How root-grafted trees form networks: Modeling network dynamics with pyNET

Natural root grafting is a widespread phenomenon in woody plants. While previous studies have focused on the effects of reduced growth and resource exchange at the individual level, we lack an understanding of the collective behavior of groups of grafted trees and the networks they form. Here, we present pyNET, a mechanistic agent-based model designed to explore the emergence of root graft networks. We performed simulation experiments with different scenarios involving water scarcity and different cost-benefit dynamics. Costs denote the resources required to form root grafts, while benefits denote the water redistributed among trees. Our model successfully replicates observed patterns linking structural variables to network characteristics. Specifically, we were able to reproduce observed characteristics such as grafting frequency and mean group size. In particular, we find that while the network structure is naturally strongly influenced by the size of the root system, the time and resources allocated to grafting are also critical factors. pyNET serves as a valuable tool for exploring the formation of root grafting networks under diverse environmental conditions and understanding their impact on resource competition. Our study supports theory development on the subject and hopefully stimulates further empirical studies.