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Strength of evidence for density dependence in abundance time series of 1198 species

Population limitation is a fundamental tenet of ecology, but the relative roles of exogenous and endogenous mechanisms remain unquantified for most species. Here we used multi-model inference (MMI), a form of model averaging, based on information theory (Akaike's Information Criterion) to evalu...

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Published in:Ecology (Durham) 2006-06, Vol.87 (6), p.1445-1451
Main Authors: Brook, Barry W., Bradshaw, Corey J. A.
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description Population limitation is a fundamental tenet of ecology, but the relative roles of exogenous and endogenous mechanisms remain unquantified for most species. Here we used multi-model inference (MMI), a form of model averaging, based on information theory (Akaike's Information Criterion) to evaluate the relative strength of evidence for density-dependent and density-independent population dynamical models in long-term abundance time series of 1198 species. We also compared the MMI results to more classic methods for detecting density dependence: Neyman-Pearson hypothesis-testing and best-model selection using the Bayesian Information Criterion or cross-validation. Using MMI on our large database, we show that density dependence is a pervasive feature of population dynamics (median MMI support for density dependence = 74.7-92.2%), and that this holds across widely different taxa. The weight of evidence for density dependence varied among species but increased consistently with the number of generations monitored. Best-model selection methods yielded similar results to MMI (a density-dependent model was favored in 66.2-93.9% of species time series), while the hypothesis-testing methods detected density dependence less frequently (32.6-49.8%). There were no obvious differences in the prevalence of density dependence across major taxonomic groups under any of the statistical methods used. These results underscore the value of using multiple modes of analysis to quantify the relative empirical support for a set of working hypotheses that encompass a range of realistic population dynamical behaviors.
doi_str_mv 10.1890/0012-9658(2006)87[1445:SOEFDD]2.0.CO;2
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A.</creatorcontrib><title>Strength of evidence for density dependence in abundance time series of 1198 species</title><title>Ecology (Durham)</title><addtitle>Ecology</addtitle><description>Population limitation is a fundamental tenet of ecology, but the relative roles of exogenous and endogenous mechanisms remain unquantified for most species. Here we used multi-model inference (MMI), a form of model averaging, based on information theory (Akaike's Information Criterion) to evaluate the relative strength of evidence for density-dependent and density-independent population dynamical models in long-term abundance time series of 1198 species. We also compared the MMI results to more classic methods for detecting density dependence: Neyman-Pearson hypothesis-testing and best-model selection using the Bayesian Information Criterion or cross-validation. 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A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Strength of evidence for density dependence in abundance time series of 1198 species</atitle><jtitle>Ecology (Durham)</jtitle><addtitle>Ecology</addtitle><date>2006-06</date><risdate>2006</risdate><volume>87</volume><issue>6</issue><spage>1445</spage><epage>1451</epage><pages>1445-1451</pages><issn>0012-9658</issn><eissn>1939-9170</eissn><coden>ECGYAQ</coden><abstract>Population limitation is a fundamental tenet of ecology, but the relative roles of exogenous and endogenous mechanisms remain unquantified for most species. Here we used multi-model inference (MMI), a form of model averaging, based on information theory (Akaike's Information Criterion) to evaluate the relative strength of evidence for density-dependent and density-independent population dynamical models in long-term abundance time series of 1198 species. 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subjects Akaike information criterion
Animal and plant ecology
Animal populations
Animal, plant and microbial ecology
Biodiversity
Biological and medical sciences
Biological taxonomies
community ecology
Demecology
Density
density dependence
Dependence
Ecological modeling
Ecosystem
endogenous population dynamics
Feedback
Fundamental and applied biological sciences. Psychology
General aspects
Models, Biological
multi-model inference
negative feedback
Plant Development
Population density
Population dynamics
Population ecology
population regulation
Sampling errors
Selection, Genetic
statistical analysis
Stochastic Processes
strength of evidence
Time dependence
Time series
time series analysis
Time series models
title Strength of evidence for density dependence in abundance time series of 1198 species
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