Munkemuller T., de Bello F., Meynard C.N., Gravel D., Lavergne S., Mouillot D., Mouquet N. and Thuiller W. (2011).

Ecography, 34, 001-013, doi:10.1111/j.1600-0587.2011.07259.x

Key message :The aim of our study is to determine with simulated data which facets of biodiversity, if any, may unravel the processes driving its spatial patterns, and to provide practical considerations about the combination of diversity indices that would produce significant and congruent signals when using null models. Our study is based on simulated species assemblages that emerge under various landscape structures in a spatially explicit individual-based model with contrasting, predefined assembly processes. We focus on four assembly processes (species-sorting, mass effect, neutral dynamics and competition colonization trade-off) and investigate the emerging species distributions with varied diversity indices (alpha, beta and gamma) measured at different spatial scales and for different diversity facets (taxonomic, functional and phylogenetic). We find that 1) the four assembly processes result in distinct spatial distributions of species under any landscape structure, 2) a broad range of diversity indices allows distinguishing between communities driven by different assembly processes, 3) null models provide congruent results only for a small fraction of diversity indices and 4) only a combination of these diversity indices allows identifying the correct assembly processes. Our study supports the inference of assembly processes from patterns of diversity only when different types of indices are combined. It highlights the need to combine phylogenetic, functional and taxonomic diversity indices at multiple spatial scales to effectively infer underlying assembly processes from diversity patterns by illustrating how combination of different indices might help disentangling the complex question of coexistence.

Schematic overview of our modelling approach: the combinations of different landscapes (i.e. spatial structure of the environment) and different species pools (i.e. trait distribution and phylogenetic relatedness) are the input for the spatially explicit and individual based simulation model. This input influences the outcome of the modelled processes in the simulation model and ultimately spatial patterns of species distributions (step 1). Based on datasets sampled from both the input information (landscapes and species-pools) and the emerging spatial distribution patterns we calculated a range of diversity indices and investigated the power of these indices to discriminate between spatial distribution patterns of species (step 2) and, in combination with null model tests, to identify non-random community assembly processes (step 3).

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OTHER TOPICS: Aesthetics of Biodiversity, Biodiversity & Ecosystem Functioning, Biogeography, Macroecology & Ecophylogenetics, Experimental Evolution, Functional Biogeography, Functional Rarity, Metacommunities, Metaecosystems, Reviews and Synthesis, Trophic Biogeography & Metaweb