DOI: 10.5061/dryad.4qrfj6qb0
title: Complex trait‒environment relationships underlie the structure of forest plant communities

description: Traits differentially adapt plant species to particular conditions
 generating compositional shifts along environmental gradients. As a
 result, community-scale trait values show concomitant shifts, termed
 trait‒environment relationships. Trait‒environment relationships are often
 assessed by evaluating community-weighted mean (CWM) traits observed along
 environmental gradients. Regression-based approaches (CWMr) assume that
 local communities exhibit traits centered at a single optimum value and
 that traits do not covary meaningfully. Evidence suggests that the shape
 of trait‒abundance relationships can vary widely along environmental
 gradients—reflecting complex interactions—and traits are usually
 interrelated. We used a model that accounts for these factors to explore
 trait‒environment relationships in herbaceous forest plant communities in
 Wisconsin (USA). We built a generalized linear mixed model (GLMM)
 to analyze how abundances of 185 species distributed among 189 forested
 sites vary in response to four functional traits (vegetative height-VH,
 leaf size-LS, leaf mass per area-LMA, and leaf carbon content), six
 environmental variables describing overstory, soil, and climate
 conditions, and their interactions. The GLMM allowed us to assess the
 nature and relative strength of the resulting 24 trait‒environment
 relationships. We also compared results between GLMM and CWMr to explore
 how conclusions differ between approaches. The GLMM identified
 five significant trait‒environment relationships that together explain
 ~40% of variation in species abundances across sites. Temperature appeared
 as a key environmental driver, with warmer and more seasonal sites
 favoring taller plants. Soil texture and temperature seasonality affected
 LS and LMA; seasonality effects on LS and LMA were nonlinear, declining at
 more seasonal sites. Though often assumed for CWMr, only some traits under
 certain conditions had centered optimum trait‒abundance relationships.
 CWMr more liberally identified (13) trait‒environment relationships as
 significant but failed to detect the temperature-seasonality‒LMA
 relationship identified by the GLMM. Synthesis. Although GLMM
 represents a more methodologically complex approach than CWMr, it
 identified a reduced set of trait‒environment relationships still capable
 of accounting for the responses of forest understory herbs to
 environmental gradients. It also identified separate effects of mean and
 seasonal temperature on LMA that appear important in these forests,
 generating useful insights and supporting broader application of GLMM
 approach to understand trait‒environment relationships.
description: Please see main text and Suplementary Materials and Methods
 (Appendix S1).
description: The data consist of 35,965 cases wherein each case reflects the
 frequency of a species at a site (the number of 1 m2 quadrats out of the
 total number of quadrats sampled at each site). Each case also includes
 functional trait data for that species and environmental data for that
 site.