High spatial resolution remote sensing models for landscape-scale CO₂ exchange in the Canadian Arctic

• Published in: Arctic, antarctic, and alpine research antarctic, and alpine research, 2020-01, Vol.52 (1), p.248-263
• Main Authors: Atkinson, David M., Hung, Jacqueline K. Y., Gregory, Fiona M., Scott, Neal A., Treitz, Paul M.
• Format: Article
• Language: English
• Subjects: Arctic; Arctic climates; Atmospheric models; Bivariate analysis; Carbon dioxide; Carbon dioxide atmospheric concentrations; Carbon dioxide exchange; Carbon dioxide variations; Climate change; Climate models; Data acquisition; Ecosystems; Environment models; Fluxes; Foreign exchange rates; Geographical locations; Global warming; Growing season; Landscape; Moisture gradient; net ecosystem exchange (NEE); normalized difference vegetation index (NDVI); Normalized difference vegetative index; Remote sensing; Satellite data; Spatial discrimination; Spatial resolution; Statistical analysis; Structure-function relationships; Terrestrial ecosystems; Vegetation; Vegetation index; Vegetation type
• ISSN: 1523-0430; 1938-4246
• DOI: 10.1080/15230430.2020.1750805

Climate warming is affecting terrestrial ecosystems in the Canadian Arctic, potentially altering the carbon balance of the landscape and contributing additional CO 2 to the atmosphere. High spatial resolution remote sensing data can enhance models of net ecosystem exchange (NEE) and its component fluxes, gross ecosystem exchange (GEE), and ecosystem respiration (ER) by quantifying vegetation structure and function over time. In this study, we explored the variability of daytime CO 2 exchange rates for three vegetation types along a natural moisture gradient at ecologically distinct mid- and high Arctic sites. We demonstrated that for the two sites studied, there was no statistically significant variation in CO 2 exchange rates for the vegetation types through the peak growing season. Hence, the capacity to model these rates with a limited number of satellite data acquisitions is feasible. Simple bivariate models relating the Normalized Difference Vegetation Index (NDVI) to CO 2 exchange processes (GEE, ER, and NEE) were developed independent of vegetation type and geographic location and validated using independent data. The spectral models explain between 33 and 94 percent of the variation in CO 2 exchange rates at each site, indicating a high level of functional convergence in ecosystem-level structure and function within Arctic landscapes.