Blockchain technology, while still challenged with key limitations, is a transformative Information and Communications Technology (ICT) that has changed our notion of trust. Improved efficiencies for agricultural sustainable development has been demonstrated when ICT-enabled farms have access to knowledge banks and other digital resources. UN FAO-recommended ICT e-agricultural infrastructure components are a confluence of ICT and blockchain technology requirements. When ICT e-agricultural systems with blockchain infrastructure are immutable and distributed ledger systems for record management, baseline agricultural environmental data integrity is safeguarded for those who participate in transparent data management. This paper reviewed blockchain-based concepts associated with ICT-based technology. Moreover, a model ICT e-agriculture system with a blockchain infrastructure is proposed for use at the local and regional scale. To determine context specific technical and social requirements of blockchain technology for ICT e-agriculture systems, an evaluation tool is presented. The proposed system and tool can be evaluated and applied to further developments of e-agriculture systems.

Real-time identification of irrigation water pollution sources and pathways (PSP) is crucial to ensure both environmental and food safety. This study uses an integrated framework based on the Internet of Things (IoT) and the blockchain technology that incorporates a directed acyclic graph (DAG)-configured wireless sensor network (WSN), and GIS tools for real-time water pollution source tracing. Water quality sensors were installed at monitoring stations in irrigation channel systems within the study area. Irrigation water quality data were delivered to databases via the WSN and IoT technologies. Blockchain and GIS tools were used to trace pollution at mapped irrigation units and to spatially identify upstream polluted units at irrigation intakes. A Water Quality Analysis Simulation Program (WASP) model was then used to simulate water quality by using backward propagation and identify potential pollution sources. We applied a “backward pollution source tracing” (BPST) process to successfully and rapidly identify electrical conductivity (EC) and copper (Cu²⁺) polluted sources and pathways in upstream irrigation water. With the BPST process, the WASP model effectively simulated EC and Cu²⁺ concentration data to identify likely EC and Cu²⁺ pollution sources. The study framework is the first application of blockchain technology for effective real-time water quality monitoring and rapid multiple PSPs identification. The pollution event data associated with the PSP are immutable.

Assessments may underestimate the annual global water scarcity, driven by seasonal water availability and consumption distribution heterogeneity

Though agricultural landscape biodiversity and ecosystem service (ES) conservation is crucial to sustainability, agricultural land is often underrepresented in ES studies, while cultural ES associated with agricultural land is often limited to aesthetic and tourism recreation value only. This study mapped 7 nonmaterial-intangible cultural ES (NICE) valuations of 34 rural farmers in western Taiwan using the Social Values for Ecosystem Services (SolVES) methodology, to show the effect of farming practices on NICE valuations. However, rather than a direct causal relationship between the environmental characteristics that underpin ES, and respondents’ ES valuations, we found that environmental data is not explanatory enough for causality within a socio-ecological production landscape where one type of land cover type (a micro mosaic of agricultural land cover) predominates. To compensate, we used a place-based approach with Google Maps data to create context-specific data to inform our assessment of NICE valuations. Based on 338 mapped points of 7 NICE valuations distributed among 6 areas within the landscape, we compared 2 groups of farmers and found that farmers’ valuations about their landscape were better understood when accounting for both the landscape’s cultural places and environmental characteristics, rather than environmental characteristics alone. Further, farmers’ experience and knowledge influenced their NICE valuations such that farm areas were found to be sources of multiple NICE benefits demonstrating that farming practices may influence ES valuation in general.

Systematic conservation planning (SCP) deals with a delicate interplay of competing interests and has far-reaching impacts for all stakeholders and systems involved. While SCP has traditionally attempted to conserve ecosystem services that benefit ecological systems, public perceptions of conservation initiatives influence their ultimate feasibility and sustainability. In an attempt to balance ecological integrity, social utility, and urban development, this study develops a framework that applies four popular models to represent these competing factors, including two ecosystem services models—InVEST (Integrated Valuation of Environmental Services and Tradeoffs) for biophysical services (BpS), and SolVES (Social Values for Ecosystem Services) for social values (SV); a land use and land cover (LULC) suitability model; and Zonation for delimiting high priority areas. We also analyze a number of conservation scenarios that consider varying levels of urban development. While BpS are distributed with considerable spatial variability, SV spatially overlap. Approximately 6% of the area was identified as having both high BpS and SV, whereas a further 24.5% of the area was identified as either high BpS low SV or vise-versa. Urban development scenarios affected the conservation area selection drastically. These results indicate tradeoffs and potential synergies between development, SV, and BpS. Our findings suggest that the information provided by the proposed framework can assist in finding solutions to social-ecological planning complexities that serve multiple stakeholders.

Local farmer knowledge is key to sustainable agriculture when organic farming promotes biodiversity conservation. Yet, farmers may not recognize ecosystem service (ES) benefits within their agricultural landscape. Surveys were administered to 113 farmers, and the opinions of 58 respondents toward organic farming were analyzed to identify influential variables when deciding to farm organically. We classified responses by geographic category within a socio-economic production landscape (SEPL), and by social influence categories. With principal component analysis (PCA), a two-scale, four-phased analysis was conducted. Coastal farmers (n = 22) were the most positive towards organic farming trends due to consumer demand. Plains farmers (n = 18) were highly interested in future opportunities for achieving consumer health and food safety objectives. Mountain farmers (n = 18) perceived the most organic transitioning barriers overall, namely irrigation. In all three geographic categories, farming decisions were not primarily related to biodiversity conservation or ES management, but rather to farming community patterns, consumer feedback, and a lack of barriers. Further, farmer opinions toward organic practices were more influenced by their life experiences than by school-taught concepts. Since no previous studies have assessed the knowledge, values, and opinions on organic farming of Taiwan’s west coast farmers from an ES perspective, the proposed approach both identifies farmers’ knowledge and opinions, and verifies a satoyama landscape with PCA results for informed decision making.