A great deal of research is focusing on how plant functional and physiological traits act to determine the communities and range of climates in which species survive and compete. Yet, the power of these approaches has rarely been tested using physiological traits, or across California communities. Our project focuses on testing hypotheses for the traits that distinguish communities and influence climate distributions across California. We report on tests applied to the 30 most abundant woody species from two ecosystems in California, chaparral and desert, to answer two main questions: (1) how do species converge or differ in functional and physiological traits between the two ecosystem types; (2) which traits predict species’ mean climate distribution ranges? We focused on physiological traits that contribute to drought tolerance, potential growth and water use including turgor loss point (πtlp), leaf mass per area (LMA), wood density (WD), leaf nutrient and isotope composition (Nmass and δC13), and traits related to venation and stomata. We obtained climate variables for all species based on observations from herbaria and databases, including mean annual temperature and precipitation (MAT, MAP), and aridity index (AI). We applied tests for trait differences among communities and tested models to find the best trait predictors of mean climate of species’ distribution ranges.
Across communities we detected strong convergence between chaparral and desert in drought-tolerance related traits, such as low πtlp, high wood density and carbon isotope ratio. Traits related to potential growth and water use differed strongly among communities, with desert species showing higher foliar nitrogen concentrations and lower LMA (p<0.05), indicating their adaptation for rapid growth response during periods of high water availability. Across species, traits could predict the mean climate variables in the natural range, especially Nmass and δC13. These results reinforce the role of drought in California in driving trait convergence and diversification across communities, and show how physiological and functional traits can be incorporated in statistical and process-based models that predict or explain species’ natural distributions according to climate.