Predicting ecotopes from hydrodynamic model data

Abstract

Estuaries worldwide are of substantial ecological value due to the presence of various gradients, such as salinity. Preserving the natural value of estuaries is vital for meeting the climate stabilization goals of the Paris Agreement. Recognizing nature as a stakeholder is imperative, given the surpassing value of ecosystem services over global gross domestic product. Quantifying the current ecological state and future ecological shifts faces challenges, including variable dependencies, spatial-temporal disparities, and the limitations in available information. This study introduces EMMA (Ecotope-Map Maker for Abiotics), a method for quantifying the effects of human interventions or climate change scenarios on estuarine ecosystems by linking abiotic characteristics derived from a hydrodynamic model to ecotopes. The Western Scheldt, an estuary connecting the Scheldt river to the North Sea in the Netherlands, serves as a case study. The method successfully reproduced an existing ecotope-map, which is dependent on real-time data such as aerial photographs. The developed method not only proves applicable in assessing the current ecological state and future ecological shifts for hypothetical scenarios but also demonstrates utility in predicting future situations, providing valuable insights for decision-makers in estuarine ecosystem management and contributing to climate and environmental preservation goals.