Modeling Potential Habitats of Macrophytes in Small Lakes: A GIS and Remote Sensing-Based Approach

Abstract

Macrophytes, which are foundational to freshwater ecosystems, face significant threats due to habitat degradation globally. Habitat suitability models are vital tools used to investigate the relationship between macrophytes and their environment. This study addresses a critical gap by developing a Geographic information system-based HSM tailored for small lakes, which are often overlooked in ecological studies. We included various abiotic predictors to model the potential macrophyte habitat for several small lakes in southern Bavaria (Germany). Key factors such as the distance to groundwater inflow, depth, availability of photosynthetically active radiation (PAR), and littoral slope were identified as significant predictors of macrophyte occurrence. Notably, the HSM integrates remote sensing-based data to derive PAR availability at the growing depths of the macrophytes using Sentinel-2 MSI data. Integration of an MSI-based time series of PAR availability enabled the introduction of a temporal component allowing monitoring and predicting changes in macrophyte habitats over time. The modeled habitat suitability score correlates highly (R = 0.908) with macrophyte occurrence. We see great promise in using habitat modeling for macrophytes as a tool for water management; in particular, the use of Sentinel-2 MSI data for habitat suitability modeling holds promise for advancing water management. By demonstrating the efficacy of GIS- and remote sensing-based HSM, we pave the way for future applications of this innovative approach in ecological conservation and resource management.