Multifunctional and diversified agriculture can address diverging pressures and demands by simultaneously enhancing productivity, biodiversity, and the provision of ecosystem services. The use of digital technologies can support this by designing and managing resource-efficient and context-specific agricultural systems. We present the Digital Agricultural Knowledge and Information System (DAKIS) to demonstrate an approach that employs digital technologies to enable decision-making towards diversified and sustainable agriculture. To develop the DAKIS, we specified, together with stakeholders, requirements for a knowledge-based decision-support tool and reviewed the literature to identify limitations in the current generation of tools. The results of the review point towards recurring challenges regarding the consideration of ecosystem services and biodiversity, the capacity to foster communication and cooperation between farmers and other actors, and the ability to link multiple spatiotemporal scales and sustainability levels. To overcome these challenges, the DAKIS provides a digital platform to support farmers' decision-making on land use and management via an integrative spatiotemporally explicit approach that analyses a wide range of data from various sources. The approach integrates remote and in situ sensors, artificial intelligence, modelling, stakeholder-stated demand for biodiversity and ecosystem services, and participatory sustainability impact assessment to address the diverse drivers affecting agricultural land use and management design, including natural and agronomic factors, economic and policy considerations, and socio-cultural preferences and settings. Ultimately, the DAKIS embeds the consideration of ecosystem services, biodiversity, and sustainability into farmers' decision-making and enables learning and progress towards site-adapted small-scale multifunctional and diversified agriculture while simultaneously supporting farmers' objectives and societal demands.

This study is an overview of the effectiveness and institutional challenges of China’s Sloping Land Conversion Program (SLCP). The SLCP is the Chinese government’s largest Payment for Ecosystem Services (PES) program and one of the largest PES programs in the world. From an institutional perspective, the SLCP is particularly interesting because it represents a hybrid governance type that includes both voluntary and hierarchical (top-down) elements rather than traditional command-and-control approach. Our analysis is based on a literature review that encompasses 164 international scientific articles. To identify institutional challenges, we linked the results regarding the effectiveness of the program to its institutional aspects. Our SLCP case study highlights the dependence of the effectiveness of a governmental PES program on the specific regulatory institutional setting and the particular actors involved. Our results show that some institutional challenges undermine the anticipated advantages of PES (local participation) and eventually reshape the program outcomes through implementation process, particularly in cases of hybrid governance structures in which institutional requirements are as important as the design of the specific financial incentives. The collaboration between relevant government actors at different hierarchical levels, and specifically the motivations and interests of the government actors responsible for the implementation on the ground, play crucial roles. The SLCP can be an important milestone in environmental policy in China and the world, if more innovative elements of a theoretically ideal PES—such as local flexibility and self-interest (or at least the acceptance of the service providers supplying the relevant ecosystem services) can be strengthened. The environmental goals can be achieved in combination with greater self-interest of the applicable government actors on all hierarchical levels.

Biodiversity conservation is one of the most important objectives of protected areas. Most biodiversity assessment-related studies use the change in species abundance data to measure the level of biodiversity conservation. Yet for many areas, long-term species data are not available and thus it is necessary to use biodiversity indices to monitor the effect of land use (LU) changes or the impact of protected area establishment. Poyang Lake wetland is one of the most important wintering sites for migratory water birds on the East Asian–Australasian flyway. To protect this habitat, 14 nature reserves were created in the region between 1997 and 2003. This paper aims to assess the effect of nature reserve creation on the status of habitat for overwintering water birds in Poyang Lake wetland by analysing LU and land cover data from 1995, 2005 and 2015. We developed a composite biodiversity index to search for current biodiversity hotspots (conservation priority) in the study area. An integrated approach consisting of the Integrated Valuation of Ecosystem Services and Trade-offs model, GIS, fragment analysis and hotspot analysis was used to realize our objective. Our results showed that the creation of the nature reserve had positive effects on overwintering water bird habitat. However, tremendous changes (such as change of habitat area, quality and fragmentation) within and outside the nature reserve showed that the role of protected area still needs to be further discussed. Moreover, regional synthesis LU management plans such as ecological restoration should be carried out. The results of the habitat assessment also indicate that a comprehensive biodiversity index framework based on net primary productivity, habitat connectivity and habitat quality could be more efficient in assessing biodiversity and defining a reasonable protected area, from data obtain in large scale perspective.

Societal Impact Statement: With the rapid development of modern agriculture and its reliance on high‐yielding and genetically uniform varieties, many traditional agricultural systems are gradually being abandoned. The genetic diversity contained in landraces is crucial for modern eco‐agriculture. An indicator evaluation model combined with machine learning could help to locate and conserve these existing traditional agricultural systems, called agricultural heritage systems (AHS). Here, this method provided the first map of potential areas of Tea‐AHS in China. These results could help policymakers to confirm priorities and rationally allocate conservation resources based on the distribution status and endangerment of AHS. This could also help local people to receive additional support for the transfer of germplasm resources and indigenous knowledge.Summary: Modern agriculture is overly dependent on high‐yielding and genetically uniform varieties, whereas traditional agricultural systems contain a large number of genetically diverse landraces and the indigenous knowledge associated with them. We call traditional agricultural systems that survive to the present‐day agricultural heritage systems (AHS). Under the impact of modernization, AHS are gradually disappearing. Identifying these systems is the first step towards conserving them, but the potential areas of AHS related to agro‐biodiversity are not yet clear. Using Chinese tea as an example, this paper provides the first universal method for identifying potential areas of AHS based on agro‐biodiversity and the first map of potential areas of Tea‐AHS in China. The map is constructed based on the maximum entropy model (Maxent) of tea germplasm resources and related indicator functions and has been validated by existing Tea‐AHS in China. The study identified 54 potential areas of Tea‐AHS. These potential areas are mainly concentrated in the southern region, in 15 provinces, including Anhui, Fujian, Guangdong, Yunnan, Guizhou, Guangxi, Hubei, and Hunan. Mangshi, Qimen County, and Chaisang District are among the high potential areas for Tea‐AHS and are the next priority for exploration and conservation work. We have verified the validity of the proposed method, which can help conserve the germplasm resources and traditional wisdom in the global AHS in a timely manner, and contribute to the development of modern and eco‐agriculture.

While land serves numerous societal functions and contributes to sustainable development, it is often unclear how these functions are affected by political decisions and common drivers of land use change, such as economic development, climate change and demographic change. This study evaluates alternative land use scenarios in reference to a rural region of Inner Mongolia Autonomous Region (China), where various processes and decisions have historically triggered unsustainable development. The scientifically tested “Framework for Participatory Impact Assessment (FoPIA)” method is developed further to address specific features of the case study region, and its function as a knowledge-brokerage (KB) tool is evaluated. Three scenarios are developed and analysed in expert workshops. “Land intensification: Agriculture” and “Land intensification: Mining” scenarios are found to have mainly negative environmental and social effects and positive economic impacts, while the “Environmental conservation and tourism” scenario is found to more positively affect all three sustainability dimensions. Assessments of methodological phases show that the FoPIA primarily serves to establish the KB process and that the framework particularly benefits from early examinations of scientific results by policy makers.