By means of stochastic optimal control, this paper aims at studying the shadow pricing of renewable natural resources in uncertainty. Two cases are considered, respectively centralized and decentralized control processes. The latter is in the form of a stochastic control of the state vector distributed between several agents. In both cases, the optimal control path that minimizes the cost function, which is a decreasing function of time, corresponds to the real option valuation as a cost-effective optional investment in the resource stock preservation in uncertainty. The results obtained from numerical simulations show coherence with those encountered in the literature on option pricing.