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

Marie-Christin Wimmler and Uta Berger

Ecological Modelling, 2024, vol. 498, issue C

Abstract: 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.

Keywords: pyMANGA; Individual-based model; Forest structure; Competition; Facilitation (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304380024003041
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:498:y:2024:i:c:s0304380024003041

DOI: 10.1016/j.ecolmodel.2024.110916

Access Statistics for this article

Ecological Modelling is currently edited by Brian D. Fath

More articles in Ecological Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().