Data from: Pairing field methods to improve inference in wildlife surveys while accommodating detection covariance
It is common to use multiple field sampling methods when implementing wildlife surveys to compare method efficacy or cost-efficiency, integrate distinct pieces of information provided by separate methods, or evaluate method-specific biases and misclassification error. Existing models that combine in...
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ftdryad:oai:v1.datadryad.org:10255/dryad.146592 2023-05-15T13:21:51+02:00 Data from: Pairing field methods to improve inference in wildlife surveys while accommodating detection covariance Clare, John McKinney, Shawn T. DePue, John E. Loftin, Cynthia S. Maine 2017-05-22T13:34:57Z http://hdl.handle.net/10255/dryad.146592 https://doi.org/10.5061/dryad.4mt00 unknown doi:10.5061/dryad.4mt00/1 doi:10.5061/dryad.4mt00/2 doi:10.5061/dryad.4mt00/3 doi:10.5061/dryad.4mt00/4 doi:10.5061/dryad.4mt00/5 doi:10.5061/dryad.4mt00/6 doi:10.1002/eap.1587 doi:10.5061/dryad.4mt00 Clare J, McKinney ST, DePue JE, Loftin CS (2017) Pairing field methods to improve inference in wildlife surveys while accommodating detection covariance. Ecological Applications 27(7): 2031-2047. 1051-0761 http://hdl.handle.net/10255/dryad.146592 occupancy distribution density American marten Article 2017 ftdryad https://doi.org/10.5061/dryad.4mt00 https://doi.org/10.5061/dryad.4mt00/1 https://doi.org/10.5061/dryad.4mt00/2 https://doi.org/10.5061/dryad.4mt00/3 https://doi.org/10.5061/dryad.4mt00/4 https://doi.org/10.5061/dryad.4mt00/5 https://doi.org/1 2020-01-01T15:51:18Z It is common to use multiple field sampling methods when implementing wildlife surveys to compare method efficacy or cost-efficiency, integrate distinct pieces of information provided by separate methods, or evaluate method-specific biases and misclassification error. Existing models that combine information from multiple field methods or sampling devices permit rigorous comparison of method-specific detection parameters, enable estimation of additional parameters such as false-positive detection probability, and improve occurrence or abundance estimates, but with the assumption that the separate sampling methods produce detections independently of one another. This assumption is tenuous if methods are paired or deployed in close proximity simultaneously, a common practice that reduces the additional effort required to implement multiple methods and reduces the risk that differences between method-specific detection parameters are confounded by other environmental factors. We develop occupancy and spatial capture-recapture models that permit covariance between the detections produced by different methods, use simulation to compare estimator performance of the new models to models assuming independence, and provide an empirical application based upon American marten (Martes americana) surveys using paired remote cameras, hair-catches, and snow tracking. Simulation results indicate existing models that assume that methods independently detect organisms produce biased parameter estimates and substantially understate estimate uncertainty when this assumption is violated, while our reformulated models are robust to either methodological independence or covariance. Empirical results suggested that remote-cameras and snow-tracking had comparable probability of detecting present martens, but that snow-tracking also produced false-positive marten detections that could potentially substantially bias distribution estimates if not corrected for. Remote cameras detected marten individuals more readily than passive hair-catches. Inability to photographically distinguish individual sex did not appear to induce negative bias in camera density estimates; instead, hair-catches appeared to produce detection competition between individuals that may have been a source of negative bias. Our model reformulations broaden the range of circumstances in which analyses incorporating multiple sources of information can be robustly used, and our empirical results demonstrate that using multiple field-methods can enhance inferences regarding ecological parameters of interest and improve understanding of how reliably survey methods sample these parameters. Article in Journal/Newspaper American marten Martes americana Dryad Digital Repository (Duke University) |
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Dryad Digital Repository (Duke University) |
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occupancy distribution density American marten |
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occupancy distribution density American marten Clare, John McKinney, Shawn T. DePue, John E. Loftin, Cynthia S. Data from: Pairing field methods to improve inference in wildlife surveys while accommodating detection covariance |
topic_facet |
occupancy distribution density American marten |
description |
It is common to use multiple field sampling methods when implementing wildlife surveys to compare method efficacy or cost-efficiency, integrate distinct pieces of information provided by separate methods, or evaluate method-specific biases and misclassification error. Existing models that combine information from multiple field methods or sampling devices permit rigorous comparison of method-specific detection parameters, enable estimation of additional parameters such as false-positive detection probability, and improve occurrence or abundance estimates, but with the assumption that the separate sampling methods produce detections independently of one another. This assumption is tenuous if methods are paired or deployed in close proximity simultaneously, a common practice that reduces the additional effort required to implement multiple methods and reduces the risk that differences between method-specific detection parameters are confounded by other environmental factors. We develop occupancy and spatial capture-recapture models that permit covariance between the detections produced by different methods, use simulation to compare estimator performance of the new models to models assuming independence, and provide an empirical application based upon American marten (Martes americana) surveys using paired remote cameras, hair-catches, and snow tracking. Simulation results indicate existing models that assume that methods independently detect organisms produce biased parameter estimates and substantially understate estimate uncertainty when this assumption is violated, while our reformulated models are robust to either methodological independence or covariance. Empirical results suggested that remote-cameras and snow-tracking had comparable probability of detecting present martens, but that snow-tracking also produced false-positive marten detections that could potentially substantially bias distribution estimates if not corrected for. Remote cameras detected marten individuals more readily than passive hair-catches. Inability to photographically distinguish individual sex did not appear to induce negative bias in camera density estimates; instead, hair-catches appeared to produce detection competition between individuals that may have been a source of negative bias. Our model reformulations broaden the range of circumstances in which analyses incorporating multiple sources of information can be robustly used, and our empirical results demonstrate that using multiple field-methods can enhance inferences regarding ecological parameters of interest and improve understanding of how reliably survey methods sample these parameters. |
format |
Article in Journal/Newspaper |
author |
Clare, John McKinney, Shawn T. DePue, John E. Loftin, Cynthia S. |
author_facet |
Clare, John McKinney, Shawn T. DePue, John E. Loftin, Cynthia S. |
author_sort |
Clare, John |
title |
Data from: Pairing field methods to improve inference in wildlife surveys while accommodating detection covariance |
title_short |
Data from: Pairing field methods to improve inference in wildlife surveys while accommodating detection covariance |
title_full |
Data from: Pairing field methods to improve inference in wildlife surveys while accommodating detection covariance |
title_fullStr |
Data from: Pairing field methods to improve inference in wildlife surveys while accommodating detection covariance |
title_full_unstemmed |
Data from: Pairing field methods to improve inference in wildlife surveys while accommodating detection covariance |
title_sort |
data from: pairing field methods to improve inference in wildlife surveys while accommodating detection covariance |
publishDate |
2017 |
url |
http://hdl.handle.net/10255/dryad.146592 https://doi.org/10.5061/dryad.4mt00 |
op_coverage |
Maine |
genre |
American marten Martes americana |
genre_facet |
American marten Martes americana |
op_relation |
doi:10.5061/dryad.4mt00/1 doi:10.5061/dryad.4mt00/2 doi:10.5061/dryad.4mt00/3 doi:10.5061/dryad.4mt00/4 doi:10.5061/dryad.4mt00/5 doi:10.5061/dryad.4mt00/6 doi:10.1002/eap.1587 doi:10.5061/dryad.4mt00 Clare J, McKinney ST, DePue JE, Loftin CS (2017) Pairing field methods to improve inference in wildlife surveys while accommodating detection covariance. Ecological Applications 27(7): 2031-2047. 1051-0761 http://hdl.handle.net/10255/dryad.146592 |
op_doi |
https://doi.org/10.5061/dryad.4mt00 https://doi.org/10.5061/dryad.4mt00/1 https://doi.org/10.5061/dryad.4mt00/2 https://doi.org/10.5061/dryad.4mt00/3 https://doi.org/10.5061/dryad.4mt00/4 https://doi.org/10.5061/dryad.4mt00/5 https://doi.org/1 |
_version_ |
1766361844985888768 |