Modeling Viability under Uncertainty

Uncertainty occupies a major place in the literature, both when it is being defined and when it is being measured. The mathematical viability framework provides useful concepts to go beyond the probabilistic views of uncertainty that are not able to capture all forms of uncertainty, particularly in the absence of statistical regularities. Bounded-set uncertainty can help to analyze changes in the evolutionary conditions that affect ecological and social systems with probabilistic or nonprobabilistic distributions. This paper introduces uncertainty into a viability model by associating stochastic and bounded-set uncertainty related to sales price as a driver of economic uncertainty. Based on an illustration of agroecosystems, the model identifies decision rules that guarantee viability. The larger the initial crop portfolio for sequential diversification is, the lower the costs to belong to the viability kernels will be, regardless of economic and environmental constraints. The diversification of farming systems transforms their complexity into an advantage against uncertainty, which opens up numerous viability trajectories.