Predicting Sea-Level Rise Impacts to Barrier Island Habitats
Researchers at WARC are determining if temporal mismatches between digital elevation models and land cover data can impact estimates of inundation of beach habitat for barrier islands and low-lying beaches off the Gulf Coast of Florida.
The Science Issue and Relevance: Sandy beach ecosystems, such as those found on barrier islands, are extremely vulnerable to the effects of climate change, including habitat loss as sea levels rise. These ecosystems are dynamic; waves, currents, tides, and storms can greatly affect barrier island morphology as sand is moved from one location to another. The fact that the habitat itself can move makes it difficult to accurately predict future habitat loss from rising seas; however, these estimates are crucial for beach-dependent species that are being assessed for protection under the U.S. Endangered Species Act (ESA). To identify suitable habitat for species of concern, remotely sensed land cover maps are often used. Land cover maps can be coupled with digital elevation models to help predict what areas might be impacted by sea-level rise. Because calculations of whether each map pixel is above or below water for a given sea-level rise projection is based on the elevation data, a mismatch between land cover and elevation data collection dates, especially for habitats that move, could result in biased predictions of habitat inundation. This project aims to assess whether the choice of land cover data can lead to incorrect predictions of the proportion of beach habitat that will be inundated as sea-levels rise for 12 barrier islands and low-lying beaches off Florida’s Gulf Coast.
Methodology for Addressing the Issue: Researchers used two land cover datasets that differed in the date that the data were acquired: one map coincided with the date that the digital elevation data were collected, and the second land cover dataset did not. Researchers compared estimates of beach habitat inundated by sea-level rise between the two datasets, demonstrating how a temporal mismatch between digital elevation models and land cover data can impact estimates of beach habitat inundation for the areas of interest.
Future Steps: Barrier island beaches can move over time, making it challenging to predict the amount of beach habitat that will be inundated under future sea-levels. Yet, decisions made by the U.S. Fish and Wildlife Service to list or de-list species under the ESA often rely on such predictions. Incorrect estimates could impact decision-making. This work demonstrates the value of using remotely sensed land cover data that has been collected at the same time as elevation data when estimating beach habitat inundation from sea-level rise.
Researchers at WARC are determining if temporal mismatches between digital elevation models and land cover data can impact estimates of inundation of beach habitat for barrier islands and low-lying beaches off the Gulf Coast of Florida.
The Science Issue and Relevance: Sandy beach ecosystems, such as those found on barrier islands, are extremely vulnerable to the effects of climate change, including habitat loss as sea levels rise. These ecosystems are dynamic; waves, currents, tides, and storms can greatly affect barrier island morphology as sand is moved from one location to another. The fact that the habitat itself can move makes it difficult to accurately predict future habitat loss from rising seas; however, these estimates are crucial for beach-dependent species that are being assessed for protection under the U.S. Endangered Species Act (ESA). To identify suitable habitat for species of concern, remotely sensed land cover maps are often used. Land cover maps can be coupled with digital elevation models to help predict what areas might be impacted by sea-level rise. Because calculations of whether each map pixel is above or below water for a given sea-level rise projection is based on the elevation data, a mismatch between land cover and elevation data collection dates, especially for habitats that move, could result in biased predictions of habitat inundation. This project aims to assess whether the choice of land cover data can lead to incorrect predictions of the proportion of beach habitat that will be inundated as sea-levels rise for 12 barrier islands and low-lying beaches off Florida’s Gulf Coast.
Methodology for Addressing the Issue: Researchers used two land cover datasets that differed in the date that the data were acquired: one map coincided with the date that the digital elevation data were collected, and the second land cover dataset did not. Researchers compared estimates of beach habitat inundated by sea-level rise between the two datasets, demonstrating how a temporal mismatch between digital elevation models and land cover data can impact estimates of beach habitat inundation for the areas of interest.
Future Steps: Barrier island beaches can move over time, making it challenging to predict the amount of beach habitat that will be inundated under future sea-levels. Yet, decisions made by the U.S. Fish and Wildlife Service to list or de-list species under the ESA often rely on such predictions. Incorrect estimates could impact decision-making. This work demonstrates the value of using remotely sensed land cover data that has been collected at the same time as elevation data when estimating beach habitat inundation from sea-level rise.