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Understanding how environmental adaptations mediate plant and ecosystem responses becomes increasingly important under accelerating global environmental change. Multi-stemmed trees, for example, differ in form and function from single-stemmed trees and may possess physiological advantages that allow for persistence during stressful climatic events such as extended drought. Following the worst drought in Hawaii in a century, we examined patterns of stem abundance and turnover in a Hawaiian lowland dry forest (LDF) and a montane wet forest (MWF) to investigate how multi-stemmed trees might influence site persistence, and how stem abundance and turnover relate to key functional traits. We found stem abundance and multi-stemmed trees to be an important component for climate resilience within the LDF. The LDF had higher relative abundance of multi-stemmed trees, stem abundance, and mean stem abundance compared to a reference MWF. Within the LDF, multi-stemmed trees had higher relative stem abundance (i.e., percent composition of stems to the total number of stems in the LDF) and higher estimated aboveground carbon than single-stemmed trees. Stem abundance varied among species and tree size classes. Stem turnover (i.e., change in stem abundance between five-year censuses) varied among species and tree size classes and species mean stem turnover was correlated with mean species stem abundance per tree. At the plot level, stem abundance per tree is also a predictor of survival, though mortality did not differ between multiple- and single-stemmed trees. Lastly, species with higher mean stem abundance per tree tended to have traits associated with a higher light-saturated photosynthetic rate, suggesting greater productivity in periods with higher water supply. Identifying the traits that allow species and forest communities to persist in dry environments or respond to disturbance is useful for forecasting ecological climate resilience or potential for restoration in tropical dry forests. 

Improved estimation of climate niches is critical, given climate change. Plant adaptation to climate depends on their physiological traits and their distributions, yet traits are rarely used to inform the estimation of species climate niches, and the power of a trait‐based approach has been controversial, given the many ecological factors and methodological issues that may result in decoupling of species' traits from their native climate.

For 107 species across six ecosystems of California, we tested the hypothesis that mechanistic leaf and wood traits can robustly predict the mean of diverse species' climate distributions, when combining methodological improvements from previous studies, including standard trait measurements and sampling plants growing together at few sites. Further, we introduce an approach to quantify species' trait‐climate mismatch.

We demonstrate a strong power to predict species mean climate from traits. As hypothesized, the prediction of species mean climate is stronger (and mismatch lower) when traits are sampled for individuals closer to species' mean climates.

Improved resolution of species' climate niches based on mechanistic traits can importantly inform conservation of vulnerable species under the threat of climatic shifts in upcoming decades.

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