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Non-linear density dependence in time series is not evidence of non-logistic growth

Non-linear density dependence in time series is not evidence of non-logistic growth
Non-linear density dependence in time series is not evidence of non-logistic growth
Time series of population density are often used to seek deviations from logistic regulation by testing for a non-linear decline in per capita growth rate with density. Here I show that this method fails when the interval between observations is not matched by the timing of density impacts on growth. Time series overestimate instantaneous density impacts at low density and underestimate them at high density. More generally, logistic growth produces a deterministically decelerating decline in per capita growth with density if the interval between measures of population size exceeds any lag in density response. Deceleration arises independently out of stochastic density fluctuations, and under-compensating regulation. These multiple influences lead to the conclusion that sequential density estimates provide insufficient information on their own to reveal the identity of non-logistic growth processes. They can yield estimates of density compensation, however, which may suggest time lags in density dependence. Analysis of an empirical time series illustrates the issues.
beverton-holt, pearl-verhulst, population regulation, theta-logistic, theta¬-ricker
483-489
Doncaster, C. Patrick
0eff2f42-fa0a-4e35-b6ac-475ad3482047
Doncaster, C. Patrick
0eff2f42-fa0a-4e35-b6ac-475ad3482047

Doncaster, C. Patrick (2008) Non-linear density dependence in time series is not evidence of non-logistic growth. Theoretical Population Biology, 73 (4), 483-489. (doi:10.1016/j.tpb.2008.02.003).

Record type: Article

Abstract

Time series of population density are often used to seek deviations from logistic regulation by testing for a non-linear decline in per capita growth rate with density. Here I show that this method fails when the interval between observations is not matched by the timing of density impacts on growth. Time series overestimate instantaneous density impacts at low density and underestimate them at high density. More generally, logistic growth produces a deterministically decelerating decline in per capita growth with density if the interval between measures of population size exceeds any lag in density response. Deceleration arises independently out of stochastic density fluctuations, and under-compensating regulation. These multiple influences lead to the conclusion that sequential density estimates provide insufficient information on their own to reveal the identity of non-logistic growth processes. They can yield estimates of density compensation, however, which may suggest time lags in density dependence. Analysis of an empirical time series illustrates the issues.

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Published date: June 2008
Keywords: beverton-holt, pearl-verhulst, population regulation, theta-logistic, theta¬-ricker

Identifiers

Local EPrints ID: 52024
URI: http://eprints.soton.ac.uk/id/eprint/52024
PURE UUID: 88572137-dd69-4cde-8322-eddf03e80902
ORCID for C. Patrick Doncaster: ORCID iD orcid.org/0000-0001-9406-0693

Catalogue record

Date deposited: 04 Jun 2008
Last modified: 16 Mar 2024 02:49

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