Models in country scale carbon accounting of forest soils

Mikko Peltoniemi, Esther Thurig, Stephen Ogle, Taru Palosuo, Marion Schrumpf, Thomas Wutzler, Klaus Butterbach-Bahl, Oleg Chertov, Alexander Komarov, Alexey Mikhailov, Annemieke Gardenas, Charles Perry, Jori Liski, Pete Smith, Raisa Makipaa

Research output: Contribution to journalArticle

53 Citations (Scopus)

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 AM 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.

Original languageEnglish
Pages (from-to)575-602
Number of pages28
JournalSilva Fennica
Volume41
Issue number3
Publication statusPublished - 2007

Keywords

  • decomposition
  • greenhouse gas inventory
  • IPCC
  • national forest inventory
  • regional and national modeling
  • soil carbon
  • soil model
  • long-term experiments
  • organic-matter dynamics
  • process-oriented model
  • PNET-N-DNDC
  • land-use
  • litter decomposition
  • climate-change
  • boreal forest
  • temperature-dependence
  • physical separation

Cite this

Peltoniemi, M., Thurig, E., Ogle, S., Palosuo, T., Schrumpf, M., Wutzler, T., ... Makipaa, R. (2007). Models in country scale carbon accounting of forest soils. Silva Fennica, 41(3), 575-602.

Models in country scale carbon accounting of forest soils. / Peltoniemi, Mikko; Thurig, Esther; Ogle, Stephen; Palosuo, Taru; Schrumpf, Marion; Wutzler, Thomas; Butterbach-Bahl, Klaus; Chertov, Oleg; Komarov, Alexander; Mikhailov, Alexey; Gardenas, Annemieke; Perry, Charles; Liski, Jori; Smith, Pete; Makipaa, Raisa.

In: Silva Fennica, Vol. 41, No. 3, 2007, p. 575-602.

Research output: Contribution to journalArticle

Peltoniemi, M, Thurig, E, Ogle, S, Palosuo, T, Schrumpf, M, Wutzler, T, Butterbach-Bahl, K, Chertov, O, Komarov, A, Mikhailov, A, Gardenas, A, Perry, C, Liski, J, Smith, P & Makipaa, R 2007, 'Models in country scale carbon accounting of forest soils', Silva Fennica, vol. 41, no. 3, pp. 575-602.
Peltoniemi M, Thurig E, Ogle S, Palosuo T, Schrumpf M, Wutzler T et al. Models in country scale carbon accounting of forest soils. Silva Fennica. 2007;41(3):575-602.
Peltoniemi, Mikko ; Thurig, Esther ; Ogle, Stephen ; Palosuo, Taru ; Schrumpf, Marion ; Wutzler, Thomas ; Butterbach-Bahl, Klaus ; Chertov, Oleg ; Komarov, Alexander ; Mikhailov, Alexey ; Gardenas, Annemieke ; Perry, Charles ; Liski, Jori ; Smith, Pete ; Makipaa, Raisa. / Models in country scale carbon accounting of forest soils. In: Silva Fennica. 2007 ; Vol. 41, No. 3. pp. 575-602.
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AU - Thurig, Esther

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AU - Wutzler, Thomas

AU - Butterbach-Bahl, Klaus

AU - Chertov, Oleg

AU - Komarov, Alexander

AU - Mikhailov, Alexey

AU - Gardenas, Annemieke

AU - Perry, Charles

AU - Liski, Jori

AU - Smith, Pete

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N2 - 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 AM 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.

AB - 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 AM 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.

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KW - greenhouse gas inventory

KW - IPCC

KW - national forest inventory

KW - regional and national modeling

KW - soil carbon

KW - soil model

KW - long-term experiments

KW - organic-matter dynamics

KW - process-oriented model

KW - PNET-N-DNDC

KW - land-use

KW - litter decomposition

KW - climate-change

KW - boreal forest

KW - temperature-dependence

KW - physical separation

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VL - 41

SP - 575

EP - 602

JO - Silva Fennica

JF - Silva Fennica

SN - 0037-5330

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ER -