Evolution of phenotype-environment associations by genetic responses to selection and phenotypic plasticity in a temporally autocorrelated environment.
Covariation between population-mean phenotypes and environmental variables, sometimes termed a "phenotype-environment association" (PEA), can result from phenotypic plasticity, genetic responses to natural selection, or both. PEAs can potentially provide information on the evolutionary dynamics of a particular set of populations, but this requires a full theoretical characterization of PEAs and their evolution. Here, we derive formulas for the expected PEA in a temporally fluctuating environment for a quantitative trait with a linear reaction norm. We compare several biologically relevant scenarios, including constant versus evolving plasticity, and the situation in which an environment affects both development and selection but at different time periods. We find that PEAs are determined not only by biological factors (e.g., magnitude of plasticity, genetic variation), but also environmental factors, such as the association between the environments of development and of selection, and in some cases the level of temporal autocorrelation. We also describe how a PEA can be used to estimate the relationship between an optimum phenotype and an environmental variable (i.e., the environmental sensitivity of selection), an important parameter for determining the extinction risk of populations experiencing environmental change. We illustrate this ability using published data on the predator-induced morphological responses of tadpoles to predation risk.
Department of Biology, Saint Louis University, St. Louis, Missouri 63103; Department of Biology and Marine Biology, University of North Carolina, Wilmington, North Carolina 28401. michelm@uncw.edu.
Matt J
MJ
Michel
Luis-Miguel
LM
Chevin
Jason H
JH
Knouft
D000818:Animals; D001001:Anura / Q000235:genetics / Q000502:physiology; D017753:Ecosystem; D019143:Evolution, Molecular; D059647:Gene-Environment Interaction; D008957:Models, Genetic; D011235:Predatory Behavior; D012641:Selection, Genetic; D062206:Spatial Analysis
Computer simulation; environmental change; environmental predictability; environmental sensitivity of selection; linear reaction norms; quantitative genetics model