Journal
ENVIRONMENTAL MODELLING & SOFTWARE
Volume 68, Issue -, Pages 27-41Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.envsoft.2015.01.016
Keywords
Risk modelling; Decision support system; Wind damage; Forest disturbance; Mechanistic modelling; Validation
Categories
Funding
- Corporate and Forestry Support, Forestry Commission, Great Britain
- INRA Scientific Package
- NERC [NE/I022183/1] Funding Source: UKRI
- Natural Environment Research Council [NE/I022183/1, ceh010010] Funding Source: researchfish
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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. Crown Copyright (C) 2015 Published by Elsevier Ltd.
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