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Use and misuse of temperature normalisation in meta-analyses of thermal responses of biological traits
There is currently unprecedented interest in quantifying variation in thermal physiology among organisms, especially in order to understand and predict the biological impacts of climate change. A key parameter in this quantification of thermal physiology is the performance or value of a rate, across...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5808315/ https://www.ncbi.nlm.nih.gov/pubmed/29441242 http://dx.doi.org/10.7717/peerj.4363 |
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author | Kontopoulos, Dimitrios - Georgios García-Carreras, Bernardo Sal, Sofía Smith, Thomas P. Pawar, Samraat |
author_facet | Kontopoulos, Dimitrios - Georgios García-Carreras, Bernardo Sal, Sofía Smith, Thomas P. Pawar, Samraat |
author_sort | Kontopoulos, Dimitrios - Georgios |
collection | PubMed |
description | There is currently unprecedented interest in quantifying variation in thermal physiology among organisms, especially in order to understand and predict the biological impacts of climate change. A key parameter in this quantification of thermal physiology is the performance or value of a rate, across individuals or species, at a common temperature (temperature normalisation). An increasingly popular model for fitting thermal performance curves to data—the Sharpe-Schoolfield equation—can yield strongly inflated estimates of temperature-normalised rate values. These deviations occur whenever a key thermodynamic assumption of the model is violated, i.e., when the enzyme governing the performance of the rate is not fully functional at the chosen reference temperature. Using data on 1,758 thermal performance curves across a wide range of species, we identify the conditions that exacerbate this inflation. We then demonstrate that these biases can compromise tests to detect metabolic cold adaptation, which requires comparison of fitness or rate performance of different species or genotypes at some fixed low temperature. Finally, we suggest alternative methods for obtaining unbiased estimates of temperature-normalised rate values for meta-analyses of thermal performance across species in climate change impact studies. |
format | Online Article Text |
id | pubmed-5808315 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-58083152018-02-13 Use and misuse of temperature normalisation in meta-analyses of thermal responses of biological traits Kontopoulos, Dimitrios - Georgios García-Carreras, Bernardo Sal, Sofía Smith, Thomas P. Pawar, Samraat PeerJ Ecology There is currently unprecedented interest in quantifying variation in thermal physiology among organisms, especially in order to understand and predict the biological impacts of climate change. A key parameter in this quantification of thermal physiology is the performance or value of a rate, across individuals or species, at a common temperature (temperature normalisation). An increasingly popular model for fitting thermal performance curves to data—the Sharpe-Schoolfield equation—can yield strongly inflated estimates of temperature-normalised rate values. These deviations occur whenever a key thermodynamic assumption of the model is violated, i.e., when the enzyme governing the performance of the rate is not fully functional at the chosen reference temperature. Using data on 1,758 thermal performance curves across a wide range of species, we identify the conditions that exacerbate this inflation. We then demonstrate that these biases can compromise tests to detect metabolic cold adaptation, which requires comparison of fitness or rate performance of different species or genotypes at some fixed low temperature. Finally, we suggest alternative methods for obtaining unbiased estimates of temperature-normalised rate values for meta-analyses of thermal performance across species in climate change impact studies. PeerJ Inc. 2018-02-09 /pmc/articles/PMC5808315/ /pubmed/29441242 http://dx.doi.org/10.7717/peerj.4363 Text en ©2018 Kontopoulos et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://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 | Ecology Kontopoulos, Dimitrios - Georgios García-Carreras, Bernardo Sal, Sofía Smith, Thomas P. Pawar, Samraat Use and misuse of temperature normalisation in meta-analyses of thermal responses of biological traits |
title | Use and misuse of temperature normalisation in meta-analyses of thermal responses of biological traits |
title_full | Use and misuse of temperature normalisation in meta-analyses of thermal responses of biological traits |
title_fullStr | Use and misuse of temperature normalisation in meta-analyses of thermal responses of biological traits |
title_full_unstemmed | Use and misuse of temperature normalisation in meta-analyses of thermal responses of biological traits |
title_short | Use and misuse of temperature normalisation in meta-analyses of thermal responses of biological traits |
title_sort | use and misuse of temperature normalisation in meta-analyses of thermal responses of biological traits |
topic | Ecology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5808315/ https://www.ncbi.nlm.nih.gov/pubmed/29441242 http://dx.doi.org/10.7717/peerj.4363 |
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