Microscale drivers of summer CO2 fluxes in the Svalbard High Arctic tundra

High-Arctic ecosystems are strongly affected by climate change, and it is still unclear whether they will become a carbon source or sink in the next few decades. In turn, such knowledge gaps on the drivers and the processes controlling CO2 fluxes and storage make future projections of the Arctic carbon budget a challenging goal. During summer 2019, we extensively measured CO2 fluxes at the soil–vegetation–atmosphere interface, together with basic meteoclimatic variables and ecological characteristics in the Bayelva river basin near Ny Ålesund, Spitzbergen, Svalbard (NO). By means of multi-regression models, we identified the main small-scale drivers of CO2 emission (Ecosystem Respiration, ER), and uptake (Gross Primary Production, GPP) in this tundra biome, showing that (i) at point scale, the temporal variability of fluxes is controlled by the classical drivers, i.e. air temperature and solar irradiance respectively for ER and GPP, (ii) at site scale, the heterogeneity of fractional vegetation cover, soil moisture and vegetation type acted as additional source of variability for both CO2 emissions and uptake. The assessment of the relative importance of such drivers in the multi-regression model contributes to a better understanding of the terrestrial carbon dioxide exchanges and of Critical Zone processes in the Arctic tundra.

Remote study of thermokarst lakes in the arctic tundra of the taimyr

The results of remote studies of thermokarst lakes in the Arctic zone of the Taimyr tundra are presented. The research was carried out on the territory of 725 thousand km2. Sentinel-2 satellite images were used in the studies, which made it possible to study the peculiarities of distribution of the number, total area of the lakes and tortuosity of their coastal borders. Histograms of the distribution of the number and total areas of the lakes in an extra wide range of their sizes from 0.2 to 5000 ha are presented. The histogram of lakes size-distribution demonstrates significant growth of their number with decrease in size. Histogram of the distribution of total areas of lakes by intervals of their sizes shows that more than 80 % of total area of lakes are dominated by lakes with sizes from 2 to 1000 ha. The analysis of the histogram of the degree of tortuosity of lakes borders distribution showed that the majority of lakes have the form of the coastal lines, which differs from a circle. The dependence of the degree of tortuosity of lakes borders on the size of lakes was studied and a positive linear trend of its change with the growth of the area of lakes was established.

Dyadobacter sandarakinus sp. nov., isolated from Arctic tundra soil, and emended descriptions of Dyadobacter alkalitolerans, Dyadobacter koreensis and Dyadobacter psychrophilus

Strain Q3-56T, isolated from Arctic tundra soil, was found to be a Gram-stain-negative, yellow-pigmented, oxidase- and catalase-positive, non-motile, non-spore-forming, rod-shaped and aerobic bacterium. Strain Q3-56T grew optimally at pH 7.0 and 28 °C. The strain could tolerate up to 1 % (w/v) NaCl with optimum growth in the absence of NaCl. The strain was not sensitive to oxacillin and ceftazidime. Phylogenetic analysis based on 16S rRNA gene sequences indicated that strain Q3-56T belonged to the genus Dyadobacter . Strain Q3-56T showed the highest sequence similarities to Dyadobacter luticola T17T (96.58 %), Dyadobacter ginsengisoli Gsoil 043T (96.50 %), Dyadobacter flavalbus NS28T (96.43 %) and Dyadobacter bucti QTA69T (96.43 %). The predominant respiratory isoprenoid quinone was identified as MK-7, The polar lipid profile of strain Q3-56T was found to contain one phosphatidylethanolamine, three unidentified aminolipids, three unidentified lipids and one unidentified phospholipid. The G+C content of the genomic DNA was determined to be 49.1 mol%. The main fatty acids were summed feature 3 (comprising C16 : 1 ω7c/C16 : 1 ω6c), iso-C15 : 0, C16 : 1 ω5c and iso-C16 : 1 3-OH. On the basis of the evidence presented in this study, a novel species of the genus Dyadobacter , Dyadobacter sandarakinus sp. nov., is proposed, with the type strain Q3-56T (=CCTCC AB 2019271T=KCTC 72739T). Emended descriptions of Dyadobacter alkalitolerans , Dyadobacter koreensis and Dyadobacter psychrophilus are also provided.

Improved ELMv1-ECA simulations of zero-curtain periods and cold-season CH₄ and CO₂ emissions at Alaskan Arctic tundra sites

Field measurements have shown that cold-season methane (CH4) and carbon dioxide (CO2) emissions contribute a substantial portion to the annual net carbon emissions in permafrost regions. However, most earth system land models do not accurately reproduce cold-season CH4 and CO2 emissions, especially over the shoulder (i.e., thawing and freezing) seasons. Here we use the Energy Exascale Earth System Model (E3SM) land model version 1 (ELMv1-ECA) to tackle this challenge and fill the knowledge gap of how cold-season CH4 and CO2 emissions contribute to the annual totals at Alaska Arctic tundra sites. Specifically, we improved the ELMv1-ECA soil water phase-change scheme, environmental controls on microbial activity, and the methane module. Results demonstrate that both soil temperature and the duration of zero-curtain periods (i.e., the fall period when soil temperatures linger around 0 ∘C) simulated by the updated ELMv1-ECA were greatly improved; e.g., the mean absolute error (MAE) in zero-curtain durations at 12 cm depth was reduced by 62 % on average. Furthermore, the MAEs of simulated cold-season carbon emissions at three tundra sites were improved by 72 % and 70 % on average for CH4 and CO2, respectively. Overall, CH4 emitted during the early cold season (September and October), which often includes most of the zero-curtain period in Arctic tundra, accounted for more than 50 % of the total emissions throughout the entire cold season (September to May) in the model, compared with around 49.4 % (43 %–58 %) in observations. From 1950 to 2017, both CO2 emissions during the zero-curtain period and during the entire cold season showed increasing trends, for example, of 0.17 and 0.36 gC m−2 yr−1 at Atqasuk. This study highlights the importance of zero-curtain periods in facilitating cold-season CH4 and CO2 emissions from tundra ecosystems.

Arctic Tundra Land Cover Classification on the Beaufort Coast Using the Kennaugh Element Framework on Dual-Polarimetric TerraSAR-X Imagery

Arctic tundra landscapes are highly complex and are rapidly changing due to the warming climate. Datasets that document the spatial and temporal variability of the landscape are needed to monitor the rapid changes. Synthetic Aperture Radar (SAR) imagery is specifically suitable for monitoring the Arctic, as SAR, unlike optical remote sensing, can provide time series regardless of weather and illumination conditions. This study examines the potential of seasonal backscatter mechanisms in Arctic tundra environments for improving land cover classification purposes by using a time series of HH/HV TerraSAR-X (TSX) imagery. A Random Forest (RF) classification was applied on multi-temporal Sigma Nought intensity and multi-temporal Kennaugh matrix element data. The backscatter analysis revealed clear differences in the polarimetric response of water, soil, and vegetation, while backscatter signal variations within different vegetation classes were more nuanced. The RF models showed that land cover classes could be distinguished with 92.4% accuracy for the Kennaugh element data, compared to 57.7% accuracy for the Sigma Nought intensity data. Texture predictors, while improving the classification accuracy on the one hand, degraded the spatial resolution of the land cover product. The Kennaugh elements derived from TSX winter acquisitions were most important for the RF model, followed by the Kennaugh elements derived from summer and autumn acquisitions. The results of this study demonstrate that multi-temporal Kennaugh elements derived from dual-polarized X-band imagery are a powerful tool for Arctic tundra land cover mapping.

Response of vegetation and carbon fluxes to brown lemming herbivory in Northern Alaska

The Arctic is warming at double the average global rate, affecting the carbon cycle of tundra ecosystems. Most research on carbon fluxes from Arctic tundra ecosystems has focused on abiotic environmental controls (e.g. temperature, rainfall, or radiation). However, Arctic tundra vegetation, and therefore the carbon balance of these ecosystems, can be substantially impacted by herbivory. In this study we tested how vegetation consumption by brown lemmings (Lemmus trimucronatus) can impact carbon exchange of a wet-sedge tundra ecosystem near Utqiaġvik, Alaska during the summer, and the recovery of vegetation during a following summer. We placed brown lemmings in individual enclosure plots and tested the impact of lemmings’ herbivory on carbon dioxide (CO2) and methane (CH4) fluxes and the normalized difference vegetation index (NDVI) immediately after lemming removal and during the following growing season. During the first summer of the experiment, lemmings’ herbivory reduced plant biomass (as shown by the decrease in the NDVI) and decreased CO2 uptake, while not significantly impacting CH4 emissions. Methane emissions were likely not significantly affected due to CH4 being produced deeper in the soil and escaping from the stem bases of the vascular plants. The summer following the lemming treatments, NDVI and CO2 fluxes returned to magnitudes similar to those observed before the start of the experiment, suggesting recovery of the vegetation, and a transitory nature of the impact of lemming herbivory. Overall, lemming herbivory has short-term but substantial effects on carbon sequestration by vegetation and might contribute to the considerable interannual variability in CO2 fluxes from tundra ecosystems.