Determining Living Shoreline Distribution in North Carolina: A Mixed Methods Study

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2023-04-28

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Abstract

Coastal landowners in North Carolina have traditionally deployed hardened structures like seawalls and bulkheads to protect coastal development from erosion and inundation. However, living shorelines have emerged in recent decades as a more ecologically integrated solution, incorporating natural and human-made components to address erosion. To date, few studies have used geospatial tools to understand the deterministic factors driving the distribution of living shorelines in North Carolina. We consider how the distribution of living shorelines varies with a community’s socioeconomic demographics, proximity to enabling institutions, and vulnerability to coastal inundation. We explore the barriers that homeowners face in acquiring a living shoreline and the perceptions that inform their decisions. Using a mixed methods approach, our study uses geospatial tools, decision-tree analysis, and semi-structured interviews with coastal landowners to distill the primary determinants governing the distribution of living shorelines across North Carolina’s coast. We find that among coastal census tracts in North Carolina, the distribution of living shorelines has a significant negative correlation with the percent of the population living in poverty, suggesting that income constrains implementation of these projects. In contrast, vulnerability to coastal inundation and proximity to enabling institutions are not predictive of living shoreline distribution. Interviews elucidate that access to information and relevant networks, capacity to navigate the installation process, and ability to pay informed many homeowners’ decisions to install a living shoreline. Taken together, our findings shed light on the need to consider equity and vulnerability in shoreline protection and coastal restoration.

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Lienhard, Kathryn, and Nicholas Fairbairn (2023). Determining Living Shoreline Distribution in North Carolina: A Mixed Methods Study. Master's project, Duke University. Retrieved from https://hdl.handle.net/10161/27197.


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