Plants can influence the composition of belowground microbiomes using root exudates. These can be poisonous compounds, beneficial mutualistic investments (private resources, i.e. available only for target recipients), or general energy-rich compounds (public resources, i.e. available for every microorganism).
These exudates are costly, and are traded off against investment in growth and reproduction. My results from an ordinary differential equation model indicate that it is a good strategy for the plant to feed the beneficial bacteria, because with the support given by the private resource, beneficial microorganisms can outcompete pathogens, and cover the root surface to protect it from further infection.
The second project examines the evolution and stability of human cooperative investment behavior. I use an agent-based, complex system model combined with evolutionary game theory tools.
Reactive strategies enable agents to assess the return value of their past investments, and decide on further investments accordingly. The unconditional component of an investment strategy determines the investment irrespective of the other agent’s investment. In contrast, the conditional component is based on the payoff gained from the income of the interaction, and the trait determines the slope of the linear function that for higher yields fosters higher investments.
My results indicate that investments can evolve to stable equilibrium levels if reactivity is high. When reactivity is at medium or low levels, however, temporarily increasing and decreasing levels of investments, the investment cycle evolves. The systemic risk associated with such fluctuating levels of investments can be mitigated if investment diversity is high, the interaction network is modularized, and the modules are heterogeneous in supporting investments.
More information
Funding: Evolution and Ecology Program
Nationality: Hungarian
Program: Evolution and Ecology Program and Risk and Resilience
Dates: October 2014 – 2017
PUBLICATIONS
International Institute for Applied Systems Analysis (IIASA)
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