A method for detecting positive growth autocorrelation without marking individuals.

ABSTRACT: In most ecological studies, within-group variation is a nuisance that obscures patterns of interest and reduces statistical power. However, patterns of within-group variability often contain information about ecological processes. In particular, such patterns can be used to detect positive growth autocorrelation (consistent variation in growth rates among individuals in a cohort across time), even in samples of unmarked individuals. Previous methods for detecting autocorrelated growth required data from marked individuals. We propose a method that requires only estimates of within-cohort variance through time, using maximum likelihood methods to obtain point estimates and confidence intervals of the correlation parameter. We test our method on simulated data sets and determine the loss in

SUBMITTER: Brooks ME 

PROVIDER: S-EPMC3810375 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature