Conference Agenda

Water-related ecosystems sustain critical ecological and economic functions, yet the existing valuation evidence of the services they provide remains fragmented and methodologically heterogeneous. This limits the ability of policy makers to incorporate water ecosystem services (WES) into environmental-economic accounting frameworks. This paper proposes a meta-regression approach to support exchange-value-based value transfer for ecosystem accounting. We compile a harmonised global dataset of 289 exchange-value estimates from 73 primary studies assessing WES delivered by freshwater, wetland, and groundwater systems. Overall, the mean annual WES value amounts to 1,957 Int$2024 ha-¹ year-¹. Among key services, water flow regulation shows the highest mean value (4,958 Int$2024 ha-¹ year-¹), followed by flood control (4,774 Int$2024 ha-¹ year-¹), water supply (2,903 Int$2024 ha-¹ year-¹), and recreation ES (1,492 Int$2024 ha-¹ year-¹). A linear mixed-effects meta-regression is applied to identify the ecological, socio-economic, and methodological drivers of WES valuation outcomes and to assess the transferability of the resulting value function. Cross-validated predictive performance indicates an average absolute transfer error of approximately 28%, indicating that the proposed meta-analytic value transfer can support the development of monetary ecosystem service accounts that are conceptually consistent and suitable for integration into environmental-economic accounting frameworks. Finally, paper presents an illustrative accounting case study, applying the estimated value function to predict an exchange value for river water supply in the Netherlands and comparing it with an accounting-based reference estimate, as well as with the prediction obtained from the recent freshwater meta-regression by Amatucci et al. (2024). The close alignment between the predicted value and the accounting benchmark provides additional evidence of the practical applicability and robustness of the proposed approach.