Structured Demographic Buffering: A Framework to Explore the Environmental Components and Demographic Mechanisms Underlying Demographic Buffering

Environmental stochasticity is a key determinant of population viability. Decades of work exploring how environmental stochasticity influences population dynamics have highlighted the ability of some natural populations to limit the negative effects of environmental stochasticity, one of the strategies being demographic buffering. Whilst various methods exist to quantify demographic buffering, we still do not know which environmental components and demographic mechanisms are most responsible for the demographic buffering observed in natural populations. Here, we introduce a framework to explore the relative impacts of environmental components (i.e., temporal autocorrelation and variance in demographic rates) on demographic buffering and the demographic mechanisms that underly these impacts (i.e., population structure and demographic rates). Using integral projection models, we show how demographic buffering is more sensitive to environmental variance relative to environmental autocorrelation. In addition, environmental autocorrelation and variance impact demographic buffering through distinct demographic mechanisms-i.e., population structure and demographic rates, respectively.

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Publication Details

Journal
Ecology Letters
Published
2025-02-01
DOI
https://doi.org/10.1111/ele.70066
Citations
6
Primary Topic
Urban, Neighborhood, and Segregation Studies
Type
article
Field-Weighted Citation Impact
25.21

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article

Structured Demographic Buffering: A Framework to Explore the Environmental Components and Demographic Mechanisms Underlying Demographic Buffering

Anna C. Vinton, Samuel J. L. Gascoigne, Aldo Compagnoni, Ulrich K. Steiner et al.
6 citations
Ecology Letters
Urban, Neighborhood, and Segregation Studies
25.21
article

Structured Demographic Buffering: A Framework to Explore the Environmental Components and Demographic Mechanisms Underlying Demographic Buffering

Anna C. Vinton, Samuel J. L. Gascoigne, Aldo Compagnoni, Ulrich K. Steiner, Shripad Tuljapurkar, Harman Jaggi, Roberto Salguero‐Gómez, Maja Kajin, Irem Sepil, Gabriel Silva Santos
article en
6 citations

Abstract

Environmental stochasticity is a key determinant of population viability. Decades of work exploring how environmental stochasticity influences population dynamics have highlighted the ability of some natural populations to limit the negative effects of environmental stochasticity, one of the strategies being demographic buffering. Whilst various methods exist to quantify demographic buffering, we still do not know which environmental components and demographic mechanisms are most responsible for the demographic buffering observed in natural populations. Here, we introduce a framework to explore the relative impacts of environmental components (i.e., temporal autocorrelation and variance in demographic rates) on demographic buffering and the demographic mechanisms that underly these impacts (i.e., population structure and demographic rates). Using integral projection models, we show how demographic buffering is more sensitive to environmental variance relative to environmental autocorrelation. In addition, environmental autocorrelation and variance impact demographic buffering through distinct demographic mechanisms-i.e., population structure and demographic rates, respectively.

Ecology LettersVol. 28(2)
University of Ljubljana (SI), University of Aberdeen (GB), German Centre for Integrative Biodiversity Research (DE), University of Oxford (GB), Martin Luther University Halle-Wittenberg (DE), Freie Universität Berlin (DE), Lanzhou University (CN), Stanford University (US)
National Science Foundation, Wellcome Trust, Royal Society, Sight Research UK, University of Oxford, Deutsche Forschungsgemeinschaft, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Directorate for Biological Sciences, Biotechnology and Biological Sciences Research Council, Natural Environment Research Council
Openalex Percentile: Top 1%
Urban, Neighborhood, and Segregation Studies
25.21
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