Agroecosystem Resilience: Utilizing Models to Characterize Uncertainty.

Building resilience of agroecosystems to the uncertainty in the future environment will require we understand and quantify the interactions among the soil, water, environment, plant, livestock, and pest components. The degree of uncertainty is being extended because of the changing climate and more variable weather during the year which will challenge the resilience of current agroecosystems leading to more variation in production and the efficiency of production. Building a platform for resilient agroecosystems requires that we quantify these interactions to determine how systems respond to deviations in the factors directly and indirectly related to productivity. For example, resilience of cropping systems to variable precipitation during the growing season will require either increasing the availability of soil water to the crop by increasing the water storage or selecting crops with greater ability to explore the soil profile or strategically adding water via irrigation. The latter does not create resilience but reduces the uncertainty. The experimental literature has many examples of crop and livestock response to different variables and often there is evidence of how these variables interact to affect productivity. One of the critical pieces to construct a framework for resilience will be to extend this knowledge into future environments to be able to quantify potential responses under uncertainty. The bridge between what we have observed and future scenarios will rely on biophysical models. These biophysical models will have to be linked with climate scenarios in order to provide an evaluation of factors which could be used to increase resilience. When we view agroecosystems the scope must change from an individual crop or animal into the complex system of multiple crops or livestock within a landscape context. To achieve the goals of increasing resilience will require transdisciplinary efforts to across experimental and theoretical boundaries.