Facilitating integrated landscape management for sustainable rice production by combining dynamic spatial models with fuzzy cognitive maps

Rice production needs to increase to accommodate the world’s growing demand while at the same time reducing environmental impacts, such as greenhouse-gas emissions and eutrophication. This required advance towards more sustainable agriculture also preserves natural capital and ecosystems services. Simultaneously, the production and processing of agricultural communities must adapt to climate change to safeguard food security and livelihoods. The system’s high level of complexity that is driven by interacting social, economic and environmental factors, calls for an integrated approach to assess and understand its past, current and future states to capitalize on complementarities while minimizing negative trade-offs.