Windthrow Hazard Mapping using GIS, Canadian Forest Products ...

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ApplicationsThese models predict the probability of damage to clearcut edges under givencombinations of environmental and management conditions. Because these maps usestand level information from broad scale inventories, they indicate conditions at thestand level not at the microsite or tree level. Furthermore, aerial photographinterpretation of wind damage does not detect low levels of damage which might beimportant in riparian areas or areas of unstable terrain. These maps are intended forstrategic planning during the development plan stage. Windthrow risk and potentialimpacts should be assessed in the field during cutblock layout. Since partiallyharvested stands were not represented in the model fitting dataset, predictions are notreliable in these stand types.ConclusionsAdequately fitting, local windthrow risk prediction models can be developed usingstand, site, topographic, wind and management variables. Spatial autocorrelation, animportant issue to consider when analysing spatial data was also taken intoconsideration and was handled more rigorously in this study than in previous studies.The availability of extreme wind data substantially improved the model. In ourinvestigations of models from coastal and interior BC locations, we are findingconsistency in the variables selected and general portability of empirical models toareas with similar conditions. This reflects consistency in the underlying factors thatcontribute to windthrow risk. However windthrow prediction models work best forlandscape sub-units whose attributes fall within the area from which data wasgathered. The resulting hazard map for TFL 30 should be useful for strategicdevelopment planning.18
ReferencesAnderson, C. J., Coutts, M.P., Ritchie, R.M., Campbell, D. J., 1989. Root extractionforce measurement for Sitka spruce. Forestry 62, 127-137.Besse, W. J. 2001. Windthrow monitoring of alternative silvicultural systems in themontane coastal forests. In Proceedings of the windthrow researchersworkshop, Jan 31- Feb. 1, Richmond, B.C.Carr, J. R. 1995. Numerical analysis for the geological sciences. Prentice Hall,Englewood Cliffs, New Jersey, USA.Cremer, K. W., C. J. Borough, F. H. McKinnel & P. R. Carter. 1982. Effects of stockingand thinning on wind damage in plantations. New Zealand J. For. Sci. 12:245 –268.Harris, A.S. 1989. Wind in the forests of southeast Alaska and guides for reducingdamage. U.S.D.A. Forest Service PNW-GTR-224. 63pp.Holmes, R. H. 1985. An analysis of windthrow along clearcut boundaries in theTsitika watershed. B.A. thesis, University of British Columbia, Vancouver, B.C.Manly, F. J., 2000. Multivariate statistical methods a primer. 2 nd edition. Chapman &Hall, New York.Mitchell, S. J., T. Hailemariam and Y. Kulis 2000. Empirical modelling of cutblock edgewindthrow risk on Vancouver Island, Canada, using stand level information.Forest Ecology and Management 5377: 1 - 14.Moore, M. K. 1977. Factors contributing to blowdown in streamside leave strips onVancouver Island. BC Min. For. Land. Manage. Rep. No.3. Victoria BC.Murphy, B. and P.L. Jackson 1997. Extreme value analysis: return periods of extremewind events in the central interior of British Columbia. Report prepared forMcGregor Model Forest Association. Prince George BC.Rollerson, T.P. 1979. Queen Charlotte Woodlands Division windthrow study. Nanaimo:MacMillan Bloedel Limited, Woodlands Services. 31pp.Rollerson, T.P. 2001. Riparian windthrow – North Vancouver Island. In Proceedings ofthe windthrow researchers workshop, Jan 31- Feb. 1, Richmond, B.C.Rowan, C., Michell, S. J., Hailemariam, T. 2001. Edge windfirming treatments incoastal British Columbia. In Proceedings of the windthrow researchersworkshop, Jan 31- Feb. 1, Richmond, B.C.Ruel, J.C. 1995. Understanding windthrow: silvicultural implications. For. Chron. 75,434-445.SAS Institute Inc., Logistic Regression Examples Using SAS System, Version 6, First19
Page 3 and 4: models have been successfully devel
Page 5 and 6: angle between peak wind direction a
Page 7 and 8: Determination of independent variab
Page 9 and 10: anking of risk groups. For practica
Page 11 and 12: Contingency tablesTrends in the pro
Page 13 and 14: k)l)0.2060001612000Proportion0.150.
Page 15 and 16: Observed0.450.40.350.30.250.20.150.
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Page 21 and 22: Appendix 1. Procedures used to buil
Page 23 and 24: Table A1-3. Map formulas used to ca
Page 25: *a pdf version of this map is attac

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