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Small variance in growth rates in annual plants has large effects on genetic drift
Author(s) -
Espeland Erin K.,
O'Farrell Michael R.
Publication year - 2010
Publication title -
american journal of botany
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.218
H-Index - 151
eISSN - 1537-2197
pISSN - 0002-9122
DOI - 10.3732/ajb.1000006
Subject(s) - biology , genetic drift , autocorrelation , inbreeding , competition (biology) , abiotic component , growth rate , ecology , effective population size , natural selection , population , intraspecific competition , stabilizing selection , statistics , genetic variation , demography , mathematics , biochemistry , geometry , sociology , gene
• Premise of the Study: Effective population size ( N e ) is a critical index of the evolutionary capacity of populations. Low N e indicates that standing genetic diversity is susceptible to loss via stochastic processes (and inbreeding) and is, therefore, unavailable for natural selection to act upon. Reported N e in plant populations is often quite low. What biological and ecological factors might produce such low N e • Methods: We conducted a simulation model to test the effect of randomly assigned and autocorrelated growth rates of annual plants on plant‐size distributions at the end of the growing season. Because plant size is directly correlated with reproductive output in annual plants, variation in plant size reflects variation in reproduction, and thus our modeled size distributions can be used to estimate N e . • Key Results: Randomly assigned growth rates had a negligble effect on N e / N . Autocorrelated growth rates decreased N e / N as the length of the growing season increased. This was the case even when the variance in growth rates was as low as 0.1% of the mean. • Conclusions: While intrinsic plant biology can affect the degree of growth autocorrelation, ecological factors such as competition, herbivory, and abiotic stress can increase or decrease levels of growth autocorrelation. Ecological factors that increase growth autocorrelation can have significant effects on genetic drift within populations.