Multiple risks in multi-objective forest planning: Integration and importance

Forest Ecology and Management

Volumn 111, Issue 2-3, 1998, Pages 265-284

  Pukkala, Timo ^a  

^a UNIVERSITY OF EASTERN FINLAND   (Finland)

Author keywords

Risk preferences; Scenario technique; Stochastic optimization; Utility function

Indexed keywords

DECISION MAKING; FORESTRY POLICY; MULTIOBJECTIVE PROGRAMMING; RISK ASSESSMENT;

EID: 0032495207     PISSN: 03781127     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0378-1127(98)00339-9     Document Type: Article

References (23)

1. Boychuck D., Martell L. A multistage stochastic programming model for sustainable forest-level timber supply under risk of fire. For. Sci. 42:1996;10-26.
2. Caulfield J.P. A stochastic efficiency approach for determining the economic rotation of a forest stand. For. Sci. 34:1988;441-457.
3. Dixon B.L., Howitt R.E. Resource production under uncertainty: A stochastic control approach to timber harvest scheduling. Am. J. Agric. Econ. 62:1980;499-507.
4. Dyer J.S., Fishburn P.C., Steuer R.E., Wallenius J., Ziontz S. Multiple criteria decision making, multi-attribute utility theory: The next ten years. Manage. Sci. 38:1992;645-654.
5. Forboseh P.F., Pickens J.B. A reservation value approach to harvest scheduling with stochastic timber prices. For. Sci. 42:1996;465-473.
6. Gong P. Adaptive optimization for forest-level timber harvest decision analysis. J. Env. Manage. 40:1994;65-90.
7. Hoganson M.H., Rose D.W. A model for recognizing forestwide risk in timber management scheduling. For. Sci. 34:1987;220-238.
8. Kangas J. Choosing the regeneration chain in a forest stand: A decision model based on multi-attribute utility theory. Univer. Joensuu Publ. Sci. 24:1992;230.
9. Kao C. Optimal stocking levels and rotation under risk. For. Sci. 28:1982;711-719.
10. Kellomäki S., Hänninen H., Kolström T., Kotisaari A., Pukkala T. A tentative model for describing the effects of some regenerative processes on the properties of natural seedling stands. Silva Fenn. 21(1):1987;1-10.
11. Law, A.M., Kelton, W.D., 1982. Simulation modeling and analysis. McGraw-Hill, New York, p. 400.
12. Leskinen, P., 1995. Puun reaalisten kantohintojen mallittaminen ja simulointi (in Finnish). University of Joensuu, Finland, p. 76+appendix.
13. Nyyssönen A., Mielikäinen K. Estimation of stand increment. (In Finnish with English summary). Acta For. Fenn. 163:1978;40.
14. Ojansuu, R., Hynynen, J., Koivunen, J., Luoma., P., 1991. Luonnonprosessit metsä-laskelmassa (MELA) - Metsä 2000-versio (in Finnish). The Finnish Forest Research Institute, Research papers 385, 59.
15. Pasanen, K., 1995. Integrating variation in tree growth into forest planning. Thesis for the Degree of Master of Science in Forestry. University of Joensuu, Finland, p. 31.
16. Pukkala, T., 1987a. Simulation model for natural regeneration of Pinus sylvestris, Picea abies Betula pendula and Betula pubescence. Silva Fen. 21(1) 37-53.
17. Pukkala, T., 1987b. A model for predicting the seed crop of Picea abies and Pinus syl vestris (In Finnish with English summary). Silva Fenn. 21(2) 135-144.
18. Pukkala, T., 1993. Metsäsuunnitteluohjelmisto MONSU, Ohjelmiston toiminta ja käyttö. (in Finnish). University of Joensuu, Finland, p. 45.
19. Pukkala T., Kellomäki S., Mustonen E. Prediction of the amenity of a tree stand. Scand. J. For. Res. 3:1988;533-544.
20. Pukkala T., Kangas J. A heuristic optimization method for forest planning and decision making. Scand. J. For. Res. 8:1993;560-570.
21. Pukkala T., Kangas J. A method for integrating risk and attitude toward risk into forest planning. For. Sci. 42:1996;198-205.
22. Saaty, T.L., 1980. The analytic hierarchy process. McGraw-Hill, New York, p. 287.
23. Valsta L. A scenario approach to stochastic anticipatory optimization in stand management. For. Sci. 38:1992;430-447.