Integrating a new version of the wind risk model ForestGALES with GIS to facilitate scientific collaboration and improving multi-purpose forest management

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I moved to Scotland from Italy in 2005. I completed my PhD at the University of Edinburgh with a thesis on the development and behaviour of the wind-risk model ForestGALES, followed by a PostDoc for the EU OPERAs project. I currently work at Forest Research as a Climate Change Researcher on forest adaptation. I will be travelling to EFIATLANTIC in Bordeaux thanks to the EFI SSV Grant to work on further developments of the ForestGALES model.

Tommaso Locatelli (Northern Research Station, Forest Research) will be hosted by Prof. Barry Gardiner (EFIATLANTIC).

The overall objective of the project is to improve the accuracy, applicability, flexibility and reliability of wind risk evaluation in forests as part of multi-risk analysis. This will be done by combining the latest, most dynamic version of the ForestGALES wind-risk model written in R, with the open-source GIS software Quantum GIS (QGIS). Pontenx forest in the south-west area of Aquitaine in France will be used as a test case because it is already well mapped and described as part of the INTEGRAL project. The overarching objective can be broken down into smaller aims: (a) Translating the ‘Turning Moment Coefficient’ (TMC) version of the wind risk model ForestGALES in the free and open source R language; (b) Coupling the R version of ForestGALES TMC (FG_R) with QGIS, a free and open source GIS software; (c) Using silvicultural, environmental, weather and topographical data from the Pontenx forest to test the functionality of FG_R and its coupling with QGIS; and (d) Producing interactive, dynamic maps of wind risk in the forest under different silvicultural treatments.

Following previous work of translating the traditional wind risk calculation method of ForestGALES from versions written in Delphi and Java into R, ForestGALES TMC will be similarly translated into R. Digital Elevation Models (freely available from USGS, and already obtained for the area) and forest and soil inventory data (already obtained by Prof. Gardiner) will be used to produce elevation and roughness maps of the area. These maps will be combined with weather data for the forest (from the Infoclimat network and Meteo France) in the WAsP (Wind Atlas Analysis and Application Program) software to generate maps of the two parameters of the distributions of wind speed and direction (Weibull-A and k) required by FG_R to model the wind climate of the area. Some growth models for the most commonly planted species in the area – maritime pine (Pinus pinaster) and oak (Quercus spp.) and of trial species of potential commercial importance (Eucalyptus spp.) are already available. Others will be obtained from contacts at INRA and from the literature. These will be used to simulate tree growth for use with FG_R, and will be combined with the spatial information on the geographical distributions of species and management practices in the project area to create spatial wind damage risk assessments with the FG_R–QGIS coupling. The resulting dynamic and interactive wind risk maps for present conditions and possible future alternatives will be used as the basis for writing a wind risk assessment report for Pontenx forest. The report will also illustrate the lessons learned from the coupling exercise, and the potential for application at larger scales and in different environments.