Articles | Volume 20, issue 4
https://doi.org/10.5194/tc-20-2017-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-20-2017-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Effects of disturbance on seasonal CO2 dynamics in two boreal forest sites underlain by permafrost
Dragos A. Vas
CORRESPONDING AUTHOR
U.S. Army Engineer Research and Development Center-Cold Regions Research and Engineering Laboratory, Ft. Wainwright, Alaska 99703, United States
Jaimie R. West
U.S. Army Engineer Research and Development Center-Cold Regions Research and Engineering Laboratory, Hanover, New Hampshire 03755, United States
David Brodylo
U.S. Army Engineer Research and Development Center-Cold Regions Research and Engineering Laboratory, Ft. Wainwright, Alaska 99703, United States
Amanda J. Barker
U.S. Army Engineer Research and Development Center-Cold Regions Research and Engineering Laboratory, Ft. Wainwright, Alaska 99703, United States
W. Brad Baxter
U.S. Army Engineer Research and Development Center-Cold Regions Research and Engineering Laboratory, Ft. Wainwright, Alaska 99703, United States
Robyn A. Barbato
U.S. Army Engineer Research and Development Center-Cold Regions Research and Engineering Laboratory, Hanover, New Hampshire 03755, United States
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David Brodylo, Lauren V. Bosche, Ryan R. Busby, Elias J. Deeb, Thomas A. Douglas, and Juha Lemmetyinen
The Cryosphere, 19, 6127–6148, https://doi.org/10.5194/tc-19-6127-2025, https://doi.org/10.5194/tc-19-6127-2025, 2025
Short summary
Short summary
We combined field-based snow depth and snow water equivalent (SWE) measurements, remote sensing data, and machine learning to estimate snow depth and SWE over a 10 km2 local scale area in Sodankylä, Finland. Associations were found for snow depth and SWE with carbon- and mineral-based forest surface soils, alongside dry and wet peatbogs. This approach to upscale field-based snow depth and SWE measurements to a local scale can be used in regions that regularly experience snowfall.
Cited articles
Akande, O. J., Ma, Z., Huang, C., He, F., and Chang, S. X.: Meta-analysis shows forest soil CO2 effluxes are dependent on the disturbance regime and biome type, Ecol. Lett., 26, 765–777, https://doi.org/10.1111/ele.14201, 2023.
Amiro, B. D.: Paired-tower measurements of carbon and energy fluxes following disturbance in the boreal forest, Glob. Change Biol., 7, 253–268, https://doi.org/10.1046/j.1365-2486.2001.00398.x, 2001.
Anderson, M. J.: A new method for non-parametric multivariate analysis of variance, Austral Ecol., 26, 32–46, https://doi.org/10.1111/j.1442-9993.2001.01070.pp.x, 2001.
Apprill, A., McNally, S., Parsons, R., and Weber, L.: Minor revision to V4 region SSU rRNA 806R gene primer greatly increases detection of SAR11 bacterioplankton, Aquat. Microb. Ecol., 75, 129–137, https://doi.org/10.3354/ame01753, 2015.
Baker, C. C. M., Barker, A. J., Douglas, T. A., Doherty, S. J., and Barbato, R. A.: Seasonal variation in near-surface seasonally thawed active layer and permafrost soil microbial communities, Environ. Res. Lett., 18, 055001, https://doi.org/10.1088/1748-9326/acc542, 2023.
Barbato, R. A., Jones, R. M., Douglas, T. A., Doherty, S. J., Messan, K., Foley, K. L., Perkins, E. J., Thurston, A. K., and Garcia-Reyero, N.: Not all permafrost microbiomes are created equal: Influence of permafrost thaw on the soil microbiome in a laboratory incubation study, Soil Biol. Biochem., 167, 108605, https://doi.org/10.1016/j.soilbio.2022.108605, 2022.
Behnamian, A., Millard, K., Banks, S. N., White, L., Richardson, M., and Pasher, J.: A systematic approach for variable selection with random forests: achieving stable variable importance values, IEEE Geosci. Remote S., 14, 1988–1992, https://doi.org/10.1109/LGRS.2017.2745049, 2017.
Bonan, G. B.: Forests and climate change: forcings, feedbacks, and the climate benefits of forests, Science, 320, 1444–1449, https://doi.org/10.1126/science.1155121, 2008.
Bond-Lamberty, B., Bailey, V. L., Chen, M., Gough, C. M., and Vargas, R.: Globally rising soil heterotrophic respiration over recent decades, Nature, 560, 80–83, https://doi.org/10.1038/s41586-018-0358-x, 2018.
Bray, J. R. and Curtis, J. T.: An ordination of the upland forest communities of southern Wisconsin, Ecol. Monogr., 27, 326–349, https://doi.org/10.2307/1942268, 1957.
Callahan, B. J., McMurdie, P. J., Rosen, M. J., Han, A. W., Johnson, A. J. A., and Dada, S. H.: High-resolution sample inference from Illumina amplicon data, Nat. Methods, 13, 581–583, https://doi.org/10.1038/nmeth.3869, 2016.
Caporaso, J. G., Lauber, C. L., Walters, W. A., Berg-Lyons, D., Lozupone, C. A., Turnbaugh, P. J., Fierer, N., and Knight, R.: Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample, P. Natl. Acad. Sci. USA, 108, 4516–4522, https://doi.org/10.1073/pnas.1000080107, 2011.
Caporaso, J. G., Lauber, C. L., Walters, W. A., Berg-Lyons, D., Huntley, J., Fierer, N., Owens, S. M., Betley, J., Fraser, L., Bauer, M., and Gormley, N.: Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms, ISME J., 6, 1621–1624, https://doi.org/10.1038/ismej.2012.8, 2012.
Chatterjee, A., Vance, G. F., Pendall, E., and Stahl, P. D.: Timber harvesting alters soil carbon mineralization and microbial community structure in coniferous forests, Soil Biol. Biochem., 40, 1901–1907, https://doi.org/10.1016/j.soilbio.2008.03.018, 2008.
Chi, J., Zhao, P., Klosterhalfen, A., Jocher, G., Kljun, N., Nilsson, M. B., and Peichl, M.: Forest floor fluxes drive differences in the carbon balance of contrasting boreal forest stands, Agr. Forest Meteorol., 306, 108454, https://doi.org/10.1016/j.agrformet.2021.108454, 2021.
Dimitriu, P. A. and Grayston, S. J.: Relationship between soil properties and patterns of bacterial ?-diversity across reclaimed and natural boreal forest soils, Microb. Ecol., 59, 563–573, https://doi.org/10.1007/s00248-009-9590-0, 2010.
Doherty, S. J., Barbato, R. A., Grandy, A. S., Thomas, W. K., Monteux, S., Dorrepaal, E., Johansson, M., and Ernakovich, J. G.: The transition from stochastic to deterministic bacterial community assembly during permafrost thaw succession, Front. Microbiol., 11, 596589, https://doi.org/10.3389/fmicb.2020.596589, 2020.
Fekete, I., Kotroczó, Z., Varga, C., Nagy, P. T., Várbíró, G., Bowden, R. D., Tóth, J. A., and Lajtha, K.: Alterations in forest detritus inputs influence soil carbon concentration and soil respiration in a Central-European deciduous forest, Soil Biol. Biochem., 74, 106–114, https://doi.org/10.1016/j.soilbio.2014.03.006, 2014.
Forbes, B. C., Ebersole, J. J., and Strandberg, B.: Anthropogenic disturbance and patch dynamics in circumpolar arctic ecosystems, Conserv. Biol., 15, 954–969, https://doi.org/10.1046/j.1523-1739.2001.015004954.x, 2001.
Foster, A. C., Wang, J. A., Frost, G. V., Davidson, S. J., Hoy, E., Turner, K. W., Sonnentag, O., Epstein, H., Berner, L. T., Armstrong, A. H., and Kang, M.: Disturbances in North American boreal forest and Arctic tundra: impacts, interactions, and responses, Environ. Res. Lett., 17, 113001, https://doi.org/10.1088/1748-9326/ac98d7, 2022.
Gordon, A. M., Schlentner, R. E., and Cleve, K. V.: Seasonal patterns of soil respiration and CO2 evolution following harvesting in the white spruce forests of interior Alaska, Can. J. Forest Res., 17, 304–310, https://doi.org/10.1139/x87-051, 1987.
Grace, J.: Understanding and managing the global carbon cycle, J. Ecol., 92, 189–202, https://doi.org/10.1111/j.0022-0477.2004.00874.x, 2004.
Harel, A., Sylvain, J. D., Drolet, G., Thiffault, E., Thiffault, N., and Tremblay, S.: Fine scale assessment of seasonal, intra-seasonal and spatial dynamics of soil CO2 effluxes over a balsam fir-dominated perhumid boreal landscape, Agr. Forest Meteorol., 335, 109469, https://doi.org/10.1016/j.agrformet.2023.109469, 2023.
Jorgenson, M. T., Douglas, T. A., Liljedahl, A. K., Roth, J. E., Cater, T. C., Davis, W. A., Frost, G. V., Miller, P. F., and Racine, C. H.: The roles of climate extremes, ecological succession, and hydrology in repeated permafrost aggradation and degradation in fens on the Tanana Flats, Alaska, J. Geophys. Res.-Biogeo., 125, e2020JG005824, https://doi.org/10.1029/2020JG005824, 2020.
Kim, Y., Kimball, J. S., Zhang, K., and McDonald, K. C.: Satellite detection of increasing Northern Hemisphere non-frozen seasons from 1979 to 2008: Implications for regional vegetation growth, Remote Sens. Environ., 121, 472–487, https://doi.org/10.1016/j.rse.2012.02.014, 2012.
Kõljalg, U., Nilsson, R. H., Abarenkov, K., Tedersoo, L., Taylor, A. F. S., Bahram, M., Bates, S. T., Bruns, T. D., Bengtsson-Palme, J., Callaghan, T. M., Douglas, B., Drenkhan, T., Eberhardt, U., Dueñas, M., Grebenc, T., Griffith, G. W., Hartmann, M., Kirk, P. M., Kohout, P., Larsson, E., Lindahl, B. D., Lücking, R., Martín, M. P., Matheny, P. B., Nguyen, N. H., Niskanen, T., Oja, J., Peay, K. G., Peintner, U., Peterson, M., Põldmaa, K., Saag, L., Saar, I., Schüßler, A., Scott, J. A., Senés, C., Smith, M. E., Suija, A., Taylor, D. L., Telleria, M. T., Weiss, M., and Larsson, K.-H.: Towards a unified paradigm for sequence-based identification of fungi, Mol. Ecol., 22, 5271–5277, https://doi.org/10.1111/mec.12481, 2013.
Köster, E., Köster, K., Berninger, F., Aaltonen, H., Zhou, X., and Pumpanen, J.: Carbon dioxide, methane and nitrous oxide fluxes from a fire chronosequence in subarctic boreal forests of Canada, Sci. Total Environ., 601, 895–905, https://doi.org/10.1016/j.scitotenv.2017.05.246, 2017.
Köster, E., Köster, K., Berninger, F., Prokushkin, A., Aaltonen, H., Zhou, X., and Pumpanen, J.: Changes in fluxes of carbon dioxide and methane caused by fire in Siberian boreal forest with continuous permafrost, J. Environ. Manage., 228, 405–415, https://doi.org/10.1016/j.jenvman.2018.09.051, 2018.
Lei, Q., Yu, H., and Lin, Z.: Understanding China's CO2 emission drivers: Insights from random forest analysis and remote sensing data, Heliyon, 10, e28562, https://doi.org/10.1016/j.heliyon.2024.e29086, 2024.
Martin, B. D., Witten, D., and Willis, A. D.: Modeling microbial abundances and dysbiosis with beta-binomial regression, Ann. Appl. Stat., 14, 94–115, https://doi.org/10.1214/19-AOAS1283, 2020.
Marty, C., Piquette, J., Morin, H., Bussières, D., Thiffault, N., Houle, D., Bradley, R. L., Simpson, M. J., Ouimet, R., and Paré, M. C.: Nine years of in situ soil warming and topography impact the temperature sensitivity and basal respiration rate of the forest floor in a Canadian boreal forest, PLoS One, 14, e0226909, https://doi.org/10.1371/journal.pone.0226909, 2019.
Miner, K. R., Turetsky, M. R., Malina, E., Bartsch, A., Tamminen, J., McGuire, A. D., Fix, A., Sweeney, C., Elder, C. D., and Miller, C. E.: Permafrost carbon emissions in a changing Arctic, Nat. Rev. Earth Environ., 3, 55–67, https://doi.org/10.1038/s43017-021-00230-3, 2022.
Mölder, F., Jablonski, K. P., Letcher, B., Hall, M. B., Tomkins-Tinch, C. H., Sochat, V., Forster, J., Lee, S., Twardziok, S. O., Kanitz, A., Wilm, A., Holtgrewe, M., Rahmann, S., Nahnsen, S., and Köster, J.: Sustainable data analysis with Snakemake, F1000Research, 10, 33, https://doi.org/10.12688/f1000research.29032.1, 2021.
Natali, S. M., Watts, J. D., Rogers, B. M., Potter, S., Ludwig, S. M., Selbmann, A. K., Sullivan, P. F., Abbott, B. W., Arndt, K. A., Birch, L., and Björkman, M. P.: Large loss of CO2 in winter observed across the northern permafrost region, Nat. Clim. Change, 9, 852–857, https://doi.org/10.1038/s41558-019-0592-8, 2019.
Nilsson, R. H., Larsson, K. H., Taylor, A. F. S., Bengtsson-Palme, J., Jeppesen, T. S., Schigel, D., Kennedy, P., Picard, K., Glöckner, F. O., Tedersoo, L., and Saar, I.: The UNITE database for molecular identification of fungi: handling dark taxa and parallel taxonomic classifications, Nucleic Acids Res., 47, D259–D264, https://doi.org/10.1093/nar/gky1022, 2019.
Oertel, C., Matschullat, J., Zurba, K., Zimmermann, F., and Erasmi, S.: Greenhouse gas emissions from soils – A review, Geochemistry, 76, 327–352, https://doi.org/10.1016/j.chemer.2016.04.002, 2016.
Oksanen, J., Simpson, G., Blanchet, F., Kindt, R., Legendre, P., Minchin, P., O'Hara, R., Solymos, P., Stevens, M., Szoecs, E., Wagner, H., Barbour, M., Bedward, M., Bolker, B., Borcard, D., Carvalho, G., Chirico, M., De Caceres, M., Durand, S., Evangelista, H., FitzJohn, R., Friendly, M., Furneaux, B., Hannigan, G., Hill, M., Lahti, L., McGlinn, D., Ouellette, M., Ribeiro Cunha, E., Smith, T., Stier, A., Ter Braak, C., and Weedon, J.: vegan: Community Ecology Package, R package version 2.6-6.1, https://search.r-project.org/CRAN/refmans/vegan/html/00Index.html (last access: 14 December 2024), 2024.
Pan, Y., Birdsey, R. A., Fang, J., Houghton, R., Kauppi, P. E., Kurz, W. A., Phillips, O. L., Shvidenko, A., Lewis, S. L., Canadell, J. G., and Ciais, P.: A large and persistent carbon sink in the world's forests, Science, 333, 988–993, https://doi.org/10.1126/science.1201609, 2011.
Parada, A. E., Needham, D. M., and Fuhrman, J. A.: Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples, Environ. Microbiol., 18, 1403–1414, https://doi.org/10.1111/1462-2920.13023, 2016.
Parker, T. C., Clemmensen, K. E., Friggens, N. L., Hartley, I. P., Johnson, D., Lindahl, B. D., Olofsson, J., Siewert, M. B., Street, L. E., Subke, J. A., and Wookey, P. A.: Rhizosphere allocation by canopy-forming species dominates soil CO2 efflux in a subarctic landscape, New Phytol., 227, 1818–1830, https://doi.org/10.1111/nph.16573, 2020.
Peng, Y., Thomas, S. C., and Tian, D.: Forest management and soil respiration: Implications for carbon sequestration, Environ. Rev., 16, 93–111, https://doi.org/10.1139/A08-003, 2008.
Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., Peplies, J., and Glöckner, F. O.: The SILVA ribosomal RNA gene database project: improved data processing and web-based tools, Nucleic Acids Res., 41, D590–D596, https://doi.org/10.1093/nar/gks1219, 2012.
R-Core-Team: R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, https://www.R-project.org/ (last access: 14 December 2024), 2018.
Rodtassana, C., Unawong, W., Yaemphum, S., Chanthorn, W., Chawchai, S., Nathalang, A., Brockelman, W. Y., and Tor-ngern, P.: Different responses of soil respiration to environmental factors across forest stages in a Southeast Asian forest, Ecol. Evol., 11, 15430–15443, https://doi.org/10.1002/ece3.8248, 2021.
Schepaschenko, D., Mukhortova, L., and Shvidenko, A.: Estimation of Impact of Disturbances on Soil Respiration in Forest Ecosystems of Russia, Forests, 16, 925, https://doi.org/10.3390/f16060925, 2025.
Schonlau, M. and Zou, R. Y.: The random forest algorithm for statistical learning, Stata J., 20, 3–29, https://doi.org/10.1177/1536867X20909688, 2020.
Shiklomanov, N. I., Streletskiy, D. A., Little, J. D., and Nelson, F. E.: Isotropic thaw subsidence in undisturbed permafrost landscapes, Geophys. Res. Lett., 40, 6356–6361, https://doi.org/10.1002/2013GL058295, 2013.
Smith, D. P. and Peay, K. G.: Sequence depth, not PCR replication, improves ecological inference from next generation DNA sequencing, PLoS One, 9, e90234, https://doi.org/10.1371/journal.pone.0090234, 2014.
Soil Survey Staff: Keys to Soil Taxonomy, 13th edition, USDA Natural Resources Conservation Service, https://www.nrcs.usda.gov/resources/guides-and-instructions/keys-to-soil-taxonomy (last access: 22 March 2025), 2022.
Storer, D. A.: A simple high sample volume ashing procedure for determination of soil organic matter, Commun. Soil Sci. Plan., 15, 759-772, https://doi.org/10.1080/00103628409367515, 1984.
Turetsky, M. R., Abbott, B. W., Jones, M. C., Anthony, K. W., Olefeldt, D., Schuur, E. A., Grosse, G., Kuhry, P., Hugelius, G., Koven, C., and Lawrence, D. M.: Carbon release through abrupt permafrost thaw, Nat. Geosci., 13, 138–143, https://doi.org/10.1038/s41561-019-0526-0, 2020.
Vas, D. A., Corriveau, E. J., Gaimaro, L. W., and Barbato, R. A.: Challenges and Limitations of Using Autonomous Instrumentation for Measuring In Situ Soil Respiration in a Subarctic Boreal Forest in Alaska, USA, ERDC/CRREL, TR-23-18, https://doi.org/10.21079/11681/48018, 2023.
Walters, W., Hyde, E. R., Berg-Lyons, D., Ackermann, G., Humphrey, G., Parada, A., Gilbert, J. A., Jansson, J. K., Caporaso, J. G., Fuhrman, J. A., and Apprill, A.: Improved bacterial 16S rRNA gene (V4 and V4-5) and fungal internal transcribed spacer marker gene primers for microbial community surveys, mSystems, 1, e00009-15, https://doi.org/10.1128/mSystems.00009-15, 2016.
Watts, J. D., Natali, S. M., Minions, C., Risk, D., Arndt, K., Zona, D., Euskirchen, E. S., Rocha, A. V., Sonnentag, O., and Helbig, M.: Soil respiration strongly offsets carbon uptake in Alaska and Northwest Canada, Environ. Res. Lett., 16, 084051, https://doi.org/10.1088/1748-9326/ac1222, 2021.
Welker, J. M., Fahnestock, J. T., and Jones, M. H.: Annual CO2 Flux in Dry and Moist Arctic Tundra: Field Responses to Increases in Summer Temperatures and Winter Snow Depth, Clim. Change, 44, 139–150, https://doi.org/10.1023/A:1005555012742, 2000.
West, J. R. and Whitman, T.: Disturbance by soil mixing decreases microbial richness and supports homogenizing community assembly processes, FEMS Microbiol. Ecol., 98, fiac057, https://doi.org/10.1093/femsec/fiac089, 2022.
Wickham, H.: ggplot2: Elegant Graphics for Data Analysis, Springer International Publishing, https://doi.org/10.1007/978-3-319-24277-4, 2016.
Willis, A., Bunge, J., and Whitman, T.: Improved detection of changes in species richness in high diversity microbial communities, J. R. Stat. Soc. C-Appl., 66, 963–977, https://doi.org/10.1111/rssc.12206, 2017.
Yilmaz, P., Parfrey, L. W., Yarza, P., Gerken, J., Pruesse, E., Quast, C., Schweer, T., Peplies, J., Ludwig, W., and Glöckner, F. O.: The All-species Living Tree Project (LTP) taxonomic frameworks, Nucleic Acids Res., 42, D643–D648, https://doi.org/10.1093/nar/gkt1209, 2014.
Yoshikawa, K., Bolton, W. R., Romanovsky, V. E., Fukuda, M., and Hinzman, L. D.: Impacts of wildfire on the permafrost in the boreal forests of Interior Alaska, J. Geophys. Res.-Atmos., 107, FFR 4-1–FFR 4-15, https://doi.org/10.1029/2001JD000438, 2002.
Zhu, X., Xu, X., and Jia, G.: Recent massive expansion of wildfire and its impact on active layer over pan-Arctic permafrost, Environ. Res. Lett., 18, 084010, https://doi.org/10.1088/1748-9326/ace205, 2023.
Short summary
Soil disturbances significantly increase soil temperatures, alter microbial communities, and boost carbon emissions. This can accelerate permafrost degradation, affecting the climate. Disturbances change the relationships between temperature, moisture, and carbon emissions, leading to higher emissions. Understanding these changes is crucial for modeling carbon cycles and mitigating the impacts of soil disturbances on the environment.
Soil disturbances significantly increase soil temperatures, alter microbial communities, and...