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Biological traits approaches in benthic marine ecology: Dead ends and new paths

Biological traits analysis (BTA) links community structure to both ecological functions and response to environmental drivers through species’ attributes. In consequence, it has become a popular approach in marine benthic studies. However, BTA will reach a dead end if the scientific community does n...

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Detalles Bibliográficos
Autores principales: de Juan, Silvia, Bremner, Julie, Hewitt, Judi, Törnroos, Anna, Mangano, Maria Cristina, Thrush, Simon, Hinz, Hilmar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9163796/
https://www.ncbi.nlm.nih.gov/pubmed/35784057
http://dx.doi.org/10.1002/ece3.9001
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author de Juan, Silvia
Bremner, Julie
Hewitt, Judi
Törnroos, Anna
Mangano, Maria Cristina
Thrush, Simon
Hinz, Hilmar
author_facet de Juan, Silvia
Bremner, Julie
Hewitt, Judi
Törnroos, Anna
Mangano, Maria Cristina
Thrush, Simon
Hinz, Hilmar
author_sort de Juan, Silvia
collection PubMed
description Biological traits analysis (BTA) links community structure to both ecological functions and response to environmental drivers through species’ attributes. In consequence, it has become a popular approach in marine benthic studies. However, BTA will reach a dead end if the scientific community does not acknowledge its current shortcomings and limitations: (a) uncertainties related to data origins and a lack of standardized reporting of trait information; (b) knowledge gaps on the role of multiple interacting traits on driving the organisms’ responses to environmental variability; (c) knowledge gaps regarding the mechanistic links between traits and functions; (d) a weak focus on the spatial and temporal variability that is inherent to the trait expression of species; and, last but not least, (e) the large reliance on expert knowledge due to an enormous knowledge gap on the basic ecology of many benthic species. BTA will only reach its full potential if the scientific community is able to standardize and unify the reporting and storage of traits data and reconsider the importance of baseline observational and experimental studies to fill knowledge gaps on the mechanistic links between biological traits, functions, and environmental variability. This challenge could be assisted by embracing new technological advances in marine monitoring, such as underwater camera technology and artificial intelligence, and making use of advanced statistical approaches that consider the interactive nature and spatio‐temporal variability of biological systems. The scientific community has to abandon some dead ends and explore new paths that will improve our understanding of individual species, traits, and the functioning of benthic ecosystems.
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spelling pubmed-91637962022-07-01 Biological traits approaches in benthic marine ecology: Dead ends and new paths de Juan, Silvia Bremner, Julie Hewitt, Judi Törnroos, Anna Mangano, Maria Cristina Thrush, Simon Hinz, Hilmar Ecol Evol Viewpoint Biological traits analysis (BTA) links community structure to both ecological functions and response to environmental drivers through species’ attributes. In consequence, it has become a popular approach in marine benthic studies. However, BTA will reach a dead end if the scientific community does not acknowledge its current shortcomings and limitations: (a) uncertainties related to data origins and a lack of standardized reporting of trait information; (b) knowledge gaps on the role of multiple interacting traits on driving the organisms’ responses to environmental variability; (c) knowledge gaps regarding the mechanistic links between traits and functions; (d) a weak focus on the spatial and temporal variability that is inherent to the trait expression of species; and, last but not least, (e) the large reliance on expert knowledge due to an enormous knowledge gap on the basic ecology of many benthic species. BTA will only reach its full potential if the scientific community is able to standardize and unify the reporting and storage of traits data and reconsider the importance of baseline observational and experimental studies to fill knowledge gaps on the mechanistic links between biological traits, functions, and environmental variability. This challenge could be assisted by embracing new technological advances in marine monitoring, such as underwater camera technology and artificial intelligence, and making use of advanced statistical approaches that consider the interactive nature and spatio‐temporal variability of biological systems. The scientific community has to abandon some dead ends and explore new paths that will improve our understanding of individual species, traits, and the functioning of benthic ecosystems. John Wiley and Sons Inc. 2022-06-03 /pmc/articles/PMC9163796/ /pubmed/35784057 http://dx.doi.org/10.1002/ece3.9001 Text en © 2022 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Viewpoint
de Juan, Silvia
Bremner, Julie
Hewitt, Judi
Törnroos, Anna
Mangano, Maria Cristina
Thrush, Simon
Hinz, Hilmar
Biological traits approaches in benthic marine ecology: Dead ends and new paths
title Biological traits approaches in benthic marine ecology: Dead ends and new paths
title_full Biological traits approaches in benthic marine ecology: Dead ends and new paths
title_fullStr Biological traits approaches in benthic marine ecology: Dead ends and new paths
title_full_unstemmed Biological traits approaches in benthic marine ecology: Dead ends and new paths
title_short Biological traits approaches in benthic marine ecology: Dead ends and new paths
title_sort biological traits approaches in benthic marine ecology: dead ends and new paths
topic Viewpoint
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9163796/
https://www.ncbi.nlm.nih.gov/pubmed/35784057
http://dx.doi.org/10.1002/ece3.9001
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