BEYOND TAXONOMIC DIVERSITY PATTERNS: HOW DO ALPHA, BETA AND GAMMA COMPONENTS OF BIRD FUNCTIONAL AND PHYLOGENETIC DIVERSITY RESPOND TO ENVIRONMENTAL GRADIENTS ACROSS FRANCE ?
Meynard C.N., Devictor V., Mouillot D., Thuiller W., Jiguet F. and Mouquet N. (2011).
Global Ecology and Biogeograhy, 20, 893-903, doi:10.1111/j.1466-8238.2010.00647.x
Key message :Our aim is to ask the extent to which functional traits and evolutionary backgrounds vary among species in a community or region. We use a spatial partitioning of diversity where gamma diversity is calculated by aggregating information on local communities, alpha diversity corresponds to diversity in one locality, and beta diversity corresponds to the average turnover between localities and the region. Changes in gamma diversity are driven by changes in both alpha and beta diversity. Low levels of human impact generally favour all three facets of regional diversity and heterogeneous landscapes usually harbour higher beta diversity in the three facets of diversity, although functional and phylogenetic turnover show some relationships in the opposite direction. Spatial and environmental factors explain a large percentage of the variation in the three diversity facets (>60%), and this is especially true for phylogenetic diversity. In all cases, spatial structure plays a preponderant role in explaining diversity gradients, suggesting an important role for dispersal limitations in structuring diversity at different spatial scales.Our results generally support the idea that changes in regional diversity are the result of changes in both local and turnover diversity, some environmental conditions such as human development have a great impact on diversity levels, and heterogeneous landscapes tend to have higher diversity levels. Interestingly, differences between diversity facets could potentially ,provide further insights into how large and small scale ecological processes interact at the onset of macroecological patterns.
A. Calculation of alpha, beta and gamma diversity. First, a 50-km circle was defined around each survey plot. This is what we call a 50-km window. Within this window, we randomly selected an additional nine plots. In this manner, all windows contain 10 plots which were used in the calculations of diversity and environmental conditions. B. Partial R2 values resulting from simultaneous autoregressive (SAR) models where diversity is the response variable and environmental conditions are the predictors: (a) gamma diversity as a function of mean environmental conditions; (b) beta diversity as a function of environmental coefficient of variation in environmental conditions.
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