Literature DB >> 25730852

Evidence and implications of higher-order scaling in the environmental variation of animal population growth.

Jake M Ferguson1, José M Ponciano2.   

Abstract

Environmental stochasticity is an important concept in population dynamics, providing a quantitative model of the extrinsic fluctuations driving population abundances. It is typically formulated as a stochastic perturbation to the maximum reproductive rate, leading to a population variance that scales quadratically with abundance. However, environmental fluctuations may also drive changes in the strength of density dependence. Very few studies have examined the consequences of this alternative model formulation while even fewer have tested which model better describes fluctuations in animal populations. Here we use data from the Global Population Dynamics Database to determine the statistical support for this alternative environmental variance model in 165 animal populations and test whether these models can capture known population-environment interactions in two well-studied ungulates. Our results suggest that variation in the density dependence is common and leads to a higher-order scaling of the population variance. This scaling will often stabilize populations although dynamics may also be destabilized under certain conditions. We conclude that higher-order environmental variation is a potentially ubiquitous and consequential property of animal populations. Our results suggest that extinction risk estimates may often be overestimated when not properly taking into account how environmental fluctuations affect population parameters.

Keywords:  environmental variance; population viability analysis; stochastic model; time series; variance scaling

Mesh:

Year:  2015        PMID: 25730852      PMCID: PMC4352823          DOI: 10.1073/pnas.1416538112

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  14 in total

1.  Age, sex, density, winter weather, and population crashes in Soay sheep.

Authors:  T Coulson; E A Catchpole; S D Albon; B J Morgan; J M Pemberton; T H Clutton-Brock; M J Crawley; B T Grenfell
Journal:  Science       Date:  2001-05-25       Impact factor: 47.728

2.  A population's stationary distribution and chance of extinction in a stochastic environment with remarks on the theory of species packing.

Authors:  M W Feldman; J Roughgarden
Journal:  Theor Popul Biol       Date:  1975-04       Impact factor: 1.570

3.  Overcompensation and population cycles in an ungulate.

Authors:  B T Grenfell; O F Price; S D Albon; T H Clutton-Brock
Journal:  Nature       Date:  1992-02-27       Impact factor: 49.962

4.  Modelling non-additive and nonlinear signals from climatic noise in ecological time series: Soay sheep as an example.

Authors:  Nils Chr Stenseth; Kung-Sik Chan; Giacomo Tavecchia; Tim Coulson; Atle Mysterud; Tim Clutton-Brock; Bryan Grenfell
Journal:  Proc Biol Sci       Date:  2004-10-07       Impact factor: 5.349

5.  On the regulation of populations of mammals, birds, fish, and insects.

Authors:  Richard M Sibly; Daniel Barker; Michael C Denham; Jim Hone; Mark Pagel
Journal:  Science       Date:  2005-07-22       Impact factor: 47.728

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

Authors:  Barry W Brook; Corey J A Bradshaw
Journal:  Ecology       Date:  2006-06       Impact factor: 5.499

7.  Deciphering the effects of climate on animal populations: diagnostic analysis provides new interpretation of Soay sheep dynamics.

Authors:  Alan Berryman; Mauricio Lima
Journal:  Am Nat       Date:  2006-10-12       Impact factor: 3.926

8.  The effect of random variations of different types on population growth.

Authors:  R Levins
Journal:  Proc Natl Acad Sci U S A       Date:  1969-04       Impact factor: 11.205

9.  Extinction risk depends strongly on factors contributing to stochasticity.

Authors:  Brett A Melbourne; Alan Hastings
Journal:  Nature       Date:  2008-07-03       Impact factor: 49.962

10.  Predicting the process of extinction in experimental microcosms and accounting for interspecific interactions in single-species time series.

Authors:  Jake M Ferguson; José M Ponciano
Journal:  Ecol Lett       Date:  2013-12-05       Impact factor: 9.492

View more
  6 in total

1.  A parametric interpretation of Bayesian Nonparametric Inference from Gene Genealogies: Linking ecological, population genetics and evolutionary processes.

Authors:  José Miguel Ponciano
Journal:  Theor Popul Biol       Date:  2017-11-22       Impact factor: 1.570

2.  An updated perspective on the role of environmental autocorrelation in animal populations.

Authors:  Jake M Ferguson; Felipe Carvalho; Oscar Murillo-García; Mark L Taper; José M Ponciano
Journal:  Theor Ecol       Date:  2015-08-30       Impact factor: 1.432

3.  Ecological change points: The strength of density dependence and the loss of history.

Authors:  José M Ponciano; Mark L Taper; Brian Dennis
Journal:  Theor Popul Biol       Date:  2018-04-26       Impact factor: 1.570

4.  Detecting and modelling delayed density-dependence in abundance time series of a small mammal (Didelphis aurita).

Authors:  E Brigatti; M V Vieira; M Kajin; P J A L Almeida; M A de Menezes; R Cerqueira
Journal:  Sci Rep       Date:  2016-02-11       Impact factor: 4.379

5.  Evolutionary tracking is determined by differential selection on demographic rates and density dependence.

Authors:  Anna Christina Vinton; David Alan Vasseur
Journal:  Ecol Evol       Date:  2020-06-01       Impact factor: 2.912

6.  Elk population dynamics when carrying capacities vary within and among herds.

Authors:  Lisa J Koetke; Adam Duarte; Floyd W Weckerly
Journal:  Sci Rep       Date:  2020-09-29       Impact factor: 4.379

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.