Abstract
Farmers do not often use climate and weather information on a regular basis, as the specific influence of weather parameters on farm-level decision making is not well-known. Agromet advisories are needed for local farming systems. Effective agrometeorological advisory systems, need tailored agricultural weather forecasts, and two-way communication. Transdisciplinary teams together with farmers can co-develop early warning Agromet advisory systems to address farmers' needs. Three examples of Agromet advisories are discussed- CAPES in Zambia, Science Field Shops in Indonesia, and the AgriCloud mobile App in South Africa. Community Agrometeorological Participatory Extension Service (CAPES) began in Monze, Zambia to communicate seasonal climate forecasts to farmers through researchers and extension interactions. Participatory groups collected spatial and temporal data about local farming systems to highlight opportunities. Communication methods used were local radio, farmers' days, trials, with farm visits. CAPES resulted in lifelong learning about climate and co-development of tailored Agromet advisories to improve climate resilience. In Science Field Shops (SFS) groups of Indonesian farmers meet experts regularly to exchange information about climate and farming activities. Farmers measure rainfall and observe their agroecological systems each day. At monthly meetings, the seasonal forecasts are discussed using dialogue-discussion methods. Agrometeorological learning is trans-disciplinary through interaction between anthropologists, agrometeorologist, and extension personnel. SFS includes eight climate services that empower farmers to address challenges and sustain their productivity. AgriCloud is an online weather-based agricultural advisory system enriching weather forecasts with agricultural information and local knowledge. Real-time overviews and warnings are tailored to farmer's needs. AgriCloud provides farmers, extension staff, and advisors daily updated weather-related farm-specific advice in 11 South African official languages. AgriCloud is available as an android mobile App, or API to use via a platform. These examples illustrate the use of weather forecasting together with tailored forecasts and communication systems to deliver Agromet advisories, showing different aspects of the incorporation of local knowledge in co-developing advisories for the farmers. In the future, various combinations can be used around the world when co-developing with the farmers.
Highlights
Effective practical local early warning agromet advisories can be developed using participatory approaches in order to incorporate local knowledge to farmers on a routine basis
Scientists from different disciplines were involved in all three examples, showing the importance of transdisciplinary teams and how they complement each other by bringing different skills to the team
This is especially apparent in Science Field Shops (SFS) where anthropologists were the initiator and team leaders, as during their exchanges with the farmers, they realized the need for expertise about climate change and adaptations
Summary
Effective practical local early warning agromet advisories can be developed using participatory approaches in order to incorporate local knowledge to farmers on a routine basis. SFS include eight basic climate services (Winarto et al, 2018), namely daily rainfall measurements; agroecological observations in their fields; analysis/evaluation of yields amongst farmers from different locations, across different seasons, and different years; monthly rainfall scenario outlook discussions; problem-solving by farmer experimentation in their fields to develop strategies to sustain yields; exchange of scientific “new” knowledge; organization of SFS groups and storage and digital analysis of farmers’ rainfall data (Winarto et al, 2019, 2020) Each of these is vital to the understanding of the farming system and the interactions with the environment as well as the local climate and weather phenomena. Farmers are making their own agromet advisories based on their own experience and information from international climate centers Farmers use their rainfall observations (represented in simple hand-drawn diagrammes) together with the scientific interpretation of seasonal forecasts to develop tailor-made climate services related to local farming systems. That would not include the essential element of the farmers decision making processes
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