DisMOSH, Cost, MOSHShoreline: Distance to foraging areas for piping plovers (foraging shoreline, cost mask, and least-cost path distance): Rockaway Peninsula, NY, 2012
Dates
Publication Date
2019-06-25
Time Period
2012
Citation
Sturdivant, E.J., Zeigler, S.L., Gutierrez, B.T., and Weber, K.M., 2019, Barrier island geomorphology and shorebird habitat metrics–Four sites in New York, New Jersey, and Virginia, 2010–2014: U.S. Geological Survey data release, https://doi.org/10.5066/P944FPA4.
Summary
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated into predictive [...]
Summary
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated into predictive models and the training data used to parameterize those models. This data release contains the extracted metrics of barrier island geomorphology and spatial data layers of habitat characteristics that are input to Bayesian networks for piping plover habitat availability and barrier island geomorphology. These datasets and models are being developed for sites along the northeastern coast of the United States. This work is one component of a larger research and management program that seeks to understand and sustain the ecological value, ecosystem services, and habitat suitability of beaches in the face of storm impacts, climate change, and sea-level rise.
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Rock12_DisMOSH_Cost_MOSHShoreline_meta.xml Original FGDC Metadata
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application/fgdc+xml
Rock12_Cost.tif
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Rock12_Cost.tif.vat.dbf
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Rock12_MOSHShoreline.CPG
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Rock12_MOSHShoreline.dbf
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Rock12_MOSHShoreline.prj
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Rock12_MOSHShoreline.sbn
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Rock12_MOSHShoreline.sbx
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Rock12_MOSHShoreline.shp
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x-gis/x-shapefile
Rock12_MOSHShoreline.shx
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Rock_DisMOSH_Cost_MOSHShoreline_browse.png “Example of the movement cost (resistance) layer and the least-cost path dista...”
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Rock12_DisMOSH.zip
Rock12_DisMOSH.tif
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Rock12_DisMOSH.tif-ColorRamp.SLD
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Related External Resources
Type: Publication that references this resource
Zeigler, S.L., Sturdivant, E.J., and Gutierrez, B.T., 2019, Evaluating barrier island characteristics and piping plover (Charadrius melodus) habitat availability along the U.S. Atlantic coast—Geospatial approaches and methodology: U.S. Geological Survey Open-File Report 2019–1071, https://doi.org/10.3133/ofr20191071.
Zeigler, S.L., Gutierrez, B.T., Sturdivant, E.J., Catlin, D.H., Fraser, J.D., Hecht, A., Karpanty, S.M., Plant, N.G., and Thieler, E.R., 2019, Using a Bayesian network to understand the importance of coastal storms and undeveloped landscapes for the creation and maintenance of early successional habitat: PLoS ONE, v. 14, no. 7, e0209986, https://doi.org/10.1371/journal.pone.0209986.
The distance to foraging layer (Rock12_DisMOSH.tif) identifies the least-cost path distance for a piping plover chick to travel from the center of each 5x5 m grid cell to low-energy foraging areas with moist substrates. The distance to foraging data was used within a Bayesian network to model the probability that a specific set of landscape characteristics would be associated with piping plover habitat. The movement cost layer (Rock12_Cost.tif) identifies barriers to the movement of piping plover chicks, with barriers including water, human development, and moderate to dense vegetation. A value of 1 indicates possibility of movement and 99,999 indicates a barrier to movement. Barriers were identified using orthoimagery captured in 2012 (see data sources below). The movement cost layer was used to calculate the least-cost path distance (Rock12_DisMOSH.tif) to the nearest foraging area (Rock12_MOSHShoreline.shp). The foraging shorelines shapefile (Rock12_MOSHShoreline.shp) delineates foraging shorelines with moist substrates for piping plovers. Foraging areas were determined from elevations measured in 2012 and orthoimagery captured in 2012. Here, foraging shorelines are defined as low-energy and could include the shorelines of sound- or bay-side beaches, interior ponds, and ephemeral pools. Ocean shorelines were not considered low-energy foraging shorelines. See Zeigler and others (2019) for additional details.
Preview Image
Example of the movement cost (resistance) layer and the least-cost path dista...