Stochastic modeling of soil biogeochemical processes in drought-prone ecosystems - Amoo, A.O.; Amoo, S.A.; Ezeonu, C.S.; Tatah, S.V. (International Journal of Mathematical Analysis and Modelling, 2026)
This review shows how stochastic modeling of soil biogeochemical processes in drought-prone ecosystems could provide an essential framework for understanding how random fluctuations in environmental conditions, particularly precipitation and temperature shape microbial functioning, nutrient cycling, and overall ecosystem resilience. In water-limited regions, these stochastic variations influence microbial metabolic rates, suppress carbon use efficiency (CUE), alter enzyme-driven decomposition, and weaken nutrient turnover. Integrating stochastic differential equations (SDEs) with microbial biomass dynamics, the article offers deeper insight into how moisture variability produces nonlinear feedbacks, including reduced mineralization during prolonged drought. Analytical tools such as Monte Carlo simulations and Fokker-Planck equations help quantify the probability of soil organic matter persistence and reveal early warning indicators of ecosystem instability, such as increased variance in CO2 fluxes preceding potential tipping points. These approaches demonstrate that stochastic forcing may either buffer or intensify nutrient losses depending on drought frequency and intensity, and underscore the critical role of microbial adaptation in sustaining ecosystem function under climatic stress, hence the call for more research in this field considering the recent climate extremes globally.