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A comparison of survey method efficiencies for estimating densities of zebra mussels (Dreissena polymorpha)

Abundance surveys are commonly used to estimate plant or animal densities and frequently require estimating detection probabilities to account for imperfect detection. The estimation of detection probabilities requires additional measurements that take time, potentially reducing the efficiency of th...

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Autores principales: Ferguson, Jake M., Jiménez, Laura, Keyes, Aislyn A., Hilding, Austen, McCartney, Michael A., St. Clair, Katherine, Johnson, Douglas H., Fieberg, John R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10340101/
https://www.ncbi.nlm.nih.gov/pubmed/37456873
http://dx.doi.org/10.7717/peerj.15528
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author Ferguson, Jake M.
Jiménez, Laura
Keyes, Aislyn A.
Hilding, Austen
McCartney, Michael A.
St. Clair, Katherine
Johnson, Douglas H.
Fieberg, John R.
author_facet Ferguson, Jake M.
Jiménez, Laura
Keyes, Aislyn A.
Hilding, Austen
McCartney, Michael A.
St. Clair, Katherine
Johnson, Douglas H.
Fieberg, John R.
author_sort Ferguson, Jake M.
collection PubMed
description Abundance surveys are commonly used to estimate plant or animal densities and frequently require estimating detection probabilities to account for imperfect detection. The estimation of detection probabilities requires additional measurements that take time, potentially reducing the efficiency of the survey when applied to high-density populations. We conducted quadrat, removal, and distance surveys of zebra mussels (Dreissena polymorpha) in three central Minnesota lakes and determined how much survey effort would be required to achieve a pre-specified level of precision for each abundance estimator, allowing us to directly compare survey design efficiencies across a range of conditions. We found that the required sampling effort needed to achieve our precision goal depended on both the survey design and population density. At low densities, survey designs that could cover large areas but with lower detection probabilities, such as distance surveys, were more efficient (i.e., required less sampling effort to achieve the same level of precision). However, at high densities, quadrat surveys, which tend to cover less area but with high detection rates, were more efficient. These results demonstrate that the best survey design is likely to be context-specific, requiring some prior knowledge of the underlying population density and the cost/time needed to collect additional information for estimating detection probabilities.
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spelling pubmed-103401012023-07-14 A comparison of survey method efficiencies for estimating densities of zebra mussels (Dreissena polymorpha) Ferguson, Jake M. Jiménez, Laura Keyes, Aislyn A. Hilding, Austen McCartney, Michael A. St. Clair, Katherine Johnson, Douglas H. Fieberg, John R. PeerJ Aquaculture, Fisheries and Fish Science Abundance surveys are commonly used to estimate plant or animal densities and frequently require estimating detection probabilities to account for imperfect detection. The estimation of detection probabilities requires additional measurements that take time, potentially reducing the efficiency of the survey when applied to high-density populations. We conducted quadrat, removal, and distance surveys of zebra mussels (Dreissena polymorpha) in three central Minnesota lakes and determined how much survey effort would be required to achieve a pre-specified level of precision for each abundance estimator, allowing us to directly compare survey design efficiencies across a range of conditions. We found that the required sampling effort needed to achieve our precision goal depended on both the survey design and population density. At low densities, survey designs that could cover large areas but with lower detection probabilities, such as distance surveys, were more efficient (i.e., required less sampling effort to achieve the same level of precision). However, at high densities, quadrat surveys, which tend to cover less area but with high detection rates, were more efficient. These results demonstrate that the best survey design is likely to be context-specific, requiring some prior knowledge of the underlying population density and the cost/time needed to collect additional information for estimating detection probabilities. PeerJ Inc. 2023-07-10 /pmc/articles/PMC10340101/ /pubmed/37456873 http://dx.doi.org/10.7717/peerj.15528 Text en © 2023 Ferguson et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Aquaculture, Fisheries and Fish Science
Ferguson, Jake M.
Jiménez, Laura
Keyes, Aislyn A.
Hilding, Austen
McCartney, Michael A.
St. Clair, Katherine
Johnson, Douglas H.
Fieberg, John R.
A comparison of survey method efficiencies for estimating densities of zebra mussels (Dreissena polymorpha)
title A comparison of survey method efficiencies for estimating densities of zebra mussels (Dreissena polymorpha)
title_full A comparison of survey method efficiencies for estimating densities of zebra mussels (Dreissena polymorpha)
title_fullStr A comparison of survey method efficiencies for estimating densities of zebra mussels (Dreissena polymorpha)
title_full_unstemmed A comparison of survey method efficiencies for estimating densities of zebra mussels (Dreissena polymorpha)
title_short A comparison of survey method efficiencies for estimating densities of zebra mussels (Dreissena polymorpha)
title_sort comparison of survey method efficiencies for estimating densities of zebra mussels (dreissena polymorpha)
topic Aquaculture, Fisheries and Fish Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10340101/
https://www.ncbi.nlm.nih.gov/pubmed/37456873
http://dx.doi.org/10.7717/peerj.15528
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