Changes in the environment can directly alter ecosystem composition and processes, and trait-based approaches can in principle improve predictions of forest responses. For over 150 years stomatal traits have been recognized as critical determinants of plant function, but rarely incorporated into prediction of community processes. The tropical forests on Hawaii Island are model systems for ecosystems with low tree species richness and high endemism, and are experiencing strong shifts in mean annual temperature and rainfall. We sampled all woody species from permanent plots in montane wet forest (MWF; 20 species) and lowland dry forest (LDF; 15 species) for measurement of leaf and whole plant traits including stomatal density (SD) and length (SL), and anatomical maximum stomatal conductance (gmax). For the stomatal traits, we tested hypotheses for (1) their variation within and among forests, (2) their linkages with other structural and physiological traits including turgor loss point (Πtlp), leaf mass per area (LMA), leaf dry mass content (LDMC) and wood density (WD), and (3) their potential predictive capacity for diameter growth rates.
Results/Conclusions
Species from the dry and wet forests showed very strong variation in stomatal traits within and between forests. Wet forest species showed 60% higher gmax on average than dry forest species, which arose from either more or larger stomata in wet forest species. The gmax was statistically independent of the other measured functional traits, including Πtlp, LMA, LDMC and WD, signaling a mechanistic independence and a potential influence on plant function distinct from those traits. Species with higher gmax values had higher diameter growth rates on average, corresponding to a potentially major deterministic role of stomatal limitation on species performance and demography within and across tropical forests. Future work will additionally link stomatal trait diversity with nutrient concentrations and species’ growth and mortality responses to climate within and across tropical forests.