%0 Research article
%T Development of spatially feasible forest plans: a comparison of two modeling approaches
%A Boston, Kevin
%A Bettinger, Pete
%D 2001
%J Silva Fennica
%V 35
%N 4
%R doi:10.14214/sf.578
%U https://silvafennica.fi/article/578
%X Spatial goals are becoming more frequent aspects of forest management  plans as regulatory and organizational policies change in response to  fisheries and wildlife concerns. The combination of green-up constraints  (harvesting restrictions that prevent the cutting of adjacent units for  a specified period of time) and habitat requirements for red-cockaded  woodpeckers (RCW) in the southeastern U.S. suggests that spatially  feasible forest plans be developed to guide management activities. We  examined two modeling approaches aimed at developing management plans  that had both harvest volume goals, RCW habitat, and green-up  constraints. The first was a two-stage method that in one stage used  linear programming to assign volume goals, and in a second stage used a  tabu search – genetic algorithm heuristic technique to minimize the  deviations from the volume goals while maximizing the present net  revenue and addressing the RCW and green-up constraints. The second  approach was a one-stage procedure where the entire management plan was  developed with the tabu search – genetic algorithm heuristic technique,  thus it did not use the guidance for timber volume levels provided by  the LP solution. The goal was to test two modeling approaches to solving  a realistic spatial harvest scheduling problem. One is where to volume  goals are calculated prior to developing the spatially feasible forest  plan, while the other approach simultaneously addresses the volume goals  while developing the spatially feasible forest plan. The resulting  forest plan from the two-stage approach was superior to that produced  from the one-stage approach in terms of net present value. The main  point from this analysis is that heuristic techniques may benefit from  guidance provided by relaxed LP solutions in their effort to develop  efficient forest management plans, particularly when both commodity  production and complex spatial wildlife habitat goals are considered.  Differences in the production of forest products were apparent between  the two modeling approaches, which could have a significant effect on  the selection of wood processing equipment and facilities.