Using landscape metrics and topographic analysis to examine forest management in a mixed forest, Hokkaido, Japan: Guidelines for management interventions and evaluation of cover changes

In this study, we identified the distribution characteristics of a mixed forest of coniferous and broad-leaved trees (a typical forest type in Hokkaido, Japan) using landscape metrics and topographic factors, and attempted to apply this knowledge to examine forest management. This approach provides a new perspective (i.e., the landscape structure) on forest management, which traditionally has been determined on the basis of individual forest stands. We first created a cover type map of the study area by means of aerial photo interpretation. The characteristics of each cover type identified from the photographs were determined using landscape metrics for each cover class. We digitized a forest administrative map (1:20,000 scale) using 20-m contours, and imported this into GIS software to produce a terrain model; on this model, we overlaid the cover types. Our examination of landscape metrics showed that most of the natural forest could be managed similarly. However, our examination of topographic characteristics revealed exceptions (e.g., areas that are difficult to regenerate) that will require particular attention when managing the natural forest. Based on the information we obtained, we proposed a guideline for sustainable forest management. From the land cover map, we proposed an “improved” cover type map to illustrate the development of a high growing stock of forest based on forest management. We compared the current cover map with the “improved” cover map and demonstrated that the improved form would have more significant effects on fauna that do not recognize differences in the proportion of the dominant species types than on those that can recognize these differences. Our results show how the information obtained using landscape metrics and terrain models is an essential tool for various stages of forest management planning.