Bridging the gap: Farmers' climate change perceptions and meteorological realities in eastern D.R. Congo

This study compared farmer perceptions with four decades (1981–2020) of meteorological observations across two agroecological zones in South Kivu, including the Equatorial High-Altitude Zone (EHAZ) and the Tropical High- and Mid-Altitude Zone (THMAZ). Using a multistage stratified random sampling technique, 450 farmers from three territories (Uvira, Kabare, and Kalehe) were surveyed. Trends were analyzed using the Mann-Kendall test and Sen's slope estimator. Seasonal onset and cessation were determined using agronomic criteria, and climate extremes were assessed using 23 ETCCDI indices. Drought conditions were evaluated using the 12-month Standardized Precipitation Evapotranspiration Index (SPEI). Logistic regression was used to identify the socioeconomic predictors of farmer alignment with these long-term meteorological records. Meteorological analysis revealed significant warming (EHAZ: 0.2 °C/decade; THMAZ: 0.3 °C/decade), but contrasting rainfall trends. EHAZ experienced a significant rainfall decline of 71.5 mm/decade, whereas THMAZ remained stable. Warm days increased by 1.9–4.0%/decade and warm nights by 2.9–4.8%/decade, whereas cool extremes declined proportionally (all p < 0.001) in both zones. Rainy season onset deteriorated in THMAZ for both seasons, where the short rainy season B recorded 20.0% complete failures and 27.5% false onsets over 40 years, compared to minimal failures in EHAZ. Farmer perceptions showed strong directional convergence with temperature (70.9%), extreme heat (66.8%) and drought trends (60.9%) but diverged for annual rainfall totals. While 38.7% aligned with multi-decadal volumetric trends, 34% reported declines in areas where annual totals were statistically stable. Logistic regression identified organizational affiliation, access to weather information, farming experience, and adaptation knowledge as significant predictors of trend alignment. These findings highlight the importance of providing agro-ecologically differentiated climate information, specifically targeting rainfall onset, dry spells, seasonal reliability, and long-term changes rather than simple weather forecasts to support effective local adaptation strategies.