Resolving the effects of functional traits on tree growth rates: The influence of temporal dynamics and divergent strategies by leaf habit

Abstract

Ensuring the sustainability of forest ecosystems requires understanding the mechanisms underlying tree growth and predicting their relative influence across taxa and environments. Functional ecology posits that variation in tree growth is related to individual differences in functional traits, which serve as proxies for resource acquisition and investment strategies. However, studies of trait–growth relationships have produced inconsistent results, likely due to unaccounted factors like interspecific interactions, ontogeny, differing leaf habit strategies, and variation in resource acquisition and allocation. We investigated the utility of key functional traits as predictors of tree height growth rates in common garden experiments in the absence of interspecific interactions. We posit that trait–growth relationships vary with age and between two groups relating to leaf habit: deciduous and evergreen species. Using data from 38 tree species planted in monoculture plots across seven sites of the International Diversity Experiment Network with Trees (IDENT) in North America and Europe, we compiled height growth rates over 9 years post‐germination. We modelled growth using a Bayesian hierarchical generalized linear model incorporating four above‐ground functional traits related to resource acquisition and investment: specific leaf area (SLA), wood density (WD), leaf dry matter content (LDMC) and seed mass (SM). Improvements in predictive power due to the variation of trait effects with age and leaf habit were evaluated via alternative hypothesis‐driven models, using the Expected Log Pointwise Predictive Density (ELPD) as a performance measure. Trait effects on growth varied with age and leaf habit, shifting between positive and negative effects, reflecting changes in resource acquisition and investment strategies. The relationships between traits and growth were strongest during the first three growing seasons for deciduous species and during the seventh to the ninth for evergreen species. Accounting for age and leaf habit substantially improved predictive power. Synthesis. Traits are not consistently associated with tree growth rates but instead reflect dynamic resource acquisition and investment strategies over time and between deciduous and evergreen species. Despite this variability, our findings confirm the utility of functional traits to predict tree growth rates, especially when trait effects are considered to vary with age and leaf habit.