Report No. 2: Collection of policies and database on food, land and water systems in Lao PDR (as 20 December 2022).

Allocation and management of agricultural land is of emergent concern due to land scarcity, diminishing supply of energy and water, and the increasing demand of food globally. To achieve social, economic and environmental goals in a specific agricultural land area, people and society must make decisions subject to the demand and supply of food, energy and water (FEW). Interdependence among these three elements, the Food-Energy-Water Nexus (FEW-N), requires that they be addressed concertedly. Despite global efforts on data, models and techniques, studies navigating the multi-faceted FEW-N space, identifying opportunities for synergistic benefits, and exploring interactions and trade-offs in agricultural land use system are still limited. Taking an experimental station in China as a model system, we present the foundations of a systematic engineering framework and quantitative decision-making tools for the trade-off analysis and optimization of stressed interconnected FEW-N networks. The framework combines data analytics and mixed-integer nonlinear modeling and optimization methods establishing the interdependencies and potentially competing interests among the FEW elements in the system, along with policy, sustainability, and feedback from various stakeholders. A multi-objective optimization strategy is followed for the trade-off analysis empowered by the introduction of composite FEW-N metrics as means to facilitate decision-making and compare alternative process and technological options. We found the framework works effectively to balance multiple objectives and benchmark the competitions for systematic decisions. The optimal solutions tend to promote the food production with reduced consumption of water and energy, and have a robust performance with alternative pathways under different climate scenarios.

The combined effects of pH, water activity (a(w)), oxygen (O2) and carbon dioxide (CO2) levels on growth and sporulation of 10 common food-borne fungi were studied. The use of a multivariate statistical method (PLS) for the analysis of data showed that the fungi could be grouped according to their physiological response to changes in the four tested factors. Carbon dioxide, a(w) and pH were found to be the most significant factors describing differences and similarities among the fungi. Maximal inhibitory effect of elevated levels of CO2 (5-25%) and decreased a(w) (0.99-0.95) varied among the 10 species from 6 to 77% and from 52 to 100%, respectively. Sporulation of the fungi was sensitive to all tested factors. Furthermore, interaction of CO2 and a(w) displayed a significant effect on sporulation. It was shown that different fungal species associated with the same ecosystem responded similarly to changes in the tested factors. Thus, fungi which are not phylogenetically related may be physiologically related or show a common strategy of life.