This paper explains the hedonic method and reports our empirical research in which we applied this method to forests. Under some conditions, we were able to interpret the gradients of a hedonic equation regarding housing land prices as the marginal willingness to pay for characteristics of the living environment. Therefore it is possible to term the partial derivatives regarding a forest as the living environment values of a forest. Our research used a hedonic equation of quadratic form. One of the independent variables is the forested area around a housing lot. Most of the signs of the estimated parameters were consistent with those expected. Using this estimated equation, we computed the living environment value of forests in a certain area. As regards some forests, the value was extremely large when compared with the value based on forestry, whereas it did not seem so high when compared with the value of a forest being turned into housing lots. The paper also points out some problems involved with the hedonic method. We showed that the hedonic prices as equilibrium prices might be indeterminate when transaction costs such as moving expenses are introduced into SCOTCHMER'S model. We also discussed the fact that the estimated hedonic equation usually ignores some variables related to an individuals' perspective on the change of living environment. Our conclusion is that we should be careful when interpreting and/or using the estimated hedonic equation.

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This paper examines Ehe relationship between growth and stand structure in selection forests dominated by todo fir (Abies sachalinensis (FR. SCHMIDT) MASTERS). Trees were classified into six Classes by their species (conifers or broad-leaved trees) and diameter (small, medium or large trees). A principal component analysis showed that the six class volumes were well summarized by the first two principal components obtained from the class volumes. The first principal component contrasted the volume of small and medium-sized conifers with the volume of large conifers and broad-leaved trees. The second principal component contrasted the volume of medium and large conifers with the volume of large broad-leaved trees. Next, a multiple regression analysis showed that there were correlations of net increment, gross increment and mortality with the principal components ; and the relationships between stand volume growth and six class volumes were shown numerically. The first principal component reflected a constant effect (i. e., independent of time since selection cutting) of stand structure on volume growth and the second principal component reflected the effect depending on selection cutting. In conclusion, selection stands with many medium-sized conifers grew more than stands containing fewer medium-sized conifers or than stands containing more trees assigned to other classes; and large conifers suppressed stand volume growth less if the selection cutting cycle was short.

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This paper introduces a system which can provide more practical spatial information by using system yield tables and GIS (geographic information system) for forest resources management. This system utilizes functions of growth and yield forecast in the system yield table and spatial retrieval in GIS, to realize the generation, search and output of forest forecast maps. In addition, the procedure for generating forest maps on the basis of system yield tables and GIS is provided. The method introduced in this paper may be useful for strengthening the function of system yield tables in forest management.

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We developed a composite method of evaluating multiple forest functions that includes the potential of each function and social requirement. The potential of each function was evaluated by a quantification method using four land description factors. We used the same factors and the same number of categories to evaluate each function and set a weighted value for each factor. Every factor was set in proportion to the range for every function and the weighted sum was equalized for each function. We then attempted to compare the potential of the four functions. A large area including Tokyo and four surrounding prefectures were divided into ten area classes based on the importance of forest functions. Then the importance of each forest function in each class (Degree of Demand) and the importance of each area class in each forest function (Degree of Necessity) was obtained by AHP. The degree of social requirements was obtained by multiplying the Degree of Demand by the Degree of Necessity. From the value for evaluating the potential and social requirements of forest functions, we obtained a new composite value for evaluating the forest functions. Forested areas with high evaluating value are important to planners because of high potential and/or requirements. However, forested areas with low evaluating values are likely to be treated lightly and become neglected. The most important thing for planners, then, is how to manage forested areas with such low evaluating value.

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