Representativeness assessment of the pan-Arctic eddy covariance site network and optimized future enhancements

Abstract

Abstract. Large changes in the Arctic carbon balance are expected as warming linked to climate change threatens to destabilize ancient permafrost carbon stocks. The eddy covariance (EC) method is an established technique to quantify net losses and gains of carbon between the biosphere and atmosphere at high spatiotemporal resolution. Over the past decades, a growing network of terrestrial EC tower sites has been established across the Arctic, but a comprehensive assessment of the network's representativeness within the heterogeneous Arctic region is still lacking. This creates additional uncertainties when integrating flux data across sites, for example when upscaling fluxes to constrain pan-Arctic carbon budgets and changes therein. This study provides an inventory of Arctic (here > = 60∘ N) EC sites, which has also been made available online (https://cosima.nceas.ucsb.edu/carbon-flux-sites/, last access: 25 January 2022). Our database currently comprises 120 EC sites, but only 83 are listed as active, and just 25 of these active sites remain operational throughout the winter. To map the representativeness of this EC network, we evaluated the similarity between environmental conditions observed at the tower locations and those within the larger Arctic study domain based on 18 bioclimatic and edaphic variables. This allows us to assess a general level of similarity between ecosystem conditions within the domain, while not necessarily reflecting changes in greenhouse gas flux rates directly. We define two metrics based on this representativeness score: one that measures whether a location is represented by an EC tower with similar characteristics (ER1) and a second for which we assess if a minimum level of representation for statistically rigorous extrapolation is met (ER4). We find that while half of the domain is represented by at least one tower, only a third has enough towers in similar locations to allow reliable extrapolation. When we consider methane measurements or year-round (including wintertime) measurements, the values drop to about 1/5 and 1/10 of the domain, respectively. With the majority of sites located in Fennoscandia and Alaska, these regions were assigned the highest level of network representativeness, while large parts of Siberia and patches of Canada were classified as underrepresented. Across the Arctic, mountainous regions were particularly poorly represented by the current EC observation network. We tested three different strategies to identify new site locations or upgrades of existing sites that optimally enhance the representativeness of the current EC network. While 15 new sites can improve the representativeness of the pan-Arctic network by 20 %, upgrading as few as 10 existing sites to capture methane fluxes or remain active during wintertime can improve their respective ER1 network coverage by 28 % to 33 %. This targeted network improvement could be shown to be clearly superior to an unguided selection of new sites, therefore leading to substantial improvements in network coverage based on relatively small investments.

Carbon uptake in Eurasian boreal forests dominates the high‐latitude net ecosystem carbon budget

“…Eurasia contributed to a majority (74%) of the boreal NEE sink, and the largest CO 2 sink by area was observed in the larch‐dominated East Siberian Taiga. Although the geographically extensive Eastern Siberian Taiga remains largely underrepresented by EC tower monitoring sites (Pallandt et al, 2022), this region has been identified as an important, perhaps increasing, carbon sink (Byrne, Liu, et al, 2022; Lin et al, 2020; Sato et al, 2016; Schulze, 2006). However, elevated fire activity here in recent years (post‐2015) (Veraverbeke et al, 2021) might now be offsetting more of the carbon uptake.…”

Reviews and syntheses: Recent advances in microwave remote sensing in support of arctic-boreal carbon cycle science

“…scale, ABR are notoriously underrepresented in this network (Fig. 1; Baldocchi et al, 2001;Pastorello et al, 2020;Pallandt et al, 2022). Satellite remote sensing and terrestrial biosphere models show promise for monitoring land surface-atmosphere interactions across ABR (Fisher et al, 2018;Lees et al, 2018).…”

“…However, spaceborne visible and infrared radiometers are affected by signal degradation from atmospheric effects, have minimal signal penetration depth in vegetation, and depend on solar illumination meaning they are restricted to daytime, clear sky observations (Kim et al, 2012). 90 (Brown et al, 2002) and distribution of eddy covariance sites where ecosystem fluxes are monitored continuously (Baldocchi et al, 2001 andPallandt et al, 2022; dot size represents the number of years of available data). The Arctic biome is delineated following the Conservation of Arctic Flora and Fauna working group of 95 the Arctic Council and the boreal biome is delineated following Potapov et al (2008).…”

Using atmospheric observations to quantify annual biogenic carbon dioxide fluxes on the Alaska North Slope

“…In a more recent study, Tao et al (2021) found an annual net CO 2 flux range of -9 to 12 TgC yr -1 for the years 2010-2016, with only 2014 being an annual net CO 2 source. Extrapolating from sitelevel CO 2 flux measurements to regional budgets is difficult due to the extreme heterogeneity of tundra ecosystems in the North Slope and a lack of spatial and seasonal representativeness by existing flux monitoring sites (Pallandt et al, 2022).…”