From stochastic environments to life histories and back.
Environmental stochasticity is known to play an important role in life-history evolution, but most general theory assumes a constant environment. In this paper, we examine life-history evolution in a variable environment, by decomposing average individual fitness (measured by the long-run stochastic...
| প্রধান লেখক: | , , |
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| বিন্যাস: | Journal article |
| ভাষা: | English |
| প্রকাশিত: |
2009
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| _version_ | 1826303869632643072 |
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| author | Tuljapurkar, S Gaillard, J Coulson, T |
| author_facet | Tuljapurkar, S Gaillard, J Coulson, T |
| author_sort | Tuljapurkar, S |
| collection | OXFORD |
| description | Environmental stochasticity is known to play an important role in life-history evolution, but most general theory assumes a constant environment. In this paper, we examine life-history evolution in a variable environment, by decomposing average individual fitness (measured by the long-run stochastic growth rate) into contributions from average vital rates and their temporal variation. We examine how generation time, demographic dispersion (measured by the dispersion of reproductive events across the lifespan), demographic resilience (measured by damping time), within-year variances in vital rates, within-year correlations between vital rates and between-year correlations in vital rates combine to determine average individual fitness of stylized life histories. In a fluctuating environment, we show that there is often a range of cohort generation times at which the fitness is at a maximum. Thus, we expect 'optimal' phenotypes in fluctuating environments to differ from optimal phenotypes in constant environments. We show that stochastic growth rates are strongly affected by demographic dispersion, even when deterministic growth rates are not, and that demographic dispersion also determines the response of life-history-specific average fitness to within- and between-year correlations. Serial correlations can have a strong effect on fitness, and, depending on the structure of the life history, may act to increase or decrease fitness. The approach we outline takes a useful first step in developing general life-history theory for non-constant environments. |
| first_indexed | 2024-03-07T06:09:15Z |
| format | Journal article |
| id | oxford-uuid:eee8a2e7-f6f2-45b0-a4b2-a09d393ec6b6 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T06:09:15Z |
| publishDate | 2009 |
| record_format | dspace |
| spelling | oxford-uuid:eee8a2e7-f6f2-45b0-a4b2-a09d393ec6b62022-03-27T11:36:21ZFrom stochastic environments to life histories and back.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:eee8a2e7-f6f2-45b0-a4b2-a09d393ec6b6EnglishSymplectic Elements at Oxford2009Tuljapurkar, SGaillard, JCoulson, TEnvironmental stochasticity is known to play an important role in life-history evolution, but most general theory assumes a constant environment. In this paper, we examine life-history evolution in a variable environment, by decomposing average individual fitness (measured by the long-run stochastic growth rate) into contributions from average vital rates and their temporal variation. We examine how generation time, demographic dispersion (measured by the dispersion of reproductive events across the lifespan), demographic resilience (measured by damping time), within-year variances in vital rates, within-year correlations between vital rates and between-year correlations in vital rates combine to determine average individual fitness of stylized life histories. In a fluctuating environment, we show that there is often a range of cohort generation times at which the fitness is at a maximum. Thus, we expect 'optimal' phenotypes in fluctuating environments to differ from optimal phenotypes in constant environments. We show that stochastic growth rates are strongly affected by demographic dispersion, even when deterministic growth rates are not, and that demographic dispersion also determines the response of life-history-specific average fitness to within- and between-year correlations. Serial correlations can have a strong effect on fitness, and, depending on the structure of the life history, may act to increase or decrease fitness. The approach we outline takes a useful first step in developing general life-history theory for non-constant environments. |
| spellingShingle | Tuljapurkar, S Gaillard, J Coulson, T From stochastic environments to life histories and back. |
| title | From stochastic environments to life histories and back. |
| title_full | From stochastic environments to life histories and back. |
| title_fullStr | From stochastic environments to life histories and back. |
| title_full_unstemmed | From stochastic environments to life histories and back. |
| title_short | From stochastic environments to life histories and back. |
| title_sort | from stochastic environments to life histories and back |
| work_keys_str_mv | AT tuljapurkars fromstochasticenvironmentstolifehistoriesandback AT gaillardj fromstochasticenvironmentstolifehistoriesandback AT coulsont fromstochasticenvironmentstolifehistoriesandback |