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Point‐Combination Transect (PCT): Incorporation of small underwater cameras to study fish communities
1. Available underwater visual census (UVC) methods such as line transects or point count observations are widely used to obtain community data of underwater species assemblages, despite their known pit‐falls. As interest in the community structure of aquatic life is growing, there is need for more...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6582616/ https://www.ncbi.nlm.nih.gov/pubmed/31244987 http://dx.doi.org/10.1111/2041-210X.13163 |
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author | Widmer, Lukas Heule, Elia Colombo, Marco Rueegg, Attila Indermaur, Adrian Ronco, Fabrizia Salzburger, Walter |
author_facet | Widmer, Lukas Heule, Elia Colombo, Marco Rueegg, Attila Indermaur, Adrian Ronco, Fabrizia Salzburger, Walter |
author_sort | Widmer, Lukas |
collection | PubMed |
description | 1. Available underwater visual census (UVC) methods such as line transects or point count observations are widely used to obtain community data of underwater species assemblages, despite their known pit‐falls. As interest in the community structure of aquatic life is growing, there is need for more standardized and replicable methods for acquiring underwater census data. 2. Here, we propose a novel approach, Point‐Combination Transect (PCT), which makes use of automated image recording by small digital cameras to eliminate observer and identification biases associated with available UVC methods. We conducted a pilot study at Lake Tanganyika, demonstrating the applicability of PCT on a taxonomically and phenotypically highly diverse assemblage of fishes, the Tanganyikan cichlid species‐flock. 3. We conducted 17 PCTs consisting of five GoPro cameras each and identified 22,867 individual cichlids belonging to 61 species on the recorded images. These data were then used to evaluate our method and to compare it to traditional line transect studies conducted in close proximity to our study site at Lake Tanganyika. 4. We show that the analysis of the second hour of PCT image recordings (equivalent to 360 images per camera) leads to reliable estimates of the benthic cichlid community composition in Lake Tanganyika according to species accumulation curves, while minimizing the effect of disturbance of the fish through SCUBA divers. We further show that PCT is robust against observer biases and outperforms traditional line transect methods. |
format | Online Article Text |
id | pubmed-6582616 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-65826162019-06-24 Point‐Combination Transect (PCT): Incorporation of small underwater cameras to study fish communities Widmer, Lukas Heule, Elia Colombo, Marco Rueegg, Attila Indermaur, Adrian Ronco, Fabrizia Salzburger, Walter Methods Ecol Evol Ecological Networks and Communities 1. Available underwater visual census (UVC) methods such as line transects or point count observations are widely used to obtain community data of underwater species assemblages, despite their known pit‐falls. As interest in the community structure of aquatic life is growing, there is need for more standardized and replicable methods for acquiring underwater census data. 2. Here, we propose a novel approach, Point‐Combination Transect (PCT), which makes use of automated image recording by small digital cameras to eliminate observer and identification biases associated with available UVC methods. We conducted a pilot study at Lake Tanganyika, demonstrating the applicability of PCT on a taxonomically and phenotypically highly diverse assemblage of fishes, the Tanganyikan cichlid species‐flock. 3. We conducted 17 PCTs consisting of five GoPro cameras each and identified 22,867 individual cichlids belonging to 61 species on the recorded images. These data were then used to evaluate our method and to compare it to traditional line transect studies conducted in close proximity to our study site at Lake Tanganyika. 4. We show that the analysis of the second hour of PCT image recordings (equivalent to 360 images per camera) leads to reliable estimates of the benthic cichlid community composition in Lake Tanganyika according to species accumulation curves, while minimizing the effect of disturbance of the fish through SCUBA divers. We further show that PCT is robust against observer biases and outperforms traditional line transect methods. John Wiley and Sons Inc. 2019-02-20 2019-06 /pmc/articles/PMC6582616/ /pubmed/31244987 http://dx.doi.org/10.1111/2041-210X.13163 Text en © 2019 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Ecological Networks and Communities Widmer, Lukas Heule, Elia Colombo, Marco Rueegg, Attila Indermaur, Adrian Ronco, Fabrizia Salzburger, Walter Point‐Combination Transect (PCT): Incorporation of small underwater cameras to study fish communities |
title | Point‐Combination Transect (PCT): Incorporation of small underwater cameras to study fish communities |
title_full | Point‐Combination Transect (PCT): Incorporation of small underwater cameras to study fish communities |
title_fullStr | Point‐Combination Transect (PCT): Incorporation of small underwater cameras to study fish communities |
title_full_unstemmed | Point‐Combination Transect (PCT): Incorporation of small underwater cameras to study fish communities |
title_short | Point‐Combination Transect (PCT): Incorporation of small underwater cameras to study fish communities |
title_sort | point‐combination transect (pct): incorporation of small underwater cameras to study fish communities |
topic | Ecological Networks and Communities |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6582616/ https://www.ncbi.nlm.nih.gov/pubmed/31244987 http://dx.doi.org/10.1111/2041-210X.13163 |
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