Abstract: The species distribution models (SDMs) simulate and predict the potential distribution of species in geographical space by quantifying the relationships between species distribution and environmental variables, and extrapolating these relationships to unknown landscape units, which makes them important tools in ecology, biogeo-graphy, and conservation biology. Current SDMs mainly take abiotic factors as prediction variables, whereas biotic factors, especially species interactions, are often ignored due to the difficulties in data quantification and modeling. Incorporating species interactions into SDMs is considered as the main challenge of SDMs. We reviewed the influence of species interactions on species distribution simulations, clarified the necessity of incorporating species interactions into SDMs, summarized four main ways to incorporate species interactions into SDMs, analyzed their strengths and limitations, and discussed the future development direction of incorporating species interactions into SDMs. The study showed that incorporating species interaction into SDMs was based on the premise that the spatial scale of species distribution simulation was consistent with that of species interactions, and that the training data should be collected from large environmental heterogeneous space to ensure the diversity of species interactions in heterogeneous habitats. In order to eliminate the influence of multicollinearity on the prediction of SDMs, all abiotic and biotic factors should be fully considered and accurately quantified. Modeling the complex population/community dynamics would be an important development direction of incorporating species interactions into SDMs.

Key words: species interaction, species distribution model, species interaction model, joint species distribution model, species interaction distribution model