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  • 1
    Publication Date: 2022-10-27
    Description: © The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Zeigler, S. L., Gutierrez, B. T., Lentz, E. E., Plant, N. G., Sturdivant, E. J., & Doran, K. S. Predicted sea-level rise-driven biogeomorphological changes on Fire Island, New York: implications for people and plovers. Earth’s Future, 10(4), (2022): e2021EF002436, https://doi.org/10.1029/2021EF002436.
    Description: Forecasting biogeomorphological conditions for barrier islands is critical for informing sea-level rise (SLR) planning, including management of coastal development and ecosystems. We combined five probabilistic models to predict SLR-driven changes and their implications on Fire Island, New York, by 2050. We predicted barrier island biogeomorphological conditions, dynamic landcover response, piping plover (Charadrius melodus) habitat availability, and probability of storm overwash under three scenarios of shoreline change (SLC) and compared results to observed 2014/2015 conditions. Scenarios assumed increasing rates of mean SLC from 0 to 4.71 m erosion per year. We observed uncertainty in several morphological predictions (e.g., beach width, dune height), suggesting decreasing confidence that Fire Island will evolve in response to SLR as it has in the past. Where most likely conditions could be determined, models predicted that Fire Island would become flatter, narrower, and more overwash-prone with increasing rates of SLC. Beach ecosystems were predicted to respond dynamically to SLR and migrate with the shoreline, while marshes lost the most area of any landcover type compared to 2014/2015 conditions. Such morphological changes may lead to increased flooding or breaching with coastal storms. However—although modest declines in piping plover habitat were observed with SLC—the dynamic response of beaches, flatter topography, and increased likelihood of overwash suggest storms could promote suitable conditions for nesting piping plovers above what our geomorphology models predict. Therefore, Fire Island may offer a conservation opportunity for coastal species that rely on early successional beach environments if natural overwash processes are encouraged.
    Description: Funding for this work was provided by the U.S. Geological Survey's Coastal and Marine Hazards and Resources Program, with supplemental funding through the Disaster Relief Act.
    Keywords: Sea level rise ; Erosion ; Coastal habitats ; Barrier island ; Shorebirds
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
    Publication Date: 2022-05-26
    Description: © The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Geophysical Research: Earth Surface 120 (2015): 2452–2475, doi:10.1002/2015JF003671.
    Description: Quantifying geomorphic variability of coastal environments is important for understanding and describing the vulnerability of coastal topography, infrastructure, and ecosystems to future storms and sea level rise. Here we use a Bayesian network (BN) to test the importance of multiple interactions between barrier island geomorphic variables. This approach models complex interactions and handles uncertainty, which is intrinsic to future sea level rise, storminess, or anthropogenic processes (e.g., beach nourishment and other forms of coastal management). The BN was developed and tested at Assateague Island, Maryland/Virginia, USA, a barrier island with sufficient geomorphic and temporal variability to evaluate our approach. We tested the ability to predict dune height, beach width, and beach height variables using inputs that included longer-term, larger-scale, or external variables (historical shoreline change rates, distances to inlets, barrier width, mean barrier elevation, and anthropogenic modification). Data sets from three different years spanning nearly a decade sampled substantial temporal variability and serve as a proxy for analysis of future conditions. We show that distinct geomorphic conditions are associated with different long-term shoreline change rates and that the most skillful predictions of dune height, beach width, and beach height depend on including multiple input variables simultaneously. The predictive relationships are robust to variations in the amount of input data and to variations in model complexity. The resulting model can be used to evaluate scenarios related to coastal management plans and/or future scenarios where shoreline change rates may differ from those observed historically.
    Description: U.S. Geological Survey (USGS) Coastal and Marine Geology Program; U.S. Fish and Wildlife Service
    Keywords: Barrier island ; Coastal evolution ; Bayesian network ; Assateague Island ; Skill ; Validation
    Repository Name: Woods Hole Open Access Server
    Type: Article
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