Condition Matters: Fine-Tuning Ecosystem Service Capacity with Ecosystem Condition

Ecosystem service (ES) capacity matrices are widely used for ES assessment and mapping due to their operational simplicity. However, capacity matrices assign uniform capacity scores to ecosystem types without accounting for local variations in ecosystem condition, leading to assessment errors arising from condition blindness. We present a methodological framework for integrating ecosystem condition into ES capacity matrices through ecosystem-specific condition thresholds. Ecosystem condition is characterised using two components: structural condition (e.g. vegetation cover, productivity, canopy height) and biological condition (e.g. biodiversity intactness, soil organic carbon, natural habitat proportion). We grouped ES into five functional groups according to their dependence on the two condition components. We then developed allocation tables linking condition levels to ES capacity within the capacity matrices. We applied our framework to a 430 km² study area in the Hauts-de-France region (France). After testing different ecosystem condition thresholds for this test case area, the 20th-80th percentiles of condition values appeared to be the most adequate to define condition classes. ... mehrWe also demonstrate that condition values have to be assessed separately for each ecosystem type (urban, agricultural, forest and aquatic). Condition adjustment modified capacity scores by 0.58-0.81 capacity score on average over the 0-5 ES scale (12-16% of the capacity range), with maximum local differences reaching 2.1 (42% of the range). Validation against six independent ES reference datasets shows statistically significant improvements in correlation coefficients ranging from 0.036 to 0.130 (mean Δr = 0.078, p < 0.001 for all services) when incorporating condition adjustments. Our framework provides an operational method for implementing the SEEA-EA conceptual linkage between ecosystem condition and ecosystem service capacity, with potential applications in natural capital accounting, land-use planning, and environmental impact assessment.