Knowledge exchange to guide decision support tool development for Chinese agriculture – an example of social science meeting geoscience for sustainable agriculture

Critical Zone Observatories (CZO) have the potential to offer a holistic, social-ecological systems approach to understanding of agricultural systems. They allow us to consider the inter-linkages of nutrients, water and human interactions across the landscape, to help society better achieve UN sustainable development goals. Here we report on how two different work packages of a multi-partner (UK and China), multi-university project are working together, at the geoscience – social science interface. Social science surveys were used to gain an understanding of knowledge exchange pathways, learning preferences and social dynamics in three regions of China that can usefully inform the design of decision support tools (DSTs). These DSTs are being developed to provide information to users about the consequences of their actions (e.g. effects of fertiliser on water quality) and to identify where changed practice may alleviate degradation of ecosystem services.

 

 

Our work assesses these tools through a Critical Zone (CZ) perspective focusing on farmers, agricultural policy makers (village to county scale) and farm advisors in Chinese agriculture. We explored the best pathways to deliver applicable DSTs in three different Chinese rural areas. We undertook: 1) surveys of Chinese (n = 27) and British (n = 16) scientists researching CZ science in China and 2) surveys and interviews of local stakeholders (592 farmers; 77 officials). This identified how knowledge was exchanged between researchers and users, and what are the preferred and effective ways of knowledge sharing. These data were used to develop a conceptual model of the science-policy-practice interface; identifying different routes for DST knowledge exchange. Alongside this, we carried out a systematic review of over 400 existing DSTs worldwide to identify tools that were: a) suitable for use in China (e.g. lower data requirements); b) had environmental protection goals and c) provided outputs which provide specific support to stakeholders in decisions. Few tools reviewed explained their approaches to KE or engagement with users or assessed the environmental impacts of agricultural practice. Our analysis highlights the need for more interdisciplinary DSTs that are co-produced with users and include both environmental consequences and financial incentives alongside parameters such as crop yield.