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Predicting species' range limits from functional traits for the tree flora of North America. | LitMetric

Predicting species' range limits from functional traits for the tree flora of North America.

Proc Natl Acad Sci U S A

AG Botany and Functional Biodiversity Research Group, Institute of Biology, University of Leipzig, 04103 Leipzig, Germany; and German Center for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, 04013 Leipzig, Germany.

Published: September 2014

Using functional traits to explain species' range limits is a promising approach in functional biogeography. It replaces the idiosyncrasy of species-specific climate ranges with a generic trait-based predictive framework. In addition, it has the potential to shed light on specific filter mechanisms creating large-scale vegetation patterns. However, its application to a continental flora, spanning large climate gradients, has been hampered by a lack of trait data. Here, we explore whether five key plant functional traits (seed mass, wood density, specific leaf area (SLA), maximum height, and longevity of a tree)--indicative of life history, mechanical, and physiological adaptations--explain the climate ranges of 250 North American tree species distributed from the boreal to the subtropics. Although the relationship between traits and the median climate across a species range is weak, quantile regressions revealed strong effects on range limits. Wood density and seed mass were strongly related to the lower but not upper temperature range limits of species. Maximum height affects the species range limits in both dry and humid climates, whereas SLA and longevity do not show clear relationships. These results allow the definition and delineation of climatic "no-go areas" for North American tree species based on key traits. As some of these key traits serve as important parameters in recent vegetation models, the implementation of trait-based climatic constraints has the potential to predict both range shifts and ecosystem consequences on a more functional basis. Moreover, for future trait-based vegetation models our results provide a benchmark for model evaluation.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4183311PMC
http://dx.doi.org/10.1073/pnas.1300673111DOI Listing

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