Current models of sea level rise for the next century project devastating effects for the Everglades, including loss of freshwater habitats as saltwater intrusion accelerates soil decomposition, altering carbon storage and nutrient cycling, and inducing peat collapse. The specific mechanisms altering soil strength and ultimate leading to peat collapse are still unclear, and stablishing relationships between soil properties that may induce collapse at scales relevant for restoration efforts is difficult given the heterogenous nature of soils and the lack of methods to efficiently evaluate such conditions. In this work I propose the use of a unique array of geophysical methods and fiber optic sensors to infer relationships between geophysical properties and soil strength at multiple scales of measurement that may be linked to specific surface features (such as vegetation patterns) that could be potentially used to generate maps of soil collapse risk. This work will be used to generate preliminary datasets for a multidisciplinary and multi-institution proposal to be submitted for federal support. The work is particularly relevant to local agencies (like NPS or SFWMD) for devising mitigation strategies in coastal FL due to sea level rise, and will train a diverse group of students therefore contributing to DEIJ.
