions). At the EU scale, the

coverage of trends indicator is approximately 80 for the Species Abundance Accounts

using all relevant bird records. This reveals the ‘Status in Trends’ indicators are

representing the Article 12 data well for the Belgium case study and the EU.

The trend data can also be used to infer which bird species categorisation process

provides most insight. Given that any disaggregation of bird species data into

different categories inevitably reduces the sample size of observations for different

ecosystems from which summary statistics can be derived, evidence of an analytical

advantage is required to justify any categorisation process. In this regard, for ‘EBCC

Farmland Birds’ category, negative ‘Overall Trends’ are observed in cropland for

Belgium (-40) and the EU (-73.33). These negative trends are far less pronounced

when considering all bird species for Belgium (0.00) and the EU (-20.48).

Consequently, additional insight may be gained from focusing on farmland species as

indicators of ecosystem condition in croplands, particularly given the paucity of

Article 17 data for this ecosystem. For EBCC Forest Birds, this argument is not so

strong. In fact the ‘Overall Trend’ and ‘Prevailing Trend’ are very consistent in

woodland / forest ecosystems when considering all birds and just EBCC Forest Birds at

the EU scale and fairly consistent (within 10 points) for the Belgium case study.

Whilst the Non SPA-Trigger Status category also offers the opportunity to focus on

common species as indicators of condition, the signals provided by the ‘Prevailing

Trend’ and ‘Overall Trend’ indicators are typically aligned with those calculated when

all birds are considered. The exceptions to this are for cropland and wood / forest

ecosystems, however, EBCC Common Farmland and Forest birds are likely to provide

more ecologically meaningful indicators of condition in these ecosystems.

Furthermore, the SPA-Trigger species do not appear to have been consistently selected

across Member States. From an accounting perspective this limits comparability and

creates challenges for aggregating data to the EU level.


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6.4 Comparison and integration with Belgium Article 17 Species Accounts

The potential for integrating the indicators derived from the Article 12 and 17 based

accounts is now greatly improved due to the alignment of their respective reporting

cycles. Furthermore, both data sets benefit from agreed aggregation procedures for

Member State data, which can inform accounting at the EU scale. However, the

updated Article 12 reporting format is only available for the 2008-2012 period, whereas

Article 17 data is available for two reporting periods. However, the need to back cast

Article 17 data to eliminate non-genuine changes also limits the comparability of data

between periods and the integration of the accounts in future periods. This

contributes to the relative stability in Article 17 conservation assessment results.

For both the Article 17 accounts (based on conservation status) and the Article 12

Species Status Accounts (based on EU population / threat status), the general stability

of species results within categories is an identified concern. For the Article 17 based

accounts, future prospects is one of the four parameters that inform the conservation

assessment. This has implications with respect to assessing current status and may

also result in the assessment being more intransigent to change. As such the

sensitivity of the Article 17 accounts may be improved by focusing on metrics

associated with individual parameters considered in the aggregated conservation

assessment result (i.e., species range, population, suitable habitat and future

prospect12). It would also be possible to improve the sensitivity of the Article 12 based

Species Status Accounts by using more disaggregated threat status categories (e.g.,

near threatened and threatened).

For Belgium, the number of breeding bird species considered in the Species Status

Accounts is 184 and in the Species Abundance Accounts is a maximum of 115. The

latter is broadly comparable with the number of conservation assessments available

for informing the Article 17 accounts (117 in total). For both datasets, river & lakes,

wetlands and forest ecosystems, the bird species or conservation assessment data is

relatively good. However, there is a paucity of conservation assessment data for

Belgium for cropland, grassland and sparsely vegetated ecosystems (maximum of 10

for grassland ecosystems in the Atlantic bioregion). For the Species Accounts

compiled using the Article 12 data there is data for at least 20 species for each of these

ecosystems. These larger sample sizes are a benefit of using the Article 12 data for

inferring the condition of a wide range of MAES ecosystems types. However, for

Belgium, there remains a paucity of both Article 12 and 17 data for urban, heathland

and shrub terrestrial ecosystems (although coverage is higher with the Article 12 data)

and marine ecosystems.

There is only limited evidence of a coherent picture emerging across both the Article

12 and 17 data (e.g., improving condition of rivers & lakes in the Atlantic

12 An approach focusing on suitable habitat and range for bird species is discussed in Appendix D


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biogeographical region and deterioration in condition of heathland & shrub for

Belgium). However, fundamentally, the Article 17 data is organised by biogeographical

region, so further work would be required to align Article 12 national data with the

Article 17 data to make such comparisons and integrations meaningful. It is likely to

be technically possible to achieve such a disaggregation using the original MAES

ecosystem associations by biogeographic region proposed by the EEA (2015a). This

would likely require further harmonisation of these associations with the Article 12

reporting data, including developing supporting associations for countries and

biogeographical regions. Alternatively, an initial focus for such comparisons could be

on countries with a single terrestrial biogeographical region, such as Hungary,

Luxembourg or Ireland, to identify if any consistent or contradictory stories emerge

across the two approaches.

An obvious but important point for comparability is that the Article 12 data relates

purely to birds, whereas the Article 17 data relates to the other species groups. It is to

be expected that these different species groups will respond differently to various

ecosystem pressures. As such, bird species statistics should not be expected to always

provide the same signals as other species and there is clear utility in maintaining

statistics across as large range of species groups as possible. For example,

understanding what is happening to fish species will likely be of primary interest for

understanding condition in river & lake ecosystems. However, it should be noted that

those species assessed under Article 17 are those of community interests and relatively

high conservation importance. This may have implications for their ability to

communicate changes in condition given the broadness of the MAES typologies.

6.5 Limitations A significant current constraint with respect to accounts constructed using Article 12

data is that data is only available for a single reporting period (2008-2012), although

the next reporting cycle is nearing completion (2012-2018). In the interim, using status

and trend indicators is likely to be the most reliable approach to obtaining more

sensitive measures of change using existing data.

A distinct attraction of the Article 12 Species Abundance Accounts is that they can be

compiled on numerical abundance data. This, potentially, provides a more sensitive

measure of biodiversity than species richness alone (i.e. statistics on population

abundances and evenness). In theory, this greatly increases the sensitivity of the

accounts as barometers of ecosystem condition, as changes in species richness and

population and conservation assessment results are likely to be relatively slow to

change. However, fundamental to this holding true in practice, is that the abundance

data reported by Member States under Article 12 is reliable, regularly updated and

consistently estimated / measured in meaningful manner over the long-term. A

treatment is set out in Chapter 4 to eliminate unreliable abundance estimates from

Article 12 data but this is based on an assumption that the quality assessments and

underlying data estimates are accurately reported. It should be noted that the


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treatment may also create bias in the datasets as, in general, it is anticipated that there

will be regional patterns in the European countries that have carried out the most

accurate surveys. At this stage it is also unclear how, and if, Member States will update

abundance data in future reporting periods. As Member States improve their bird

monitoring assessment processes, it is possible that similar issues will emerge with

respect to distinguishing between genuine and non-genuine improvements, as

encountered with the Article 17 data.

Reflecting on the results presented in Chapter 5, for both Article 12 and 17 data sets

there remains a paucity of data for marine, coastal, open ocean and urban ecosystems.

This clearly reflects constraints facing the spatial disaggregation of both the Article 12

and 17 data. This is explored considered further in Appendix B, which provides a

spatial analysis with respect to the integration of more detailed information on

ecosystem extent with data on bird species distributions and populations collated

under Article 12 (described further in Section 7.4). Currently, it appears that there is

limited potential to relate results from Article 12 and 17 reporting to the distribution of

European ecosystems beyond a broad scale. These constraints in the main data

sources underpinning the reporting on the State of Nature in Europe indicate more

detailed spatial reporting on biodiversity trends is required generally, including for

building spatially explicit species accounts.

In order to organise bird species abundance data by ecosystem type, national

abundance measures are divided equally across all the ecosystems a bird species is

associated with. This is acknowledged as a simplifying assumption, which clearly does

not consider the relative extent of each preferred ecosystem within the ecosystem

accounting area, the strength of preference for different ecosystem types or the birds

reported distribution. A related issue is identified with respect to the Article 17 data,

as a conservation assessment result for a species occupying a small area of

biogeographic region in a country carries the same weight as an assessment result for a

species occupying the entire area of a much larger biogeographic region in a country.

For both datasets this illustrates the limitations associated with spatial disaggregation

of this data.


The Species Status Accounts are useful for organising population status assessments from a MAES ecosystem perspective. However, their potential to inform at a Member State scale on ecosystem condition is considered limited.

The Species Abundance Accounts were considered to provide a greater insight into ecosystem condition.

Testing different aggregations of bird species data suggested that using all relevant records, generally, provided the greatest analytical power and ecosystem type coverage.


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EBBC Common Farmland species may provide a more sensitive indicator of cropland ecosystem condition for biodiversity.

The trend indicators proposed were found to be representing the bird data well at the EU scale and for the Belgium case study.

Whilst the ‘Overall Trend’ indicator was found to be a more sensitive indicator of loss of bird species status, the ‘Prevailing Trend’ indicator may be more appropriate as it also accounts for bird species with a stable status.

Combining the trend indicators with population status categories in the accounting table leads to some circularity as the same information is used to calculate the indicators and defines these categories.

There is potential to integrate information from the Article 12 and 17 accounts. However, this is currently limited by the fact that Article 17 data is organised by biogeographical region and often requires back casting non-genuine assessments results.

The main limitations for calculating Species Accounts using Article 12 data were:

o only one reporting period available;

o uncertainty over future reporting;

o paucity of data for marine and urban ecosystems; and,

o disaggregating bird species data by ecosystem type and, more generally, spatially.


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7 Conclusions As shown in Chapter 5, it is possible to construct accounts relevant to bird species diversity and species conservation status using the Article 12 and Article 17 reporting data. At the EU scale, the Species Accounts for the EU suggest condition for supporting biodiversity is improving (slightly) in rivers & lakes and woodland / forest ecosystems and declining (slightly) in cropland, grassland and heathland and shrub. The trends in farmland birds more strongly support the notion that the condition of cropland and grassland ecosystems for supporting biodiversity are declining in the EU.

The flexibility exists using the Article 12 reporting to aggregate data in several ways, by ecosystem type, country, EU or different groups (e.g., common birds). Whilst there is clearly potential for integrating data organised by these Species Accounts with wider ecosystem accounts, several limitations are encountered.

7.1 Policy insights from Species Accounts As shown in Figure 1, biodiversity is included in thematic accounts within the SEEA-EEA. This reflects that species-level biodiversity is not only an important determinant of ecosystem condition and service delivery but also an important objective for environmental management in its own right. With respect to the former, Species Accounts can provide indicators to inform on the condition of ecosystems and the potential to deliver ecosystem services at EU and Member State scales. This can directly inform on progress towards protecting, conserving and enhancing the EUs natural capital (as per the 7th Environmental Action Plan) and maintaining and restoring ecosystems and their services (as per Target 2 of the EU Biodiversity Strategy). With respect to specific biodiversity objectives for the EU, these are clearly established under Target 1 of the EU’s Biodiversity Strategy. These comprise:

50% more species assessments under the Habitats Directive show an improved conservation status; and,

50% more species assessments under the Birds Directive show a secure or improved status (EC, 2011).

Given the time-series nature of both Article 12 and 17 reporting data, there is also clear rationale for organising this data in a Species Account format to track progress towards these targets. Given the ambitions of natural capital accounting, these Species Accounts would provide a means to integrate information on species-level biodiversity with a wider set of data on ecosystems, the way they are used and the economy. This can greatly assist in planning to meet the actions set out in Target 2 and Target 1 of the EU Biodiversity Strategy in a holistic manner. As a simple example, it would be useful to examine the correlations that exist between the ecosystem extent and the information organised in the Species Accounts. This would include evaluating the relationships between the availability of preferred ecosystems and the habitats they contain with species-level diversity and abundance data. Initial analysis in this regard is provided in Appendix B.


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7.2 Species Accounts for Ecosystem Condition Measurement Drawing on the critical assessment provided in Chapter 6, conclusions with respect to the requirements for Article 12 Species Accounts for informing on ecosystem condition (as set out in Chapter 1) are provided below:

• The condition parameters should match critical pressures on, and changes in, ecosystem condition identified in recent MAES work. The Article 12 Species Abundance Accounts generate indicators on species richness, abundance and evenness that match the condition parameters proposed in MAES (2014). Whilst accounts relevant to species threat status are calculated and tested, they are found to be most appropriate for EU scale assessment for ecosystem condition. As Article 12 reporting using the improved format is only available for a single period (2008-2012), overall and prevailing trend indicators are also integrated and also match to information on species abundance.

• As far as feasible, condition parameters should be chosen that are applicable and comparable across all MAES ecosystem types. The indicators generated via the Article 12 Species Abundance and Status Accounts can be produced for all the MAES terrestrial ecosystem types. However, data is limited for urban ecosystems. For marine ecosystems there is often no data on bird species, particularly for the Belgium case study. The statistics on bird species presented in the accounts are directly comparable when all bird species records are used. However, some ecosystems are inherently more suitable for supporting birds than others and comparisons of these statistics should not be used to infer which ecosystem is in the best relative condition. The overall and prevailing trend indicators allow an assessment of which ecosystems have lost condition, with respect to biodiversity suitability.

• Where appropriate or necessary ecosystem-specific condition parameters should be included. The testing of the Article 12 Species Abundance Accounts indicate that focusing on EBCC farmland birds may be the most appropriate approach for measuring condition for cropland ecosystems.

• The overall number of condition parameters per ecosystem type should not be too high (e.g. in the range of 3 – 5). An aggregated threat status index and the Shannon’s Index were tested as constructs for summarising information of bird species diversity organised in the Species Status and Abundance Accounts. Other indicators for ecosystems, including species richness and total abundance are also proposed. These demonstrate the Species Accounts can summarise information in a single condition parameter.

• The condition parameters chosen should ideally be underpinned by data sets that allow a reliable quantitative analysis of trends at suitable spatial and temporal scale. The potential to spatially disaggregate the Article 12 data beyond Member State scale is limited. Furthermore, when assigning bird species data to ecosystems some simplifying assumptions have been made that compromises the reliability of the data. With respect to temporal scale, a significant constraint is that Article 12 data following the new reporting format


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is only available for a single reporting period (2008-2012). However, the next reporting cycle is nearing completion (2012-2018).

• The condition parameters should be linked to levels of ecosystem service delivery. The Article 12 based accounts provide information on the condition of ecosystems for biodiversity. This reflects a key management goal in its own right and will be directly linked to cultural ecosystem services, such as experiential interactions (especially bird watching or hunting) and the knowledge that ecosystems with high biodiversity exist. Other links are likely to be more implicit, for example wetlands with higher bird species abundance or diversity are likely to be more healthy and able to deliver various regulating services. Reflecting the wider literature (e.g., Harrison et al., 2014), it is unlikely that it will be possible to establish direct functional relationships between aggregated bird species statistics and ecosystem service delivery.

7.3 Data and ecological knowledge constraints The main ecological and data constraints encountered during the calculation of the Species Accounts comprised:

Absence of time-series data for updated Article 12 reporting

A general stability in time-series data for Article 17 conservation assessment results (partially due to non-genuine changes)

Lack of knowledge on how to best disaggregate species data across multiple ecosystems;

Lack of species data for marine, coastal, open ocean and urban ecosystems

Limited information on the distribution of species and incorporating this into the Species Accounts

Lack of geo-referenced species data to inform disaggregation of national or national - biogeographical region scale

Reliance on Overall and Prevailing trend indicators due to time-series data issues

Limitations in comparing species-level biodiversity statistics between ecosystem types and across scales

Uncertainty on how Member States will update bird species data in future Article 12 reporting periods

Lack of ecological knowledge on links between species-level biodiversity and ecosystem service provision

7.4 Next Steps The Species Abundance Accounts are believed to have the greatest potential for informing on ecosystem condition, particularly with respect to its suitability for


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biodiversity. As such it is recommended that the Species Abundance Accounts using all relevant Article 12 data on birds and the EBBC categories are used when the next round of Article 12 reporting data becomes available (estimated 2019).

Over the shorter term, an important next step is testing the integration of the Species Accounts presented herein with wider ecosystem accounts. Next steps in this direction include:

Experimenting with statistics for ecological robust identified indicator species of ‘good condition’ for specific ecosystem types

Developing the final methodological approach and data processing set-up to be ready for implementation when the next reporting cycle for the data sets used are completed.

Comparative analysis between Member States to identify any bias that emerges from relying on good quality bird species abundance data.

Evaluating if data on national bird species populations and conservation assessment results could be distributed proportionately depending on the extent of each ecosystem, using information from the ecosystem extent accounts. This could be supported by the information on distributions reported by Member States.

Evaluating the strength of the species relative preferences for different ecosystem types, and if this could potentially influence the signals communicated by the Species Accounts.

Experiment with disaggregating bird species via their ecosystem preferences at biogeographic region disaggregate by biogeographical region, using the linkages proposed by the EEA (2015a). This would provide a better alignment with the Article 17 based accounts.

Experimenting further with more refined species habitat preference data and the distribution ranges reported by Member States. This is evaluated further in Appendix B, specifically with respect to accounting for habitat suitability using Corine Land Cover associations. This could also be improved using various species distribution or status modelling approaches.

Undertake comparative analysis between the trends reported for common bird species by the PECBMS and the data generated by the Article 12 Species Accounts as a form of validation.

Using national monitoring data (including that collected to inform the PECBMS) to inform a more concrete spatial ecosystem accounting approach.

Making the case for improving the reporting by Member States to inform analysis of the state of species in Europe and the environment generally in the future


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A potential issue with respect to ecosystem condition parameters based on species metrics (e.g., Shannon’s Index) is the absence of predefined reference levels for ‘good’ condition for comparison. Target 1 of the EU biodiversity strategy provides policy goals for relative improvements, which Species Accounts can track progress towards. However, further work is required in to how these are made into operational benchmarks for accounting across scales. In the short term an accrual approach can be adopted, which will identify if these metrics communicate a picture of improving or worsening condition. It may also be possible to set historic baselines in countries for the abundance of birds or even use national trends to back cast data. In particular, using Member State trend data on Common Birds synthesised via the PECBMS is likely to be a definite possibility in this regard.

Ultimately, it will also be important to investigate the link between condition indicators realised from the Species Accounts and ecosystem service provision. This reflects that condition parameters should be predicated on their ability to communicate the effective capacity of an ecosystem to provide services. However, this may best be considered in the context of multi-functionality (i.e., number of services) rather than physical levels of delivery of distinct ecosystem services.

It would be useful to examine the correlations that exist between the ecosystem extent and these condition parameters (and the information organised in the Species Accounts generally). In particular it would be interesting to evaluate the relationships between the availability of preferred ecosystems and the habitats they contain with species-level diversity and abundance data. This is considered further in Appendix B.

Another method of deriving species-level diversity indicators relevant to ecosystem condition would be to extend the EBCC approach for common farmland and woodland bird species. This could comprise focusing on agreed individual species (or groups) that are most characteristic of ecosystem types when they are in good condition, as is common in habitat assessment exercises. Statistics and indices relevant to these species could then be recovered from the Article 12 and 17 datasets for inclusion in wider condition accounts.

It should be noted that a number of decisions have been made with respect to the treatment of bird species records and the organisation of data to inform the accounting process. Whilst these are unlikely to have heavily influenced the general results communicated by the accounts, users should be aware that certain records have been omitted due to data quality and inconsistencies.


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European Red List of Birds Consortium (2014) Using the data reported by Member States under Article 12 of the Birds Directive to summarise and present species’ population status at EU level and measure progress towards Target 1(ii) of the EU Biodiversity Strategy to 2020. Version 6: March 2016. Available at: https://circabc.europa.eu/sd/a/4b101339-6e13-4379-ada5-400e5d1ec8ac/Point 3 - Background-Paper- 21 Nov 2013 .pdf.

Harrison, P. A. et al. (2014) ‘Linkages between biodiversity attributes and ecosystem services: A systematic review’, Ecosystem Services, 9, pp. 191–203. Available at: http://www.sciencedirect.com/science/article/pii/S2212041614000576 (Accessed: 15 July 2014).

Hendriks, M. et al. (2016) BioScore 2.0: A species-by-species model to assess anthropogenic impacts on terrestrial biodiversity in Europe. The Hague.

Ivanov, E. D. et al. (2013) Developing an accounting method for species and habitats of European conservation importance. CEM Working Paper No 11_Version 3.0. Available at: https://www.nottingham.ac.uk/cem/pdf/CEM_Working_Paper_11_Article17_V3_1_22.06.2013.pdf.

Van Kleunen, A. (2003) ‘Habitat use of European breeding birds. An explanatory note to the allocation of EUNIS habitats to all European breeding birds’, in Sovon Dutch Centre for Field Ornithology.

MA (2005a) Ecosystems and Human Well-being: Policy Responses - Appendix. Washington D.C.

MA (2005b) Ecosystems and human well-being: Synthesis, Millennium Ecosystem Assessment. Washington DC, USA. Available at: http://www.millenniumassessment.org/documents/document.356.aspx.pdf.

MA (2005c) Millenium Ecosystem Assessment: Ecosystems and Human Wellbeing, Volume 1, Current State and Trends. Washington D. C. Available at: http://www.millenniumassessment.org/en/Condition.html.


65

MAES (2013) Mapping and Assessment of Ecosystems and their Services: An analytical framework for ecosystem assessments under Action 5 of the EU Biodiversity Strategy to 2020. Available at: http://ec.europa.eu/environment/nature/knowledge/ecosystem_assessment/pdf/MAESWorkingPaper2013.pdf.

MAES (2014) Mapping and Assessment of Ecosystems and their Services: Indicators for ecosystem assessments under Action 5 of the EU Biodiversity Strategy to 2020. 2nd Report. Available at: http://ec.europa.eu/environment/nature/knowledge/ecosystem_assessment/pdf/2ndMAESWorkingPaper.pdf.

MAES (2016) Mapping and Assessment of Ecosystems and their Services: Mapping and assessing the condition of Europe’s ecosystems: Progress and challenges. 3rd Report. Available at: http://ec.europa.eu/environment/nature/knowledge/ecosystem_assessment/pdf/3rdMAESReport_Condition.pdf.

N2K Group (2011) Assessment and reporting under Article 12 of the Birds Directive: Explanatory Notes & Guidelines for the period 2008-2012. Available at: https://circabc.europa.eu/sd/a/4fc954f6-61e3-4a0b-8450-ca54e5e4dd53/Art.12 guidelines final Dec 11.pdf.

Peet, R. K. (1975) ‘Relative Diversity Indices’, Ecology, 56(2), pp. 496–498. doi: 10.2307/1934984.

Remme, R. P., Hein, L. and Van Swaay, C. A. M. (2016) ‘Exploring spatial indicators for biodiversity accounting’, Ecological Indicators. Elsevier Ltd, 70, pp. 232–248. doi: 10.1016/j.ecolind.2016.06.024.

Roscher, S. et al. (2015) Article 12 datasets (tabular and spatial). Available at: https://bd.eionet.europa.eu/Reports/ETCBDTechnicalWorkingpapers/Art12_datasets_rp1.

Van Strien, A. J., Soldaat, L. L. and Gregory, R. D. (2012) ‘Desirable mathematical properties of indicators for biodiversity change’, Ecological Indicators. Elsevier Ltd, 14(1), pp. 202–208. doi: 10.1016/j.ecolind.2011.07.007.

UN et al. (2014) System of Environmental Economic Accounting 2012— Experimental Ecosystem Accounting. New York. Available at: http://unstats.un.org/unsd/envaccounting/seeaRev/eea_final_en.pdf.

UNEP-WCMC (2015) Experimental Biodiversity Accounting as a component of the System of Environmental-Economic Accounting Experimental Ecosystem Accounting (SEEA-EEA). Supporting document to the Advancing the SEEA Experimental Ecosystem Accounting project. Available at: https://www.unep-wcmc.org/news/guidance-on-experimental-biodiversity-accounting-using-the-seea-eea-framework.


66

Appendices Appendix A: Article 17 and Article 12 based Accounts for Slovakia

Article 17

Table 16 provides the Article 17 account for Slovakia based on reported species in

Article 17 according to Conservation Status and the trend in Conservation Status

between 2006 and 2012.

Table 16 Account for Slovakia using Article 17 Approach

Bioregion 1

Urban

2

Cropland

3

Grassland

4

Forest

5

Heathland

and shrub

6

Sparsely

vegetated

land

7

Inland

wetlands

8

Rivers

and lakes

Total by CS

FV Favourable 14 15 5 6 7 7 39U1 Inadequate 2 2 18 20 5 6 16 17 63U2 Bad 1 1 13 8 3 2 4 8 27XX Unknown 8 4 18 4 6 3 8 34Total 11 3 49 61 17 20 30 40 163FV Favourable 1 10 10 4 1 6 6 28U1 Inadequate 6 2 14 19 7 4 19 23 59U2 Bad 1 16 8 4 1 10 7 35XX Unknown 6 1 2 12 2 1 4 6 25Total 13 4 42 49 17 7 39 42 147

1 Favourable 12 15 5 3 7 7 362 Unfavourable - Improving 1 2 1 1 2 1 43 Unfavourable - Unknown trend 1 14 Unknown 8 4 18 4 6 3 8 345 Unfavourable - Stable 20 14 6 6 10 12 506 Unfavourable - Declining 3 2 11 13 2 4 8 11 38Total 11 3 49 61 17 20 30 40 163Overall indexes


ART17 trend in CS -18.2 -33.3 -18.4 -19.7 -11.8 -15.0 -20.0 -25.0 -20.9



1 Favourable 1 9 10 3 6 6 262 Unfavourable - Improving 1 2 2 1 1 43 Unfavourable - Unknown trend 1 1 24 Unknown 6 1 2 12 2 1 4 6 255 Unfavourable - Stable 1 17 13 7 4 15 7 426 Unfavourable - Declining 6 1 11 12 4 2 13 22 48Total 13 4 42 49 17 7 39 42 147Overall indexes


ART17 trend in CS -15.4 0.0 -21.4 -20.4 -17.6 0.0 -30.8 -47.6 -29.3



FV Favourable 1 1 5 2 4 2 36U1 Inadequate 2 2 1 7 6 66U2 Bad 2 2 3 13 3 11 14 27XX Unknown 1 2 2 1 2 3 34Total 4 2 8 22 6 1 24 25 163FV Favourable 4 1 8 1 2 4 7 26U1 Inadequate 4 3 3 6 4 2 6 5 60U2 Bad 3 2 3 3 2 2 10 10 36XX Unknown 1 1 5 1 1 2 25Total 12 5 8 22 8 6 21 24 147

Pannonian

Alpine

Pannonian


Alpine

Pannonian

Alpine




67

Article 12

On the following pages a set of accounts for Slovakia derived using the Article 12 approach are presented.

Table 17 Species Abundance Account using all birds for Slovakia

Population Based Account Using Article 12 Data for 2007 and 2012: Slovakia


Heathland /


Sparsely


Woodland /

Forest


individuals)

Number of species

Shannon's Index

Prevailing Trends4 - -3.70 -21.74 -12.50 - 24.56 28.57 28.57 21.82 28.57 18.84

Overall Trend5 - -48.15 -47.83 -43.75 - -5.26 0.00 -14.29 -7.27 -19.05 -18.12

Intensity of change6 - 55.56 73.91 68.75 - 61.40 64.29 52.38 61.82 50.79 58.70

Coverage of trends7 - 100.00 100.00 100.00 - 91.23 92.86 95.24 90.91 98.41 95.65


Number of species

Shannon's Index

Total abundance (No. 0.00E+00 1.97E+06 1.59E+06 6.99E+05 0.00E+00 1.15E+05 4.28E+05 3.06E+06 8.52E+04 7.87E+06 1.58E+07

Number of species 0 27 23 16 0 57 28 21 55 63 138

Shannon's Index - - - - - - - - - - -1 This is subject to confirmation and examples of a potential classification system are provided in the above table2 The historic Article 12 reporting format may mean it is not possible to ascertain the situation for 2005-20073 These are the three best measures to be evaluated for use in the accounts4 (Stable + Increasing – decreasing) / (No. species this is all including unknowns) * 1005 (Increase – declining) / (No. Species this is all including unknowns and stable) * 100



All Ecosystems




MAES

Net Change8


68

Table 18 Species Abundance Account using EBCC Common Bird Categories for Slovakia

Common Bird Species Population Based Account Using Article 12 Data for 2007 and 2012: Slovakia


Heathland /


Sparsely


Woodland /

Forest

Other

Farmland

Forest

Other

Farmland

Forest

Common (non-

specific)

Farmland

Forest

Other - 40.00 33.33 -50.00 - 27.27 -22.22 53.85 33.33 66.67 40.00

Farmland - 0.00 -50.00 -50.00 - - -100.00 -33.33 - 100.00 -33.33

Forest - 100.00 - 33.33 - - 100.00 50.00 - 38.89 38.89

Other - -20.00 -16.67 -75.00 - -9.09 -44.44 -7.69 -4.76 -4.17 -12.00

Farmland - -50.00 -75.00 -75.00 - - -100.00 -66.67 - 0.00 -66.67

Forest - 0.00 - -33.33 - - 0.00 50.00 - -5.56 -5.56

Other - 40.00 50.00 75.00 - 54.55 66.67 38.46 52.38 29.17 44.00

Farmland - 50.00 75.00 75.00 - - 100.00 66.67 - 0.00 66.67

Forest - 0.00 - 33.33 - - 0.00 50.00 - 50.00 50.00

Other - 100.00 100.00 100.00 - 90.91 88.89 100.00 90.48 100.00 96.00

Farmland - 100.00 100.00 100.00 - - 100.00 100.00 - 100.00 100.00

Forest - 100.00 - 100.00 - - 100.00 50.00 - 94.44 94.44

Other

Farmland

Forest

Other

Farmland

Forest

Other

Farmland

Forest

Other 0.00E+00 1.54E+06 1.39E+06 7.67E+04 0.00E+00 1.11E+05 3.97E+05 2.88E+06 7.95E+04 5.39E+06 1.19E+07

Farmland 0.00E+00 3.46E+05 2.07E+05 6.42E+04 0.00E+00 0.00E+00 1.00E+04 1.76E+05 0.00E+00 3.63E+04 8.39E+05

Forest 0.00E+00 8.25E+04 0.00E+00 5.58E+05 0.00E+00 0.00E+00 2.00E+04 1.20E+03 0.00E+00 2.43E+06 3.09E+06

Other 0 10 6 4 0 22 9 13 21 24 50

Farmland 0 8 8 4 0 0 2 3 0 2 12

Forest 0 1 0 3 0 0 1 2 0 18 18

Other - 0.66 0.18 0.88 - 2.14 0.64 1.78 2.09 2.08 2.22

Farmland - 1.25 1.05 0.96 - - 0.02 0.43 - 0.62 1.62

Forest - 0.00 - 0.70 - - 0.00 0.23 - 1.86 1.921 This is subject to confirmation and examples of a potential classification system are provided in the above table2 The historic Article 12 reporting format may mean it is not possible to ascertain the situation for 2005-20073 These are the three best measures to be evaluated for use in the accounts4 (Stable + Increasing – decreasing) / (No. species this is all including unknowns) * 1005 (Increase – declining) / (No. Species this is all including unknowns and stable) * 100



All Ecosystems




MAES

Shannon's Index

Bird group

classes1

Total abundance

(No. individuals)

Number of

species

Number of

species

Shannon's Index

Prevailing Trends4

Overall Trend5

Intensity of

change6

Coverage of

trends7

Total abundance

(No. individuals)

Number of

species

Net Change8

Total abundance

(No. individuals)

Shannon's Index


69

Table 19 Species Abundance Account using SPA-Trigger Status for Slovakia

SPA-Trigger Species Population Based Account Using Article 12 Data for 2007 and 2012: Slovakia


Heathland /

Shrub Marine Inlets

Rivers /

Lakes

Sparsely


Woodland /

Forest

Non SPA-Trigger

Species

SPA-Trigger Species

Non SPA-Trigger

Species

SPA-Trigger Species

Non SPA-Trigger

Species

SPA-Trigger Species

Non SPA-Trigger

Species - 15.79 9.09 0.00 - 31.43 40.00 38.89 25.00 50.00 32.95

SPA-Trigger Species - -50.00 -50.00 -25.00 - 13.64 15.38 -33.33 17.39 -14.29 -6.00

Non SPA-Trigger

Species - -36.84 -36.36 -50.00 - -5.71 0.00 -11.11 -12.50 -7.14 -12.50

SPA-Trigger Species - -75.00 -58.33 -37.50 - -4.55 0.00 -33.33 0.00 -42.86 -28.00

Non SPA-Trigger

Species - 47.37 54.55 50.00 - 51.43 53.33 44.44 50.00 40.48 48.86


Non SPA-Trigger

Species - 100.00 100.00 100.00 - 88.57 93.33 94.44 87.50 97.62 94.32


Non SPA-Trigger

Species

SPA-Trigger Species

Non SPA-Trigger

Species

SPA-Trigger Species

Non SPA-Trigger

Species

SPA-Trigger Species

Non SPA-Trigger

Species 0.00E+00 1.96E+06 1.58E+06 6.88E+05 0.00E+00 1.10E+05 4.17E+05 3.05E+06 8.04E+04 7.84E+06 1.57E+07

SPA-Trigger Species 0.00E+00 1.23E+04 1.16E+04 1.05E+04 0.00E+00 4.92E+03 1.09E+04 3.14E+03 4.73E+03 2.71E+04 8.51E+04

Non SPA-Trigger

Species 0 19 11 8 0 35 15 18 32 42 88

SPA-Trigger Species 0 8 12 8 0 22 13 3 23 21 50

Non SPA-Trigger

Species - 1.34 0.65 1.33 - 2.14 0.80 1.92 2.14 2.64 2.81

SPA-Trigger Species - 0.36 0.59 0.25 - 1.55 0.43 0.56 1.68 1.92 2.151 This is subject to confirmation and examples of a potential classification system are provided in the above table2 The historic Article 12 reporting format may mean it is not possible to ascertain the situation for 2005-20073 These are the three best measures to be evaluated for use in the accounts4 (Stable + Increasing – decreasing) / (No. species this is all including unknowns) * 1005 (Increase – declining) / (No. Species this is all including unknowns and stable) * 100



Shannon's Index

Prevailing Trends4

Overall Trend5

Intensity of

change6

Coverage of

trends7

Total abundance

(No. Individuals)

Number of

species

All Ecosystems




MAES

Shannon's Index

Bird group classes1

Total abundance

(No. Individuals)

Total abundance

(No. Individuals)

Shannon's Index

Net Change8

Number of

species

Number of

species


70

Table 20 Species Abundance Account using Threat Status Categories for Account for Slovakia

EU Conservation Status Species Population Based Account Using Article 12 for 2007 and 2012: Slovakia


Heathland /

Shrub Marine Inlets

Rivers /

Lakes

Sparsely


Woodland /

Forest

Not Secure

Secure

Threatened

Unknown

Not Secure

Secure

Threatened

Unknown

Not Secure

Secure

Threatened

Unknown

Not Secure - -20.00 0.00 -33.33 - -71.43 -100.00 -75.00 -66.67 -28.57 -50.00

Secure - 22.22 -28.57 0.00 - 50.00 60.00 52.94 43.59 47.83 40.21

Threatened - -100.00 0.00 0.00 - -16.67 0.00 - -16.67 0.00 -8.33

Unknown - -100.00 -100.00 -100.00 - 0.00 -100.00 - 0.00 -33.33 -27.27

Not Secure - -60.00 -25.00 -66.67 - -85.71 -100.00 -75.00 -83.33 -42.86 -66.67

Secure - -33.33 -64.29 -40.00 - 17.50 25.00 0.00 12.82 -6.52 -2.06

Threatened - -100.00 0.00 0.00 - -33.33 -25.00 - -33.33 -50.00 -33.33

Unknown - -100.00 -100.00 -100.00 - -50.00 -100.00 - -50.00 -66.67 -63.64

Not Secure - 60.00 75.00 66.67 - 85.71 100.00 75.00 83.33 71.43 77.78

Secure - 44.44 64.29 60.00 - 57.50 55.00 47.06 58.97 45.65 53.61

Threatened - 100.00 100.00 100.00 - 66.67 75.00 - 66.67 50.00 66.67

Unknown - 100.00 100.00 100.00 - 50.00 100.00 - 50.00 66.67 63.64

Not Secure - 100.00 100.00 100.00 - 100.00 100.00 75.00 100.00 85.71 94.44

Secure - 100.00 100.00 100.00 - 90.00 90.00 100.00 89.74 100.00 95.88

Threatened - 100.00 100.00 100.00 - 83.33 100.00 - 83.33 100.00 91.67

Unknown - 100.00 100.00 100.00 - 100.00 100.00 - 100.00 100.00 100.00

Not Secure

Secure

Threatened

Unknown

Not Secure

Secure

Threatened

Unknown

Not Secure

Secure

Threatened

Unknown

Not Secure 0.00E+00 3.16E+05 1.55E+05 1.54E+05 0.00E+00 9.22E+03 3.29E+05 4.78E+05 9.21E+03 1.49E+05 1.60E+06

Secure 0.00E+00 1.65E+06 1.44E+06 5.44E+05 0.00E+00 9.79E+04 9.72E+04 2.58E+06 6.88E+04 7.69E+06 1.42E+07

Threatened 0.00E+00 1.66E+00 2.74E+02 2.27E+02 0.00E+00 7.22E+03 2.41E+02 0.00E+00 6.24E+03 1.52E+04 2.94E+04

Unknown 0.00E+00 5.22E+02 2.00E+01 1.66E+00 0.00E+00 8.99E+02 1.88E+03 0.00E+00 8.99E+02 1.29E+04 1.71E+04

Not Secure 0 5 4 3 0 7 3 4 6 7 18

Secure 0 18 14 10 0 40 20 17 39 46 97

Threatened 0 1 4 2 0 6 4 0 6 4 12

Unknown 0 3 1 1 0 4 1 0 4 6 11

Not Secure - 1.01 0.38 0.35 - 1.12 0.06 0.65 1.12 0.29 1.55

Secure - 0.91 0.37 1.01 - 1.89 1.30 1.65 1.89 2.59 2.60

Threatened - 0.00 0.38 0.19 - 0.69 0.42 - 0.35 0.08 1.09

Unknown - 0.18 0.00 0.00 - 0.50 0.00 - 0.50 1.34 1.721 This is subject to confirmation and examples of a potential classification system are provided in the above table2 The historic Article 12 reporting format may mean it is not possible to ascertain the situation for 2005-20073 These are the three best measures to be evaluated for use in the accounts4 (Stable + Increasing – decreasing) / (No. species this is all including unknowns) * 1005 (Increase – declining) / (No. Species this is all including unknowns and stable) * 100



Shannon's Index

Number of

species

Total abundance

(No. individuals)

Number of

species

Number of

species

All

Ecosystems




MAES

Total abundance

(No. individuals)

Bird group

classes1

Total abundance

(No. individuals)

Shannon's Index

Coverage of

trends7

Intensity of

change6

Overall Trend5

Prevailing Trends4

Net Change8

Shannon's Index


71

Table 21 Species Status Account for Account for Slovakia

Bird Species Status and Trends in Status Reported under Article 12 for 2007 and 2012: SlovakiaMAES


Heathland /


Sparsely

Vegetat

ed Urban Wetlands

Woodland /

Forest


Not Secure

Secure

Threatened

Unknown

Aggregate Index


Not Secure - -15.38 -22.22 -20.00 - -55.56 -83.33 -57.14 -44.44 8.33 -25.71

Secure - 7.69 -22.22 5.26 - 45.10 38.46 41.67 36.00 38.57 33.09

Threatened - -100.00 -25.00 33.33 - -28.57 0.00 - -30.00 20.00 -11.76

Unknown - -75.00 -50.00 -60.00 - -9.09 -33.33 100.00 -20.00 -14.29 -22.58

Not Secure - -53.85 -44.44 -50.00 - -66.67 -83.33 -71.43 -55.56 -33.33 -51.43

Secure - -38.46 -61.11 -36.84 - 11.76 7.69 -8.33 4.00 -11.43 -8.63

Threatened - -100.00 -37.50 0.00 - -42.86 -25.00 - -50.00 -40.00 -41.18

Unknown - -87.50 -75.00 -80.00 - -54.55 -66.67 0.00 -60.00 -57.14 -61.29

Not Secure - 53.85 66.67 50.00 - 88.89 83.33 71.43 77.78 50.00 62.86

Secure - 53.85 61.11 57.89 - 54.90 61.54 50.00 56.00 48.57 53.24

Threatened - 100.00 87.50 66.67 - 71.43 75.00 - 70.00 40.00 64.71

Unknown - 87.50 75.00 80.00 - 54.55 66.67 0.00 60.00 57.14 61.29

Not Secure - 92.31 88.89 80.00 - 100.00 83.33 85.71 88.89 91.67 88.57

Secure - 100.00 100.00 100.00 - 88.24 92.31 100.00 88.00 98.57 94.96

Threatened - 100.00 100.00 100.00 - 85.71 100.00 - 90.00 100.00 94.12

Unknown - 100.00 100.00 100.00 - 100.00 100.00 100.00 100.00 100.00 100.00

Net Change8

Not Secure

Secure

Threatened

Unknown


Not Secure 0 13 9 10 0 9 6 7 9 12 35

Secure 0 26 18 19 0 51 26 24 50 70 139

Threatened 0 3 8 3 0 7 4 0 10 5 17

Unknown 0 8 4 5 0 11 6 2 10 14 31

Aggregate Index - 77.38 64.29 75.00 - 82.84 80.56 88.71 78.99 87.36 81.941 This is subject to confirmation and examples of a potential classification system are provided in the above table2 The historic Article 12 reporting format may mean it is not possible to ascertain the situation for 2005-20073 These are the three best measures to be evaluated for use in the accounts4 (Stable + Increasing – decreasing) / (No. species this is all including unknowns) * 1005 (Increase – declining) / (No. Species this is all including unknowns and stable) * 100


Aggregate index =

Where Secure = 0

Not Secure = 1

Threatened = 2


N = Number of species (excluding unkown)

All Ecosystems

Number of Species (S)

Bird group classes1

Number of Species

Prevailing Trends4

Overall Trend5


Coverage of trends7

Number of Species

∗ −∑ =

∗



72

Appendix B: Spatial Analysis As highlighted in the second MAES (2014) report, species distributions can potentially provide useful indicators of ecosystem condition. Under the new reporting format, the Article 12 data does provide distribution data. In this Appendix, a critical assessment of how this data and more refined knowledge on bird species habitat preferences can be used to support more ecologically meaningful Species Accounting is explored.

Increasing the resolution of bird species habitat links The MAES typology is derived from aggregations of Corine (coordination of information on the environment) land cover classes (CLC). Corine has been providing land cover data since 1985, the most recent EU wide datasets are for the years 2006 and 2012 and provided at 100 metre resolution. The CLC consists of 44 classes, which are aggregated to the 9 MAES classes to support reporting on state and trends of biodiversity from an ecosystem perspective.

All bird species considered for reporting under Article 12 of the Birds Directive are allocated to ecosystem-types as defined by the MAES typology. However, as the MAES classification consists of only 9 broad land cover classes, the analytical power of the accounts for inferring the condition of ecosystems can potentially be improved using bird species associations with the underlying CLC classes. These associations can be obtained from work undertaken at the Sovon Dutch Centre for Field Ornithology by Van Kleunen (2003). Van Kleunen (2003) defines the habitat use of all European breeding birds, in terms of EUNIS codes from regional and European atlases and literature. More recently these EUNIS codes were then translated to the classes of the CORINE land-cover map (Hendriks et al., 2016). Figure 3 illustrates how this more detailed understanding of bird species habitat preferences can be employed to achieve a further disaggregation of Species Accounts by ecosystem type.

Figure 3 Linkages between Article 12 data and accounts at different aggregation levels showing increasing analytical power


73

Organising information on biodiversity at a more disaggregated level, potentially, increases the analytical power of the account by allowing integration with more refined information on land cover change, ecosystem extent and associated accounting constructs. This is illustrated in Figure 4, which reveals the spatial location of the changes Corine land cover between the 2006 and 2012 for Belgium using the MAES and CLC classifications.

Figure 4 Spatial representation of differences in Corine land cover between 2006 and 2012 for MAES (left) and CLC typologies (right) for Belgium

Figure 4 clearly shows that the CLC classes are experiencing changes but these are obscured within the aggregated MAES classes. This is further illustrated by Figure 5, which shows substantial changes in coniferous and mixed forest to transitional woodland and shrub.


74

Figure 5 Land cover changes between 2006 and 2012 for the CLC typology in Belgium

As shown in Table 22, these changes would be obscured as these CLC classes are all aggregated within the same woodland / forest class under the MAES typology. As it could be that coniferous and mixed forest ecosystem are experiencing different pressures (including habitat conversion), associating bird species as barometers of ecosystem condition at this more disaggregated level can help identify if this is the case and inform more suitable response options for managing woodland and forest ecosystems.

Table 22 CLC Classes within MAES Wood / Forest Ecosystem Type

MAES Type CLC Code

CLC Class

4 - Woodland and forest

311 Broad-leaved forest

312 Coniferous forest

313 Mixed forest

324 Transitional woodland shrub

-8000

-6000

-4000

-2000

0

2000

4000

6000

8000

10000

12000

14000

Co

nti

nu

ou

s u

rban

fab

ric

Dis

con

tin

uo

us

urb

an f

abri

c

Ind

ust

rial

or

com

mer

cial

un

its

Ro

ad a

nd

rai

l net

wo

rks

and

ass

oci

ated

lan

d

Po

rt a

reas

Air

po

rts

Min

eral

ext

ract

ion

sit

es

Du

mp

sit

es

Co

nst

ruct

ion

sit

es

Gre

en u

rban

are

as

Spo

rt a

nd

leis

ure

fac

iliti

es

No

n-i

rrig

ate

d a

rab

le la

nd

Fru

it t

rees

an

d b

erry

pla

nta

tio

ns

Pas

ture

s

Co

mp

lex

cult

ivat

ion

pat

tern

s

Lan

d p

rin

cip

ally

occ

up

ied

by

agri

cult

ure

,…

Bro

ad-l

eave

d f

ore

st

Co

nif

ero

us

fore

st

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sChange in CLC class Extent in Belgium: 2006 to 2012


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To illustrate how the species associations vary under different typologies, an example is provided for two EBCC common bird species in Table 23. Table 23 shows Acrocephalus palustris (marsh warbler) has links to two MAES classes and four CLC classes and Acrocephalus arundinaceus (great reed warbler) has also links to two MAES classes but to only one CLC class.13

Table 23 Ecosystem associations for Acrocephalus palustris and Acrocephalus arundinaceus under MAES and CLC typologies

Species MAES MAES Association CLC CLC Association

Acrocephalus palustris

7 Inland wetlands 4.1.1 Inland marshes

8 Rivers and lakes 4.1.2 Peatbogs

3.2.2 Moors and heathland

3.2.4 Transitional woodland shrub

Acrocephalus arundinaceus

7 Inland wetlands 4.1.1 Inland marshes

8 Rivers and lakes

These different associations can lead to either allow more refined or wider inferences on ecosystem condition to be drawn from the status of these different bird species within an ecosystem accounting area. For example, Figure 6 provides the distribution for Acrocephalus palustris, using both associations. Associated analysis reveals the extent of the MAES classes (44,689 ha) the species is associated with is half that of the CLC classes (21,307 ha). Conversely, Figure 7, shows for the distribution of Acrocephalus arundinaceus the extent of MAES classes the species is associated with (6,747 ha) is larger than the CLC classes (3,090 ha), as this species only has one habitat preference in this more detailed classification (see Table 22).

Figure 6 Distribution of Acrocephalus palustris in Belgium based on MAES associations (left) and CLC associations (right) for 2012

13 These links pertain to the two biogeographical regions within Belgium


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Figure 7 Distribution of Acrocephalus arundinaceus in Belgium based on MAES associations (left) and CLC associations (right) for 2012

Accounting for suitable habitat As identified by the EEA in Table 1, landscape heterogeneity may offer an insight into ecosystem condition within an accounting area. This is because it provides an indicator of ecosystem diversity, which is also likely to correlate with species level diversity as different configurations of ecosystems / land cover will support different communities and species. Analysing the landscape through the lens of species suitability provides an opportunity to integrate information on land cover change within the EU with information on species-level diversity and potential landscape scale condition.

An important component of the Article 12 report is a map of breeding distribution mapped using a 10 x 10 km grid, which can contribute the combined analysis of land cover and species status. However, as the Article 12 species distribution data is only available for one reporting period (2008-2012), it is not possible to directly compare species distributions until data becomes available for the next reporting period.

An option to produce information to support Species Accounts is to evaluate the total area of suitable habitat change (based on changes in CLC classes between 2006 and 2012) within the distributions of individuals or groups of species provided under the Article 12 (2008-2012) reporting. The suitable habitat change analysis can be done both at the level of MAES ecosystem classes, using the species-MAES associations provided with the Article 12 data or for the more disaggregated CLC classes using the SOVON species-CLC associations (which allows for a more spatially detailed analysis). This could then potentially be aggregated within the higher level MAES classes to provide a better insight into which areas of MAES ecosystems were more important for protection than others. For example, an area of forest and woodland (MAES class) with a mix of consistent forest CLC classes is more likely to support multiple bird species than one of consistent CLC class. The steps required to undertake such an analysis, comprise:


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1. Create a consistent and sensible analysis unit (i.e. grid cells)

2. Calculate the total area of each Corine land cover type within the analysis unit

for the two time periods 2006 and 2012

3. Calculate the total area of each species distribution (as reported under Article

12) within the analysis unit

4. Using the crosswalk of links between species and Corine land cover types, for

each analysis unit calculate the total area of suitable habitat for both time

periods

5. Calculate the difference in suitable habitat per analysis unit

Habitat suitability accounting example for Belgium To illustrate the above approach, an example calculation was done for Belgium for all EBCC common birds. The list of species was matched with the spatial Article 12 data for Belgium (bird distributions were clipped to extent of Belgium plus additional 10km buffer), resulting in 95 bird species for analysis. For the analysis unit, the EEA grid at 1-km resolution for Belgium was downloaded from the EEA website. This grid is available for the whole of the EU with unique grid cell references, which are necessary for the analysis. The feature layer with species distributions was then intersected with the EEA grid, resulting in a layer providing information on the area of overlap of each species with each unique grid cell. The Corine land cover raster datasets for 2006 and 2012 were then first converted to polygon feature layers and then intersected with the EEA grid, resulting in a layer with, for each grid cell, the area of each CLC land cover type.

To carry out the calculations, tables of the above layers were exported to a SQL database (SQLite) as well as a table of the crosswalk with species CLC habitat links and analysis was done through a series of SQL queries, as follows:

In the database, the species intersect layer was first linked to the crosswalk

table, i.e. each species was linked to their preferred CLC habitat class by

matching species names.

This table was then matched with the Corine land cover intersect table

matching the CLC habitat links for each species and for each grid cell (i.e. only

retaining links where grid cell ID’s also match). This was done for both 2006

and 2012 Corine intersect layers.

Finally, suitable habitat for each grid cell was calculated by summing the areas

of suitable habitat within grid cells for all species.

Changes in suitable habitat between 2006 and 2012 were then calculated for each grid cell and the table exported and joined with the spatial EEA grid. The resulting changes (expressed as percentage changes) at the grid cell level are shown in Figure 8. Clearly the spatial pattern of the changes is similar to the areas where there are changes in


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CLC land cover type between 2006 and 2012 (see Figure 4). However, this analysis adds the direction and severity of changes at individual and species group level.

Figure 8 Percentage change in suitable habitat between 2006 and 2012 for 95 common bird species in Belgium based on Corine land cover classes

The data also allow for investigating individual species or spatial areas (grid cells). For instance, an assessment can be made of the number of species increasing or decreasing as well as the underlying changes in habitat spatially. As an example, Figure 9 shows a grid cell specific example of analysis for EEA grid reference 1kmE3987N3025 where a total of 56 of the 95 species occur, 12 of these species lose habitat between 2006 and 2012, while 15 species gain habitat in that period and 3 more species can occur in that grid cell in 2012, compared to 2006. These data items could potentially inform a proxy account of biodiversity trends.


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Figure 9 Grid cell specific analysis of suitable habitat changes for common birds in Belgium

An example of a species specific analysis is provided in Figure 10, showing the suitable habitat distribution for Acrocephalus palustris for 2006 and 2012 based on Corine data, as well as the proportion of suitable habitat in each grid cell (low, medium, high). The total amount of suitable habitat for this species has increased, illustrating how changes in ecosystem extent can be integrated with information of species level diversity. The change in the extent of suitable habitat is driven by the increase in the CLC class: transitional woodland shrub (Acrocephalus palustris preferred CLC classs), which mostly replaces coniferous and mixed forest.

Figure 10 Suitable habitat distribution for Acrocephalus palustris in 2006 and 2012 for Belgium using Corine CLC data. Colours indicate the proportion of suitable habitat in the grid cell


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Spatial Issues

Using the CLC species-habitat linkages and CLC data provides greater spatial detail for the assessment of ecosystem condition than relying on the coarse MAES typology and associated linkages. For example, within a MAES ecosystem type, changes in various CLC classes may reflect critical habitat changes, for example degradation of primary to secondary forest habitats. However, a particular issue illustrated in Table 22 is that the CLC species habitat links do not nest under the MAES classes. As such, further harmonisation and expert input would be required in order to allow nested disaggregation of MAES ecosystem preferences to CLC. In addition, the CLC species-habitat linkages remain specific to biogeographical region (i.e. a species can have a single link within one biogeographical region but multiple in another). As such the information on biogeographical regions would need to be included in any accounting approach where the CLC species-habitat linkages were used. In terms of informing wider analysis, however, the CLC associations do provide a means of refining bird species distributions to better understand the impacts of habitat conversion of species distribution and, overall, landscape condition. This can potentially add support for analyses that integrate of information on land cover / ecosystem extent with species-level biodiversity. Finally, the analysis with the CLC classes is computationally more demanding and may be more difficult to do at the European scale.

The species distribution data reported under Article 12 by member states is very coarse

and in many cases modelled from observational data. Therefore there is high

uncertainty whether this species presence data and analysis at 1-km resolution may

provide false accuracy with regards to species presence. With future updates of the

species distribution data, it would be possible to also analyse direct changes in

distributions, which could be linked to ecosystem condition changes. In any spatial

analysis this can be linked with species preferences, either by MAES ecosystem type of

CLC Class, as discussed above. However, any such assessment will be predicated on

potential presence only.

In order to ground-truth any spatial approach or demonstrate the validity of the

accounts constructed by ecosystem type access to primary geo-referenced bird

monitoring data is required. This highlights the potential role for national survey data

collected to inform the PECBMS and national assessments can play in supporting the

development of accounts relevant to species-level diversity and, by extension,

indicators of ecosystem condition in the EU.

Testing the development of species accounts for measuring...

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