Assessing and forecasting the effects of submersion on biodiversity. A method to implement an ecological-quality indicator in a context of coastal realignment and rising sea levels

Abstract

In the context of climate change and sea-level rise, coastal realignment consists in reopening polders to marine waters to favor ‘nature-based’ mitigation measures. Such operations have consequences on biodiversity, which vary depending on the parameters studied and site features. In this study, a multimetric indicator aiming to evaluate and predict the potential ecological quality of sites undergoing a realignment operation was developed. This indicator is based on the combination of two tools, (i) a biological-capacity matrix to assess the importance of different habitats of a defined typology for taxonomical, patrimonial and functional parameters; (ii) habitat maps obtained by photointerpretation for past habitats, by machine learning using space-borne imagery for present habitats and by forecasting using submersion models for future habitats. The indicator is presented in the form of a radar chart, with each axis corresponding to one parameter of the biological-capacity matrix and highlighting its different values for different coastal-realignment scenarios or different time horizons.

Keywords

• Saltmarsh
• Habitats
• Machine learning
• Marine submersion
• Sea-level rise
• Climate change