HOW TO CITE TSPACE ITEMSAlways cite the published version, so the author(s) will receive recognition through services that track citation counts, e.g. Scopus. If you need to cite the page number of the TSpace version (original manuscript or accepted manuscript) because you cannot access the published version, then cite the TSpace version in addition to the published version using the permanent URI (handle) found on the record page. Abstract. Species spatial distributions are the result of population demography, behavioral traits, and species interactions in spatially heterogeneous environmental conditions. Hence the composition of species assemblages is an integrative response variable, and its variability can be explained by the complex interplay among several structuring factors. The thorough analysis of spatial variation in species assemblages may help infer processes shaping ecological communities. We suggest that ecological studies would benefit from the combined use of the classical statistical models of community composition data, such as constrained or unconstrained multivariate analyses of site-by-species abundance tables, with rapidly emerging and diversifying methods of spatial pattern analysis. Doing so allows one to deal with spatially explicit ecological models of beta diversity in a biogeographic context through the multiscale analysis of spatial patterns in original species data tables, including spatial characterization of fitted or residual variation from environmental models. We summarize here the recent progress for specifying spatial features through spatial weighting matrices and spatial eigenfunctions in order to define spatially constrained or scale-explicit multivariate analyses. Through a worked example on tropical tree communities, we also show the potential of the overall approach to identify significant residual spatial patterns that could arise from the omission of important unmeasured explanatory variables or processes. REVIEWS

Summary 1.Tests of significance of the individual canonical axes in redundancy analysis allow researchers to determine which of the axes represent variation that can be distinguished from random. Variation along the significant axes can be mapped, used to draw biplots or interpreted through subsequent analyses, whilst the nonsignificant axes may be dropped from further consideration. 2. Three methods have been implemented in computer programs to test the significance of the canonical axes; they are compared in this paper. The simultaneous test of all individual canonical axes, which is appealing because of its simplicity, produced incorrect (highly inflated) levels of type I error for the axes following those corresponding to true relationships in the data, so it is invalid. The 'marginal' testing method implemented in the 'vegan' R package and the 'forward' testing method implemented in the program CANOCO were found to have correct levels of type I error and comparable power. Permutation of the residuals achieved greater power than permutation of the raw data. 3. R functions found in a Supplement to this paper provide the first formal description of the 'marginal' and 'forward' testing methods.

Aim An intensively debated issue in macroecology is whether unicellular organisms show biogeographic patterns different from those of macroorganisms. One aspect of this debate addresses beta diversity, that is, do microbial organisms exhibit distance-decay patterns similar to those of macroorganisms? And if so, is the decay of community similarity caused by spatially limited dispersal or by niche-related factors? We studied the community similarity of stream diatoms, macroinvertebrates and bryophytes across the same set of sites in relation to environmental and geographic distance.Location A geographical gradient of c. 1100 km in Finland. MethodsWe first identified the subset of environmental variables that produced the highest correlation with community similarities for each taxonomic group. Based on these variables, we used partial Mantel tests to separate the independent influences of environmental and geographical distance for distance decay of community similarity, separately for diatoms, bryophytes and macroinvertebrates. Finally, macroinvertebrates were divided into three groups based on their different dispersal categories and a partial Mantel test was used to assess whether each of these groups were differently affected by environmental versus geographic distance, i.e. is dispersal a key factor in tests of niche versus neutral models. ResultsThe level of environmental control was by far the strongest for diatoms; however, all groups were controlled more by environmental factors than by limited dispersal. Macroinvertebrate species with low dispersal ability were significantly related to geographic distance, while more effective dispersers showed no relationship to geography but were instead strongly related to environmental distance. Main conclusionsOur results suggest that patterns between macro-and microorganisms are not fundamentally different, but the level of environmental control varies according to dispersal ability. The relative importance of niche versus dispersal processes is not simply a function of organism size but other traits (e.g. life-history type, dispersal capacity) may obscure this relationship.

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