In this project we use tree data structures to model the growth and dynamics of tree leaves attacked by insects using the cellular automata and percolation theory ideas similar to fire and infectious disease spreading models.

Results/Conclusions

We developed a stochastic model of a generic tree where, at each step, probabilistic distributions are used to predict if a particular tree branch is going to break into sub-branches or end with leaves. Once such a tree structure is created, a volume containing leaves is determined and broken into a large number of computational cells. Then the dynamics of the leaves behavior including bug eating, aging, light and weather conditions is first evaluated on the computational cells and then is mapped back onto the tree leaves. The computational results show trends similar to extensive field measurements done by Lowman in different forest canopies.