Drivers of the structure of plant–hummingbird interaction networks at multiple temporal scales

CHÁVEZ-GONZÁLEZ, EDGAR; VIZENTIN-BUGONI, JEFERSON; VÁZQUEZ, DIEGO P.; MACGREGOR-FORS, IAN; DÁTTILO, WESLEY; ORTIZ-PULIDO, RAÚL

OECOLOGIA

SPRINGER

Año: 2020 vol. 193 p. 913 - 924

0029-8549

In semi-arid environments, the marked contrast in temperature and precipitation over the year strongly shapes ecological communities. The composition of species and their ecological interactions within a community may vary greatly over time. Although intra-annual variations are often studied, empirical information on how plant?bird relationships are structured within and among years, and how their drivers may change over time are still limited. In this study, we analyzed the temporal dynamics of the structure of plant?hummingbird interaction networks by evaluating changes in species richness, diversity of interactions, modularity, network specialization, nestedness, and β-diversity of interactions throughout four years in a Mexican xeric shrubland landscape. We also evaluated if the relative importance of abundance, phenology, morphology, and nectar sugar content consistently explains the frequency of pairwise interactions between plants and hummingbirds across different years. We found that species richness, diversity of interactions, nestedness, and network specialization did vary within and among years. We also observed that the β-diversity of interactions was high among years and was mostly associated with species turnover (i.e., changes in species composition), with a minor contribution of interaction rewiring (i.e., shifting partner species at different times). Finally, the temporal co-occurrence of hummingbird and plant species among months was the best predictor of the frequency of pairwise interactions, and this pattern was consistent within and among years. Our study underscores the importance of considering the temporal scale to understand how changes in species phenologies, and the resulting temporal co-occurrences influence the structure of interaction networks.