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Time to detection data for Point Reyes pond-breeding amphibians, 2017

Metadata Updated: July 6, 2024

Occupancy models provide a reliable method of estimating species distributions while accounting for imperfect detectability. The cost of accounting for false absences is that detection and nondetection surveys typically require repeated visits to a site or multiple-observer techniques. More efficient methods of collecting data to estimate detection probabilities would allow additional sites to be surveyed for the same amount of effort, which would support more precise estimation of covariate effects to improve inference about underlying ecological processes. Time-to-detection surveys allow the estimation of detection probability based on a single site visit by one observer, and therefore might be an efficient technique for herpetological occupancy studies. We evaluated the use of time-to-detection surveys to estimate the occupancy of pond-breeding amphibians at Point Reyes National Seashore, California, USA, including variables that affected detection rates and the probability of occurrence. We found that detection times were short enough, and occupancy was high enough, to reliably estimate the probability of occurrence of three pond-breeding amphibians at Point Reyes National Seashore, and that survey and site conditions had species-specific effects on detection rates. In particular, pond characteristics affected detection times of all commonly detected species. Probability of occurrence of Sierran Treefrogs (Hyliola sierra) and Rough-skinned Newts (Taricha granulosa) was negatively related to the detection of fish and pond area. Time-to-detection surveys can provide an efficient method for estimating detection probabilities and accounting for false absences in occupancy studies of reptiles and amphibians.

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.

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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/cca2568133065ee98cddd6275c752105
Identifier USGS:5b75ef4be4b0f5d5787feb3b
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 4e3e246a-d9d0-4838-9693-e6507990c8cb
Harvest Source Id 52bfcc16-6e15-478f-809a-b1bc76f1aeda
Harvest Source Title DOI EDI
Metadata Type geospatial
Old Spatial -123.13751220572,37.854557660235,-122.59368896355,38.265442899653
Publisher Hierarchy White House > U.S. Department of the Interior > U.S. Geological Survey
Source Datajson Identifier True
Source Hash ac7b913a527b09ef33f99c00e5876e8aed8595e2d527289f3289ce72e4519cad
Source Schema Version 1.1
Spatial {"type": "Polygon", "coordinates": -123.13751220572, 37.854557660235, -123.13751220572, 38.265442899653, -122.59368896355, 38.265442899653, -122.59368896355, 37.854557660235, -123.13751220572, 37.854557660235}

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