Biophysical controls of increased tundra productivity in the western Canadian Arctic

• Published in: Remote Sensing of Environment
• Main Authors: Chen, Angel, Lantz, Trevor C., Hermosilla, Txomin, Wulder, Michael A.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Remote Sensing of Environment 2021
• Subjects: Landsat; Random Forests; Arctic tundra; Greening; EVI; Vegetation indices; Climate change; Arctic; Canada; Arctic Institute of North America; The Arctic Institute; Tundra
• Online Access: http://hdl.handle.net/1828/12770; https://doi.org/10.1016/j.rse.2021.112358

Rapid climate warming has widely been considered as the main driver of recent increases in Arctic tundra productivity. Field observations and remote sensing both show that tundra “greening” has been widespread, but heterogeneity in regional and landscape-scale trends suggest that additional controls are mediating the response of tundra vegetation to warming. In this study, we examined the relationship between changes in vegetation productivity in the western Canadian Arctic and biophysical variables by analyzing trends in the Enhanced Vegetation Index (EVI) obtained from nonparametric regression of annual Landsat surface reflectance composites. We used Random Forests classification and regression tree modelling to predict the trajectory and magnitude of greening from 1984 to 2016 and identify biophysical controls. More than two-thirds of our study area showed statistically significant increases in vegetation productivity, but observed changes were heterogeneous, occurring most rapidly within areas of the Southern Arctic that were: (1) dominated by dwarf and upright shrub cover types, (2) moderately sloping, and (3) located at lower elevation. These findings suggest that the response of tundra vegetation to warming is mediated by regional- and landscape-scale variation in microclimate, topography and soil moisture, and physiological differences among plant functional groups. Our work highlights the potential of the joint analysis of annual remotely sensed vegetation indices and broad-scale biophysical data to understand spatial variation in tundra vegetation change. This research was funded by the Natural Sciences and Engineering Research Council of Canada (RGPIN 06210-2018: TCL), the University of Victoria, the Arctic Institute of North America (Lorraine Allison Scholarship: AC), the Northern Scientific Training Program and the Polar Continental Shelf Program. Data processing and analysis was partially enabled by the computational capabilities provided by WestGrid (www.westgrid.ca) and Compute Canada ...