Salinity tolerance in plant species varies widely due to adaptation and acclimation processes at the cellular and whole-plant scales. In mangroves, extreme substrate salinity induces hydraulic failure and ion excess toxicity and reduces growth and survival, thus suggesting a potentially critical role for physiological acclimation to salinity. We tested the hypothesis that osmotic adjustment, a key type of plasticity that mitigates salinity shock, would take place in coordination with declines in whole-plant hydraulic conductance in a common garden experiment using saplings of three mangrove species with different salinity tolerances (Avicennia germinans L., Rhizophora mangle L. and Laguncularia racemosa (L.) C.F. Gaertn., ordered from higher to lower salinity tolerance). For each mangrove species, four salinity treatments (1, 10, 30 and 50 practical salinity units) were established and the time trajectories were determined for leaf osmotic potential (Ψ_s), stomatal conductance (g_s), whole-plant hydraulic conductance (K_plant) and predawn disequilibrium between xylem and substrate water potentials (Ψ_pdd). We expected that, for all three species, salinity increments would result in coordinated declines in Ψ_s, g_s and K_plant, and that the Ψ_pdd would increase with substrate salinity and time of exposure. In concordance with our predictions, reductions in substrate water potential promoted a coordinated decline in Ψ_s, g_s and K_plant, whereas the Ψ_pdd increased substantially during the first 4 days but dissipated after 7 days, indicating a time lag for equilibration after a change in substratum salinity. Our results show that mangroves confront and partially ameliorate acute salinity stress via simultaneous reductions in Ψ_s, g_s and K_plant, thus developing synergistic physiological responses at the cell and whole-plant scales.

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.

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 free Plain Language Summary for this article on the Journal blog.