The complexity of nature can only be solved by nature’s intrinsic problem-solving approach. Therefore, the computational modelling of nature requires careful observations of its underlying principles in order that these laws can be abstracted into formulas suitable for the algorithmic configuration. This chapter proposes a novel modelling approach for biodiversity informatics research. The approach is based on the emergence phenomenon for predicting vegetation distribution patterns in a multi-variable ecosystem where Artificial Life-based vegetation grow, compete, adapt, reproduce and conquer plots of landscape in order to survive their generation. The feasibility of the modelling approach presented in this chapter may provide a firm foundation not only for predicting vegetation distribution in a wide variety of landscapes, but could also be extended for studying biodiversity and the loss of animal species for sustainable management of resources.
Gut inference: A computational modelling approach
