AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (4.6 MB)
Collect
AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article | Open Access

Large-scale modelling wind damage vulnerability through combination of high-resolution forest resources maps and ForestGALES

Morgane Merlina( )Tommaso LocatellibBarry Gardinerb,c,dRasmus Astrupa
Norwegian Institute for Bioeconomy Research (NIBIO), Division of Forestry and Forest Resources, Department of Forest Management, Høgskoleveien 8, 1433 Ås, Norway
Forest Research, Northern Research Station, Roslin, Scotland, United Kingdom
Institut Européen De La Forêt Cultivée, Cestas, France
Department of Forestry Economics and Forest Planning, Albert-Ludwigs-University Freiburg, Freiburg Im Breisgau, Germany

Peer review under the responsibility of Editorial Office of Forest Ecosystems.

Show Author Information

Abstract

Assessing forest vulnerability to disturbances at a high spatial resolution and for regional and national scales has become attainable with the combination of remote sensing-derived high-resolution forest maps and mechanistic risk models. This study demonstrated large-scale and high-resolution modelling of wind damage vulnerability in Norway. The hybrid mechanistic wind damage model, ForestGALES, was adapted to map the critical wind speeds (CWS) of damage across Norway using a national forest attribute map at a 16 ​m ​× ​16 ​m spatial resolution. Parametrization of the model for the Norwegian context was done using the literature and the National Forest Inventory data. This new parametrization of the model for Norwegian forests yielded estimates of CWS significantly different from the default parametrization. Both parametrizations fell short of providing acceptable discrimination of the damaged area following the storm of November 19, 2021 in the central southern region of Norway when using unadjusted CWS. After adjusting the CWS and the storm wind speeds by a constant factor, the Norwegian parametrization provided acceptable discrimination and was thus defined as suitable to use in future studies, despite the lack of field- and laboratory experiments to directly derive parameters for Norwegian forests. The windstorm event used for model validation in this study highlighted the challenges of predicting wind damage to forests in landscapes with complex topography. Future studies should focus on further developing ForestGALES and new datasets describing extreme wind climates to better represent the wind and tree interactions in complex topography, and predict the level of risk in order to develop local climate-smart forest management strategies.

References

【1】
【1】
 
 
Forest Ecosystems

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Merlin M, Locatelli T, Gardiner B, et al. Large-scale modelling wind damage vulnerability through combination of high-resolution forest resources maps and ForestGALES. Forest Ecosystems, 2025, 14(1). https://doi.org/10.1016/j.fecs.2025.100361

72

Views

1

Downloads

5

Crossref

4

Web of Science

4

Scopus

0

CSCD

Received: 22 March 2025
Revised: 23 May 2025
Accepted: 12 June 2025
Published: 01 October 2025
© 2025 The Authors.

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).