Skip to main content
Dryad

Data from: Phenotype-environment matching predicts both positive and negative effects of intraspecific variation

Cite this dataset

Dibble, Christopher; Rudolf, Volker H. W. (2019). Data from: Phenotype-environment matching predicts both positive and negative effects of intraspecific variation [Dataset]. Dryad. https://doi.org/10.5061/dryad.99k4n5s

Abstract

Natural populations can vary considerably in their genotypic and/or phenotypic diversity. Differences in this intraspecific diversity can have important consequences for contemporary ecological dynamics, but the direction and magnitude of these effects appear inconsistent across studies and systems. Here we proposed and tested the hypothesis that context-dependent ecological effects of altering phenotypic variance are predictable and arise from the relationship between a population’s mean phenotype and the local environmental optimum. By factorially manipulating the mean and variance of a key host trait in environments with and without a lethal parasite, we demonstrate that increasing phenotypic variance can have beneficial effects for host populations (e.g. smaller disease epidemics), but only when the population’s initial phenotype was poorly-matched to the local environment. When phenotypes were initially well-suited to environmental conditions, in contrast, greater phenotypic variance led to larger disease epidemics. Significant reductions in individual susceptibility occurred in both contexts over time, but the mechanisms leading to those reductions differed; strong selection was caused by either a ‘suboptimal’ trait mean and insufficient trait variance, or a ‘near-optimal’ trait mean and too much trait variance. Increasing intraspecific variation is clearly not always beneficial for populations, instead producing predictable ecological and evolutionary effects that depend on environmental context and biological interactions.

Usage notes

Funding

National Science Foundation, Award: NSF-DEB 1256860

Location

South East Texas