M. Syndonia Bret‐Harte


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Evaluating photosynthetic activity across Arctic-Boreal land cover types using solar-induced fluorescence
Rui Cheng, Troy S. Magney, Erica L Orcutt, Zoe Pierrat, Philipp Köhler, David R. Bowling, M. Syndonia Bret‐Harte, Eugénie Euskirchen, Martin Jung, Hideki Kobayashi, A. V. Rocha, Oliver Sonnentag, J. Stutz, Sophia Walther, Donatella Zona, Christian Frankenberg
Environmental Research Letters, Volume 17, Issue 11

Abstract Photosynthesis of terrestrial ecosystems in the Arctic-Boreal region is a critical part of the global carbon cycle. Solar-induced chlorophyll Fluorescence (SIF), a promising proxy for photosynthesis with physiological insight, has been used to track gross primary production (GPP) at regional scales. Recent studies have constructed empirical relationships between SIF and eddy covariance-derived GPP as a first step to predicting global GPP. However, high latitudes pose two specific challenges: (a) Unique plant species and land cover types in the Arctic–Boreal region are not included in the generalized SIF-GPP relationship from lower latitudes, and (b) the complex terrain and sub-pixel land cover further complicate the interpretation of the SIF-GPP relationship. In this study, we focused on the Arctic-Boreal vulnerability experiment (ABoVE) domain and evaluated the empirical relationships between SIF for high latitudes from the TROPOspheric Monitoring Instrument (TROPOMI) and a state-of-the-art machine learning GPP product (FluxCom). For the first time, we report the regression slope, linear correlation coefficient, and the goodness of the fit of SIF-GPP relationships for Arctic-Boreal land cover types with extensive spatial coverage. We found several potential issues specific to the Arctic-Boreal region that should be considered: (a) unrealistically high FluxCom GPP due to the presence of snow and water at the subpixel scale; (b) changing biomass distribution and SIF-GPP relationship along elevational gradients, and (c) limited perspective and misrepresentation of heterogeneous land cover across spatial resolutions. Taken together, our results will help improve the estimation of GPP using SIF in terrestrial biosphere models and cope with model-data uncertainties in the Arctic-Boreal region.


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The ABCflux database: Arctic–boreal CO<sub>2</sub> flux observations and ancillary information aggregated to monthly time steps across terrestrial ecosystems
Anna-Maria Virkkala, Susan M. Natali, Brendan M. Rogers, Jennifer D. Watts, K. E. Savage, Sara June Connon, Marguerite Mauritz, Edward A. G. Schuur, D. L. Peter, C. Minions, Julia Nojeim, R. Commane, Craig A. Emmerton, Mathias Goeckede, Manuel Helbig, David Holl, Hiroyasu Iwata, Hideki Kobayashi, Pasi Kolari, Efrén López‐Blanco, Maija E. Marushchak, Mikhail Mastepanov, Lutz Merbold, Frans‐Jan W. Parmentier, Matthias Peichl, Torsten Sachs, Oliver Sonnentag, Masahito Ueyama, Carolina Voigt, Mika Aurela, Julia Boike, Gerardo Celis, Namyi Chae, Torben R. Christensen, M. Syndonia Bret‐Harte, Sigrid Dengel, A. J. Dolman, C. Edgar, Bo Elberling, Eugénie Euskirchen, Achim Grelle, Juha Hatakka, Elyn Humphreys, Järvi Järveoja, Ayumi Kotani, Lars Kutzbach, Tuomas Laurila, Annalea Lohila, Ivan Mammarella, Yukiko Matsuura, Gesa Meyer, Mats Nilsson, Steven F. Oberbauer, Sang Jong Park, Roman E. Petrov, А. С. Прокушкин, Christopher Schulze, Vincent L. St. Louis, Eeva‐Stiina Tuittila, Juha‐Pekka Tuovinen, William L. Quinton, Andrej Varlagin, Donatella Zona, Viacheslav I. Zyryanov
Earth System Science Data, Volume 14, Issue 1

Abstract. 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).

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Vegetation type is an important predictor of the arctic summer land surface energy budget
Jacqueline Oehri, Gabriela Schaepman‐Strub, Jin‐Soo Kim, Raleigh Grysko, Heather Kropp, Inge Grünberg, Vitalii Zemlianskii, Oliver Sonnentag, Eugénie Euskirchen, Merin Reji Chacko, Giovanni Muscari, Peter D. Blanken, Joshua Dean, Alcide di Sarra, R. J. Harding, Ireneusz Sobota, Lars Kutzbach, Elena Plekhanova, Aku Riihelä, Julia Boike, Nathaniel B. Miller, Jason Beringer, Efrén López‐Blanco, Paul C. Stoy, Ryan C. Sullivan, Marek Kejna, Frans‐Jan W. Parmentier, John A. Gamon, Mikhail Mastepanov, Christian Wille, Marcin Jackowicz-Korczyński, Dirk Nikolaus Karger, William L. Quinton, Jaakko Putkonen, Dirk van As, Torben R. Christensen, Maria Z. Hakuba, Robert S. Stone, Stefan Metzger, Baptiste Vandecrux, G. V. Frost, Martin Wild, Birger Ulf Hansen, Daniela Meloni, Florent Dominé, Mariska te Beest, Torsten Sachs, Aram Kalhori, A. V. Rocha, Scott Williamson, S. Crepinsek, A. L. Atchley, Richard Essery, Benjamin R. K. Runkle, David Holl, Laura D. Riihimaki, Hiroyasu Iwata, Edward A. G. Schuur, Christopher Cox, A. A. Grachev, J. P. McFadden, Robert S. Fausto, Mathias Goeckede, Masahito Ueyama, Norbert Pirk, Gijs de Boer, M. Syndonia Bret‐Harte, Matti Leppäranta, Konrad Steffen, Thomas Friborg, Atsumu Ohmura, C. Edgar, Johan Olofsson, Scott D. Chambers
Nature Communications, Volume 13, Issue 1

Abstract Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm −2 ) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.