The first project focuses on soil above and belowground interactions, and considers plants and microorganisms inhabiting the root system. Plants have evolved multiple means of influencing the composition of belowground microbiomes, including various biochemical components released in the form of exudates by the roots. Root exudates can be composed of poisonous allelochemical compounds, beneficial mutualistic investments (private resources, i.e. available only for target recipients), and general energy-rich compounds (public resources, i.e. available for every microorganism).
These exudates are costly for the plant, and are traded off against other investments, most importantly investment in above and belowground growth and reproduction. The best strategy of the plant depends both on the composition of the belowground microbiome, and on the strategies of aboveground competitors.
Plant traits can determine investments in growth and reproduction, root exudates, and the ratio of different components (private vs. public resources) in the latter. Our first results from an ordinary differential equation model indicate that it is a good strategy for the plant to feed the beneficial bacteria, as with the support given by the private resource provided by the plant, beneficial microorganisms can outcompete pathogens, and can cover the root surface to protect it from further infection. Further investigations will be carried out to determine if such strategy will remain advantageous in a plant community context as well.
The second project focuses on the problem of the evolution and stability of human cooperative behavior. Human socioeconomic systems are characterized by interactions of interdependent agents, such as individuals, firms, banks, or countries. We employ an agent-based, complex system model combined with tools of evolutionary game theory. In particular, we study the evolution and stability of iterative, reciprocal investment behavior with reactive investment strategies.
Reactive strategies enable agents to assess the return value of their past investments, and decide on further investments accordingly. The investment strategy of an agent is characterized by two traits: unconditional investment and conditional investment. The unconditional component determines the investment offered by the agent at the initiation of the interaction, and in the subsequent rounds, irrespective of the other agent’s investment. In contrast, the conditional investment 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. The level of reactivity determines the ratio of these two components in the overall investment of an agent.
Our results indicate that investments can evolve to stable equilibrium levels if reactivity is high, meaning that the conditional investment component dominates the overall investment of an agent. 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 when investment diversity is high, the interaction network is modularized, and the modules are heterogeneous in supporting investments. We demonstrate how optimal levels of reactivity, diversity, modularity, and heterogeneity are helpful in terms of stabilizing investment levels while minimizing systemic risk.
Last edited: 02 March 2016
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