Mean Species Abundance (MSA) is a composite biodiversity integrity indicator, defined as the average abundance of original species relative to their abundance in undisturbed reference ecosystems. An MSA value of 1 (100%) corresponds to a pristine ecosystem with full integrity; an MSA value of 0 indicates the complete local extinction of original species.
MSA is derived from the GLOBIO4 model (Global Biodiversity Model for Policy Support, PBL Netherlands Environmental Assessment Agency), a globally calibrated framework for estimating the combined impact of multiple human pressure drivers on biodiversity.
The indicator is decomposed into five sub-indicators, each capturing the impact of a distinct pressure driver:
The overall MSA value displayed on the platform is the area-weighted mean of the MSA values for all CORINE Land Cover (CLC) classes present within the site polygon.
MSA is computed using the GLOBIO methodology (Alkemade et al., 2009; Schipper et al., 2020). Each sub-indicator captures a different pressure driver.
MSA Land Use is derived from CORINE Land Cover classes. Each pixel is mapped to its CLC class, and each class is assigned an MSA value from GLOBIO look-up tables calibrated by ecological meta-analysis. The spatial mean across all valid pixels within the site polygon yields the KPI value:
MSA Climate Change quantifies biodiversity loss from temperature increase:
where cc_degradation = per-pixel CLC class climate-change degradation coefficient, and Delta T = difference between the mean temperature of the current year and the 1941--1961 reference baseline.
MSA Infrastructure models disturbance from roads using a logistic regression:
where d = Euclidean distance in km from the nearest road (capped at 150 km). The 1/3 weight factor reflects that 2/3 of species are assumed unaffected by infrastructure.
MSA Fragmentation models the effect of habitat patch size:
where A = area in km squared of the connected natural land-cover patch (computed via connected-component labelling with roads as barriers).
Data are sourced from the GLOBIO MSA Model v4 and CORINE Land Cover at 100 m resolution.
Mini Bar Chart. A set of horizontal bar rows showing the MSA sub-indicator values (Land Use, Climate Change, Infrastructure, Fragmentation) as proportional bars within a biodiversity state panel.
Purpose: To display, in a single panel, how each pressure driver (land use, climate change, infrastructure, fragmentation) contributes to the overall biodiversity integrity of the site, comparing the site (ROI) against the control area (CA).
Description: The panel is titled "Mean species abundance" and is found within the State of Biodiversity section (ESRS E4-5, AR 37). It shows four bar rows labelled: "From land use", "From climate change", "From infrastructure presence nearby", and "From habitat fragmentation (infrastructure and land use)". Each bar row shows the ROI value as a proportional bar coloured by quality grade (A--E palette), with the CA value shown alongside for comparison. Within the land-use row, two sub-rows ("Animals", "Plants") break down the fauna and flora components. A "Total" aggregated row summarises the overall MSA score. An objectives panel below the bars shows restoration targets (Regenerate 30%, Match Neighbor, Half Earth, Match Benchmark, Full Recovery).
MSA Sub-indicators
How it's calculated: Each bar value is the sub-indicator MSA score for that pressure driver, expressed as a percentage (0--100), computed via the GLOBIO model. The Total row is the area-weighted mean across CLC classes. Sub-indicator quality grades use their own thresholds (see legend below).
Legend:
For the Total MSA row:
| Level | Range (%) | Color | Meaning |
|---|---|---|---|
| A | 80 -- 100 | ■ #00A67A | Near-pristine biodiversity; minimal degradation |
| B | 65 -- 80 | ■ #00DF80 | Good species abundance; limited pressures |
| C | 50 -- 65 | ■ #FFD21E | Moderate degradation; measurable impact |
| D | 30 -- 50 | ■ #FF8B16 | Significant degradation; reduced species abundance |
| E | 0 -- 30 | ■ #FF367F | Severe biodiversity loss; heavily degraded ecosystem |
Interpretation example:
If the panel shows MSA Land Use = 45 (grade D, orange bar) and MSA Climate Change = 88 (grade A, green bar), the site's biodiversity is primarily threatened by land use rather than climate change — directing conservation efforts towards land cover restoration rather than emissions reduction.
Highlights Card. A compact summary card in the environmental highlights grid showing the site's total MSA score.
Purpose: To surface the overall biodiversity integrity score at a glance, alongside other environmental KPIs (heat islands, protected areas, etc.), so users can immediately assess the biodiversity status of their site.
Description: The card displays the label "MSA total site" and a numeric value (0--100, expressed as a percentage) for the site (ROI). The card may show a delta badge comparing the site value against the control area. This element appears in the summary tab of the Highlights section ("Your relationship with climate and nature") on the Overview page.
How it's calculated: The displayed value is the area-weighted mean MSA across all CLC classes within the site polygon.
Interpretation example:
If the card shows 62, the site retains 62% of its original species abundance relative to a pristine reference — a moderate score indicating measurable human pressure but a functioning ecosystem.
Highlights Table Row. A set of columns in the multi-site KPI comparison table on the Overview page, one row per site, showing MSA and its sub-indicators side by side.
Purpose: To enable multi-site comparison of biodiversity integrity across all sites in a portfolio, showing Total MSA, biodiversity damage in hectares, and the four sub-indicator values (Climate Change, Infrastructure, Fragmentation, Animals, Plants) at a glance.
Description: The table includes 7 MSA-related columns: MSA (SITE/CONTROL), Biodiversity damage extent (ha), MSA Climate Change (SITE/CONTROL), MSA Infrastructure (SITE/CONTROL), MSA Fragmentation (SITE/CONTROL), MSA Animals (SITE/CONTROL), and MSA Plants (SITE/CONTROL). Each cell shows the site value and the control area value side by side. The table supports copy-to-clipboard and CSV export.
How it's calculated: Each column is the corresponding sub-indicator value. The biodiversity damage extent (ha) is calculated as (1 − MSA/100) multiplied by the site area in hectares.
Legend: No colour-coded legend visible in the table itself; values are plain numeric.
Interpretation example:
If the MSA column shows "72 / 85" (site/control), the site has lower biodiversity integrity than its surrounding landscape — indicating that anthropogenic pressures within the site boundary are reducing species abundance relative to the regional background.
Sites Progress Column. A selectable axis label in the multi-site matrix scatter chart, allowing MSA to be placed on the X or Y axis to compare sites along the biodiversity integrity dimension.
Purpose: To allow portfolio-level analysis by comparing how MSA relates to other KPIs (e.g., aridity, heat island) across all sites simultaneously in a bubble/scatter view.
Description: In the Sites Progress matrix, each site is represented as a bubble. MSA can be selected as either the X or Y axis variable from a dropdown. When selected, the axis label reads "Mean Species Abundance (MSA)" and the axis description tooltip explains the indicator. Sub-indicator variants such as "MSA Climate Change" are also available.
How it's calculated: Axis values are the site's total MSA score (or the relevant sub-indicator).
Interpretation example:
If MSA is plotted on the Y axis and heat island intensity (UTFVI) on the X axis, sites in the upper-left quadrant have high biodiversity and low heat stress — optimal ecological conditions — while those in the lower-right combine high heat stress with low biodiversity integrity.
Data Table. A paginated historical data table on the Scenarios page showing per-site MSA (Land Use) and MSA Hectares values across polygon versions and years.
Purpose: To provide a historical record of MSA Land Use scores and biodiversity damage in hectares for each site across all computed scenario versions, enabling trend analysis and version comparison.
Description: The table has two MSA-specific columns: "MSA (LU)" (the land-use sub-indicator value, expressed as a percentage) and "MSA Hectares (ha)" (the biodiversity damage extent in equivalent degraded hectares). Both show a Site and a Control value side by side. Other columns include NP (kg/ha/y), Impermeability %, Natural cover %, year, polygon version, and land use version.
How it's calculated: "MSA (LU)" = area-weighted mean of per-pixel CLC class MSA look-up values. "MSA Hectares (ha)" = (1 − MSA Land Use / 100) multiplied by site area in hectares.
Interpretation example:
If the table shows MSA (LU) = 42 Site / 67 Control for 2022 and MSA (LU) = 38 Site / 68 Control for 2023, the site's biodiversity is declining while the control remains stable — suggesting increasing land use pressure within the site boundary.
Map Layer. An interactive raster map layer showing MSA values at pixel level (100 m resolution), available within the CLC & Pollinator Analysis layer group.
Purpose: To reveal the spatial distribution of biodiversity integrity across the site and its surroundings, identifying degraded patches (low MSA, dark/red pixels) and well-preserved areas (high MSA, green pixels).
Description: The layer selector under the map contains a "MSA" group with four sub-layers: MSA (overall Land Use), MSA Climate Change, MSA Fragmentation, and MSA Infrastructure. Each sub-layer renders a continuous colour raster with the GLOBIO-calibrated colour scale. Additional sub-layers include the fauna component (Animals), flora component (Plants), and the machine-learning-based MSA prediction.
How it's calculated: Each pixel receives the MSA value corresponding to its CLC class from GLOBIO look-up tables (for MSA Land Use) or from the relevant sub-indicator model (MSA Climate Change, MSA Infrastructure, MSA Fragmentation).
Legend: Continuous colour gradient (256 steps):
| Sub-layer | Range | Gradient |
|---|---|---|
| MSA / MSA Land Use | 0 -- 1 | ■ #0e0a07 (degraded) → ■ #e5251f (red) → ■ #fbbd5a (amber) → ■ #29b635 (pristine) |
| MSA Climate Change | 0.75 -- 1 | ■ #e5251f → ■ #fbbd5a → ■ #29b635 |
| MSA Infrastructure | 0.67 -- 1 | ■ #e5251f → ■ #fbbd5a → ■ #29b635 |
| MSA Fragmentation | 0.80 -- 1 | ■ #e5251f → ■ #fbbd5a → ■ #29b635 |
Interpretation example:
If the map shows a large green patch in the eastern part of the site transitioning to dark red near a road network in the west, the western edge is highly degraded by infrastructure disturbance (low MSA Infrastructure) while the forest interior retains near-pristine conditions.
| Source | Provider | Coverage | Resolution | Period |
|---|---|---|---|---|
| GLOBIO MSA Model v4 | PBL Netherlands Environmental Assessment Agency | Global | Look-up table (CLC-based) | Continuous |
| CORINE Land Cover | European Environment Agency | Europe | 100 m | 1990 -- 2018 |
| CLC Backbone | European Environment Agency | Europe | 100 m | 2012, 2018 |
MSA Land Use is computed by mapping each 100 m pixel to its CORINE Land Cover class and assigning the corresponding MSA value from GLOBIO look-up tables, which are calibrated by ecological meta-analysis across hundreds of published studies. The fauna and flora sub-components use dedicated look-up columns for animals and plants respectively. The spatial mean across all valid pixels within the site polygon yields the final KPI value.
MSA Climate Change uses a per-pixel CLC class climate-change degradation coefficient combined with the temperature anomaly relative to the 1941--1961 baseline. The formula produces values in the 75--100 range, as climate change effects in the GLOBIO model are constrained to a maximum 25% reduction in species abundance.
MSA Infrastructure applies a logistic regression model calibrated on warm-blooded vertebrate responses to road proximity. The Euclidean distance to the nearest road is computed for each pixel, capped at 150 km. The 1/3 weighting factor reflects that only warm-blooded vertebrates are modelled as sensitive to infrastructure disturbance.
MSA Fragmentation uses connected-component labelling on the natural land-cover raster, with roads acting as barriers, to compute the area of each contiguous natural habitat patch. The logistic regression converts patch area to an MSA value using the same 1/3 weighting approach.
The overall MSA value is the area-weighted mean across all CLC classes present in the site polygon.
Alkemade, R., van Oorschot, M., Miles, L., Nellemann, C., Bakkenes, M., ten Brink, B. (2009). "GLOBIO3: A Framework to Investigate Options for Reducing Global Terrestrial Biodiversity Loss". Ecosystems, 12(3), 374--390. DOI: 10.1007/s10021-009-9229-5
Schipper, A.M., et al. (2020). "Projecting terrestrial biodiversity intactness with GLOBIO 4". Global Change Biology, 26(2), 760--771. DOI: 10.1111/gcb.14848
PBL Netherlands Environmental Assessment Agency (2020). "GLOBIO: Global Biodiversity Model for Policy Support". PBL Publication 3748. https://www.globio.info/