Biophysical Determinants of Shifting Tundra Vegetation Productivity in the Beaufort Delta Region of Canada

• Published in: Ecosystems
• Main Authors: Seider, Jordan H., Lantz, Trevor C., Hermosilla, Txomin, Wulder, Michael A., Wang, Jonathan A.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Springer Science and Business Media LLC 2022
• Subjects: Ecology; Environmental Chemistry; Ecology, Evolution, Behavior and Systematics; Canada; Tuktoyaktuk; Yukon; Tundra
• Online Access: http://dx.doi.org/10.1007/s10021-021-00725-6; https://link.springer.com/content/pdf/10.1007/s10021-021-00725-6.pdf; https://link.springer.com/article/10.1007/s10021-021-00725-6/fulltext.html

Abstract Temperature increases across the circumpolar north have driven rapid increases in vegetation productivity, often described as ‘greening’. These changes have been widespread, but spatial variation in their pattern and magnitude suggests that biophysical factors also influence the response of tundra vegetation to climate warming. In this study, we used field sampling of soils and vegetation and random forests modeling to identify the determinants of trends in Landsat-derived Enhanced Vegetation Index, a surrogate for productivity, in the Beaufort Delta region of Canada between 1984 and 2016. This region has experienced notable change, with over 71% of the Tuktoyaktuk Coastlands and over 66% of the Yukon North Slope exhibiting statistically significant greening. Using both classification and regression random forests analyses, we show that increases in productivity have been more widespread and rapid at low-to-moderate elevations and in areas dominated by till blanket and glaciofluvial deposits, suggesting that nutrient and moisture availability mediate the impact of climate warming on tundra vegetation. Rapid greening in shrub-dominated vegetation types and observed increases in the cover of low and tall shrub cover (4.8% and 6.0%) also indicate that regional changes have been driven by shifts in the abundance of these functional groups. Our findings demonstrate the utility of random forests models for identifying regional drivers of tundra vegetation change. To obtain additional fine-grained insights on drivers of increased tundra productivity, we recommend future research combine spatially comprehensive time series satellite data (as used herein) with samples of high spatial resolution imagery and integrated field investigations.