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...
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| Format: | Article |
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PeerJ Inc.
2018-02-01
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| Series: | PeerJ |
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| Online Access: | https://peerj.com/articles/4363.pdf |
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| author | Dimitrios - Georgios Kontopoulos Bernardo García-Carreras Sofía Sal Thomas P. Smith Samraat Pawar |
| author_facet | Dimitrios - Georgios Kontopoulos Bernardo García-Carreras Sofía Sal Thomas P. Smith Samraat Pawar |
| author_sort | Dimitrios - Georgios Kontopoulos |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-09T08:04:13Z |
| format | Article |
| id | doaj.art-2c717d14fec7465b987475f3b581b68d |
| institution | Directory Open Access Journal |
| issn | 2167-8359 |
| language | English |
| last_indexed | 2024-03-09T08:04:13Z |
| publishDate | 2018-02-01 |
| publisher | PeerJ Inc. |
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| series | PeerJ |
| spelling | doaj.art-2c717d14fec7465b987475f3b581b68d2023-12-03T00:25:25ZengPeerJ Inc.PeerJ2167-83592018-02-016e436310.7717/peerj.4363Use and misuse of temperature normalisation in meta-analyses of thermal responses of biological traitsDimitrios - Georgios Kontopoulos0Bernardo García-Carreras1Sofía Sal2Thomas P. Smith3Samraat Pawar4Science and Solutions for a Changing Planet DTP, Imperial College London, London, United KingdomDepartment of Life Sciences, Silwood Park, Imperial College London, Ascot, Berkshire, United KingdomDepartment of Life Sciences, Silwood Park, Imperial College London, Ascot, Berkshire, United KingdomDepartment of Life Sciences, Silwood Park, Imperial College London, Ascot, Berkshire, United KingdomDepartment of Life Sciences, Silwood Park, Imperial College London, Ascot, Berkshire, United KingdomThere 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.https://peerj.com/articles/4363.pdfSharpe-SchoolfieldThermal responsePhysiologyTemperature |
| spellingShingle | Dimitrios - Georgios Kontopoulos Bernardo García-Carreras Sofía Sal Thomas P. Smith Samraat Pawar Use and misuse of temperature normalisation in meta-analyses of thermal responses of biological traits PeerJ Sharpe-Schoolfield Thermal response Physiology Temperature |
| 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 | Sharpe-Schoolfield Thermal response Physiology Temperature |
| url | https://peerj.com/articles/4363.pdf |
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