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ESTIMATING THE FUNCTIONAL FORM FOR THE DENSITY DEPENDENCE FROM LIFE HISTORY DATA
Author(s) -
Coulson T.,
Ezard T. H. G.,
Pelletier F.,
Tavecchia G.,
Stenseth N. C.,
Childs D. Z.,
Pilkington J. G.,
Pemberton J. M.,
Kruuk L. E. B.,
Clutton-Brock T. H.,
Crawley M. J.
Publication year - 2008
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.1890/07-1099.1
Subject(s) - density dependence , population , population density , covariate , vital rates , ecology , population size , climate change , population growth , population model , age structure , series (stratigraphy) , statistical physics , statistics , econometrics , biology , demography , mathematics , physics , paleontology , sociology
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.

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