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Integrating ecosystem services into impact assessments: A process-based approach applied to the Belgian coastal zone
Van der Biest, K.; Staes, J.; Prigge, L.; Schellekens, T.; Bonte, D.; D'hondt, B.; Ysebaert, T.; Vanagt, T.; Meire, P. (2023). Integrating ecosystem services into impact assessments: A process-based approach applied to the Belgian coastal zone. Sustainability 15(21): 15506. https://dx.doi.org/10.3390/su152115506
In: Sustainability. MDPI: Basel. e-ISSN 2071-1050
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| Trefwoorden |
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| Author keywords |
impact assessment; ecosystem services; marine ecosystem; coastal ecosystem; cumulative effects; scoping; ecosystem processes; cross-sectoral effect |
| Auteurs | | Top |
- Van der Biest, K., meer
- Staes, J.
- Prigge, L.
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- Schellekens, T.
- Bonte, D.
- D'hondt, B.
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- Ysebaert, T.
- Vanagt, T.
- Meire, P.
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| Abstract |
Policy makers increasingly acknowledge the importance of considering ecosystem services (ESs) and biodiversity in impact assessment (IA) to reduce ecosystem degradation and halt ongoing losses of biodiversity. Recent research demonstrates how ESs can add value to IA, i.e., by shifting the focus from avoiding negative impacts to creating opportunities, by linking effects on ecological functioning to benefits for society, and by providing a multi-disciplinary framework that allows to consider cross-sectoral effects. However, challenges exist to its implementation in practice. The most commonly used ES models do not consider interactions among ESs. This restricts their capacity to account for cross-sectoral effects. Integrating ESs into IA also increases time investments as they cover a wide variety of disciplines and need detailed information. This paper presents a pragmatic approach that tackles these challenges and may facilitate the inclusion of ESs into IA. The approach focuses on ecosystem processes as the driver of ESs and biodiversity and the basis to evaluate effects of a project. Using the Belgian coastal ecosystem, we illustrate how the approach restricts data needs by identifying the priority ESs, how it improves the coverage of cross-sectoral effects in IA, and how it contributes to a more objective selection of impacts. |
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