Articles | Volume 22, issue 20
https://doi.org/10.5194/bg-22-6097-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-22-6097-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
28 Oct 2025
Research article |
| 28 Oct 2025
| 28 Oct 2025
Soil signals of key mechanisms driving greater protection of organic carbon under aspen compared to spruce forests in a North American montane ecosystem
Lena Wang
College of Earth Ocean and Atmospheric Science, Oregon State University, 101 SW 26th St, Corvallis, OR 97331, USA
Sharon A. Billings
Department of Ecology and Evolutionary Biology and Kansas Biological Survey & Center for Ecological Research, University of Kansas, 2101 Constant Ave., Lawrence, KS 66047, USA
Department of Civil and Environmental Engineering, Pennsylvania State University, 212 Sackett, University Park, PA 16802, USA
Daniel R. Hirmas
Department of Plant and Soil Science, Texas Tech University, 2500 Broadway Lubbock, TX 7940, USA
Keira Johnson
College of Earth Ocean and Atmospheric Science, Oregon State University, 101 SW 26th St, Corvallis, OR 97331, USA
Devon Kerins
Department of Civil and Environmental Engineering, Pennsylvania State University, 212 Sackett, University Park, PA 16802, USA
Julio Pachon
Sydney Institute of Agriculture, School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW 2006, Australia
Curtis Beutler
Lawrence Berkeley National Laboratory, Berkeley CA, 1 Cyclotron Road, Berkeley, CA 94720, USA
Department of Environmental Sciences, University of California Riverside, 2460B Geology Building, Riverside, CA 92521, USA
Karla M. Jarecke
College of Earth Ocean and Atmospheric Science, Oregon State University, 101 SW 26th St, Corvallis, OR 97331, USA
Vaishnavi Varikuti
Department of Plant and Soil Science, Texas Tech University, 2500 Broadway Lubbock, TX 7940, USA
Micah Unruh
Department of Ecology and Evolutionary Biology and Kansas Biological Survey & Center for Ecological Research, University of Kansas, 2101 Constant Ave., Lawrence, KS 66047, USA
Hoori Ajami
Rocky Mountain Biological Laboratory, Gothic 8000 Co Rd 317, Crested Butte, CO 81224, USA
Holly Barnard
Department of Geography, Institute of Arctic and Alpine Research, University of Colorado – Boulder, Guggenheim 110, 260 UCB, Boulder, CO 80309-0260, USA
Alejandro N. Flores
Department of Geosciences, Boise State University, 1295 University Drive, Boise, ID 83706, USA
Kenneth Williams
Lawrence Berkeley National Laboratory, Berkeley CA, 1 Cyclotron Road, Berkeley, CA 94720, USA
Department of Environmental Sciences, University of California Riverside, 2460B Geology Building, Riverside, CA 92521, USA
Pamela L. Sullivan
CORRESPONDING AUTHOR
College of Earth Ocean and Atmospheric Science, Oregon State University, 101 SW 26th St, Corvallis, OR 97331, USA
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Kachinga Silwimba, Alejandro N. Flores, Irene Cionni, Sharon A. Billings, Pamela L. Sullivan, Hoori Ajami, Daniel R. Hirmas, and Li Li
Geosci. Model Dev., 18, 7707–7734, https://doi.org/10.5194/gmd-18-7707-2025, https://doi.org/10.5194/gmd-18-7707-2025, 2025
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Land models need reliable soil properties to simulate water, but these settings are uncertain. We analyzed Community Land Model version 5 simulations for the United States from 1980 to 2010 to see how different soil settings shape patterns of soil moisture. Compared with an independent global land dataset, patterns align in many regions but differ in water-limited areas such as the Great Plains. Our maps show where to improve settings and guide future tests with observations.
Rainey Aberle, Ellyn Enderlin, Shad O'Neel, Caitlyn Florentine, Louis Sass, Adam Dickson, Hans-Peter Marshall, and Alejandro Flores
The Cryosphere, 19, 1675–1693, https://doi.org/10.5194/tc-19-1675-2025, https://doi.org/10.5194/tc-19-1675-2025, 2025
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Tracking seasonal snow on glaciers is critical for understanding glacier health. Yet previous work has not directly compared machine learning algorithms for snow classification across satellite image products. To address this, we developed a new automated workflow for tracking seasonal snow on glaciers using several image products and machine learning models. Applying this method can help provide insights into glacier health, water resources, and the effects of climate change on snow cover.
James Stegen, Amy J. Burgin, Michelle H. Busch, Joshua B. Fisher, Joshua Ladau, Jenna Abrahamson, Lauren Kinsman-Costello, Li Li, Xingyuan Chen, Thibault Datry, Nate McDowell, Corianne Tatariw, Anna Braswell, Jillian M. Deines, Julia A. Guimond, Peter Regier, Kenton Rod, Edward K. P. Bam, Etienne Fluet-Chouinard, Inke Forbrich, Kristin L. Jaeger, Teri O'Meara, Tim Scheibe, Erin Seybold, Jon N. Sweetman, Jianqiu Zheng, Daniel C. Allen, Elizabeth Herndon, Beth A. Middleton, Scott Painter, Kevin Roche, Julianne Scamardo, Ross Vander Vorste, Kristin Boye, Ellen Wohl, Margaret Zimmer, Kelly Hondula, Maggi Laan, Anna Marshall, and Kaizad F. Patel
Biogeosciences, 22, 995–1034, https://doi.org/10.5194/bg-22-995-2025, https://doi.org/10.5194/bg-22-995-2025, 2025
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The loss and gain of surface water (variable inundation) are common processes across Earth. Global change shifts variable inundation dynamics, highlighting a need for unified understanding that transcends individual variably inundated ecosystems (VIEs). We review the literature, highlight challenges, and emphasize opportunities to generate transferable knowledge by viewing VIEs through a common lens. We aim to inspire the emergence of a cross-VIE community based on a proposed continuum approach.
Max Berkelhammer, Gerald F. M. Page, Frank Zurek, Christopher Still, Mariah S. Carbone, William Talavera, Laura Hildebrand, James Byron, Kyle Inthabandith, Angellica Kucinski, Melissa Carlson, Kelsey Foss, Wendy Brown, Rosemary W. H. Carroll, Austin Simonpietri, Marshall Worsham, Ian Breckheimer, Anna Ryken, Reed Maxwell, David Gochis, Mark S. Raleigh, Eric Small, and Kenneth H. Williams
Hydrol. Earth Syst. Sci., 29, 701–718, https://doi.org/10.5194/hess-29-701-2025, https://doi.org/10.5194/hess-29-701-2025, 2025
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Warming in montane systems is affecting the snowmelt input amount. At the global scale, this will impact subalpine forests that rely on spring snowmelt to support their water demands. We use a network of sensors across a hillslope in the Upper Colorado Basin to show that the changing spring snowpack has a more pronounced impact on dense forest stands, while open stands show a higher reliance on summer rain and are less sensitive to significant changes in snow.
Zewei Ma, Kaiyu Guan, Bin Peng, Wang Zhou, Robert Grant, Jinyun Tang, Murugesu Sivapalan, Ming Pan, Li Li, and Zhenong Jin
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-340, https://doi.org/10.5194/hess-2024-340, 2024
Revised manuscript accepted for HESS
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We explore tile drainage’ impacts on the integrated hydrology-biogeochemistry-plant system, using ecosys with soil oxygen and microbe dynamics. We found that tile drainage lowers soil water content and improves soil oxygen levels, which helps crops grow better, especially during wet springs, and the developed root system also helps mitigate drought stress on dry summers. Overall, tile drainage increases crop resilience to climate change, making it a valuable future agricultural practice.
Tobias Karl David Weber, Lutz Weihermüller, Attila Nemes, Michel Bechtold, Aurore Degré, Efstathios Diamantopoulos, Simone Fatichi, Vilim Filipović, Surya Gupta, Tobias L. Hohenbrink, Daniel R. Hirmas, Conrad Jackisch, Quirijn de Jong van Lier, John Koestel, Peter Lehmann, Toby R. Marthews, Budiman Minasny, Holger Pagel, Martine van der Ploeg, Shahab Aldin Shojaeezadeh, Simon Fiil Svane, Brigitta Szabó, Harry Vereecken, Anne Verhoef, Michael Young, Yijian Zeng, Yonggen Zhang, and Sara Bonetti
Hydrol. Earth Syst. Sci., 28, 3391–3433, https://doi.org/10.5194/hess-28-3391-2024, https://doi.org/10.5194/hess-28-3391-2024, 2024
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Pedotransfer functions (PTFs) are used to predict parameters of models describing the hydraulic properties of soils. The appropriateness of these predictions critically relies on the nature of the datasets for training the PTFs and the physical comprehensiveness of the models. This roadmap paper is addressed to PTF developers and users and critically reflects the utility and future of PTFs. To this end, we present a manifesto aiming at a paradigm shift in PTF research.
Matthias Sprenger, Rosemary W. H. Carroll, David Marchetti, Carleton Bern, Harsh Beria, Wendy Brown, Alexander Newman, Curtis Beutler, and Kenneth H. Williams
Hydrol. Earth Syst. Sci., 28, 1711–1723, https://doi.org/10.5194/hess-28-1711-2024, https://doi.org/10.5194/hess-28-1711-2024, 2024
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Stable isotopes of water (described as d-excess) in mountain snowpack can be used to infer proportions of high-elevation snowmelt in stream water. In a Colorado River headwater catchment, nearly half of the water during peak streamflow is derived from melted snow at elevations greater than 3200 m. High-elevation snowpack contributions were higher for years with lower snowpack and warmer spring temperatures. Thus, we suggest that d-excess could serve to assess high-elevation snowpack changes.
Gary Sterle, Julia Perdrial, Dustin W. Kincaid, Kristen L. Underwood, Donna M. Rizzo, Ijaz Ul Haq, Li Li, Byung Suk Lee, Thomas Adler, Hang Wen, Helena Middleton, and Adrian A. Harpold
Hydrol. Earth Syst. Sci., 28, 611–630, https://doi.org/10.5194/hess-28-611-2024, https://doi.org/10.5194/hess-28-611-2024, 2024
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We develop stream water chemistry to pair with the existing CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) dataset. The newly developed dataset, termed CAMELS-Chem, includes common stream water chemistry constituents and wet deposition chemistry in 516 catchments. Examples show the value of CAMELS-Chem to trend and spatial analyses, as well as its limitations in sampling length and consistency.
Chao Wang, Stephen Leisz, Li Li, Xiaoying Shi, Jiafu Mao, Yi Zheng, and Anping Chen
Earth Syst. Dynam., 15, 75–90, https://doi.org/10.5194/esd-15-75-2024, https://doi.org/10.5194/esd-15-75-2024, 2024
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Climate change can significantly impact river runoff; however, predicting future runoff is challenging. Using historical runoff gauge data to evaluate model performances in runoff simulations for the Mekong River, we quantify future runoff changes in the Mekong River with the best simulation combination. Results suggest a significant increase in the annual runoff, along with varied seasonal distributions, thus heightening the need for adapted water resource management measures.
William Rudisill, Alejandro Flores, and Rosemary Carroll
Geosci. Model Dev., 16, 6531–6552, https://doi.org/10.5194/gmd-16-6531-2023, https://doi.org/10.5194/gmd-16-6531-2023, 2023
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It is important to know how well atmospheric models do in mountains, but there are not very many weather stations. We evaluate rain and snow from a model from 1987–2020 in the Upper Colorado River basin against the available data. The model works rather well, but there are still some uncertainties in remote locations. We then use snow maps collected by aircraft, streamflow measurements, and some advanced statistics to help identify how well the model works in ways we could not do before.
Adam P. Schreiner-McGraw and Hoori Ajami
Hydrol. Earth Syst. Sci., 26, 1145–1164, https://doi.org/10.5194/hess-26-1145-2022, https://doi.org/10.5194/hess-26-1145-2022, 2022
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We assess the impact of uncertainty in measurements of precipitation and air temperature on simulated groundwater processes in a mountainous watershed. We illustrate the role of topography in controlling how uncertainty in the input datasets propagates through the soil and into the groundwater. While the focus of previous investigations has been on the impact of precipitation uncertainty, we show that air temperature uncertainty is equally important in controlling the groundwater recharge.
Haruko M. Wainwright, Sebastian Uhlemann, Maya Franklin, Nicola Falco, Nicholas J. Bouskill, Michelle E. Newcomer, Baptiste Dafflon, Erica R. Siirila-Woodburn, Burke J. Minsley, Kenneth H. Williams, and Susan S. Hubbard
Hydrol. Earth Syst. Sci., 26, 429–444, https://doi.org/10.5194/hess-26-429-2022, https://doi.org/10.5194/hess-26-429-2022, 2022
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This paper has developed a tractable approach for characterizing watershed heterogeneity and its relationship with key functions such as ecosystem sensitivity to droughts and nitrogen export. We have applied clustering methods to classify hillslopes into
watershed zonesthat have distinct distributions of bedrock-to-canopy properties as well as key functions. This is a powerful approach for guiding watershed experiments and sampling as well as informing hydrological and biogeochemical models.
Wei Zhi, Yuning Shi, Hang Wen, Leila Saberi, Gene-Hua Crystal Ng, Kayalvizhi Sadayappan, Devon Kerins, Bryn Stewart, and Li Li
Geosci. Model Dev., 15, 315–333, https://doi.org/10.5194/gmd-15-315-2022, https://doi.org/10.5194/gmd-15-315-2022, 2022
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Watersheds are the fundamental Earth surface functioning unit that connects the land to aquatic systems. Here we present the recently developed BioRT-Flux-PIHM v1.0, a watershed-scale biogeochemical reactive transport model, to improve our ability to understand and predict solute export and water quality. The model has been verified against the benchmark code CrunchTope and has recently been applied to understand reactive transport processes in multiple watersheds of different conditions.
Frances A. Podrebarac, Sharon A. Billings, Kate A. Edwards, Jérôme Laganière, Matthew J. Norwood, and Susan E. Ziegler
Biogeosciences, 18, 4755–4772, https://doi.org/10.5194/bg-18-4755-2021, https://doi.org/10.5194/bg-18-4755-2021, 2021
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Soil respiration is a large and temperature-responsive flux in the global carbon cycle. We found increases in microbial use of easy to degrade substrates enhanced the temperature response of respiration in soils layered as they are in situ. This enhanced response is consistent with soil composition differences in warm relative to cold climate forests. These results highlight the importance of the intact nature of soils rarely studied in regulating responses of CO2 fluxes to changing temperature.
William R. Wieder, Derek Pierson, Stevan Earl, Kate Lajtha, Sara G. Baer, Ford Ballantyne, Asmeret Asefaw Berhe, Sharon A. Billings, Laurel M. Brigham, Stephany S. Chacon, Jennifer Fraterrigo, Serita D. Frey, Katerina Georgiou, Marie-Anne de Graaff, A. Stuart Grandy, Melannie D. Hartman, Sarah E. Hobbie, Chris Johnson, Jason Kaye, Emily Kyker-Snowman, Marcy E. Litvak, Michelle C. Mack, Avni Malhotra, Jessica A. M. Moore, Knute Nadelhoffer, Craig Rasmussen, Whendee L. Silver, Benjamin N. Sulman, Xanthe Walker, and Samantha Weintraub
Earth Syst. Sci. Data, 13, 1843–1854, https://doi.org/10.5194/essd-13-1843-2021, https://doi.org/10.5194/essd-13-1843-2021, 2021
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Data collected from research networks present opportunities to test theories and develop models about factors responsible for the long-term persistence and vulnerability of soil organic matter (SOM). Here we present the SOils DAta Harmonization database (SoDaH), a flexible database designed to harmonize diverse SOM datasets from multiple research networks.
Karun Pandit, Hamid Dashti, Andrew T. Hudak, Nancy F. Glenn, Alejandro N. Flores, and Douglas J. Shinneman
Biogeosciences, 18, 2027–2045, https://doi.org/10.5194/bg-18-2027-2021, https://doi.org/10.5194/bg-18-2027-2021, 2021
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A dynamic global vegetation model, Ecosystem Demography (EDv2.2), is used to understand spatiotemporal dynamics of a semi-arid shrub ecosystem under alternative fire regimes. Multi-decadal point simulations suggest shrub dominance for a non-fire scenario and a contrasting phase of shrub and C3 grass growth for a fire scenario. Regional gross primary productivity (GPP) simulations indicate moderate agreement with MODIS GPP and a GPP reduction in fire-affected areas before showing some recovery.
Hang Wen, Pamela L. Sullivan, Gwendolyn L. Macpherson, Sharon A. Billings, and Li Li
Biogeosciences, 18, 55–75, https://doi.org/10.5194/bg-18-55-2021, https://doi.org/10.5194/bg-18-55-2021, 2021
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Carbonate weathering is essential in regulating carbon cycle at the century timescale. Plant roots accelerate weathering by elevating soil CO2 via respiration. It however remains poorly understood how and how much rooting characteristics modify flow paths and weathering. This work indicates that deepening roots in woodlands can enhance carbonate weathering by promoting recharge and CO2–carbonate contact in the deep, carbonate-abundant subsurface.
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Short summary
Our study looked at how different forest types and conditions affected soil microbes and soil carbon and stability. Aspen organic matter led to higher microbial activity, smaller soil aggregates, and more stable soil carbon, possibly reducing dissolved organic carbon movement from hillslopes to streams. This shows the importance of models like the Microbial Efficiency – Matrix Stabilization framework for predicting CO2 release, soil carbon stability, and carbon movement.
Our study looked at how different forest types and conditions affected soil microbes and soil...
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