Published Date
Forest Policy and Economics January 2005, Vol.7(1):39–52,doi:10.1016/S1389-9341(03)00010-8
Author
Wenchao Zhou,
Peichen Gong
Department of Forest Economics, Swedish University of Agricultural Sciences, SE-901 83 Umeå, Sweden
Received 15 March 2002. Revised 18 November 2002. Accepted 3 February 2003. Available online 18 April 2003.
Abstract
This paper examines the tradeoffs between different uses of forests in three communes in the mountain region in northern Sweden. The most important uses of the forests include timber production, preservation of biodiversity, reindeer grazing and recreation. Management outcomes with respect to the different uses are measured in terms of the net present value (NPV) of timber production profits, the sum of deadwood volume over time, the minimum periodic lichen production, and a minimum periodic recreation index (RI). The analysis shows that the forests can be managed to achieve dramatically different mixes of NPV, deadwood volume, and lichen production, whereas the RI varies only within a narrow range. To maximize the NPV, lichen production would reduce by 40% from its maximum level, and the volume of deadwood would be close to 0 in period 2 and thereafter. Maximization of deadwood volume would lead to the maximum lichen production, while the NPV would fall below 0. Maximization of lichen production reduces the NPV by at least 20%, and could reduce the amount of deadwood by up to 75%. When lichen production is restricted to its maximum, there is a wide range of possible choices with respect to the mix of the NPV and deadwood volume. The marginal cost of increasing the deadwood volume ranges from 1.12 to 20 SEK/m3. The choice between lichen production and deadwood volume is most flexible when the NPV is fixed at approximately 93% of its maximum.
Published Date
Journal of Forest Economics 14 September 2004, Vol.10(2):97–113, doi:10.1016/j.jfe.2004.05.003
Author
Wenchao Zhou
Peichen Gong,
Department of Forest Economics, Swedish University of Agricultural Sciences, SE-901 83, Umeå, Sweden
Received 1 October 2003. Accepted 15 March 2004. Available online 21 August 2004.
Abstract
This study analyzes the economic effects of environmental concerns in forest management in the Swedish mountain region. The environmental concerns include the amount of deadwood, the area of broad-leaved forest, and the area of old-growth forest. The analysis is performed by formulating a fuzzy linear programming model for the forests in three communes. The model is solved using the modeling to generate alternative approach to generate a number of management plans, which are maximally different from each other in the decision space and are satisfactory with respect to the timber production objective. The results show that, if the forests are managed to meet the interim targets for Healthy Forests, the net present value of the profits of timber production is considerably reduced and this reduction could be as high as 55%. The results also show that among the three environmental goals the increase in deadwood volume is the most restrictive one.
Published Date
Ecological Modelling 20 January 2001, Vol.136(2):113–129,doi:10.1016/S0304-3800(00)00364-1 Author
Satya Priya,
Ryosuke Shibasaki
Center for Spatial Information Science, University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan
Received 2 November 1999. Revised 6 June 2000. Accepted 14 July 2000. Available online 26 March 2001.
Abstract
Traditional decision support systems based on crop simulation models are normally site-specific. In policy formulation, however, spatial variability of crop production often need to be evaluated due to different soil conditions, weather conditions and agricultural practices within a target-region. To address the spatial variability, a spatial model ‘Spatial EPIC’ was developed based on a crop simulation model EPIC (Erosion Productivity Impact Calculator). Since site-specific crop simulation models require point-based or fine resolution data, it is necessary to feed the fine resolution data at each grid-cell in order to ‘spatialize’ crop simulation models. The authors proposed a method to generate fine resolution data from coarse resolution data, which are usually available at regional or national level. In addition, since the original EPIC crop management practices are static in nature, a dynamic adaptation loop is added to evaluate the impacts of agricultural practice changes over temporal scale. Validation of the spatial EPIC was conducted at different spatial scales, i.e. national scale (approx. 50 km cell-size) and regional scale (approx. 10 km cell-size) in India. Results showed that at both resolutions level crop yield varied significantly as a function of seasonal climatic variation, soil water holding characteristics and applied crop management strategies. Also, the study successfully demonstrated model applicability in evaluating an impact of climate changes over major cereal crops productivity at national level taking spatial variability into account.
