Model-Based Selection of Areas for the Restoration of Acrocephalus paludicola Habitats in NE Germany

Abstract

The global Aquatic Warbler (Acrocephalus paludicola, Vieillot, 1817) population has suffered a major decline due to the large-scale destruction of its natural habitat (fen mires). The species is at risk of extinction, especially in NE Germany/NW Poland. In this study, we developed habitat suitability models based on satellite and environmental data to identify potential areas for habitat restoration on which further surveys and planning should be focused. To create a reliable model, we used all Aquatic Warbler presences in the study area since 1990 as well as additional potentially suitable habitats identified in the field. We combined the presence/absence regression tree algorithm Cubist with the presence-only algorithm Maxent since both commonly outperform other algorithms. To integrate the separate model results, we present a new way to create a metamodel using the initial model results as variables. Additionally, a histogram approach was applied to further reduce the final search area to the most promising sites. Accuracy increased when using both remote sensing and environmental data. It was highest for the integrated metamodel (Cohen's Kappa of 0.4, P<0.001). The final result of this study supports the selection of the most promising sites for Aquatic Warbler habitat restoration.