Literature DB >> 14582010

The many growth rates and elasticities of populations in random environments.

Shripad Tuljapurkar1, Carol C Horvitz, John B Pascarella.   

Abstract

Despite considerable interest in the dynamics of populations subject to temporally varying environments, alternate population growth rates and their sensitivities remain incompletely understood. For a Markovian environment, we compare and contrast the meanings of the stochastic growth rate (lambdaS), the growth rate of average population (lambdaM), the growth rate for average transition rates (lambdaA), and the growth rate of an aggregate represented by a megamatrix (shown here to equal lambdaM). We distinguish these growth rates by the averages that define them. We illustrate our results using data on an understory shrub in a hurricane-disturbed landscape, employing a range of hurricane frequencies. We demonstrate important differences among growth rates: lambdaS<lambdaM, but lambdaA can be < or > lambdaM. We show that stochastic elasticity, ESij, and megamatrix elasticity, EMij, describe a complex perturbation of both means and variances of rates by the same proportion. Megamatrix elasticities respond slightly and stochastic elasticities respond strongly to changing the frequency of disturbance in the habitat (in our example, the frequency of hurricanes). The elasticity EAij of lambdaA does not predict changes in the other elasticities. Because ES, although commonly utilized, is difficult to interpret, we introduce elasticities with a more direct interpretation: ESmu for perturbations of means and ESsigma for variances. We argue that a fundamental tool for studying selection pressures in varying environments is the response of growth rate to vital rates in all habitat states.

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Year:  2003        PMID: 14582010     DOI: 10.1086/378648

Source DB:  PubMed          Journal:  Am Nat        ISSN: 0003-0147            Impact factor:   3.926


  27 in total

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4.  Reproduction is adapted to survival characteristics across geographically isolated medfly populations.

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5.  Evolution of simple multicellular life cycles in dynamic environments.

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Journal:  J R Soc Interface       Date:  2019-05-31       Impact factor: 4.118

6.  Fluctuations in lifetime selection in an autocorrelated environment.

Authors:  Olivier Cotto; Luis-Miguel Chevin
Journal:  Theor Popul Biol       Date:  2020-04-08       Impact factor: 1.570

7.  Low demographic variability in wild primate populations: fitness impacts of variation, covariation, and serial correlation in vital rates.

Authors:  William F Morris; Jeanne Altmann; Diane K Brockman; Marina Cords; Linda M Fedigan; Anne E Pusey; Tara S Stoinski; Anne M Bronikowski; Susan C Alberts; Karen B Strier
Journal:  Am Nat       Date:  2010-11-30       Impact factor: 3.926

8.  Contributions of covariance: decomposing the components of stochastic population growth in Cypripedium calceolus.

Authors:  Raziel Davison; Florence Nicolè; Hans Jacquemyn; Shripad Tuljapurkar
Journal:  Am Nat       Date:  2013-01-18       Impact factor: 3.926

9.  A new way to integrate selection when both demography and selection gradients vary over time.

Authors:  Carol C Horvitz; Tim Coulson; Shripad Tuljapurkar; Douglas W Schemske
Journal:  Int J Plant Sci       Date:  2010-11       Impact factor: 1.785

10.  The dynamics of a quantitative trait in an age-structured population living in a variable environment.

Authors:  Tim Coulson; Shripad Tuljapurkar
Journal:  Am Nat       Date:  2008-11       Impact factor: 3.926

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