An approach to modelling tree root architecture in virtual urban growing conditions

Authors: Justin Miron*, Ryerson University, Geography and Environmental Studies, Andrew A Millward, Ryerson University, Geography and Environmental Studies
Topics: Environmental Science, Quantitative Methods, Urban Geography
Keywords: urban forest, tree root, model, simulation
Session Type: Paper
Scheduler ID: FRI-085-5:20 p.m.
Day: 4/13/2018
Start / End Time: 5:20 PM / 7:00 PM
Room: Proteus, Sheraton, 8th Floor

Tree roots are structurally and functionally important to the survival of trees, and this can be more so in urban environments where underground space for roots is limited. Tree root architecture models can provide a complementary approach to traditional on-site field investigation. Root architecture models are unique in that they can simulate the spatial arrangements of root system structure explicitly, and allow investigators to create hypothetical simulations to test their assumptions about drivers of root growth. The use of root architecture models in the literature is extensive, but their application to tree root systems is less common. This research demonstrates a root architecture model, Rootbox, as a case study in the application of plant architecture models to simulate tree root growth in urban conditions. Model parameterization was based on conformity of root simulations to tree root architecture reported in the literature. The model is deployed in four hypothetical urban soil scenarios, which are representative of planting sites commonly observed in urban settings. Findings indicate that plausible tree root system architectures can be produced by Rootbox, but only after several adaptive changes to both the source code/model design. Custom soil models can integrate with the simulation to represent urban conditions by modifying both the growth direction and elongation of the root architecture, and thus offer greater control over the output architecture. Rootbox offers a flexible method of simulating the architecture of tree root systems; further research is required to optimize the model’s parameters and functions enabling greater user control over output.

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