Effect of Network Structure and Adaptive Foraging on Pollination Services of Species-Rich Plant-Pollinator Communities.

Network science has had a great impact on ecology by providing tools to characterize the structure of species interactions in communities and evaluate the effect of such network structure on community dynamics. This has been particularly the case for the study of plant-pollinator communities, which has experienced a tremendous growth with the adoption of network analyses. Here, I build on such body of research to evaluate how network structure and adaptive foraging of pollinators affect ecosystem services of plant-pollinator communities. Specifically, I quantify-using model simulations-pollen deposition in networks that exhibit structures like the ones of empirical networks (hereafter empirically connected networks) and those with higher connectance and lower nestedness than empirical networks, for scenarios where pollinators are fixed foragers and scenarios where they are adaptive foragers. I found that empirically connected networks with adaptive foraging exhibit the highest pollen deposition rate. Increased network connectance reduces pollen deposition, as increased number of interactions leads to greater conspecific pollen dilution in the absence of other mechanisms such as pollinator floral constancy. High nestedness in moderately connected networks increases the proportion of pollinators visiting only one or two plant species, which are associated with the highest quality visits. Adaptive foraging allows pollinators to quantitatively specialize on specialist plant species, which increases conspecific pollen deposition. This research advances pollination biology by elucidating how population dynamics, consumer-resource interactions (i.e., pollinators foraging on floral rewards), adaptive foraging, and network structure (i.e., nestedness and connectance) affect pollen deposition in a network context.