Articles | Volume 12, issue 1
https://doi.org/10.5194/soil-12-497-2026
© 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/soil-12-497-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Original research article
| 
27 Apr 2026
Original research article |
| 27 Apr 2026
| 27 Apr 2026
Prediction of peat properties from transmission mid-infrared spectra
Henning Teickner
CORRESPONDING AUTHOR
Ecohydrology & Biogeochemistry Group, Institute of Landscape Ecology, University of Münster, 48149 Münster, Germany
Spatiotemporal Modelling Lab, Institute for Geoinformatics, University of Münster, 48149 Münster, Germany
Klaus-Holger Knorr
Ecohydrology & Biogeochemistry Group, Institute of Landscape Ecology, University of Münster, 48149 Münster, Germany
Related authors
Henning Teickner, Julien Arsenault, Mariusz Gałka, and Klaus-Holger Knorr
EGUsphere, https://doi.org/10.5194/egusphere-2025-5819, https://doi.org/10.5194/egusphere-2025-5819, 2025
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Nicolas Behrens, Klaus-Holger Knorr, Christoph Rückriem, and Mana Gharun
EGUsphere, https://doi.org/10.5194/egusphere-2026-1496, https://doi.org/10.5194/egusphere-2026-1496, 2026
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
We analysed carbon fluxes and their response to climate in a drained bog. Annual budgets varied from net emissions to neutrality. 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.
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
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
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, Julien Arsenault, Mariusz Gałka, and Klaus-Holger Knorr
EGUsphere, https://doi.org/10.5194/egusphere-2025-5819, https://doi.org/10.5194/egusphere-2025-5819, 2025
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Ramona J. Heim, Andrey Yurtaev, Anna Bucharova, Wieland Heim, Valeriya Kutskir, Klaus-Holger Knorr, Christian Lampei, Alexandr Pechkin, Dora Schilling, Farid Sulkarnaev, and Norbert Hölzel
Biogeosciences, 19, 2729–2740, https://doi.org/10.5194/bg-19-2729-2022, https://doi.org/10.5194/bg-19-2729-2022, 2022
Short summary
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.
Cited articles
Agethen, S. and Knorr, K.-H.: Juncus Effusus Mono-Stands in Restored Cutover Peat Bogs – Analysis of Litter Quality, Controls of Anaerobic Decomposition, and the Risk of Secondary Carbon Loss, Soil Biol. Biochem., 117, 139–152, https://doi.org/10.1016/j.soilbio.2017.11.020, 2018. a, b
Alewell, C., Giesler, R., Klaminder, J., Leifeld, J., and Rollog, M.: Stable carbon isotopes as indicators for environmental change in palsa peats, Biogeosciences, 8, 1769–1778, https://doi.org/10.5194/bg-8-1769-2011, 2011. a
Artz, R. R., Chapman, S. J., Jean Robertson, A., Potts, J. M., Laggoun-Défarge, F., Gogo, S., Comont, L., Disnar, J.-R., and Francez, A.-J.: FTIR Spectroscopy Can Be Used as a Screening Tool for Organic Matter Quality in Regenerating Cutover Peatlands, Soil Biol. Biochem., 40, 515–527, https://doi.org/10.1016/j.soilbio.2007.09.019, 2008. a, b, c
Asada, T., Warner, B., and Aravena, R.: Effects of the Early Stage of Decomposition on Change in Carbon and Nitrogen Isotopes in Sphagnum Litter, J. Plant Interact., 1, 229–237, https://doi.org/10.1080/17429140601056766, 2005a. a, b
Asada, T., Warner, B. G., and Aravena, R.: Nitrogen Isotope Signature Variability in Plant Species from Open Peatland, Aquat. Bot., 82, 297–307, https://doi.org/10.1016/j.aquabot.2005.05.005, 2005b. a, b, c
Bader, C., Müller, M., Schulin, R., and Leifeld, J.: Peat decomposability in managed organic soils in relation to land use, organic matter composition and temperature, Biogeosciences, 15, 703–719, https://doi.org/10.5194/bg-15-703-2018, 2018. a, b, c, d
Baird, A. J., Morris, P. J., and Belyea, L. R.: The DigiBog Peatland Development Model 1: Rationale, Conceptual Model, and Hydrological Basis, Ecohydrology, 5, 242–255, https://doi.org/10.1002/eco.230, 2012. a
Battley, E. H.: An Empirical Method for Estimating the Entropy of Formation and the Absolute Entropy of Dried Microbial Biomass for Use in Studies on the Thermodynamics of Microbial Growth, Thermochim. Acta, 326, 7–15, https://doi.org/10.1016/S0040-6031(98)00584-X, 1999. a, b
Bauer, I. E.: Modelling Effects of Litter Quality and Environment on Peat Accumulation over Different Time-Scales: Peat Accumulation over Different Time-Scales, J. Ecol., 92, 661–674, https://doi.org/10.1111/j.0022-0477.2004.00905.x, 2004. a, b
Baysinger, M. R., Wilson, R. M., Hanson, P. J., Kostka, J. E., and Chanton, J. P.: Compositional Stability of Peat in Ecosystem-Scale Warming Mesocosms, PLOS ONE, 17, e0263994, https://doi.org/10.1371/journal.pone.0263994, 2022. a
Beleites, C. and Sergo, V.: hyperSpec: A Package to Handle Hyperspectral Data Sets in R, Comprehensive R Archive Network (CRAN) [code], https://doi.org/10.32614/CRAN.package.hyperSpec, 2021. a
Bellon-Maurel, V., Fernandez-Ahumada, E., Palagos, B., Roger, J.-M., and McBratney, A.: Critical Review of Chemometric Indicators Commonly Used for Assessing the Quality of the Prediction of Soil Attributes by NIR Spectroscopy, TRAC-Trend. Anal. Chem., 29, 1073–1081, https://doi.org/10.1016/j.trac.2010.05.006, 2010. a
Bergner, K. and Albano, C.: Thermal Analysis of Peat, Anal. Chem., 65, 204–208, https://doi.org/10.1021/ac00051a003, 1993. a, b, c
Biester, H., Knorr, K.-H., Schellekens, J., Basler, A., and Hermanns, Y.-M.: Comparison of different methods to determine the degree of peat decomposition in peat bogs, Biogeosciences, 11, 2691–2707, https://doi.org/10.5194/bg-11-2691-2014, 2014. a, b, c, d
Boothroyd, I. M., Worrall, F., Moody, C. S., Clay, G. D., Abbott, G. D., and Rose, R.: Sulfur Constraints on the Carbon Cycle of a Blanket Bog Peatland, J. Geophys. Res.-Biogeo., 126, https://doi.org/10.1029/2021JG006435, 2021. a
Bowling, D. R., Pataki, D. E., and Randerson, J. T.: Carbon Isotopes in Terrestrial Ecosystem Pools and CO2 Fluxes, New Phytol., 178, 24–40, https://doi.org/10.1111/j.1469-8137.2007.02342.x, 2008. a
Bragazza, L. and Iacumin, P.: Seasonal Variation in Carbon Isotopic Composition of Bog Plant Litter during 3 Years of Field Decomposition, Biol. Fert. Soils, 46, 73–77, https://doi.org/10.1007/s00374-009-0406-7, 2009. a
Broder, T., Blodau, C., Biester, H., and Knorr, K. H.: Peat decomposition records in three pristine ombrotrophic bogs in southern Patagonia, Biogeosciences, 9, 1479–1491, https://doi.org/10.5194/bg-9-1479-2012, 2012. a, b, c
Bürkner, P.-C.: Advanced Bayesian Multilevel Modeling with the R Package brms, The R Journal, 10, 395–411, https://doi.org/10.32614/RJ-2018-017, 2018. a
Chambers, F. M., Beilman, D. W., and Yu, Z.: Methods for Determining Peat Humification and for Quantifying Peat Bulk Density, Organic Matter and Carbon Content for Palaeostudies of Climate and Peatland Carbon Dynamics, Mires Peat, 10, 1–10, 2011. a
Chapman, S., Campbell, C., Fraser, A., and Puri, G.: FTIR Spectroscopy of Peat in and Bordering Scots Pine Woodland: Relationship with Chemical and Biological Properties, Soil Biol. Biochem., 33, 1193–1200, https://doi.org/10.1016/S0038-0717(01)00023-2, 2001. a, b, c, d
Charman, D. J., Beilman, D. W., Blaauw, M., Booth, R. K., Brewer, S., Chambers, F. M., Christen, J. A., Gallego-Sala, A., Harrison, S. P., Hughes, P. D. M., Jackson, S. T., Korhola, A., Mauquoy, D., Mitchell, F. J. G., Prentice, I. C., van der Linden, M., De Vleeschouwer, F., Yu, Z. C., Alm, J., Bauer, I. E., Corish, Y. M. C., Garneau, M., Hohl, V., Huang, Y., Karofeld, E., Le Roux, G., Loisel, J., Moschen, R., Nichols, J. E., Nieminen, T. M., MacDonald, G. M., Phadtare, N. R., Rausch, N., Sillasoo, Ü., Swindles, G. T., Tuittila, E.-S., Ukonmaanaho, L., Väliranta, M., van Bellen, S., van Geel, B., Vitt, D. H., and Zhao, Y.: Climate-related changes in peatland carbon accumulation during the last millennium, Biogeosciences, 10, 929–944, https://doi.org/10.5194/bg-10-929-2013, 2013. a, b
Cocozza, C., D'Orazio, V., Miano, T. M., and Shotyk, W.: Characterization of Solid and Aqueous Phases of a Peat Bog Profile Using Molecular Fluorescence Spectroscopy, ESR and FT-IR, and Comparison with Physical Properties, Org. Geochem., 34, 49–60, https://doi.org/10.1016/S0146-6380(02)00208-5, 2003. a
Dale, J., Shock, E., Macleod, G., Aplin, A., and Larter, S.: Standard Partial Molal Properties of Aqueous Alkylphenols at High Pressures and Temperatures, Geochim. Cosmochim. Ac., 61, 4017–4024, https://doi.org/10.1016/S0016-7037(97)00212-3, 1997. a
Dangal, S., Sanderman, J., Wills, S., and Ramirez-Lopez, L.: Accurate and Precise Prediction of Soil Properties from a Large Mid-Infrared Spectral Library, Soil Systems, 3, 11, https://doi.org/10.3390/soilsystems3010011, 2019. a, b
Diaconu, A.-C., Tanţău, I., Knorr, K.-H., Borken, W., Feurdean, A., Panait, A., and Gałka, M.: A Multi-Proxy Analysis of Hydroclimate Trends in an Ombrotrophic Bog over the Last Millennium in the Eastern Carpathians of Romania, Palaeogeogr. Palaeocl., 538, 109390, https://doi.org/10.1016/j.palaeo.2019.109390, 2020. a
Dick, J. M.: CHNOSZ: Thermodynamic Calculations and Diagrams for Geochemistry, Front. Earth Sci., 7, 180, https://doi.org/10.3389/feart.2019.00180, 2019. a
Downey, G. and Byrne, P.: Prediction of Moisture and Bulk Density in Milled Peat by near Infrared Reflectance, J. Sci. Food Agr., 37, 231–238, https://doi.org/10.1002/jsfa.2740370306, 1986. a
Drollinger, S., Kuzyakov, Y., and Glatzel, S.: Effects of Peat Decomposition on δ13C and δ15N Depth Profiles of Alpine Bogs, CATENA, 178, 1–10, https://doi.org/10.1016/j.catena.2019.02.027, 2019. a, b, c
Drollinger, S., Knorr, K.-H., Knierzinger, W., and Glatzel, S.: Peat Decomposition Proxies of Alpine Bogs along a Degradation Gradient, Geoderma, 369, 114331, https://doi.org/10.1016/j.geoderma.2020.114331, 2020. a
Ellerbrock, R. H. and Gerke, H. H.: FTIR Spectral Band Shifts Explained by OM–Cation Interactions, J. Plant Nutr. Soil Sc., 184, 388–397, https://doi.org/10.1002/jpln.202100056, 2021. a, b
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. a
Frolking, S., Talbot, J., Jones, M. C., Treat, C. C., Kauffman, J. B., Tuittila, E.-S., and Roulet, N.: Peatlands in the Earth's 21st Century Climate System, Environ. Rev., 19, 371–396, https://doi.org/10.1139/a11-014, 2011. a, b
Gałka, M., Diaconu, A.-C., Feurdean, A., Loisel, J., Teickner, H., Broder, T., and Knorr, K.-H.: Relations of Fire, Palaeohydrology, Vegetation Succession, and Carbon Accumulation, as Reconstructed from a Mountain Bog in the Harz Mountains (Germany) during the Last 6200 Years, Geoderma, 424, 115991, https://doi.org/10.1016/j.geoderma.2022.115991, 2022a. a, b
Gałka, M., Hölzer, A., Feurdean, A., Loisel, J., Teickner, H., Diaconu, A.-C., Szal, M., Broder, T., and Knorr, K.-H.: Insight into the Factors of Mountain Bog and Forest Development in the Schwarzwald Mts.: Implications for Ecological Restoration, Ecol. Indic., 140, 109039, https://doi.org/10.1016/j.ecolind.2022.109039, 2022b. a
Gallego-Sala, A. V., Charman, D. J., Brewer, S., Page, S. E., Prentice, I. C., Friedlingstein, P., Moreton, S., Amesbury, M. J., Beilman, D. W., Björck, S., Blyakharchuk, T., Bochicchio, C., Booth, R. K., Bunbury, J., Camill, P., Carless, D., Chimner, R. A., Clifford, M., Cressey, E., Courtney-Mustaphi, C., De Vleeschouwer, F., de Jong, R., Fialkiewicz-Koziel, B., Finkelstein, S. A., Garneau, M., Githumbi, E., Hribjlan, J., Holmquist, J., Hughes, P. D. M., Jones, C., Jones, M. C., Karofeld, E., Klein, E. S., Kokfelt, U., Korhola, A., Lacourse, T., Le Roux, G., Lamentowicz, M., Large, D., Lavoie, M., Loisel, J., Mackay, H., MacDonald, G. M., Makila, M., Magnan, G., Marchant, R., Marcisz, K., Martínez Cortizas, A., Massa, C., Mathijssen, P., Mauquoy, D., Mighall, T., Mitchell, F. J. G., Moss, P., Nichols, J., Oksanen, P. O., Orme, L., Packalen, M. S., Robinson, S., Roland, T. P., Sanderson, N. K., Sannel, A. B. K., Silva-Sánchez, N., Steinberg, N., Swindles, G. T., Turner, T. E., Uglow, J., Väliranta, M., van Bellen, S., van der Linden, M., van Geel, B., Wang, G., Yu, Z., Zaragoza-Castells, J., and Zhao, Y.: Latitudinal Limits to the Predicted Increase of the Peatland Carbon Sink with Warming, Nat. Clim. Change, 8, 907–913, https://doi.org/10.1038/s41558-018-0271-1, 2018. a, b
Gnatowski, T., Ostrowska-Ligęza, E., Kechavarzi, C., Kurzawski, G., and Szatyłowicz, J.: Heat Capacity of Drained Peat Soils, Appl. Sci., 12, 1579, https://doi.org/10.3390/app12031579, 2022. a, b, c
Granberg, G., Grip, H., Löfvenius, M. O., Sundh, I., Svensson, B. H., and Nilsson, M.: A Simple Model for Simulation of Water Content, Soil Frost, and Soil Temperatures in Boreal Mixed Mires, Water Resour. Res., 35, 3771–3782, https://doi.org/10.1029/1999WR900216, 1999. a, b, c
Harris, L. and Olefeldt, D.: Permafrost Thaw Causes Large Carbon Loss in Boreal Peatlands While Changes to Peat Quality Are Limited, DRYAD [data set], https://doi.org/10.5061/DRYAD.47D7WM3KK, 2023. a
Harris, L. I., Olefeldt, D., Pelletier, N., Blodau, C., Knorr, K.-H., Talbot, J., Heffernan, L., and Turetsky, M.: Permafrost Thaw Causes Large Carbon Loss in Boreal Peatlands While Changes to Peat Quality Are Limited, Glob. Change Biol., 29, gcb.16894, https://doi.org/10.1111/gcb.16894, 2023. a
Hartmann, C. and Nopmanee, S.: Global Soil Laboratory Assessment, 2018 Online Survey, Tech. rep., Food and Agriculture Organization of the United Nations, Rome, ISBN 978-92-5-131988-8, https://www.fao.org/3/ca7091en/CA7091EN.pdf (last access: 18 October 2022), 2019. a
Hayes, D., Hayes, M., and Leahy, J.: Analysis of the Lignocellulosic Components of Peat Samples with Development of near Infrared Spectroscopy Models for Rapid Quantitative Predictions, Fuel, 150, 261–268, https://doi.org/10.1016/j.fuel.2015.01.094, 2015. a
Helgeson, H. C.: Summary and Critique of the Thermodynamic Properties of Rock-Forming Minerals, Kline Geology Laboratory Yale University, New Haven, https://earth.geology.yale.edu/~ajs/1978/ajs_278A_1.pdf/1.pdf (last access: 1 April 2026), 1978. a
Helgeson, H. C., Owens, C. E., Knox, A. M., and Richard, L.: Calculation of the Standard Molal Thermodynamic Properties of Crystalline, Liquid, and Gas Organic Molecules at High Temperatures and Pressures, Geochim. Cosmochim. Ac., 62, 985–1081, https://doi.org/10.1016/S0016-7037(97)00219-6, 1998. a
Helgeson, H. C., Richard, L., McKenzie, W. F., Norton, D. L., and Schmitt, A.: A Chemical and Thermodynamic Model of Oil Generation in Hydrocarbon Source Rocks, Geochim. Cosmochim. Ac., 73, 594–695, https://doi.org/10.1016/j.gca.2008.03.004, 2009. a
Hobbie, E. A. and Werner, R. A.: Intramolecular, Compound-specific, and Bulk Carbon Isotope Patterns in C3 and C4 Plants: A Review and Synthesis, New Phytol., 161, 371–385, https://doi.org/10.1111/j.1469-8137.2004.00970.x, 2004. a
Hodgkins, S. B., Richardson, C. J., Dommain, R., Wang, H., Glaser, P. H., Verbeke, B., Winkler, B. R., Cobb, A. R., Rich, V. I., Missilmani, M., Flanagan, N., Ho, M., Hoyt, A. M., Harvey, C. F., Vining, S. R., Hough, M. A., Moore, T. R., Richard, P. J. H., De La Cruz, F. B., Toufaily, J., Hamdan, R., Cooper, W. T., and Chanton, J. P.: Tropical Peatland Carbon Storage Linked to Global Latitudinal Trends in Peat Recalcitrance, Nat. Commun., 9, 3640, https://doi.org/10.1038/s41467-018-06050-2, 2018. a, b, c
Hölzer, A. and Hölzer, A.: Silicon and Titanium in Peat Profiles as Indicators of Human Impact, The Holocene, 8, 685–696, https://doi.org/10.1191/095968398670694506, 1998. a
Hömberg, A.: Geochemische Charakterisierung von Mooren der Changbai Mountains, Bachelor thesis, Münster, Münster, 2014. a
Keeling, C. D.: The Suess Effect: 13Carbon-14Carbon Interrelations, Environ. Int., 2, 229–300, https://doi.org/10.1016/0160-4120(79)90005-9, 1979. a
Kendall, R. A.: Microbial and Substrate Decomposition Factors in Commercially Extracted Peatlands in Canada, Master's thesis, McGill University, Montréal, https://escholarship.mcgill.ca/concern/theses/gh93h442s (last access: 19 October 2021), 2020. a
Kim, S., Kramer, R. W., and Hatcher, P. G.: Graphical Method for Analysis of Ultrahigh-Resolution Broadband Mass Spectra of Natural Organic Matter, the van Krevelen Diagram, Anal. Chem., 75, 5336–5344, https://doi.org/10.1021/ac034415p, 2003. a, b
Kuhry, P. and Vitt, D. H.: Fossil Carbon/Nitrogen Ratios as a Measure of Peat Decomposition, Ecology, 77, 271–275, https://doi.org/10.2307/2265676, 1996. a
Laiho, R., Bhuiyan, R., Straková, P., Mäkiranta, P., Badorek, T., and Penttilä, T.: Modified Ingrowth Core Method plus Infrared Calibration Models for Estimating Fine Root Production in Peatlands, Plant Soil, 385, 311–327, https://doi.org/10.1007/s11104-014-2225-3, 2014. a
Lang, S. I., Cornelissen, J. H. C., Klahn, T., van Logtestijn, R. S. P., Broekman, R., Schweikert, W., and Aerts, R.: An Experimental Comparison of Chemical Traits and Litter Decomposition Rates in a Diverse Range of Subarctic Bryophyte, Lichen and Vascular Plant Species, J. Ecol., 97, 886–900, https://doi.org/10.1111/j.1365-2745.2009.01538.x, 2009. a
Langel, R. and Dyckmans, J.: A Closer Look into the Nitrogen Blank in Elemental Analyser/Isotope Ratio Mass Spectrometry Measurements, Rapid Commun. Mass Sp., 31, 2051–2055, https://doi.org/10.1002/rcm.7999, 2017. a
LaRowe, D. E. and Dick, J. M.: Calculation of the Standard Molal Thermodynamic Properties of Crystalline Peptides, Geochim. Cosmochim. Ac., 80, 70–91, https://doi.org/10.1016/j.gca.2011.11.041, 2012. a
LaRowe, D. E. and Helgeson, H. C.: Biomolecules in Hydrothermal Systems: Calculation of the Standard Molal Thermodynamic Properties of Nucleic-Acid Bases, Nucleosides, and Nucleotides at Elevated Temperatures and Pressures, Geochim. Cosmochim. Ac., 70, 4680–4724, https://doi.org/10.1016/j.gca.2006.04.010, 2006a. a
LaRowe, D. E. and Helgeson, H. C.: The Energetics of Metabolism in Hydrothermal Systems: Calculation of the Standard Molal Thermodynamic Properties of Magnesium-Complexed Adenosine Nucleotides and NAD and NADP at Elevated Temperatures and Pressures, Thermochim. Acta, 448, 82–106, https://doi.org/10.1016/j.tca.2006.06.008, 2006b. a
Lerch, T. Z., Nunan, N., Dignac, M.-F., Chenu, C., and Mariotti, A.: Variations in Microbial Isotopic Fractionation during Soil Organic Matter Decomposition, Biogeochemistry, 106, 5–21, https://doi.org/10.1007/s10533-010-9432-7, 2011. a, b
Linstrom, P.: NIST Chemistry WebBook, NIST Standard Reference Database 69, https://doi.org/10.18434/T4D303, 1997. a
Liu, H., Price, J., Rezanezhad, F., and Lennartz, B.: Centennial-scale Shifts in Hydrophysical Properties of Peat Induced by Drainage, Water Resour. Res., 56, https://doi.org/10.1029/2020WR027538, 2020. a
Loisel, J., Yu, Z., Beilman, D. W., Camill, P., Alm, J., Amesbury, M. J., Anderson, D., Andersson, S., Bochicchio, C., Barber, K., Belyea, L. R., Bunbury, J., Chambers, F. M., Charman, D. J., De Vleeschouwer, F., Fiałkiewicz-Kozieł, B., Finkelstein, S. A., Gałka, M., Garneau, M., Hammarlund, D., Hinchcliffe, W., Holmquist, J., Hughes, P., Jones, M. C., Klein, E. S., Kokfelt, U., Korhola, A., Kuhry, P., Lamarre, A., Lamentowicz, M., Large, D., Lavoie, M., MacDonald, G., Magnan, G., Mäkilä, M., Mallon, G., Mathijssen, P., Mauquoy, D., McCarroll, J., Moore, T. R., Nichols, J., O'Reilly, B., Oksanen, P., Packalen, M., Peteet, D., Richard, P. J., Robinson, S., Ronkainen, T., Rundgren, M., Sannel, A. B. K., Tarnocai, C., Thom, T., Tuittila, E.-S., Turetsky, M., Väliranta, M., van der Linden, M., van Geel, B., van Bellen, S., Vitt, D., Zhao, Y., and Zhou, W.: A Database and Synthesis of Northern Peatland Soil Properties and Holocene Carbon and Nitrogen Accumulation, The Holocene, 24, 1028–1042, https://doi.org/10.1177/0959683614538073, 2014. a, b, c, d, e
Loisel, J., van Bellen, S., Pelletier, L., Talbot, J., Hugelius, G., Karran, D., Yu, Z., Nichols, J., and Holmquist, J.: Insights and Issues with Estimating Northern Peatland Carbon Stocks and Fluxes since the Last Glacial Maximum, Earth-Sci. Rev., 165, 59–80, https://doi.org/10.1016/j.earscirev.2016.12.001, 2017. a, b
Loisel, J., Gallego-Sala, A. V., Amesbury, M. J., Magnan, G., Anshari, G., Beilman, D. W., Benavides, J. C., Blewett, J., Camill, P., Charman, D. J., Chawchai, S., Hedgpeth, A., Kleinen, T., Korhola, A., Large, D., Mansilla, C. A., Müller, J., van Bellen, S., West, J. B., Yu, Z., Bubier, J. L., Garneau, M., Moore, T., Sannel, A. B. K., Page, S., Väliranta, M., Bechtold, M., Brovkin, V., Cole, L. E. S., Chanton, J. P., Christensen, T. R., Davies, M. A., De Vleeschouwer, F., Finkelstein, S. A., Frolking, S., Gałka, M., Gandois, L., Girkin, N., Harris, L. I., Heinemeyer, A., Hoyt, A. M., Jones, M. C., Joos, F., Juutinen, S., Kaiser, K., Lacourse, T., Lamentowicz, M., Larmola, T., Leifeld, J., Lohila, A., Milner, A. M., Minkkinen, K., Moss, P., Naafs, B. D. A., Nichols, J., O'Donnell, J., Payne, R., Philben, M., Piilo, S., Quillet, A., Ratnayake, A. S., Roland, T. P., Sjögersten, S., Sonnentag, O., Swindles, G. T., Swinnen, W., Talbot, J., Treat, C., Valach, A. C., and Wu, J.: Expert Assessment of Future Vulnerability of the Global Peatland Carbon Sink, Nat. Clim. Change, 11, 70–77, https://doi.org/10.1038/s41558-020-00944-0, 2021. a
Ludwig, B., Schmilewski, G., and Terhoeven-Urselmans, T.: Use of near Infrared Spectroscopy to Predict Chemical Parameters and Phytotoxicity of Peats and Growing Media, Sci. Hortic., 109, 86–91, https://doi.org/10.1016/j.scienta.2006.02.020, 2006. a
Mahdiyasa, A. W., Large, D. J., Muljadi, B. P., Icardi, M., and Triantafyllou, S.: MPeat – A Fully Coupled Mechanical-ecohydrological Model of Peatland Development, Ecohydrology, 15, https://doi.org/10.1002/eco.2361, 2022. a
Malmer, N. and Holm, E.: Variation in the C/N-quotient of Peat in Relation to Decomposition Rate and Age Determination with 210Pb, Oikos, 43, 171, https://doi.org/10.2307/3544766, 1984. a
Masiello, C. A., Gallagher, M. E., Randerson, J. T., Deco, R. M., and Chadwick, O. A.: Evaluating Two Experimental Approaches for Measuring Ecosystem Carbon Oxidation State and Oxidative Ratio, J. Geophys. Res., 113, G03010, https://doi.org/10.1029/2007JG000534, 2008. a, b, c
Mathijssen, P. J., Gałka, M., Borken, W., and Knorr, K.-H.: Plant Communities Control Long Term Carbon Accumulation and Biogeochemical Gradients in a Patagonian Bog, Sci. Total Environ., 684, 670–681, https://doi.org/10.1016/j.scitotenv.2019.05.310, 2019. a
McBratney, A. B., Minasny, B., and Viscarra Rossel, R.: Spectral Soil Analysis and Inference Systems: A Powerful Combination for Solving the Soil Data Crisis, Geoderma, 136, 272–278, https://doi.org/10.1016/j.geoderma.2006.03.051, 2006. a, b
McTiernan, K. B., Garnett, M. H., Mauquoy, D., Ineson, P., and Coûteaux, M.-M.: Use of Near-Infrared Reflectance Spectroscopy (NIRS) in Palaeoecological Studies of Peat, The Holocene, 8, 729–740, https://doi.org/10.1191/095968398673885510, 1998. a, b
Moore, T., Blodau, C., Turunen, J., Roulet, N. T., and Richard, P. J. H.: Patterns of Nitrogen and Sulfur Accumulation and Retention in Ombrotrophic Bogs, Eastern Canada, Glob. Change Biol., 11, 356–367, https://doi.org/10.1111/j.1365-2486.2004.00882.x, 2005. a, b
Moore, T. R., Large, D., Talbot, J., Wang, M., and Riley, J. L.: The Stoichiometry of Carbon, Hydrogen, and Oxygen in Peat, J. Geophys. Res.-Biogeo., 123, 3101–3110, https://doi.org/10.1029/2018JG004574, 2018. a, b, c
Moore, T. R., Knorr, K.-H., Thompson, L., Roy, C., and Bubier, J. L.: The Effect of Long-Term Fertilization on Peat in an Ombrotrophic Bog, Geoderma, 343, 176–186, https://doi.org/10.1016/j.geoderma.2019.02.034, 2019. a
Münchberger, W.: Past and Present Carbon Dynamics in Contrasting South Patagonian Bog Ecosystems, PhD thesis, University Münster, Münster, https://repositorium.uni-muenster.de/document/miami/47b241cc-192d-4ec2-9a91-d85b7f6ca78d/diss_muenchberger.pdf (last access: 13 October 2021), 2019. a
Münchberger, W., Knorr, K.-H., Blodau, C., Pancotto, V. A., and Kleinebecker, T.: Zero to moderate methane emissions in a densely rooted, pristine Patagonian bog – biogeochemical controls as revealed from isotopic evidence, Biogeosciences, 16, 541–559, https://doi.org/10.5194/bg-16-541-2019, 2019. a
Nadelhoffer, K. J. and Fry, B.: Controls on Natural Nitrogen-15 and Carbon-13 Abundances in Forest Soil Organic Matter, Soil Sci. Soc. Am. J., 52, 1633–1640, https://doi.org/10.2136/sssaj1988.03615995005200060024x, 1988. a, b
Nichols, J. E. and Peteet, D. M.: Rapid Expansion of Northern Peatlands and Doubled Estimate of Carbon Storage, Nat. Geosci., 12, 917–921, https://doi.org/10.1038/s41561-019-0454-z, 2019. a
Nocita, M., Stevens, A., van Wesemael, B., Aitkenhead, M., Bachmann, M., Barthès, B., Ben Dor, E., Brown, D. J., Clairotte, M., Csorba, A., Dardenne, P., Demattê, J. A., Genot, V., Guerrero, C., Knadel, M., Montanarella, L., Noon, C., Ramirez-Lopez, L., Robertson, J., Sakai, H., Soriano-Disla, J. M., Shepherd, K. D., Stenberg, B., Towett, E. K., Vargas, R., and Wetterlind, J.: Soil Spectroscopy: An Alternative to Wet Chemistry for Soil Monitoring, in: Advances in Agronomy, vol. 132, 139–159, Elsevier, ISBN 978-0-12-802135-4, https://doi.org/10.1016/bs.agron.2015.02.002, 2015. a, b
Normand, A. E., Turner, B. L., Lamit, L. J., Smith, A. N., Baiser, B., Clark, M. W., Hazlett, C., Kane, E. S., Lilleskov, E., Long, J. R., Grover, S. P., and Reddy, K. R.: Organic Matter Chemistry Drives Carbon Dioxide Production of Peatlands, Geophys. Res. Lett., 48, https://doi.org/10.1029/2021GL093392, 2021. a
O'Connor, M. T., Cardenas, M. B., Ferencz, S. B., Wu, Y., Neilson, B. T., Chen, J., and Kling, G. W.: Empirical Models for Predicting Water and Heat Flow Properties of Permafrost Soils, Geophys. Res. Lett., 47, e2020GL087646, https://doi.org/10.1029/2020GL087646, 2020. a, b, c, d
Olde Venterink, H., Wassen, M. J., Verkroost, A. W. M., and De Ruiter, P. C.: Species Richness-Productivity Patterns Differ between N-, P-, and K-limited Wetlands, Ecology, 84, 2191–2199, https://doi.org/10.1890/01-0639, 2003. a, b, c
Padarian, J., Minasny, B., and McBratney, A.: Assessing the Uncertainty of Deep Learning Soil Spectral Models Using Monte Carlo Dropout, Geoderma, 425, 116063, https://doi.org/10.1016/j.geoderma.2022.116063, 2022. a
Parikh, S. J., Goyne, K. W., Margenot, A. J., Mukome, F. N., and Calderón, F. J.: Soil Chemical Insights Provided through Vibrational Spectroscopy, in: Advances in Agronomy, vol. 126, 148 pp., Elsevier, ISBN 978-0-12-800132-5, https://doi.org/10.1016/B978-0-12-800132-5.00001-8, 2014. a, b
Patel, S. A. and Erickson, L. E.: Estimation of Heats of Combustion of Biomass from Elemental Analysis Using Available Electron Concepts, Biotechnol. Bioeng., 23, 2051–2067, https://doi.org/10.1002/bit.260230910, 1981. a
Pelletier, N., Talbot, J., Olefeldt, D., Turetsky, M., Blodau, C., Sonnentag, O., and Quinton, W. L.: Influence of Holocene Permafrost Aggradation and Thaw on the Paleoecology and Carbon Storage of a Peatland Complex in Northwestern Canada, The Holocene, 27, 1391–1405, https://doi.org/10.1177/0959683617693899, 2017. a
Perez-Guaita, D., Kuligowski, J., Quintás, G., Garrigues, S., and de la Guardia, M.: Atmospheric Compensation in Fourier Transform Infrared (FT-IR) Spectra of Clinical Samples, Appl. Spectrosc., 67, 1339–1342, https://doi.org/10.1366/13-07159, 2013. a, b
Pérez-Rodríguez, M., Horák-Terra, I., Rodríguez-Lado, L., and Martínez Cortizas, A.: Modelling Mercury Accumulation in Minerogenic Peat Combining FTIR-ATR Spectroscopy and Partial Least Squares (PLS), Spectrochim. Acta A, 168, 65–72, https://doi.org/10.1016/j.saa.2016.05.052, 2016. a
Piironen, J. and Vehtari, A.: Sparsity Information and Regularization in the Horseshoe and Other Shrinkage Priors, Electron. J. Stat., 11, https://doi.org/10.1214/17-EJS1337SI, 2017a. a
Piironen, J. and Vehtari, A.: On the Hyperprior Choice for the Global Shrinkage Parameter in the Horseshoe Prior, arXiv [preprint], https://doi.org/10.48550/arXiv.1610.05559, 2017b. a, b, c
Popovic, M.: Thermodynamic Properties of Microorganisms: Determination and Analysis of Enthalpy, Entropy, and Gibbs Free Energy of Biomass, Cells and Colonies of 32 Microorganism Species, Heliyon, 5, e01950, https://doi.org/10.1016/j.heliyon.2019.e01950, 2019. a
Qiu, C., Ciais, P., Zhu, D., Guenet, B., Chang, J., Chaudhary, N., Kleinen, T., Li, X., Müller, J., Xi, Y., Zhang, W., Ballantyne, A., Brewer, S. C., Brovkin, V., Charman, D. J., Gustafson, A., Gallego-Sala, A. V., Gasser, T., Holden, J., Joos, F., Kwon, M. J., Lauerwald, R., Miller, P. A., Peng, S., Page, S., Smith, B., Stocker, B. D., Sannel, A. B. K., Salmon, E., Schurgers, G., Shurpali, N. J., Wårlind, D., and Westermann, S.: A Strong Mitigation Scenario Maintains Climate Neutrality of Northern Peatlands, One Earth, 5, 86–97, https://doi.org/10.1016/j.oneear.2021.12.008, 2022. a, b, c, d, e
R Core Team: R: A Language and Environment for Statistical Computing, Vienna, Austria, https://www.R-project.org/ (last access: 18 January 2024), 2022. a
Reuter, H., Gensel, J., Elvert, M., and Zak, D.: Infrared Spectra (FTIR) of Phragmites Australis Litter, Initial and after Anoxic Decomposition in Three Wetland Substrates, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.902069, 2019a. a
Reuter, H., Gensel, J., Elvert, M., and Zak, D.: CuO Lignin, and Bulk Decomposition Data of a 75-Day Anoxic Phragmites Australis Litter Decomposition Experiment in Soil Substrates from Three Northeast German Wetlands, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.902176, 2019b. a
Reuter, H., Gensel, J., Elvert, M., and Zak, D.: Evidence for preferential protein depolymerization in wetland soils in response to external nitrogen availability provided by a novel FTIR routine, Biogeosciences, 17, 499–514, https://doi.org/10.5194/bg-17-499-2020, 2020. a
Richard, L.: Calculation of the standard molal thermodynamic properties as a function of temperature and pressure of some geochemically important organic sulfur compounds, Geochim. Cosmochim. Ac., 65, 3827–3877, https://doi.org/10.1016/S0016-7037(01)00761-X, 2001. a
Richard, L. and Helgeson, H. C.: Calculation of the Thermodynamic Properties at Elevated Temperatures and Pressures of Saturated and Aromatic High Molecular Weight Solid and Liquid Hydrocarbons in Kerogen, Bitumen, Petroleum, and Other Organic Matter of Biogeochemical Interest, Geochim. Cosmochim. Ac., 62, 3591–3636, https://doi.org/10.1016/S0016-7037(97)00345-1, 1998. a
Rinnan, R. and Rinnan, Å.: Application of near Infrared Reflectance (NIR) and Fluorescence Spectroscopy to Analysis of Microbiological and Chemical Properties of Arctic Soil, Soil Biol. Biochem., 39, 1664–1673, https://doi.org/10.1016/j.soilbio.2007.01.022, 2007. a
Roberts, D. R., Bahn, V., Ciuti, S., Boyce, M. S., Elith, J., Guillera-Arroita, G., Hauenstein, S., Lahoz-Monfort, J. J., Schröder, B., Thuiller, W., Warton, D. I., Wintle, B. A., Hartig, F., and Dormann, C. F.: Cross-Validation Strategies for Data with Temporal, Spatial, Hierarchical, or Phylogenetic Structure, Ecography, 40, 913–929, https://doi.org/10.1111/ecog.02881, 2017. a
Schellekens, J., Bindler, R., Martínez-Cortizas, A., McClymont, E. L., Abbott, G. D., Biester, H., Pontevedra-Pombal, X., and Buurman, P.: Preferential Degradation of Polyphenols from Sphagnum – 4-Isopropenylphenol as a Proxy for Past Hydrological Conditions in Sphagnum-Dominated Peat, Geochim. Cosmochim. Ac., 150, 74–89, https://doi.org/10.1016/j.gca.2014.12.003, 2015. a
Schuster, W., Knorr, K.-H., Blodau, C., Gałka, M., Borken, W., Pancotto, V. A., and Kleinebecker, T.: Control of Carbon and Nitrogen Accumulation by Vegetation in Pristine Bogs of Southern Patagonia, Sci. Total Environ., 810, 151293, https://doi.org/10.1016/j.scitotenv.2021.151293, 2022. a
Serk, H., Nilsson, M. B., Figueira, J., Krüger, J. P., Leifeld, J., Alewell, C., and Schleucher, J.: Organo-Chemical Characterisation of Peat Decomposition Reveals Preferential Degradation of Hemicelluloses as Main Cause for Organic Matter Loss in the Acrotelm, SSRN [preprint], https://doi.org/10.2139/ssrn.4051383, 2022. a
Shock, E. L.: Hydrothermal Dehydration of Aqueous Organic Compounds, Geochim. Cosmochim. Ac., 57, 3341–3349, https://doi.org/10.1016/0016-7037(93)90542-5, 1993. a
Shotyk, W.: Peat Bog Archives of Atmospheric Metal Deposition: Geochemical Evaluation of Peat Profiles, Natural Variations in Metal Concentrations, and Metal Enrichment Factors, Environ. Rev., 4, 149–183, https://doi.org/10.1139/a96-010, 1996. a
Sivula, T., Magnusson, M., Matamoros, A. A., and Vehtari, A.: Uncertainty in Bayesian Leave-One-out Cross-Validation Based Model Comparison, arXiv [preprint], https://doi.org/10.48550/arXiv.2008.10296, 2022. a
Stan Development Team: Stan Modeling Language Users Guide and Reference Manual, version 2.36.0, https://mc-stan.org/ (last access: 3 April 2026), 2021. a
Stevens, A. and Ramirez-Lopez, L.: prospectr: Miscellaneous Functions for Processing and Sample Selection of Spectroscopic Data, Comprehensive R Archive Network (CRAN) [code], https://doi.org/10.32614/CRAN.package.prospectr, 2013. a
Straková, P., Larmola, T., Andrés, J., Ilola, N., Launiainen, P., Edwards, K., Minkkinen, K., and Laiho, R.: Quantification of Plant Root Species Composition in Peatlands Using FTIR Spectroscopy, Front. Plant Sci., 11, 597, https://doi.org/10.3389/fpls.2020.00597, 2020. a
Stuart, B. H.: Infrared Spectroscopy: Fundamentals and Applications, Analytical Techniques in the Sciences, John Wiley & Sons, Ltd, Chichester, UK, ISBN 978-0-470-01114-0 978-0-470-85428-0, https://doi.org/10.1002/0470011149, 2004. a, b
Tatzber, M., Stemmer, M., Spiegel, H., Katzlberger, C., Haberhauer, G., and Gerzabek, M. H.: An Alternative Method to Measure Carbonate in Soils by FT-IR Spectroscopy, Environ. Chem. Lett., 5, 9–12, https://doi.org/10.1007/s10311-006-0079-5, 2007. a, b
Teickner, H.: ir: Functions to Handle and Preprocess Infrared Spectra, Comprehensive R Archive Network (CRAN) [code], https://doi.org/10.32614/CRAN.package.ir, 2022. a
Teickner, H.: pmird: R interface to the Peatland Mid-infrared Database, Zenodo [code], https://doi.org/10.5281/zenodo.19397082, 2025a. a, b
Teickner, H.: irpeatmodels: Mid-infrared Prediction Models for Peat, Zenodo [code], https://doi.org/10.5281/zenodo.17187912, 2025b. a, b, c
Teickner, H. and Hodgkins, S.: irpeat 0.3.0: Functions to Analyze Mid-Infrared Spectra of Peat Samples, Zenodo [code], https://doi.org/10.5281/zenodo.17200517, 2025. a, b
Teickner, H. and Knorr, K.-H.: hklmirs: Reproducible Research Compendium for “Improving Models to Predict Holocellulose and Klason Lignin Contents for Peat Soil Organic Matter with Mid-Infrared Spectra” and “Comment on Hodgkins et al. (2018): Predicting Absolute Holocellulose and Klason Lignin Contents for Peat Remains Challenging”, Zenodo [code], https://doi.org/10.5281/zenodo.6935424, 2022a. a
Teickner, H. and Knorr, K.-H.: Improving models to predict holocellulose and Klason lignin contents for peat soil organic matter with mid-infrared spectra, SOIL, 8, 699–715, https://doi.org/10.5194/soil-8-699-2022, 2022b. a
Teickner, H. and Knorr, K.-H.: Gap-Filled Subset of the Peatland Mid-Infrared Database (1.0.0), Zenodo [data set], https://doi.org/10.5281/zenodo.17187559, 2025a. a, b
Teickner, H. and Knorr, K.-H.: Compendium of R Code and Data for “Prediction of Peat Properties from Transmission Mid-Infrared Spectra”, Zenodo [code, data set], https://doi.org/10.5281/zenodo.17209177, 2025b. a
Teickner, H., Gao, C., and Knorr, K.-H.: Reproducible Research Compendium with R Code and Data for: “Electrochemical Properties of Peat Particulate Organic Matter on a Global Scale: Relation to Peat Chemistry and Degree of Decomposition”, Zenodo [code, data set], https://doi.org/10.5281/zenodo.5792970, 2021. a, b
Teickner, H., Gao, C., and Knorr, K.-H.: Electrochemical Properties of Peat Particulate Organic Matter on a Global Scale: Relation to Peat Chemistry and Degree of Decomposition, Global Biogeochem. Cy., 36, e2021GB007160, https://doi.org/10.1029/2021GB007160, 2022. a, b, c
Teickner, H., Agethen, S., Berger, S., Boelsen, R. I., Borken, W., Bragazza, L., Broder, T., De La Cruz, F. B., Diaconu, A.-C., Dise, N. B., Drollinger, S., Estop-Aragonés, C., Gałka, M., Martí, M., Glatzel, S., Groß, J., Harris, L., Heffernan, L., Hodgkins, S. B., Hömberg-Grandjean, A., Hoppe, H., Kleinebecker, T., Knierzinger, W., Liu, H., Mathijssen, P. J., Mollmann, C., Schuster, W., Närtker, L., Olefeldt, D., Pancotto, V., Pelletier, N., Reuter, H., Robroek, B., Svensson, B., Talbot, J., Thompson, L., Worrall, F., Yu, Z.-G., and Knorr, K.-H.: Peatland Mid-Infrared Database (1.0.0), Zenodo [data set], https://doi.org/10.5281/zenodo.17092587, 2025a. a, b, c, d, e, f
Teickner, H., Agethen, S., Berger, S., Boelsen, R. I., Borken, W., Bragazza, L., Broder, T., De La Cruz, F. B., Diaconu, A.-C., Dise, N. B., Drollinger, S., Estop-Aragonés, C., Gałka, M., Martí Generó, M., Glatzel, S., Groß, J., Harris, L., Heffernan, L., Hodgkins, S. B., Hömberg-Grandjean, A., Hoppe, H., Knierzinger, W., Liu, H., Mathijssen, P. J. H., Mollmann, C., Schuster, W., Närtker, L., Olefeldt, D., Pancotto, V., Pelletier, N., Reuter, H., Robroek, B., Svensson, B., Talbot, J., Thompson, L. M., Worrall, F., Yu, Z.-G., and Knorr, K.-H.: Peatland Mid-Infrared Database 1.0.0, EarthArXiv [preprint], https://doi.org/10.31223/X51450, 2025b. a, b, c
Thornton, W.: XV. The Relation of Oxygen to the Heat of Combustion of Organic Compounds, The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science, 33, 196–203, https://doi.org/10.1080/14786440208635627, 1917. a
Treat, C. C., Jones, M. C., Brosius, L. S., Grosse, G., and Walter Anthony, K. M.: Radiocarbon dates of peatland initiation across the northern high latitudes, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.864101, 2016. a, b
Turunen, J., Roulet, N. T., Moore, T. R., and Richard, P. J. H.: Nitrogen Deposition and Increased Carbon Accumulation in Ombrotrophic Peatlands in Eastern Canada: N Deposition and Peat Accumulation, Global Biogeochem. Cy., 18, https://doi.org/10.1029/2003GB002154, 2004. a
Vehtari, A., Gelman, A., and Gabry, J.: Practical Bayesian Model Evaluation Using Leave-One-out Cross-Validation and WAIC, Stat. Comput., 27, 1413–1432, https://doi.org/10.1007/s11222-016-9696-4, 2017. a
Vehtari, A., Gabry, J., Magnusson, M., Yao, Y., Bürkner, P.-C., Paananen, T., Gelman, A., Goodrich, B., and Piironen, J.: loo: Efficient Leave-One-out Cross-Validation and WAIC for Bayesian Models, Comprehensive R Archive Network (CRAN) [code], https://doi.org/10.32614/CRAN.package.loo, 2019. a
Vehtari, A., Gelman, A., Simpson, D., Carpenter, B., and Bürkner, P.-C.: Rank-Normalization, Folding, and Localization: An Improved
Viscarra Rossel, R. A., Jeon, Y. S., Odeh, I. O. A., and McBratney, A. B.: Using a Legacy Soil Sample to Develop a Mid-IR Spectral Library, Soil Res., 46, https://doi.org/10.1071/SR07099, 2008. a, b
Viscarra Rossel, R. A., Shen, Z., Ramirez Lopez, L., Behrens, T., Shi, Z., Wetterlind, J., Sudduth, K. A., Stenberg, B., Guerrero, C., Gholizadeh, A., Ben-Dor, E., St Luce, M., and Orellano, C.: An Imperative for Soil Spectroscopic Modelling Is to Think Global but Fit Local with Transfer Learning, Earth-Sci. Rev., 254, 104797, https://doi.org/10.1016/j.earscirev.2024.104797, 2024. a
Wadoux, A. M.-C., Malone, B., Minasny, B., Fajardo, M., and McBratney, A. B.: Soil Spectral Inference with R: Analysing Digital Soil Spectra Using the R Programming Environment, Progress in Soil Science, Springer International Publishing, Cham, ISBN 978-3-030-64896-1, https://doi.org/10.1007/978-3-030-64896-1, 2021. a, b, c, d, e
Wagman, D. D., Evans, W. H., Parker, V. B., Schumm, R. H., and Halow, I.: The NBS Tables of Chemical Thermodynamic Properties. Selected Values for Inorganic and C1 and C2 Organic Substances in SI Units, Tech. rep., National Bureau of Standards, Washington D.C., https://srd.nist.gov/JPCRD/jpcrdS2Vol11.pdf (last access: 14 November 2022), 1982. a
Wallace, W. E. and NIST Mass Spectrometry Data Center: Infrared Spectra, in: NIST Chemistry WebBook, NIST Standard Reference Database 69, National Institute of Standards and Technology, Gaithersburg MD, https://doi.org/10.18434/T4D303, 1997. a
Wang, G., Ju, Y., Yan, Z., and Li, Q.: Pore Structure Characteristics of Coal-Bearing Shale Using Fluid Invasion Methods: A Case Study in the Huainan–Huaibei Coalfield in China, Marine and Petroleum Geology, 62, 1–13, https://doi.org/10.1016/j.marpetgeo.2015.01.001, 2015a. a
Wang, M. and Moore, T. R.: Carbon, Nitrogen, Phosphorus, and Potassium Stoichiometry in an Ombrotrophic Peatland Reflects Plant Functional Type, Ecosystems, 17, 673–684, https://doi.org/10.1007/s10021-014-9752-x, 2014. a, b, c
Wang, M., Moore, T. R., Talbot, J., and Riley, J. L.: The Stoichiometry of Carbon and Nutrients in Peat Formation: C and Nutrients in Peat, Global Biogeochem. Cy., 29, 113–121, https://doi.org/10.1002/2014GB005000, 2015b. a
Waughman, G. J.: Chemical Aspects of the Ecology of Some South German Peatlands, J. Ecol., 68, 1025, https://doi.org/10.2307/2259473, 1980. a
Wieder, R. K.: Element Stoichiometry and Nutrient Limitation in Bog Plant and Lichen Species, Biogeochemistry, 160, 355–379, https://doi.org/10.1007/s10533-022-00968-y, 2022. a, b, c, d
Wieder, R. K., Vile, M. A., Albright, C. M., Scott, K. D., Vitt, D. H., Quinn, J. C., and Burke-Scoll, M.: Effects of Altered Atmospheric Nutrient Deposition from Alberta Oil Sands Development on Sphagnum Fuscum Growth and C, N and S Accumulation in Peat, Biogeochemistry, 129, 1–19, https://doi.org/10.1007/s10533-016-0216-6, 2016. 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, https://doi.org/10.1007/BF00333212, 1996. a, b, c
Worrall, F.: Sulphur Constraints on the Carbon Cycle of a Blanket Bog Peatland, Durham University Research Data Repository [data set], https://doi.org/10.15128/R2PK02C9794, 2021. a
Worrall, F., Moody, C. S., Clay, G. D., Burt, T. P., Kettridge, N., and Rose, R.: Thermodynamic Control of the Carbon Budget of a Peatland, J. Geophys. Res.-Biogeo., 123, 1863–1878, https://doi.org/10.1029/2017JG003996, 2018. a
Xia, Z., Zheng, Y., Stelling, J. M., Loisel, J., Huang, Y., and Yu, Z.: Environmental Controls on the Carbon and Water (H and O) Isotopes in Peatland Sphagnum Mosses, Geochim. Cosmochim. Ac., 277, 265–284, https://doi.org/10.1016/j.gca.2020.03.034, 2020. a, b
Yu, Z., Campbell, I. D., Vitt, D. H., and Apps, M. J.: Modelling Long-Term Peatland Dynamics. I. Concepts, Review, and Proposed Design, Ecol. Model., 145, 197–210, https://doi.org/10.1016/S0304-3800(01)00391-X, 2001. a
Yu, Z. C.: Northern peatland carbon stocks and dynamics: a review, Biogeosciences, 9, 4071–4085, https://doi.org/10.5194/bg-9-4071-2012, 2012. a
Zaccone, C., Plaza, C., Ciavatta, C., Miano, T. M., and Shotyk, W.: Advances in the Determination of Humification Degree in Peat since Achard (1786): Applications in Geochemical and Paleoenvironmental Studies, Earth-Sci. Rev., 185, 163–178, https://doi.org/10.1016/j.earscirev.2018.05.017, 2018. a, b, c
Zhang, L., Carpenter, B., Gelman, A., and Vehtari, A.: Pathfinder: Parallel Quasi-Newton Variational Inference, J. Mach. Learn. Res., 23, 1–49, 2022. a
Short summary
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.
We developed models that predict physical and chemical peat properties from mid-infrared spectra...
