Interactions between species are influenced by different ecological mechanisms, such as morphological matching, phenological overlap, and species abundances. How these mechanisms explain interaction frequencies across environmental gradients remains poorly understood. Consequently, we also know little about the mechanisms that drive the geographical patterns in network structure, such as complementary specialization and modularity. Here, we use data on morphologies, phenologies and abundances to explain interaction frequencies between hummingbirds and plants at a large geographic scale. For 24 quantitative networks sampled throughout the Americas, we found that the tendency of species to interact with morphologically matching partners contributed to specialized and modular network structures. Morphological matching best explained interaction frequencies in networks found closer to the equator and in areas with low temperature seasonality. When comparing the three ecological mechanisms within networks, we found that both morphological matching and phenological overlap generally outperformed abundances in the explanation of interaction frequencies. Together, these findings provide insights into the ecological mechanisms that underlie geographical patterns in resource specialization. Notably, our results highlight morphological constraints on interactions as a potential explanation for increasing resource specialization towards lower latitudes.

Data consisting of 24 quantitative interaction networks sampled throughout the Americas, in areas mostly or entirely covered with native vegetation (Table ESM2). The networks comprise 106 hummingbird species, 31% of all described hummingbird species in the world according to the IOC World Bird List v.7.3 (ESM3), and 450 plant species belonging to 57 plant families (ESM4, see ESM5a for additional details on sampling).

The abundance of plant species was measured as the number of flowers produced per species in each community throughout the entire sampling period. Flowers were counted in plots or transects estimated regularly throughout the sampling period. The abundance of hummingbirds within sites was measured in the field by counting the number of visual and aural detections of individuals across transects (n=12 networks) or point counts (n=4 networks), or the number of individuals captured by mist-netting (n=8 networks; ESM5a). Because the abundance sampling protocols were not standardized among networks, we treated the data as relative abundance, i.e. for all species we calculate their abundance as the proportion of the total number of individuals within a given community. Still, we note that mist nets may be especially efficient for surveying elusive understory species, such as traplining hummingbirds, whereas transects and point counts may be better at surveying species at higher vegetation strata [34]. We recognize that the caveat inherent in using different sampling schemes across networks may influence the outcome of our analyses. However, as we used relative abundances to model interaction frequencies within networks (not between networks), we believe that the different sampling schemes had a minimal influence on our results.

The phenology of each plant and hummingbird species in each network was determined as the presence-absence of, respectively, open flowers and individuals at each sampling period (usually months). Flower morphology was characterized by the effective corolla length, measured as the distance from the nectary to the corolla opening. The effective corolla length reflects the minimum length of mouthparts required for pollinators to access the nectar legitimately. Hummingbird bill morphology was measured as the length of the exposed culmen from captured hummingbird individuals (see ESM5b further details on sampling).