Matsutake (Tricholoma spp.) are a group of commercially important mushrooms that are
increasingly threatened by over-collection. Ecologically sustainablemanagement of matsutake
has been hindered by the lack of essential information such as reliable distribution
maps. Although a variety of spatial distribution models have been applied to map many
different plants, this has rarely been attempted for mushrooms. In this study, we employed
a logistic regression and a GIS expert system to model the fine-scale spatial distribution
of matsutake in Yunnan, southwest China. Both models predicted mushroom habitat to
an accuracy acceptable for resource management. The overall mapping accuracy of the
GIS expert system was slightly better than the logistic regression model (70.37% versus
65.43%). Furthermore, unlike the logistic regression model, developing the GIS expert system
required no field-based samples. This has important practical implications because it is
very difficult to survey and samplemushrooms and other non-wood forest products (NWFP),
which are usually inconspicuous species and/or lower plants. Therefore, when adequate
samples are not available, incorporating local expert knowledge can help make betterinformed
management decisions and provide an affordable habitat identification tool.