This work proposes a more holistic forest management approach compared to previous efforts by the same authors, by integrating suppression planning into an already developed fire simulation-based optimization framework. Forest management is iteratively guided by feedback from fire spread simulations (developed in previous work) and the optimization of firefighting resource base locations. The approach employs mixed integer programming to solve the forest management problem and optimize the distribution of firefighting bases. It uses shortest path algorithms to assess fire potential by identifying high-risk paths that could lead to unacceptable fire spread. If such paths are detected, the algorithm adjusts the constraints of the forestry model and re-optimizes both forest management and firefighting base placement. This iterative process continues until no unacceptable fire paths are found. Fire paths are obtained by representing the forest as a network. To model potential base locations, a resource network is also defined. We present computational experiments conducted in a Portuguese forest to test this approach.