Gap-filled subset of the Peatland Mid-Infrared Database (1.0.0)

Introduction This is a gap-filled subset of the Peatland Mid-Infrared Database (1.0.0) (pmird database) stored in the rds format from the R programming language. Measurements for some peat properties were gap-filled using mid-infrared spectra (MIRS) prediction models described in Teickner and Knorr (2025) or calculated from element contents or bulk densities using auxiliary models. Format File irp_pmird_gap_filled.rds contains a list with the following elements: meta: A data frame with a row for each record (id_measurement) in the pmird database for which attributes were gap-filled and three columns: id_measurement, id_sample, id_measurement. Values of these columns identify unique records in the pmird database. The remaining elements are all data frames with a row for each row in meta and each column representing a peat property. yhat: A data frame with gap-filled values predicted from the MIRS prediction models. For the meaning of the variables, please see Teickner and Knorr (2025) and the documentation of the prediction models in the R packages irpeatmodels (Teickner 2025a) and irpeat (Teickner 2025b). yhat_auxilliary: A data frame with gap-filled values computed without MIRS prediction models. Gap-filled values are available for the following peat properties: C_to_N_3 (C/N), O_to_C_3 (O/C), H_to_C_3 (H/C), nosc_2 (nominal oxidation state of carbon, NOSC): Values are computed from element contents measured with elemental analyzers. dgf0_3 (standard Gibbs free enrgy of formation): Values are computed from element contents measured with elemental analyzers with auxiliary models as described in Teickner and Knorr (2025). volume_fraction_solids_1 (volume fraction of solids), non_macroporosity_1 (volume fraction of non-macropores), macroporosity_1 (volume fraction of macropores), saturated_hydraulic_conductivity_1 (saturated hydraulic conductivity), dry_thermal_conductivity_1 (dry thermal conductivity): Values are estimated with pedotransfer functions described in Teickner and Knorr (2025) from bulk density measurements. specific_heat_capacity_1 (specific heat capacity): Values are estimated with a pedotransfer function described in Teickner and Knorr (2025) from N content measurements. is_in_training_pd: A data frame with a logical value for each entry indicating whether the MIRS used for gap-filling of values in yhat is within the training prediction domain of the respective MIRS prediction model (TRUE) or not (FALSE). For the definition of training prediction domain, see Teickner and Knorr (2025). is_in_testing_pd: A data frame with a logical value for each entry indicating whether the MIRS used for gap-filling of values in yhat is within the testing prediction domain of the respective MIRS prediction model (TRUE) or not (FALSE). For the definition of training prediction domain, see Teickner and Knorr (2025). Usage notes To load the data within an R session, the following R packages need to be installed: tibble, posterior, and units. The rds file containing the data can be loaded as follows: d <- readRDS(file = file, refhook = \(x) new.env()) Here, file is the path to the rds file. The columns in yhat and yhat_auxilliary are rvar objects from the posterior package (https://mc-stan.org/posterior/articles/rvar.html). Data sources Data in the database were derived from the following sources: De la Cruz, Osborne, and Barlaz (2016), Hodgkins et al. (2018), Knierzinger et al. (2020), Knierzinger (2020), Münchberger (2019), Münchberger et al. (2019), Schuster et al. (2022), Drollinger, Kuzyakov, and Glatzel (2019), Drollinger et al. (2020), Agethen and Knorr (2018), Kendall (2020), L. I. Harris et al. (2023), L. Harris and Olefeldt (2023), Pelletier et al. (2017), Teickner, Gao, and Knorr (2021), Teickner, Gao, and Knorr (2022), Heffernan (2019), Heffernan et al. (2020), Broder et al. (2012), Anzenhofer (2014, unpublished), Mathijssen et al. (2019), Wagner (2013), Hömberg (2014), Berger et al. (2017), Berger et al. (2018), T. R. Moore et al. (2019), Diaconu et al. (2020), Gałka, Hölzer, et al. (2022), Gałka, Diaconu, et al. (2022), L. I. Harris et al. (2018), L. I. Harris et al. (2019), Boothroyd et al. (2021), Worrall (2021), Reuter et al. (2019b), Reuter et al. (2019a), Reuter et al. (2020), T. Moore et al. (2005), Turunen et al. (2004). Acknowledgements Development of this database was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) grant no. KN 929/23-1 to Klaus-Holger Knorr and grant no. PE 1632/18-1 to Edzer Pebesma. References Agethen, Svenja, and Klaus-Holger Knorr. 2018. “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 Biology and Biochemistry 117: 139–52. https://doi.org/10.1016/j.soilbio.2017.11.020. Anzenhofer, Regina. 2014, unpublished. “Biogeochemical Characterization of Peat Profiles Along a Vegetation Gradient in an Ombrotrophic Bog, Patagonia.” Master’s thesis. Berger, Sina, Gerhard Gebauer, Christian Blodau, and Klaus-Holger Knorr. 2017. “Peatlands in a Eutrophic World – Assessing the State of a Poor Fen-Bog Transition in Southern Ontario, Canada, After Long Term Nutrient Input and Altered Hydrological Conditions.” Soil Biology and Biochemistry 114 (November): 131–44. https://doi.org/10.1016/j.soilbio.2017.07.011. Berger, Sina, Leandra S. E. Praetzel, Marie Goebel, Christian Blodau, and Klaus-Holger Knorr. 2018. “Differential Response of Carbon Cycling to Long-Term Nutrient Input and Altered Hydrological Conditions in a Continental Canadian Peatland.” Biogeosciences 15 (3): 885–903. https://doi.org/10.5194/bg-15-885-2018. Boothroyd, I. M., F. Worrall, C. S. Moody, G. D. Clay, G. D. Abbott, and R. Rose. 2021. “Sulfur Constraints on the Carbon Cycle of a Blanket Bog Peatland.” Journal of Geophysical Research: Biogeosciences 126 (8). https://doi.org/10.1029/2021JG006435. Broder, T., C. Blodau, H. Biester, and K. H. Knorr. 2012. “Peat Decomposition Records in Three Pristine Ombrotrophic Bogs in Southern Patagonia.” Biogeosciences 9 (4): 1479–91. https://doi.org/10.5194/bg-9-1479-2012. De la Cruz, Florentino B., Jason Osborne, and Morton A. Barlaz. 2016. “Determination of Sources of Organic Matter in Solid Waste by Analysis of Phenolic Copper Oxide Oxidation Products of Lignin.” Journal of Environmental Engineering 142 (2): 04015076. https://doi.org/10.1061/(ASCE)EE.1943-7870.0001038. Diaconu, Andrei-Cosmin, Ioan Tanţău, Klaus-Holger Knorr, Werner Borken, Angelica Feurdean, Andrei Panait, and Mariusz Gałka. 2020. “A Multi-Proxy Analysis of Hydroclimate Trends in an Ombrotrophic Bog over the Last Millennium in the Eastern Carpathians of Romania.” Palaeogeography, Palaeoclimatology, Palaeoecology 538 (January): 109390. https://doi.org/10.1016/j.palaeo.2019.109390. Drollinger, Simon, Klaus-Holger Knorr, Wolfgang Knierzinger, and Stephan Glatzel. 2020. “Peat Decomposition Proxies of Alpine Bogs Along a Degradation Gradient.” Geoderma 369 (June): 114331. https://doi.org/10.1016/j.geoderma.2020.114331. Drollinger, Simon, Yakov Kuzyakov, and Stephan Glatzel. 2019. “Effects of Peat Decomposition on 13C and 15N Depth Profiles of Alpine Bogs.” CATENA 178 (July): 1–10. https://doi.org/10.1016/j.catena.2019.02.027. Gałka, Mariusz, Andrei-Cosmin Diaconu, Angelica Feurdean, Julie Loisel, Henning Teickner, Tanja Broder, and Klaus-Holger Knorr. 2022. “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 (October): 115991. https://doi.org/10.1016/j.geoderma.2022.115991. Gałka, Mariusz, Adam Hölzer, Angelica Feurdean, Julie Loisel, Henning Teickner, Andrei-Cosmin Diaconu, Marta Szal, Tanja Broder, and Klaus-Holger Knorr. 2022. “Insight into the Factors of Mountain Bog and Forest Development in the Schwarzwald Mts.: Implications for Ecological Restoration.” Ecological Indicators 140 (July): 109039. https://doi.org/10.1016/j.ecolind.2022.109039. Harris, Lorna I., Tim R. Moore, Nigel T. Roulet, and Andrew J. Pinsonneault. 2018. “Lichens: A Limit to Peat Growth?” Edited by John Lee. Journal of Ecology 106 (6): 2301–19. https://doi.org/10.1111/1365-2745.12975. ———. 2019. “Data from: Lichens: A Limit to Peat Growth?” Data. https://doi.org/10.5061/dryad.s136dc8. Harris, Lorna I., David Olefeldt, Nicolas Pelletier, Christian Blodau, Klaus-Holger Knorr, Julie Talbot, Liam Heffernan, and Merritt Turetsky. 2023. “Permafrost Thaw Causes Large Carbon Loss in Boreal Peatlands While Changes to Peat Quality Are Limited.” Global Change Biology, August, gcb.16894. https://doi.org/10.1111/gcb.16894. Harris, Lorna, and David Olefeldt. 2023. “Permafrost Thaw Causes Large Carbon Loss in Boreal Peatlands While Changes to Peat Quality Are Limited.” Dryad. https://doi.org/10.5061/DRYAD.47D7WM3KK. Heffernan, Liam. 2019. “Peat Carbon, δ 14C, Macrofossil, and Humification Data from a Thawing Permafrost Peatland in Western Canada.” UAL Dataverse. https://doi.org/10.7939/DVN/MKM0ZE. Heffernan, Liam, Cristian Estop-Aragonés, Klaus-Holger Knorr, Julie Talbot, and David Olefeldt. 2020. “Long-Term Impacts of Permafrost Thaw on Carbon Storage in Peatlands: Deep Losses Offset by Surficial Accumulation.” Journal of Geophysical Research: Biogeosciences 125 (3). https://doi.org/10.1029/2019JG005501. Hodgkins, Suzanne B., Curtis J. Richardson, René Dommain, Hongjun Wang, Paul H. Glaser, Brittany Verbeke, B. Rose Winkler, et al. 2018. “Tropical Peatland Carbon Storage Linked to Global Latitudinal Trends in Peat Recalcitrance.” Nature Communications 9 (1): 3640. https://doi.org/10.1038/s41467-018-06050-2. Hömberg, Annkathrin. 2014. “Geochemische Charakterisierung von Mooren der Changbai Mountains.” {Bachelor thesis}, Münster: Münster. Kendall, Rachel Anne. 2020. “Microbial and Substrate D

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