Due to their ability to grow in complex environments, fungi are present in and affect most ecosystems.  Fungi are, among other things, the organisms mainly responsible for wood decay. Furthermore, fungi are the primary decomposers of litter in forests, and wooden material is subject to their attacks. Many efforts have therefore been spent to fully comprehend the processes steering fungal growth and the mathematics behind it in order to build fungal growth models.

Most of these models, however, are unable to fully grasp the dynamics of fungal growth. In addition, in these models, growth is often confined to a lattice, and therefore they cannot realistically represent the irregular nature of fungi.

This work presents a spatially explicit, lattice-free 3D model of fungal growth, one that explicitly accounts for nutrient uptake, translocation, anastomosis, apical growth and irregular branching, as such surpassing the capabilities of previous models on which it is based. Highly versatile, the model is able to produce realistic simulations of different fungal species and to replicate the results of some problem-specific established models.

Furthermore, in order to enable model calibration, a new automated image analysis technique is introduced. This technique combines automated image analysis with graph theory. This results in one of the few objective tools for extracting statistics (such as number of tips or branching angle) from image time series, which are required to validate spatially explicit fungal growth models. Furthermore, this technique permits the comparison of different fungal growth models and can easily be extended to other filamentous organisms.

As such, this work offers a significant advantage which will undoubtedly open new doors for a better understanding of fungal growth and its consequences.