Integrating environmental and spatial processes in ecological community dynamics.
The processes controlling the abundances of species across multiple sites form the cornerstone of modern ecology. In these metacommunities, the relative importance of local environmental and regional spatial processes is currently hotly debated, especially in terms of the validity of neutral model. I collected 158 published data sets with information on community structure, environmental and spatial variables. I showed that approximately 50% of the variation in community composition is explained by both environmental and spatial variables. The majority of the data sets were structured by species-sorting dynamics (SS), followed by a combination of SS and mass-effect dynamics. While neutral processes were the only structuring process in 8% of the collected natural communities, disregarding neutral dispersal processes would result in missing important patterns in 37% of the studied communities. Moreover, metacommunity characteristics such as dispersal type, habitat type and spatial scale predicted part of the detected variation in metacommunity structure.
Modifying the t test for assessing the correlation between two spatial processes
Clifford, Richardson, and Hm they require the estimation of an effective sample size that takes into account the spatial structure of both processes. Clifford et al. developed their method on the basis of an approximation of the variance of the sample correlation coefficient and assessed it by Monte Carlo simulations for lattice and non-lattice networks of moderate to large size. In the present paper, the variance of the sample covariance is computed for a finite number of locations, under the multinormality assumption, and the mathematical derivation of the definition of effective sample size is given. The theoretically expected number of degrees of freedom for the modified t test with renewed modifications is compared with that computed on the basis of equation (2.9) of Clifford et al. (1989). The largest differences are observed for small numbers of locations and high autocorrelation, in particular when the latter is present with opposite sign in the two processes. Basic references that were missing in Clifford et al. (1989) are given and inherent ambiguities are discussed.
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