Integrated survey methodologies provide process-driven framework for marine renewable energy environmental impact
James Chapman1, Benjamin J Williamson2, Ana Couto1
1School of Biological Sciences, Zoology Building, University of Aberdeen, Tillydrone Avenue, AB24 2TZ, UK.
Marine Environmental Research
|May 8, 2024
Summary
Marine renewable energy assessments need better data on predator-prey links. This study used acoustics and models to understand how fish school movements, influenced by hydrodynamics, affect seabird presence for improved environmental impact assessments (EIA) and habitat regulations appraisals (HRA).
Area of Science:
- Marine ecology
- Oceanography
- Environmental impact assessment
Background:
- Marine renewable energy (MRE) developments cause environmental changes impacting marine life.
- Current UK Environmental Impact Assessment (EIA) and Habitats Regulations Appraisal (HRA) guidelines inadequately address predator-prey dynamics and vulnerability.
- Understanding the link between hydrodynamics, prey distribution, and top predator movements is crucial for effective assessments.
Purpose of the Study:
- To develop a process-driven framework for investigating predator-prey linkages between seabirds and fish schools.
- To assess the effectiveness of integrating multi-trophic survey data with hydrodynamic models.
- To inform revisions of EIA and HRA guidelines for more robust marine ecosystem impact assessments.
Main Methods:
- Integration of multi-trophic ship survey data (active acoustics, observer data) with a 3D hydrodynamic model.
- Utilizing an upward-facing seabed platform for in situ data collection.
- Analyzing predator-prey linkages and the influence of environmental covariates.
Main Results:
- Observer data revealed the necessity of measuring physical drivers of species distribution variance.
- Active acoustics demonstrated the value of in situ data over modelled data for predicting prey and predator presence.
- Hydrodynamic changes significantly influence fish school distribution and, consequently, top predator presence.
Conclusions:
- Current EIA and HRA methods require revision to incorporate process-driven understanding of predator-prey interactions.
- In situ data collection and advanced modeling are essential for accurately predicting ecosystem impacts of MRE.
- Improved frameworks will enhance the robustness and transferability of assessments for MRE and climate change impacts.
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