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Optimizing speleological monitoring efforts: insights from long-term data for tropical iron caves

Understanding the factors underpinning species abundance patterns in space and time is essential to implement effective cave conservation actions. Yet, the methods employed to monitor cave biodiversity still lack standardization, and no quantitative assessment has yet tried to optimize the amount an...

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Autores principales: Trevelin, Leonardo Carreira, Simões, Matheus Henrique, Prous, Xavier, Pietrobon, Thadeu, Brandi, Iuri Viana, Jaffé, Rodolfo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8054738/
https://www.ncbi.nlm.nih.gov/pubmed/33959423
http://dx.doi.org/10.7717/peerj.11271
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author Trevelin, Leonardo Carreira
Simões, Matheus Henrique
Prous, Xavier
Pietrobon, Thadeu
Brandi, Iuri Viana
Jaffé, Rodolfo
author_facet Trevelin, Leonardo Carreira
Simões, Matheus Henrique
Prous, Xavier
Pietrobon, Thadeu
Brandi, Iuri Viana
Jaffé, Rodolfo
author_sort Trevelin, Leonardo Carreira
collection PubMed
description Understanding the factors underpinning species abundance patterns in space and time is essential to implement effective cave conservation actions. Yet, the methods employed to monitor cave biodiversity still lack standardization, and no quantitative assessment has yet tried to optimize the amount and type of information required to efficiently identify disturbances in cave ecosystems. Using a comprehensive monitoring dataset for tropical iron caves, comprising abundance measurements for 33 target taxa surveyed across 95 caves along four years, here we provide the first evidence-based recommendations to optimize monitoring programs seeking to follow target species abundance through time. We found that seasonality did not influence the ability to detect temporal abundance trends. However, in most species, abundance estimates assessed during the dry season resulted in a more accurate detection of temporal abundance trends, and at least three surveys were required to identify global temporal abundance trends. Finally, we identified a subset of species that could potentially serve as short-term disturbance indicators. Results suggest that iron cave monitoring programs implemented in our study region could focus sampling efforts in the dry season, where detectability of target species is higher, while assuring data collection for at least three years. More generally, our study reveals the importance of long-term cave monitoring programs for detecting possible disturbances in subterranean ecosystems, and for using the generated information to optimize future monitoring efforts.
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spelling pubmed-80547382021-05-05 Optimizing speleological monitoring efforts: insights from long-term data for tropical iron caves Trevelin, Leonardo Carreira Simões, Matheus Henrique Prous, Xavier Pietrobon, Thadeu Brandi, Iuri Viana Jaffé, Rodolfo PeerJ Biodiversity Understanding the factors underpinning species abundance patterns in space and time is essential to implement effective cave conservation actions. Yet, the methods employed to monitor cave biodiversity still lack standardization, and no quantitative assessment has yet tried to optimize the amount and type of information required to efficiently identify disturbances in cave ecosystems. Using a comprehensive monitoring dataset for tropical iron caves, comprising abundance measurements for 33 target taxa surveyed across 95 caves along four years, here we provide the first evidence-based recommendations to optimize monitoring programs seeking to follow target species abundance through time. We found that seasonality did not influence the ability to detect temporal abundance trends. However, in most species, abundance estimates assessed during the dry season resulted in a more accurate detection of temporal abundance trends, and at least three surveys were required to identify global temporal abundance trends. Finally, we identified a subset of species that could potentially serve as short-term disturbance indicators. Results suggest that iron cave monitoring programs implemented in our study region could focus sampling efforts in the dry season, where detectability of target species is higher, while assuring data collection for at least three years. More generally, our study reveals the importance of long-term cave monitoring programs for detecting possible disturbances in subterranean ecosystems, and for using the generated information to optimize future monitoring efforts. PeerJ Inc. 2021-04-16 /pmc/articles/PMC8054738/ /pubmed/33959423 http://dx.doi.org/10.7717/peerj.11271 Text en © 2021 Trevelin 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 Biodiversity
Trevelin, Leonardo Carreira
Simões, Matheus Henrique
Prous, Xavier
Pietrobon, Thadeu
Brandi, Iuri Viana
Jaffé, Rodolfo
Optimizing speleological monitoring efforts: insights from long-term data for tropical iron caves
title Optimizing speleological monitoring efforts: insights from long-term data for tropical iron caves
title_full Optimizing speleological monitoring efforts: insights from long-term data for tropical iron caves
title_fullStr Optimizing speleological monitoring efforts: insights from long-term data for tropical iron caves
title_full_unstemmed Optimizing speleological monitoring efforts: insights from long-term data for tropical iron caves
title_short Optimizing speleological monitoring efforts: insights from long-term data for tropical iron caves
title_sort optimizing speleological monitoring efforts: insights from long-term data for tropical iron caves
topic Biodiversity
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8054738/
https://www.ncbi.nlm.nih.gov/pubmed/33959423
http://dx.doi.org/10.7717/peerj.11271
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