Identification of initial vegetation and habitat changes in small temperate fens using remote sensing

Abstract Small temperate fens rank among the most endangered habitats in temperate Europe. In agricultural landscapes, they are highly vulnerable to eutrophication and desiccation, which accelerate biodiversity loss and shifts in the carbon balance due to peat mineralization. The initial signs of habitat change are commonly manifested by shifts in vegetation structure and dominance, accompanied by increasing productivity, which precede major qualitative changes in species composition. The in‐time monitoring of vegetation productivity and site wetness at large areas is essential for guiding conservation management strategies for fens to slow down or reverse undesired changes. Here, we evaluated the ability of satellite (Sentinel‐2) and high‐resolution aerial imagery to detect early, structure‐ and productivity‐related signals of fen deterioration. We compared multispectral and optical imagery with ground‐based data, including both direct measurements and indicators derived from the species composition of the vegetation plots. At the landscape scale where both the acidic poor fens and the base‐rich fens occurred, MSAVI and NGRDI indices performed best, indicating primarily the vascular plant cover, species richness and representation of nutrient‐demanding species. At the within‐site scale, where the differences among plots were largely driven by habitat deterioration, NDVI, NDWI and RENDVI well captured differences in vascular plant productivity estimates and moss biomass measurements. Our results indicate that remote sensing is applicable for the identification of individual fen habitats and their nutrient status at the landscape scale and is even effective in detecting incipient habitat deterioration associated with increasing productivity. We demonstrate that remote sensing also performs well for small, island‐like fen patches. Its wider integration into the mire research would improve monitoring and enhance the amount of available ecological data.