Metadata Factsheet

3. Goals and Targets addressed

3a. Goal

Headline Indicator for Goal A: The integrity, connectivity and resilience of all ecosystems are maintained, enhanced, or restored, substantially increasing the area of natural ecosystems by 2050; Human induced extinction of known threatened species is halted, and, by 2050, the extinction rate and risk of all species are reduced tenfold and the abundance of native wild species is increased to healthy and resilient levels; The genetic diversity within populations of wild and domesticated species, is maintained, safeguarding their adaptive potential.

3b. Target

Headline Indicator for Target 1: Ensure that all areas are under participatory, integrated and biodiversity inclusive spatial planning and/or effective management processes addressing land- and sea-use change, to bring the loss of areas of high biodiversity importance, including ecosystems of high ecological integrity, close to zero by 2030, while respecting the rights of indigenous peoples and local communities.

Target 2, 3 and 7.

5. Definitions, concepts and classifications

Indicator definition:

The Red List of Ecosystems framework assesses the relative risk of ecosystem collapse of an ecosystem type. The indicator ‘Red List Index of Ecosystems (RLIe)’ measures the average risk of ecosystem collapse of a group of ecosystems, and tracks change in this over time based on genuine change in the risk category of each ecosystem (i.e. excluding changes in categories owing to improved knowledge or better data). The Index is expressed as changes in an index ranging from 0 to 1, with decreases (towards 0) resulting from more threatened ecosystems or heighted risk, and increases (towards 1) showing improvements in risk status. A value of 0 means that all ecosystems have collapsed. A value of 1 means that all ecosystems are listed as Least Concern.

The RLIe can be calculated for any set of ecosystem types for which there are Red List of Ecosystems assessments. It can thus be calculated at the subnational, national, regional or global level, or for broad ecosystem groups (e.g. ecosystem functional groups).

Other key concepts and definitions:

Ecosystems: a dynamic complex of plant, animal and micro-organism communities and their non-living environment interacting as a functional unit (Convention on Biological Diversity, 1992). Specifically, ecosystems are made up of living components (biotic complexes and assemblages of species), the abiotic environment, the processes and interactions within and between the biotic and abiotic components, and the physical space in which these operate (Keith et al., 2013).

Ecosystem types are differentiated from one another by a degree of uniqueness in composition, structure, and ecological processes and function. Ecosystem types present a useful model or abstraction of the complexities of the natural world. Similar definitions are used for other, often synonymous, terms such as ecological communities, habitats, biotopes, and vegetation types (Keith et al. 2013, Nicholson et al. 2021). Ecosystem types can be described, classified, and identified using the IUCN Global Ecosystem Typology (Keith et al. 2022).

Ecosystem collapse is the endpoint of ecosystem decline, when an ecosystem loses its defining features (i.e., species, assemblages, structure, and functions) and is replaced by a different, often depauperate, ecosystem type. Collapse can be irreversible, but some ecosystems may recover, over long timeframes or with restoration. The risk of ecosystem collapse is the likelihood that an ecosystem will collapse over a specified timeframe (Keith et al. 2013).

Risk categories: The risk of ecosystem collapse is based on the risk categories each ecosystem is assigned through assessment under the Red List of Ecosystems framework. The risk categories include, in order of increasing risk of collapse: Least Concern, Near Threatened, Vulnerable, Endangered, Critically Endangered, and Collapsed. If there are insufficient data to assign a risk category, a criterion or ecosystem type it is considered Data Deficient, or Not Evaluated if not assessed.

Ecosystem functional groups: The number of ecosystem types will be reported by Ecosystem Functional Group from the Global Ecosystem Typology. Ecosystem functional groups comprise “a group of related ecosystems within a biome that share common ecological drivers, which in turn promote similar biotic traits that characterise the group. Derived from the top-down by subdivision of biomes” (Keith et al. 2022, https://global-ecosystems.org/). Examples include: M1.1 seagrass meadows, M1.2 kelp forests and M1.3 photic coral reefs in the marine realm, T1.1 tropical/subtropics lowland rainforests and T4.2 pyric tussock savannas in the terrestrial realm, F1.6 episodic arid rivers and F2.8 artesian springs and oasis in the freshwater realm, and MFT1.3 coastal saltmarshes and reedbeds in the transitional realm between freshwater, marine and terrestrial realms.

Guidelines for the application of the Red List of Ecosystems can be found on the IUCN website (Keith et al. 2013; Bland et al. 2017).

5b. Method of computation

Reported data:

The reported data will come from Red List of Ecosystems assessments. The data reported will be the number of ecosystems in each risk category, per ecosystem functional group, as a table (see example in Table 1). Only the categories of risk (Least Concern, Near Threatened, Vulnerable, Endangered, Critically Endangered, and Collapsed) will be used for calculation of RLIe, but additional columns for categories Not Evaluated or Data Deficient can be added to the table to indicate existing data gaps in national assessments (see section 5j on data gaps and 5k on missing data). Further guidance in this topic will be finalised in 2024. This advice will also address how to report on ecosystem functional groups in which no or only some ecosystem types have been assessed, differentiating ‘Not Evaluated’ ecosystem types within an otherwise assessed group (i.e. identified but not assessed, which may be included in the reporting table), and whole ecosystem functional groups or biomes that have not been evaluated (where the number of ecosystem types may be unknown, as the classification process may not have begun within the country). The advice will also deal with treatment of EFGs, biomes or even realms that are not applicable in the country (e.g. no marine ecosystems types in a land-locked country).

Table 1. An example of the type of data to be reported on A1 Red list of ecosystems: the number of ecosystems per risk category per ecosystem functional group, showing results for Colombia’s national Red List of Ecosystems assessment (Etter et al. 2020a), where CO=Collapsed, CR= Critically Endangered, EN=Endangered, VU=Vulnerable, NT=Near threatened, LC=Least Concern, DD=Data deficient, and NE=Not Evaluated. Reporting templates will be provided in 2024. See a further example in Table 2 in section 5k.

Red List Index of Ecosystems (RLIe):

The RLIe measures trends in ecosystem collapse risk based on the proportion of ecosystem types in each risk category (for details see Rowland et al. 2020). The RLIe is the weighted mean of ordinal ranks assigned to each risk category:

where Wc_(i,t) is the risk category rank for ecosystem i in year t (Collapsed=5, Critically Endangered=4, Endangered=3, Vulnerable=2, Near Threatened=1, Least Concern=0; following the approach taken for the Red List Index of species survival; Butchart et al. 2004; 2007), W_CO is the maximum category rank (CO = Collapsed=5), and n is the total number of ecosystem excluding Data Deficient or Not Evaluated ecosystem. The RLIe ranges from 0 (all ecosystems Collapsed) to 1 (all Least Concern).Data Deficient ecosystem types may be included by included by allocating them to risk categories in proportion with data sufficient ecosystem types (see section 5k on missing data). The RLIe should be calculated for each ecosystem type.

Genuine change

The Indicator should only report on genuine changes in risk category. The IUCN Red List of Ecosystems group will publish guidance on this topic in 2024/ in the forthcoming update to the Guidelines for the application of IUCN Red List of Ecosystems Categories and Criteria. This draws on guidelines from the Red List of Threatened Species and associate indicators (see headline indicator A.3), and experience from countries that have undertaken repeat Red List of Ecosystems assessments (e.g. Finland, Norway and South Africa).

Indicator testing:

A key question for indicators is how sensitive they are to biodiversity change. Several studies have tested aspects of the Red List of Ecosystems framework in its capacity to detect meaningful change in ecosystems. For example, Murray et al. (2017) tested metrics for restricted range size (Criterion B – restricted geographic distribution) for their capacity as predictors of ecosystem collapse in landscapes subject to stochastic threats. They found that the methods currently used in Red List of Ecosystems assessments for measuring range size are the best spatial metrics for estimating risks from stochastic threats. Analyses from Norway found that the RLIe could provide time-series to reliably compare alternative policy scenarios (Kyrkjeeide et al. 2021). The RLIe has been tested for sensitivity and responsiveness using an ecosystem simulation model of a coral reef (Rowland et al. 2020b), showing that the RLIe can differentiate between low and high threat levels, responds to both increases in threats (e.g., climate change) and decreases (e.g., effective conservation policy), and detects change in area and integrity.

5c. Data collection method

The reported data will ideally stem from national Red List of Ecosystems assessments. However data can also come from regional, global and sub-national assessments, subject to national validation (see section 5e). Ideally, data should come ideally from comprehensive assessments of all ecosystems in all ecosystem functional groups within a country. If this is not possible, data can be used from assessments of all ecosystems within an ecosystem functional group (nationally or globally, e.g. Figure 2), or in a sub-national area such as a province. The Red List of Ecosystems is the global standard for assessing risk of ecosystem collapse and biodiversity loss to all marine, freshwater, and terrestrial ecosystems. Red List of Ecosystems assessments collate standardised knowledge, maps and data about ecosystems, and apply quantitative criteria to estimate relative risks of ecosystem collapse to identify threatened ecosystems. The five criteria are: (A) change in ecosystem area; (B) restricted ecosystem distribution; (C) change in the abiotic environment (e.g., hydrological processes); (D) change in biotic processes and components (e.g., species interactions); and (E) the probability of collapse estimated using dynamic ecosystem models (where such models are available). Change in area and integrity (Criteria A, C and D) is assessed over a 50-year timeframe (past and/or future), and/or since the onset of industrialised change (1750 at the earliest). Change in integrity (Criteria C and D) is measured using ecosystem-specific metrics, to capture different ways in which ecosystems respond to drivers of biodiversity loss. For example, integrity can be tracked in forests using the proportion of old-growth (Burns et al. 2015), in coral reefs using coral cover and fish abundance (Obura et al. 2022), and in rivers using hydrological flow (Ghoraba et al. 2019).

Through assessment against one or more criteria, ecosystems are assigned to ordinal risk categories: Collapsed, Critically Endangered, Endangered, Vulnerable, Near Threatened, Least Concern; if there are insufficient data to assign a risk category, a criterion or ecosystem is considered Data Deficient, or Not Evaluated if not assessed. Ecosystems listed as Critically Endangered, Endangered, Vulnerable are considered threatened, and ecosystems in those categories can collectively be referred to as “threatened”.

Detailed guidelines are available to support the assessment of each criterion (Bland et al. 2017; Keith et al. 2013). Ideally, as many criteria as possible should be assessed, but the scope can be tailored to the resources and data available. Guidelines to support rapid assessments using one or a few criteria have been developed (e.g. Holness & Botts 2022) and used in national assessments across Africa (e.g. NEMA 2020).

Data used in Red List of Ecosystems assessments can come from a diverse range of sources (see reviews in Rowland et al 2018, Murray et al 2018). Ecosystem classifications and maps used in these assessments typically come from national ecosystem inventories (e.g. forest types), local experts (e.g. within universities or environment institutes), government agencies, or when these are not available, from global classifications and maps of ecosystem types (e.g., the Global Ecosystem Typology, https://global-ecosystems.org/). Data on change in ecosystem area (for Criterion A) typically comes from similar data, although an increasing number of global datasets are also available – many of these are listed as data sources for Headline Indicator A.2 (extent of natural ecosystems) and as complementary indicators in the Global Biodiversity Framework monitoring framework (e.g., tree cover loss, wetland extent trends index, and trends in mangrove extent). Assessing Criteria C and D requires ecosystem-specific variables, which may come from a range of data sources, including scientific literature, reports, experts, historical accounts, and existing indicators (including some listed as complementary indicators in the monitoring framework, e.g., live coral cover). These data may be field-based empirical data, remotely sensed (e.g., satellite imagery, see Murray et al 2018), modelled (extrapolating from field and/or remotely sensed data) or a combination. The Red List of Ecosystems guidelines (Bland et al 2017) provide advice on the types of data needed, and how it should be analysed. Further guidance and reviews are currently being developed to provide further support for assessors.

5d. Accessibility of methodology

Application of the Red List of Ecosystems framework for undertaking Red List of Ecosystems assessments is supported by a range of resources, all accessible via the Red List of Ecosystems website (iucnrle.org):

• Formal guidelines published by IUCN (Bland et al. 2017): https://portals.iucn.org/library/sites/library/fil.... 
• Multiple peer-reviewed scientific papers have been published to describe the assessment methods in detail (e.g. Keith et al 2013, and others – see reference list below)
• Free online training material via FutureLearn (in partnership with Deakin University and IUCN) and IUCN Academy.

• Tools to support assessment (available at https://iucnrle.org/rle-material-and-tools)
• A growing database of assessments https://iucnrle.org/rle-database

The Red List Index of Ecosystems can be calculated for any set of ecosystem types for which Red List of Ecosystems assessments have been undertaken. The method for calculating the RLIe was published in an open-access peer-reviewed paper (Rowland et al. 2020).

Scripts to calculate the indicator using the program RStudio are publicly available via the Red List of Ecosystems GitHub site (https://github.com/red-list-ecosystem/rle_indices). The script provides the code to calculate the indicator and includes examples of the indicator outputs using sample data from the continental assessment of 136 temperate and tropical forests across 51 countries/territories in the Caribbean and Americas (Ferrer-Paris et al. 2019). The sample data are provided to demonstrate the structure of the data required to calculate the indicator. The RLIe can also be calculated in a spreadsheet, using the formula and weightings in 5b; a reporting template with such a calculation will be developed as part of the reporting advice.

5e. Data sources

The ideal data for reporting on A.1 are national Red List of Ecosystems assessments, typically done by governments or in partnership with government (e.g. with partners in universities or NGOs). Thus the data should ideally come from national databases.

Where national data do not exist, there are several other sources of assessment data that can be used for national reporting, including from regional and sub-national assessments. A review published in 2024 estimates that Red List of Ecosystems assessments are available for 63 countries for all terrestrial ecosystem types, 41 countries for all freshwater ecosystems (including freshwater-transitional ecosystem types such as wetlands), and 32 countries for all marine ecosystems (including marine transitional ecosystem types such as mangroves). A further 30 countries have assessments for subsets or groups of terrestrial ecosystems, for example, temperate and tropical forest ecosystem types in the Americas (Figure 2), while 49 have subsets of marine and marine-transitional ecosystem types, e.g. all coral reefs (Obura et al 2021) or mangroves (Etter et al 2020a), and 47 have subsets of freshwater ecosystems (see figure 4 and Nicholson et al. 2024).

Data used from sources other than national Red List of Ecosystems assessments will require validation to be used in national reporting, e.g. from national biodiversity experts. Guidelines and tools will be developed in 2024/2025 to support countries in this validation process.

Red List of Ecosystems assessments are typically published in technical reports, and/or peer-reviewed publications. An increasing number of assessments are available in a publicly-available, centralised database of assessments, including some national assessments (e.g. Colombia – the database is available via the Red List of Ecosystems website: iucnrle.org). This database will become a key source of data at national, regional and global scales in the medium term. In the short-term, Red List of Ecosystems assessments may be accessed from relevant national agencies, NGOs, or other data holders/providers.

5f. Availability and release calendar

To date, over 4000 ecosystems have been assessed using the Red List of Ecosystems framework (Figure 4) in over 110 countries (Nicholson et al. 2024). For countries where assessments are not available, global terrestrial assessments are anticipated to be available for key ecosystems by 2026-2027, in particular key terrestrial and freshwater ecosystem types, with anticipated updates every 5 years. Some countries have already undertaken repeat assessments (e.g., South Africa, Norway, and Finland) providing time-series. At a national level, the release will vary by country.

The RLIe can already be calculated for all countries that have completed Red List of Ecosystems assessments (Figure 4), and a time-series for those countries with repeat assessments (e.g. Norway, Figure 4). Countries can use available code or seek assistance to calculate RLIe values from their National Red List of Ecosystems assessments.

Figure 4. Current availability of Red List of Ecosystems assessments by country. Countries where all terrestrial ecosystems have been assessed (comprehensive assessments) are shown in red (63 countries), and those with subsets of terrestrial ecosystem assessed are shown in pink (25). Regions where all marine ecosystems (including marine-transitional ecosystems) have been assessed are shown in dark blue (32), those with subsets of marine ecosystems assessed in pale blue (46). Black dots show individual ecosystems that have been assessed, separate from any comprehensive assessments or group assessments (e.g. all forests). Coverage of freshwater ecosystems (including freshwater-transitional ecosystems such as wetlands) is not shown, but typically mirrors terrestrial assessments (41 countries, with subsets in 43).

5g. Time series

5h. Data providers

The preferred primary source will be national Red List of Ecosystems assessments (see section 5e), typically undertaken by government environmental agencies, often in partnership with universities, NGOs and other partners. These assessments will typically be available via government databases and/or reports, and/or in the scientific literature. They may also be available in the Red List of Ecosystems Database. 

Where national assessments are not available, data can come from sub-national, regional or global assessments, as outlined in section 5e, subject to national validation. Some of these are available in the Red List of Ecosystems database (https://assessments.iucnrle.org), or may be available via reports, scientific publications or partner organisations (e.g. NGOs). See section 5e.

5i Data compilers

Data to calculate the indicator are currently compiled independently by the assessment teams for available national or global assessments. It is anticipated that in the medium term, tools hosted by IUCN and the IUCN Commission on Ecosystem Management, including the Red List of Ecosystems database, may provide national and global-level indicators, but these are not yet available.

5j. Gaps in data coverage

To date, over 4000 ecosystems have been assessed in over 100 countries (Nicholson et al. 2024; iucnrle.org/rle-in-progress). The current goal is to assess key ecosystem groups by 2026-2027. Figure 4 shows the spatial coverage at the start of 2024, based on data in Nicholson et al. (2024). Subject to national validation, up to 90 countries may be able to report based on these data.

Assessment effort are biased towards terrestrial ecosystem types, with more countries having assessments of all terrestrial ecosystems than freshwater or marine, while South America has much greater spatial coverage than Northern Africa, South Asia or Eastern Europe. Spatial gaps will be closed through a combination of targeted global-level projects across broad thematic ecosystem groups (e.g. forests, mangroves, coral reefs), and national assessments. National reporting of Not Evaluated and Data Deficient categories could provide further evidence on existing data gaps and help guide future efforts.

5k. Treatment of missing values

There are multiple forms of missing data that need to be addressed for headline indicator A.1 Red List of Ecosystems, including lack of assessments, and uncertain assessments. Explicitly reporting on ecosystems that are Not Evaluated, Data Deficient or Not Applicable (i.e. marine ecosystems in a landlocked country, or polar ecosystem functional groups in a tropical country), at ecosystem type, ecosystem functional group or biome level, will help identify data and knowledge gaps for targeted work. In some cases it will be appropriate to report these in the national reporting tables (see Table 2 for Myanmar); reporting guidance will be developed in 2024/2025.

Guidelines will be developed to support countries in reporting in the face of missing data on Red List status of their ecosystems. These will range from countries with near-complete national assessments (e.g. most ecosystem functional groups are comprehensively assessed, i.e. all ecosystem types assessed), to those with comprehensive assessments for only some ecosystem functional groups, to those with no or very little data (the white areas of Figure 4).

Countries may also have available Red List of Ecosystems assessments (e.g. regional assessments), that require validation for use in national reporting. Guidelines for validation and data-quality assessment will also be developed, with the aim of developing consistent validation protocols for headline indicators A.2 Extent of natural ecosystems and B1 Services provided by ecosystems, which may also rely on non-government data sources.

Table 2. Example table for reporting on A1 Red list of ecosystems: the number of ecosystems per risk category per ecosystem functional group, showing results for Myanmar, including Data Deficient ecosystem types that were assessed but where there were insufficient data or information to assign them to a risk category (Murray et al. 2020).

National ecosystem assessments can also be incomplete where there are insufficient resources to evaluate all criteria or ecosystem types – such ecosystems are reported as Not Evaluated. Category Not Evaluated is always excluded from calculation of RLIe.  Missing data may stem from incomplete assessments, or coarse scale assessments that exclude finer scale variation in ecosystems. 

Individual ecosystem assessments can also be uncertain, where insufficient data exist to assign an ecosystem type to a risk category. This can result in some poorly known ecosystem types being listed Data Deficient. Uncertainty in Red List of Ecosystems assessment can be dealt with through a range of methods, including bounds in estimates of risk category – please see the Red List of Ecosystems Guidelines for more information (Bland et al 2017).

Data deficient ecosystem types can be included in the Red List Index of ecosystem (RLIe) through similar means to headline indicator A.3 Red List Index for species, i.e. by randomly allocating Data Deficient (DD) ecosystem types to risk categories with a probability proportional to the number of non-DD ecosystem types in each risk category, repeating this 1,000 times through a bootstrapping procedure, and reporting the mean.

6. Scale

6a. Scale of use

Scale of application: Global, Regional, National

Scale of data disaggregation/aggregation

Global/ regional scale indicator can be disaggregated to national level: Yes

National data is collated to form global indicator: Yes

The indicator can be used at national, regional, and global levels, depending on data availability. Global/regional values can be disaggregated to national scales (e.g. Ferrer-Paris et al. 2019, Obura et al. 2022). In principle, national data can be aggregated to form regional/global assessments, though this is yet to be applied and will require more testing.  

6b. National/regional indicator production

6c. Sources of differences between global and national figures

The procedure for applying the Red List of Ecosystems framework is the same across national to global scales. The outcomes may vary between national and global levels where:

• National assessments have more detailed ecosystem units than global assessments; for example, a comparison of ecosystem classifications in South Africa found that more ecosystems were listed as threatened when using more finely defined units (Payet et al. 2013).

• Ecosystems extend beyond national boundary, particularly for smaller countries. This can also be dealt with to some degree by aligning and aggregating similar ecosystems with the Global Ecosystem Typology, and considering how this issue is addressed in species red listing (e.g. national assessment guidelines that account for rescue effects).

• There are inconsistencies among nations in data and indicators used in assessments, and in the criteria assessed. This will require tools to be developed, learning from experiences in economics where the methods have been developed to account for ways in which national accounts, GDP and other economic indicators vary per country.

An example of this can be seen in Figures 1 and 2, which show results from the Colombian National assessment, where the RLIe for forest ecosystems is approx. 0.63 (Figure 1) and results for Colombia from the regional forest ecosystem assessment, where the RLIe is approx. 0.52 (Figure 2). With more research and analyses, understanding of the general patterns, underlying causes and implications of these differences will improve.

6d. Regional and global estimates & data collection for global monitoring

6d.1 Description of the methodology

The methods of conducting Red List of Ecosystems assessments are well established, and the same across national, regional and global scales. The methods of calculating the RLIe are also the same across national, regional and global scales. At present, indicators at these different scales are calculated based on assessments at the corresponding scales; country values are not yet aggregated to calculate regional or global assessments. Where ecosystem types extend beyond national boundaries, there is the possibility of aggregating data using the IUCN Global Ecosystem Typology – approaches for doing so are currently being trialled.

6d.2 Additional methodological details

6d.3 Description of the mechanism for collecting data from countries

7a Other MEAs, processes and organisations

7a. Other MEA and processes

N/A

7b. Biodiversity Indicator Partnership

Yes

10. Data reporter

10a. Organisation

International Union for Conservation of Nature (IUCN)

Commission on Ecosystem Management (CEM)

10b. Contact person(s)

This meta-data sheet was prepared by Emily Nicholson (University of Melbourne, Australia; AHTEG), with contributions from: Brett Painter (Environment and Climate Change Canada, AHTEG), Jess Rowland (Monash University, Australia), Arild Lindgaard (Norwegian government); Tytti Kontula and Anne Raunio (SYKE, Finland); Mandy Driver (independent consultant, South Africa) Andrew Skowno (SANBI, South Africa), Jose Ferrer-Paris (University of NSW, Australia), David Keith (University of NSW, Australia), Marcos Valderrabano (IUCN), Tom Brooks (IUCN), David Obura (CORDIO East Africa), Mishal Gudka (University of Melbourne, CORDIO East Africa), Julianna Santos (University of Melbourne) and the Ad Hoc Technical Expert Group (AHTEG).

Emily Nicholson (emily.nicholson@unimelb.edu.au)

Marcos Valderrabano (marcos.valderrabano@iucn.org)