A new metric to calculate the opportunity for selection on quantitative characters
Background: Evolutionary changes in natural populations can occur on ecological time scales. Investigators have become very interested in characterizing short-term fluctuations in selection pressure, in identifying the circumstances under which the opportunity for selection is greatest, and in deter...
| 主要な著者: | , |
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| フォーマット: | Journal article |
| 言語: | English |
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2012
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| _version_ | 1826260828619276288 |
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| author | Pelletier, F Coulson, T |
| author_facet | Pelletier, F Coulson, T |
| author_sort | Pelletier, F |
| collection | OXFORD |
| description | Background: Evolutionary changes in natural populations can occur on ecological time scales. Investigators have become very interested in characterizing short-term fluctuations in selection pressure, in identifying the circumstances under which the opportunity for selection is greatest, and in determining whether this opportunity is realized. Aims: Introduce a new metric to explore how the opportunity for selection on the mean of a phenotypic character varies with time. Using data from two long-term studies of marked individuals, examine how the opportunity for and the selection on a character mean and variance covary with population growth. Metrics: The traditional opportunity for selection metric (OS) is defined as the variance in relative fitness or the variation in absolute fitness divided by the square of the mean absolute fitness. This metric might not be appropriate to evaluate the maximum selection acting on a quantitative character because individual variation in both quantitative characters and in fitness underpins evolution by natural selection. We therefore develop a new metric, the opportunity for selection on a quantitative character (OSM), which considers variation in both character and fitness distributions. Methods: Determine selection, OS, and OSM, in both simulated and empirical data. Compare the results for the traditional OS metric with the new OSM. Results: The classical measure of the OS correlates with the OSM when calculated on simulated data but their association was curvilinear for non-normally distributed fitness components. Similar results were found for empirical data but their correlations were lower. Selection is strongest in declining populations and is greatest when the OSM is large, as in harsh environments. Conclusions: Because most fitness components are non-normally distributed, OS will only approximately capture the maximum possible selection differential on phenotypic characters over a time step. The OSM should be a more useful metric for determining how selection will alter the distribution of characters. © 2012 Fanie Pelletier. |
| first_indexed | 2024-03-06T19:11:55Z |
| format | Journal article |
| id | oxford-uuid:1711140f-7e4a-4df8-a9ee-aaa9ac0e9abd |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T19:11:55Z |
| publishDate | 2012 |
| record_format | dspace |
| spelling | oxford-uuid:1711140f-7e4a-4df8-a9ee-aaa9ac0e9abd2022-03-26T10:34:56ZA new metric to calculate the opportunity for selection on quantitative charactersJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:1711140f-7e4a-4df8-a9ee-aaa9ac0e9abdEnglishSymplectic Elements at Oxford2012Pelletier, FCoulson, TBackground: Evolutionary changes in natural populations can occur on ecological time scales. Investigators have become very interested in characterizing short-term fluctuations in selection pressure, in identifying the circumstances under which the opportunity for selection is greatest, and in determining whether this opportunity is realized. Aims: Introduce a new metric to explore how the opportunity for selection on the mean of a phenotypic character varies with time. Using data from two long-term studies of marked individuals, examine how the opportunity for and the selection on a character mean and variance covary with population growth. Metrics: The traditional opportunity for selection metric (OS) is defined as the variance in relative fitness or the variation in absolute fitness divided by the square of the mean absolute fitness. This metric might not be appropriate to evaluate the maximum selection acting on a quantitative character because individual variation in both quantitative characters and in fitness underpins evolution by natural selection. We therefore develop a new metric, the opportunity for selection on a quantitative character (OSM), which considers variation in both character and fitness distributions. Methods: Determine selection, OS, and OSM, in both simulated and empirical data. Compare the results for the traditional OS metric with the new OSM. Results: The classical measure of the OS correlates with the OSM when calculated on simulated data but their association was curvilinear for non-normally distributed fitness components. Similar results were found for empirical data but their correlations were lower. Selection is strongest in declining populations and is greatest when the OSM is large, as in harsh environments. Conclusions: Because most fitness components are non-normally distributed, OS will only approximately capture the maximum possible selection differential on phenotypic characters over a time step. The OSM should be a more useful metric for determining how selection will alter the distribution of characters. © 2012 Fanie Pelletier. |
| spellingShingle | Pelletier, F Coulson, T A new metric to calculate the opportunity for selection on quantitative characters |
| title | A new metric to calculate the opportunity for selection on quantitative characters |
| title_full | A new metric to calculate the opportunity for selection on quantitative characters |
| title_fullStr | A new metric to calculate the opportunity for selection on quantitative characters |
| title_full_unstemmed | A new metric to calculate the opportunity for selection on quantitative characters |
| title_short | A new metric to calculate the opportunity for selection on quantitative characters |
| title_sort | new metric to calculate the opportunity for selection on quantitative characters |
| work_keys_str_mv | AT pelletierf anewmetrictocalculatetheopportunityforselectiononquantitativecharacters AT coulsont anewmetrictocalculatetheopportunityforselectiononquantitativecharacters AT pelletierf newmetrictocalculatetheopportunityforselectiononquantitativecharacters AT coulsont newmetrictocalculatetheopportunityforselectiononquantitativecharacters |