Recent attempts to examine the biological processes responsible for the general characteristics of mutualistic networks focus on two types of explanations: nonmatching biological attributes of species that prevent the occurrence of certain interactions (“forbidden links”), arising from trait complementarity in mutualist networks (as compared to barriers to exploitation in antagonistic ones), and random interactions among individuals that are proportional to their abundances in the observed community (“neutrality hypothesis”). We explored the consequences that simple linkage rules based on the first two hypotheses (complementarity of traits versus barriers to exploitation) had on the topology of plant–pollination networks. Independent of the linkage rules used, the inclusion of a small set of traits (two to four) sufficed to account for the complex topological patterns observed in real-world networks. Optimal performance was achieved by a “mixed model” that combined rules that link plants and pollinators whose trait ranges overlap (“complementarity models”) and rules that link pollinators to flowers whose traits are below a pollinator-specific barrier value (“barrier models”). Deterrence of floral parasites (barrier model) is therefore at least as important as increasing pollination efficiency (complementarity model) in the evolutionary shaping of plant–pollinator networks.
Whether they are antagonistic—as between predator and prey—or beneficial—as between pollinator and flower, interactions among all the key species in an ecosystem follow regular patterns. Connectivity (the proportion of possible interactions that are actually realised), for instance, decreases with network size. The “forbidden links” hypothesis proposes that connectivity decreases because interactions are prevented by a mismatch of biological attributes between certain species. Mismatches could arise from the evolution of complementary traits in mutualistic relationships (such as insects preferring to pollinate only flowers of a certain colour) or of traits that prevent exploitation in antagonistic ones (such as a plant growing a long corolla so that insects without a long proboscis cannot reach the nectar reward). We explored the consequences of simple linkage rules based on these two variants on the topology of plant–pollination networks. When compared to data for 37 real plant–pollinator networks, we show that a “mixed” model that combines simple rules from both “complementarity” and “barrier” models best explains the pattern of interactions. This implies, for example, that deterring floral parasites is at least as important as increasing pollination efficiency in the evolution of plant–pollinator networks. Our work emphasises the value of explaining the underlying ecological and evolutionary mechanisms generating such patterns.
The topology of plant-pollinator networks can be explained by relatively simple rules incorporating both "complementarity" and "barrier" traits, thus providing insights into the possible evolutionary and ecological processes driving the pattern.