Abstract
A proper forest planning process includes the assessment of the decision-makers’ preferences concerning the future forest use. For some owners, it may be a difficult task to express their preferences exactly and in the form that is required for planning calculations. This study presents a new kind of approach for analyzing the effects of preferential uncertainty. The approach consists of examination of the differences in the actual decision variables in forest planning, i.e. selected treatments for stands between holding-level forest plans. In example calculations, the preferential uncertainty was examined from three different viewpoints: the uncertainty in the weights of the objective variables; the uncertainty in the partial utility function; and the combination of these two uncertainty sources. One thousand preference realizations were generated for each of these uncertainty sources. More than one treatment schedules are proposed for stands that are affected by preferential uncertainty. These stands were detected from among the resulting set of 1,000 forest plans. With this done, two potential decision-making strategies, an adaptive behavior strategy and a threshold proportion strategy, were applied as guides in decision-making for stands, which have more than one treatment alternative selected in the produced optimal forest plans. The adaptive behavior technique required that the forest owner select one treatment alternative for at least one stand that has more than one proposed treatment alternative. The treatment alternatives having frequencies exceeding the given threshold frequency were all accepted simultaneously in the threshold strategy. The main benefit of the approach is to present the effects of uncertainties in a way that can be easily understood by the actual decision-makers. It is a promising tool for practical decision-making situations because at least Finnish non-industrial private forest owners quite often focus on making stand-level forest management decisions. It is also suitable for examinations of other uncertainty sources such as timber prices or inventory data.
Similar content being viewed by others
References
Alho J, Kangas J (1997) Analysing uncertainties in experts’ opinions of forest plan performance. For Sci 43:521–528
Alho JM, Kolehmainen O, Leskinen P (2001) Regression methods for pairwise comparisons data. In: Schmoldt DL, Kangas J, Mendoza GA, Pesonen M (eds) The Analytic Hierarchy Process in natural resource and environmental decision making. Kluwer, Dortrecht, pp 235–251
Bettinger P, Graetz D, Boston K, Sessions J, Chung W (2002) Eight heuristic planning techniques applied to three increasingly difficult wildlife planning problems. Silva Fenn 36(2):561–584
Dowsland KA (1993) Simulated annealing. In: Reeves CR (ed) Modern heuristic techniques for combinatorial problems. Blackwell, Oxford, pp 20–69
Gong P (1994) Adaptive optimization for forest-level timber harvest decision analysis. J Environ Manag 40:65–90. doi:10.1006/jema.1994.1005
Hyvän metsänhoidon suositukset. Metsätalouden kehittämiskeskus Tapio. Julkaisusarja 13/2001. Helsinki. Finland (in Finnish)
Haara A (2003) Comparing simulation methods for modelling the errors of stand inventory data. Silva Fenn 37(4):477–491
Haara A (2005) The assessment of the uncertainty of the updated stand-level inventory data. In: Haara A (ed) The uncertainty of forest management planning data in Finnish non-industrial private forestry. Dissertationes Forestales 8. ISBN 951–651-107-4. Internet: http://www.metla.fi/dissertationes
Hof JG, Pickens JB (1991) Chance-constrained and chance-maximizing mathematical programs in renewable resource management. For Sci 37:308–325
Hynynen J, Ojansuu R, Hökkä H, Siipilehto J, Salminen H, Haapala P (2002) Models for predicting stand development in MELA system. The Finnish Forest Research Institute. Research Papers 835, p 116. ISBN 951-40-1815-X
Jokinen A (2005) Standardization and entrainment in forest management. In: Haila Y, Dyke C (eds) How nature speaks: the dynamics of the human ecological condition. Duke University Press, Durham
Kangas A (2006) The risk of decision making with incomplete criteria weight information. Can J For Res 36:195–205. doi:10.1139/x05-243
Kangas A, Kangas J (2004) Probability, possibility and evidence: approaches to consider risk and uncertainty forestry decision analysis. For Policy Econ 6:169–188. doi:10.1016/S1389-9341(02)00083-7
Kangas J, Leskinen P, Pukkala T (2000) Integrating timber price scenario modeling with tactical management planning of private forestry at forest holding level. Silva Fenn 34(4):399–409
Kangas J, Pukkala T, Kangas A (2001) HERO: heuristic optimisation for multi-criteria forestry decision analysis. In: Schmoldt D, Kangas J, Medoza GA, Pesonen M (eds) The analytic hierarchy process in natural resource and environmental decision making. Managing forest ecosystems, vol 3. Kluwer, Dordrecht, pp 51–65
Kangas A, Heikkinen E, Maltamo M (2004) Accuracy of partially visually assessed stand characteristics: a case study of Finnish forest inventory by compartments. Can J For Res 34:916–930. doi:10.1139/x03-266
Leskinen P (2001) Statistical methods for measuring preferences. University of Joensuu, Publications in Social Sciences 48
Leskinen P, Kangas J (1998a) Modelling and simulation of timber prices for forest planning calculations. Scand J For Res 13:469–476
Leskinen P, Kangas J (1998b) Analysing uncertainties of interval judgment data in multiple-criteria evaluation of forest plans. Silva Fenn 32(4):363–372
Leskinen P, Kangas J, Pasanen A-M (2003) Assessing ecological values with dependent explanatory variables in multi-criteria forest ecosystem management. Ecol ModelL 170:1–12. doi:10.1016/S0304-3800(03)00283-7
Leskinen P, Kangas A, Kangas J (2004) Rank-based modelling of preferences in multi-criteria decision making. Eur J Oper Res 158:721–733. doi:10.1016/S0377-2217(03)00384-9
Leskinen P, Viitanen J, Kangas A, Kangas J (2006) Alternatives to incorporate uncertainty and risk attitude in multicriteria evaluation of forest plans. For Sci 52(3):304–312
Liesiö J, Mild P, Salo A (2007) Preference programming for robust portfolio modeling and project selection. Eur J Oper Res 181:1488–1505. doi:10.1016/j.ejor.2005.12.041
Pukkala T (1998) Multiple risks in multi-objective forest planning: integration and importance. For Ecol Manage 111:265–284. doi:10.1016/S0378-1127(98)00339-9
Pukkala T (2002a) Measuring non-wood forest outputs in numerical forest planning. A review of Finnish research. In: Pukkala T (ed) Multi-objective forest planning. Managing forest ecosystems, vol 6. Kluwer, Dordrecht, pp 173–207
Pukkala T (2002b) Introduction to multi-objective forest planning. In: Pukkala T (ed) Multi-objective forest planning. Managing forest ecosystems, vol 6. Kluwer, Dordrecht, pp 1–20
Pukkala T, Kangas J (1993) A heuristic optimization method for forest planning and decision making. Scand J For Res 8:560–570
Pukkala T, Kangas J (1996) A method for integrating risk and attitude toward risk into forest planning. For Sci 42(2):198–205
Pukkala T, Kurttila M (2005) Examining the performance of six heuristic optimisation techniques in different forest planning problems. Silva Fenn 39(1):67–80
Pukkala T, Heinonen T (2006) Optimizing heuristic search in forest planning. Nonlinear Anal Real World Appl 7:1284–1297. doi:10.1016/j.nonrwa.2005.11.011
Pykäläinen J (2000a) Defining forest owner’s forest-management goals by means of a thematic interview in interactive forest planning. Silva Fenn 34(1):47–59
Pykäläinen J (2000b) Interactive use of multi-criteria decision analysis in forest planning. Academic dissertation. University of Joensuu, Faculty of Forestry, p 37
Redsven V, Anola-Pukkila A, Haara A, Hirvelä H, Härkönen K, Kettunen L, et al. (2002) MELA2002 Reference Manual (mela2002.pdf). The Finnish Forest Research Institute, Helsinki, p 588
Siitonen M, Nuutinen T (1996) Timber production analyses in Finland and the MELA System. In: Päivinen R, Roihuvuo L, Siitonen M (eds) Large-scale Forestry Scenario Models: Experiences and Requirements. EFI Proceedings No 5. European Forest Institute, Joensuu, Finland, pp 89–98
Tikkanen J, Isokääntä T, Pykäläinen J, Leskinen P (2006) Applying cognitive mapping approach to explore the objective-structure of forest owners in a Northern Finnish case area. For Policy Econ 9:139–152. doi:10.1016/j.forpol.2005.04.001
von Winterfield D, Edwards W (1986) Decision analysis and behavioral research. Cambridge University Press, Cambridge
Acknowledgments
This study is supported by the Academy of Finland (decision number 210417), and the Ministry of Agriculture and Forestry of Finland in connection with the project “Ecological considerations in landscape-level collaborative planning of private forestry”.
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by M. Moog.
Appendix
Appendix
See Table 6
Rights and permissions
About this article
Cite this article
Kurttila, M., Muinonen, E., Leskinen, P. et al. An approach for examining the effects of preferential uncertainty on the contents of forest management plan at stand and holding level. Eur J Forest Res 128, 37–50 (2009). https://doi.org/10.1007/s10342-008-0237-3
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10342-008-0237-3