Predicting plant species climate preferences on the basis of mechanistic traits

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.Here we provide 4 separate files:1. Legend with complete trait names and units2. Trait data for each sampled individual3. Trait data and climate variables averaged at the species-level4. Trait data and climate variables averaged at the site-levelFunding provided by: La Kretz Center for California Conservation Science*Crossref Funder Registry ID: Award Number: Funding provided by: UCNRS Stunt Ranch Reserve*Crossref Funder Registry ID: Award Number: Funding provided by: Ecological Society of AmericaCrossref Funder Registry ID: http://dx.doi.org/10.13039/100013246Award Number: Funding provided by: Conselho Nacional de Desenvolvimento Científico e TecnológicoCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100003593Award Number: 202813/2014-2Funding provided by: National Science FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000001Award Number: 2017949Funding provided by: National Science FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000001Award Number: 1951244Funding provided by: University of California, Los AngelesCrossref Funder Registry ID: http://dx.doi.org/10.13039/100007185Award Number:To test predictions of species' climate-trait relationships, we sampled single representative ecosystems of widespread types. We selected the most abundant species for sampling at each site according to reserve managers and forest inventories. The species included in this study are taxonomically diverse, representing 31 plant families of mostly woody species, and including many cases of closely related species that occur in contrasting environments. Individual trees were sampled across the landscape and we avoided sampling adjacent individuals of the same species; thus, the microclimate of exact sampling location differs across species and across individuals of the same species. Most species were sampled from a single site, but fifteen of the 107 species were among the most common in two ecosystems (and one species, Eriogonum fasciculatum in three ecosystems), and they were sampled in both locations. For 3–5 individuals of 14 to 26 species per site, we collected a mature, sun-exposed and non-epicormic branch, with no signs of damage and herbivory using pole pruners or a slingshot. Branches were transported to the lab in dark plastic bags with moist paper and rehydrated overnight in a dark saturated atmosphere before harvesting current-year grown, fully expanded leaves for all subsequent analyses. For compound-leafed species, whole leaves were used