Naigaga, HellenRukarwa, Runyararo JolynSsekandi, Joseph2026-06-292026-06-292026-04-02Naigaga, H., Rukarwa, R. J., & Ssekandi, J. (2026). Integrating local plant-phenology knowledge into anticipating seasonal weather changes: evidence from smallholder farmers in Uganda’s Mount Elgon region (cross-sectional survey). BMC Environmental Science, 3(1), 11.3004-8710https://dir.muni.ac.ug/handle/20.500.12260/1002This study advances SDG 2 (Zero Hunger) by promoting climate-resilient and sustainable agricultural practices (Target 2.4). It further contributes to SDG 13 (Climate Action) through the integration of indigenous knowledge to enhance community adaptation to climate risks (Target 13.1), and supports SDG 15 (Life on Land) by fostering the sustainable use of land and biodiversity (Target 15.1). The research is consistent with Uganda’s National Development Plan IV, particularly the Agro-Industrialisation Programme and the Natural Resources, Environment, Climate Change, Land and Water Management Programme. It achieves this by supporting climate-smart agriculture, sustainable resource management, and evidence-based adaptation strategies. By demonstrating that plant phenology serves as a reliable, locally validated tool for weather forecasting, the study facilitates the integration of indigenous ecological knowledge with scientific meteorological systems. This integrated approach seeks to enhance agricultural decision-making, strengthen climate resilience, improve food security, and promote sustainable rural livelihoods in Uganda.Background Indigenous communities have long relied on detailed empirical knowledge of natural phenomena to inform their daily lives and livelihoods. Adaptation to climate change among smallholder farmers is a critical step in achieving sustainable livelihoods. This study explored the potential of integrating indigenous ecological knowledge with scientific methods to improve weather forecasting in the Mt. Elgon region of Uganda. Methods A cross-sectional survey design was employed involving 384 respondents. Data were collected using structured questionnaires to examine perceptions of climate change, local weather pattern changes, and the use of plant phenological indicators for anticipating weather changes. Descriptive statistics was used to summarize responses, and comparative analysis was conducted to assess convergence between local forecasts and meteorological records. A Pearson correlation test was used to assess the relationship between local weather forecasts and formal meteorological information. A chi-square test of independence was used to examine how demographic factors influence farmers’ knowledge and use of phenological indicators. Results Respondents demonstrated extensive knowledge of local weather patterns and perceived declining reliability of rainy seasons in the region. 88% of respondents demonstrated familiarity with plant species used for anticipating weather changes. Local ecological knowledge-based reporting identified distinct rainy and dry months, with January identified as the driest month (98.7%) and April as the rainiest (87%), which converged with the meteorological weather forecast in the region. Plant phenology is a reliable predictor of seasonal weather changes, particularly among tree species such as Cordia africana and Erythrina abyssinica. Leaf shedding indicates impending dry seasons, while new foliage signals the onset of rainfall. Cordia africana and Erythrina abyssinica exhibit a high frequency of usage in weather prediction. The influence of plant phenology on farming activities was evident, with planting time being the most affected decision. Conclusion Plant phenology is a reliable, locally validated predictor of seasonal weather changes in the Mt. Elgon region. Integrating local knowledge with scientific approaches enhances the accuracy and resilience of weather forecasting in rural farming systems.enWeather changesFarmingMeteorologyLocal knowledgeArticle