ABSTRACT
The disappointing results achieved so far in relation to sustainability goals (e.g., reduction of greenhouse gas emissions, protection of biodiversity or circularization of the economy) flag the necessity to improve the effectiveness of sustainability policies and the models used to inform the process of decision making. When dealing with complex sustainability issues (“wicked problems”), the conventional approach to purposeful modelling (the Cartesian dream of prediction and control) might not be the best-suited approach. Existing quantitative approaches (conventional approaches based on economic narratives) do not allow an integrated analysis of the different factors determining: 1) material standard of living; 2) food, energy, water security; and 3) environmental security because these factors can only be observed across different dimensions and scales of analysis. For this reason, today, relevant sustainability issues can only be analyzed in quantitative terms “one at the time” using nonequivalent models. This is what generates the “silo governance syndrome” – i.e., solving a given problem by setting targets that ignore negative side effects related to other problems. This fact can explain, for example, why many policies dealing with sustainability of agriculture (both in developed and in developing countries) have been so far ineffective and even contradictory with each other. This chapter outlines how such complex systems are analyzed and makes recommendations on how to strengthen this process to improve the decision-making process for the transformation of agriculture.
