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Defining plant ecological specialists and generalists: Building a framework for identification and classification

Specialization is a widespread but highly ambiguous and context‐dependent ecological concept. This quality makes comparisons across related studies difficult and makes associated terms such as “specialist” and “generalist” scientifically obscure. Here, we present a metric‐based framework to quantify...

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Autores principales: Kirsch, Alex, Kaproth, Matthew A.
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/PMC9685674/
https://www.ncbi.nlm.nih.gov/pubmed/36440310
http://dx.doi.org/10.1002/ece3.9527
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author Kirsch, Alex
Kaproth, Matthew A.
author_facet Kirsch, Alex
Kaproth, Matthew A.
author_sort Kirsch, Alex
collection PubMed
description Specialization is a widespread but highly ambiguous and context‐dependent ecological concept. This quality makes comparisons across related studies difficult and makes associated terms such as “specialist” and “generalist” scientifically obscure. Here, we present a metric‐based framework to quantify specialization in 141 Quercus species using functional traits, biogeography, and species interactions. Rankings of specialization based on five metrics were used to answer questions about how specialization is used colloquially (i.e., individual species assessment by experts) and influenced by phylogenetics (Ancestral Character State Reconstruction, Automatic Shift Detection), biogeography (patterns of clustering by region and with climate), and species threat level (IUCN Red List). Metric‐based ranking can be representative of specialization in a consistent and practical manner, correlating with IUCN Red List data, and the mean scores of individual expert assessments. Specialization is shown to be highly correlated with precipitation seasonality and only moderately influenced by evolutionary history. Data‐deficient species were more likely to be highly specialized, and higher specialization was positively correlated with greater IUCN threat level. Frameworks for characterizing specialization and generalization can be done using metric ranking and can turn concepts that are often unclear into a definitive system. Metric‐based rankings of specialization can also be used to reveal interesting insights about a clade's evolutionary history and geographic distribution when paired with the related phylogenetic and geographic data. Metric‐based rankings can be applied to other systems and be a valuable tool for identifying species at risk and in need of conservation.
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spelling pubmed-96856742022-11-25 Defining plant ecological specialists and generalists: Building a framework for identification and classification Kirsch, Alex Kaproth, Matthew A. Ecol Evol Research Articles Specialization is a widespread but highly ambiguous and context‐dependent ecological concept. This quality makes comparisons across related studies difficult and makes associated terms such as “specialist” and “generalist” scientifically obscure. Here, we present a metric‐based framework to quantify specialization in 141 Quercus species using functional traits, biogeography, and species interactions. Rankings of specialization based on five metrics were used to answer questions about how specialization is used colloquially (i.e., individual species assessment by experts) and influenced by phylogenetics (Ancestral Character State Reconstruction, Automatic Shift Detection), biogeography (patterns of clustering by region and with climate), and species threat level (IUCN Red List). Metric‐based ranking can be representative of specialization in a consistent and practical manner, correlating with IUCN Red List data, and the mean scores of individual expert assessments. Specialization is shown to be highly correlated with precipitation seasonality and only moderately influenced by evolutionary history. Data‐deficient species were more likely to be highly specialized, and higher specialization was positively correlated with greater IUCN threat level. Frameworks for characterizing specialization and generalization can be done using metric ranking and can turn concepts that are often unclear into a definitive system. Metric‐based rankings of specialization can also be used to reveal interesting insights about a clade's evolutionary history and geographic distribution when paired with the related phylogenetic and geographic data. Metric‐based rankings can be applied to other systems and be a valuable tool for identifying species at risk and in need of conservation. John Wiley and Sons Inc. 2022-11-24 /pmc/articles/PMC9685674/ /pubmed/36440310 http://dx.doi.org/10.1002/ece3.9527 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 Research Articles
Kirsch, Alex
Kaproth, Matthew A.
Defining plant ecological specialists and generalists: Building a framework for identification and classification
title Defining plant ecological specialists and generalists: Building a framework for identification and classification
title_full Defining plant ecological specialists and generalists: Building a framework for identification and classification
title_fullStr Defining plant ecological specialists and generalists: Building a framework for identification and classification
title_full_unstemmed Defining plant ecological specialists and generalists: Building a framework for identification and classification
title_short Defining plant ecological specialists and generalists: Building a framework for identification and classification
title_sort defining plant ecological specialists and generalists: building a framework for identification and classification
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9685674/
https://www.ncbi.nlm.nih.gov/pubmed/36440310
http://dx.doi.org/10.1002/ece3.9527
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