DCpts, DTpts, SLpts: Dune crest, dune toe, and mean high water shoreline positions: Edwin B. Forsythe NWR, NJ, 2012
Dates
Publication Date
2019-06-25
Start Date
2012-11-01
End Date
2012-11-05
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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ebf12_DC_DT_SLpts_meta.xml Original FGDC Metadata
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ebf_DC_DT_SLpts_browse.png “Example geomorphology points (mean high water shoreline, dune toe, and dune c...”
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ebf12_DCpts.zip
ebf12_DCpts.cpg
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ebf12_DCpts.csv
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ebf12_DCpts.dbf
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ebf12_DCpts.prj
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ebf12_DTpts.zip
ebf12_DTpts.cpg
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ebf12_DTpts.csv
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ebf12_DTpts.dbf
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ebf12_SLpts.zip
ebf12_SLpts.cpg
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ebf12_SLpts.csv
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ebf12_SLpts.dbf
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ebf12_SLpts.prj
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ebf12_SLpts.sbn
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ebf12_SLpts.sbx
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ebf12_SLpts.shp
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ebf12_SLpts.shx
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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.
These datasets measure positions of geomorphic features, specifically dune crests, dune toes, and mean high water (MHW) shoreline pertaining to sandy beaches at Edwin B. Forsythe NWR, NJ in 2012. They can be used to calculate beach width and height. The source data were created for the purpose of modeling coastal hazards related to dune overtopping.
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Example geomorphology points (mean high water shoreline, dune toe, and dune c...