Topological and Morphological Controls on Morphodynamics of Salt Marsh Interiors

Abstract

Salt marshes are important coastal environments and provide multiple benefits to society. They are considered to be declining in extent globally, including on the UK east coast. The dynamics and characteristics of interior parts of salt marsh systems are spatially variable and can fundamentally affect biotic distributions and the way in which the landscape delivers ecosystem services. It is therefore important to understand, and be able to predict, how these landscape configurations may evolve over time and where the greatest dynamism will occur. This study estimates morphodynamic changes in salt marsh areas for a regional domain over a multi-decadal timescale. We demonstrate at a landscape scale that relationships exist between the topology and morphology of a salt marsh and changes in its condition over time. We present an inherently scalable satellite-derived measure of change in marsh platform integrity that allows the monitoring of changes in marsh condition. We then demonstrate that easily derived geospatial and morphometric parameters can be used to determine the probability of marsh degradation. We draw comparisons with previous work conducted on the east coast of the USA, finding differences in marsh responses according to their position within the wider coastal system between the two regions, but relatively consistent in relation to the within-marsh situation. We describe the sub-pixel-scale marsh morphometry using a morphological segmentation algorithm applied to 25 cm-resolution maps of vegetated marsh surface. We also find strong relationships between morphometric indices and change in marsh platform integrity which allow for the inference of past dynamism but also suggest that current morphology may be predictive of future change. We thus provide insight into the factors governing marsh degradation that will assist the anticipation of adverse changes to the attributes and functions of these critical coastal environments and inform ongoing ecogeomorphic modelling developments.