Investigating ontogenetic space with developmental cell lineages

Development plays a significant role in biological evolution, and is likely to prove an effective route to overcoming the limitations of direct genotype-phenotype mappings in artificial evolution. Nonetheless, the relationship between development and evolution is complex and still poorly understood. One question of current interest concerns the possible role that developmental processes may play in orienting evolution. A first step towards exploring this issue from a theoretical perspective is understanding the structure of ontogenetic space: the space of possible genotype-phenotype mappings. Using a quantitative model of development that enables ontogenetic space to be characterised in terms of complexity, we show that ontogenetic landscapes have a characteristic structure that varies with genotypic properties.

Simulating spray deposition on plant canopies within a wind tunnel

Three-dimensional computer modelling techniques are being used to develop a probabilistic model of turbulence-related spray transport around various plant architectures to investigate the influence of plant architectures and crop geometry on the sprayapplication process. Plant architecture models that utilise a set of growth rules expressed in the Lindenmayer systems (L-systems) formalism have been developed and programmed using L-studio software. Modules have been added to simulate the movement ofdroplets through the air and deposition on the plant canopy. Deposition of spray on an artificial plant structure was measured in the wind tunnel at the University of Queensland, Gatton campus and the results compared to the model simulation. Further trials are planned to measure the deposition of spray droplets on various crop and weed species and the results from these trials will be used to refine and validate the combined spray and plant architecture model.

Dynamics of gene expression in an artificial genome

Complex systems techniques provide a powerful tool to study the emergent properties of networks of interacting genes. In this study we extract models of genetic regulatory networks from an artificial genome, represented by a sequence of nucleotides, and analyse how variations in the connectivity and degree of inhibition of the extracted networks affects the resulting classes of behaviours. For low connectivity systems were found to be very stable. Only with higher connectivity was a significant occurrence of chaos found. Most interestingly, the peak in occurrence of chaos occurs perched on the edge of a phase transition in the occurrence of attractors.