Analytical thresholds reveal mechanisms of cross-scale dynamics in adaptive mutualistic networks

Abstract

Cross-scale integration remains a persistent challenge in ecology. Mechanistic network models can advance this integration by linking individual- and population-level processes with emergent community structure and dynamics, but their complexity often leaves their implications understood primarily through computer simulations. Here, I analyze a consumer-resource model of plant--pollinator interactions with adaptive foraging to show how simulation-discovered patterns can be translated into analytical threshold relationships. The model connects individual-level foraging, floral rewards, visitation, and pollination quality to population dynamics, competition for shared resources and services, and emergent community and network structure. Analytical decomposition identifies threshold conditions for population persistence, finite-density establishment, sustained pollination services, and community-level effects of network structure mediated by adaptive foraging. These relationships clarify how rewards, visitation, pollination quality, recruitment, and network architecture jointly constrain community outcomes. By connecting simulation-motivated patterns to analytical threshold conditions, this work shows how mechanistically detailed models can produce general insight into the biological processes and constraints that shape ecological communities.