Models of joint distribution of species with benthic communitiesfrom the small rivers of the Volga basin as a case study
Considered are the theoretical and practical aspects of building joint species distribution models, which are a modern tool for the analysis of ecological communities. It is shown that in the case when observational data are quantitative indicators of population density (in particular, the number of species in hydrobiological studies), it is inappropriate to use the MaxEnt method and others based on the concept of “pseudo-absence” points. Contemporary multidimensional models of the joint distribution of communities should include a set of parameters that assess the impact of the following groups of fixed and random factors on the species occurrence: (a) covariates and categorical variables describing environmental conditions and characteristics of biotopes, (b) main indicators characterizing each species, and phylogenetic structure of communities, (c) functions of spatial autocorrelation of data at observation points, (d) residual (i.e., not caused by external factors) associativity of species. The analysis of published data and the practical examples of implementation showed that the mentioned requirements, in general, are satisfied by the methodological platform and R-package HMSC (Hierarchical Modelling of Species Communities), on the basis of which multidimensional hierarchical generalized linear models with mixed parameters, estimated by Bayesian procedure, are constructed. The main concepts and blocks of the HMSC platform are described and the results of models construction based on the authors’ data – long-term hydrobiological studies of benthic communities in 132 small and medium-sized rivers in the Middle and Lower Volga basin – are discussed. The parameters of a set of one-dimensional candidate models for the abundance distribution of the subfamily Prodiamesinae (Diptera, Chironomidae) are analyzed and a forecast map of its range within the region is built. To illustrate the multidimensional case, a model of the joint spatial distribution of 31 species of chironomids is constructed and its coefficients are analyzed. A residual correlation graph of statistically significant interspecies interactions has been built. The conclusion is made that the HMSC method and software package can be effectively used to solve fundamental problems of communities ecology: how the areas of individual populations, the structure of their communities and the nature of interspecific interactions depend on environmental conditions, as well as to predict future trends of these processes in response to global changes.