The System of Environmental Economic Accounting - Ecosystem Accounting (SEEA-EA) is a spatially-based, integrated statistical framework for organising biophysical information about ecosystems, measuring ecosystem services, tracking changes in ecosystem extent and condition, valuing ecosystem services and assets and linking this information to measures of economic and human activity. It is an integrated statistical framework adopted by the United Nations Statistical Commission.
The SEEA-EA outlines five sets of ecosystem accounts:
As part of a recent amendment to Regulation (EU) No 691/2011 on environmental economic accounts, it will be mandatory to report ecosystem extent, condition and services (physical flow) accounts in line with SEEA-EA. The monetary flow of ecosystem services and the monetary value of ecosystem assets will not need to be accounted for under the new regulation. Mandatory reporting by member states commences in 2026.
The System of Environmental-Economic Accounting – Ecosystem Accounting (SEEA-EA) sets out an Ecosystem Condition Typology (ECT) which distinguishes between abiotic ecosystem characteristics, biotic ecosystem characteristics, and landscape and seascape characteristics (Table 4.1).
| Group | Class | Descriptor |
|---|---|---|
| Abiotic ecosystem characteristics | A1. Physical state | Physical descriptors of the abiotic components of the ecosystem (e.g. soil structure, water availability). |
| A2. Chemical state | Chemical composition of abiotic ecosystem compartments (e.g. soil nutrient levels, water quality, air pollutant concentrations). | |
| Biotic ecosystem characteristics | B1. Compositional state | Composition/diversity of ecological communities at a given location and time (e.g. presence/abundance of key species, diversity of relevant species groups). |
| B2. Structural state | Aggregate properties (e.g. mass, density) of the whole ecosystem or its main biotic components (e.g. total biomass, canopy coverage, annual maximum normalised difference vegetation index (NDVI)). | |
| B3. Functional state | Summary statistics (e.g. frequency, intensity) on the biological, chemical and physical interactions between the main ecosystem compartments (e.g. primary productivity, community age, disturbance frequency). | |
| Landscape-level characteristics | C1. Landscape and seascape | Metrics describing mosaics of ecosystem types at coarse (landscape, seascape) spatial scales (e.g. landscape diversity, connectivity, fragmentation). |
This release compiled indicators representing each of these ECT characteristics to ensure that all dimensions of the typology were included. Within these broad groups, indicators were further mapped to specific condition classes - physical, chemical, compositional, structural, and functional state, alongside landscape and seascape - to ensure comprehensive coverage of the ecosystem's condition across each dimension (Table 4.2). Some indicators also correspond to those mandated under Regulation (EU) 691/2011 (marked with an asterisk). Together, these indicators provide a structured, multi-dimensional basis for assessing and monitoring the condition of Ireland's Forest & Woodland ecosystems over time.
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*mandatory indicators as per Regulation (EU) 691/2011 |
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| Group | Class | Indicators | Measurement Unit |
|---|---|---|---|
| Abiotic ecosystem characteristics |
1. Physical state 2 Chemical state |
Normalised Difference Water Index (NDWI) Soil Organic Carbon stock in topsoil |
index (-1 to 1) tonnes/ha |
| Biotic ecosystem characteristics |
3. Compositional state |
Forest bird index* |
index |
|
4. Structural state |
Normalised Difference Vegetation Index (NDVI) Tree Cover Density* |
index (-1 to 1) % |
|
| 5. Functional state |
Growing Stock Volume Forest Disturbances |
m3/ha % of total forest |
|
|
Landscape and seascape characteristics |
6. Landscape and seascape |
Landscape Naturalness | % |
The Normalised Difference Moisture Index (NDMI) is a satellite-derived indicator used to measure the water content of vegetation. It is calculated based on near-infrared (NIR) and short-wave infrared (SWIR) reflectance. Values range from -1 to +1, with higher values typically indicating water content in vegetation, and negative values indicating water stress. Within the Ecosystem Condition Typology (ECT), NDMI falls under the Physical State Characteristics class.
NDMI was calculated using Sentinel‑2 L2A imagery - Bands 8 (near-infrared) and 11 (short-wave infrared) - accessed through the Copernicus Data Space Ecosystem (CDSE) via the OpenEO API, covering the calendar year from January to December. Median values for each band were compiled into a raster, and a NDMI raster was computed using the formula proposed by Gao (B08 - B11)/(B08 + B11) at a resolution of 10m x 10m, then aggregated to 100m x 100m and reprojected to EPSG:3035 coordinate system to match the resolution and coordinate reference system of the ecosystem extent map. Zonal statistics for the resulting raster were extracted for Ireland's Forest & Woodland ecosystems at both level 1 and level 2 of the EU Ecosystem Typology.
Note: NDMI is a type of index that measures water content; the term Normalised Difference Water Index is often used interchangeably with NDMI. However, NDWI can also refer to an index computed using Green and Near-Infrared bands (McFeeters formula) which measures open surface water bodies and flooded areas, so for the sake of clarity NDMI is used here.
Soil organic carbon (SOC) stock refers to the total mass of organic carbon stored within a given volume or depth of soil, typically expressed in tonnes of carbon per hectare. For this indicator, SOC stock was measured to a depth of 30cm and represents carbon accumulated from decomposed plant and animal matter. It is a key indicator of soil health, fertility, and the land's capacity to sequester carbon and mitigate climate change. SOC stock is influenced by land use, management practices, vegetation cover, and soil type, and changes in its level over time can signal shifts in ecosystem condition. Within the ECT, SOC stock falls under the Chemical State Characteristics class.
Values for the reference years were provided by the Forest Service based on National Forest Inventory (NFI) data. NFI reporting years do not align with the three yearly reporting schedule for Ecosystem Accounts under Regulation (EU) 691/2011, and so the 2018 figures used for Table 2.1 are drawn from the 2017 NFI, while the 2024 figures are based on the 2022 NFI. SOC stock (tonnes/ha) was calculated by dividing the total quantity of soil organic carbon (tonnes) by the total NFI forest area (hectares).
Tree Cover Density refers to the percentage of ground area covered by tree canopy within a given unit of land, providing a measure of canopy closure and forest structural density. It is a mandatory indicator under Regulation (EU) 691/2011 and, within the ECT, falls under the Structural State class, reflecting the physical arrangement and density of vegetation within the ecosystem. Changes in tree cover density over time can indicate afforestation, deforestation, forest degradation, or canopy regeneration, making it a useful proxy for tracking structural changes in forest ecosystems.
Tree cover density for Forest & Woodland ecosystems was calculated using the Tree Cover Density product (10 x 10m resolution) accessed on the Copernicus Data Space Ecosystem. Zonal statistics were extracted for Ireland's Forest & Woodland ecosystem at both level 1 and level 2 of the EU Ecosystem Typology.
The Normalised Difference Vegetation Index (NDVI) is a widely used satellite-derived indicator that provides a consistent measure of vegetation presence, condition, and productivity across large areas. NDVI is calculated from the difference between near infrared light - which healthy vegetation strongly reflects - and red light, which vegetation absorbs for photosynthesis. Values range from -1 to +1, with higher values indicating denser or more vigorous green vegetation. Within the ECT, NDVI falls under the Structural State Characteristics class.
NDVI was calculated using the same workflow as NDMI, this time substituting Bands 4 (red) and 8 (near-infrared) to measure vegetation productivity.
Growing stock volume refers to the volume of standing trees in a forest, typically measured in cubic metres per hectare, encompassing the stem wood of living trees above a certain diameter threshold. It is a fundamental measure of forest resource availability and productivity, reflecting both the extent of forest cover and the density and maturity of tree stands. Growing stock volume is widely used to track changes in forest biomass over time, assess timber supply potential, and estimate carbon stores in living tree biomass, making it a key indicator of ecosystem condition.
Values for the reference years were calculated from the European Forest Accounts data compiled by CSO Environment Division for the European Forest Accounts module of Regulation (EU) 691/2011.
Forest disturbances such as wildfires, diseases, and storm/wind events represent significant pressures on forest ecosystems, affecting tree health, stand structure, and the overall resilience of forest cover. Wildfires can cause immediate and extensive loss of biomass, alter soil properties, and release stored carbon back into the atmosphere. Forest diseases - caused by pathogens such as fungi, bacteria, or other phytopathogens - tend to act more gradually, driving tree mortality, reduced growth rates, and long-term shifts in species composition. Storm and wind damage, by contrast, is typically episodic: high winds can cause sudden, widespread windthrow and windbreak, producing abrupt losses of standing volume and altering stand structure in a single event, while also leaving surviving trees more vulnerable to secondary pests such as bark beetles. Because it tends to occur in short, intense episodes rather than accumulate gradually, storm damage can generate large single-year spikes in reported damaged area, distinguishing its temporal pattern from that of disease or, to a lesser extent, wildfire. Monitoring the extent and frequency of these disturbances is essential for understanding pressures on ecosystem condition and forest resilience over time.
For Ireland, occurrence-based data on disease damage were drawn from official ash dieback statistics published by the Department of Agriculture, Food and the Marine, while wildfire figures were drawn from Ireland's reported Common Reporting Tables (CRT) and national inventory reporting under the UNFCCC. Storm/wind damage data were compiled from an expert estimate for 2017 and a 2025 government report assessing forest damage following Storms Darragh and Éowyn. Reported storm damage rose sharply in 2025, consistent with the severity of that storm season, with an estimated 23,652 ha of forest affected - the largest single-year figure recorded for this damaging agent in the reporting series.
Landscape naturalness reflects the extent and continuity of semi-natural and natural habitats relative to artificial land uses, infrastructure, and landscape modification. Within the ECT, landscape naturalness falls under the Landscape & Seascape Characteristics class.
Landscape naturalness was assessed following the methodology presented in Maes et al. (2023) and aligned with the Global Biodiversity Framework indicator A-2, which requires distinguishing natural from anthropogenic ecosystems at level 2. A 23 x 23 pixel (529-hectare) moving-window approach was used to calculate the proportion of natural ecosystem pixels in the neighbourhood of each forest pixel. The resulting values were grouped into twelve categories ranging from 0% to 100%. Table 4.3 sets out the crosswalk between ecosystem type and naturalness class used.
For Ireland's Forest & Woodland ecosystem, the types of Forest & Woodland considered to be highly modified or anthropogenic are Plantations and Transitional Forest & Woodland Shrub, which comprise approximately 75% of the total forest area, as shown in Table 2.2. Naturalness values reflect the landscape context of each forest type relative to surrounding land cover rather than an intrinsic property of the forest itself, and are mainly affected by the surrounding prevalence of managed grassland and cropland, in addition to plantations within the forest estate itself.
Ecosystem extent maps for the reference years 2018, 2021, and 2024 were compiled by the CSO Ecosystem Accounts Division, drawing on national and EU geospatial datasets including CLCplus Backbone, Copernicus High Resolution Layer (HRL) data, PRIME2, the National Land Cover Map, the Land Parcel Identification System (LPIS), and forest administrative and survey data, using a 1-hectare minimum mapping unit aligned with the EU Ecosystem Typology. For more information see Ecosystem Extent Accounts 2024.
NDVI and NDMI were derived from Sentinel-2 surface reflectance data, accessed and processed through the OpenEO API on the Copernicus Data Space Ecosystem, with composites produced for the calendar year for each reference year.
Soil organic carbon stock data were provided by the Forest Service, based on National Forest Inventory (NFI) data, with the 2018 reference year drawn from the 2017 NFI and the 2024 reference year from the 2022 NFI.
Growing stock volume was sourced from European Forest Accounts data, compiled by CSO Environment Division, based on data from the NFI and survey data.
Forest disturbance data were provided by the Forest Service, based on multiple sources depending on damaging agent: disease damage from official ash dieback statistics published by the Department of Agriculture, Food and the Marine; wildfire from Ireland's Common Reporting Tables (CRT) and National Inventory Document (NID) reporting under the UNFCCC; and storm/wind damage from an expert estimate (2017) and Earth Observation data-based assessment for 2025 (McInerney et al. 2026). Note that the 2025 figure includes damage from Storm Darragh (December 2024) as well as Storm Éowyn (January 2025); as it was not possible to separate the effects of the storms in the data source, it was all allocated to the more severe event in 2025.
Landscape naturalness was assessed following the methodology of Maes et al. (2023), aligned with Global Biodiversity Framework indicator A-2, using the CSO ecosystem extent maps to classify Level 2 ecosystem types as natural or anthropogenic within a 529-hectare moving-window analysis.
Reported SOC stock values reflect a temporal mismatch between the reference years and underlying survey data, with the 2018 and 2024 figures actually derived from 2017 and 2022 NFI reports respectively, meaning short-term changes in land management or condition may not be captured.
Reported forest damage figures are drawn from different data sources and methodologies depending on the damage type and year, including official disease statistics, Common Reporting Tables (CRT)/ National Inventory Document (NID) reporting for wildfire, and a mix of expert estimation (2017) and Earth Observation based assessment (2025) for storm damage, which limits direct comparability of trends over time.
Since naturalness is measured relative to landscape context within a 529-hectare neighbourhood rather than as an intrinsic property of a given forest pixel, the resulting values are sensitive to the composition of surrounding land cover and to the fixed window size, which may not capture naturalness patterns at finer or coarser spatial scales. In Ireland's case, naturalness values for Forest & Woodland are driven mainly by the surrounding prevalence of managed grassland and cropland, in addition to plantation forestry itself. Low naturalness values for Ireland's forest estate should therefore be read as a consequence of this plantation-dominated, agriculturally fragmented landscape structure, rather than as a property of individual stands in isolation.
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