Journal of Ecology and Environment

The Ecological Society of Korea (한국생태학회)
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Estimating the Soil Carbon Stocks for a Pinus densiflora Forest Using the Soil Carbon Model, Yasso

  • Lee, Ah-Reum (Department of Climate Environment, Graduate School of Life and Environmental Sciences, Korea University) ;
  • Noh, Nam-Jin (Division of Environmental Science and Ecological Engineering, Korea University) ;
  • Cho, Yong-Sung (Department of Climate Environment, Graduate School of Life and Environmental Sciences, Korea University) ;
  • Lee, Woo-Kyun (Department of Climate Environment, Graduate School of Life and Environmental Sciences, Korea University) ;
  • Son, Yo-Whan (Department of Climate Environment, Graduate School of Life and Environmental Sciences, Korea University)
  • Published : 2009.02.28
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Abstract

The soil carbon stock for a Pinus densiflora forest at Gwangneung, central Korea was estimated using the soil carbon model, Yasso. The soil carbon stock measured in the forest was 43.73 t C $ha^{-1}$, and the simulated initial (steady state) soil carbon stock and the simulated current soil carbon stock in 2007 were 39.19 t C $ha^{-1}$ and 38.90 t C $ha^{-1}$, respectively. Under the assumption of a $0.1^{\circ}C$ increase in mean annual temperature per year, the decomposition and litter fractionation rates increased from 0.28 to 0.56 % $year^{-1}$ and the soil carbon stock decreased from 0.03 to 0.12 % $year^{-1}$. Yasso is a simple and general model that can be applied in cases where there is insufficient input information. However, in order to obtain more accurate estimates in Korea, parameters need to be recalibrated under Korean climatic and vegetation conditions. In addition, the Yasso model needs to be linked to other models to generate better litter input data.

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References

  1. Chertov OG, Komarov AS, Nadporozhskaya M, Bykhovets SS, Zudin SL. 2001. ROMUL - a model of forest soil organic matter dynamics as a substantial tool for forest ecosystem modeling. Ecol Model 138: 289-308 https://doi.org/10.1016/S0304-3800(00)00409-9
  2. Coleman K, Jenkinson DS. 1996. Simulating trends in soil organic carbon in long-term experiments using RothC-26.3. Geoderma 81: 29-44 https://doi.org/10.1016/S0016-7061(97)00079-7
  3. Currie WS, Aber JD. 1997. Modeling leaching as a decomposition process in humid, montane forests. Ecology 78: 1844-1860 https://doi.org/10.1890/0012-9658(1997)078[1844:MLAADP]2.0.CO;2
  4. Falloon P, Smith P. 2002. Simulating SOC changes in long-term experiments with RothC and CENTURY: model evaluation for a regional scale application. Soil Use Manage 18: 101-111 https://doi.org/10.1111/j.1475-2743.2002.tb00227.x
  5. Faubert P, Lindner M, Thurig E, Peltoniemi M, Palosuo T, Chertov O, Komarov A, Mikhailov A, Suckow F, Lasch P, Wattenbach M, Smith P, Gottschalk P. 2005. Comparison of soil carbon stocks and stock changes simulated with four soil models. CarboInvent report. Doc. No.: WP6-D6.3-EFI
  6. Hynynen J, Ahtikoski A, Siitonen J, Sievanen R, Liski J. 2005. Applying the MOTTI simulator to analyze the effects of alternative management schedules on timber and non-timber production. For Ecol Manag 207: 5-18 https://doi.org/10.1016/j.foreco.2004.10.015
  7. Jeon IY, Shin C, Kim G, Mun H. 2007. Organic carbon distribution of the Pinus densiflora forest on Songgye valley at Mt. Worak national park. J Ecol Field Biol 30: 17-21 https://doi.org/10.5141/JEFB.2007.30.1.017
  8. Jung HJ, Won HG, Kim IH. 2004. Forest Sites of Korea : Forest soil. Korea Forest Research Institute
  9. Karjalainen T, Pussinen A, Liski J, Nabuurs GJ, Erhard M, Eggers T, Sonntag M, Mohren GMJ. 2002. An approach towards an estimate of the impact of forest management and climate change on the European forest sector carbon budget: Germany as a case study. For Ecol Manag 162: 87-103 https://doi.org/10.1016/S0378-1127(02)00052-X
  10. Kelly RH, Parton WJ, Crocker GJ, Grace PR, Klír J, Korschens M, Poulton PR, Richter DD. 1997. Simulating trends in soil organic carbon in long-term experiments using the century model. Geoderma 81: 75-90 https://doi.org/10.1016/S0016-7061(97)00082-7
  11. Kim CS. 2006. Soil carbon cycling and soil CO$_{2}$ efflux in a red pine (Pinus densiflora) stand. J Ecol Field Biol 29: 23-27 https://doi.org/10.5141/JEFB.2006.29.1.023
  12. Lim JH, Shin JH, Jin GZ, Chun JH, Oh JS. 2003. Forest stand structure, site characteristics and carbon budget of the Kwangneung national forest in Korea. Korean J Agri For Meteo 5: 101-109
  13. Liski J, Nissinen A, Erhard M, Taskinen O. 2003. Climatic effects on litter decomposition from arctic tundra to tropical rainforest. Global Change Biol 9: 1-10 https://doi.org/10.1046/j.1365-2486.2003.00507.x
  14. Liski J, Perruchoud D, Karjalainen T. 2002. Increasing carbon stocks in the forest soils of western Europe. For Ecol Manag 169: 159-175 https://doi.org/10.1016/S0378-1127(02)00306-7
  15. Liski J, Palosuo T, Peltoniemi M, Sievaenen R. 2005. Carbon and decomposition model Yasso for forest soils. Ecol Model 189: 168-182 https://doi.org/10.1016/j.ecolmodel.2005.03.005
  16. Liski J, Westman CJ. 1995. Density of organic carbon in soil at coniferous forest sites in Southern Finland. Biogeochemistry 29: 183-197 https://doi.org/10.1007/BF02186047
  17. Masera OR, Garza-Caligaris JF, Kanninen M, Karjalainen T, Liski J, Nabuurs GJ, Pussinen A, Jong BHJ, Mohren GMJ. 2003. Modeling carbon sequestration in afforestation, agroforestry and forest management projects: the CO2FIX V.2 approach. Ecol Model 164: 177-199 https://doi.org/10.1016/S0304-3800(02)00419-2
  18. Morisada K, Ono K, Kanomata H. 2004. Organic carbon stock in forest soils in Japan. Geoderma 119: 21-32 https://doi.org/10.1016/S0016-7061(03)00220-9
  19. Nakane K, Tsubota H, Yamamoto M. 1984. Cycling of soil carbon in Japanese red pine forest I. Before a clear-felling. Bot Mag Tokyo 97: 39-60 https://doi.org/10.1007/BF02488146
  20. Palosuo T, Liski J, Trofymow JA, Titus BD. 2005. Litter decomposition affected by climate and litter quality - Testing the Yasso model with litterbag data from the Canadian intersite decomposition experiment. Ecol Model 189: 183-198 https://doi.org/10.1016/j.ecolmodel.2005.03.006
  21. Paul KI, Polglase PJ, Richards GP. 2003. Predicted change in soil carbon following afforestation or reforestation, and analysis of controlling factors by linking a C accounting model (CAMFor) to models of forest growth (3PG), litter decomposition (GENDEC) and soil C turnover (RothC). For Ecol Manag 177: 485-501 https://doi.org/10.1016/S0378-1127(02)00454-1
  22. Peltoniemi M, Makipaa R, Liski J, Tamminen P. 2004. Changes in soil carbon with stand age - an evaluation of a modeling method with empirical data. Global Change Biol 10: 2078-2091 https://doi.org/10.1111/j.1365-2486.2004.00881.x
  23. Powlson DS, Smith P, Smith JU. 1996. Evaluation of Soil Organic Matter Models. Springer-Verlag. Berlin
  24. Schmid S, Thürig E, Kaufmann E, Lischke H, Bugmann H. 2006. Effect of forest management on future carbon pools and fluxes: A model comparison. For Ecol Manag 237: 65-82 https://doi.org/10.1016/j.foreco.2006.09.028
  25. Thornthwaite CW. 1948. An approach toward a rational classification of climate. Geogr Rev 38: 55-94 https://doi.org/10.2307/210739
  26. UNFCCC. 1997. Kyoto Protocol. http://www.unfccc.de/resource
  27. You YH, Jeong NG, Lee YY, Kim JH, Lee JY, Mun HT. 2000. Mass loss and nutrients dynamics during the litter decomposition in Kwangneung Experimental Forest. J Korean For Soc 89: 41-48

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