An assessment of sampling designs using SCR analyses to estimate abundance of boreal caribou
Abstract Accurately estimating abundance is a critical component of monitoring and recovery of rare and elusive species. Spatial capture–recapture (SCR) models are an increasingly popular method for robust estimation of ecological parameters. We provide an analytical framework to assess results from...
Published in: | Ecology and Evolution |
---|---|
Main Authors: | , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Wiley
2020
|
Subjects: | |
Online Access: | http://dx.doi.org/10.1002/ece3.6797 https://onlinelibrary.wiley.com/doi/pdf/10.1002/ece3.6797 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ece3.6797 |
id |
crwiley:10.1002/ece3.6797 |
---|---|
record_format |
openpolar |
spelling |
crwiley:10.1002/ece3.6797 2024-06-23T07:56:22+00:00 An assessment of sampling designs using SCR analyses to estimate abundance of boreal caribou McFarlane, Samantha Manseau, Micheline Steenweg, Robin Hervieux, Dave Hegel, Troy Slater, Simon Wilson, Paul J. 2020 http://dx.doi.org/10.1002/ece3.6797 https://onlinelibrary.wiley.com/doi/pdf/10.1002/ece3.6797 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ece3.6797 en eng Wiley http://creativecommons.org/licenses/by/4.0/ Ecology and Evolution volume 10, issue 20, page 11631-11642 ISSN 2045-7758 2045-7758 journal-article 2020 crwiley https://doi.org/10.1002/ece3.6797 2024-06-06T04:19:28Z Abstract Accurately estimating abundance is a critical component of monitoring and recovery of rare and elusive species. Spatial capture–recapture (SCR) models are an increasingly popular method for robust estimation of ecological parameters. We provide an analytical framework to assess results from empirical studies to inform SCR sampling design, using both simulated and empirical data from noninvasive genetic sampling of seven boreal caribou populations ( Rangifer tarandus caribou ), which varied in range size and estimated population density. We use simulated population data with varying levels of clustered distributions to quantify the impact of nonindependence of detections on density estimates, and empirical datasets to explore the influence of varied sampling intensity on the relative bias and precision of density estimates. Simulations revealed that clustered distributions of detections did not significantly impact relative bias or precision of density estimates. The genotyping success rate of our empirical dataset ( n = 7,210 samples) was 95.1%, and 1,755 unique individuals were identified. Analysis of the empirical data indicated that reduced sampling intensity had a greater impact on density estimates in smaller ranges. The number of captures and spatial recaptures was strongly correlated with precision, but not absolute relative bias. The best sampling designs did not differ with estimated population density but differed between large and small ranges. We provide an efficient framework implemented in R to estimate the detection parameters required when designing SCR studies. The framework can be used when designing a monitoring program to minimize effort and cost while maximizing effectiveness, which is critical for informing wildlife management and conservation. Article in Journal/Newspaper Rangifer tarandus Wiley Online Library Ecology and Evolution 10 20 11631 11642 |
institution |
Open Polar |
collection |
Wiley Online Library |
op_collection_id |
crwiley |
language |
English |
description |
Abstract Accurately estimating abundance is a critical component of monitoring and recovery of rare and elusive species. Spatial capture–recapture (SCR) models are an increasingly popular method for robust estimation of ecological parameters. We provide an analytical framework to assess results from empirical studies to inform SCR sampling design, using both simulated and empirical data from noninvasive genetic sampling of seven boreal caribou populations ( Rangifer tarandus caribou ), which varied in range size and estimated population density. We use simulated population data with varying levels of clustered distributions to quantify the impact of nonindependence of detections on density estimates, and empirical datasets to explore the influence of varied sampling intensity on the relative bias and precision of density estimates. Simulations revealed that clustered distributions of detections did not significantly impact relative bias or precision of density estimates. The genotyping success rate of our empirical dataset ( n = 7,210 samples) was 95.1%, and 1,755 unique individuals were identified. Analysis of the empirical data indicated that reduced sampling intensity had a greater impact on density estimates in smaller ranges. The number of captures and spatial recaptures was strongly correlated with precision, but not absolute relative bias. The best sampling designs did not differ with estimated population density but differed between large and small ranges. We provide an efficient framework implemented in R to estimate the detection parameters required when designing SCR studies. The framework can be used when designing a monitoring program to minimize effort and cost while maximizing effectiveness, which is critical for informing wildlife management and conservation. |
format |
Article in Journal/Newspaper |
author |
McFarlane, Samantha Manseau, Micheline Steenweg, Robin Hervieux, Dave Hegel, Troy Slater, Simon Wilson, Paul J. |
spellingShingle |
McFarlane, Samantha Manseau, Micheline Steenweg, Robin Hervieux, Dave Hegel, Troy Slater, Simon Wilson, Paul J. An assessment of sampling designs using SCR analyses to estimate abundance of boreal caribou |
author_facet |
McFarlane, Samantha Manseau, Micheline Steenweg, Robin Hervieux, Dave Hegel, Troy Slater, Simon Wilson, Paul J. |
author_sort |
McFarlane, Samantha |
title |
An assessment of sampling designs using SCR analyses to estimate abundance of boreal caribou |
title_short |
An assessment of sampling designs using SCR analyses to estimate abundance of boreal caribou |
title_full |
An assessment of sampling designs using SCR analyses to estimate abundance of boreal caribou |
title_fullStr |
An assessment of sampling designs using SCR analyses to estimate abundance of boreal caribou |
title_full_unstemmed |
An assessment of sampling designs using SCR analyses to estimate abundance of boreal caribou |
title_sort |
assessment of sampling designs using scr analyses to estimate abundance of boreal caribou |
publisher |
Wiley |
publishDate |
2020 |
url |
http://dx.doi.org/10.1002/ece3.6797 https://onlinelibrary.wiley.com/doi/pdf/10.1002/ece3.6797 https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ece3.6797 |
genre |
Rangifer tarandus |
genre_facet |
Rangifer tarandus |
op_source |
Ecology and Evolution volume 10, issue 20, page 11631-11642 ISSN 2045-7758 2045-7758 |
op_rights |
http://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.1002/ece3.6797 |
container_title |
Ecology and Evolution |
container_volume |
10 |
container_issue |
20 |
container_start_page |
11631 |
op_container_end_page |
11642 |
_version_ |
1802649413959548928 |