Using Tabu search to schedule timber harvests subject to spatial wildlife goals for big game

An algorithm was developed that uses Tabu search to schedule timber harvests subject to even-flow of timber volume harvested, adjacency constraints, and spatial wildlife habitat quality goals. A subroutine within the algorithm senses the size of contiguous cover blocks in order to evaluate the wildlife habitat quality goals. The wildlife habitat quality goals consist of (1) maintaining at least 80% of the forage area within 200 m of a hiding or thermal patch at least 3 ha in size, and (2) maintaining 80% of the forage area within 300 m of a hiding or thermal patch at least 17 ha in size. To illustrate the procedure, feasible harvest plans for a three-period planning horizon were developed. Two scenarios were examined: (1) units 0–39 years old were considered forage, and there was no minimum harvest age for timbered units, and (2) units 0–9 years old were considered forage with a minimum harvest age of 50 years for timbered units. The second wildlife habitat quality goal was found to be the most limiting in both scenarios, while the first wildlife goal was at a minimum for only one of the three periods in the case study. The results of the first scenario showed that the second wildlife goal was at the minimum level for all three periods when the algorithm has reached a steady-state area of locating solutions. The second scenario resulted in a much more spatially and temporally constrained set of results, where all solutions met the wildlife goals, yet a steady state was not reached and harvest levels eventually deviated widely from an even-flow perspective. We demonstrate that an algorithm can be developed to simultaneously evaluate these types of spatial wildlife goals which do not have a predictable response to decision choices.