NDLI: A Method for Detecting Positive Growth Autocorrelation without Marking Individuals

Content Provider	PubMed Central
Author	Brooks, Mollie E. Mccoy, Michael W. Bolker, Benjamin M.
Editor	Dalby, Andrew R.
Copyright Year	2013
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 statistical power due to the inability to identify individuals. We show how to accommodate nonlinear growth trajectories and test the effects of size-dependent mortality on our method's accuracy. The method can detect significant growth autocorrelation at moderate levels of autocorrelation with moderate-sized cohorts (for example, statistical power of 80% to detect growth autocorrelation ρ 2 = 0.5 in a cohort of 100 individuals measured on 16 occasions). We present a case study of growth in the red-eyed tree frog. Better quantification of the processes driving size variation will help ecologists improve predictions of population dynamics. This work will help researchers to detect growth autocorrelation in cases where marking is logistically infeasible or causes unacceptable decreases in the fitness of marked individuals.
Related Links	http://dx.doi.org/10.1371/journal.pone.0076389
Starting Page	76389
File Format	PDF
ISSN	19326203
e-ISSN	19326203
Journal	PLoS ONE
Issue Number	10
Volume Number	8
Language	English
Publisher	Public Library of Science
Publisher Date	2013-10-01
Access Restriction	Open
Rights Holder	Public Library of Science
Subject Keyword	Biochemistry, Genetics and Molecular Biology(all) Agricultural and Biological Sciences(all) Medicine(all) Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary

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