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Dryad

Data from: Drivers and cascading ecological consequences of Gambusia affinis trait variation

Cite this dataset

Wood, Zachary et al. (2021). Data from: Drivers and cascading ecological consequences of Gambusia affinis trait variation [Dataset]. Dryad. https://doi.org/10.5061/dryad.3n5tb2rjh

Abstract

Phenotypic trait differences among populations can shape ecological outcomes for communities and ecosystems. However, few studies have mechanistically linked heritable and plastic components of trait variation to generalizable processes of ecology, such as trophic cascades. Here we assess morphological and behavioral trait variation in nine populations of common-garden reared western mosquitofish (Gambusia affinis) from three distinct ancestral predator environments (three populations per environment), each reared in the presence and absence of predator cues. We then use a pond mesocosm experiment to examine the ecological consequences of trait variation and density variation. Our results show significant among-population trait variation, but this variation was generally unrelated to ancestral predator environment. When traits did vary congruently with respect to ancestral predator environment, this trait variation was driven by gene-by-environment interactions. Variation in several mosquitofish traits altered the cascading effects of mosquitofish on zooplankton and primary producers, but the effect of any given trait was typically weaker than that of density. We note that the relatively stronger ecological effects of density may mask the effects of traits in some systems. Our example here shows that trait variation can be highly noncongruent with respect to a perceived selective agent, phenotypic change is a product of complex interactions between genes and the environment, and numerous interacting phenotypes generate significant but potentially cryptic cascading ecological change. 

Methods

All methods are available in the associated manuscript.

Usage notes

All metadata are available in 'Wood Metadata.pdf'.

Funding

NSF DEB*, Award: 1457333

NSF DEB, Award: 1457112