Paper Info
Title
Projected Wind Impact on Abies balsamea (Balsam fir)-Dominated Stands in New Brunswick (Canada) Based on Remote Sensing and Regional Modelling of Climate and Tree Species Distribution.
Abstract
The paper describes the development of predictive equations of windthrow for five tree species based on remote sensing of wind-affected stands in southwestern New Brunswick (NB). The data characterises forest conditions before, during and after the passing of extratropical cyclone Arthur, July 4-5, 2014. The five-variable logistic function developed for balsam fir (bF) was validated against remote-sensing-acquired windthrow data for bF-stands affected by the Christmas Mountains windthrow event of November 7, 1994. In general, the prediction of windthrow in the area agreed fairly well with the windthrow sites identified by photogrammetry. The occurrence of windthrow in the Christmas Mountains was prominent in areas with shallow soils and prone to localised accelerations in mean and turbulent airflow. The windthrow function for bF was subsequently used to examine the future impact of windthrow under two climate scenarios (RCP's 4.5 and 8.5) and species response to local changes anticipated with global climate change, particularly with respect to growing degree-days and soil moisture. Under climate change, future windthrow in bF stands (2006-2100) is projected to be modified as the species withdraws from the high-elevation areas and NB as a whole, as the climate progressively warms and precipitation increases, causing the growing environment of bF to deteriorate.
Year
DOI
Venue
2020
10.3390/rs12071177
REMOTE SENSING
Keywords
DocType
Volume
computational fluid dynamics,genetic programming-based logistic regression,landscape scale,wind gusts,photointerpretation,regional climate modelling and analysis,species shifts
Journal
12
Issue
Citations 
PageRank 
7
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Charles P.-A. Bourque100.34
Philippe Gachon200.34
Benjamin R. MacLellan300.34
James I. MacLellan400.34