Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Skip to content

Manatee environmental DNA data, and associated attributes, collected from the United States, Cuba, and Cameroon, from 2013-2015

Metadata Updated: July 6, 2024

Environmental DNA (eDNA) detection is a rapidly expanding technique used to non-invasively detect cryptic, low density, or logistically difficult-to-study species, such as imperiled manatees. Genetic material shed into the environment through tissue and body fluids is concentrated from water samples and analyzed for the presence of targeted eDNA. To help delineate manatee habitat ranges, high use areas, and seasonal population changes, a cytochrome-b quantitative PCR and state-of-the-art droplet digital PCR (ddPCR) eDNA assay was developed for the three extant and vulnerable manatee species: both subspecies of the West Indian manatee (Florida and Antillean), the African manatee and Amazonian manatee. Occurrence (ψ) and detection (p) probabilities were estimated to inform management efforts and population monitoring. To validate the assay, water was analyzed from a relatively high-density Florida manatee east coast population and produced an average 31,564 target DNA molecules/liter (ψ=0.84 (0.40-0.99); p=0.99 (0.95-1.00)). Similar occupancy estimates were produced from investigations of less well-characterized Florida manatee populations in the Florida Panhandle (ψ=0.79 (0.54-0.97)) and Cuba (ψ=0.89 (0.54-1.00)) while occupancy estimates of the African species in Cameroon were lower (ψ=0.49 (0.09-0.95)). The estimates were higher than those generated using aerial survey data on the west coast of Florida. Future eDNA studies could assess locations where manatees are difficult to identify visually (e.g., dark or turbid water common in the Amazon River, and Africa), are present in patchy distributions, or where repatriation efforts are proposed (e.g., Brazil, Guadeloupe). Moreover, this technology could be extended to species on the verge of extinction (e.g., manatees in Jamaica and Haiti, and Asian dugongs), where conventional survey methods are challenging.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

Downloads & Resources

Dates

Metadata Created Date June 1, 2023
Metadata Updated Date July 6, 2024

Metadata Source

Harvested from DOI EDI

Additional Metadata

Resource Type Dataset
Metadata Created Date June 1, 2023
Metadata Updated Date July 6, 2024
Publisher U.S. Geological Survey
Maintainer
@Id http://datainventory.doi.gov/id/dataset/d412018ce5360b8c0a2ec04947b08768
Identifier USGS:59cc190ae4b017cf31424733
Data Last Modified 20200830
Category geospatial
Public Access Level public
Bureau Code 010:12
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://datainventory.doi.gov/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id aba56a5f-1662-478c-8488-108862efd660
Harvest Source Id 52bfcc16-6e15-478f-809a-b1bc76f1aeda
Harvest Source Title DOI EDI
Metadata Type geospatial
Old Spatial -87.626953125,3.283113991917241,10.338134765625002,30.826780904779774
Publisher Hierarchy White House > U.S. Department of the Interior > U.S. Geological Survey
Source Datajson Identifier True
Source Hash 5c0cf462e2ba3c9268c01ce193f4fd6961ec550581e9df8461bc3590d398feaa
Source Schema Version 1.1
Spatial {"type": "Polygon", "coordinates": -87.626953125, 3.283113991917241, -87.626953125, 30.826780904779774, 10.338134765625002, 30.826780904779774, 10.338134765625002, 3.283113991917241, -87.626953125, 3.283113991917241}

Didn't find what you're looking for? Suggest a dataset here.