A selection harvesting algorithm for use in spatially explicit individual-based forest simulation models

Based on this simple process, we built two different versions of the harvesting algorithm. An “empirical” algorithm was designed and calibrated to reproduce the observed spatial and size distribution of stumps (harvested trees) at a study site in central Ontario, and was successful in reproducing harvesting patterns found in the field, notably variability in the cluster size of harvested trees. The “user-defined” algorithm implements alternative harvesting regimes (user-defined harvest targets), which may differ in the intensity of harvesting, the size-specificity of harvesting, and the spatial pattern of harvesting. We show that the user-defined harvesting algorithm succeeds in meeting harvest targets specified by the user (e.g., size class distribution and basal area of trees harvested), while simultaneously adjusting the gap size specified (i.e., the distribution of harvested trees per cluster). Incorporation of this harvesting algorithm into spatially explicit, individual-based models will permit analyses of long-term responses of forest stands to harvesting scenarios that more realistically capture the complex patterns of within-stand variability generated by selection silviculture as practiced in actual managed forests.