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ArticleShallow soils are warmer under trees and tall shrubs across arctic and boreal ecosystems(IOP Publishing, 2020-12-18) Kropp, Heather ; Loranty, Michael M. ; Natali, Susan M. ; Kholodov, Alexander L. ; Rocha, Adrian V. ; Myers-Smith, Isla H. ; Abbott, Benjamin W. ; Abermann, Jakob ; Blanc-Betes, Elena ; Blok, Daan ; Blume-Werry, Gesche ; Boike, Julia ; Breen, Amy L. ; Cahoon, Sean M. P. ; Christiansen, Casper T. ; Douglas, Thomas A. ; Epstein, Howard E. ; Frost, Gerald V. ; Goeckede, Mathias ; Høye, Toke T. ; Mamet, Steven D. ; O’Donnell, Jonathan A. ; Olefeldt, David ; Phoenix, Gareth K. ; Salmon, Verity G. ; Sannel, A. Britta K. ; Smith, Sharon L. ; Sonnentag, Oliver ; Smith Vaughn, Lydia ; Williams, Mathew ; Elberling, Bo ; Gough, Laura ; Hjort, Jan ; Lafleur, Peter M. ; Euskirchen, Eugenie ; Heijmans, Monique M. P. D. ; Humphreys, Elyn ; Iwata, Hiroki ; Jones, Benjamin M. ; Jorgenson, M. Torre ; Grünberg, Inge ; Kim, Yongwon ; Laundre, James A. ; Mauritz, Marguerite ; Michelsen, Anders ; Schaepman-Strub, Gabriela ; Tape, Ken D. ; Ueyama, Masahito ; Lee, Bang-Yong ; Langley, Kirsty ; Lund, MagnusSoils 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.
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ArticleRepresentativeness of eddy-covariance flux footprints for areas surrounding AmeriFlux sites(Elsevier, 2021-02-14) Chu, Housen ; Luo, Xiangzhong ; Ouyang, Zutao ; Chan, W. Stephen ; Dengel, Sigrid ; Biraud, Sebastien ; Torn, Margaret S. ; Metzger, Stefan ; Kumar, Jitendra ; Arain, M. Altaf ; Arkebauer, Tim J. ; Baldocchi, Dennis D. ; Bernacchi, Carl ; Billesbach, Dave ; Black, T. Andrew ; Blanken, Peter D. ; Bohrer, Gil ; Bracho, Rosvel ; Brown, Shannon ; Brunsell, Nathaniel A. ; Chen, Jiquan ; Chen, Xingyuan ; Clark, Kenneth ; Desai, Ankur R. ; Duman, Tomer ; Durden, David J. ; Fares, Silvano ; Forbrich, Inke ; Gamon, John ; Gough, Christopher M. ; Griffis, Timothy ; Helbig, Manuel ; Hollinger, David ; Humphreys, Elyn ; Ikawa, Hiroki ; Iwata, Hiroki ; Ju, Yang ; Knowles, John F. ; Knox, Sara H. ; Kobayashi, Hideki ; Kolb, Thomas ; Law, Beverly ; Lee, Xuhui ; Litvak, Marcy ; Liu, Heping ; Munger, J. William ; Noormets, Asko ; Novick, Kim ; Oberbauer, Steven F. ; Oechel, Walter ; Oikawa, Patty ; Papuga, Shirley A. ; Pendall, Elise ; Prajapati, Prajaya ; Prueger, John ; Quinton, William L. ; Richardson, Andrew D. ; Russell, Eric S. ; Scott, Russell L. ; Starr, Gregory ; Staebler, Ralf ; Stoy, Paul C. ; Stuart-Haëntjens, Ellen ; Sonnentag, Oliver ; Sullivan, Ryan C. ; Suyker, Andy ; Ueyama, Masahito ; Vargas, Rodrigo ; Wood, Jeffrey D. ; Zona, DonatellaLarge 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.
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ArticleORCHIDEE-PEAT (revision 4596), a model for northern peatland CO2, water, and energy fluxes on daily to annual scales(Copernicus Publications on behalf of the European Geosciences Union, 2018-02-05) Qiu, Chunjing ; Zhu, Dan ; Ciais, Philippe ; Guenet, Bertrand ; Krinner, Gerhard ; Peng, Shushi ; Aurela, Mika ; Bernhofer, Christian ; Brümmer, Christian ; Bret-Harte, M. Syndonia ; Chu, Housen ; Chen, Jiquan ; Desai, Ankur R. ; Dušek, Jiˇrí ; Euskirchen, Eugenie ; Fortuniak, Krzysztof ; Flanagan, Lawrence B. ; Friborg, Thomas ; Grygoruk, Mateusz ; Gogo, Sébastien ; Grünwald, Thomas ; Hansen, Birger U. ; Holl, David ; Humphreys, Elyn ; Hurkuck, Miriam ; Kiely, Gerard ; Klatt, Janina ; Kutzbach, Lars ; Largeron, Chloé ; Laggoun-Défarg, Fatima ; Lund, Magnus ; Lafleur, Peter M. ; Li, Xuefei ; Mammarella, Ivan ; Merbold, Lutz ; Nilsson, Mats B. ; Olejnik, Janusz ; Ottosson-Löfvenius, Mikaell ; Oechel, Walter ; Parmentier, Frans-Jan W. ; Peichl, Matthias ; Pirk, Norbert ; Peltola, Olli ; Pawlak, Włodzimierz ; Rasse, Daniel ; Rinne, Janne ; Shaver, Gaius R. ; Schmid, Hans Peter ; Sottocornola, Matteo ; Steinbrecher, Rainer ; Sachs, Torsten ; Urbaniak, Marek ; Zona, Donatella ; Ziemblinska, KlaudiaPeatlands 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.