Net ecosystem exchange of CO₂ with rapidly changing high Arctic landscapes

Abstract

High Arctic landscapes are expansive and changing rapidly. However, our understanding of their functional responses and potential to mitigate or enhance anthropogenic climate change is limited by few measurements. We collected eddy covariance measurements to quantify the net ecosystem exchange (NEE) of CO2 with polar semidesert and meadow wetland landscapes at the highest latitude location measured to date (82°N). We coupled these rare data with ground and satellite vegetation production measurements (Normalized Difference Vegetation Index; NDVI) to evaluate the effectiveness of upscaling local to regional NEE. During the growing season, the dry polar semidesert landscape was a near-zero sink of atmospheric CO2 (NEE: -0.3 ± 13.5 g C m(-2) ). A nearby meadow wetland accumulated over 300 times more carbon (NEE: -79.3 ± 20.0 g C m(-2) ) than the polar semidesert landscape, and was similar to meadow wetland NEE at much more southerly latitudes. Polar semidesert NEE was most influenced by moisture, with wetter surface soils resulting in greater soil respiration and CO2 emissions. At the meadow wetland, soil heating enhanced plant growth, which in turn increased CO2 uptake. Our upscaling assessment found that polar semidesert NDVI measured on-site was low (mean: 0.120-0.157) and similar to satellite measurements (mean: 0.155-0.163). However, weak plant growth resulted in poor satellite NDVI-NEE relationships and created challenges for remotely detecting changes in the cycling of carbon on the polar semidesert landscape. The meadow wetland appeared more suitable to assess plant production and NEE via remote sensing; however, high Arctic wetland extent is constrained by topography to small areas that may be difficult to resolve with large satellite pixels. We predict that until summer precipitation and humidity increases enough to offset poor soil moisture retention, climate-related changes to productivity on polar semideserts may be restricted.

Spatial variation and linkages of soil and vegetation in the Siberian Arctic tundra – coupling field observations with remote sensing data

“…Contrary to our expectations and earlier findings (Suvanto et al, 2014;Emmerton et al, 2016;Riihimäki et al, 2017), topographical features could not enhance the capture of spatial variation in plant and soil properties above the level 30 achieved by NDVI when the timing of the satellite image was appropriate for the examined attribute (e.g. late-season image for capturing variation in LAI).…”

Mapping Arctic Tundra Vegetation Communities Using Field Spectroscopy and Multispectral Satellite Data in North Alaska, USA

“…The improved performance when including VIs in this study is especially useful in regards to monitoring plant productivity and ecosystem functioning. It has been shown previously [82,83] that NDVI can be linked heavily with net ecosystem exchange (NEE) [84,85] and CH 4 fluxes [25] for example. NDVI can be highly correlated with vegetation leaf area index (LAI), but also is invariant at higher LAI ranges and can be very sensitive to background variations in vegetation communities such as background soil and water [8].…”

Assessing the dynamics of vegetation productivity in circumpolar regions with different satellite indicators of greenness and photosynthesis

“…7). At the site-level, gas flux measurements find a similar timing of maximum GPP in the first half/mid-July (Emmerton et al, 2016) and at the time of the annual temperature peak (Kross et al, 2014;Welker et al, 2004). Similarly for Lafleur and Humphreys (2008) who report on largest annual site-level NEE after summer solstice near the annual temperature maximum between DOYs190-210 and a dominant role of GEP in driving these dynamics.…”

“…The results of our study confirm the important separation between indicators of greenness and photosynthesis and non-negligible differences between data sets of the same indicators. Upon data availability in the future, similar cross-comparisons to the chlorophyll-carotenoid 20 index (Gamon et al, 2016) and the photochemical reflectance index (Gamon et al, 1992) Tuovinen, J.-P., Aurela, M., Hatakka, J., Räsänen, A., Virtanen, T., Mikola, J., Ivakhov, V., Kondratyev, V., and Laurila, T.: Interpreting eddy covariance data from heterogeneous Siberian tundra: land cover-specific methane fluxes and spatial representativeness, Biogeosciences Figure 1. ESA CCI land cover in regions with less than 5% tree cover according to Hansen et al (2013).…”