Estimating the functional form for the density dependence from life history data.
Two contrasting approaches to the analysis of population dynamics are currently popular: demographic approaches where the associations between demographic rates and statistics summarizing the population dynamics are identified; and time series approaches where the associations between population dyn...
| Main Authors: | , , , , , , , , , , |
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| Formato: | Journal article |
| Idioma: | English |
| Publicado em: |
2008
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| _version_ | 1826264033694580736 |
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| author | Coulson, T Ezard, T Pelletier, F Tavecchia, G Stenseth, N Childs, D Pilkington, J Pemberton, J Kruuk, L Clutton-Brock, T Crawley, M |
| author_facet | Coulson, T Ezard, T Pelletier, F Tavecchia, G Stenseth, N Childs, D Pilkington, J Pemberton, J Kruuk, L Clutton-Brock, T Crawley, M |
| author_sort | Coulson, T |
| collection | OXFORD |
| description | Two contrasting approaches to the analysis of population dynamics are currently popular: demographic approaches where the associations between demographic rates and statistics summarizing the population dynamics are identified; and time series approaches where the associations between population dynamics, population density, and environmental covariates are investigated. In this paper, we develop an approach to combine these methods and apply it to detailed data from Soay sheep (Ovis aries). We examine how density dependence and climate contribute to fluctuations in population size via age- and sex-specific demographic rates, and how fluctuations in demographic structure influence population dynamics. Density dependence contributes most, followed by climatic variation, age structure fluctuations and interactions between density and climate. We then simplify the density-dependent, stochastic, age-structured demographic model and derive a new phenomenological time series which captures the dynamics better than previously selected functions. The simple method we develop has potential to provide substantial insight into the relative contributions of population and individual-level processes to the dynamics of populations in stochastic environments. |
| first_indexed | 2024-03-06T20:01:19Z |
| format | Journal article |
| id | oxford-uuid:276402a4-8956-4f1d-83ff-d5eebb39bcc4 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T20:01:19Z |
| publishDate | 2008 |
| record_format | dspace |
| spelling | oxford-uuid:276402a4-8956-4f1d-83ff-d5eebb39bcc42022-03-26T12:06:41ZEstimating the functional form for the density dependence from life history data.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:276402a4-8956-4f1d-83ff-d5eebb39bcc4EnglishSymplectic Elements at Oxford2008Coulson, TEzard, TPelletier, FTavecchia, GStenseth, NChilds, DPilkington, JPemberton, JKruuk, LClutton-Brock, TCrawley, MTwo contrasting approaches to the analysis of population dynamics are currently popular: demographic approaches where the associations between demographic rates and statistics summarizing the population dynamics are identified; and time series approaches where the associations between population dynamics, population density, and environmental covariates are investigated. In this paper, we develop an approach to combine these methods and apply it to detailed data from Soay sheep (Ovis aries). We examine how density dependence and climate contribute to fluctuations in population size via age- and sex-specific demographic rates, and how fluctuations in demographic structure influence population dynamics. Density dependence contributes most, followed by climatic variation, age structure fluctuations and interactions between density and climate. We then simplify the density-dependent, stochastic, age-structured demographic model and derive a new phenomenological time series which captures the dynamics better than previously selected functions. The simple method we develop has potential to provide substantial insight into the relative contributions of population and individual-level processes to the dynamics of populations in stochastic environments. |
| spellingShingle | Coulson, T Ezard, T Pelletier, F Tavecchia, G Stenseth, N Childs, D Pilkington, J Pemberton, J Kruuk, L Clutton-Brock, T Crawley, M Estimating the functional form for the density dependence from life history data. |
| title | Estimating the functional form for the density dependence from life history data. |
| title_full | Estimating the functional form for the density dependence from life history data. |
| title_fullStr | Estimating the functional form for the density dependence from life history data. |
| title_full_unstemmed | Estimating the functional form for the density dependence from life history data. |
| title_short | Estimating the functional form for the density dependence from life history data. |
| title_sort | estimating the functional form for the density dependence from life history data |
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