Beyond the aggregated paradigm: phenology and structure in mutualistic networks

Abstract

Abstract Mutualistic interactions, where species interact to obtain mutual benefits, constitute an essential component of natural ecosystems. The use of ecological networks to represent the species and their ecological interactions allows the study of structural and dynamic patterns common to different ecosystems. However, by neglecting the temporal dimension of mutualistic communities, relevant insights into the organization and functioning of natural ecosystems can be lost. Therefore, it is crucial to incorporate empirical phenology -the cycles of species' activity within a season- to fully understand the impact of temporal variability on network architecture. In this paper, by using empirical datasets together with a set of synthetic models, we propose a framework to characterize the phenology of plant-pollinator communities and assess how it reshapes their portrayal as a network. Analyses of three empirical cases reveal that non-trivial information is missed when representing the network of interactions as static, which leads to overestimating the value of fundamental structural features. We discuss the implications of our findings for mutualistic relationships and intra-guild competition for common resources. We show that recorded interactions and species' activity duration are pivotal factors in accurately replicating observed patterns within mutualistic communities. Furthermore, our exploration of synthetic models underscores the system-specific character of the mechanisms driving phenology, increasing our understanding of the complexities of natural ecosystems.