Abstract
A hierarchical spatial framework for large-scale, long-term forest landscape planning is presented along with example policy analyses for a 560,000 ha area of the Oregon Coast Range. The modeling framework suggests utilizing the detail provided by satellite imagery to track forest vegetation condition and for representation of fine-scale features, such as riparian areas. Spatial data are then aggregated up to management units, where forest management decisions are simulated. Management units may also be aggregated into harvest blocks to closer emulate management behavior. Land allocations, subdivisions of landowner groups, can be used to represent different levels of management. A management unit may contain multiple land allocations, such as riparian management emphases that vary based on distance from the stream system. The management emphasis required by each land allocation is retained in the simulation of policies. When applied within a large-scale forest landscape planning context, the implications of policies that suggest clearcut size restrictions, minimum harvest ages, or the development of interior habitat areas can be assessed. Simulations indicated that the minimum harvest age constraint has a stronger influence on even-flow harvest levels than do maximum clearcut size or interior habitat area constraints. Even-flow timber harvest level objectives, however, also have an effect on the results: time periods beyond the constraining time period show a build-up of timber inventory, which suggests a possible relaxation or modification of the objective in order to achieve average harvest ages that are closer to the minimum harvest age.
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