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ABSTRACT Identifying the physiological mechanisms by which plants are adapted to drought is critical to predict species responses to climate change. We measured the responses of leaf hydraulic and stomatal conductances (K_leafandg_s, respectively) to dehydration, and their association with anatomy, in seven species of CaliforniaCeanothusgrown in a common garden, including some of the most drought‐tolerant species in the semi‐arid flora. We tested for matching of maximum hydraulic supply and demand and quantified the role of decline ofK_leafin driving stomatal closure. AcrossCeanothusspecies, maximumK_leafandg_swere negatively correlated, and bothK_leafandg_sshowed steep declines with decreasing leaf water potential (i.e., a high sensitivity to dehydration). The leaf water potential at 50% decline ing_swas linked with a low ratio of maximum hydraulic supply to demand (i.e., maximumK_leaf:g_s). This sensitivity ofg_s, combined with low minimum epidermal conductance and water storage, could contribute to prolonged leaf survival under drought. The specialized anatomy of subg.Cerastesincludes trichomous stomatal crypts and pronounced hypodermis, and was associated with higher water use efficiency and water storage. Combining our data with comparative literature of other California species, species of subg. Cerastesshow traits associated with greater drought tolerance and reliance on leaf water storage relative to other California species. In addition to drought resistance mechanisms such as mechanical protection and resistance to embolism, drought avoidance mechanisms such as sensitive stomatal closure could contribute importantly to drought tolerance in dry‐climate adapted species. 

Abstract Plant ecological strategies are shaped by numerous functional traits and their trade‐offs. Trait network analysis enables testing hypotheses for the shifting of trait correlation architecture across communities differing in climate and productivity.We built plant trait networks (PTNs) for 118 species within six communities across an aridity gradient, from forest to semi‐desert across the California Floristic Province, based on 34 leaf and wood functional traits, representing hydraulic and photosynthetic function, structure, economics and size. We developed hypotheses for the association of PTN parameters with climate and ecosystem properties, based on theory for the adaptation of species to low resource/stressful environments versus higher resource availability environments with greater potential niche differentiation. Thus, we hypothesized that across community PTNs, trait network connectivity (i.e., the degree that traits are intercorrelated) and network complexity (i.e., the number of trait modules, and the degree of trait integration among modules) would be lower for communities adapted to arid climates and higher for communities adapted to greater water availability, similarly to trends expected for phylogenetic diversity, functional richness and productivity. Further, within given PTNs, we hypothesized that traits would vary strongly in their network connectivity and that the traits most centrally connected within PTNs would be those with the least across‐species variation.Across communities from more arid to wetter climates, PTN architecture varied from less to more interconnected and complex, in association with functional richness, but PTN architecture was independent of phylogenetic diversity and ecosystem productivity. Within the community PTNs, traits with lower species variation were more interconnected.Synthesis. The responsiveness of PTN architecture to climate highlights how a wide range of traits contributes to physiological and ecological strategies with an architecture that varies among plant communities. Communities in more arid environments show a lower degree of phenotypic integration, consistent with lesser niche differentiation. Our study extends the usefulness of PTNs as an approach to quantify tradeoffs among multiple traits, providing connectivity and complexity parameters as tools that clarify plant environmental adaptation and patterns of trait associations that would influence species distributions, community assembly, and ecosystem resilience in response to climate change. 

Abstract 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. Read the freePlain Language Summaryfor this article on the Journal blog. 

Summary Conifers prevail in the canopies of many terrestrial biomes, holding a great ecological and economic importance globally. Current increases in temperature and aridity are imposing high transpirational demands and resulting in conifer mortality. Therefore, identifying leaf structural determinants of water use efficiency is essential for predicting physiological impacts due to environmental variation.Using synchrotron‐generated microtomography imaging, we extracted leaf volumetric anatomy and stomatal traits in 34 species across conifers with a special focus onPinus, the richest conifer genus.We show that intrinsic water use efficiency (WUE_i) is positively driven by leaf vein volume. Needle‐like leaves ofPinus, as opposed to flat leaves or flattened needles of other genera, showed lower mesophyll porosity, decreasing the relative mesophyll volume. This led to increased ratios of stomatal pore number per mesophyll or intercellular airspace volume, which emerged as powerful explanatory variables, predicting both stomatal conductance and WUE_i.Our results clarify how the three‐dimensional organisation of tissues within the leaf has a direct impact on plant water use and carbon uptake. By identifying a suite of structural traits that influence important physiological functions, our findings can help to understand how conifers may respond to the pressures exerted by climate change.