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

B BROOK, Corey Bradshaw

    Research output: Contribution to journalArticleResearchpeer-review

    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 densitydependent 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. � 2006 by the Ecological Society of America.
    Original languageEnglish
    Pages (from-to)1445-1451
    Number of pages7
    JournalEcology
    Volume87
    Issue number6
    Publication statusPublished - 2006

    Fingerprint

    density dependence
    time series analysis
    time series
    hypothesis testing
    weight-of-evidence
    Akaike information criterion
    testing method
    selection methods
    population density
    population dynamics
    statistical analysis
    testing
    ecology

    Cite this

    BROOK, B ; Bradshaw, Corey. / Strength of evidence for density dependence in abundance time series of 1198 species. In: Ecology. 2006 ; Vol. 87, No. 6. pp. 1445-1451.
    @article{efe843766357487b8aebf9201d97ad76,
    title = "Strength of evidence for density dependence in abundance time series of 1198 species",
    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 densitydependent 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. � 2006 by the Ecological Society of America.",
    keywords = "abundance, Akaike information criterion, density dependence, hypothesis testing, time series, article, biological model, ecosystem, genetic selection, growth, development and aging, plant, statistics, Ecosystem, Models, Biological, Plants, Selection (Genetics), Selection, Genetic, Stochastic Processes",
    author = "B BROOK and Corey Bradshaw",
    year = "2006",
    language = "English",
    volume = "87",
    pages = "1445--1451",
    journal = "Ecology",
    issn = "0012-9658",
    publisher = "Ecological Society of America",
    number = "6",

    }

    BROOK, B & Bradshaw, C 2006, 'Strength of evidence for density dependence in abundance time series of 1198 species', Ecology, vol. 87, no. 6, pp. 1445-1451.

    Strength of evidence for density dependence in abundance time series of 1198 species. / BROOK, B; Bradshaw, Corey.

    In: Ecology, Vol. 87, No. 6, 2006, p. 1445-1451.

    Research output: Contribution to journalArticleResearchpeer-review

    TY - JOUR

    T1 - Strength of evidence for density dependence in abundance time series of 1198 species

    AU - BROOK, B

    AU - Bradshaw, Corey

    PY - 2006

    Y1 - 2006

    N2 - 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 densitydependent 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. � 2006 by the Ecological Society of America.

    AB - 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 densitydependent 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. � 2006 by the Ecological Society of America.

    KW - abundance

    KW - Akaike information criterion

    KW - density dependence

    KW - hypothesis testing

    KW - time series

    KW - article

    KW - biological model

    KW - ecosystem

    KW - genetic selection

    KW - growth, development and aging

    KW - plant

    KW - statistics

    KW - Ecosystem

    KW - Models, Biological

    KW - Plants

    KW - Selection (Genetics)

    KW - Selection, Genetic

    KW - Stochastic Processes

    M3 - Article

    VL - 87

    SP - 1445

    EP - 1451

    JO - Ecology

    JF - Ecology

    SN - 0012-9658

    IS - 6

    ER -