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A comprehensive but practical methodology for selecting biological indicators for long-term monitoring

The selection of the many biological indicators described in scientific literature is rarely based on systematic or clear-cut processes, and often takes into account only a single or very few taxa, or even disregards the complex interactions that exist between the components of biodiversity. In cert...

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Autores principales: Puig-Gironès, Roger, Real, Joan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8923439/
https://www.ncbi.nlm.nih.gov/pubmed/35290396
http://dx.doi.org/10.1371/journal.pone.0265246
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author Puig-Gironès, Roger
Real, Joan
author_facet Puig-Gironès, Roger
Real, Joan
author_sort Puig-Gironès, Roger
collection PubMed
description The selection of the many biological indicators described in scientific literature is rarely based on systematic or clear-cut processes, and often takes into account only a single or very few taxa, or even disregards the complex interactions that exist between the components of biodiversity. In certain cases, the particular context of a site–for example in the Mediterranean Basin–makes it difficult to apply the choice of indicators to other regions proposed in the literature. Therefore, the selection of appropriate methodologies for generating relevant indicators for a particular site is of crucial importance. Here, we present a simple quantitative methodology capable of incorporating multidisciplinary information for assessing and selecting appropriate methods and indicators for monitoring local biodiversity. The methodology combines several ecological levels (species, habitats, processes, and ecosystem disturbances), and embraces biological interactions and common functional guilds (detritivores, producers, herbivores, and carnivores). We followed an iterative selection procedure consisting of five phases: 1) collection focal area useful information; 2) classification of this information into interrelated datasets; 3) assessment and selection of the relevant components using a quantitative relevance index; 4) the adding of taxonomic, physiognomic and functional similarities to the relevant components; and 5) the quantitative selection of the priority indicators in the study area. To demonstrate the potential of this methodology, we took as a case study the biodiversity components and their ecological interactions present in a protected area. We show that our methodology can help select appropriate local and long-term indicators, reduce the number of components required for thorough biodiversity monitoring, and underline the importance of ecological processes.
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spelling pubmed-89234392022-03-16 A comprehensive but practical methodology for selecting biological indicators for long-term monitoring Puig-Gironès, Roger Real, Joan PLoS One Research Article The selection of the many biological indicators described in scientific literature is rarely based on systematic or clear-cut processes, and often takes into account only a single or very few taxa, or even disregards the complex interactions that exist between the components of biodiversity. In certain cases, the particular context of a site–for example in the Mediterranean Basin–makes it difficult to apply the choice of indicators to other regions proposed in the literature. Therefore, the selection of appropriate methodologies for generating relevant indicators for a particular site is of crucial importance. Here, we present a simple quantitative methodology capable of incorporating multidisciplinary information for assessing and selecting appropriate methods and indicators for monitoring local biodiversity. The methodology combines several ecological levels (species, habitats, processes, and ecosystem disturbances), and embraces biological interactions and common functional guilds (detritivores, producers, herbivores, and carnivores). We followed an iterative selection procedure consisting of five phases: 1) collection focal area useful information; 2) classification of this information into interrelated datasets; 3) assessment and selection of the relevant components using a quantitative relevance index; 4) the adding of taxonomic, physiognomic and functional similarities to the relevant components; and 5) the quantitative selection of the priority indicators in the study area. To demonstrate the potential of this methodology, we took as a case study the biodiversity components and their ecological interactions present in a protected area. We show that our methodology can help select appropriate local and long-term indicators, reduce the number of components required for thorough biodiversity monitoring, and underline the importance of ecological processes. Public Library of Science 2022-03-15 /pmc/articles/PMC8923439/ /pubmed/35290396 http://dx.doi.org/10.1371/journal.pone.0265246 Text en © 2022 Puig-Gironès, Real 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, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Puig-Gironès, Roger
Real, Joan
A comprehensive but practical methodology for selecting biological indicators for long-term monitoring
title A comprehensive but practical methodology for selecting biological indicators for long-term monitoring
title_full A comprehensive but practical methodology for selecting biological indicators for long-term monitoring
title_fullStr A comprehensive but practical methodology for selecting biological indicators for long-term monitoring
title_full_unstemmed A comprehensive but practical methodology for selecting biological indicators for long-term monitoring
title_short A comprehensive but practical methodology for selecting biological indicators for long-term monitoring
title_sort comprehensive but practical methodology for selecting biological indicators for long-term monitoring
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8923439/
https://www.ncbi.nlm.nih.gov/pubmed/35290396
http://dx.doi.org/10.1371/journal.pone.0265246
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