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Framework synthesis study presents a modular ecosystem assessment model across diverse environmental sectors, highlighting streamlined translation of ecological evidence into policy.
This repository contains the Supplementary materials for SELINA Deliverable D6.5. SELINA Deliverable D6.5, titled "Integrated Ecosystem Assessment," represents a core scientific output of the SELINA project, specifically designed to address the persistent implementation gap between scientific evidence and its practical application in policy and business. This Deliverable focuses on advancing integrated ecosystem assessments, which translate fragmented research into a cohesive, actionable format that combines biophysical, socio-cultural, and economic value domains. The primary result of this work is the Framework for Integrated Ecosystem Assessment (FIEA), a modular and stepwise structure developed through an iterative co-creation process with diverse stakeholders. The FIEA synthesises the complementary strengths of existing foundational frameworks, such as the operational MAES Framework (Burkhard et al., 2018), the Natural Capital Protocol (Capitals Coalition, 2016), the IPBES 5-step valuation framework (Termansen et al., 2023), and the Integrated Approach to Planning (Ministry of Environmental Protection and Regional Development of the Republic of Latvia, 2021) into a single, unified architecture. Its flexible design allows users across various sectors to select specific steps tailored to their capacity. Deeper social-ecological integration is explored through five thematic LoIs on the topics of ES co-production, the DPSIR (Driver–Pressure–State–Impact–Response) model, temporal scales, integration across value domains, and the role of biodiversity for ES. The findings and methodological insights generated in this Deliverable establish a robust foundation for the final phases of the SELINA project. All outcomes will be integrated into the interactive SELINA Compendium of Guidance (CoG), which serves as the primary science-policy-business interface for evidence-based decision-making.
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Lange et al. (2026) studied this question.
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