A Predictive Modelling Framework for the Microbial Ecology of Traditional West African Fermented Foods Under Climate Variability

Climate variability is altering the temperature and humidity conditions under which traditional fermented foods are produced across West Africa, with the potential to shift the microbial ecology of fermentation in ways that affect both product quality and food safety. This study develops a predictive modelling framework for the microbial ecology of four traditional Nigerian fermented foods, namely ogi, fufu, iru, and nono, under projected climate variability scenarios for Nigeria. The theoretical contribution is a stochastic differential equation-based model of microbial community dynamics that incorporates temperature, water activity, pH, and substrate composition as environmental drivers of community composition shifts, drawing on ecological succession theory applied to food fermentation systems. The model was parameterised using empirical data from controlled fermentation trials conducted under current and projected future temperature scenarios at the International Institute of Tropical Agriculture, Ibadan, and validated against field samples collected from production sites in Oyo, Benue, Kano, and Bauchi States. The model predicts community-level responses including the displacement of beneficial Lactobacillus species by opportunistic enterobacteria under temperature excursions of 3 to 5 degrees Celsius above current means. A risk assessment module translates predicted microbial community shifts into food safety probability outcomes for each fermented food type. The study draws on predictive food microbiology theory, climate adaptation literature, and fermentation systems biology. The original contribution lies in the integrated ecological-climate modelling framework and its application to traditional food fermentation safety in a Nigerian context. Keywords: predictive microbiology, fermented foods, climate variability, microbial ecology, food safety