Niche and neutral processes jointly influence species interactions. Predictions of interactions based on these processes assume that they operate similarly across all species. However, species characteristics could systematically create differences in the strength of niche or neutral processes for each interspecific interaction. We used national-level records of plant-frugivore interactions, species traits, biogeographic status (native vs. exotic), phylogenies and species range sizes to test the hypothesis that the strength of niche processes in species interactions changes in predictable ways depending on trophic generalism and biogeographic status of the interacting species. The strength of niche processes (measured as trait matching) decreased when the generalism of the interacting partners increased. Furthermore, the slope of this negative relationship between trait matching and generalism of the interacting partners was steeper (more negative) for interactions between exotic species than those between native species. These results remained significant after accounting for the potential effects of neutral processes (estimated by species range size). These observed changes in the strength of niche processes in generating species interactions, after accounting for effects of neutral processes, could improve predictions of ecological networks from species trait data. Specifically, due to their shorter co-evolutionary history, exotic species tend to interact with native species even when lower trait matching occurs than in interactions among native species. Likewise, interactions between generalist bird species and generalist plant species should be expected to occur despite low trait matching between species, whereas interactions between specialist species involve higher trait matching.

Plant-animal mutualistic networks sustain terrestrial biodiversity and human food security. Global environmental changes threaten these networks, underscoring the urgency for developing a predictive theory on how networks respond to perturbations. Here, I synthesise theoretical advances towards predicting network structure, dynamics, interaction strengths and responses to perturbations. I find that mathematical models incorporating biological mechanisms of mutualistic interactions provide better predictions of network dynamics. Those mechanisms include trait matching, adaptive foraging, and the dynamic consumption and production of both resources and services provided by mutualisms. Models incorporating species traits better predict the potential structure of networks (fundamental niche), while theory based on the dynamics of species abundances, rewards, foraging preferences and reproductive services can predict the extremely dynamic realised structures of networks, and may successfully predict network responses to perturbations. From a theoretician\'s standpoint, model development must more realistically represent empirical data on interaction strengths, population dynamics and how these vary with perturbations from global change. From an empiricist\'s standpoint, theory needs to make specific predictions that can be tested by observation or experiments. Developing models using short-term empirical data allows models to make longer term predictions of community dynamics. As more longer term data become available, rigorous tests of model predictions will improve.