Over the last decade, geological uncertainty, its effects on long-term mine planning and methods for related risk management have been studied. However, the combined effect of geological and commodity price uncertainty has received less attention in the technical literature. A research experiment addressing both these sources of uncertainty is presented here, while accounting for their differences. In particular, while the current commodity price is known at the beginning of every new mining period, the geology, including mineral grades, metal content, material types and so on, remain uncertain, even when additional information becomes available. The proposed method first uses a two-stage model to manage the geological uncertainty leading to a scenario-independent extraction sequence and, based on different metal production targets, a pool of subsets of mining blocks is also precomputed for every period. Then, a stochastic dynamic algorithm is developed and employed to define the best policy in terms of metal production targets to follow, depending on the evolution of the related commodity price. This policy follows the scenario tree of the commodity price, as it is scenario-dependent (price only) with non-anticipativity constraints, similar to an operator adapting to a fluctuating market. This new approach is tested on a small case study and reveals the counter-intuitive combined effects of both sources of uncertainty.