Introduction Climate variability threatens water availability, agricultural and livestock productivity, and rural wellbeing in the Andean-Amazon transition zone, one of the most vulnerable areas of the Amazon basin, yet most participatory studies of local climate perception in the region remain descriptive.MethodsThis study analyzed the effects of local climate variability indicators on the socioecological components of the Andean-Amazon region using Fuzzy Cognitive Maps and Monte Carlo simulations, based on the knowledge of rural producers in the Hacha River basin, Caquetá, Colombia. A total of 430 farming households were surveyed to characterize the study population, and 52 of these producers participated in five focus groups to identify local climate variability indicators and their effects across socioecological components.ResultsFive indicators were identified and ranked by perceived impact: temperature increase, increased rainfall, strong winds, sudden changes in temperature, and seasonal variation. Together, these generated 21 effects distributed across agricultural, livestock, water, edaphic, and social components. Temperature increase and strong winds showed the highest centrality values in the Fuzzy Cognitive Map, with the livestock and edaphic components concentrating the greatest number and magnitude of effects. Monte Carlo simulations confirmed that most effects retained substantial impact magnitudes under uncertainty, with increased parasites and diseases in livestock, erosion, and organic matter decline identified as critical across all simulations.DiscussionThese findings show that integrating local knowledge with participatory modeling can identify the socioecological components most critically affected by climate variability and inform context-specific adaptation strategies, such as agroforestry, in rural Andean-Amazon communities.