Logging is widespread in tropical regions, with approximately 50% of all humid tropical forests (1.73 × 109 ha) regarded as production forests. To maintain the ecosystem functions of carbon sequestration and timber supply in tropical production forests over a long term, forest management must be sustainable under changing climate conditions. Individual-based forest models are useful tools to enhance our understanding about the long-term effects of harvest and climate change on forest dynamics because they link empirical field data with simulations of ecological processes. The objective of this study is to analyze the combined effects of selective logging and climate change on biomass stocks and timber harvest in a tropical forest in French Guiana. By applying a forest model, we simulated natural forest dynamics under the baseline scenario of current climate conditions and compared the results with scenarios of selective logging under climate change. The analyses revealed how substantially forest dynamics are altered under different scenarios of climate change. (1) Repeated logging within recovery times decreased biomass and timber harvest, irrespective of the intensity of climate change. (2) With moderate climate change as envisaged by the 5th IPCC Assessment Report (representative concentration pathway 2.6), the average biomass remained the same as in the baseline scenario (-1%), but with intensive climate change (RCP 8.5), the average biomass decreased by 12%. (3) The combination of selective logging and climate change increased the likelihood of changes in forest dynamics, driven mainly by rising temperatures. Under RCP 8.5, the average timber harvest was almost halved, regardless of the logging cycle applied. An application-oriented use of forest models will help to identify opportunities to reduce the effects of unwanted ecosystem changes in a changing environment. To ensure that ecosystem functions in production forests are maintained under climate change cond