Assessing Coastal Ecological Vulnerability to Sea-Level Rise in the Manokin Watershed: A Ridge Regression Approach

Abstract

Coastal wetlands of the Mid-Atlantic United States face increasing risks from sea-level rise (SLR), storm surge, and saltwater intrusion, yet spatially explicit, multivariate assessments of ecological vulnerability remain scarce. This study analyzes 400 synthetic habitat vulnerability units across four subareas and seven habitat types within the Manokin Watershed on Maryland’s Eastern Shore. This study characterizes the biophysical landscape using descriptive statistics for 12 continuous environmental variables and key categorical attributes, highlighting differences among habitat types and subareas. Ridge Regression is then applied to model the ecological Vulnerability Index (VI) using 13 biophysical predictors, with emphasis on the influence of projected 2050 SLR. The model attains a 10 fold cross validated R² of 1.00 (RMSE = 3.61 × 10⁻⁸, p < .001), confirming that the VI is essentially a linear combination of its component metrics. The Exposure Index (β = 0.040, z = 31.07, p < .001) and Sensitivity Index (β = 0.030, z = 31.27, p < .001) are the strongest direct predictors, while Adaptive Capacity (β = −0.010) and Ecological Resilience (β = −0.008) provide significant buffering effects. SLR 2050 is statistically significant but functions mainly as an indirect driver through its contribution to exposure. Results indicate that enhancing ecological resilience, shoreline protection, and surrounding conservation areas may reduce vulnerability more effectively than habitat unit scale SLR mitigation efforts.