Potential impact of climate change on the risk of windthrow in eastern Canada’s forests

Christian Saad, Yan Boulanger (), Marilou Beaudet, Philippe Gachon, Jean-Claude Ruel and Sylvie Gauthier
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Christian Saad: Université du Québec à Montréal
Yan Boulanger: Laurentian Forestry Centre
Marilou Beaudet: Laurentian Forestry Centre
Philippe Gachon: Laurentian Forestry Centre
Jean-Claude Ruel: Université Laval
Sylvie Gauthier: Laurentian Forestry Centre

Climatic Change, 2017, vol. 143, issue 3, No 15, 487-501

Abstract: Abstract Climate change is likely to affect windthrow risks at northern latitudes by potentially changing high wind probabilities and soil frost duration. Here, we evaluated the effect of climate change on windthrow risk in eastern Canada’s balsam fir (Abies balsamea [L.] Mill.) forests using a methodology that accounted for changes in both wind speed and soil frost duration. We used wind speed and soil temperature projections at the regional scale from the CRCM5 regional climate model (RCM) driven by the CanESM2 global climate model (GCM) under two representative concentration pathways (RCP4.5, RCP8.5), for a baseline (1976–2005) and two future periods (2041–2070, 2071–2100). A hybrid mechanistic model (ForestGALES) that considers species resistance to uprooting and wind speed distribution was used to calculate windthrow risk. An increased risk of windthrow (3 to 30%) was predicted for the future mainly due to an increased duration of unfrozen soil conditions (by up to 2 to 3 months by the end of the twenty-first century under RCP8.5). In contrast, wind speed did not vary markedly with a changing climate. Strong regional variations in wind speeds translated into regional differences in windthrow risk, with the easternmost region (Atlantic provinces) having the strongest winds and the highest windthrow risk. Because of the inherent uncertainties associated with climate change projections, especially regarding wind climate, further research is required to assess windthrow risk from the optimum combination of RCM/GCM ensemble simulations.

Date: 2017
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DOI: 10.1007/s10584-017-1995-z

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