The project aims to identify optimal policies to protect ecological systems that provide ecological services to nature and humanity when these systems are potentially vulnerable to abrupt and significant changes. The project also aims to integrate the concept of Value of Information (Vol) in this framework of dynamic decision making. Hence this research project helps to solve inter-temporal ecological and environmental problems in the presence of abrupt shifts within a framework of uncertainty and will, in this way, contribute to ensuring a better and more sustainable use of the most valuable natural resources.
Figure: Creative Commons attribution on the image "Gene Drive inheritence". (Mariuswalter, 2017)
Synthetic gene drive is a genetic engineering technology which biases the chance of inheritance of the desired gene in a population. Hence drive genes can increase in frequency even when they have fitness disadvantage. This technology has numerous potential advantages (human health, agriculture and threatened species conservation) but also comes with great risks and challenges (confinement, societal impact, ecological and health impact). The focus of my work is to assess the risks of synthetic gene-drive systems in terms of spread and resistance evolution using mathematical modelling and simulations.
Drugs that specifically target pathogens have been one of the major medical breakthroughs of the last century, but their success is continually under threat due to the evolution of drug resistant strains. In Kosakowski et al., 2018, we studied the competition between antibiotic producing bacteria, non-producers (or cheaters), and sensitive cells in a 2D lattice. We examine the conditions under which multiple bacterial strains can coexist and how those conditions are affected by the evolution of antibiotic production and underlying interaction structure of the population.
Corruption in the form of bribery pose a serious challenge to good governance in many countries. This project focuses on understanding the conditions under which harassment bribery can be reduced by using the framework of evolutionary game-theory. Our analysis reveals how the interplay between network topology, connectivity and strategy update rules can affect population level outcomes in such asymmetric games on inter-dependent networks.