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bioRxiv · 10.1101/2024.08.30.610451

Coupling renewable energy infrastructure planning and biodiversity conservation: a modeling-based framework

Froidevaux, J. S. P.·LeViol, I.·Barre, K.·Bas, Y.·Kerbiriou, C.
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Abstract

Reconciling renewable energy planning and biodiversity conservation is urgently needed to address the interconnected crises of climate change and biodiversity loss. However, current strategies to avoid or limit the negative effects of renewable energy on biodiversity still hold major limitations during the planning process that could be overcome with modeling approaches. Here we propose a new applied modeling-based framework aiming to determine potential threats posed by proposed or built projects to biodiversity. By capitalizing on large-scale standardized citizen science biodiversity data to create reference scales of biodiversity levels, this approach aims to better inform the Ecological Impact Assessment (EIA) process at different stages pre- and post-project construction. We demonstrate the practical application of the framework using bat and onshore wind energy development in France as a case study. We reveal that current approaches in renewable energy planning failed to identify sites of biodiversity significance with >90% of wind turbines approved for construction to be placed in sites of high significance for bats. The risks posed by future wind turbines to bats concern all taxa (that are all protected in the European Union), including species with higher collision risks. We highlight how the proposed modeling-based framework could contribute to a more objective evaluation of pre- and post-construction impacts on biodiversity and become a prevalent component of the EIA decision-making. Its implementation could lead to a more biodiversity-friendly renewable energy planning in accordance with the world-leading target to halt biodiversity decline by 2030.

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Froidevaux, J. S. P., LeViol, I., Barre, K., Bas, Y., Kerbiriou, C.. 2024-08-30. Coupling renewable energy infrastructure planning and biodiversity conservation: a modeling-based framework. https://doi.org/10.1101/2024.08.30.610451

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