Reliable local weather predictions are essential for informing indigenous farmers in Ghana about climate change alternatives, as they heavily rely on rain-fed agriculture for their subsistence. The literature highlights numerous examples of how scientific understanding has fallen short in addressing the needs of rural areas over the past century. However, indigenous knowledge has proven invaluable in helping rural farming families adapt to climate shocks and make informed decisions about adaptation strategies. To ensure that indigenous knowledge systems receive the recognition they deserve, there is a pressing need to improve assessment procedures. This study assessed farmers' perspectives on indigenous knowledge of weather forecasting for climate adaptation and evaluated farmers' perceptions regarding climate change in the Tolon district of Ghana. Using a mixed methods approach, the study collected data through questionnaires, interviews and focus group discussions. The findings revealed a range of indigenous indicators used by farmers to forecast weather, including celestial movement (star and moon), emergence of red and black ants, wind movement, flowering and fruit production of some indigenous trees, the behaviour of certain trees (developing tree new leaves of baobab), the croaking of frogs, birds, the appearance of rainbow and lightning. The findings underscore the importance of considering indigenous knowledge network when developing climate change adaptation strategies. Policymakers are urged to educate indigenous communities about the impacts of climate stress and provide support to boost agricultural productivity.
Indigenous indicators adaptation strategies climate change indigenous knowledge systems indigenous farmers Tolon district
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| Primary Language | English |
|---|---|
| Subjects | Ecological Impacts of Climate Change and Ecological Adaptation, Human Impacts of Climate Change and Human Adaptation, Climate Change Impacts and Adaptation (Other) |
| Journal Section | Research Article |
| Authors | |
| Project Number | N/A |
| Early Pub Date | November 18, 2025 |
| Publication Date | December 31, 2025 |
| Submission Date | November 29, 2024 |
| Acceptance Date | January 25, 2025 |
| Published in Issue | Year 2025 Volume: 8 Issue: 4 |