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Optimising sampling of fish assemblages on intertidal reefs using remote underwater video

BACKGROUND: Assessing fish assemblages in subtidal and intertidal habitats is challenging due to the structural complexity of many of these systems. Trapping and collecting are regarded as optimal ways to sample these assemblages, but this method is costly and destructive, so researchers also use vi...

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Autores principales: Erickson, Katherine R., Bugnot, Ana B., Figueira, Will F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10211360/
https://www.ncbi.nlm.nih.gov/pubmed/37250718
http://dx.doi.org/10.7717/peerj.15426
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author Erickson, Katherine R.
Bugnot, Ana B.
Figueira, Will F.
author_facet Erickson, Katherine R.
Bugnot, Ana B.
Figueira, Will F.
author_sort Erickson, Katherine R.
collection PubMed
description BACKGROUND: Assessing fish assemblages in subtidal and intertidal habitats is challenging due to the structural complexity of many of these systems. Trapping and collecting are regarded as optimal ways to sample these assemblages, but this method is costly and destructive, so researchers also use video techniques. Underwater visual census and baited remote underwater video stations are commonly used to characterise fish communities in these systems. More passive techniques such as remote underwater video (RUV) may be more appropriate for behavioural studies, or for comparing proximal habitats where the broad attraction caused by bait plumes could be an issue. However, data processing for RUVs can be time consuming and create processing bottlenecks. METHODS: Here, we identified the optimal subsampling method to assess fish assemblages on intertidal oyster reefs using RUV footage and bootstrapping techniques. We quantified how video subsampling effort and method (systematic vs random) affect the accuracy and precision of three different fish assemblage metrics; species richness and two proxies for the total abundance of fish, MaxN(T) and MeanCount(T), which have not been evaluated previously for complex intertidal habitats. RESULTS: Results suggest that MaxN(T) and species richness should be recorded in real time, whereas optimal sampling for MeanCount(T) is every 60 s. Systematic sampling proved to be more accurate and precise than random sampling. This study provides valuable methodology recommendations which are relevant for the use of RUV to assess fish assemblages in a variety of shallow intertidal habitats.
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spelling pubmed-102113602023-05-26 Optimising sampling of fish assemblages on intertidal reefs using remote underwater video Erickson, Katherine R. Bugnot, Ana B. Figueira, Will F. PeerJ Aquaculture, Fisheries and Fish Science BACKGROUND: Assessing fish assemblages in subtidal and intertidal habitats is challenging due to the structural complexity of many of these systems. Trapping and collecting are regarded as optimal ways to sample these assemblages, but this method is costly and destructive, so researchers also use video techniques. Underwater visual census and baited remote underwater video stations are commonly used to characterise fish communities in these systems. More passive techniques such as remote underwater video (RUV) may be more appropriate for behavioural studies, or for comparing proximal habitats where the broad attraction caused by bait plumes could be an issue. However, data processing for RUVs can be time consuming and create processing bottlenecks. METHODS: Here, we identified the optimal subsampling method to assess fish assemblages on intertidal oyster reefs using RUV footage and bootstrapping techniques. We quantified how video subsampling effort and method (systematic vs random) affect the accuracy and precision of three different fish assemblage metrics; species richness and two proxies for the total abundance of fish, MaxN(T) and MeanCount(T), which have not been evaluated previously for complex intertidal habitats. RESULTS: Results suggest that MaxN(T) and species richness should be recorded in real time, whereas optimal sampling for MeanCount(T) is every 60 s. Systematic sampling proved to be more accurate and precise than random sampling. This study provides valuable methodology recommendations which are relevant for the use of RUV to assess fish assemblages in a variety of shallow intertidal habitats. PeerJ Inc. 2023-05-22 /pmc/articles/PMC10211360/ /pubmed/37250718 http://dx.doi.org/10.7717/peerj.15426 Text en © 2023 Erickson 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
Erickson, Katherine R.
Bugnot, Ana B.
Figueira, Will F.
Optimising sampling of fish assemblages on intertidal reefs using remote underwater video
title Optimising sampling of fish assemblages on intertidal reefs using remote underwater video
title_full Optimising sampling of fish assemblages on intertidal reefs using remote underwater video
title_fullStr Optimising sampling of fish assemblages on intertidal reefs using remote underwater video
title_full_unstemmed Optimising sampling of fish assemblages on intertidal reefs using remote underwater video
title_short Optimising sampling of fish assemblages on intertidal reefs using remote underwater video
title_sort optimising sampling of fish assemblages on intertidal reefs using remote underwater video
topic Aquaculture, Fisheries and Fish Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10211360/
https://www.ncbi.nlm.nih.gov/pubmed/37250718
http://dx.doi.org/10.7717/peerj.15426
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