Increasing modularity when downscaling networks from species to individuals

Abstract

Downscaling networks from species to individuals is a useful approach to incorporate inter‐individual variation and to investigate whether topology of species‐based networks results from processes acting at the scale of individuals, such as foraging behaviour. Here, we analyzed pollen‐transport networks at two scales, i.e. pollinator species–plant species (sp–sp) and pollinator individuals–plant species (i–sp), and assessed whether modularity – a prevalent pattern in most pollination networks – is consistent across both scales. To test this we use three different algorithms developed for the calculation of modularity (unipartite, bipartite and weighted bipartite modularity) and compare the results obtained. Downscaling networks revealed a higher modular structure in i–sp networks than in sp–sp networks, regardless of the modular metric used. Using a null model approach, we show that modularity at the individual scale is originated by the existence of a high heterogeneity and specialization in the partition of pollen resources among conspecific individuals, a pattern which obviously cannot be observed at the species level. Modules in i–sp networks consisted of individuals sometimes neither taxonomically nor functionally related, but sharing common pollen resources at different moments of the flowering season. Interestingly, conspecific individuals may belong to different modules. Both plant and insect phenologies were important drivers of the modularity detected in individual‐based networks, even determining the topological roles of nodes in the networks. A temporal turnover of modules was identified, i.e. modules of individuals assembled and disassembled over time as species modify their foraging choices throughout the flowering season adjusting to ecological conditions. Downscaling from species to individual‐based networks is a promising approach to study the interplay among structural patterns and processes at different, but interdependent organizational levels.