A review of mechanistic modelling of wind damage risk to forests

Summary This paper reviews the current status of mechanistic models for wind damage risk assessment, describing model structure, applicability, validation and current limitations. We focus particularly on the hybrid mechanistic/empirical models GALES and HWIND, which have been designed for calculating wind damage risk at the stand level within uniform forests and which are the most widely adopted models within the research community. These models have been integrated with different methods for predicting the local wind climate in order to calculate the probability of wind damage in a number of different countries. We also discuss ongoing modelling work and proposals for future development in order to deal with complex forest structures and to predict the wind damage risk of individual trees within stands through the integration of mechanistic risk models with forest growth and yield models within a geographical information system framework. This kind of model integration will enable spatial representation of tree lists and damage propagation and allow managers to evaluate the effect of different harvesting and thinning scenarios on the risk of windthrow of both stands and individual trees within a stand.

[1]  C. Quine,et al.  The Assessment of Wind Exposure for Forestry in Upland Britain , 1987 .

[2]  John R. Moore.  Differences in maximum resistive bending moments of Pinus radiata trees grown on a range of soil types. , 2000 .

[3]  M. Watts,et al.  Mechanical stability of black spruce in the clay belt region of northern Ontario , 1987 .

[4]  Genevieve Patenaude,et al.  The Estimation of Wind Risk in Forests Stands using Airborne Laser Scanning (ALS)( Silvilaser) , 2008 .

[5]  C. Ung,et al.  Comparing height growth and biomass production of black spruce trees in logged and burned stands , 2004 .

[6]  H. Peltola,et al.  A mechanistic model for calculating windthrow and stem breakage of Scots pines at stand age. , 1993 .

[7]  B. Gardiner,et al.  Modelling the windthrow risk for simulated forest stands of Maritime pine (Pinus pinaster Ait.) , 2005 .

[8]  Peter L. Jackson,et al.  Comparison of wind speeds obtained using numerical weather prediction models and topographic exposure indices for predicting windthrow in mountainous terrain , 2008 .

[9]  J. Grace,et al.  Wind and Trees: Tree physiological responses , 1995 .

[10]  D. C. van der Werf,et al.  Introducing tree interactions in wind damage simulation , 2007 .

[11]  J. Suarez,et al.  Estimating windthrow risk in balsam fir stands with the ForestGales model , 2000 .

[12]  Stephen E. Belcher,et al.  Flow over a hill covered with a plant canopy , 2004 .

[13]  S. Mitchell.  A diagnostic framework for windthrow risk estimation , 1998 .

[14]  C. Quine,et al.  Revised windiness scores for the windthrow hazard classification: the revised scoring method , 1992 .

[15]  Jean-Claude Ruel,et al.  Windthrow hazard modelling in boreal forests of black spruce and jack pine , 2005 .

[16]  Yves Brunet,et al.  Impact of forest edge shape on tree stability: a large-eddy simulation study , 2008 .

[17]  Stanley A. Changnon,et al.  Factors affecting temporal fluctuations in damaging storm activity in the United States based on insurance loss data , 1999 .

[18]  Heikki Hänninen,et al.  Sima: a model for forest succession based on the carbon and nitrogen cycles with application to silvicultural management of the forest ecosystem , 1992 .

[19]  Barry Gardiner,et al.  4 - Understanding how the interaction of wind and trees results in wind-throw, stem break-age, and canopy gap formation , 2007 .

[20]  H. Peltola,et al.  Mechanical stability of trees under static loads. , 2006, American journal of botany.

[21]  J. Finnigan.  2 – The Turbulent Wind in Plant and Forest Canopies , 2007 .

[22]  Uldis Silins,et al.  Measure of simultaneous tree sways and estimation of crown interactions among a group of trees , 2001, Trees.

[23]  J. Hunt,et al.  Turbulent wind flow over a low hill , 1975 .

[24]  Sophie E. Hale,et al.  Biomass expansion factors and root: shoot ratios for coniferous tree species in Great britain , 2004 .

[25]  Stephen J. Mitchell,et al.  Portability of stand-level empirical windthrow risk models , 2005 .

[26]  Alexis Achim,et al.  Modelling the vulnerability of balsam fir forests to wind damage , 2005 .

[27]  C. Bergeron.  Modélisation du chablis en pessières régulières et irrégulières : effet de la diversité structurale des pessières noires boréales sur la résistance et la susceptibilité au chablis , 2007 .

[28]  S. Mitchell,et al.  Overturning resistance of western redcedar and western hemlock in mixed-species stands in coastal British Columbia , 2007 .

[29]  B. Gardiner,et al.  Does steep terrain influence tree stability? A field investigation , 2005 .

[30]  Jonas Fridman,et al.  Modelling probability of snow and wind damage in Scots pine stands using tree characteristics , 1997 .

[31]  F. Telewski,et al.  Wind and Trees: Wind-induced physiological and developmental responses in trees , 1995 .

[32]  Alexis Achim,et al.  Résistance comparée de l'épinette blanche et du sapin baumier au renversement , 2002 .

[33]  R. Shaw,et al.  Wind loading on trees across a forest edge : A large eddy simulation , 2006 .

[34]  Christopher P. Quine,et al.  Monitoring of windthrow occurrence and progression in spruce forests in Britain , 1998 .

[35]  Stephen J. Mitchell,et al.  Wind tunnel measurements of crown streamlining and drag relationships for three conifer species , 2004 .

[36]  S. Dupont,et al.  Influence of foliar density profile on canopy flow: A large-eddy simulation study , 2008 .

[37]  E. Johnson,et al.  Plant Disturbance Ecology: The Process and the Response , 2007 .

[38]  H. Peltola,et al.  A mechanistic model for assessing the risk of wind and snow damage to single trees and stands of Scots pine, Norway spruce, and birch , 1999 .

[39]  Ari Venäläinen,et al.  Simulations of the influence of clear-cutting on the risk of wind damage on a regional scale over a 20-year period , 2006 .

[40]  Ola Sallnäs,et al.  WINDA—a system of models for assessing the probability of wind damage to forest stands within a landscape , 2004 .

[41]  S. A. Neild,et al.  Estimating stem and root-anchorage flexibility in trees. , 1999, Tree physiology.

[42]  Barry Gardiner,et al.  A prism-based system for monitoring the swaying of trees under wind loading , 1998 .

[43]  Timo Pukkala,et al.  The use of heuristic optimization in risk management of wind damage in forest planning , 2007 .

[44]  T. Andrew Black,et al.  Modelling the effect of mean pressure gradient on the mean flow within forests , 1994 .

[45]  Barry Gardiner,et al.  Wind flows and forces in a model spruce forest , 1994 .

[46]  G. J. Mayhead,et al.  Some drag coefficients for British forest trees derived from wind tunnel studies , 1973 .

[47]  Ari Venäläinen,et al.  Simulations of the influence of forest management on wind climate on a regional scale , 2004 .

[48]  Hongcheng Zeng,et al.  A GIS-based decision support system for risk assessment of wind damage in forest management , 2007, Environ. Model. Softw..

[49]  John R Moore,et al.  Simulating the dynamic behavior of Douglas-fir trees under applied loads by the finite element method. , 2008, Tree physiology.

[50]  Petri Pellikka,et al.  FOREST STAND CHARACTERISTICS AND WIND AND SNOW INDUCED FOREST DAMAGE IN BOREAL FOREST , 2003 .

[51]  Heli Peltola,et al.  Integration of component models from the tree, stand and regional levels to assess the risk of wind damage at forest margins , 2000 .

[52]  Stephen J. Mitchell,et al.  Empirical modelling of windthrow risk in partially harvested stands using tree, neighbourhood, and stand attributes , 2005 .

[53]  C. Quine.  Estimation of mean wind climate and probability of strong winds for wind risk assessment. , 2000 .

[54]  Guillaume Cornu,et al.  CAPSIS: Computer-aided projection for strategies in silviculture : Advantages of a shared forest-modelling platform , 2002 .

[55]  上村 佳奈.  Developing a decision-support system for wind risk modelling as a part of forest management in Japan , 2007 .

[56]  Ari Venäläinen,et al.  Influence of clear-cutting on the risk of wind damage at forest edges , 2004 .

[57]  H. Peltola,et al.  Mechanical stability of Scots pine, Norway spruce and birch: an analysis of tree-pulling experiments in Finland , 2000 .

[58]  Barry Gardiner,et al.  Developing a decision support approach to reduce wind damage risk - a case study on sugi ( Cryptomeria japonica (L.f.) D.Don) forests in Japan , 2008 .

[59]  Kenneth Earl Byrne.  Critical turning moments and drag equations for British Columbia conifers , 2005 .

[60]  B. Gardiner,et al.  Comparison of two models for predicting the critical wind speeds required to damage coniferous trees , 2000 .

[61]  B. Courbaud,et al.  Development of an individual tree-based mechanical model to predict wind damage within forest stands , 2004 .

[62]  H. R. Oliver,et al.  Wind Measurements in a Pine Forest During a Destructive Gale , 1974 .

[63]  T. Fourcaud,et al.  A finite element model for investigating effects of aerial architecture on tree oscillations. , 2006, Tree physiology.

[64]  B. Gardiner,et al.  Anchorage of coniferous trees in relation to species, soil type, and rooting depth , 2006 .

[65]  B. Gardiner,et al.  The stability of different silvicultural systems: a wind-tunnel investigation , 2005 .

[66]  B. Gardiner,et al.  Field and wind tunnel assessments of the implications of respacing and thinning for tree stability , 1997 .