Does trait variation within broadly distributed species mirror patterns across species? A case study in Puerto Rico

摘要

Although populations are phenotypically diverse, the majority of trait-based studies have focused on examining differences among species. The justification for this broadly applied approach is based on the assumption that differences among species are always greater than within species. This is likely true for local communities, but species are often broadly distributed across a wide range of environments and patterns of intraspecific variation might surpass differences among species. Therefore, an appropriate interpretation of the functional diversity requires an assessment of patterns of trait variation across different ecological scales. In this study, we examine and characterize patterns of leaf trait variation for species that are broadly distributed along an elevational gradient. We focus on seven leaf traits that represent a main axis of functional differentiation in plants reflecting the balance between photosynthetic efficiency, display, and stomatal conductance. We evaluated patterns of trait variance across ecological scales (elevation, species, populations, and individuals) and examined trait covariance at both within species and across species levels, along the elevation gradient. Our results show three key patterns: (1) intraspecific leaf trait variation for broadly distributed species is comparable to the interspecific trait variation, (2) the trait variance structure is highly variable across species, and (3) trait coordination between pairs of leaf traits is evident across species along the gradient, but not always within species. Combined, our results show that trait coordination and covariance are highly idiosyncratic across broadly distributed and co-occurring species, indicating that species may achieve similar functional roles even when exhibiting different phenotypes. This result challenges the traditional paradigm of functional ecology that assumes single trait values as optimal solutions for environments. In conclusion, patterns of trait var