Complex trait‒environment relationships underlie the structure of forest plant communities

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 Regression-based approaches (CWMr) assume that local communities exhibit centred at single optimum value and do not covary meaningfully. Evidence suggests the shape of trait‒abundance can vary widely gradients—reflecting complex interactions—and usually interrelated. We used model accounts for these factors explore in herbaceous forest Wisconsin (USA). built generalized linear mixed (GLMM) analyse how abundances 185 distributed among 189 forested sites response four functional (vegetative height—VH, leaf size—LS, mass per area—LMA carbon content), six variables describing overstorey, soil climate conditions, their interactions. The GLMM allowed us assess nature relative strength resulting 24 also compared results between CWMr conclusions differ approaches. identified five significant together explain ~40% variation across sites. Temperature appeared as key driver, with warmer more seasonal favouring taller plants. Soil texture temperature seasonality affected LS LMA; effects on LMA were nonlinear, declining Although assumed CWMr, only some under certain had liberally (13) but failed detect seasonality‒LMA relationship GLMM. Synthesis. represents methodologically approach than it reduced set still capable accounting responses understorey herbs It separate appear important forests, useful insights supporting broader application understand