Using joint species distribution models for evaluating how species‐to‐species associations depend on the environmental context

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A comprehensive evaluation of predictive performance of 33 species distribution models at species and community levels (2019, background): “…that assuming shared responses to the environment can improve predictive performance especially for rare species through “borrowing information from other species” (Guisan et al. 1999, Ovaskainen and Soininen 2011, Hui et al. 2013, Madon et al. 2013, Ovaskainen et al. 2016, Tikhonov et al. 2017).”
Biotic interactions in species distribution modelling: 10 questions to guide interpretation and avoid false conclusions (2018, background): “Spatial latent variable jSDM (Ovaskainen, Roy, et al., 2016; Tikhonov et al., 2017) Spatial structure in latent covariates.”
How to make more out of community data? A conceptual framework and its implementation as models and software. (2017, background): “In the context of HMSC, context dependence of the association matrices can be incorporated by modelling the underlying latent variable structure as a function of environmental covariates (Tikhonov et al. 2017), or more generally as functions of space or time.”