Bayesian network model that predicts the probability of habitat availability (days) per winter month for age-0 Gulf Sturgeon at a 30-m pixel scale in Apalachicola Bay, FL
The Gulf Sturgeon is a federally listed, anadromous species, inhabiting Gulf Coast rivers, estuaries, and coastal waters from Louisiana to Florida. The U.S. Geological Survey partnered with the U.S. Fish and Wildlife Service (USFWS), U.S. Army Corps of Engineers, University of Georgia, and their conservation partners to support adaptive management of Gulf Sturgeon (Acipenser oxyrinchus desotoi) by developing a quantitative, spatial model. The model is a Bayesian network that predicts the probability of habitat availability (days) per winter month for age-0 Gulf Sturgeon at a 30-m pixel scale in estuarine critical habitat. The model predicts habitat availability (days) for 75 alternative physiological and habitat scenarios, which were the unique combination of river discharge, winter month, and month of arrival to the estuary. The probability of habitat availability (days) is predicted from habitat characteristics that could be influenced by management actions. The model's structure was defined by empirical data, expert elicitation, and simplifying assumptions.
Complete Metadata
| accessLevel | public |
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"fn": "James Patrick Cronin",
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| description | The Gulf Sturgeon is a federally listed, anadromous species, inhabiting Gulf Coast rivers, estuaries, and coastal waters from Louisiana to Florida. The U.S. Geological Survey partnered with the U.S. Fish and Wildlife Service (USFWS), U.S. Army Corps of Engineers, University of Georgia, and their conservation partners to support adaptive management of Gulf Sturgeon (Acipenser oxyrinchus desotoi) by developing a quantitative, spatial model. The model is a Bayesian network that predicts the probability of habitat availability (days) per winter month for age-0 Gulf Sturgeon at a 30-m pixel scale in estuarine critical habitat. The model predicts habitat availability (days) for 75 alternative physiological and habitat scenarios, which were the unique combination of river discharge, winter month, and month of arrival to the estuary. The probability of habitat availability (days) is predicted from habitat characteristics that could be influenced by management actions. The model's structure was defined by empirical data, expert elicitation, and simplifying assumptions. |
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| identifier | http://datainventory.doi.gov/id/dataset/USGS_5ab94893e4b081f61ab9ca2a |
| keyword |
[
"Apalachicola Bay",
"Bayesian network",
"Gulf coast",
"Sturgeons/Paddlefishes",
"USGS:5ab94893e4b081f61ab9ca2a",
"adaptive management",
"decision support tools",
"environment",
"estuaries",
"farming",
"habitat objectives",
"landscape conservation",
"recovery objectives",
"spatial models",
"strategic habitat conservation",
"water condition"
]
|
| modified | 2021-01-20T00:00:00Z |
| publisher |
{
"name": "U.S. Geological Survey",
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|
| spatial | -85.263684009375, 29.591217918316, -84.702303475953, 29.820224339057 |
| theme |
[
"Geospatial"
]
|
| title | Bayesian network model that predicts the probability of habitat availability (days) per winter month for age-0 Gulf Sturgeon at a 30-m pixel scale in Apalachicola Bay, FL |
