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This study demonstrates that Indigenous local observations and experiences can enrich knowledge of climate change, particularly in data-deficient regions that are not adequately covered by weather stations. Paradoxically, these places host groups of Indigenous Peoples who have rich knowledge about their local climates from their many years of constant interactions with the environment. The study used group-based semi-structured interviews to collaborate with keystone elderly participants who had profound knowledge and lived experiences about observed changes in their local environment ( n  = 13). These participants were identified through theoretical sampling from four remote Indigenous villages of Mbire District in Zimbabwe. The purpose of the study was to identify indicators of climate change impacts from communities believed not to have been much influenced by the scientific construct of climate change. Results revealed that the locals have a keen interest to closely observe changes occurring in their environment, including finer accounts of experiences with climatic events, owing to their predominantly climate-sensitive livelihoods. These results corroborate existing evidence about a warmer and drier climate and the reported increase in the frequency and severity of drought as well as floods in the area, and add finer details to the changes in ecological, hydrological and human systems, which are not sufficiently reported in existing climate impact studies. We also flagged new observations in biological systems as pointers for further intensive investigation. Given the complexity associated with understanding impacts of climate change and the urgent need to refine knowledge about the same, we argued for perforation of the boundaries of climate science to accommodate enriching perceptions of Indigenous communities who have been religiously observing changes happening in their local environment, albeit being relegated.

Indigenous local observations and experiences can give useful indicators of climate change in data-deficient regions