Articles | Volume 17, issue 13
https://doi.org/10.5194/gmd-17-5349-2024
© 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/gmd-17-5349-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
11 Jul 2024
Development and technical paper |
| 11 Jul 2024
| 11 Jul 2024
Modelling boreal forest's mineral soil and peat C dynamics with the Yasso07 model coupled with the Ricker moisture modifier
Natural Resources Institute Finland (Luke), Helsinki, Finland
Aleksi Lehtonen
Natural Resources Institute Finland (Luke), Helsinki, Finland
Alla Yurova
Northwest Institute of Eco-environment and Resources, Lanzhou, China
Rose Abramoff
Lawrence Berkeley National Laboratory, University of California, Berkeley, Berkeley, CA, USA
Institute for Globally Distributed Open Research and Education (IGDORE), Montclair, NJ, USA
Bertrand Guenet
Laboratoire de Géologie, L'École Normale Supérieure (ENS), Paris, France
Elisa Bruni
Laboratoire de Géologie, L'École Normale Supérieure (ENS), Paris, France
Samuli Launiainen
Natural Resources Institute Finland (Luke), Helsinki, Finland
Mikko Peltoniemi
Natural Resources Institute Finland (Luke), Helsinki, Finland
Shoji Hashimoto
Forestry and Forest Products Research Institute (FFPRI), Tsukuba, Japan
Xianglin Tian
Dept. of Forest Sciences, University of Helsinki, Helsinki, Finland
College of Forestry, Northwest A&F University, Yangling, Shaanxi, China
Juha Heikkinen
Natural Resources Institute Finland (Luke), Helsinki, Finland
Kari Minkkinen
Dept. of Forest Sciences, University of Helsinki, Helsinki, Finland
Raisa Mäkipää
Natural Resources Institute Finland (Luke), Helsinki, Finland
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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
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Maiju Linkosalmi, Juha-Pekka Tuovinen, Olli Nevalainen, Mikko Peltoniemi, Cemal M. Taniş, Ali N. Arslan, Juuso Rainne, Annalea Lohila, Tuomas Laurila, and Mika Aurela
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Geosci. Model Dev., 15, 2813–2838, https://doi.org/10.5194/gmd-15-2813-2022, https://doi.org/10.5194/gmd-15-2813-2022, 2022
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A methane model that features methane production and transport by plants, the ebullition process and diffusion in soil, oxidation to CO2, and CH4 fluxes to the atmosphere has been embedded in the ORCHIDEE-PEAT land surface model, which includes an explicit representation of northern peatlands. This model, ORCHIDEE-PCH4, was calibrated and evaluated on 14 peatland sites. Results show that the model is sensitive to temperature and substrate availability over the top 75 cm of soil depth.
Céline Gommet, Ronny Lauerwald, Philippe Ciais, Bertrand Guenet, Haicheng Zhang, and Pierre Regnier
Earth Syst. Dynam., 13, 393–418, https://doi.org/10.5194/esd-13-393-2022, https://doi.org/10.5194/esd-13-393-2022, 2022
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Dissolved organic carbon (DOC) leaching from soils into river networks is an important component of the land carbon (C) budget, but its spatiotemporal variation is not yet fully constrained. We use a land surface model to simulate the present-day land C budget at the European scale, including leaching of DOC from the soil. We found average leaching of 14.3 Tg C yr−1 (0.6 % of terrestrial net primary production) with seasonal variations. We determine runoff and temperature to be the main drivers.
Yuanyuan Huang, Phillipe Ciais, Maurizio Santoro, David Makowski, Jerome Chave, Dmitry Schepaschenko, Rose Z. Abramoff, Daniel S. Goll, Hui Yang, Ye Chen, Wei Wei, and Shilong Piao
Earth Syst. Sci. Data, 13, 4263–4274, https://doi.org/10.5194/essd-13-4263-2021, https://doi.org/10.5194/essd-13-4263-2021, 2021
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Pavel Alekseychik, Aino Korrensalo, Ivan Mammarella, Samuli Launiainen, Eeva-Stiina Tuittila, Ilkka Korpela, and Timo Vesala
Biogeosciences, 18, 4681–4704, https://doi.org/10.5194/bg-18-4681-2021, https://doi.org/10.5194/bg-18-4681-2021, 2021
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Elisa Bruni, Bertrand Guenet, Yuanyuan Huang, Hugues Clivot, Iñigo Virto, Roberta Farina, Thomas Kätterer, Philippe Ciais, Manuel Martin, and Claire Chenu
Biogeosciences, 18, 3981–4004, https://doi.org/10.5194/bg-18-3981-2021, https://doi.org/10.5194/bg-18-3981-2021, 2021
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Drones with thermal cameras are powerful new tools with the potential to provide new insights into atmospheric turbulence and heat fluxes. In a pioneering experiment, a Matrice 210 drone with a Zenmuse XT2 thermal camera was used to record 10–20 min thermal videos at 500 m a.g.l. over the Siikaneva peatland in southern Finland. A method to visualize the turbulent structures and derive their parameters from thermal videos is developed. The study provides a novel approach for turbulence analysis.
Yan Sun, Daniel S. Goll, Jinfeng Chang, Philippe Ciais, Betrand Guenet, Julian Helfenstein, Yuanyuan Huang, Ronny Lauerwald, Fabienne Maignan, Victoria Naipal, Yilong Wang, Hui Yang, and Haicheng Zhang
Geosci. Model Dev., 14, 1987–2010, https://doi.org/10.5194/gmd-14-1987-2021, https://doi.org/10.5194/gmd-14-1987-2021, 2021
Short summary
Short summary
We evaluated the performance of the nutrient-enabled version of the land surface model ORCHIDEE-CNP v1.2 against remote sensing, ground-based measurement networks and ecological databases. The simulated carbon, nitrogen and phosphorus fluxes among different spatial scales are generally in good agreement with data-driven estimates. However, the recent carbon sink in the Northern Hemisphere is substantially underestimated. Potential causes and model development priorities are discussed.
Cited articles
Abramoff, R. Z., Guenet, B., Zhang, H., Georgiou, K., Xu, X., Viscarra Rossel, R. A., Yuan, W., and Ciais, P.: Improved global-scale predictions of soil carbon stocks with Millennial Version 2, Soil Biol. Biochem., 164, 108466, https://doi.org/10.1016/j.soilbio.2021.108466, 2022.
Adair, E. C., Parton, W. J., Del Grosso, S. J., Silver, W. L., Harmon, M. E., Hall, S. A., Burke, I. C., and Hart, S. C.: Simple three-pool model accurately describes patterns of long-term litter decomposition in diverse climates, Glob. Change Biol., 14, 2636–2660, https://doi.org/10.1111/j.1365-2486.2008.01674.x, 2008.
Barnard, R. L., Blazewicz, S. J., and Firestone, M. K.: Rewetting of soil: Revisiting the origin of soil CO2 emissions, Soil Biol. Biochem., 147, 107819, https://doi.org/10.1016/j.soilbio.2020.107819, 2020.
Berg, B., Booltink, H., Breymeyer, A., Ewertsson, A., Gallardo, A., Holm, B., Johansson, M.-B., Koivuoja, S., Meentemeyer, V., Nyman, P., Olofsson, J., Pettersson, A.-S., Reurslag, A., Staaf, H., Staaf, I., and Uba, L.: Data on needle litter decomposition and soil climate as well as site characteristics for some coniferous forest sites, Part I, Site characteristics, Report 41, Swedish University of Agricultural Sciences, Department of Ecology and Environmental Research, Uppsala, 1991a.
Berg, B., Booltink, H., Breymeyer, A., Ewertsson, A., Gallardo, A., Holm, B., Johansson, M.-B., Koivuoja, S., Meentemeyer, V., Nyman, P., Olofsson, J., Pettersson, A.-S., Reurslag, A., Staaf, H., Staaf, I., and Uba, L.: Data on needle litter decomposition and soil climate as well as site characteristics for some coniferous forest sites, Part II, Decomposition data, Report 42, Swedish University of Agricultural Sciences, Department of Ecology and Environmental Research, Uppsala, 1991b.
Berg, B., Berg, M. P., Bottner, P., Box, E., Breymeyer, A., De Anta, R. C., Couteaux, M., Mälkönen, E., McClaugherty, C., Meentemeyer, V., Munoz, F., Piussi, P., Remacle, J., and De Santo, A. V.: Litter mass loss in pine forests of Europe and Eastern United States: some relationships with climate and litter quality, Biogeochemistry, 20, 127–159, https://doi.org/10.1007/BF00000785, 1993.
Bhatti, J., Errington, R., Bauer, I., and Hurdle, P.: Carbon stock trends along forested peatland margins in central Saskatchewan, Can. J. Soil Sci., 86, 321–333, https://doi.org/10.4141/S05-085, 2006.
Bolker, B. M.: Deterministic Functions for Ecological Modeling, in: 3. Deterministic Functions for Ecological Modeling, Princeton University Press, 72–102, https://doi.org/10.1515/9781400840908-004, 2008.
Bona, K. A., Shaw, C., Thompson, D. K., Hararuk, O., Webster, K., Zhang, G., Voicu, M., and Kurz, W. A.: The Canadian model for peatlands (CaMP): A peatland carbon model for national greenhouse gas reporting, Ecol. Model., 431, 109164, https://doi.org/10.1016/j.ecolmodel.2020.109164, 2020.
Brooks, S. P. and Gelman, A.: General Methods for Monitoring Convergence of Iterative Simulations, J. Comput. Graphical Stat., 7, 434–455, https://doi.org/10.1080/10618600.1998.10474787, 1998.
Cajander A. K.: Forest types and their significance, Acta Forestalia Fennica, 56, 5, https://doi.org/10.14214/aff.7396, 1949.
Chadburn, S. E., Burke, E. J., Gallego-Sala, A. V., Smith, N. D., Bret-Harte, M. S., Charman, D. J., Drewer, J., Edgar, C. W., Euskirchen, E. S., Fortuniak, K., Gao, Y., Nakhavali, M., Pawlak, W., Schuur, E. A. G., and Westermann, S.: A new approach to simulate peat accumulation, degradation and stability in a global land surface scheme (JULES vn5.8_accumulate_soil) for northern and temperate peatlands, Geosci. Model Dev., 15, 1633–1657, https://doi.org/10.5194/gmd-15-1633-2022, 2022.
Chen, S., Wang, J., Zhang, T., and Hu, Z.: Climatic, soil, and vegetation controls of the temperature sensitivity (Q10) of soil respiration across terrestrial biomes, Global Ecology and Conservation, 22, e00955, https://doi.org/10.1016/j.gecco.2020.e00955, 2020.
Clymo, R. S.: A Model of Peat Bog Growth, in: Production Ecology of British Moors and Montane Grasslands, Ecological Studies, vol 27, edited by: Heal, O. W. and Perkins, D. F., Springer, Berlin, Heidelberg, https://doi.org/10.1007/978-3-642-66760-2_9, 1978.
Clymo, R. S.: Models of peat growth, Suo, 43, 127–136, 1992.
Dalsgaard, L., Lange, H., Strand, L. T., Callesen, I., Borgen, S. K., Liski, J., and Astrup, R.: Underestimation of boreal forest soil carbon stocks related to soil classification and drainage, Can. J. Forest Res., 46, 1413–1425, https://doi.org/10.1139/cjfr-2015-0466, 2016.
Das, S., Richards, B. K., Hanley, K. L., Krounbi, L., Walter, M. F., Walter, M. T., Steenhuis, T. S., and Lehmann, J.: Lower mineralizability of soil carbon with higher legacy soil moisture, Soil Biol. Biochem., 130, 94–104, https://doi.org/10.1016/j.soilbio.2018.12.006, 2019.
Davidson, E. A., Belk, E., and Boone, R. D.: Soil water content and temperature as independent or confounded factors controlling soil respiration in a temperate mixed hardwood forest, Glob. Change Biol., 4, 217–227, https://doi.org/10.1046/j.1365-2486.1998.00128.x, 1998.
Davidson, E. A., Savage, K. E., Trumbore, S. E., and Borken, W.: Vertical partitioning of CO2 production within a temperate forest soil, Glob. Change Biol., 12, 944–956, https://doi.org/10.1111/j.1365-2486.2005.01142.x, 2006.
Davidson, E. A., Samanta, S., Caramori, S. S., and Savage, K.: The Dual Arrhenius and Michaelis–Menten kinetics model for decomposition of soil organic matter at hourly to seasonal time scales, Glob. Change Biol., 18, 371–384, https://doi.org/10.1111/j.1365-2486.2011.02546.x, 2012.
Dimitrov, D. D., Bhatti, J. S., and Grant, R. F.: The transition zones (ecotone) between boreal forests and peatlands: Ecological controls on ecosystem productivity along a transition zone between upland black spruce forest and a poor forested fen in central Saskatchewan, Ecol. Model., 291, 96–108, https://doi.org/10.1016/j.ecolmodel.2014.07.020, 2014.
Dimitrov, D. D., Lafleur, P., Sonnentag, O., Talbot, J., and Quinton, W. L.: Hydrology of peat estimated from near-surface water contents, Hydrolog. Sci. J., 67, 1702–1721, https://doi.org/10.1080/02626667.2022.2099281, 2022.
Fairbairn, L., Rezanezhad, F., Gharasoo, M., Parsons, C. T., Macrae, M. L., Slowinski, S., and Van Cappellen, P.: Relationship between soil CO2 fluxes and soil moisture: Anaerobic sources explain fluxes at high water content, Geoderma, 434, 116493, https://doi.org/10.1016/j.geoderma.2023.116493, 2023.
Falloon, P., Jones, C. D., Ades, M., and Paul, K.: Direct soil moisture controls of future global soil carbon changes: An important source of uncertainty, Global Biogeochem. Cy., 25, GB3010, https://doi.org/10.1029/2010GB003938, 2011.
Frolking, S., Roulet, N. T., Moore, T. R., Richard, P. J. H., Lavoie, M., and Muller, S. D.: Modeling Northern Peatland Decomposition and Peat Accumulation, Ecosystems, 4, 479–498, https://doi.org/10.1007/s10021-001-0105-1, 2001.
Frolking, S., Roulet, N. T., Tuittila, E., Bubier, J. L., Quillet, A., Talbot, J., and Richard, P. J. H.: A new model of Holocene peatland net primary production, decomposition, water balance, and peat accumulation, Earth Syst. Dynam., 1, 1–21, https://doi.org/10.5194/esd-1-1-2010, 2010.
Gao, Y., Markkanen, T., Aurela, M., Mammarella, I., Thum, T., Tsuruta, A., Yang, H., and Aalto, T.: Response of water use efficiency to summer drought in a boreal Scots pine forest in Finland, Biogeosciences, 14, 4409–4422, https://doi.org/10.5194/bg-14-4409-2017, 2017.
Ghezzehei, T. A., Sulman, B., Arnold, C. L., Bogie, N. A., and Berhe, A. A.: On the role of soil water retention characteristic on aerobic microbial respiration, Biogeosciences, 16, 1187–1209, https://doi.org/10.5194/bg-16-1187-2019, 2019.
Gholz, H. L., Wedin, D. A., Smitherman, S. M., Harmon, M. E., and Parton, W. J.: Long-term dynamics of pine and hardwood litter in contrasting environments: toward a global model of decomposition, Glob. Change Biol., 6, 751–765, https://doi.org/10.1046/j.1365-2486.2000.00349.x, 2000.
Goll, D. S., Brovkin, V., Liski, J., Raddatz, T., Thum, T., and Todd-Brown, K. E. O.: Strong dependence of CO2 emissions from anthropogenic land cover change on initial land cover and soil carbon parametrization, Global Biogeochem. Cy., 29, 1511–1523, https://doi.org/10.1002/2014GB004988, 2015.
González-Domínguez, B., Niklaus, P. A., Studer, M. S., Hagedorn, F., Wacker, L., Haghipour, N., Zimmermann, S., Walthert, L., McIntyre, C., and Abiven, S.: Temperature and moisture are minor drivers of regional-scale soil organic carbon dynamics, Sci. Rep.-UK, 9, 6422, https://doi.org/10.1038/s41598-019-42629-5, 2019.
Han, Q., Zeng, Y., Zhang, L., Wang, C., Prikaziuk, E., Niu, Z., and Su, B.: Global long term daily 1 km surface soil moisture dataset with physics informed machine learning, Sci. Data, 10, 101, https://doi.org/10.1038/s41597-023-02011-7, 2023.
Hararuk, O., Xia, J., and Luo, Y.: Evaluation and improvement of a global land model against soil carbon data using a Bayesian Markov chain Monte Carlo method, J. Geophys. Res.-Biogeo., 119, 403–417, https://doi.org/10.1002/2013JG002535, 2014.
Hararuk, O., Smith, M. J., and Luo, Y.: Microbial models with data-driven parameters predict stronger soil carbon responses to climate change, Glob. Change Biol., 21, 2439–2453, https://doi.org/10.1111/gcb.12827, 2015.
Hartig, F., Dyke, J., Hickler, T., Higgins, S. I., O'Hara, R. B., Scheiter, S., and Huth, A.: Connecting dynamic vegetation models to data – an inverse perspective, J. Biogeogr., 39, 2240–2252, https://doi.org/10.1111/j.1365-2699.2012.02745.x, 2012.
Hartig, F., Minunno, F., Paul, S., Cameron, D., Ott, T., and Pichler, M.: BayesianTools: General-Purpose MCMC and SMC Samplers and Tools for Bayesian Statistics, https://CRAN.R-project.org/package=BayesianTools (last access: 5 July 2024), 2019.
Hartshorn, A. S., Southard, R. J., and Bledsoe, C. S.: Structure and Function of Peatland-Forest Ecotones in Southeastern Alaska, Soil Sci. Soc. Am. J., 67, 1572–1581, https://doi.org/10.2136/sssaj2003.1572, 2003.
Hashimoto, S., Morishita, T., Sakata, T., Ishizuka, S., Kaneko, S., and Takahashi, M.: Simple models for soil CO2, CH4, and N2O fluxes calibrated using a Bayesian approach and multi-site data, Ecol. Model., 222, 1283–1292, https://doi.org/10.1016/j.ecolmodel.2011.01.013, 2011.
Hashimoto, S., Nanko, K., Ťupek, B., and Lehtonen, A.: Data-mining analysis of the global distribution of soil carbon in observational databases and Earth system models, Geosci. Model Dev., 10, 1321–1337, https://doi.org/10.5194/gmd-10-1321-2017, 2017.
Huang, W. and Hall, S. J.: Elevated moisture stimulates carbon loss from mineral soils by releasing protected organic matter, Nat. Commun., 8, 1774, https://doi.org/10.1038/s41467-017-01998-z, 2017.
Humphrey, V., Berg, A., Ciais, P., Gentine, P., Jung, M., Reichstein, M., Seneviratne, S. I., and Frankenberg, C.: Soil moisture–atmosphere feedback dominates land carbon uptake variability, Nature, 592, 65–69, https://doi.org/10.1038/s41586-021-03325-5, 2021.
Jian, J., Steele, M. K., Zhang, L., Bailey, V. L., Zheng, J., Patel, K. F., and Bond-Lamberty, B. P.: On the use of air temperature and precipitation as surrogate predictors in soil respiration modelling, Eur. J. Soil Sci., 73, e13149, https://doi.org/10.1111/ejss.13149, 2022.
Karhu, K., Fritze, H., Hämaläinen, K., Vanhala, P., Jungner, H., Oinonen, M., Sonninen, E., Tuomi, M., Spetz, P., Kitunen, V., and Liski, J.: Temperature sensitivity of soil carbon fractions in boreal forest soil, Ecology 91, 370–376, https://www.jstor.org/stable/25661063 (last access: 5 July 2024), 2010.
Keenan, T. F., Davidson, E. A., Munger, J. W., and Richardson, A. D.: Rate my data: quantifying the value of ecological data for the development of models of the terrestrial carbon cycle, Ecol. Appl., 23, 273–286, https://doi.org/10.1890/12-0747.1, 2013.
Kelly, R. H., Parton, W. J., Hartman, M. D., Stretch, L. K., Ojima, D. S., and Schimel, D. S.: Intra-annual and interannual variability of ecosystem processes in shortgrass steppe, J. Geophys. Res.-Atmos., 105, 20093–20100, https://doi.org/10.1029/2000JD900259, 2000.
Kleinen, T., Brovkin, V., and Schuldt, R. J.: A dynamic model of wetland extent and peat accumulation: results for the Holocene, Biogeosciences, 9, 235–248, https://doi.org/10.5194/bg-9-235-2012, 2012.
Kleinen, T., Gromov, S., Steil, B., and Brovkin, V.: Atmospheric methane underestimated in future climate projections, Environ. Res. Lett., 16, 094006, https://doi.org/10.1088/1748-9326/ac1814, 2021.
Laine, J., Komulainen, V. M., Laiho, R., Minkkinen, K., Rasinmaki, A., Sallantaus, T., Sarkkola, S., Silvan, N., Tolonen, K., Tuittila, E. S., Vasander, H., and Paivanen, J.: Lakkasuo: a guide to mire ecosystem, Helsingin yliopiston metsäekologian laitoksen julkaisuja, Helsingin yliopisto, metsäekologian laitos, Helsinki, 2004.
Launiainen, S., Guan, M., Salmivaara, A., and Kieloaho, A.-J.: Modeling boreal forest evapotranspiration and water balance at stand and catchment scales: a spatial approach, Hydrol. Earth Syst. Sci., 23, 3457–3480, https://doi.org/10.5194/hess-23-3457-2019, 2019.
Lehtonen, A., Linkosalo, T., Peltoniemi, M., Sievänen, R., Mäkipää, R., Tamminen, P., Salemaa, M., Nieminen, T., Ťupek, B., Heikkinen, J., and Komarov, A.: Forest soil carbon stock estimates in a nationwide inventory: evaluating performance of the ROMULv and Yasso07 models in Finland, Geosci. Model Dev., 9, 4169–4183, https://doi.org/10.5194/gmd-9-4169-2016, 2016a.
Lehtonen, A., Palviainen, M., Ojanen, P., Kalliokoski, T., Nöjd, P., Kukkola, M., Penttilä, T., Mäkipää, R., Leppälammi-Kujansuu, J., and Helmisaari, H.-S.: Modelling fine root biomass of boreal tree stands using site and stand variables. For. Ecol. Manag., 359, 361–369, https://doi.org/10.1016/j.foreco.2015.06.023, 2016b.
Leifeld, J. and Menichetti, L.: The underappreciated potential of peatlands in global climate change mitigation strategies, Nat. Commun., 9, 1071, https://doi.org/10.1038/s41467-018-03406-6, 2018.
Leppä, K., Hökkä, H., Laiho, R., Launiainen, S., Lehtonen, A., Mäkipää, R., Peltoniemi, M., Saarinen, M., Sarkkola, S., and Nieminen, M.: Selection Cuttings as a Tool to Control Water Table Level in Boreal Drained Peatland Forests, Front. Earth Sci., 8, https://doi.org/10.3389/feart.2020.576510, 2020.
Luo, Y. and Schuur, E. A. G.: Model parameterization to represent processes at unresolved scales and changing properties of evolving systems, Glob. Change Biol., 26, 1109–1117, https://doi.org/10.1111/gcb.14939, 2020.
Luo, Y., Ogle, K., Tucker, C., Fei, S., Gao, C., LaDeau, S., Clark, J. S., and Schimel, D. S.: Ecological forecasting and data assimilation in a data-rich era, Ecol. Appl., 21, 1429–1442, https://doi.org/10.1890/09-1275.1, 2011.
Manzoni, S., Schimel, J. P., and Porporato, A.: Responses of soil microbial communities to water stress: results from a meta-analysis, Ecology, 93, 930–938, https://doi.org/10.1890/11-0026.1, 2012.
Metherell, A. K., Harding, L. A., Cole, C. V., and Parton, W. J.: CENTURY Soil Organic Matter Model Environment Technical Documentation, Agroecosystem Version 4.0, Technical Report No. 4, Great Plains System Research Unit, USDA-ARS, Ft. Collins, 1993.
Moyano, F. E., Vasilyeva, N., Bouckaert, L., Cook, F., Craine, J., Curiel Yuste, J., Don, A., Epron, D., Formanek, P., Franzluebbers, A., Ilstedt, U., Kätterer, T., Orchard, V., Reichstein, M., Rey, A., Ruamps, L., Subke, J.-A., Thomsen, I. K., and Chenu, C.: The moisture response of soil heterotrophic respiration: interaction with soil properties, Biogeosciences, 9, 1173–1182, https://doi.org/10.5194/bg-9-1173-2012, 2012.
Moyano, F. E., Manzoni, S., and Chenu, C.: Responses of soil heterotrophic respiration to moisture availability: An exploration of processes and models, Soil Biol. Biochem., 59, 72–85, https://doi.org/10.1016/j.soilbio.2013.01.002, 2013.
Parton, W. J.: The CENTURY model, in: Evaluation of Soil Organic Matter Models, NATO ASI Series, edited by: Powlson, D. S., Smith, P., and Smith, J. U., Springer, Berlin, Heidelberg, 283–291, https://doi.org/10.1007/978-3-642-61094-3_23, 1996.
Patel, K. F., Myers-Pigg, A., Bond-Lamberty, B., Fansler, S. J., Norris, C. G., McKever, S. A., Zheng, J., Rod, K. A., and Bailey, V. L.: Soil carbon dynamics during drying vs. rewetting: Importance of antecedent moisture conditions, Soil Biol. Biochem., 156, 108165, https://doi.org/10.1016/j.soilbio.2021.108165, 2021.
Pumpanen, J., Ilvesniemi, H., Kulmala, L., Siivola, E., Laakso, H., Kolari, P., Helenelund, C., Laakso, M., Uusimaa, M., and Hari, P.: Respiration in Boreal Forest Soil as Determined from Carbon Dioxide Concentration Profile, Soil Sci. Soc. Am. J., 72, 1187–1196, https://doi.org/10.2136/sssaj2007.0199, 2008.
Qiu, C., Zhu, D., Ciais, P., Guenet, B., Krinner, G., Peng, S., Aurela, M., Bernhofer, C., Brümmer, C., Bret-Harte, S., Chu, H., Chen, J., Desai, A. R., Dušek, J., Euskirchen, E. S., Fortuniak, K., Flanagan, L. B., Friborg, T., Grygoruk, M., Gogo, S., Grünwald, T., Hansen, B. U., Holl, D., Humphreys, E., Hurkuck, M., Kiely, G., Klatt, J., Kutzbach, L., Largeron, C., Laggoun-Défarge, F., Lund, M., Lafleur, P. M., Li, X., Mammarella, I., Merbold, L., Nilsson, M. B., Olejnik, J., Ottosson-Löfvenius, M., Oechel, W., Parmentier, F.-J. W., Peichl, M., Pirk, N., Peltola, O., Pawlak, W., Rasse, D., Rinne, J., Shaver, G., Schmid, H. P., Sottocornola, M., Steinbrecher, R., Sachs, T., Urbaniak, M., Zona, D., and Ziemblinska, K.: ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO2, water, and energy fluxes on daily to annual scales, Geosci. Model Dev., 11, 497–519, https://doi.org/10.5194/gmd-11-497-2018, 2018.
Raich, J. W., Parton, W. J., Russell, A. E., Sanford, R. L., and Vitousek, P. M.: Analysis of factors regulating ecosystemdevelopment on Mauna Loa using the Century model, Biogeochemistry, 51, 161–191, https://doi.org/10.1023/A:1006495408992, 2000.
R Core Team: R: A language and environment for statistical computing, R Foundation for Statistical Computing, Vienna, Austria, https://www.R-project.org/ (last access: 5 July 2024), 2023.
Repola, J.: Biomass equations for birch in Finland, Silva Fenn., 42, 605–624, https://doi.org/10.14214/sf.236, 2008.
Repola, J.: Biomass equations for Scots pine and Norway spruce in Finland, Silva Fenn., 43, 625–647, https://doi.org/10.14214/sf.184, 2009.
Sainte-Marie, J., Barrandon, M., Saint-André, L., Gelhaye, E., Martin, F., and Derrien, D.: C-STABILITY an innovative modeling framework to leverage the continuous representation of organic matter, Nat. Commun., 12, 810, https://doi.org/10.1038/s41467-021-21079-6, 2021,.
Scharlemann, J. P., Tanner, E. V., Hiederer, R., and Kapos, V.: Global soil carbon: understanding and managing the largest terrestrial carbon pool, Carbon Manag., 5, 81–91, https://doi.org/10.4155/cmt.13.77, 2014.
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.
Sierra, C. A., Müller, M., and Trumbore, S. E.: Models of soil organic matter decomposition: the SoilR package, version 1.0, Geosci. Model Dev., 5, 1045–1060, https://doi.org/10.5194/gmd-5-1045-2012, 2012.
Sierra, C. A., Trumbore, S. E., Davidson, E. A., Vicca, S., and Janssens, I.: Sensitivity of decomposition rates of soil organic matter with respect to simultaneous changes in temperature and moisture, J. Adv. Model. Earth Sy., 7, 335–356, https://doi.org/10.1002/2014MS000358, 2015.
Sierra, C. A., Malghani, S., and Loescher, H. W.: Interactions among temperature, moisture, and oxygen concentrations in controlling decomposition rates in a boreal forest soil, Biogeosciences, 14, 703–710, https://doi.org/10.5194/bg-14-703-2017, 2017.
Skopp, J., Jawson, M. D., and Doran, J. W.: Steady-State Aerobic Microbial Activity as a Function of Soil Water Content, Soil Sci. Soc. Am. J., 54, 1619–1625, https://doi.org/10.2136/sssaj1990.03615995005400060018x, 1990.
Speich, M., Dormann, C. F., and Hartig, F.: Sequential Monte-Carlo algorithms for Bayesian model calibration – A review and method comparison, Ecol. Model., 455, 109608, https://doi.org/10.1016/j.ecolmodel.2021.109608, 2021.
Statistics Finland: Greenhouse gas emissions in Finland 1990 to 2021. National Inventory Report under the UNFCCC and the Kyoto Protocol, Statistics Finland, https://www.stat.fi/static/media/uploads/tup/khkinv/fi_nir_eu_2021_2023-03-15.pdf (last access: 15 May 2023), 2023.
St-Hilaire, F., Wu, J., Roulet, N. T., Frolking, S., Lafleur, P. M., Humphreys, E. R., and Arora, V.: McGill wetland model: evaluation of a peatland carbon simulator developed for global assessments, Biogeosciences, 7, 3517–3530, https://doi.org/10.5194/bg-7-3517-2010, 2010.
Straková, P., Anttila, J., Spetz, P., Kitunen, V., Tapanila, T., and Laiho, R.: Litter quality and its response to water level drawdown in boreal peatlands at plant species and community level, Plant Soil, 335, 501–520, https://doi.org/10.1007/s11104-010-0447-6, 2010.
Thum, T., Nabel, J. E. M. S., Tsuruta, A., Aalto, T., Dlugokencky, E. J., Liski, J., Luijkx, I. T., Markkanen, T., Pongratz, J., Yoshida, Y., and Zaehle, S.: Evaluating two soil carbon models within the global land surface model JSBACH using surface and spaceborne observations of atmospheric CO2, Biogeosciences, 17, 5721–5743, https://doi.org/10.5194/bg-17-5721-2020, 2020.
Todd-Brown, K. E. O., Randerson, J. T., Post, W. M., Hoffman, F. M., Tarnocai, C., Schuur, E. A. G., and Allison, S. D.: Causes of variation in soil carbon simulations from CMIP5 Earth system models and comparison with observations, Biogeosciences, 10, 1717–1736, https://doi.org/10.5194/bg-10-1717-2013, 2013.
Trofymow, J. A.: The Canadian Intersite Decomposition ExperimenT (CIDET), Project and site establishment report, Information report BCX-378, Pacific Forestry Centre, Victoria, Canada, 1998.
Tuomi, M., Vanhala, P., Karhu, K., Fritze, H., and Liski, J.: Heterotrophic soil respiration—Comparison of different models describing its temperature dependence, Ecol. Model., 211, 182–190, https://doi.org/10.1016/j.ecolmodel.2007.09.003, 2008.
Tuomi, M., Thum, T., Järvinen, H., Fronzek, S., Berg, B., Harmon, M., Trofymow, J. A., Sevanto, S., and Liski, J.: Leaf litter decomposition – Estimates of global variability based on Yasso07 model, Ecol. Model., 220, 3362–3371, https://doi.org/10.1016/j.ecolmodel.2009.05.016, 2009.
Tuomi, M., Laiho, R., Repo, A., and Liski, J.: Wood decomposition model for boreal forests, Ecol. Model., 222, 709–718, https://doi.org/10.1016/j.ecolmodel.2010.10.025, 2011.
Ťupek, B., Minkkinen, K., Kolari, P., Starr, M., Chan, T., Alm, J., Vesala, T., Laine, J., and Nikinmaa, E.: Forest floor versus ecosystem CO2 exchange along boreal ecotone between upland forest and lowland mire, Tellus B, 60, 153–166, https://doi.org/10.1111/j.1600-0889.2007.00328.x, 2008.
Ťupek, B., Minkkinen, K., Pumpanen, J., Vesala, T., and Nikinmaa, E.: CH4 and N2O dynamics in the boreal forest–mire ecotone, Biogeosciences, 12, 281–297, https://doi.org/10.5194/bg-12-281-2015, 2015.
Ťupek, B., Ortiz, C. A., Hashimoto, S., Stendahl, J., Dahlgren, J., Karltun, E., and Lehtonen, A.: Underestimation of boreal soil carbon stocks by mathematical soil carbon models linked to soil nutrient status, Biogeosciences, 13, 4439–4459, https://doi.org/10.5194/bg-13-4439-2016, 2016.
Ťupek, B., Launiainen, S., Peltoniemi, M., Sievänen, R., Perttunen, J., Kulmala, L., Penttilä, T., Lindroos, A.-J., Hashimoto, S., and Lehtonen, A.: Evaluating CENTURY and Yasso soil carbon models for CO2 emissions and organic carbon stocks of boreal forest soil with Bayesian multi-model inference, Eur. J. Soil Sci., 70, 847–858, https://doi.org/10.1111/ejss.12805, 2019.
Tupek, B., Yurova, A., and Lehtonen, A.: Data assimilation of boreal forest – mire ecotone soil C dynamics into Yasso07 model coupled with updated moisture modifier, Zenodo [code and data set], https://doi.org/10.5281/zenodo.8111475, 2023.
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.
Vávřová, P., Penttilä, T., and Laiho, R.: Decomposition of Scots pine fine woody debris in boreal conditions: Implications for estimating carbon pools and fluxes, Forest Ecol. Manag., 257, 401–412, https://doi.org/10.1016/j.foreco.2008.09.017, 2009.
Viskari, T., Laine, M., Kulmala, L., Mäkelä, J., Fer, I., and Liski, J.: Improving Yasso15 soil carbon model estimates with ensemble adjustment Kalman filter state data assimilation, Geosci. Model Dev., 13, 5959–5971, https://doi.org/10.5194/gmd-13-5959-2020, 2020.
Viskari, T., Pusa, J., Fer, I., Repo, A., Vira, J., and Liski, J.: Calibrating the soil organic carbon model Yasso20 with multiple datasets, Geosci. Model Dev., 15, 1735–1752, https://doi.org/10.5194/gmd-15-1735-2022, 2022.
Wania, R., Ross, I., and Prentice, I. C.: Implementation and evaluation of a new methane model within a dynamic global vegetation model: LPJ-WHyMe v1.3.1, Geosci. Model Dev., 3, 565–584, https://doi.org/10.5194/gmd-3-565-2010, 2010.
Weishampel, P., Kolka, R., and King, J. Y.: Carbon pools and productivity in a 1-km2 heterogeneous forest and peatland mosaic in Minnesota, USA, Forest Ecol. Manag. 257, 747–754, https://doi.org/10.1016/j.foreco.2008.10.008, 2009.
Xia, J. Y., Luo, Y. Q., Wang, Y.-P., Weng, E. S., and Hararuk, O.: A semi-analytical solution to accelerate spin-up of a coupled carbon and nitrogen land model to steady state, Geosci. Model Dev., 5, 1259–1271, https://doi.org/10.5194/gmd-5-1259-2012, 2012.
Xu, T., White, L., Hui, D., and Luo, Y.: Probabilistic inversion of a terrestrial ecosystem model: Analysis of uncertainty in parameter estimation and model prediction, Global Biogeochem. Cy., 20, GB2007, https://doi.org/10.1029/2005GB002468, 2006.
Yan, Z., Bond-Lamberty, B., Todd-Brown, K. E., Bailey, V. L., Siliang, L., Congqiang, L., and Chongxuan, L.: A moisture function of soil heterotrophic respiration that incorporates microscale processes, Nat. Commun., 9, 2562, https://doi.org/10.1038/s41467-018-04971-6, 2018.
Zhiyanski, M.: Seasonal dynamics of fine root biomass in selected forest stands, Silva Balcanica, 15, 5–15, 2014.
Zhou, W., Hui, D., and Shen, W.: Effects of Soil Moisture on the Temperature Sensitivity of Soil Heterotrophic Respiration: A Laboratory Incubation Study, PLOS ONE, 9, e92531, https://doi.org/10.1371/journal.pone.0092531, 2014.
Short summary
Updating the Yasso07 soil C model's dependency on decomposition with a hump-shaped Ricker moisture function improved modelled soil organic C (SOC) stocks in a catena of mineral and organic soils in boreal forest. The Ricker function, set to peak at a rate of 1 and calibrated against SOC and CO2 data using a Bayesian approach, showed a maximum in well-drained soils. Using SOC and CO2 data together with the moisture only from the topsoil humus was crucial for accurate model estimates.
Updating the Yasso07 soil C model's dependency on decomposition with a hump-shaped Ricker...
