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

Abstract

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.

A High Spatial Resolution Satellite Remote Sensing Time Series Analysis of Cape Bounty, Melville Island, Nunavut (2004–2018)

“…Though additional images within the growing season would likely add more nuance and clarity to the maximum NDVI (potentially by vegetation type), given that the growing season in the High Arctic is short and often cloudy, the lack of any trend in NDVI by day of acquisition within the growing season suggests that a single high spatial resolution optical data can be used with some level of confidence in a time series analysis. Similarly, Atkinson et al (2020) found that NDVI derived from a single peak growing season IKONOS image could successfully model CO 2 exchange rates at landscape scales for the CBAWO.…”

“…Additionally, the scar zones have been shown to have different ecosystem exchange and respiration rates than the surrounding undisturbed areas (Beamish et al 2014). As permafrost disturbances become more widespread in the High Arctic, tracking them, regardless of size, may help inform carbon sequestration and release models (e.g., Atkinson et al 2020).…”

Interannual Variability of Summer Net Ecosystem CO2 Exchange in High Arctic Tundra

“…Atkinson et al. (2020) also found satellite‐derived NDVI (at a 4 m resolution) was able to explain spatial differences in the CBAWO daytime summer NEE and its component fluxes, GPP and R eco . In that study, fluxes were measured using static chambers across multiple vegetation communities, including less productive dry and mesic tundra where NDVI varied from approximately 0.05 to 0.25.…”

“…These successful relationships between satellite‐derived NDVI and CO 2 exchange processes at CBAWO likely reflect multiple factors that influence vegetation productivity. Across the CBAWO, spatial patterns in vegetation are organized along a seasonal moisture gradient (Atkinson et al., 2020) as they are in many other High and Low Arctic landscapes (Emmerton et al., 2016; Sjögersten et al., 2006; Walker et al., 2005). Soil moisture could influence interannual patterns in NEE as well and at the CBAWO, summer net CO 2 uptake significantly increased with precipitation.…”