4.2 Article

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

Journal

ARCTIC ANTARCTIC AND ALPINE RESEARCH
Volume 52, Issue 1, Pages 248-263

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/15230430.2020.1750805

Keywords

Carbon dioxide exchange; net ecosystem exchange (NEE); normalized difference vegetation index (NDVI); Arctic

Funding

  1. Polar Continental Shelf Program
  2. Northern Scientific Training Program
  3. Natural Sciences and Engineering Research Council of Canada (NSERC) [388581]

Ask authors/readers for more resources

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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.2
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available