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Bibliographic Details
Main Authors: Lorré, Dries, Vandamme, Sara, Braeckman, Ulrike, Janssen, Colin R, Asselman, Jana
Format: Artículo científico
Language:en
Published: The Science of the total environment 2025
Subjects:
Online Access:https://pubmed.ncbi.nlm.nih.gov/40288166/
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Table of Contents:
  • Quantitative approach for assessing risks and benefits to the supply of ecosystem services in response to human activities. Lorré, Dries Vandamme, Sara Braeckman, Ulrike Janssen, Colin R Asselman, Jana Risk Assessment Ecosystem Conservation of Natural Resources Environmental Monitoring Human Activities Humans Animals Escalating human activities threaten ecosystems and the benefits they provide, known as ecosystem services (ES). Despite the recognized importance of ES for both ecological health and human well-being, integrated methods for evaluating ES within decision-making frameworks remain limited. Current environmental assessments, such as ecological risk assessment (ERA), typically focus on risks to specific endpoints such as survival, growth and reproduction of test species without capturing broader ecosystem risks and benefits. This study introduces a novel method designed to quantitatively assess risks and benefits to ES supply by integrating ES as assessment endpoints within ERA. Using cumulative distribution functions, we establish risk and benefit thresholds and calculate the probability and magnitude of exceeding these following human interventions. The method was tested by quantifying risk and benefit metrics for a regulating ES, waste remediation, in three marine offshore case studies: an existing offshore wind farm, a hypothetical mussel longline culture, and a multi-use scenario combining both. The results enabled detailed comparisons of the probability and magnitude of creating risks and providing benefits across scenarios, demonstrating the utility of cumulative distribution functions for both visualizing and quantifying risks and benefits to ES supply. This generic and broadly applicable method can evaluate ES trade-offs regardless of the ecosystem under study, providing a valuable tool to operationalize the integration of ES into decision-making and environmental management frameworks.