Description: Soils are warming as air temperatures rise across the Arctic and Boreal region concurrent with the expansion of tall-statured shrubs and trees in the tundra. Changes in vegetation structure and function are expected to alter soil thermal regimes, thereby modifying climate feedbacks related to permafrost thaw and carbon cycling. However, current understanding of vegetation impacts on soil temperature is limited to local or regional scales and lacks the generality necessary to predict soil warming and permafrost stability on a pan-Arctic scale. Here we synthesize shallow soil and air temperature observations with broad spatial and temporal coverage collected across 106 sites representing nine different vegetation types in the permafrost region. We showed ecosystems with tall-statured shrubs and trees (〉 40 cm) have warmer shallow soils than those with short-statured tundra vegetation when normalized to a constant air temperature. In tree and tall shrub vegetation types, cooler temperatures in the warm season do not lead to cooler mean annual soil temperature indicating that ground thermal regimes in the cold-season rather than the warm-season are most critical for predicting soil warming in ecosystems underlain by permafrost. Our results suggest that the expansion of tall shrubs and trees into tundra regions can amplify shallow soil warming, and could increase the potential for increased seasonal thaw depth and increase soil carbon cycling rates and lead to increased carbon dioxide loss and further permafrost thaw.

Description: Four years of growing season eddy covariance measurements of net carbon dioxide (CO2) and energy fluxes were used to examine the similarities/differences in surface-atmosphere interactions at two dwarf shrub tundra sites within Canada’s Southern Arctic ecozone, separated by approximately 1000 km. Both sites, Trail Valley Creek (TVC) and Daring Lake (DL1), are characterised by similar climate (with some differences in radiation due to latitudinal differences), vegetation composition and structure, and are underlain by continuous permafrost, but differ in their soil characteristics. Total atmospheric heating (the sum of latent and sensible heat fluxes) was similar at the two sites. However, at DL1, where the surface organic layer was thinner and mineral soil coarser in texture, latent heat fluxes were greater, sensible heat fluxes were lower, soils were warmer and the active layer thicker. At TVC, cooler soils likely kept ecosystem respiration relatively low despite similar total growing season productivity. As a result, the 4-year mean net growing season ecosystem CO2 uptake (May 1 - September 30) was almost twice as large at TVC (64 ± 19 g C m-2) compared to DL1 (33 ± 11 g C m-2). These results highlight that soil and thaw characteristics are important to understand variability in surface-atmosphere interactions among tundra ecosystems. As recent studies have shown, winter fluxes play an important role in the annual CO2 balance of Arctic tundra ecosystems. However, flux measurements were not available at TVC and DL1 during the cold season. Thus, the process-based ecosystem model CLASSIC (the Canadian Land Surface Scheme including biogeochemical Cycles, formerly CLASS-CTEM) was used to simulate year-round fluxes. In order to represent the Arctic shrub tundra better, shrub and sedge plant functional types were included in CLASSIC and results were evaluated using measurements at DL1. Preliminary results indicate that cold season CO2 losses are substantial and may exceed the growing season CO2 uptake at DL1 during 2010-2017. The joint use of observations and models is valuable in order to better constrain the Arctic CO2 balance.

Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Kropp, H., Loranty, M. M., Natali, S. M., Kholodov, A. L., Rocha, A., V., Myers-Smith, I., Abbot, B. W., Abermann, J., Blanc-Betes, E., Blok, D., Blume-Werry, G., Boike, J., Breen, A. L., Cahoon, S. M. P., Christiansen, C. T., Douglas, T. A., Epstein, H. E., Frost, G., V., Goeckede, M., Hoye, T. T., Mamet, S. D., O'Donnell, J. A., Olefeldt, D., Phoenix, G. K., Salmon, V. G., Sannel, A. B. K., Smith, S. L., Sonnentag, O., Vaughn, L. S., Williams, M., Elberling, B., Gough, L., Hjort, J., Lafleur, P. M., Euskirchen, E. S., Heijmans, M. M. P. D., Humphreys, E. R., Iwata, H., Jones, B. M., Jorgenson, M. T., Gruenberg, I., Kim, Y., Laundre, J., Mauritz, M., Michelsen, A., Schaepman-Strub, G., Tape, K. D., Ueyama, M., Lee, B., Langley, K., & Lund, M. Shallow soils are warmer under trees and tall shrubs across arctic and boreal ecosystems. Environmental Research Letters, 16(1), (2021): 015001. doi:10.1088/1748-9326/abc994.

Description: Soils are warming as air temperatures rise across the Arctic and Boreal region concurrent with the expansion of tall-statured shrubs and trees in the tundra. Changes in vegetation structure and function are expected to alter soil thermal regimes, thereby modifying climate feedbacks related to permafrost thaw and carbon cycling. However, current understanding of vegetation impacts on soil temperature is limited to local or regional scales and lacks the generality necessary to predict soil warming and permafrost stability on a pan-Arctic scale. Here we synthesize shallow soil and air temperature observations with broad spatial and temporal coverage collected across 106 sites representing nine different vegetation types in the permafrost region. We showed ecosystems with tall-statured shrubs and trees (〉40 cm) have warmer shallow soils than those with short-statured tundra vegetation when normalized to a constant air temperature. In tree and tall shrub vegetation types, cooler temperatures in the warm season do not lead to cooler mean annual soil temperature indicating that ground thermal regimes in the cold-season rather than the warm-season are most critical for predicting soil warming in ecosystems underlain by permafrost. Our results suggest that the expansion of tall shrubs and trees into tundra regions can amplify shallow soil warming, and could increase the potential for increased seasonal thaw depth and increase soil carbon cycling rates and lead to increased carbon dioxide loss and further permafrost thaw.

Description: We thank G Peter Kershaw, LeeAnn Fishback, Cathy Wilson, and Coleen Iversen for assistance in collection of data. We thank the Permafrost Carbon Network for support and organization of the data synthesis. We thank Vladimir Romanovsky for his feedback and contribution of publicly available data. This project was supported by the National Science Foundation (Grant No. 1417745 to M L, Grant No. 1417700 to S M N, Grant No. 1417908 to A K, Grant No. 1556772 to A R, Grant No. 1637459 to L G, Grant No. 1636476 and Grant No. 1503912 to E S E, Grant No. 1806213 to B M J, Grant No. 1833056 to K D T), UK Natural Environment Research Council (Grant No. NE/M016323/1 to I H M S, Grant No. NE/K00025X/1 to G K P, Grant No. NE/K000292/1 to M W), Natural Sciences and Engineering Research (to P L, I H M S, Grant No. RGPIN-2016-04688 to D O), Council of Canada, Canadian Graduate Scholarship to (I H M -S), Greenland Ecosystem Monitoring Programme: ClimateBasis (to J A and K A), The Next-Generation Ecosystem Experiments (NGEE Arctic) project is supported by the Office of Biological and Environmental Research in the DOE Office of Science (to A L B), Engineer Research and Development Center Army Direct (6.1) Research Program and the Strategic Environmental Research and Development Program (projects RC-2110 and 18-1170 to T A D), United States Geological Survey (to E E S), Arctic Challenge for Sustainability (ArCS; Grant No. JPMXD1300000000) and ArCS II (Grant No. JPMXD1420318865) (to M U and H I), the Danish National Research Foundation (Grant No. CENPERM DNRF100 to B E), the Academy of Finland (Grant No. 315519), the National Research Foundation of Korea (Grant Nos. NRF-2016M1A5A1901769; KOPRI-PN20081 to K Y and B Y L), Research Network for Geosciences in Berlin and Potsdam (to I G), the Swiss National Science Foundation (Grant No. 140631 to G S S), the URPP Global Change and Biodiversity, University of Zurich (to G S S), the University of Alberta Northern Research Awards (to D O), and the Northern Scientific Training Program (to D O), and UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE) Office of Science, Biological and Environmental Research (to V G S). S M has been supported by grants and/or in-kind from Natural Sciences and Engineering Research Council of Canada, AMAX Northwest Mining, Co. (North American Tungsten Corp., Ltd), Imperial Oil, Ltd, University of Alberta, Earthwatch International (EI), The Garfield Weston Foundation, Wapusk National Park, Churchill Northern Studies Centre, and the Northern Scientific Training Program. All code for this project are archived (DOI: 10.5281/zenodo.4041165). The data that support the findings of this study are openly available through the Arctic Data Center (Heather Kropp, Michael Loranty, Britta Sannel, Jonathan O'Donnell, Elena Blanc-Betes, et al 2020. Synthesis of soil-air temperature and vegetation measurements in the pan-Arctic. 1990-2016. Arctic Data Center. doi:10.18739/A2736M31X).

Description: © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Geoscientific Model Development 11 (2018): 497-519, doi:10.5194/gmd-11-497-2018.

Description: Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r2 =  0.76; Nash–Sutcliffe modeling efficiency, MEF  =  0.76) and ecosystem respiration (ER, r2 =  0.78, MEF  =  0.75), with lesser accuracy for latent heat fluxes (LE, r2 =  0.42, MEF  =  0.14) and and net ecosystem CO2 exchange (NEE, r2 =  0.38, MEF  =  0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r2 values (0.57–0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r2 〈 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized Vcmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average Vcmax value.

Description: This study was supported by the European Research Council Synergy grant ERC-2013-SyG- 610028 IMBALANCE-P.

Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Chu, H., Luo, X., Ouyang, Z., Chan, W. S., Dengel, S., Biraud, S. C., Torn, M. S., Metzger, S., Kumar, J., Arain, M. A., Arkebauer, T. J., Baldocchi, D., Bernacchi, C., Billesbach, D., Black, T. A., Blanken, P. D., Bohrer, G., Bracho, R., Brown, S., Brunsell, N. A., Chen, J., Chen, X., Clark, K., Desai, A. R., Duman, T., Durden, D., Fares, S., Forbrich, I., Gamon, J. A., Gough, C. M., Griffis, T., Helbig, M., Hollinger, D., Humphreys, E., Ikawa, H., Iwata, H., Ju, Y., Knowles, J. F., Knox, S. H., Kobayashi, H., Kolb, T., Law, B., Lee, X., Litvak, M., Liu, H., Munger, J. W., Noormets, A., Novick, K., Oberbauer, S. F., Oechel, W., Oikawa, P., Papuga, S. A., Pendall, E., Prajapati, P., Prueger, J., Quinton, W. L., Richardson, A. D., Russell, E. S., Scott, R. L., Starr, G., Staebler, R., Stoy, P. C., Stuart-Haentjens, E., Sonnentag, O., Sullivan, R. C., Suyker, A., Ueyama, M., Vargas, R., Wood, J. D., & Zona, D. Representativeness of eddy-covariance flux footprints for areas surrounding AmeriFlux sites. Agricultural and Forest Meteorology, 301, (2021): 108350, https://doi.org/10.1016/j.agrformet.2021.108350.

Description: Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 103 to 107 m2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use.

Description: We thank the AmeriFlux site teams for sharing their data and metadata with the network. Funding for these flux sites is acknowledged in the site data DOI, shown in Table S1. This analysis was supported in part by funding provided to the AmeriFlux Management Project by the U.S. Department of Energy's Office of Science under Contract No. DE-AC02-05CH11231. All footprint climatologies, site-level representativeness indices, and monthly EVI and sensor location biases can be accessed via the Zenodo Data Repository (Datasets S1–S6, http://doi.org/10.5281/zenodo.4015350).

Description: Past efforts to synthesize and quantify the magnitude and change in carbon dioxide (CO2) fluxes in terrestrial ecosystems across the rapidly warming Arctic–boreal zone (ABZ) have provided valuable information but were limited in their geographical and temporal coverage. Furthermore, these efforts have been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting their potential to be used in large-scale carbon budget assessments. To bridge these gaps, we developed a standardized monthly database of Arctic–boreal CO2 fluxes (ABCflux) that aggregates in situ measurements of terrestrial net ecosystem CO2 exchange and its derived partitioned component fluxes: gross primary productivity and ecosystem respiration. The data span from 1989 to 2020 with over 70 supporting variables that describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. Here, we describe these variables, the spatial and temporal distribution of observations, the main strengths and limitations of the database, and the potential research opportunities it enables. In total, ABCflux includes 244 sites and 6309 monthly observations; 136 sites and 2217 monthly observations represent tundra, and 108 sites and 4092 observations represent the boreal biome. The database includes fluxes estimated with chamber (19 % of the monthly observations), snow diffusion (3 %) and eddy covariance (78 %) techniques. The largest number of observations were collected during the climatological summer (June–August; 32 %), and fewer observations were available for autumn (September–October; 25 %), winter (December–February; 18 %), and spring (March–May; 25 %). ABCflux can be used in a wide array of empirical, remote sensing and modeling studies to improve understanding of the regional and temporal variability in CO2 fluxes and to better estimate the terrestrial ABZ CO2 budget. ABCflux is openly and freely available online (Virkkala et al., 2021b, https://doi.org/10.3334/ORNLDAAC/1934).

Description: Arctic warming is affecting snow cover and soil hydrology, with consequences for carbon sequestration in tundra ecosystems. The scarcity of observations in the Arctic has limited our understanding of the impact of covarying environmental drivers on the carbon balance of tundra ecosystems. In this study, we address some of these uncertainties through a novel record of 119 site-years of summer data from eddy covariance towers representing dominant tundra vegetation types located on continuous permafrost in the Arctic. Here we found that earlier snowmelt was associated with more tundra net CO2 sequestration and higher gross primary productivity (GPP) only in June and July, but with lower net carbon sequestration and lower GPP in August. Although higher evapotranspiration (ET) can result in soil drying with the progression of the summer, we did not find significantly lower soil moisture with earlier snowmelt, nor evidence that water stress affected GPP in the late growing season. Our results suggest that the expected increased CO2 sequestration arising from Arctic warming and the associated increase in growing season length may not materialize if tundra ecosystems are not able to continue sequestering CO2 later in the season.

Description: The regional variability in tundra and boreal carbon dioxide (CO2) fluxes can be high, complicating efforts to quantify sink-source patterns across the entire region. Statistical models are increasingly used to predict (i.e., upscale) CO2 fluxes across large spatial domains, but the reliability of different modeling techniques, each with different specifications and assumptions, has not been assessed in detail. Here, we compile eddy covariance and chamber measurements of annual and growing season CO2 fluxes of gross primary productivity (GPP), ecosystem respiration (ER), and net ecosystem exchange (NEE) during 1990–2015 from 148 terrestrial high-latitude (i.e., tundra and boreal) sites to analyze the spatial patterns and drivers of CO2 fluxes and test the accuracy and uncertainty of different statistical models. CO2 fluxes were upscaled at relatively high spatial resolution (1 km2) across the high-latitude region using five commonly used statistical models and their ensemble, that is, the median of all five models, using climatic, vegetation, and soil predictors. We found the performance of machine learning and ensemble predictions to outperform traditional regression methods. We also found the predictive performance of NEE-focused models to be low, relative to models predicting GPP and ER. Our data compilation and ensemble predictions showed that CO2 sink strength was larger in the boreal biome (observed and predicted average annual NEE −46 and −29 g C m−2 yr−1, respectively) compared to tundra (average annual NEE +10 and −2 g C m−2 yr−1). This pattern was associated with large spatial variability, reflecting local heterogeneity in soil organic carbon stocks, climate, and vegetation productivity. The terrestrial ecosystem CO2 budget, estimated using the annual NEE ensemble prediction, suggests the high-latitude region was on average an annual CO2 sink during 1990–2015, although uncertainty remains high.