Predicting the probability of wind damage in both natural and managed forests is important for understanding forest ecosystem functioning the environmental impact of storms and for forest risk management . We undertook a thorough validation of three versions of the hybrid mechanistic wind risk model ForestGALES and a statistical logistic regression model against observed damage in a Scottish upland conifer forest following a major storm . Statistical analysis demonstrated that increasing tree height and local wind speed during the storm were the main factors associated with increased damage levels . All models provided acceptable discrimination between damaged and undamaged forest stands but there were trade offs between the accuracy of the mechanistic models and model bias . The two versions of the mechanistic model with the lowest bias gave very comparable overall results at the forest scale and could form part of a decision support system for managing forest wind damage risk . Maximum width of canopy Length of the live crown Drag coefficient scale parameter Drag coefficient Regression between stem weight and resistance to overturning Critical wind speed for damage Zero plane displacement Stem diameter at base of tree Stem diameter at breast height Average spacing between trees Windiness score from Quine and White Dimensionless factor to account for additional turning moment due to crown and stem weight Dimensionless factor to account for reduction in clear wood MOR due to knots Dimensionless factor to account for gustiness of wind Tree height von Karman constant 0.4 Maximum turning moment due to wind loading only and not including additional moment due to overhanging crown and stem Modulus of rupture on wood for species of interest Parameter controlling reduction in drag coefficient with wind speed Density of air Forestry Commission sub compartment database Ratio of average tree spacing after and before a thinning Stem weight Turning moment coefficient from Hale et al . Ratio of turning moment coefficient after and before thinning Wind speed at 10 m above the zero plane displacement height Wind speed at tree height Friction velocity Weibull scale parameter Weibull shape parameter Wind speed calculated from DAMS score Wind speed calculated from WAsP airflow model Wind speed at meteorological station Distance from forest edge Yield class Aerodynamic roughness Name of software ForestGALES Developers Forest Research and INRA Contact address Forest Research Northern Research Station Roslin Midlothian EH25 9SY United Kingdom Email forestgales.support @ forestry.gsi.gov.uk Availability and Online Documentation The software along with supporting material is freely available . Go to http www.forestresearch.gov.uk forestgales to find out how to obtain the software or email forestgales.support @ forestry.gsi.gov.uk Year first available 2000 Hardware required IBM compatible PC Software required MS Windows Programming language Borland Delphi 5.0 . Versions have also been written in Python Fortran R and Java . Contact the corresponding author for further details . Program size 10 MB . With all additional support files and manuals 25 MB . 


Summary: Comprehensive description and validation of three versions of a mechanistic wind risk model for even aged forests. Analysis of the performance of mechanistic and logistic regression models against measured damage in a conifer forest. All models provided acceptable discrimination between damaged and undamaged forest stands. The two version of the mechanistic model with the lowest bias gave very comparable overall results at the forest scale. Statistical analysis showed that increasing tree height and local wind speed were the main factors associated with damage.