Interagency Ecological Program and US Fish and Wildlife Service: Enhanced Delta Smelt Monitoring Program Experimental Larval Survey Data 2018-2019
The United States Fish and Wildlife Service’s (USFWS) Experimental Larval Survey was designed and implemented by the Enhanced Delta Smelt Monitoring Program to assess alternative sampling methods for monitoring the larval life stages of the federally endangered Delta Smelt (Hypomesus transpacificus) within the San Francisco Estuary, California, USA. From 2018 to 2019, four different sampling methods (Beach Seine, Manta Trawl Net, 20-mm Surface Trawl Net, 20-mm Midwater Trawl Net) nested in time and space were used to estimate the occupancy rate, relative density, and size distribution of larval Delta Smelt across sampling methods and water depth strata within the San Francisco Estuary. For more information on the Lodi USFWS Office and the Enhanced Delta Smelt Monitoring Program: https://www.fws.gov/lodi/.
Complete Metadata
| accessLevel | public |
|---|---|
| bureauCode |
[
"010:18"
]
|
| contactPoint |
{
"fn": "Todd Sutherland",
"@type": "vcard:Contact",
"hasEmail": "mailto:todd_sutherland@fws.gov"
}
|
| description | The United States Fish and Wildlife Service’s (USFWS) Experimental Larval Survey was designed and implemented by the Enhanced Delta Smelt Monitoring Program to assess alternative sampling methods for monitoring the larval life stages of the federally endangered Delta Smelt (Hypomesus transpacificus) within the San Francisco Estuary, California, USA. From 2018 to 2019, four different sampling methods (Beach Seine, Manta Trawl Net, 20-mm Surface Trawl Net, 20-mm Midwater Trawl Net) nested in time and space were used to estimate the occupancy rate, relative density, and size distribution of larval Delta Smelt across sampling methods and water depth strata within the San Francisco Estuary. For more information on the Lodi USFWS Office and the Enhanced Delta Smelt Monitoring Program: https://www.fws.gov/lodi/. |
| distribution |
[
{
"@type": "dcat:Distribution",
"title": "Data Service",
"format": "API",
"accessURL": "https://portal.edirepository.org/nis/mapbrowse?scope=edi&identifier=994&revision=3",
"description": "Data Portal Website"
},
{
"@type": "dcat:Distribution",
"title": "edi.994.3.xml",
"format": "xml",
"mediaType": "application/xml",
"description": "Experimental Larval Survey Metadata",
"downloadURL": "https://iris.fws.gov/APPS/ServCat/DownloadFile/261058?Reference=142803"
}
]
|
| identifier | http://datainventory.doi.gov/id/dataset/FWS_ServCat_142803 |
| issued | 2021-10-15T00:00:00Z |
| keyword |
[
"Chinook Salmon",
"Delta Smelt",
"General: Biology | At-Risk-Biota | T&E Species",
"General: Biology | Communities and Ecosystems | Estuary",
"General: Biology | Communities and Ecosystems | Ocean",
"General: Biology | Communities and Ecosystems | Riverine",
"General: Biology | Invasive Species | Invasive/Exotic Animals",
"General: Biology | Species | Fishes",
"General: Management | Natural Resources Management | Fisheries Management",
"General: Management | Natural Resources Management | Water Management",
"General: Water | Hydrology | Estuary",
"Interagency Ecological Program",
"Largemouth Bass",
"Longfin Smelt",
"Mississippi Silverside",
"Sacramento Splittail",
"Sacramento-San Joaquin Delta",
"San Francisco Estuary",
"United States Fish and Wildlife Service",
"Wakasagi",
"abundance",
"aquatic ecosystems",
"brackish water",
"ecology",
"endangered species",
"estuaries",
"fishes",
"freshwater",
"invasive species",
"manta net",
"rivers",
"seine",
"water quality"
]
|
| landingPage | https://iris.fws.gov/APPS/ServCat/Reference/Profile/142803 |
| modified | 2021-10-15T00:00:00Z |
| programCode |
[
"010:028",
"010:094"
]
|
| publisher |
{
"name": "U.S. Fish and Wildlife Service",
"@type": "org:Organization"
}
|
| spatial | -121.246788,38.12431,-121.246384,38.12457 |
| temporal | 2018-01-01/2019-01-01 |
| theme |
[
"Tabular Dataset"
]
|
| title | Interagency Ecological Program and US Fish and Wildlife Service: Enhanced Delta Smelt Monitoring Program Experimental Larval Survey Data 2018-2019 |
