DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Monomoy Island, MA, 2013-2014

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.

Data and Resources

Field Value
accessLevel public
bureauCode {010:12}
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identifier http://datainventory.doi.gov/id/dataset/usgs-5daa372be4b09fd3b0c9ce2a
metadata_type geospatial
modified 2020-08-10T00:00:00Z
old-spatial -70.02111328, 41.53820056, -69.93312697, 41.66332745
publisher U.S. Geological Survey
resource-type Dataset
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spatial {"type": "Polygon", "coordinates": [[[-70.02111328, 41.53820056], [-70.02111328, 41.66332745], [ -69.93312697, 41.66332745], [ -69.93312697, 41.53820056], [-70.02111328, 41.53820056]]]}
theme {geospatial}
Groups
  • AmeriGEOSS
  • National Provider
  • North America
Tags
  • AmeriGEO
  • AmeriGEOSS
  • CKAN
  • GEO
  • GEOSS
  • National
  • North America
  • United States
  • atlantic-ocean
  • barrier-island
  • bayesian-network
  • biota
  • cape-cod
  • charadrius-melodus
  • cmgp
  • coastal-and-marine-geology-program
  • coastal-habitat
  • ecology
  • environment
  • foraging-ecology
  • geographic-information-systems
  • geography
  • geomorphology
  • geospatial-analysis
  • geospatial-datasets
  • gis
  • ma
  • massachusetts
  • mean-high-water
  • mhw
  • monomoy-island
  • monomoy-national-wildlife-refuge
  • north-america
  • piping-plovers
  • st-petersburg-coastal-and-marine-science-center
  • u-s-geological-survey
  • united-states
  • usa
  • usgs
  • usgs-5daa372be4b09fd3b0c9ce2a
  • woods-hole-coastal-and-marine-science-center
isopen False
license_id notspecified
license_title License not specified
maintainer Sara L. Zeigler
maintainer_email szeigler@usgs.gov
metadata_created 2025-09-23T21:29:24.395165
metadata_modified 2025-09-23T21:29:24.395172
notes 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.
num_resources 2
num_tags 41
title DisMOSH, Cost, MOSH_Shoreline: Distance to foraging areas for piping plovers including foraging shoreline, cost mask, and least-cost path distance: Monomoy Island, MA, 2013-2014