Articles | Volume 16, issue 8
https://doi.org/10.5194/essd-16-3687-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-3687-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
16 Aug 2024
Data description article |
| 16 Aug 2024
| 16 Aug 2024
A synthesized field survey database of vegetation and active-layer properties for the Alaskan tundra (1972–2020)
Xiaoran Zhu
Department of Earth & Environment, Boston University, Boston, Massachusetts 02215, USA
Dong Chen
CORRESPONDING AUTHOR
Department of Geographical Sciences, University of Maryland, College Park, Maryland 20742, USA
Maruko Kogure
Department of Geographical Sciences, University of Maryland, College Park, Maryland 20742, USA
Elizabeth Hoy
NASA Goddard Space Flight Center, Greenbelt, Maryland 20771, USA
Global Science & Technology, Inc., Greenbelt, Maryland 20770, USA
Logan T. Berner
School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, Arizona 86004, USA
Amy L. Breen
International Arctic Research Center, University of Alaska Fairbanks, Fairbanks, Alaska 99775, USA
Abhishek Chatterjee
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California 91109, USA
Scott J. Davidson
School of Geography, Earth and Environmental Sciences, University of Plymouth, Plymouth, PL3 4PA, UK
Department of Geography and Environmental Management, University of Waterloo, Waterloo, N2L 3G1, Canada
Gerald V. Frost
Alaska Biological Research, Inc., Fairbanks, Alaska 99775, USA
Teresa N. Hollingsworth
Aldo Leopold Wilderness Research Institute, Rocky Mountain Research Station, Missoula, Montana 59801, USA
Boreal Ecology Team, PNW Research Station, Fairbanks, Alaska 99775, USA
Go Iwahana
International Arctic Research Center, University of Alaska Fairbanks, Fairbanks, Alaska 99775, USA
Randi R. Jandt
International Arctic Research Center, University of Alaska Fairbanks, Fairbanks, Alaska 99775, USA
Anja N. Kade
Department of Biology and Wildlife, University of Alaska Fairbanks, Fairbanks, Alaska 99775, USA
Tatiana V. Loboda
Department of Geographical Sciences, University of Maryland, College Park, Maryland 20742, USA
Matt J. Macander
Alaska Biological Research, Inc., Fairbanks, Alaska 99775, USA
Michelle Mack
Department of Biological Sciences, Northern Arizona University, Flagstaff, Arizona 86004, USA
Charles E. Miller
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California 91109, USA
Eric A. Miller
Bureau of Land Management Alaska Fire Service, Fort Wainwright, Alaska 99703, USA
Susan M. Natali
Woodwell Climate Research Center, Falmouth, Massachusetts 02540, USA
Martha K. Raynolds
Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks Alaska 99775, USA
Adrian V. Rocha
Department of Biological Sciences, University of Notre Dame, Notre Dame, Indiana 46556, USA
Shiro Tsuyuzaki
Graduate School of Environmental Earth Science, Hokkaido University, Sapporo, 060-0810, Japan
Craig E. Tweedie
Department of Biological Sciences and the Environmental Science and Engineering Program, The University of Texas at El Paso, El Paso, Texas 79968, USA
Donald A. Walker
Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks Alaska 99775, USA
Mathew Williams
School of GeoSciences, University of Edinburgh, Edinburgh, EH9 3FF, UK
Department of Geographical Sciences, University of Maryland, College Park, Maryland 20742, USA
Yingtong Zhang
Department of Earth & Environment, Boston University, Boston, Massachusetts 02215, USA
Nancy French
Michigan Tech Research Institute, Michigan Technological University, Ann Arbor, Michigan 48105, USA
Scott Goetz
School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, Arizona 86004, USA
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EGUsphere, https://doi.org/10.5194/egusphere-2026-2222, https://doi.org/10.5194/egusphere-2026-2222, 2026
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Olivia Meier-Legault, Nicholas Brown, Larry Adjun, Michel Allard, Alejandro Alvarez, Maude Auclair, Alex Bevington, Samuel Bilodeau, William Cable, Olivia Carpino, Ariane Castagner, Lin Chen, Alexandre Chiasson, Ryan Connon, Stephanie Coulombe, Jeffrey Crompton, Derek Cronmiller, Gautier Davesne, Mason Dominico, Marc-André Ducharme, Timothy Ensom, Louise Farquharson, Vanessa Foord, Daniel Fortier, Philippe Fortier, Duane Froese, Samuel Gagnon, Francis Gauthier, Marten Geertsema, Etienne Godin, Galina Jonat, Steven V. Kokelj, Michelle Landry, Antoni Lewkowicz, Panya Lipovsky, Emmanual L’Hérault, Hannah Macdonell, Lancelot Massé, Dmitry Nicolsky, Moya Painter, Leesee Papatsie, Victor Pozsgay, William Quinton, Vladimir Romanovsky, Ashley C.A. Rudy, Denis Sarrazin, Emilie Stewart-Jones, Donald Walker, Thomas Wright, Joseph Young, and Stephan Gruber
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-585, https://doi.org/10.5194/essd-2025-585, 2025
Revised manuscript accepted for ESSD
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This dataset includes monthly measurements of carbon dioxide and methane exchange between land, water, and the atmosphere from over 1,000 sites in Arctic and boreal regions. It combines measurements from a variety of ecosystems, including wetlands, forests, tundra, lakes, and rivers, gathered by over 260 researchers from 1984–2024. This dataset can be used to improve and reduce uncertainty in carbon budgets in order to strengthen our understanding of climate feedbacks in a warming world.
Elchin E. Jafarov, Hélène Genet, Velimir V. Vesselinov, Valeria Briones, Aiza Kabeer, Andrew L. Mullen, Benjamin Maglio, Tobey Carman, Ruth Rutter, Joy Clein, Chu-Chun Chang, Dogukan Teber, Trevor Smith, Joshua M. Rady, Christina Schädel, Jennifer D. Watts, Brendan M. Rogers, and Susan M. Natali
Geosci. Model Dev., 18, 3857–3875, https://doi.org/10.5194/gmd-18-3857-2025, https://doi.org/10.5194/gmd-18-3857-2025, 2025
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This study improves how we tune ecosystem models to reflect carbon and nitrogen storage in Arctic soils. By comparing model outputs with data from a black spruce forest in Alaska, we developed a clearer, more efficient method of matching observations. This is a key step towards understanding how Arctic ecosystems may respond to warming and release carbon, helping make future climate predictions more reliable.
Anna C. Talucci, Michael M. Loranty, Jean E. Holloway, Brendan M. Rogers, Heather D. Alexander, Natalie Baillargeon, Jennifer L. Baltzer, Logan T. Berner, Amy Breen, Leya Brodt, Brian Buma, Jacqueline Dean, Clement J. F. Delcourt, Lucas R. Diaz, Catherine M. Dieleman, Thomas A. Douglas, Gerald V. Frost, Benjamin V. Gaglioti, Rebecca E. Hewitt, Teresa Hollingsworth, M. Torre Jorgenson, Mark J. Lara, Rachel A. Loehman, Michelle C. Mack, Kristen L. Manies, Christina Minions, Susan M. Natali, Jonathan A. O'Donnell, David Olefeldt, Alison K. Paulson, Adrian V. Rocha, Lisa B. Saperstein, Tatiana A. Shestakova, Seeta Sistla, Oleg Sizov, Andrey Soromotin, Merritt R. Turetsky, Sander Veraverbeke, and Michelle A. Walvoord
Earth Syst. Sci. Data, 17, 2887–2909, https://doi.org/10.5194/essd-17-2887-2025, https://doi.org/10.5194/essd-17-2887-2025, 2025
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Wildfires have the potential to accelerate permafrost thaw and the associated feedbacks to climate change. We assembled a dataset of permafrost thaw depth measurements from burned and unburned sites contributed by researchers from across the northern high-latitude region. We estimated maximum thaw depth for each measurement, which addresses a key challenge: the ability to assess impacts of wildfire on maximum thaw depth when measurement timing varies.
Qing Ying, Benjamin Poulter, Jennifer D. Watts, Kyle A. Arndt, Anna-Maria Virkkala, Lori Bruhwiler, Youmi Oh, Brendan M. Rogers, Susan M. Natali, Hilary Sullivan, Amanda Armstrong, Eric J. Ward, Luke D. Schiferl, Clayton D. Elder, Olli Peltola, Annett Bartsch, Ankur R. Desai, Eugénie Euskirchen, Mathias Göckede, Bernhard Lehner, Mats B. Nilsson, Matthias Peichl, Oliver Sonnentag, Eeva-Stiina Tuittila, Torsten Sachs, Aram Kalhori, Masahito Ueyama, and Zhen Zhang
Earth Syst. Sci. Data, 17, 2507–2534, https://doi.org/10.5194/essd-17-2507-2025, https://doi.org/10.5194/essd-17-2507-2025, 2025
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We present daily methane (CH4) fluxes of northern wetlands at 10 km resolution during 2016–2022 (WetCH4) derived from a novel machine learning framework. We estimated an average annual CH4 emission of 22.8 ± 2.4 Tg CH4 yr−1 (15.7–51.6 Tg CH4 yr−1). Emissions were intensified in 2016, 2020, and 2022, with the largest interannual variation coming from Western Siberia. Continued, all-season tower observations and improved soil moisture products are needed for future improvement of CH4 upscaling.
Valeria Briones, Hélène Genet, Elchin E. Jafarov, Brendan M. Rogers, Jennifer D. Watts, Anna-Maria Virkkala, Annett Bartsch, Benjamin C. Maglio, Joshua Rady, and Susan M. Natali
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-226, https://doi.org/10.5194/essd-2025-226, 2025
Manuscript not accepted for further review
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Arctic warming is causing permafrost to thaw, affecting ecosystems and climate. Since land cover, especially vegetation, shapes how permafrost responds, accurate maps are crucial. Using machine learning, we combined existing global and regional datasets to create a hybrid detailed 1-km map of Arctic-Boreal land cover, improving the representation of forests, shrubs, and wetlands across the circumpolar.
Mathew Williams, David T. Milodowski, T. Luke Smallman, Kyle G. Dexter, Gabi C. Hegerl, Iain M. McNicol, Michael O'Sullivan, Carla M. Roesch, Casey M. Ryan, Stephen Sitch, and Aude Valade
Biogeosciences, 22, 1597–1614, https://doi.org/10.5194/bg-22-1597-2025, https://doi.org/10.5194/bg-22-1597-2025, 2025
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Southern African woodlands are important in both regional and global carbon cycles. A new carbon analysis created by combining satellite data with ecosystem modelling shows that the region has a neutral C balance overall but with important spatial variations. Patterns of biomass and C balance across the region are the outcome of climate controls on production and vegetation–fire interactions, which determine the mortality of vegetation and spatial variations in vegetation function.
Marcos B. Sanches, Manoel Cardoso, Celso von Randow, Chris Jones, and Mathew Williams
EGUsphere, https://doi.org/10.5194/egusphere-2025-942, https://doi.org/10.5194/egusphere-2025-942, 2025
Preprint archived
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This study examines South America's role in the global carbon cycle using flux and stock analyses from CMIP6 Earth System Models. We discuss the continent’s relevance, model-observation agreement, and the impacts of dry and wet years on major biomes. Additionally, we assess model results indicating that parts of South America could shift from carbon sinks to emitters, significantly affecting the global carbon balance.
Charles E. Miller, Peter C. Griffith, Elizabeth Hoy, Naiara S. Pinto, Yunling Lou, Scott Hensley, Bruce D. Chapman, Jennifer Baltzer, Kazem Bakian-Dogaheh, W. Robert Bolton, Laura Bourgeau-Chavez, Richard H. Chen, Byung-Hun Choe, Leah K. Clayton, Thomas A. Douglas, Nancy French, Jean E. Holloway, Gang Hong, Lingcao Huang, Go Iwahana, Liza Jenkins, John S. Kimball, Tatiana Loboda, Michelle Mack, Philip Marsh, Roger J. Michaelides, Mahta Moghaddam, Andrew Parsekian, Kevin Schaefer, Paul R. Siqueira, Debjani Singh, Alireza Tabatabaeenejad, Merritt Turetsky, Ridha Touzi, Elizabeth Wig, Cathy J. Wilson, Paul Wilson, Stan D. Wullschleger, Yonghong Yi, Howard A. Zebker, Yu Zhang, Yuhuan Zhao, and Scott J. Goetz
Earth Syst. Sci. Data, 16, 2605–2624, https://doi.org/10.5194/essd-16-2605-2024, https://doi.org/10.5194/essd-16-2605-2024, 2024
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NASA’s Arctic Boreal Vulnerability Experiment (ABoVE) conducted airborne synthetic aperture radar (SAR) surveys of over 120 000 km2 in Alaska and northwestern Canada during 2017, 2018, 2019, and 2022. This paper summarizes those results and provides links to details on ~ 80 individual flight lines. This paper is presented as a guide to enable interested readers to fully explore the ABoVE L- and P-band SAR data.
Yiming Xu, Qianlai Zhuang, Bailu Zhao, Michael Billmire, Christopher Cook, Jeremy Graham, Nancy French, and Ronald Prinn
EGUsphere, https://doi.org/10.5194/egusphere-2024-1324, https://doi.org/10.5194/egusphere-2024-1324, 2024
Preprint archived
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We use a process-based model to simulate the fire impacts on soil thermal and hydrological dynamics and carbon budget of forest ecosystems in Northern Eurasia based on satellite-derived burn severity data. We find that fire severity generally increases in this region during the study period. Simulations indicate that fires increase soil temperature and water runoff. Fires lead the forest ecosystems to lose 2.3 Pg C, shifting the forests from a carbon sink to a source in this period.
Sarah M. Ludwig, Luke Schiferl, Jacqueline Hung, Susan M. Natali, and Roisin Commane
Biogeosciences, 21, 1301–1321, https://doi.org/10.5194/bg-21-1301-2024, https://doi.org/10.5194/bg-21-1301-2024, 2024
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Landscapes are often assumed to be homogeneous when using eddy covariance fluxes, which can lead to biases when calculating carbon budgets. In this study we report eddy covariance carbon fluxes from heterogeneous tundra. We used the footprints of each flux observation to unmix the fluxes coming from components of the landscape. We identified and quantified hot spots of carbon emissions in the landscape. Accurately scaling with landscape heterogeneity yielded half as much regional carbon uptake.
Nicole Jacobs, Christopher W. O'Dell, Thomas E. Taylor, Thomas L. Logan, Brendan Byrne, Matthäus Kiel, Rigel Kivi, Pauli Heikkinen, Aronne Merrelli, Vivienne H. Payne, and Abhishek Chatterjee
Atmos. Meas. Tech., 17, 1375–1401, https://doi.org/10.5194/amt-17-1375-2024, https://doi.org/10.5194/amt-17-1375-2024, 2024
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The accuracy of trace gas retrievals from spaceborne observations, like those from the Orbiting Carbon Observatory 2 (OCO-2), are sensitive to the referenced digital elevation model (DEM). Therefore, we evaluate several global DEMs, used in versions 10 and 11 of the OCO-2 retrieval along with the Copernicus DEM. We explore the impacts of changing the DEM on biases in OCO-2-retrieved XCO2 and inferred CO2 fluxes. Our findings led to an update to OCO-2 v11.1 using the Copernicus DEM globally.
Daniel H. Cusworth, Andrew K. Thorpe, Charles E. Miller, Alana K. Ayasse, Ralph Jiorle, Riley M. Duren, Ray Nassar, Jon-Paul Mastrogiacomo, and Robert R. Nelson
Atmos. Chem. Phys., 23, 14577–14591, https://doi.org/10.5194/acp-23-14577-2023, https://doi.org/10.5194/acp-23-14577-2023, 2023
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Carbon dioxide (CO2) emissions from combustion sources are uncertain in many places across the globe. Satellites have the ability to detect and quantify emissions from large CO2 point sources, including coal-fired power plants. In this study, we tasked two satellites to routinely observe CO2 emissions at 30 coal-fired power plants between 2021 and 2022. These results present the largest dataset of space-based CO2 emission estimates to date.
Jinsol Kim, John B. Miller, Charles E. Miller, Scott J. Lehman, Sylvia E. Michel, Vineet Yadav, Nick E. Rollins, and William M. Berelson
Atmos. Chem. Phys., 23, 14425–14436, https://doi.org/10.5194/acp-23-14425-2023, https://doi.org/10.5194/acp-23-14425-2023, 2023
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In this study, we present the partitioning of CO2 signals from biogenic, petroleum and natural gas sources by combining CO, 13CO2 and 14CO2 measurements. Using measurements from flask air samples at three sites in the greater Los Angeles region, we find larger and positive contributions of biogenic signals in winter and smaller and negative contributions in summer. The largest contribution of natural gas combustion generally occurs in summer.
Gifford H. Miller, Simon L. Pendleton, Alexandra Jahn, Yafang Zhong, John T. Andrews, Scott J. Lehman, Jason P. Briner, Jonathan H. Raberg, Helga Bueltmann, Martha Raynolds, Áslaug Geirsdóttir, and John R. Southon
Clim. Past, 19, 2341–2360, https://doi.org/10.5194/cp-19-2341-2023, https://doi.org/10.5194/cp-19-2341-2023, 2023
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Receding Arctic ice caps reveal moss killed by earlier ice expansions; 186 moss kill dates from 71 ice caps cluster at 250–450, 850–1000 and 1240–1500 CE and continued expanding 1500–1880 CE, as recorded by regions of sparse vegetation cover, when ice caps covered > 11 000 km2 but < 100 km2 at present. The 1880 CE state approached conditions expected during the start of an ice age; climate models suggest this was only reversed by anthropogenic alterations to the planetary energy balance.
Nathan Alec Conroy, Jeffrey M. Heikoop, Emma Lathrop, Dea Musa, Brent D. Newman, Chonggang Xu, Rachael E. McCaully, Carli A. Arendt, Verity G. Salmon, Amy Breen, Vladimir Romanovsky, Katrina E. Bennett, Cathy J. Wilson, and Stan D. Wullschleger
The Cryosphere, 17, 3987–4006, https://doi.org/10.5194/tc-17-3987-2023, https://doi.org/10.5194/tc-17-3987-2023, 2023
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This study combines field observations, non-parametric statistical analyses, and thermodynamic modeling to characterize the environmental causes of the spatial variability in soil pore water solute concentrations across two Arctic catchments with varying extents of permafrost. Vegetation type, soil moisture and redox conditions, weathering and hydrologic transport, and mineral solubility were all found to be the primary drivers of the existing spatial variability of some soil pore water solutes.
Vineet Yadav, Subhomoy Ghosh, and Charles E. Miller
Geosci. Model Dev., 16, 5219–5236, https://doi.org/10.5194/gmd-16-5219-2023, https://doi.org/10.5194/gmd-16-5219-2023, 2023
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Measuring the performance of inversions in linear Bayesian problems is crucial in real-life applications. In this work, we provide analytical forms of the local and global sensitivities of the estimated fluxes with respect to various inputs. We provide methods to uniquely map the observational signal to spatiotemporal domains. Utilizing this, we also show techniques to assess correlations between the Jacobians that naturally translate to nonstationary covariance matrix components.
Luana S. Basso, Chris Wilson, Martyn P. Chipperfield, Graciela Tejada, Henrique L. G. Cassol, Egídio Arai, Mathew Williams, T. Luke Smallman, Wouter Peters, Stijn Naus, John B. Miller, and Manuel Gloor
Atmos. Chem. Phys., 23, 9685–9723, https://doi.org/10.5194/acp-23-9685-2023, https://doi.org/10.5194/acp-23-9685-2023, 2023
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The Amazon’s carbon balance may have changed due to forest degradation, deforestation and warmer climate. We used an atmospheric model and atmospheric CO2 observations to quantify Amazonian carbon emissions (2010–2018). The region was a small carbon source to the atmosphere, mostly due to fire emissions. Forest uptake compensated for ~ 50 % of the fire emissions, meaning that the remaining forest is still a small carbon sink. We found no clear evidence of weakening carbon uptake over the period.
David T. Milodowski, T. Luke Smallman, and Mathew Williams
Biogeosciences, 20, 3301–3327, https://doi.org/10.5194/bg-20-3301-2023, https://doi.org/10.5194/bg-20-3301-2023, 2023
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Model–data fusion (MDF) allows us to combine ecosystem models with Earth observation data. Fragmented landscapes, with a mosaic of contrasting ecosystems, pose a challenge for MDF. We develop a novel MDF framework to estimate the carbon balance of fragmented landscapes and show the importance of accounting for ecosystem heterogeneity to prevent scale-dependent bias in estimated carbon fluxes, disturbance fluxes in particular, and to improve ecological fidelity of the calibrated models.
Stefano Potter, Sol Cooperdock, Sander Veraverbeke, Xanthe Walker, Michelle C. Mack, Scott J. Goetz, Jennifer Baltzer, Laura Bourgeau-Chavez, Arden Burrell, Catherine Dieleman, Nancy French, Stijn Hantson, Elizabeth E. Hoy, Liza Jenkins, Jill F. Johnstone, Evan S. Kane, Susan M. Natali, James T. Randerson, Merritt R. Turetsky, Ellen Whitman, Elizabeth Wiggins, and Brendan M. Rogers
Biogeosciences, 20, 2785–2804, https://doi.org/10.5194/bg-20-2785-2023, https://doi.org/10.5194/bg-20-2785-2023, 2023
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Here we developed a new burned-area detection algorithm between 2001–2019 across Alaska and Canada at 500 m resolution. We estimate 2.37 Mha burned annually between 2001–2019 over the domain, emitting 79.3 Tg C per year, with a mean combustion rate of 3.13 kg C m−2. We found larger-fire years were generally associated with greater mean combustion. The burned-area and combustion datasets described here can be used for local- to continental-scale applications of boreal fire science.
Thomas E. Taylor, Christopher W. O'Dell, David Baker, Carol Bruegge, Albert Chang, Lars Chapsky, Abhishek Chatterjee, Cecilia Cheng, Frédéric Chevallier, David Crisp, Lan Dang, Brian Drouin, Annmarie Eldering, Liang Feng, Brendan Fisher, Dejian Fu, Michael Gunson, Vance Haemmerle, Graziela R. Keller, Matthäus Kiel, Le Kuai, Thomas Kurosu, Alyn Lambert, Joshua Laughner, Richard Lee, Junjie Liu, Lucas Mandrake, Yuliya Marchetti, Gregory McGarragh, Aronne Merrelli, Robert R. Nelson, Greg Osterman, Fabiano Oyafuso, Paul I. Palmer, Vivienne H. Payne, Robert Rosenberg, Peter Somkuti, Gary Spiers, Cathy To, Brad Weir, Paul O. Wennberg, Shanshan Yu, and Jia Zong
Atmos. Meas. Tech., 16, 3173–3209, https://doi.org/10.5194/amt-16-3173-2023, https://doi.org/10.5194/amt-16-3173-2023, 2023
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NASA's Orbiting Carbon Observatory 2 and 3 (OCO-2 and OCO-3, respectively) provide complementary spatiotemporal coverage from a sun-synchronous and precession orbit, respectively. Estimates of total column carbon dioxide (XCO2) derived from the two sensors using the same retrieval algorithm show broad consistency over a 2.5-year overlapping time record. This suggests that data from the two satellites may be used together for scientific analysis.
Michael Moubarak, Seeta Sistla, Stefano Potter, Susan M. Natali, and Brendan M. Rogers
Biogeosciences, 20, 1537–1557, https://doi.org/10.5194/bg-20-1537-2023, https://doi.org/10.5194/bg-20-1537-2023, 2023
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Tundra wildfires are increasing in frequency and severity with climate change. We show using a combination of field measurements and computational modeling that tundra wildfires result in a positive feedback to climate change by emitting significant amounts of long-lived greenhouse gasses. With these effects, attention to tundra fires is necessary for mitigating climate change.
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
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Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
Peter Stimmler, Mathias Goeckede, Bo Elberling, Susan Natali, Peter Kuhry, Nia Perron, Fabrice Lacroix, Gustaf Hugelius, Oliver Sonnentag, Jens Strauss, Christina Minions, Michael Sommer, and Jörg Schaller
Earth Syst. Sci. Data, 15, 1059–1075, https://doi.org/10.5194/essd-15-1059-2023, https://doi.org/10.5194/essd-15-1059-2023, 2023
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Arctic soils store large amounts of carbon and nutrients. The availability of nutrients, such as silicon, calcium, iron, aluminum, phosphorus, and amorphous silica, is crucial to understand future carbon fluxes in the Arctic. Here, we provide, for the first time, a unique dataset of the availability of the abovementioned nutrients for the different soil layers, including the currently frozen permafrost layer. We relate these data to several geographical and geological parameters.
Andrew F. Feldman, Zhen Zhang, Yasuko Yoshida, Abhishek Chatterjee, and Benjamin Poulter
Atmos. Chem. Phys., 23, 1545–1563, https://doi.org/10.5194/acp-23-1545-2023, https://doi.org/10.5194/acp-23-1545-2023, 2023
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We investigate the conditions under which satellite-retrieved column carbon dioxide concentrations directly hold information about surface carbon dioxide fluxes, without the use of inversion models. We show that OCO-2 column carbon dioxide retrievals, available at 1–3 month latency, can be used to directly detect and roughly estimate extreme biospheric CO2 fluxes. As such, these OCO-2 retrievals have value for rapidly monitoring extreme conditions in the terrestrial biosphere.
Broghan M. Erland, Cristen Adams, Andrea Darlington, Mackenzie L. Smith, Andrew K. Thorpe, Gregory R. Wentworth, Steve Conley, John Liggio, Shao-Meng Li, Charles E. Miller, and John A. Gamon
Atmos. Meas. Tech., 15, 5841–5859, https://doi.org/10.5194/amt-15-5841-2022, https://doi.org/10.5194/amt-15-5841-2022, 2022
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Accurately estimating greenhouse gas (GHG) emissions is essential to reaching net-zero goals to combat the climate crisis. Airborne box-flights are ideal for assessing regional GHG emissions, as they can attain small error. We compare two box-flight algorithms and found they produce similar results, but daily variability must be considered when deriving emissions inventories. Increasing the consistency and agreement between airborne methods moves us closer to achieving more accurate estimates.
Brendan Byrne, Junjie Liu, Yonghong Yi, Abhishek Chatterjee, Sourish Basu, Rui Cheng, Russell Doughty, Frédéric Chevallier, Kevin W. Bowman, Nicholas C. Parazoo, David Crisp, Xing Li, Jingfeng Xiao, Stephen Sitch, Bertrand Guenet, Feng Deng, Matthew S. Johnson, Sajeev Philip, Patrick C. McGuire, and Charles E. Miller
Biogeosciences, 19, 4779–4799, https://doi.org/10.5194/bg-19-4779-2022, https://doi.org/10.5194/bg-19-4779-2022, 2022
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Plants draw CO2 from the atmosphere during the growing season, while respiration releases CO2 to the atmosphere throughout the year, driving seasonal variations in atmospheric CO2 that can be observed by satellites, such as the Orbiting Carbon Observatory 2 (OCO-2). Using OCO-2 XCO2 data and space-based constraints on plant growth, we show that permafrost-rich northeast Eurasia has a strong seasonal release of CO2 during the autumn, hinting at an unexpectedly large respiration signal from soils.
Vasileios Myrgiotis, Thomas Luke Smallman, and Mathew Williams
Biogeosciences, 19, 4147–4170, https://doi.org/10.5194/bg-19-4147-2022, https://doi.org/10.5194/bg-19-4147-2022, 2022
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This study shows that livestock grazing and grass cutting can determine whether a grassland is adding (source) or removing (sink) carbon (C) to/from the atmosphere. The annual C balance of 1855 managed grassland fields in Great Britain was quantified for 2017–2018 using process modelling and earth observation data. The examined fields were, on average, small C sinks, but the summer drought of 2018 led to a 9-fold increase in the number of fields that became C sources in 2018 compared to 2017.
Colm Sweeney, Abhishek Chatterjee, Sonja Wolter, Kathryn McKain, Robert Bogue, Stephen Conley, Tim Newberger, Lei Hu, Lesley Ott, Benjamin Poulter, Luke Schiferl, Brad Weir, Zhen Zhang, and Charles E. Miller
Atmos. Chem. Phys., 22, 6347–6364, https://doi.org/10.5194/acp-22-6347-2022, https://doi.org/10.5194/acp-22-6347-2022, 2022
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The Arctic Carbon Atmospheric Profiles (Arctic-CAP) project demonstrates the utility of aircraft profiles for independent evaluation of model-derived emissions and uptake of atmospheric CO2, CH4, and CO from land and ocean. Comparison with the Goddard Earth Observing System (GEOS) modeling system suggests that fluxes of CO2 are very consistent with observations, while those of CH4 have some regional and seasonal biases, and that CO comparison is complicated by transport errors.
Noriaki Ohara, Benjamin M. Jones, Andrew D. Parsekian, Kenneth M. Hinkel, Katsu Yamatani, Mikhail Kanevskiy, Rodrigo C. Rangel, Amy L. Breen, and Helena Bergstedt
The Cryosphere, 16, 1247–1264, https://doi.org/10.5194/tc-16-1247-2022, https://doi.org/10.5194/tc-16-1247-2022, 2022
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New variational principle suggests that a semi-ellipsoid talik shape (3D Stefan equation) is optimum for incoming energy. However, the lake bathymetry tends to be less ellipsoidal due to the ice-rich layers near the surface. Wind wave erosion is likely responsible for the elongation of lakes, while thaw subsidence slows the wave effect and stabilizes the thermokarst lakes. The derived 3D Stefan equation was compared to the field-observed talik thickness data using geophysical methods.
Lei Ma, George Hurtt, Lesley Ott, Ritvik Sahajpal, Justin Fisk, Rachel Lamb, Hao Tang, Steve Flanagan, Louise Chini, Abhishek Chatterjee, and Joseph Sullivan
Geosci. Model Dev., 15, 1971–1994, https://doi.org/10.5194/gmd-15-1971-2022, https://doi.org/10.5194/gmd-15-1971-2022, 2022
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We present a global version of the Ecosystem Demography (ED) model which can track vegetation 3-D structure and scale up ecological processes from individual vegetation to ecosystem scale. Model evaluation against multiple benchmarking datasets demonstrated the model’s capability to simulate global vegetation dynamics across a range of temporal and spatial scales. With this version, ED has the potential to be linked with remote sensing observations to address key scientific questions.
Yan Yang, A. Anthony Bloom, Shuang Ma, Paul Levine, Alexander Norton, Nicholas C. Parazoo, John T. Reager, John Worden, Gregory R. Quetin, T. Luke Smallman, Mathew Williams, Liang Xu, and Sassan Saatchi
Geosci. Model Dev., 15, 1789–1802, https://doi.org/10.5194/gmd-15-1789-2022, https://doi.org/10.5194/gmd-15-1789-2022, 2022
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Global carbon and water have large uncertainties that are hard to quantify in current regional and global models. Field observations provide opportunities for better calibration and validation of current modeling of carbon and water. With the unique structure of CARDAMOM, we have utilized the data assimilation capability and designed the benchmarking framework by using field observations in modeling. Results show that data assimilation improves model performance in different aspects.
Thomas E. Taylor, Christopher W. O'Dell, David Crisp, Akhiko Kuze, Hannakaisa Lindqvist, Paul O. Wennberg, Abhishek Chatterjee, Michael Gunson, Annmarie Eldering, Brendan Fisher, Matthäus Kiel, Robert R. Nelson, Aronne Merrelli, Greg Osterman, Frédéric Chevallier, Paul I. Palmer, Liang Feng, Nicholas M. Deutscher, Manvendra K. Dubey, Dietrich G. Feist, Omaira E. García, David W. T. Griffith, Frank Hase, Laura T. Iraci, Rigel Kivi, Cheng Liu, Martine De Mazière, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Matthias Schneider, Coleen M. Roehl, Mahesh Kumar Sha, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Yao Té, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, and Debra Wunch
Earth Syst. Sci. Data, 14, 325–360, https://doi.org/10.5194/essd-14-325-2022, https://doi.org/10.5194/essd-14-325-2022, 2022
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We provide an analysis of an 11-year record of atmospheric carbon dioxide (CO2) concentrations derived using an optimal estimation retrieval algorithm on measurements made by the GOSAT satellite. The new product (version 9) shows improvement over the previous version (v7.3) as evaluated against independent estimates of CO2 from ground-based sensors and atmospheric inversion systems. We also compare the new GOSAT CO2 values to collocated estimates from NASA's Orbiting Carbon Observatory-2.
Stephanie G. Stettz, Nicholas C. Parazoo, A. Anthony Bloom, Peter D. Blanken, David R. Bowling, Sean P. Burns, Cédric Bacour, Fabienne Maignan, Brett Raczka, Alexander J. Norton, Ian Baker, Mathew Williams, Mingjie Shi, Yongguang Zhang, and Bo Qiu
Biogeosciences, 19, 541–558, https://doi.org/10.5194/bg-19-541-2022, https://doi.org/10.5194/bg-19-541-2022, 2022
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Uncertainty in the response of photosynthesis to temperature poses a major challenge to predicting the response of forests to climate change. In this paper, we study how photosynthesis in a mountainous evergreen forest is limited by temperature. This study highlights that cold temperature is a key factor that controls spring photosynthesis. Including the cold-temperature limitation in an ecosystem model improved its ability to simulate spring photosynthesis.
Anna-Maria Virkkala, Susan M. Natali, Brendan M. Rogers, Jennifer D. Watts, Kathleen Savage, Sara June Connon, Marguerite Mauritz, Edward A. G. Schuur, Darcy Peter, Christina Minions, Julia Nojeim, Roisin Commane, Craig A. Emmerton, Mathias Goeckede, Manuel Helbig, David Holl, Hiroki 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, Han Dolman, Colin W. Edgar, Bo Elberling, Eugenie Euskirchen, Achim Grelle, Juha Hatakka, Elyn Humphreys, Järvi Järveoja, Ayumi Kotani, Lars Kutzbach, Tuomas Laurila, Annalea Lohila, Ivan Mammarella, Yojiro Matsuura, Gesa Meyer, Mats B. Nilsson, Steven F. Oberbauer, Sang-Jong Park, Roman Petrov, Anatoly S. Prokushkin, Christopher Schulze, Vincent L. St. Louis, Eeva-Stiina Tuittila, Juha-Pekka Tuovinen, William Quinton, Andrej Varlagin, Donatella Zona, and Viacheslav I. Zyryanov
Earth Syst. Sci. Data, 14, 179–208, https://doi.org/10.5194/essd-14-179-2022, https://doi.org/10.5194/essd-14-179-2022, 2022
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The effects of climate warming on carbon cycling across the Arctic–boreal zone (ABZ) remain poorly understood due to the relatively limited distribution of ABZ flux sites. Fortunately, this flux network is constantly increasing, but new measurements are published in various platforms, making it challenging to understand the ABZ carbon cycle as a whole. Here, we compiled a new database of Arctic–boreal CO2 fluxes to help facilitate large-scale assessments of the ABZ carbon cycle.
Thomas Luke Smallman, David Thomas Milodowski, Eráclito Sousa Neto, Gerbrand Koren, Jean Ometto, and Mathew Williams
Earth Syst. Dynam., 12, 1191–1237, https://doi.org/10.5194/esd-12-1191-2021, https://doi.org/10.5194/esd-12-1191-2021, 2021
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Our study provides a novel assessment of model parameter, structure and climate change scenario uncertainty contribution to future predictions of the Brazilian terrestrial carbon stocks to 2100. We calibrated (2001–2017) five models of the terrestrial C cycle of varied structure. The calibrated models were then projected to 2100 under multiple climate change scenarios. Parameter uncertainty dominates overall uncertainty, being ~ 40 times that of either model structure or climate change scenario.
David Olefeldt, Mikael Hovemyr, McKenzie A. Kuhn, David Bastviken, Theodore J. Bohn, John Connolly, Patrick Crill, Eugénie S. Euskirchen, Sarah A. Finkelstein, Hélène Genet, Guido Grosse, Lorna I. Harris, Liam Heffernan, Manuel Helbig, Gustaf Hugelius, Ryan Hutchins, Sari Juutinen, Mark J. Lara, Avni Malhotra, Kristen Manies, A. David McGuire, Susan M. Natali, Jonathan A. O'Donnell, Frans-Jan W. Parmentier, Aleksi Räsänen, Christina Schädel, Oliver Sonnentag, Maria Strack, Suzanne E. Tank, Claire Treat, Ruth K. Varner, Tarmo Virtanen, Rebecca K. Warren, and Jennifer D. Watts
Earth Syst. Sci. Data, 13, 5127–5149, https://doi.org/10.5194/essd-13-5127-2021, https://doi.org/10.5194/essd-13-5127-2021, 2021
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Wetlands, lakes, and rivers are important sources of the greenhouse gas methane to the atmosphere. To understand current and future methane emissions from northern regions, we need maps that show the extent and distribution of specific types of wetlands, lakes, and rivers. The Boreal–Arctic Wetland and Lake Dataset (BAWLD) provides maps of five wetland types, seven lake types, and three river types for northern regions and will improve our ability to predict future methane emissions.
Cited articles
Alaska Large Fire Database | FRAMES: https://www.frames.gov/catalog/10465, last access: 21 December 2022.
Arndt, K. A., Santos, M. J., Ustin, S., Davidson, S. J., Stow, D., Oechel, W. C., Tran, T. T. P., Graybill, B., and Zona, D.: Arctic greening associated with lengthening growing seasons in Northern Alaska, Environ. Res. Lett., 14, 125018, https://doi.org/10.1088/1748-9326/ab5e26, 2019.
Berner, L. T., Massey, R., Jantz, P., Forbes, B. C., Macias-Fauria, M., Myers-Smith, I., Kumpula, T., Gauthier, G., Andreu-Hayles, L., Gaglioti, B. V., Burns, P., Zetterberg, P., D'Arrigo, R., and Goetz, S. J.: Summer warming explains widespread but not uniform greening in the Arctic tundra biome, Nat. Commun., 11, 4621, https://doi.org/10.1038/s41467-020-18479-5, 2020.
Berner, L. T., Jantz, P., Tape, K. D., and Goetz, S. J.: ABoVE: Gridded 30-m Aboveground Biomass, Shrub Dominance, North Slope, AK, 2007–2016, ORNL DAAC [data set], Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1565, 2018.
Breen, A. L.: Arctic Vegetation Plots in Burned and Unburned Tundra, Alaska, 2011–2012, ORNL DAAC [data set], Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1547, 2018a.
Breen, A. L.: Arctic Vegetation Plots, Poplars, Arctic and Interior AK and YT, Canada, 2003–2005, ORNL DAAC [data set], Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1376, 2018b.
CAVM Team: Circumpolar Arctic Vegetation Map, U.S. Fish and Wildlife Service, Anchorage, Alaska, ISBN 0-9767525-0-6, 2003.
Chapin, F. S., Sturm, M., Serreze, M. C., McFadden, J. P., Key, J. R., Lloyd, A. H., McGuire, A. D., Rupp, T. S., Lynch, A. H., Schimel, J. P., Beringer, J., Chapman, W. L., Epstein, H. E., Euskirchen, E. S., Hinzman, L. D., Jia, G., Ping, C.-L., Tape, K. D., Thompson, C. D. C., Walker, D. A., and Welker, J. M.: Role of Land-Surface Changes in Arctic Summer Warming, Science, 310, 657–660, https://doi.org/10.1126/science.1117368, 2005.
Chen, D., Zhu, X., Kogure, M., Hoy, E. E., Xu, X., French, N. H. F., Berner, L. T., Breen, A. L., Bret-Harte, S., Davidson, S. J., Ebersole, J. J., Frost, G. V., Goetz, S. J., Hewitt, R. E., Hung, J. K. Y., Iversen, C. M., Iwahana, G., Jandt, R., Jenkins, L. K., Kade, A. N., Klupar, I., Loboda, T. V., Ludwig, S., Macander, M. J., Mack, M. C., Meyers, C. R., Michaelides, R. J., Miller, E. A., Natali, S., Nawrocki, T. W., Nelson, P. R., Parsekian, A. D., Rastetter, E., Raynolds, M. K., Rocha, A. V., Schaefer, K., Schickhoff, U., Schuur, E. a. G., Tsuyuzaki, S., Tweedie, C. E., Zesati, S. V., Walker, D. A., Webber, P. J., Williams, M., and Zona, D.: Field Data on Soils, Vegetation, and Fire History for Alaska Tundra Sites, 1972–2020, ORNL DAAC [data set], https://doi.org/10.3334/ORNLDAAC/2177, 2023.
Chen, Y., Hu, F. S., and Lara, M. J.: Divergent shrub-cover responses driven by climate, wildfire, and permafrost interactions in Arctic tundra ecosystems, Glob. Change Biol., 27, 652–663, https://doi.org/10.1111/gcb.15451, 2021.
Davidson, S. J. and Zona, D.: Arctic Vegetation Plots in Flux Tower Footprints, North Slope, Alaska, 2014, ORNL DAAC [data set], Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1546, 2018.
Dial, R. J., Maher, C. T., Hewitt, R. E., and Sullivan, P. F.: Sufficient conditions for rapid range expansion of a boreal conifer, Nature, 608, 546–551, https://doi.org/10.1038/s41586-022-05093-2, 2022.
Ebersole, J. J.: Arctic Vegetation Plots at Oumalik, AK, 1983–1985, ORNL DAAC [data set], Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1506, 2018.
Ernakovich, J. G., Hopping, K. A., Berdanier, A. B., Simpson, R. T., Kachergis, E. J., Steltzer, H., and Wallenstein, M. D.: Predicted responses of arctic and alpine ecosystems to altered seasonality under climate change, Glob. Change Biol., 20, 3256–3269, https://doi.org/10.1111/gcb.12568, 2014.
French, N. H. F., Jenkins, L. K., Loboda, T. V., Flannigan, M., Jandt, R., Bourgeau-Chavez, L. L., and Whitley, M.: Fire in arctic tundra of Alaska: past fire activity, future fire potential, and significance for land management and ecology, Int. J. Wildland Fire, 24, 1045–1061, https://doi.org/10.1071/WF14167, 2015.
Frost, G. V., Loehman, R. A., Nelson, P. R., and Paradis, D. P.: ABoVE: Vegetation Composition across Fire History Gradients on the Y-K Delta, Alaska, ORNL DAAC [data set], Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1772, 2020.
Gallant, A. L., Binnian, E. F., Omernik, J. M., and Shasby, M. B.: Ecoregions of Alaska, U.S. Geological Survey Professional Paper 1567, 73, United States Government Printing Office: Washington, DC, USA, 1995.
Goetz, S. J., Bunn, A. G., Fiske, G. J., and Houghton, R. A.: Satellite-observed photosynthetic trends across boreal North America associated with climate and fire disturbance, P. Natl. Acad. Sci. USA, 102, 13521–13525, https://doi.org/10.1073/pnas.0506179102, 2005.
Hagedorn, F., Shiyatov, S. G., Mazepa, V. S., Devi, N. M., Grigor'ev, A. A., Bartysh, A. A., Fomin, V. V., Kapralov, D. S., Terent'ev, M., Bugman, H., Rigling, A., and Moiseev, P. A.: Treeline advances along the Urals mountain range – driven by improved winter conditions?, Glob. Change Biol., 20, 3530–3543, https://doi.org/10.1111/gcb.12613, 2014.
He, J., Chen, D., Jenkins, L., and Loboda, T. V.: Impacts of wildfire and landscape factors on organic soil properties in Arctic tussock tundra, Environ. Res. Lett., 16, 085004, https://doi.org/10.1088/1748-9326/ac1192, 2021.
Heijmans, M. M. P. D., Magnússon, R. Í., Lara, M. J., Frost, G. V., Myers-Smith, I. H., van Huissteden, J., Jorgenson, M. T., Fedorov, A. N., Epstein, H. E., Lawrence, D. M., and Limpens, J.: Tundra vegetation change and impacts on permafrost, Nat. Rev. Earth Environ., 3, 68–84, https://doi.org/10.1038/s43017-021-00233-0, 2022.
Hollingsworth, T. N., Breen, A., Mack, M. C., and Hewitt, R. E.: Seward Peninsula post-fire vegetation and soil data from multiple burns occurring from 1971 to 2012: “SPANFire” Study Sites Sampled in July 2012, http://www.lter.uaf.edu/data/data-detail/id/752 (last access: 15 August 2024), 2020.
Hu, F. S., Higuera, P. E., Walsh, J. E., Chapman, W. L., Duffy, P. A., Brubaker, L. B., and Chipman, M. L.: Tundra burning in Alaska: Linkages to climatic change and sea ice retreat, J. Geophys. Res.-Biogeo., 115, G04002, https://doi.org/10.1029/2009JG001270, 2010.
Iwahana, G., Harada, K., Uchida, M., Tsuyuzaki, S., Saito, K., Narita, K., Kushida, K., and Hinzman, L. D.: Geomorphological and geochemistry changes in permafrost after the 2002 tundra wildfire in Kougarok, Seward Peninsula, Alaska, J. Geophys. Res.-Earth, 121, 1697–1715, https://doi.org/10.1002/2016JF003921, 2016.
Jandt, R., Joly, K., Meyers, C. R., and Racine, C.: Slow recovery of lichen on burned caribou winter range in Alaska tundra: Potential influences of climate warming and other disturbance factors, Arct. Antarct. Alp. Res., 40, 89–95, https://doi.org/10.1657/1523-0430(06-122)[jandt]2.0.co;2, 2008.
Jandt, R. R. and Meyers, C. R.: Recovery of lichen in tussock tundra following fire in northwestern Alaska, in: US Department of the Interior, Bureau of Land Management, Alaska State Office, https://doi.org/10.5962/BHL.TITLE.61209, 2000.
Jorgenson, M. T.: Arctic Vegetation Plots in NPS Arctic Network Parks, Alaska, 2002–2008, ORNL DAAC [data set], Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1542, 2018.
Kade, A. N.: Arctic Vegetation Plots at Frost Boil Sites, North Slope, Alaska, 2000–2006, ORNL DAAC [data set], Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1361, 2018.
Kasischke, E. S., Williams, D., and Barry, D.: Analysis of the patterns of large fires in the boreal forest region of Alaska, Int. J. Wildland Fire, 11, 131–144, 2002.
Kaufman, D. S., Schneider, D. P., McKay, N. P., Ammann, C. M., Bradley, R. S., Briffa, K. R., Miller, G. H., Otto-Bliesner, B. L., Overpeck, J. T., Vinther, B. M., Members, P., Abbott, M., Axford, Y., Bird, B., B. Birks, H. J., Bjune, A. E., Briner, J., Cook, T., Chipman, M., Fracus, P., Gajewski, K., Geirsdóttir, Á., Hu, F. S., Kutchko, B., Lamoureux, S., Loso, M., MacDonald, G., Peros, M., Porinchu, D., Schiff, C., Seppä, H., and Thomas, E.: Recent Warming Reverses Long-Term Arctic Cooling, Science, 325, 1236–1239, https://doi.org/10.1126/science.1173983, 2009.
Lewkowicz, A. G. and Way, R. G.: Extremes of summer climate trigger thousands of thermokarst landslides in a High Arctic environment, Nat. Commun., 10, 1329, https://doi.org/10.1038/s41467-019-09314-7, 2019.
Loboda, T. V., Chen, D., Hall, J. V., and He, J.: ABoVE: Landsat-derived Burn Scar dNBR across Alaska and Canada, 1985–2015, ORNL DAAC [data set], https://doi.org/10.3334/ORNLDAAC/1564, 2018.
Loboda, T. V., Jenkins, L. K., Chen, D., He, J., and Baer, A.: Burned and Unburned Field Site Data, Noatak, Seward, and North Slope, AK, 2016–2018, ORNL DAAC [data set], Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1919, 2022.
Ludwig, S., Holmes, R. M., Schade, J., Natali, S., and Mann, P.: Polaris Project 2017: Vegetation biomass, carbon, and nitrogen, Yukon-Kuskokwim Delta, Alaska, Arctic Data Center [data set], https://doi.org/10.18739/A2FJ29D12, 2018a.
Ludwig, S., Holmes, R. M., Natali, S., Mann, P., and Schade, J.: Polaris Project 2017: Soil fluxes, carbon, and nitrogen, Yukon-Kuskokwim Delta, Alaska, Arctic Data Center [data set], https://doi.org/10.18739/A2Q23R08G, 2018b.
Ludwig, S., Holmes, R. M., Natali, S., Schade, J., and Mann, P.: Yukon-Kuskokwim Delta fire: vegetation biomass, Yukon-Kuskokwim Delta Alaska, 2016, Arctic Data Center [data set], https://doi.org/10.18739/A29S1KK6T, 2018c.
Macander, M. J., Frost, G. V., Nelson, P. R., and Swingley, C. S.: ABoVE: Tundra Plant Functional Type Continuous-Cover, North Slope, Alaska, 2010–2015, ORNL DAAC [data set], Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1830, 2020.
Mack, M.: Characterization of burned and unburned moist acidic tundra sites for estimating C and N loss from the 2007 Anaktuvuk River Fire, sampled in 2008. ver 5., Environmental Data Initiative, https://doi.org/10.6073/pasta/81868b65c853d5eb2052d9f1a8397d0d, 2016.
Mack, M. C., Bret-Harte, M. S., Hollingsworth, T. N., Jandt, R. R., Schuur, E. A. G., Shaver, G. R., and Verbyla, D. L.: Carbon loss from an unprecedented Arctic tundra wildfire, Nature, 475, 489–492, https://doi.org/10.1038/nature10283, 2011.
Masrur, A., Petrov, A. N., and DeGroote, J.: Circumpolar spatio-temporal patterns and contributing climatic factors of wildfire activity in the Arctic tundra from 2001–2015, Environ. Res. Lett., 13, 014019, https://doi.org/10.1088/1748-9326/aa9a76, 2018.
Mekonnen, Z. A., Riley, W. J., Berner, L. T., Bouskill, N. J., Torn, M. S., Iwahana, G., Breen, A. L., Myers-Smith, I. H., Criado, M. G., Liu, Y., Euskirchen, E. S., Goetz, S. J., Mack, M. C., and Grant, R. F.: Arctic tundra shrubification: a review of mechanisms and impacts on ecosystem carbon balance, Environ. Res. Lett., 16, 053001, https://doi.org/10.1088/1748-9326/abf28b, 2021.
Miller, E. A., Jandt, R., Baughman, C. A., Jones, B. M., and Yokel, D. A.: ABoVE: Post-Fire and Unburned Field Site Data, Anaktuvuk River Fire Area, 2008–2017, ORNL DAAC [data set], Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/2119, 2022.
Miller, E. A., Jones, B. M., Baughman, C. A., Jandt, R. R., Jenkins, J. L., and Yokel, D. A.: Unrecorded Tundra Fires of the Arctic Slope, Alaska USA, Fire, 6, 101, https://doi.org/10.3390/fire6030101, 2023.
Myers-Smith, I. H., Kerby, J. T., Phoenix, G. K., Bjerke, J. W., Epstein, H. E., Assmann, J. J., John, C., Andreu-Hayles, L., Angers-Blondin, S., Beck, P. S. A., Berner, L. T., Bhatt, U. S., Bjorkman, A. D., Blok, D., Bryn, A., Christiansen, C. T., Cornelissen, J. H. C., Cunliffe, A. M., Elmendorf, S. C., Forbes, B. C., Goetz, S. J., Hollister, R. D., de Jong, R., Loranty, M. M., Macias-Fauria, M., Maseyk, K., Normand, S., Olofsson, J., Parker, T. C., Parmentier, F.-J. W., Post, E., Schaepman-Strub, G., Stordal, F., Sullivan, P. F., Thomas, H. J. D., Tømmervik, H., Treharne, R., Tweedie, C. E., Walker, D. A., Wilmking, M., and Wipf, S.: Complexity revealed in the greening of the Arctic, Nat. Clim. Change, 10, 106–117, https://doi.org/10.1038/s41558-019-0688-1, 2020.
Natali, S.: Yukon-Kuskokwim Delta fire: thaw depth, soil temperature, and point-intercept vegetation, Yukon-Kuskokwim Delta Alaska, 2015–2016, Arctic Data Center [data set], https://doi.org/10.18739/A2707WP16, 2018.
Nawrocki, T. W., Wells, A. F., Macander, M. J., Powers, E. M., Flagstad, L. A., Droghini, A., Gravely, H. A., Steer, M. A., Frost, G. V., Boucher, T. V., Roland, C. A., Miller, A. E., Swanson, D. K., and Johanson, J. K.: Alaska Vegetation Plots (AKVEG) Database, University of Alaska Anchorage, https://akveg.uaa.alaska.edu (last access: 12 April 2023), 2022.
Oechel, W. C., Hastings, S. J., Vourlrtis, G., Jenkins, M., Riechers, G., and Grulke, N.: Recent change of Arctic tundra ecosystems from a net carbon dioxide sink to a source, Nature, 361, 520–523, https://doi.org/10.1038/361520a0, 1993.
Olefeldt, D., Hovemyr, M., Kuhn, M., Bastviken, D., and Bohn, T.: The fractional land cover estimates from the Boreal-Arctic Wetland and Lake Dataset (BAWLD), 2021, Arctic Data Center [data set], https://doi.org/10.18739/A2C824F9X, 2021.
Rantanen, M., Karpechko, A. Yu., Lipponen, A., Nordling, K., Hyvärinen, O., Ruosteenoja, K., Vihma, T., and Laaksonen, A.: The Arctic has warmed nearly four times faster than the globe since 1979, Commun. Earth Environ.t, 3, 168, https://doi.org/10.1038/s43247-022-00498-3, 2022.
Raynolds, M. K.: Arctic Vegetation Plots ATLAS Project North Slope and Seward Peninsula, AK, 1998–2000, ORNL DAAC [data set], Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1541, 2018.
Raynolds, M. K., Walker, D. A., Balser, A., Bay, C., Campbell, M., Cherosov, M. M., Daniëls, F. J. A., Eidesen, P. B., Ermokhina, K. A., Frost, G. V., Jedrzejek, B., Jorgenson, M. T., Kennedy, B. E., Kholod, S. S., Lavrinenko, I. A., Lavrinenko, O. V., Magnússon, B., Matveyeva, N. V., Metúsalemsson, S., Nilsen, L., Olthof, I., Pospelov, I. N., Pospelova, E. B., Pouliot, D., Razzhivin, V., Schaepman-Strub, G., Šibík, J., Telyatnikov, M. Yu., and Troeva, E.: A raster version of the Circumpolar Arctic Vegetation Map (CAVM), Remote Sens. Environ., 232, 111297, https://doi.org/10.1016/j.rse.2019.111297, 2019.
Rees, W. G., Hofgaard, A., Boudreau, S., Cairns, D. M., Harper, K., Mamet, S., Mathisen, I., Swirad, Z., and Tutubalina, O.: Is subarctic forest advance able to keep pace with climate change?, Glob. Change Biol., 26, 3965–3977, https://doi.org/10.1111/gcb.15113, 2020.
Rocha, A.: Leaf area index (LAI) recorded from a nitrogen (N), phosphorus (P) and N+P fertilization experiment at the 2007 Anaktuvuk River, Alaska, USA fire scar during the 2016–2019 growing seasons ver 2, Environmental Data Initiative [data set], https://doi.org/10.6073/pasta/06559231aa04fd7fecd661f107985c8f, 2020.
Rocha, A. and Shaver, G.: Anaktuvuk River fire scar thaw depth measurements during the 2008 to 2014 growing season ver 6, Environmental Data Initiative [data set], https://doi.org/10.6073/pasta/93121fc86e6fbcf88de4a9350609aed6, 2016.
Rocha, A. V., Blakely, B., Jiang, Y., Wright, K. S., and Curasi, S. R.: Is arctic greening consistent with the ecology of tundra? Lessons from an ecologically informed mass balance model, Environ. Res. Lett., 13, 125007, https://doi.org/10.1088/1748-9326/aaeb50, 2018.
Russell, I. C.: Notes on the Surface Geology of Alaska, GSA Bull., 1, 99–162, https://doi.org/10.1130/GSAB-1-99, 1890.
Schaefer, K., Clayton, L. K., Battaglia, M. J., Bourgeau-Chavez, L. L., Chen, R. H., Chen, A. C., Chen, J., Bakian-Dogaheh, K., Douglas, T. A., Grelick, S. E., Iwahana, G., Jafarov, E., Liu, L., Ludwig, S., Michaelides, R. J., Moghaddam, M., Natali, S., Panda, S. K., Parsekian, A. D., Rocha, A. V., Schaefer, S. R., Sullivan, T. D., Tabatabaeenejad, A., Wang, K., Wilson, C. J., Zebker, H. A., Zhang, T., and Zhao, Y.: ABoVE: Soil Moisture and Active Layer Thickness in Alaska and NWT, Canada, 2008–2020, ORNL DAAC [data set], Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1903, 2021.
Schickhoff, U.: Arctic Vegetation Plots in Willow Communities, North Slope, Alaska, 1997, ORNL DAAC [data set], Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1368, 2018.
Schrader, F. C.: Recent Work of the U. S. Geological Survey in Alaska, Bull. Am. Geogr. Soc., 34, 1–16, https://doi.org/10.2307/198855, 1902.
Schuur, E. A. G., Crummer, K. G., Vogel, J. G., and Mack, M. C.: Plant Species Composition and Productivity following Permafrost Thaw and Thermokarst in Alaskan Tundra, Ecosystems, 10, 280–292, https://doi.org/10.1007/s10021-007-9024-0, 2007.
Schuur, E. A. G., McGuire, A. D., Schädel, C., Grosse, G., Harden, J. W., Hayes, D. J., Hugelius, G., Koven, C. D., Kuhry, P., Lawrence, D. M., Natali, S. M., Olefeldt, D., Romanovsky, V. E., Schaefer, K., Turetsky, M. R., Treat, C. C., and Vonk, J. E.: Climate change and the permafrost carbon feedback, Nature, 520, 171–179, https://doi.org/10.1038/nature14338, 2015.
Shaver, G.: Leaf Area Index every 15 cm of 1m x 1m chamber flux and point frame plots and sites where dataloggers monitored PAR above, within and below S. pulchra and B. nana canopies during the growing season at the Toolik Field Station in AK, Summer 2012, Environmental Data Initiative [data set], https://doi.org/10.6073/pasta/627698983259d6963a6083d5251723cc, 2012.
Shaver, G.: Summary of soil temperature, moisture, and thaw depth for 14 chamber flux measurements sampled near LTER shrub sites at Toolik Field Station, Alaska, summer 2012, Environmental Data Initiative [data set], https://doi.org/10.6073/pasta/7ccf390e6fe4824e93b7a2b844605a40, 2013.
Shaver, G.: Summary of three different Leaf Area Index (LAI) methodologies of 19 1m x 1m point frame plots sampled near the LTER Shrub plots at Toolik Field Station in AK the summer of 2012, Environmental Data Initiative [data set], https://doi.org/10.6073/pasta/17302da4bd951a9dc4140187f03fae24, 2023.
Shaver, G. and Laundre, J.: Summer soil temperature and moisture at the Anaktuvuk River Severely burned site from 2010 to 2013, ver 2, Environmental Data Initiative [data set], https://doi.org/10.6073/pasta/3094e3e293703580c95e17ddce51af65, 2016.
Sloan, V. L.: Arctic Vegetation Plots for NGEE-Arctic at Barrow, Alaska, 2012, ORNL DAAC [data set], Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1505, 2018.
Tsuyuzaki, S., Iwahana, G., and Saito, K.: Tundra fire alters vegetation patterns more than the resultant thermokarst, Polar Biol., 41, 753–761, https://doi.org/10.1007/s00300-017-2236-7, 2018.
Tweedie, C. E., Webber, P. J., Komarkova, V., and Villarreal, S.: Arctic Vegetation Plots at Atqasuk, Alaska, 1975, 2000, and 2010, ORNL DAAC [data set], Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1371, 2018.
Walker, D. A.: Arctic Vegetation Plots Legacy Project Barter Island and Point Barrow, Alaska, 1994, ORNL DAAC [data set], Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1534, 2018a.
Walker, D. A.: Arctic Vegetation Plots, Prudhoe Bay ArcSEES Road Study, Lake Colleen, Alaska, 2014, ORNL DAAC [data set], Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1555, 2018b.
Walker, M. D.: Arctic Vegetation Plots from Pingo Communities, North Slope, Alaska, 1984–1986, ORNL DAAC [data set], Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1507, 2018c.
Walker, D. A.: Arctic Vegetation Plots at Happy Valley, Alaska, 1994, ORNL DAAC [data set], Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1354, 2018d.
Walker, D. A.: Arctic Vegetation Plots at Imnavait Creek, Alaska, 1984–1985, ORNL DAAC [data set], Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1356, 2018e.
Walker, D. A.: Arctic Vegetation Plots at Toolik Lake, Alaska, 1989, ORNL DAAC [data set], Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1333, 2018f.
Walker, D. A., Raynolds, M. K., Daniëls, F. J. A., Einarsson, E., Elvebakk, A., Gould, W. A., Katenin, A. E., Kholod, S. S., Markon, C. J., Melnikov, E. S., Moskalenko, N. G., Talbot, S. S., Yurtsev, B. A., and other members of the CAVM Team: The Circumpolar Arctic Vegetation Map, J. Veg. Sci., 16, 267–282, 2005.
Webber, P. J., Villarreal, S., and Tweedie, C. E.: Arctic Vegetation Plots for IBP Tundra Biome, Barrow, Alaska, 1972–2010, ORNL DAAC, Oak Ridge, Tennessee, USA, https://doi.org/10.3334/ORNLDAAC/1535, 2018.
Williams, M. and Rastetter, E.: Measurements of Leaf area, foliar C and N for 14 sites along a transect down the Kuparuk River basin, summer 1997, North Slope, Alaska. Environmental Data Initiative [data set], https://doi.org/10.6073/pasta/a5a4d4154e0a8181a5523b4d9c49ed99, 1999.
Short summary
The Arctic tundra is experiencing widespread physical and biological changes, largely in response to warming, yet scientific understanding of tundra ecology and change remains limited due to relatively limited accessibility and studies compared to other terrestrial biomes. To support synthesis research and inform future studies, we created the Synthesized Alaskan Tundra Field Dataset (SATFiD), which brings together field datasets and includes vegetation, active-layer, and fire properties.
The Arctic tundra is experiencing widespread physical and biological changes, largely in...
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