LinkedBNs_4Habitat - Matlab files to link Bayesian networks to generate habitat predictions
October 3, 2022
Matlab m-files that were used to generate performance tests and hindcasts for geomorphologic characteristics and piping plover habitat probabilities for Fire Island New York
Citation Information
| Publication Year | 2022 |
|---|---|
| Title | LinkedBNs_4Habitat - Matlab files to link Bayesian networks to generate habitat predictions |
| DOI | 10.5066/P9R63EMY |
| Authors | Ben Gutierrez, Nathaniel G Plant |
| Product Type | Software Release |
| Record Source | USGS Digital Object Identifier Catalog |
| USGS Organization | Woods Hole Coastal and Marine Science Center |
Related Content
Integrating Bayesian networks to forecast sea-level rise impacts on barrier island characteristics and habitat availability
Evaluation of sea-level rise (SLR) impacts on coastal landforms and habitats is a persistent need for informing coastal planning and management, including policy decisions, particularly those that balance human interests and habitat protection throughout the coastal zone. Bayesian networks (BNs) are used to model barrier island change under different SLR scenarios that are relevant to management a
Authors
Benjamin T. Gutierrez, Sara Zeigler, Erika Lentz, Emily J. Sturdivant, Nathaniel Plant
Related Content
Integrating Bayesian networks to forecast sea-level rise impacts on barrier island characteristics and habitat availability
Evaluation of sea-level rise (SLR) impacts on coastal landforms and habitats is a persistent need for informing coastal planning and management, including policy decisions, particularly those that balance human interests and habitat protection throughout the coastal zone. Bayesian networks (BNs) are used to model barrier island change under different SLR scenarios that are relevant to management a
Authors
Benjamin T. Gutierrez, Sara Zeigler, Erika Lentz, Emily J. Sturdivant, Nathaniel Plant