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Mikko Peltoniemi (email), Esther Thürig, Stephen Ogle, Taru Palosuo, Marion Schrumpf, Thomas Wutzler, Klaus Butterbach-Bahl, Oleg Chertov, Alexander Komarov, Aleksey Mikhailov, Annemieke Gärdenäs, Charles Perry, Jari Liski, Pete Smith, Raisa Mäkipää

Models in country scale carbon accounting of forest soils

Peltoniemi M., Thürig E., Ogle S., Palosuo T., Schrumpf M., Wutzler T., Butterbach-Bahl K., Chertov O., Komarov A., Mikhailov A., Gärdenäs A., Perry C., Liski J., Smith P., Mäkipää R. (2007). Models in country scale carbon accounting of forest soils. Silva Fennica vol. 41 no. 3 article id 290. https://doi.org/10.14214/sf.290

Abstract

Countries need to assess changes in the carbon stocks of forest soils as a part of national greenhouse gas (GHG) inventories under the United Nations Framework Convention on Climate Change (UNFCCC) and the Kyoto Protocol (KP). Since measuring these changes is expensive, it is likely that many countries will use alternative methods to prepare these estimates. We reviewed seven well-known soil carbon models from the point of view of preparing country-scale soil C change estimates. We first introduced the models and explained how they incorporated the most important input variables. Second, we evaluated their applicability at regional scale considering commonly available data sources. Third, we compiled references to data that exist for evaluation of model performance in forest soils. A range of process-based soil carbon models differing in input data requirements exist, allowing some flexibility to forest soil C accounting. Simple models may be the only reasonable option to estimate soil C changes if available resources are limited. More complex models may be used as integral parts of sophisticated inventories assimilating several data sources. Currently, measurement data for model evaluation are common for agricultural soils, but less data have been collected in forest soils. Definitions of model and measured soil pools often differ, ancillary model inputs require scaling of data, and soil C measurements are uncertain. These issues complicate the preparation of model estimates and their evaluation with empirical data, at large scale. Assessment of uncertainties that accounts for the effect of model choice is important part of inventories estimating large-scale soil C changes. Joint development of models and large-scale soil measurement campaigns could reduce the inconsistencies between models and empirical data, and eventually also the uncertainties of model predictions.

Keywords
decomposition; greenhouse gas inventory; IPCC; national forest inventory; regional and national modeling; soil carbon; soil model

Author Info
  • Peltoniemi, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail mikko.peltoniemi@metla.fi (email)
  • Thürig, Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, Switzerland; European Forest Institute, Joensuu, Finland ORCID ID:
  • Ogle, Natural Resources Ecology Laboratory, Colorado State University, Fort Collins, USA ORCID ID:
  • Palosuo, European Forest Institute, Joensuu, Finland ORCID ID:
  • Schrumpf, Max-Planck-Institute for Biogeochemistry, Jena, Germany ORCID ID:
  • Wutzler, Max-Planck-Institute for Biogeochemistry, Jena, Germany ORCID ID:
  • Butterbach-Bahl, Institute for Meteorology and Climate Research, Forschungszentrum Karlsruhe GmbH, Garmisch-Partenkirchen, Germany ORCID ID:
  • Chertov, St. Petersburg State University, St. Petersburg-Peterhof, Russia ORCID ID:
  • Komarov, Institute of Physicochemical and Biological Problems in Soil Science of Russian Academy of Sciences, Pushchino, Russia ORCID ID:
  • Mikhailov, Institute of Physicochemical and Biological Problems in Soil Science of Russian Academy of Sciences, Pushchino, Russia ORCID ID:
  • Gärdenäs, Dept. of Soil Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden ORCID ID:
  • Perry, USDA Forest Service, Northern Research Station, St. Paul, MN USA ORCID ID:
  • Liski, Finnish Environment Institute, Helsinki, Finland ORCID ID:
  • Smith, School of Biological Sciences, University of Aberdeen, Aberdeen, UK ORCID ID:
  • Mäkipää, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland ORCID ID:E-mail raisa.makipaa@metla.fi

Received 25 August 2006 Accepted 5 July 2007 Published 31 December 2007

Available at https://doi.org/10.14214/sf.290 | Download PDF


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