1 Ecoinformatics & Biodiversity, Faculty of Science, Aarhus University, Aarhus University2 Department of Computer Science - Center for Massive Data Algoritmics, Department of Computer Science, Science and Technology, Aarhus University3 UC Irvine4 UC Berkeley5 University of New Mexico6 UC San Diego7 Department of Computer Science - Center for Massive Data Algoritmics, Department of Computer Science, Science and Technology, Aarhus University
Patterns of precipitation are likely to change significantly in the coming century, with important but poorly understood consequences for plant communities. Experimental and correlative studies may provide insight into expected changes, but little research has addressed the degree of concordance between these approaches. We synthesized results from four experimental water addition studies with a correlative analysis of community changes across a large natural precipitation gradient in the United States. We investigated whether community composition, summarized with plant functional traits, responded similarly to increasing precipitation among studies and sites. In field experiments, increased precipitation favored species with small seed size,short leaf life span and high leaf nitrogen (N) concentration. However, with increasing precipitation along the natural gradient, community composition shiftedtowards species with higher mean seed mass, longer leaf life span and lower leaf Nconcentrations. The differences in temporal and spatial scale of experimental manipulations and natural gradients may explain these contrasting results. Our results highlight the complexity of responses to climate change, and suggest that transient dynamics may not reflect long-term shifts in functional diversity and community composition. We propose a model of community change that incorporates these differences between short- and long-term responses to climate change.