Predicting plant species climate niches on the basis of mechanistic traits
Camila D. Medeiros, Christian Henry, Santiago Trueba, Ioana G. Anghel, Samantha Dannet Diaz de Leon Guerrero, Alexandria L. Pivovaroff, Leila R. Fletcher, Grace P. John, James A. Lutz, Rodrigo Méndez‐Alonzo, Lawren Sack
Abstract
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 free Plain Language Summary for this article on the Journal blog.