Coastal landscapes evolve in response to sea-level rise (SLR) through a variety of geologic processes and ecological feedbacks. When the SLR rate surpasses the rate at which these processes build elevation and drive lateral migration, inundation is likely.
To examine the role of land cover diversity and composition in landscape response to SLR across the northeastern United States.
Using an existing probabilistic framework, we quantify the probability of inundation, a measure of vulnerability, under different SLR scenarios on the coastal landscape. Resistant areas—wherein a dynamic response is anticipated—are defined as unlikely (p < 0.33) to inundate. Results are assessed regionally for different land cover types and at 26 sites representing varying levels of land cover diversity.
Modeling results suggest that by the 2050s, 44% of low-lying, habitable land in the region is unlikely to inundate, further declining to 36% by the 2080s. In addition to a decrease in SLR resistance with time, these results show an increasing uncertainty that the coastal landscape will continue to evolve in response to SLR as it has in the past. We also find that resistance to SLR is correlated with land cover composition, wherein sites containing land cover types adaptable to SLR impacts show greater potential to undergo biogeomorphic state shifts rather than inundating with time.
Our findings support other studies that have highlighted the importance of ecological composition and diversity in stabilizing the physical landscape and suggest that flexible planning strategies, such as adaptive management, are particularly well suited for SLR preparation in diverse coastal settings.
|Publication Subtype||Journal Article|
|Title||Probabilistic patterns of inundation and biogeomorphic changes due to sea-level rise along the northeastern U.S. Atlantic coast|
|Series title||Landscape Ecology|
|Contributing office(s)||Woods Hole Coastal and Marine Science Center|
|State||Connecticut, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Virginia|
|Google Analytic Metrics||Metrics page|