2015 GSA Annual Meeting in Baltimore, Maryland, USA (1-4 November 2015)

Paper No. 134-12
Presentation Time: 9:00 AM-6:30 PM


GUTIERREZ, Benjamin T., Woods Hole Coastal & Marine Science Center, U.S. Geological Survey, 384 Woods Hole Road, Woods Hole, MA 02543, GIEDER, Katherina, Department of Fish and Wildlife Conservation, Virginia Tech, 150 Cheatham Hall, Blacksburg, VA 24061-0321, PLANT, Nathaniel, U.S. Geological Survey, 600 4th St. South, St. Petersburg, FL 33701, THIELER, E. Robert, U.S. Geological Survey, Woods Hole Coastal and Marine Science Center, 384 Woods Hole Road, Woods Hole, MA 02543, STIPPA, Saywer, Woods Hole, MA 02543, ZEIGLER, Sara, U.S. Geological Survey, Department of Fish and Wildlife Conservation, Virginia Tech, 150 Cheatham Hall, Blacksburg, VA 24061 and KARPANTY, Sarah, Department of Fish and Wildlife Conservation, Virginia Tech, 150 Cheatham Hal, Blacksburg, VA 24061, bgutierrez@usgs.gov

The ability to evaluate the impact of sea-level rise (SLR) on coastal landforms and habitats is important for managers and decision makers. On the east coast of the United States, the fate of barrier islands for the remainder of the 21st century is a critical concern because of a need to maintain both human development and habitat integrity. This situation is expected to worsen as sea-level rises and as the region is struck by extreme storms. We have developed methods to evaluate the fate of barrier islands under higher SLR rates (4-4.5 mm/yr), and to evaluate their habitat value relevant to a number of species that are threatened or endangered which rely on barrier island habitats such as the piping plover (Charadrius melodus).

We present an integrated modelling approach that provides probabilistic predictions of barrier island morphology and nesting habitat suitability for the federally threatened piping plover given future SLR scenarios. To implement this approach, we use three Bayesian networks (BN) to predict the most likely shoreline change rate and barrier island morphology. We use these predictions to evaluate piping plover nesting habitat suitability. The BN models were evaluated using datasets for Assateague Island, Maryland/Virginia using data from 1999, 2002, and 2008 that represent different barrier island geomorphologic and habitat states. Results show that distinct geomorphic conditions are associated with different long-term shoreline change rates and that the shoreline change rates depend on sea-level rise rates. Inclusion of other input variables, such as large-scale geomorphology or rates of beach nourishment lead to the skillful predictions of specific metrics such as dune height, beach width, and beach height that influence habitat suitability. By linking the BN models together to evaluate the extent of suitable nesting habitat for piping plovers yielded predictions that have a 60% success rate. This modelling framework also allows us to evaluate scenarios related to coastal management plans and/or future scenarios where shoreline-change rates may differ from those observed historically. Initial results show that modest SLR rates may increase suitable piping plover nesting habitat area in 50‒100 years and that some beach management strategies can change habitat availability.