<em><span>Coffee arabica</span></em><span> species have already been affected by climate change, with economic and social implications. Small-holder farmers have faced and will continue to face significant challenges in sustaining the production of their coffee plants. This study aimed to determine the optimal bio-climatic factors for coffee production in current and future climate change scenarios by simulating coffee distribution's responses to nine selective bio-climatic factors under the scenarios of moderate representative concentration pathway (RCP4.5) and worst representative concentration pathway (RCP8.5). The Maxent model was used to simulate the distribution of <em>C. arabica</em>. Multiple regression models (path and response optimizers) were used to parameterize and optimize the logistic outputs from the Maxent model. Results showed that climatic factors such as total precipitation, precipitation seasonality, and mean temperature are the most important climatic factors in influencing <em>C. arabica</em> farming. Under the current condition, total precipitation significantly benefits <em>C. arabica</em> whereas precipitation seasonality significantly affects it (P < 0.001). The annual mean temperature has neither benefited nor affected it. Under the RCP4.5, C. arabica would positively react to the rising annual mean temperature and total precipitation but adversely react to the rising precipitation seasonality. For current, RCP4.5, and RCP8.5, the average five top-optimal multiple responses of <em>C. arabica</em> were 75.8, 77, and 70%, respectively. Under RCP8.5, the maximum optimal response of the plant will be an annual temperature of 23.77°C, total precipitation of 1806 mm, and 77% precipitation seasonality. In comparison to the current and RCP8.5 climatic scenarios, the distribution responses of <em>C. arabica</em> to the climatic factors would be significantly greater in the RCP4.5 scenario (P > 0.001). As precipitation and temperature-related variables increase, the cultivation of <em>C. arabica</em> will increase by 1.2% under RCP4.5 but decrease by 5.6% under RCP8.5. A limited number of models and environmental factors were used in this study, suggesting that intensive research into other environmental aspects is needed using different models.</span>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.