Researchers at the University of Queensland have worked on research projects in the PNG Highlands since 2005. These projects were, and are, applied research to manage soil fertility in sweetpotato-based cropping systems in the Highlands. They were funded by the Australian Centre for International Agricultural Research. Our key collaborator was PNG’s National Agricultural Research Institute. Although the projects were in the field of Soil Science, specifically soil fertility management, our approach has always been multidisciplinary.

The Water Resources Department, Government of Maharashtra, responsible for building infrastructure and delivering water to farmers and other users, has so far created irrigation potential of about 5.3. million hectares and the current utilization is about 76%. About 5000 Water User Associations (WUAs) have been established to manage the water supply within their designated areas. However, the water use efficiency and productivity is adversely impacting the overall water security of the state.

The International Fund for Agricultural Development (IFAD) financed the second Cordillera Highland Agricultural Resource Management Project (CHARMP2), in areas where poverty is most severe among indigenous peoples in the highlands of the Cordillera Region in northern Philippines. The aim is to reduce poverty and improve the livelihoods of indigenous peoples living in farming communities in the mountainous project area. The indigenous peoples consist of many tribes whose main economic activity is agriculture.

The co-creation and sharing of knowledge among different types of actors with complementary expertise is known as the Multi-Actor Approach (MAA). This paper presents how Horizon2020 Thematic-Networks (TNs) deal with the MAA and put forward best practices during the different project phases, based on the results of a desktop study, interviews, surveys and expert workshops. The study shows that not all types of actors are equally involved in TN consortia and participatory activities, meaning TNs might be not sufficiently demand-driven and the uptake of the results is not optimal.