Articles | Volume 7, issue 4
https://doi.org/10.5194/gmd-7-1519-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-7-1519-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model experiment description paper
| 
24 Jul 2014
Model experiment description paper |
| 24 Jul 2014
Comparing microbial and chemical kinetics for modelling soil organic carbon decomposition using the DecoChem v1.0 and DecoBio v1.0 models
G. Xenakis
School of GeoSciences, University of Edinburgh, Crew Building, The King's Buildings, West Mains Road, Edinburgh, Midlothian, EH9 3JN, UK
now at: Forest Research, Northern Research Station, Roslin, Midlothian, EH25 9SY, UK
M. Williams
School of GeoSciences, University of Edinburgh, Crew Building, The King's Buildings, West Mains Road, Edinburgh, Midlothian, EH9 3JN, UK
Related authors
Sirwan Yamulki, Jack Forster, Georgios Xenakis, Adam Ash, Jacqui Brunt, Mike Perks, and James I. L. Morison
Biogeosciences, 18, 4227–4241, https://doi.org/10.5194/bg-18-4227-2021, https://doi.org/10.5194/bg-18-4227-2021, 2021
Short summary
Short summary
The effect of clear-felling on soil greenhouse gas (GHG) fluxes was assessed in a Sitka spruce forest. Measurements over 4 years showed that CO2, CH4, and N2O fluxes responded differently to clear-felling due to significant changes in soil biotic and abiotic factors and showed large variations between years. Over 3 years since felling, the soil GHG flux was reduced by 45% due to a much larger reduction in CO2 efflux than increases in N2O (up to 20%) and CH4 (changed from sink to source) fluxes.
Tim J. Green, David T. Milodowski, T. Luke Smallman, Annikki Mäkelä, and Mathew Williams
EGUsphere, https://doi.org/10.5194/egusphere-2026-2222, https://doi.org/10.5194/egusphere-2026-2222, 2026
Short summary
Short summary
Widely used satellite-based products of leaf area index (LAI) used in carbon cycle studies consistently show unrealistically high seasonality over northern evergreen needleleaf forests. This study uses a model-data fusion approach to show how these biases adversely affect carbon cycle model results by comparing outputs against a calibration that includes leaf lifespan data and summer-only LAI. Results highlight the urgent need for modelling studies and LAI producers to address these biases.
Mathew Williams, David T. Milodowski, T. Luke Smallman, Kyle G. Dexter, Gabi C. Hegerl, Iain M. McNicol, Michael O'Sullivan, Carla M. Roesch, Casey M. Ryan, Stephen Sitch, and Aude Valade
Biogeosciences, 22, 1597–1614, https://doi.org/10.5194/bg-22-1597-2025, https://doi.org/10.5194/bg-22-1597-2025, 2025
Short summary
Short summary
Southern African woodlands are important in both regional and global carbon cycles. A new carbon analysis created by combining satellite data with ecosystem modelling shows that the region has a neutral C balance overall but with important spatial variations. Patterns of biomass and C balance across the region are the outcome of climate controls on production and vegetation–fire interactions, which determine the mortality of vegetation and spatial variations in vegetation function.
Marcos B. Sanches, Manoel Cardoso, Celso von Randow, Chris Jones, and Mathew Williams
EGUsphere, https://doi.org/10.5194/egusphere-2025-942, https://doi.org/10.5194/egusphere-2025-942, 2025
Preprint archived
Short summary
Short summary
This study examines South America's role in the global carbon cycle using flux and stock analyses from CMIP6 Earth System Models. We discuss the continent’s relevance, model-observation agreement, and the impacts of dry and wet years on major biomes. Additionally, we assess model results indicating that parts of South America could shift from carbon sinks to emitters, significantly affecting the global carbon balance.
Xiaoran Zhu, Dong Chen, Maruko Kogure, Elizabeth Hoy, Logan T. Berner, Amy L. Breen, Abhishek Chatterjee, Scott J. Davidson, Gerald V. Frost, Teresa N. Hollingsworth, Go Iwahana, Randi R. Jandt, Anja N. Kade, Tatiana V. Loboda, Matt J. Macander, Michelle Mack, Charles E. Miller, Eric A. Miller, Susan M. Natali, Martha K. Raynolds, Adrian V. Rocha, Shiro Tsuyuzaki, Craig E. Tweedie, Donald A. Walker, Mathew Williams, Xin Xu, Yingtong Zhang, Nancy French, and Scott Goetz
Earth Syst. Sci. Data, 16, 3687–3703, https://doi.org/10.5194/essd-16-3687-2024, https://doi.org/10.5194/essd-16-3687-2024, 2024
Short summary
Short summary
The Arctic tundra is experiencing widespread physical and biological changes, largely in response to warming, yet scientific understanding of tundra ecology and change remains limited due to relatively limited accessibility and studies compared to other terrestrial biomes. To support synthesis research and inform future studies, we created the Synthesized Alaskan Tundra Field Dataset (SATFiD), which brings together field datasets and includes vegetation, active-layer, and fire properties.
Luana S. Basso, Chris Wilson, Martyn P. Chipperfield, Graciela Tejada, Henrique L. G. Cassol, Egídio Arai, Mathew Williams, T. Luke Smallman, Wouter Peters, Stijn Naus, John B. Miller, and Manuel Gloor
Atmos. Chem. Phys., 23, 9685–9723, https://doi.org/10.5194/acp-23-9685-2023, https://doi.org/10.5194/acp-23-9685-2023, 2023
Short summary
Short summary
The Amazon’s carbon balance may have changed due to forest degradation, deforestation and warmer climate. We used an atmospheric model and atmospheric CO2 observations to quantify Amazonian carbon emissions (2010–2018). The region was a small carbon source to the atmosphere, mostly due to fire emissions. Forest uptake compensated for ~ 50 % of the fire emissions, meaning that the remaining forest is still a small carbon sink. We found no clear evidence of weakening carbon uptake over the period.
David T. Milodowski, T. Luke Smallman, and Mathew Williams
Biogeosciences, 20, 3301–3327, https://doi.org/10.5194/bg-20-3301-2023, https://doi.org/10.5194/bg-20-3301-2023, 2023
Short summary
Short summary
Model–data fusion (MDF) allows us to combine ecosystem models with Earth observation data. Fragmented landscapes, with a mosaic of contrasting ecosystems, pose a challenge for MDF. We develop a novel MDF framework to estimate the carbon balance of fragmented landscapes and show the importance of accounting for ecosystem heterogeneity to prevent scale-dependent bias in estimated carbon fluxes, disturbance fluxes in particular, and to improve ecological fidelity of the calibrated models.
Vasileios Myrgiotis, Thomas Luke Smallman, and Mathew Williams
Biogeosciences, 19, 4147–4170, https://doi.org/10.5194/bg-19-4147-2022, https://doi.org/10.5194/bg-19-4147-2022, 2022
Short summary
Short summary
This study shows that livestock grazing and grass cutting can determine whether a grassland is adding (source) or removing (sink) carbon (C) to/from the atmosphere. The annual C balance of 1855 managed grassland fields in Great Britain was quantified for 2017–2018 using process modelling and earth observation data. The examined fields were, on average, small C sinks, but the summer drought of 2018 led to a 9-fold increase in the number of fields that became C sources in 2018 compared to 2017.
Yan Yang, A. Anthony Bloom, Shuang Ma, Paul Levine, Alexander Norton, Nicholas C. Parazoo, John T. Reager, John Worden, Gregory R. Quetin, T. Luke Smallman, Mathew Williams, Liang Xu, and Sassan Saatchi
Geosci. Model Dev., 15, 1789–1802, https://doi.org/10.5194/gmd-15-1789-2022, https://doi.org/10.5194/gmd-15-1789-2022, 2022
Short summary
Short summary
Global carbon and water have large uncertainties that are hard to quantify in current regional and global models. Field observations provide opportunities for better calibration and validation of current modeling of carbon and water. With the unique structure of CARDAMOM, we have utilized the data assimilation capability and designed the benchmarking framework by using field observations in modeling. Results show that data assimilation improves model performance in different aspects.
Stephanie G. Stettz, Nicholas C. Parazoo, A. Anthony Bloom, Peter D. Blanken, David R. Bowling, Sean P. Burns, Cédric Bacour, Fabienne Maignan, Brett Raczka, Alexander J. Norton, Ian Baker, Mathew Williams, Mingjie Shi, Yongguang Zhang, and Bo Qiu
Biogeosciences, 19, 541–558, https://doi.org/10.5194/bg-19-541-2022, https://doi.org/10.5194/bg-19-541-2022, 2022
Short summary
Short summary
Uncertainty in the response of photosynthesis to temperature poses a major challenge to predicting the response of forests to climate change. In this paper, we study how photosynthesis in a mountainous evergreen forest is limited by temperature. This study highlights that cold temperature is a key factor that controls spring photosynthesis. Including the cold-temperature limitation in an ecosystem model improved its ability to simulate spring photosynthesis.
Thomas Luke Smallman, David Thomas Milodowski, Eráclito Sousa Neto, Gerbrand Koren, Jean Ometto, and Mathew Williams
Earth Syst. Dynam., 12, 1191–1237, https://doi.org/10.5194/esd-12-1191-2021, https://doi.org/10.5194/esd-12-1191-2021, 2021
Short summary
Short summary
Our study provides a novel assessment of model parameter, structure and climate change scenario uncertainty contribution to future predictions of the Brazilian terrestrial carbon stocks to 2100. We calibrated (2001–2017) five models of the terrestrial C cycle of varied structure. The calibrated models were then projected to 2100 under multiple climate change scenarios. Parameter uncertainty dominates overall uncertainty, being ~ 40 times that of either model structure or climate change scenario.
Sirwan Yamulki, Jack Forster, Georgios Xenakis, Adam Ash, Jacqui Brunt, Mike Perks, and James I. L. Morison
Biogeosciences, 18, 4227–4241, https://doi.org/10.5194/bg-18-4227-2021, https://doi.org/10.5194/bg-18-4227-2021, 2021
Short summary
Short summary
The effect of clear-felling on soil greenhouse gas (GHG) fluxes was assessed in a Sitka spruce forest. Measurements over 4 years showed that CO2, CH4, and N2O fluxes responded differently to clear-felling due to significant changes in soil biotic and abiotic factors and showed large variations between years. Over 3 years since felling, the soil GHG flux was reduced by 45% due to a much larger reduction in CO2 efflux than increases in N2O (up to 20%) and CH4 (changed from sink to source) fluxes.
Cited articles
Allison, S. D., Wallenstein, M. D., and Bradford, M. A.: Soil-carbon response to warming dependent on microbial physiology, Nat. Geosci., 3, 336–340, 2010.
Blagodatsky, S. A., Blagodatskaya, E., Yuyukina, T., and Kuzyakov, Y.: Model of apparent and real priming effects: Linking microbial activity with soil organic matter decomposition, Soil Biol. Biochem., 42, 1275–1283, 2010.
Blagodatsky, S. A., Rüdiger, G., Kiese, R., Werner, C., and Butterbach-Bahl, K.: Modelling of microbial carbon and nitrogen turnover in soil with special emphasis on N-trace gases emission, Plant Soil, 346, 297–330, 2011.
Blagodatsky, S. A., Yevdokimov, I. V., Larionova, A. A., and Richter, J.: Microbial growth in soil and nitrogen turnover: Model calibration with laboratory data, Soil Biol. Biochem., 13, 1757–1764, 1998.
Chapin, F., McKendrick, J., and Johnson, D.: Seasonal changes in carbon fractions in Alaskan tundra plants of differing growth form: implications for herbivory, J. Ecol., 74, 707–731, 1986.
Coleman, K., Jenkinson, D., Crocker, G., Grace, P., Klír, J., Körchens, M., Poulton, P., and Richter, D.: Simulating trends in soil organic carbon in long-term experiments using RothC-26.3, Geoderma, 81, 29–44, 1997.
Fenner, N. and Freeman, C.: Drought-induced carbon loss in peatlands, Nat. Geosci., 4, 895–900, 2011.
Frey, S. D., Lee, J., Melillo, J. M., and Six, J.: The temperature response of soil microbial efficiency and its feedback to climate, Nature Climate Change, 3, 395–398, 2013.
Hartley, I. P., Garnett, M. H., Sommerkorn, M., Hopkins, D. W., Fletcher, B. J., Sloan, V. L., Phoenix, G. K., and Wookey, P. A.: A potential loss of carbon associated with great plant growth in the European Arctic, Nature Climate Change, 2, 875–879, 2012.
Ise, T., Dunn, A. L., Wofsy, S. C., and Moorcroft, P. R.: High sensitivity of peat decomposition to climate change through water-table feedback, Nat. Geosci., 1, 763–766, 2008.
Jenkinson, D. and Rayner, J.: The turnover of soil organic matter in some of the Rothamsted classical experiments, Soil Sci., 123, 298–305, 1977.
Jorgenson, T., Romanovsky, V., Jarden, J., Shur, Y., O'Donnel, J., Schuur, E., Kanavskiy, M., and Marchenko, S.: Resilience and vulnerability of permafrost to climate change, Can. J. Forest Res., 40, 1219–1236, 2010.
Koven, C., Ringeval, B., Friedlingstein, P. Ciais, P., Cadule, P., Khvorostyanov, D., Krinner, G., and Tamocai, C.: Permafrost carbon-climate feedbacks accelerate global warming, P. Natl. Acad. Sci., 108, 14769–14774, 2011.
Li, C., Frolking, S., and Frolking, T.: A model of nitrous oxide evolution from soil driven by rainfall events: 1. Model structure and sensitivity, J. Geophys. Res., 97, 9759–9776, 1992.
Li, C., Frolking, S., Crocker, G., Grace, P., Klír, J., Körchens, M., and Poulton, P.: Simulating trends in soil organic carbon in long-term experiments using the DNDC model, Geoderma, 81, 45–60, 1997.
Liski, J., Palosuo, T., Peltoniemi, M., and Sievänen: Carbon and decomposition model Yasso for forest soils, Ecol. Model., 189, 168–182, 2005.
Luo, Y., Wan, S., Hui, D., and Wallace, L.: Acclimatization of soil respiration to warming in a tall grass prairie, Nature, 413, 622–625, 2001.
Mahecha, M. D., Reichesten, M., Carvalhais, N., Lasslope, G., Lange, H., Seneviratne, S. I., Vargas, R., Ammann, C., Altaf Arrain, M., Cescatti, A., Janssens, I. A. Migliavacca, M., Montagnani, L., and Richardson, A. D.: Global convergence in the temperature sensitivity of respiration at ecosystem level, Science, 329, 838–840, 2010.
McGuire, D., Anderson, L., Christensen, T., Dallimore, S., Guo, L., Hayes, D., Heimann, M., Lorenson, T., MacDonald, R., and Roulet, N.: Sensitivity of the carbon cycle in the Arctic to climate change, Ecol. Monogr., 79, 523–555, 2009.
Melillo, J. M., Steudler, P. A., Aber, J. D., Newkirk, K., Lux, H., Bowles, F. P., Catricala, C., Magill, A., Ahrens, T., and Morrisseau, S.: Soil warming and carbon-cycle feedbacks to the climate system, Science, 298, 2173–2176, 2002.
Metherell, A., Harding, L., Cole, C., and Parton, W.: CENTURY soil organic matter model environment. Technical documentation. Agroecosystem version .0, Tech. rep., Great Plains System Research Unit, 1993.
Panikov, N. S.: Microbial growth kinetics, Springer, 1995.
Parton, W., Steward, J., and Cole, C.: Dynamics of C, N, P and S in grassland soils: a model., Biogeochemistry, 5, 109–131, 1988.
Rogers, M., Sullivan, P., and Welker, J.: Evidence of nonlinearity in the response of net ecosystem CO2 exchange to increasing levels of winter snow depth in the high Arctic of Northwest Greenland, Arct. Antarct. Alp. Res., 43, 95–106, 2011.
Sanderson, M., Hemming, D., and Betts, R.: Regional temperature and precipitation changes under high-end (≥ 4 °C) global warming, Philos. T. Roy. Soc., 369, 85–98, 2011.
Schädel, C., Luo, Y., Evans, D. R., Fei, S., and Schaeffer, S. M.: Separating soil CO2 efflux into C-pool-specific decay rates via inverse analysis of soil incubation data, Oecologia, 171, 721–732, 2013.
Schmidt, M., Torn, M., Abiven, S., Dittmar, T., Guggenberger, G., Janssens, I., Kleber, M., Kögel-Knabner, I., Lehmann, J., Manning, D., Nannipieri, P., Rasse, D. P., Weiner, S., and Trumbore, E.: Persistence of soil organic matter as an ecosystem property, Nature, 478, 49–56, 2011.
Sloan, V. L., Benjemin, J. F., Press, M. C., Williams, M., and Phoenix, G. K.: Leaf and root carbon stocks and turnover are coupled across multiple Arctic ecosystems, Glob. Change Biol., 19, 3668–3676, 2013.
Smith, J., Gottschalk, P., Bellarby, J., Chapman, S., Lilly, A., Towers, W., Bell, J., Coleman, K., Nayak, D., Richards, M., Hillier, J., Flynn, H., Wattenbach, M., Aitkenhead, M., Yeluripati, J., Farmer, J., Milne, R., Thomson, M., Evans, C., Whitmore, A., Falloon, P., and Smith, P.: Estimating changes in Scottish soil carbon stocks using ECOSSE. I. Model description and uncertainties, Clim. Res., 45, 179–192, 2010.
Smith, P., Smith, J., Flynn, H., Killham, K., Rangel-Castro, I., Foereid, B., Aitkenhead, M., Chapman, S., Towers, W., Bell, J., Lumsdon, D., Milne, R., Thomson, A., Simmons, I., Skiba, U., Reynolds, B., Evans, C., Frogbrook, Z., Bradley, I., Whitmore, A., and Falloon, P.: ECOSSE: Estimating carbon in organic soils – Sequestration and emissions, Final Report, Tech. rep., Scottish Executive, 2007.
Street, L. E., Subke, J. A., Sommerkom, M., Sloan, V., Ducrotoy, H., Phoenix, G. K., and Williams, M.: The role of mosses in carbon uptake and partitioning in Arctic vegetation, New Phytol., 199, 163–175, 2013.
Tarnocai, C., Canadell, J., Schuur, E., Kuhry, P., and Mazhitova, G.: Soil organic carbon pools in the northern circumpolar permafrost region, Global Biogeochem. Cy., 23, GB2023, https://doi.org/10.1029/2008GB003327, 2009.
Turetsky, M. R., Crow, S. E., Evans, R. J., Vitt, D. H., and Weider, K. R.: Trade-offs in resource allocation among moss species control decomposition in boreal peatlands, J. Ecol., 96, 1297–1305, 2008.
Wetterstedt, J. A. M. and Ågren, G. I.: Quality or decomposer efficiency – Which is most important in the temperature response of litter decomposition? A modeling study using the GLUE methodology, Biogeochemistry, 8, 477–487, 2011.
Wieder, W. R., Bonan, G. B., and Allison, S. D.: Global soil carbon projections are improved by modelling microbial processes, Nature, 3, 909–912, 2013.
Wisser, D., Marchenko, S., Talbot, J., Treat, C., and Frolking, S.: Soil temperature response to 21st century global warming: the role of and some implications for peat carbon in thawing permafrost soils in North America, Earth Syst. Dynam., 2, 121–138, https://doi.org/10.5194/esd-2-121-2011, 2011.
Wutzler, T. and Reichstein, M.: Colimitation of decomposition by substrate and decomposers – a comparison of model formulations, Biogeosciences, 5, 749–759, https://doi.org/10.5194/bg-5-749-2008, 2008.
Xenakis, G., Ray, D., and Mencuccini, M.: Sensitivity and uncertainty analysis from a coupled 3-PG and soil organic matter decomposition model, Ecol. Model., 219, 1–16, 2008.
