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Assessing data bias in visual surveys from a cetacean monitoring programme

Long-term monitoring datasets are fundamental to understand physical and ecological responses to environmental changes, supporting management and conservation. The data should be reliable, with the sources of bias identified and quantified. CETUS Project is a cetacean monitoring programme in the Eas...

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Autores principales: Oliveira-Rodrigues, Cláudia, Correia, Ana M., Valente, Raul, Gil, Ágatha, Gandra, Miguel, Liberal, Marcos, Rosso, Massimiliano, Pierce, Graham, Sousa-Pinto, Isabel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9649672/
https://www.ncbi.nlm.nih.gov/pubmed/36357425
http://dx.doi.org/10.1038/s41597-022-01803-7
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author Oliveira-Rodrigues, Cláudia
Correia, Ana M.
Valente, Raul
Gil, Ágatha
Gandra, Miguel
Liberal, Marcos
Rosso, Massimiliano
Pierce, Graham
Sousa-Pinto, Isabel
author_facet Oliveira-Rodrigues, Cláudia
Correia, Ana M.
Valente, Raul
Gil, Ágatha
Gandra, Miguel
Liberal, Marcos
Rosso, Massimiliano
Pierce, Graham
Sousa-Pinto, Isabel
author_sort Oliveira-Rodrigues, Cláudia
collection PubMed
description Long-term monitoring datasets are fundamental to understand physical and ecological responses to environmental changes, supporting management and conservation. The data should be reliable, with the sources of bias identified and quantified. CETUS Project is a cetacean monitoring programme in the Eastern North Atlantic, based on visual methods of data collection. This study aims to assess data quality and bias in the CETUS dataset, by 1) applying validation methods, through photographic confirmation of species identification; 2) creating data quality criteria to evaluate the observer’s experience; and 3) assessing bias to the number of sightings collected and to the success in species identification. Through photographic validation, the species identification of 10 sightings was corrected and a new species was added to the CETUS dataset. The number of sightings collected was biased by external factors, mostly by sampling effort but also by weather conditions. Ultimately, results highlight the importance of identifying and quantifying data bias, while also yielding guidelines for data collection and processing, relevant for species monitoring programmes based on visual methods.
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spelling pubmed-96496722022-11-15 Assessing data bias in visual surveys from a cetacean monitoring programme Oliveira-Rodrigues, Cláudia Correia, Ana M. Valente, Raul Gil, Ágatha Gandra, Miguel Liberal, Marcos Rosso, Massimiliano Pierce, Graham Sousa-Pinto, Isabel Sci Data Analysis Long-term monitoring datasets are fundamental to understand physical and ecological responses to environmental changes, supporting management and conservation. The data should be reliable, with the sources of bias identified and quantified. CETUS Project is a cetacean monitoring programme in the Eastern North Atlantic, based on visual methods of data collection. This study aims to assess data quality and bias in the CETUS dataset, by 1) applying validation methods, through photographic confirmation of species identification; 2) creating data quality criteria to evaluate the observer’s experience; and 3) assessing bias to the number of sightings collected and to the success in species identification. Through photographic validation, the species identification of 10 sightings was corrected and a new species was added to the CETUS dataset. The number of sightings collected was biased by external factors, mostly by sampling effort but also by weather conditions. Ultimately, results highlight the importance of identifying and quantifying data bias, while also yielding guidelines for data collection and processing, relevant for species monitoring programmes based on visual methods. Nature Publishing Group UK 2022-11-10 /pmc/articles/PMC9649672/ /pubmed/36357425 http://dx.doi.org/10.1038/s41597-022-01803-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Analysis
Oliveira-Rodrigues, Cláudia
Correia, Ana M.
Valente, Raul
Gil, Ágatha
Gandra, Miguel
Liberal, Marcos
Rosso, Massimiliano
Pierce, Graham
Sousa-Pinto, Isabel
Assessing data bias in visual surveys from a cetacean monitoring programme
title Assessing data bias in visual surveys from a cetacean monitoring programme
title_full Assessing data bias in visual surveys from a cetacean monitoring programme
title_fullStr Assessing data bias in visual surveys from a cetacean monitoring programme
title_full_unstemmed Assessing data bias in visual surveys from a cetacean monitoring programme
title_short Assessing data bias in visual surveys from a cetacean monitoring programme
title_sort assessing data bias in visual surveys from a cetacean monitoring programme
topic Analysis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9649672/
https://www.ncbi.nlm.nih.gov/pubmed/36357425
http://dx.doi.org/10.1038/s41597-022-01803-7
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