Hierarchical Modelling of Species Communities (HMSC) is a model-based approach for analyzing community ecological data (Ovaskainen et a. 2017a). The obligatory data for HMSC-analyses includes a matrix of species occurrences or abundances and a matrix of environmental covariates. Optional data include information about species traits and phylogenetic relationships, and information about the spatiotemporal context of the sampling design. HMSC partitions variation in species occurrences to components that relate to environmental filtering, species interactions, and random processes. HMSC yields inference both at species and community levels. It can be used to generate simulated communities under given environmental conditions, and thus its predictions can be compared to independent validation data, and it can be used for scenario simulations.
The current version of HMSC-R is found from https://github.com/hmsc-r/HMSC. For a description of the software, see https://www.biorxiv.org/content/10.1101/603217v1 and the vignettes 1-5 at https://github.com/hmsc-r/HMSC/tree/master/vignettes.
The old matlab and R versions of HMSC can be found from here.
Ovaskainen, O., Tikhonov, G., Norberg, A., Blanchet, F. G., Duan, L., Dunson, D., Roslin, T. and Abrego, N. 2017a. How to make more out of community data? A conceptual framework and its implementation as models and software. Ecology Letters 20, 561-576
Ovaskainen, O., Tikhonov, G., Dunson, D., Grøtan, V., Engen, S., Sæther, B.-E. and Abrego, N. 2017b. How are species interactions structured in species rich communities? A new method for analysing time-series data. Proceedings of the Royal Society B: Biological Sciences, 284, 20170768.
Tikhonov, G., Abrego, N., Dunson, D. and Ovaskainen, O. 2017. Using joint species distribution models for evaluating how species-to-species associations depend on the environmental context. Methods in Ecology and Evolution 8, 443-452.