Articles | Volume 19, issue 10
https://doi.org/10.5194/bg-19-2729-2022
© Author(s) 2022. 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-19-2729-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
01 Jun 2022
Research article |
| 01 Jun 2022
| 01 Jun 2022
Fire in lichen-rich subarctic tundra changes carbon and nitrogen cycling between ecosystem compartments but has minor effects on stocks
Ramona J. Heim
CORRESPONDING AUTHOR
Institute of Landscape Ecology, Biodiversity and Ecosystem Research Group, University of Münster, Heisenbergstraße 2, 48149 Münster, Germany
Andrey Yurtaev
Research Institute of Ecology and Natural Resources Management, Tyumen State University, 6 Volodarskogo Street, Tyumen, Russia
Anna Bucharova
Institute of Landscape Ecology, Biodiversity and Ecosystem Research Group, University of Münster, Heisenbergstraße 2, 48149 Münster, Germany
Department of Biology, Conservation Biology Group, University of Marburg, Karl-von-Frisch-Straße 8, 35043 Marburg, Germany
Wieland Heim
Institute of Landscape Ecology, Biodiversity and Ecosystem Research Group, University of Münster, Heisenbergstraße 2, 48149 Münster, Germany
Department of Biology, Animal Ecology, University of Turku, Vesilinnantie 5, 20500 Turku, Finland
Valeriya Kutskir
Research Institute of Ecology and Natural Resources Management, Tyumen State University, 6 Volodarskogo Street, Tyumen, Russia
Klaus-Holger Knorr
Institute of Landscape Ecology, Ecohydrology and Biogeochemistry Group, University of Münster, Heisenbergstraße 2, 48149 Münster, Germany
Christian Lampei
Institute of Landscape Ecology, Biodiversity and Ecosystem Research Group, University of Münster, Heisenbergstraße 2, 48149 Münster, Germany
Alexandr Pechkin
Research Center of the Yamal-Nenets Autonomous District, Salekhard 629008, Russia
Dora Schilling
Institute of Landscape Ecology, Biodiversity and Ecosystem Research Group, University of Münster, Heisenbergstraße 2, 48149 Münster, Germany
Farid Sulkarnaev
Research Institute of Ecology and Natural Resources Management, Tyumen State University, 6 Volodarskogo Street, Tyumen, Russia
Norbert Hölzel
Institute of Landscape Ecology, Biodiversity and Ecosystem Research Group, University of Münster, Heisenbergstraße 2, 48149 Münster, Germany
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Henning Teickner, Julien Arsenault, Mariusz Gałka, and Klaus-Holger Knorr
Biogeosciences, 23, 5549–5570, https://doi.org/10.5194/bg-23-5549-2026, https://doi.org/10.5194/bg-23-5549-2026, 2026
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We present a method to estimate the degree of decomposition (fraction of initial mass remaining) of peat from mid-infrared spectra, which also allows to reconstruct the initial mass (aboveground net primary production). Both quantities are required to estimate the mass and carbon balance of peatlands and are useful to model peat physical and hydraulic properties. The approach is therefore useful to test and improve peatland models and our understanding of the long-term peatland carbon cycle.
Nicolas Behrens, Klaus-Holger Knorr, Christoph Rückriem, and Mana Gharun
Biogeosciences, 23, 5071–5094, https://doi.org/10.5194/bg-23-5071-2026, https://doi.org/10.5194/bg-23-5071-2026, 2026
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We analysed carbon fluxes and their response to climate in a drained bog. Annual budgets varied from net emissions to near-neutral. Warm spring temperatures increased CO2 uptake, a warm autumn increased emissions. Atmospheric drought early in the year reduced CO2 uptake more than later. Our results show that carbon fluxes from drained bogs are variable and the timing of climate anomalies controls their impact on carbon fluxes. This will be increasingly important with ongoing climate warming.
Christine L. Olson, Kevin Schaefer, Alyssa Azaroff, Hélène Angot, Sasiri Bandara, Thomas A. Douglas, Bo Elberling, Maria Florencia Fahnestock, Xinbin Feng, Charlotte Haugk, Gustaf Hugelius, Erfan Jahangir, Sofi Jonsson, Shichang Kang, Adam Kirkwood, Jennifer Korosi, Igor Lehnherr, Artem Lim, Rinat Manasypov, Dmitriy Moskovchenko, Mina Nasr, Daniel Obrist, David Olefeldt, Connor Olson, Oleg Pokrovsky, Laura Sereni, Sarah Shakil, M. Isabel Smith, Jens Søndergaard, Jeroen Sonke, Kasia Staniszewska, Jens Strauss, Kyra St. Pierre, Lauren Thompson, Andrey Yurtaev, Yanxu Zhang, and Scott Zolkos
Earth Syst. Sci. Data, 18, 4509–4522, https://doi.org/10.5194/essd-18-4509-2026, https://doi.org/10.5194/essd-18-4509-2026, 2026
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Permafrost regions store large amounts of mercury, a toxic pollutant that can be released as the ground warms. We combined thousands of measurements from soils, plants, water, and lake sediments into one open database to better understand where mercury is stored and how it moves. The results show clear differences among environments and reveal major data gaps, helping improve future research, monitoring, and decision-making.
Lina Oskamp, Marta Pérez Rodríguez, Adelina Calean, Olaf Rienitz, Klaus-Holger Knorr, Kazumasa Oguri, Masashi Tsuchiya, Marco Benkhettab Sindlev, Stephan Krisch, Arianna Olivelli, Frank Wenzhöfer, Ronnie N. Glud, and Harald Biester
EGUsphere, https://doi.org/10.5194/egusphere-2026-3608, https://doi.org/10.5194/egusphere-2026-3608, 2026
This preprint is open for discussion and under review for Ocean Science (OS).
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Lead (Pb) isotopes in marine sediments are used as source tracers of Pb in the oceans. Recent studies suggested Pb isotope exchange on sinking particles, but it remained unknown if this affects isotope signatures. Our study on deep-sea sediments of the South Atlantic Ocean reveals that Pb isotope separation occurs in sinking particles and depends on the intensity of primary productivity.
Henning Teickner and Klaus-Holger Knorr
SOIL, 12, 497–519, https://doi.org/10.5194/soil-12-497-2026, https://doi.org/10.5194/soil-12-497-2026, 2026
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We developed models that predict physical and chemical peat properties from mid-infrared spectra (MIRS). These peat properties are necessary for modeling peatland dynamics. Compared to direct measurements of these properties, measurements of MIRS require less sample material and save time. Unlike existing models that focus on peat, the models developed here are openly available, relatively easy to use and have basic quality checks and estimates for prediction errors.
Hannes Keck, Laurence Strubbe, Paul M. Magyar, Adriano Joss, Andreas Froemelt, André Kupferschmid, Klaus-Holger Knorr, and Joachim Mohn
EGUsphere, https://doi.org/10.5194/egusphere-2026-857, https://doi.org/10.5194/egusphere-2026-857, 2026
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We monitored nitrous oxide in a pilot wastewater treatment plant in real time to understand how microbes produce and remove this greenhouse gas. We designed and tested a laser-based analytical setup, with which we were able to show that denitrification is the main source of nitrous oxide emissions and that low oxygen concentrations enhances nitrous oxide removal. Our approach offers a new way to monitor the wastewater treatment processes and to cut climate-relevant nitrous oxide emissions.
Henning Teickner, Edzer Pebesma, and Klaus-Holger Knorr
Earth Syst. Dynam., 16, 891–914, https://doi.org/10.5194/esd-16-891-2025, https://doi.org/10.5194/esd-16-891-2025, 2025
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The Holocene Peatland Model (HPM) is a widely used peatland model to understand and predict long-term peatland dynamics. Here, we test whether the HPM can predict Sphagnum litterbag decomposition rates from oxic to anoxic conditions. Our results indicate that decomposition rates change more gradually from oxic to anoxic conditions and may be underestimated under anoxic conditions, possibly because the effect of water table fluctuations on decomposition rates is not considered.
Henning Teickner, Edzer Pebesma, and Klaus-Holger Knorr
Biogeosciences, 22, 417–433, https://doi.org/10.5194/bg-22-417-2025, https://doi.org/10.5194/bg-22-417-2025, 2025
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Decomposition rates for Sphagnum mosses, the main peat-forming plants in northern peatlands, are often derived from litterbag experiments. Here, we estimate initial leaching losses from available Sphagnum litterbag experiments and analyze how decomposition rates are biased when initial leaching losses are ignored. Our analyses indicate that initial leaching losses range between 3 to 18 mass-% and that this may result in overestimated mass losses when extrapolated to several decades.
Carrie L. Thomas, Boris Jansen, Sambor Czerwiński, Mariusz Gałka, Klaus-Holger Knorr, E. Emiel van Loon, Markus Egli, and Guido L. B. Wiesenberg
Biogeosciences, 20, 4893–4914, https://doi.org/10.5194/bg-20-4893-2023, https://doi.org/10.5194/bg-20-4893-2023, 2023
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Peatlands are vital terrestrial ecosystems that can serve as archives, preserving records of past vegetation and climate. We reconstructed the vegetation history over the last 2600 years of the Beerberg peatland and surrounding area in the Thuringian Forest in Germany using multiple analyses. We found that, although the forest composition transitioned and human influence increased, the peatland remained relatively stable until more recent times, when drainage and dust deposition had an impact.
Laura Clark, Ian B. Strachan, Maria Strack, Nigel T. Roulet, Klaus-Holger Knorr, and Henning Teickner
Biogeosciences, 20, 737–751, https://doi.org/10.5194/bg-20-737-2023, https://doi.org/10.5194/bg-20-737-2023, 2023
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We determine the effect that duration of extraction has on CO2 and CH4 emissions from an actively extracted peatland. Peat fields had high net C emissions in the first years after opening, and these then declined to half the initial value for several decades. Findings contribute to knowledge on the atmospheric burden that results from these activities and are of use to industry in their life cycle reporting and government agencies responsible for greenhouse gas accounting and policy.
Matthias Koschorreck, Klaus Holger Knorr, and Lelaina Teichert
Biogeosciences, 19, 5221–5236, https://doi.org/10.5194/bg-19-5221-2022, https://doi.org/10.5194/bg-19-5221-2022, 2022
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At low water levels, parts of the bottom of rivers fall dry. These beaches or mudflats emit the greenhouse gas carbon dioxide (CO2) to the atmosphere. We found that those emissions are caused by microbial reactions in the sediment and that they change with time. Emissions were influenced by many factors like temperature, water level, rain, plants, and light.
Henning Teickner and Klaus-Holger Knorr
SOIL, 8, 699–715, https://doi.org/10.5194/soil-8-699-2022, https://doi.org/10.5194/soil-8-699-2022, 2022
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The chemical quality of biomass can be described with holocellulose (relatively easily decomposable by microorganisms) and Klason lignin (relatively recalcitrant) contents. Measuring both is laborious. In a recent study, models have been proposed which can predict both quicker from mid-infrared spectra. However, it has not been analyzed if these models make correct predictions for biomass in soils and how to improve them. We provide such a validation and a strategy for their improvement.
Cordula Nina Gutekunst, Susanne Liebner, Anna-Kathrina Jenner, Klaus-Holger Knorr, Viktoria Unger, Franziska Koebsch, Erwin Don Racasa, Sizhong Yang, Michael Ernst Böttcher, Manon Janssen, Jens Kallmeyer, Denise Otto, Iris Schmiedinger, Lucas Winski, and Gerald Jurasinski
Biogeosciences, 19, 3625–3648, https://doi.org/10.5194/bg-19-3625-2022, https://doi.org/10.5194/bg-19-3625-2022, 2022
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Methane emissions decreased after a seawater inflow and a preceding drought in freshwater rewetted coastal peatland. However, our microbial and greenhouse gas measurements did not indicate that methane consumers increased. Rather, methane producers co-existed in high numbers with their usual competitors, the sulfate-cycling bacteria. We studied the peat soil and aimed to cover the soil–atmosphere continuum to better understand the sources of methane production and consumption.
Liam Heffernan, Maria A. Cavaco, Maya P. Bhatia, Cristian Estop-Aragonés, Klaus-Holger Knorr, and David Olefeldt
Biogeosciences, 19, 3051–3071, https://doi.org/10.5194/bg-19-3051-2022, https://doi.org/10.5194/bg-19-3051-2022, 2022
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Permafrost thaw in peatlands leads to waterlogged conditions, a favourable environment for microbes producing methane (CH4) and high CH4 emissions. High CH4 emissions in the initial decades following thaw are due to a vegetation community that produces suitable organic matter to fuel CH4-producing microbes, along with warm and wet conditions. High CH4 emissions after thaw persist for up to 100 years, after which environmental conditions are less favourable for microbes and high CH4 emissions.
Cited articles
Asplund, J. and Wardle, D. A.: How lichens impact on terrestrial community and ecosystem properties, Biol. Rev., 92, 1720–1738, https://doi.org/10.1111/brv.12305, 2017. a
Blok, D., Faucherre, S., Banyasz, I., Rinnan, R., Michelsen, A., and Elberling, B.: Contrasting above- and belowground organic matter decomposition and carbon and nitrogen dynamics in response to warming in High Arctic tundra, Glob. Change Biol., 24, 2660–2672, 2018. a
Böhlke, J. K., Mroczkowski, S. J., and Coplen, T. B.: Oxygen isotopes in nitrate: New reference materials for 18O : 17O : 16O measurements and observations on nitrate-water equilibration, Rapid Commun. Mass Sp., 17, 1835–1846, 2003. a
Bret-Harte, M. S., Mack, M. C., Shaver, G. R., Huebner, D. C., Johnston, M., Mojica, C. A., Pizano, C., and Reiskind, J. A.: The response of Arctic vegetation and soils following an unusually severe tundra fire, Philos. T. Roy. Soc. B, 368, 20120490, https://doi.org/10.1098/rstb.2012.0490, 2013. a, b
Bürkner, P.-C.: brms: An R Package for Bayesian Multilevel Models Using Stan, J. Stat. Softw., 80, 1–28, https://doi.org/10.18637/jss.v080.i01, 2017. a, b
Bürkner, P.-C.: Advanced Bayesian Multilevel Modeling with the R Package brms, R J., 10, 395–411, https://doi.org/10.32614/RJ-2018-017, 2018. a, b
Cahoon, S. M. P., Sullivan, P. F., and Post, E.: Greater abundance of Betula nana and early onset of the growing season increase ecosystem CO2 uptake in West Greenland, Ecosystems, 19, 1149–1163, 2016. a
Chambers, S. D., Beringer, J., Randerson, J. T., and Chapin, I. S.: Fire effects on net radiation and energy partitioning: Contrasting responses of tundra and boreal forest ecosystems, J. Geophys. Res.-Atmos., 110, 1–9, https://doi.org/10.1029/2004JD005299, 2005. a
Chapin III, F. S., McGuire, A. D., Randerson, J., Pielke, R., Baldocchi, D., Hobbie, S. E., Roulet, N., Eugster, W., Kasischke, E., and Rastetter, E. B.: Arctic and boreal ecosystems of western North America as components of the climate system, Glob. Change Biol., 6, 211–223, 2000. a
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, 2021. a
Coplen, T. B., Brand, W. A., Gehre, M., Gröning, M., Meijer, H. A. J., Toman, B., and Verkouteren, R. M.: New guidelines for δ13C measurements, Anal. Chem., 78, 2439–2441, 2006. a
Dahl, E.: Stability of tundra ecosystems in Fennoscandia, in: Fennoscandian tundra ecosystems, Springer, 231–236, https://doi.org/10.1007/978-3-642-66276-8_29, 1975. a
De Baets, S., Van de Weg, M. J., Lewis, R., Steinberg, N., Meersmans, J., Quine, T. A., Shaver, G. R., and Hartley, I. P.: Investigating the controls on soil organic matter decomposition in tussock tundra soil and permafrost after fire, Soil Biol. Biochem., 99, 108–116, 2016. a
Dormann, C. F. and Woodin, S. J.: Climate change in the Arctic: using plant functional types in a meta-analysis of field experiments, Funct. Ecol., 16, 4–17, 2002. a
Ehleringer, J. R., Buchmann, N., and Flanagan, L. B.: Carbon isotope ratios in belowground carbon cycle processes, Ecol. Appl., 10, 412–422, 2000. a
Ellis, C. J., Crittenden, P. D., Scrimgeour, C. M., and Ashcroft, C.: The natural abundance of 15N in mat-forming lichens, Oecologia, 136, 115–123, 2003. a
Estop-Aragonés, C., Olefeldt, D., Abbott, B. W., Chanton, J. P., Czimczik, C. I., Dean, J. F., Egan, J. E., Gandois, L., Garnett, M. H., and Hartley, I. P.: Assessing the Potential for Mobilization of Old Soil Carbon After Permafrost Thaw: A Synthesis of 14C Measurements From the Northern Permafrost Region, Global Biogeochem. Cy., 34, e2020GB006672, https://doi.org/10.1029/2020GB006672, 2020. a
Farquhar, G. D., Ehleringer, J. R., and Hubick, K. T.: Carbon isotope discrimination and photosynthesis, Annu. Rev. Plant Biol., 40, 503–537, 1989. a
Frost, G. V., Loehman, R. A., Saperstein, L. B., Macander, M. J., Nelson, P. R., Paradis, D. P., and Natali, S. M.: Multi-decadal patterns of vegetation succession after tundra fire on the Yukon-Kuskokwim Delta, Alaska, Environ. Res. Lett., 15, 25003, https://doi.org/10.1088/1748-9326/ab5f49, 2020. a, b
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., and Moore, R.: Google Earth Engine: Planetary-scale geospatial analysis for everyone, Remote Sens. Environ., 202, 18–27, 2017. a
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. a, b
Heim, R. J., Bucharova, A., Brodt, L., Kamp, J., Rieker, D., Soromotin, A. V., Yurtaev, A., and Hoelzel, N.: Post-fire vegetation succession in the Siberian subarctic tundra over 45 years, Sci. Total Environ., 760, 143425, https://doi.org/10.1016/j.scitotenv.2020.143425, 2021a. a, b, c, d, e, f, g, h, i, j, k, l
Heim, R. J., Yurtaev, A., Bucharova, A., Heim, W., Kutskir, V., Knorr, K.-H., Lampei, C., Pechkin, A., Schilling, D., Sulkarnaev, F., and Hoelzel, N.: Dataset for “Fire in lichen-rich subarctic tundra changes carbon and nitrogen cycling between ecosystem compartments but has minor effects on stocks”, Zenodo [data set], https://doi.org/10.5281/zenodo.5582683, 2021b. a
Heim, R. J., Yurtaev, A., Bucharova, A., Heim, W., Kutskir, V., Knorr, K.-H., Lampei, C., Pechkin, A., Schilling, D., Sulkarnaev, F., and Hoelzel, N.: R-Code for “Fire in lichen-rich subarctic tundra changes carbon and nitrogen cycling between ecosystem compartments but has minor effects on stocks”, Zenodo [code],
https://doi.org/10.5281/zenodo.5583511, 2021c. a
Hewitt, R. E., Bent, E., Hollingsworth, T. N., Chapin III, F. S., and Taylor, D. L.: Resilience of Arctic mycorrhizal fungal communities after wildfire facilitated by resprouting shrubs, Ecoscience, 20, 296–310, 2013. a
Holloway, J. E., Lewkowicz, A. G., Douglas, T. A., Li, X., Turetsky, M. R., Baltzer, J. L., and Jin, H.: Impact of wildfire on permafrost landscapes: A review of recent advances and future prospects, Permafrost Periglac., 31, 371–382, 2020. a
Holzkämper, S., Tillman, P. K., Kuhry, P., and Esper, J.: Comparison of stable carbon and oxygen isotopes in Picea glauca tree rings and Sphagnum fuscum moss remains from subarctic Canada, Quaternary Res., 78, 295–302, 2012. a
Hu, F. S., Higuera, P. E., Duffy, P., Chipman, M. L., Rocha, A. V., Young, A. M., Kelly, R., and Dietze, M. C.: Arctic tundra fires: Natural variability and responses to climate change, Front. Ecol. Environ., 13, 369–377, https://doi.org/10.1890/150063, 2015. a
IUSS Working Group WRB: World Reference Base for Soil Resources 2014, update 2015 International soil classification system for naming soils and creating legends for soil maps, World Soil Resources Reports, No. 106, FAO, Rome, ISBN 978-92-5-108369-7, 2015. a
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. a
Jansson, J. K. and Hofmockel, K. S.: Soil microbiomes and climate change, Nat. Rev. Microbiol., 18, 35–46, https://doi.org/10.1038/s41579-019-0265-7, 2020. a
Jiang, Y., Rocha, A. V., O'Donnell, J. A., Drysdale, J. A., Rastetter, E. B., Shaver, G. R., and Zhuang, Q.: Contrasting soil thermal responses to fire in Alaskan tundra and boreal forest, J. Geophys. Res.-Earth, 120, 363–378, https://doi.org/10.1002/2014jf003180, 2015. a
Jonasson, S., Chapin III, F. S., and Shaver, G. R.: Biogeochemistry in the Arctic: patterns, processes, and controls, in: Global biogeochemical cycles in the climate system, Elsevier, 139–150, https://doi.org/10.1016/B978-012631260-7/50012-1, 2001. a
Korner-Nievergelt, F., Roth, T., Felten, S. V., Guelat, J., Almasi, B., and Korner-Nievergelt, P.: Bayesian Data Analysis in Ecology using Linear Models with R, BUGS and Stan, Elsevier, London, ISBN 978-0-12-801370-0, 2015. a
Kornienko, S. G.: Cartography of pyrogenic violations of the vegetation cover on the Tazovsky Peninsula with satellite data, Actual Problems of Oil and Gas, 1, 1–11, 2018. a
Kytöviita, M.-M. and Crittenden, P. D.: Growth and nitrogen relations in the mat-forming lichens Stereocaulon paschale and Cladonia stellaris, Ann. Bot.-London, 100, 1537–1545, 2007. a
Lakatos, M., Hartard, B., and Máguas, C.: The stable isotopes δ13C and δ18O of lichens can be used as tracers of microenvironmental carbon and water sources, Terrestrial Ecology, 1, 77–92, 2007. a
Lasslop, G., Hantson, S., Harrison, S. P., Bachelet, D., Burton, C., Forkel, M., Forrest, M., Li, F., Melton, J. R., and Yue, C.: Global ecosystems and fire: multi-model assessment of fire-induced tree cover and carbon storage reduction, Glob. Change Biol., 26, 5027–5041, https://doi.org/10.1111/gcb.15160, 2020. a
Longton, R. E.: The role of bryophytes and lichens in polar ecosystems, Special Publication-British Ecological Society, 13, 69–96, 1997. a
Loranty, M. M., Natali, S. M., Berner, L. T., Goetz, S. J., Holmes, R. M., Davydov, S. P., Zimov, N. S., and Zimov, S. A.: Siberian tundra ecosystem vegetation and carbon stocks four decades after wildfire, J. Geophys. Res.-Biogeo., 119, 2144–2154, https://doi.org/10.1002/2014jg002730, 2014. a, b
Mack, M. C., Schuur, E. A. G., Bret-Harte, M. S., Shaver, G. R., and Chapin, F. S.: Ecosystem carbon storage in arctic tundra reduced by long-term nutrient fertilization, Nature, 431, 440–443, 2004. a
Marion, G. M., Bockheim, J. G., and Brown, J.: Arctic soils and the ITEX experiment, Glob. Change Biol., 3, 33–43, 1997. a
Maslov, M. N., Maslova, O. A., and Kopeina, E. I.: Changes in the pools of total and labile soil organic carbon during post-fire succession in the Khibiny Mountain tundra ecosystems, Eurasian Soil Sci.+, 53, 330–338, 2020. a
McLaren, J. R., Buckeridge, K. M., van de Weg, M. J., Shaver, G. R., Schimel, J. P., and Gough, L.: Shrub encroachment in Arctic tundra: Betula nana effects on above-and belowground litter decomposition, Ecology, 98, 1361–1376, 2017. a
Mollicone, D., Eva, H. D., and Achard, F.: Ecology: Human role in Russian wild fires, Nature, 440, 436, 2006. a
Moritz, M. A., Parisien, M.-A., Batllori, E., Krawchuk, M. A., Van Dorn, J., Ganz, D. J., and Hayhoe, K.: Climate change and disruptions to global fire activity, Ecosphere, 3, 1–22, 2012. a
Narita, K., Harada, K., Saito, K., Sawada, Y., Fukuda, M., and Tsuyuzaki, S.: Vegetation and Permafrost Thaw Depth 10 Years after a Tundra Fire in 2002, Seward Peninsula, Alaska, Arct. Antarct. Alp. Res., 47, 547–559, https://doi.org/10.1657/AAAR0013-031, 2015. a
Peterson, B. J. and Fry, B.: Stable isotopes in ecosystem studies, Annu. Rev. Ecol. Syst., 18, 293–320, 1987. a
Post, E., Alley, R. B., Christensen, T. R., Macias-Fauria, M., Forbes, B. C., Gooseff, M. N., Iler, A., Kerby, J. T., Laidre, K. L., and Mann, M. E.: The polar regions in a 2 ∘C warmer world, Science Advances, 5, eaaw9883, https://doi.org/10.1126/sciadv.aaw9883, 2019. a
R Core Team: R: A Language and Environment for Statistical Computing, Vienna, Austria, http://www.r-project.org/index.html (last access: 24 May 22), 2020. a
Rinnan, R., Michelsen, A., Bååth, E., and Jonasson, S.: Fifteen years of climate change manipulations alter soil microbial communities in a subarctic heath ecosystem, Glob. Change Biol., 13, 28–39, 2007. a
Rosen, Y.: Warming, fires, warming, fires: How tundra wildfires could create an unstoppable cycle,
https://www.adn.com/alaska-
news/science/2016/05/30/warming-fires-warming-fires-how-
tundra-wildfires-could-create-an-unstoppable-cycle/
(last access: 24 May 2022), 2017. a
Sancho, L. G., Belnap, J., Colesie, C., Raggio, J., and Weber, B.: Carbon budgets of biological soil crusts at micro-, meso-, and global scales, in: Biological soil crusts: an organizing principle in drylands, Springer, 287–304, https://doi.org/10.1007/978-3-319-30214-0_15, 2016. a
Schuur, E. A. G., Trumbore, S. E., Mack, M. C., and Harden, J. W.: Isotopic composition of carbon dioxide from a boreal forest fire: Inferring carbon loss from measurements and modeling, Global Biogeochem. Cy., 17, 1, 2003. a
Schuur, E. A. G., Vogel, J. G., Crummer, K. G., Lee, H., Sickman, J. O., and Osterkamp, T. E.: The effect of permafrost thaw on old carbon release and net carbon exchange from tundra, Nature, 459, 556–559, 2009. a
Turetsky, M. R.: The role of bryophytes in carbon and nitrogen cycling, Bryologist, 106, 395–409, 2003. a
Turetsky, M. R., Bond-Lamberty, B., Euskirchen, E., Talbot, J., Frolking, S., McGuire, A. D., and Tuittila, E.: The resilience and functional role of moss in boreal and arctic ecosystems, New Phytol., 196, 49–67, 2012. a
Turetsky, M. R., Benscoter, B., Page, S., Rein, G., Van Der Werf, G. R., and Watts, A.: Global vulnerability of peatlands to fire and carbon loss, Nat. Geosci., 8, 11–14, https://doi.org/10.1038/ngeo2325, 2015. a
U.S. Geological Survey: Earth Explorer, https://earthexplorer.usgs.gov/ (last access: 24 May 2022), 2018. a
Veraverbeke, S., Delcourt, C. J. F., Kukavskaya, E., Mack, M., Walker, X., Hessilt, T., Rogers, B., and Scholten, R. C.: Direct and longer-term carbon emissions from arctic-boreal fires: a short review of recent advances, Current Opinion in Environmental Science and Health, 23, 100277, https://doi.org/10.1016/j.coesh.2021.100277, 2021. a
Vilchek, G. E. and Bykova, O. Y.: The origin of regional ecological problems within the northern Tyumen Oblast, Russia, Arctic Alpine Res., 24, 99–107, 1992. a
Williams, T. G. and Flanagan, L. B.: Effect of changes in water content on photosynthesis, transpiration and discrimination against 13CO2 and C18O16O in Pleurozium and Sphagnum, Oecologia, 108, 38–46, 1996. a
Williams, T. G. and Flanagan, L. B.: Measuring and modelling environmental influences on photosynthetic gas exchange in Sphagnum and Pleurozium, Plant Cell Environ., 21, 555–564, 1998. a
Young, A. M., Higuera, P. E., Duffy, P. A., and Hu, F. S.: Climatic thresholds shape northern high-latitude fire regimes and imply vulnerability to future climate change, Ecography, 39, 1–12, 2016. a
Yu, Q., Epstein, H. E., Engstrom, R., Shiklomanov, N., and Strelestskiy, D.: Land cover and land use changes in the oil and gas regions of Northwestern Siberia under changing climatic conditions, Environ. Res. Lett., 10, 124020, https://doi.org/10.1088/1748-9326/10/12/124020, 2015. a
Yurkovskaya, T. K.: Vegetation map [Karta rastitel'nosti], in: National Atlas of Soils of the Russian Federation [Natsional'nyy atlas pochv Rossiyskoy Federatsii], edited by: Shoba, S. A., Alyabina, I. O., Urusevskaya, I. S., and Chernova, O. V., Moscow State University, Moscow, 46–48, https://doi.org/10.31111/geobotmap/1984.3, 2011. a
Short summary
Fires will probably increase in Arctic regions due to climate change. Yet, the long-term effects of tundra fires on carbon (C) and nitrogen (N) stocks and cycling are still unclear. We investigated the long-term fire effects on C and N stocks and cycling in soil and aboveground living biomass.
We found that tundra fires did not affect total C and N stocks because a major part of the stocks was located belowground in soils which were largely unaltered by fire.
Fires will probably increase in Arctic regions due to climate change. Yet, the long-term effects...
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