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  • 1
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    Predicted sea-level rise-driven biogeomorphological changes on Fire Island, New York: implications for people and plovers (2022)
    American Geophysical Union
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    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
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    Using a Bayesian network to predict barrier island geomorphologic characteristics (2016)
    John Wiley & Sons
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    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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  • 3
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    Smartphone technologies and Bayesian networks to assess shorebird habitat selection (2018)
    John Wiley & Sons
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    Publication Date: 2022-05-26
    Description: © The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Wildlife Society Bulletin 41 (2017): 666–677, doi:10.1002/wsb.820.
    Description: Understanding patterns of habitat selection across a species’ geographic distribution can be critical for adequately managing populations and planning for habitat loss and related threats. However, studies of habitat selection can be time consuming and expensive over broad spatial scales, and a lack of standardized monitoring targets or methods can impede the generalization of site-based studies. Our objective was to collaborate with natural resource managers to define available nesting habitat for piping plovers (Charadrius melodus) throughout their U.S. Atlantic coast distribution from Maine to North Carolina, with a goal of providing science that could inform habitat management in response to sea-level rise. We characterized a data collection and analysis approach as being effective if it provided low-cost collection of standardized habitat-selection data across the species’ breeding range within 1–2 nesting seasons and accurate nesting location predictions. In the method developed, 〉30 managers and conservation practitioners from government agencies and private organizations used a smartphone application, “iPlover,” to collect data on landcover characteristics at piping plover nest locations and random points on 83 beaches and barrier islands in 2014 and 2015. We analyzed these data with a Bayesian network that predicted the probability a specific combination of landcover variables would be associated with a nesting site. Although we focused on a shorebird, our approach can be modified for other taxa. Results showed that the Bayesian network performed well in predicting habitat availability and confirmed predicted habitat preferences across the Atlantic coast breeding range of the piping plover. We used the Bayesian network to map areas with a high probability of containing nesting habitat on the Rockaway Peninsula in New York, USA, as an example application. Our approach facilitated the collation of evidence-based information on habitat selection from many locations and sources, which can be used in management and decision-making applications. © 2017 The Authors. Wildlife Society Bulletin published by Wiley Periodicals, Inc. on behalf of The Wildlife Society.
    Description: U.S. Fish and Wildlife Service; U.S. Department of Interior Hurricane Sandy Recovery Program; North Atlantic Landscape Conservation Cooperative; U.S. Geological Survey Coastal and Marine Geology Program
    Keywords: Atlantic coast ; Barrier islands ; Bayesian network ; Charadrius melodus ; Coastal geomorphology ; Habitat availability ; iPlover ; Nesting
    Repository Name: Woods Hole Open Access Server
    Type: Article
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