Density regulation amplifies environmentally induced population fluctuations

Background Density-dependent regulation is ubiquitous in population dynamics, and its potential interaction with environmental stochasticity complicates the characterization of the random component of population dynamics. Yet, this issue has not received attention commensurate with its relevance for...

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Main Authors: Crispin M. Mutshinda, Aditya Mishra, Zoe V. Finkel, Andrew J. Irwin
Format: Article
Language:English
Published: PeerJ Inc. 2023-02-01
Series:PeerJ
Subjects:
Online Access:https://peerj.com/articles/14701.pdf
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author Crispin M. Mutshinda
Aditya Mishra
Zoe V. Finkel
Andrew J. Irwin
author_facet Crispin M. Mutshinda
Aditya Mishra
Zoe V. Finkel
Andrew J. Irwin
author_sort Crispin M. Mutshinda
collection DOAJ
description Background Density-dependent regulation is ubiquitous in population dynamics, and its potential interaction with environmental stochasticity complicates the characterization of the random component of population dynamics. Yet, this issue has not received attention commensurate with its relevance for descriptive and predictive modeling of population dynamics. Here we use a Bayesian modeling approach to investigate the contribution of density regulation to population variability in stochastic environments. Methods We analytically derive a formula linking the stationary variance of population abundance/density under Gompertz regulation in a stochastic environment with constant variance to the environmental variance and the strength of density feedback, to investigate whether and how density regulation affects the stationary variance. We examine through simulations whether the relationship between stationary variance and density regulation inferred analytically under the Gompertz model carries over to the Ricker model, widely used in population dynamics modeling. Results The analytical decomposition of the stationary variance under stochastic Gompertz dynamics implies higher variability for strongly regulated populations. Simulation results demonstrate that the pattern of increasing population variability with increasing density feedback found under the Gompertz model holds for the Ricker model as well, and is expected to be a general phenomenon with stochastic population models. We also analytically established and empirically validated that the square of the autoregressive parameter of the Gompertz model in AR(1) form represents the proportion of stationary variance due to density dependence. Discussion Our results suggest that neither environmental stochasticity nor density regulation can alone explain the patterns of population variability in stochastic environments, as these two components of temporal variation interact, with a tendency for density regulation to amplify the magnitude of environmentally induced population fluctuations. This finding has far-reaching implications for population viability. It implies that intense intra-specific resource competition increases the risk of environment-driven population collapse at high density, making opportune harvesting a sensible practice for improving the resistance of managed populations such as fish stocks to environmental perturbations. The separation of density-dependent and density-independent processes will help improve population dynamics modeling, while providing a basis for evaluating the relative importance of these two categories of processes that remains a topic of long-standing controversy among ecologists.
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spelling doaj.art-192a1caff12244989d42a36a960f189c2023-12-03T10:00:12ZengPeerJ Inc.PeerJ2167-83592023-02-0111e1470110.7717/peerj.14701Density regulation amplifies environmentally induced population fluctuationsCrispin M. Mutshinda0Aditya Mishra1Zoe V. Finkel2Andrew J. Irwin3Department of Mathematics & Statistics, Dalhousie University, Halifax, NS, CanadaFlatiron Institute, New York, NY, USADepartment of Oceanography, Dalhousie University, Halifax, NS, CanadaDepartment of Mathematics & Statistics, Dalhousie University, Halifax, NS, CanadaBackground Density-dependent regulation is ubiquitous in population dynamics, and its potential interaction with environmental stochasticity complicates the characterization of the random component of population dynamics. Yet, this issue has not received attention commensurate with its relevance for descriptive and predictive modeling of population dynamics. Here we use a Bayesian modeling approach to investigate the contribution of density regulation to population variability in stochastic environments. Methods We analytically derive a formula linking the stationary variance of population abundance/density under Gompertz regulation in a stochastic environment with constant variance to the environmental variance and the strength of density feedback, to investigate whether and how density regulation affects the stationary variance. We examine through simulations whether the relationship between stationary variance and density regulation inferred analytically under the Gompertz model carries over to the Ricker model, widely used in population dynamics modeling. Results The analytical decomposition of the stationary variance under stochastic Gompertz dynamics implies higher variability for strongly regulated populations. Simulation results demonstrate that the pattern of increasing population variability with increasing density feedback found under the Gompertz model holds for the Ricker model as well, and is expected to be a general phenomenon with stochastic population models. We also analytically established and empirically validated that the square of the autoregressive parameter of the Gompertz model in AR(1) form represents the proportion of stationary variance due to density dependence. Discussion Our results suggest that neither environmental stochasticity nor density regulation can alone explain the patterns of population variability in stochastic environments, as these two components of temporal variation interact, with a tendency for density regulation to amplify the magnitude of environmentally induced population fluctuations. This finding has far-reaching implications for population viability. It implies that intense intra-specific resource competition increases the risk of environment-driven population collapse at high density, making opportune harvesting a sensible practice for improving the resistance of managed populations such as fish stocks to environmental perturbations. The separation of density-dependent and density-independent processes will help improve population dynamics modeling, while providing a basis for evaluating the relative importance of these two categories of processes that remains a topic of long-standing controversy among ecologists.https://peerj.com/articles/14701.pdfAutoregressive processCompensatory dynamicsEnvironmental stochasticityDensity dependence
spellingShingle Crispin M. Mutshinda
Aditya Mishra
Zoe V. Finkel
Andrew J. Irwin
Density regulation amplifies environmentally induced population fluctuations
PeerJ
Autoregressive process
Compensatory dynamics
Environmental stochasticity
Density dependence
title Density regulation amplifies environmentally induced population fluctuations
title_full Density regulation amplifies environmentally induced population fluctuations
title_fullStr Density regulation amplifies environmentally induced population fluctuations
title_full_unstemmed Density regulation amplifies environmentally induced population fluctuations
title_short Density regulation amplifies environmentally induced population fluctuations
title_sort density regulation amplifies environmentally induced population fluctuations
topic Autoregressive process
Compensatory dynamics
Environmental stochasticity
Density dependence
url https://peerj.com/articles/14701.pdf
work_keys_str_mv AT crispinmmutshinda densityregulationamplifiesenvironmentallyinducedpopulationfluctuations
AT adityamishra densityregulationamplifiesenvironmentallyinducedpopulationfluctuations
AT zoevfinkel densityregulationamplifiesenvironmentallyinducedpopulationfluctuations
AT andrewjirwin densityregulationamplifiesenvironmentallyinducedpopulationfluctuations