Local and regional processes drive distance decay in structure in a spatial multilayer plant-pollinator network

Abstract

Understanding spatial variation in species distribution and community structure is at the core of biogeography and community ecology. Nevertheless, the effect of distance on metacommunity structure remains little studied. We use plant-pollinator network data from the Canary Islands to examine how plant-pollinator community structure changes across geographical distances at a regional scale and disentangle its underlying local and regional processes. We represent plant-pollinator communities as a metacommunity using a multilayer network. We quantified multilayer modularity to test for distance decay in structure across space. In multilayer modularity, the same species can belong to different modules in different layers, and modules can span layers. This enabled quantifying how similarity in module composition varied with distance between locations. We developed four null models, each controlling for a separate component of the multilayer network, to disentangle the role of species turnover, interaction rewiring, and local factors in driving distance decay in module similarity. We found a pattern of distance decay in structure, indicating that locations tended to share fewer modules with increasing distance. Species turnover (but not interaction rewiring) was the primary regional process triggering distance decay in structure. Local factors also played an essential role in determining the structure similarity of communities at a regional scale. These local differences could, in turn, influence regional processes occurring between locations. Finally, the extent to which species shared partners across locations did not affect distance decay in structure. Our work highlights the interplay between local and regional processes underlying biogeographic patterns. Our methodology provides a general framework for linking communities in space and testing different hypotheses regarding the factors generating spatial structure.