Natural resource management policies have historically been evaluated and implemented without using simulations of potential forest landscape condition over time. Forest-based resource policies have traditionally been based on stand-level analyses of individual land ownerships. Simulation models that integrate ecological and economic concerns, while adequately modeling the behavior of landowners, can help policy-makers think through the implications of potential forest policies in a spatial manner.

This research project involves the development and testing of landscape simulation and optimization models that can accommodate economic and ecological goals and constraints to allow one to assess alternative forest policies. The LAndscape Management Policy Simulator (LAMPS), for example, is a spatially-explicit, dynamic simulation model developed to examine forest policies over long time frames with both deterministic and stochastic processes, while recognizing spatial aspects of activities across the landscape. The model projects forest conditions over time and is valuable in helping assess the implications of green-up and adjacency constraints, leave-tree retention policies, and riparian restrictions. The model has suggested, for example, that moving from a 5-year green-up to a 10-year green-up policy may reduce aggregate harvest levels for all landowners by about 19%. And, leaving 10% of clearcuts in un-cut clumps may reduce aggregate harvest levels by about 7%.