Chinese Geographical Science

, Volume 23, Issue 5, pp 519–536 | Cite as

Carbon dynamics in woody biomass of forest ecosystem in China with forest management practices under future climate change and rising CO2 concentration

  • Lei Zhou
  • Shaoqiang Wang
  • Georg Kindermann
  • Guirui Yu
  • Mei Huang
  • Robert Mickler
  • Florian Kraxner
  • Hao Shi
  • Yazhen Gong


It is critical to study how different forest management practices affect forest carbon sequestration under global climate change regime. Previous researches focused on the stand-level forest carbon sequestration with rare investigation of forest carbon stocks influenced by forest management practices and climate change at regional scale. In this study, a general integrative approach was used to simulate spatial and temporal variations of woody biomass and harvested biomass of forest in China during the 21st century under different scenarios of climate and CO2 concentration changes and management tasks by coupling Integrated Terrestrial Ecosystem Carbon budget (InTEC) model with Global Forest Model (G4M). The results showed that forest management practices have more predominant effects on forest stem stocking biomass than climate and CO2 concentration change. Meanwhile, the concurrent future changes in climate and CO2 concentration will enhance the amounts of stem stocking biomass in forests of China by 12%–23% during 2001–2100 relative to that with climate change only. The task for maximizing stem stocking biomass will dramatically enhance the stem stocking biomass from 2001–2100, while the task for maximum average increment will result in an increment of stem stocking biomass before 2050 then decline. The difference of woody biomass responding to forest management tasks was owing to the current age structure of forests in China. Meanwhile, the sensitivity of long-term woody biomass to management practices for different forest types (coniferous forest, mixed forest and deciduous forest) under changing climate and CO2 concentration was also analyzed. In addition, longer rotation length under future climate change and rising CO2 concentration scenario will dramatically increase the woody biomass of China during 2001–2100. Therefore, our estimation indicated that taking the role of forest management in the carbon cycle into the consideration at regional or national level is very important to project the forest carbon sequestration under future climate change and rising atmospheric CO2 concentration.


global forest model carbon stock forest management rotation length harvested biomass future climate change 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Ainsworth E A, Long S P, 2005. What have we learned from 15 years of free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2. New Phytologist, 165(2): 351–372. doi: 10.1111/j.1469-8137.2004.01224.xCrossRefGoogle Scholar
  2. Berthelot M, Friedlingstein P, Ciais P et al., 2002. Global response of the terrestrial biosphere to CO2 and climate change using a coupled climate-carbon cycle model. Global Biogeochemical Cycles, 16(4): 1084. doi: 10.1029/2001GB001827CrossRefGoogle Scholar
  3. Bu R C, He H S, Hu Y M et al., 2008. Using the LANDIS model to evaluate forest harvesting and planting strategies under possible warming climates in northeastern China. Forest Ecology and Management, 254(3): 407–419. doi: 10.1016/j.foreco.2007.09.080CrossRefGoogle Scholar
  4. Caldwell I M, Maclaren V W, Chen J M et al., 2007. An integrated assessment model of carbon sequestration benefits: A case study of Liping County, China. Journal of Environmental Management, 85(3): 757–773. doi: 10.1016/j.jenvman.2006.08.020CrossRefGoogle Scholar
  5. Cao M, Woodward F I, 1998. Dynamic responses of terrestrial ecosystem carbon cycling to global climate change. Nature, 393(6682): 249–252. doi: 10.1038/30460CrossRefGoogle Scholar
  6. Chen J M, Chen W J, Liu J et al., 2000. Annual carbon balance of Canada’s forests during 1895-1996. Global Biogeochemical Cycles, 14(3): 839–849. doi: 10.1029/1999GB001207CrossRefGoogle Scholar
  7. Chen J M, Ju W M, Cihlar J et al., 2003. Spatial distribution of carbon sources and sinks in Canada’s forests. Tellus B, 55(2): 622–641. doi: 10.1034/j.1600-0889.2003.00036.xCrossRefGoogle Scholar
  8. Ciais P, Reichstein M, Viovy N et al., 2005. Europe-wide reduction in primary productivity caused by the heat and drought in 2003. Nature, 437(7058): 529–533. doi: 10.1038/nature03972CrossRefGoogle Scholar
  9. Coomes D A, Holdaway R J, Kobe R K et al., 2012. A general integrative framework for modelling woody biomass production and carbon sequestration rates in forests. Journal of Ecology, 100(1): 42–64. doi: 10.1111/j.1365-2745.2011.01920.xCrossRefGoogle Scholar
  10. Cooper C F, 1983. Carbon storage in managed forests. Canadian Journal of Forest Research, 13(1): 155–166. doi: 10.1139/x83-022CrossRefGoogle Scholar
  11. Cramer W, Bondeau A, Woodward F I et al., 2001. Global response of terrestrial ecosystem structure and function to CO2 and climate change: Results from six dynamic global vegetation models. Global Change Biology, 7(4): 357–373. doi:10.1046/j.1365-2486.2001.00383.xCrossRefGoogle Scholar
  12. Eggers J, Lindner M, Zudin S et al., 2008. Impact of changing wood demand, climate and land use on European forest resources and carbon stocks during the 21st century. Global Change Biology, 14(10): 2288–2303. doi: 10.1111/j.1365-2486.2008.01653.xCrossRefGoogle Scholar
  13. Fang J Y, Chen A P, Peng C H et al., 2001. Changes in forest biomass carbon storage in China between 1949 and 1998. Science, 292(5525): 2320–2322. doi: 10.1126/science.1058629CrossRefGoogle Scholar
  14. Fang J Y, Piao S L, Field C B et al., 2003. Increasing net primary production in China from 1982-1999. Frontiers in Ecology and the Environment, 1(6): 293–297. doi: 10.1890/1540-9295(2003)001[0294:INPPIC]2.0.CO;2CrossRefGoogle Scholar
  15. Farquhar G D, von Caemmerer S, Berry J A, 1980. A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta, 149(1): 78–90. doi: 10.1007/BF00386231CrossRefGoogle Scholar
  16. Feng X, Liu G, Chen J M et al., 2007. Net primary productivity of China’s terrestrial ecosystems from a process model driven by remote sensing. Journal of Environmental Management, 85(3): 563–573. doi: 10.1016/j.jenvman.2006.09.021CrossRefGoogle Scholar
  17. FAO (Food and Agriculture Organization of the United Nations), 2005. FAOSTAT Database. Available at: Google Scholar
  18. Giorgi F, Mearns L O, 2002. Calculation of average, uncertainty range and reliability of regional climate changes from AOGCM simulations via the’ Reliability Ensemble Averaging (REA)’ method. Journal of Climate, 15(10): 1141–1158. doi: 10.1175/1520-0442(2002)015<1141:COAURA>2.0.CO;2CrossRefGoogle Scholar
  19. Giorgi F, Mearns L O, 2003. Probability of regional climate change based on the Reliability Ensemble Averaging (REA) method. Geophysical Research Letters, 30(12): 1629–1632. doi: 10.1029/2003GL017130CrossRefGoogle Scholar
  20. Govinda A, Chen, J M, Bernierc P et al., 2011. Spatially distributed modeling of the long-term carbon balance of a boreal landscape. Ecological Modelling, 222(15): 2780–2795. doi: 10.1016/j.ecolmodel.2011.04.007CrossRefGoogle Scholar
  21. Gusti M, 2010. An Algorithm for Simulation of Forest Management Decisions in the Global Forest Model. Artificial Intelligence, 4: 45–49.Google Scholar
  22. Gusti M, Kindermann G, 2011. An Approach to Modeling Land Use Change and Forest Management on a Global Scale. Austria: International Institute for Applied Systems Analysis.Google Scholar
  23. He H S, Larsen D R, Mladenoff D J, 2002. Exploring component based approaches in forest landscape modeling. Environmental Modelling and Software, 17(6): 519–529. doi: 10.1016/S1364-8152(02)00014-2CrossRefGoogle Scholar
  24. Hutchinson M F, 2002. ANUSPLIN Version 4.2 User Guide. Canberra: Australian National University, 1–48.Google Scholar
  25. IPCC (Intergovernmental Panel on Climate Change), 2007. Climate Change 2007: The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK: Cambridge University Press.Google Scholar
  26. Jarvis P G, 1998. European Forests and Global Change: The Likely Impacts of Rising CO 2 and Temperature. Cambridge: Cambridge University Press, 1–398.Google Scholar
  27. Joyce L A, Birdsey R, 2000. The Impacts of Climate Change on America’s Forests: A Technical Document Supporting the 2000 USDA Forest Service RPA Assessment. Fort Collins: US Department of Agriculture, Forest Service, Rocky Mountain Research Station.Google Scholar
  28. Ju W M, Chen J M, 2005. Distribution of soil carbon stocks in Canada’s forests and wetlands simulated based on drainage class, topography and remotely sensed vegetation parameters. Hydrological Processes, 19(1): 77–94. doi: 10.1002/hyp.5775CrossRefGoogle Scholar
  29. Ju W M, Chen J M, Black T A et al., 2006. Modeling coupled water and carbon fluxes in a boreal aspen forest. Agricultural and Forest Meteorology, 140(1–4): 136–151. doi: 10.1016/j.agrformet.2006.08.008CrossRefGoogle Scholar
  30. Ju W M, Chen J M, Harvey D et al., 2007. Future carbon balance of China’s forests under climate change and increasing CO2. Journal of Environmental Management, 85(3): 538–562. doi: 10.1016/j.jenvman.2006.04.028CrossRefGoogle Scholar
  31. Ju W M, Chen J M, 2008. Simulating the effects of past changes in climate, atmospheric composition, and fire disturbance on soil carbon in Canada’s forests and wetlands. Global Biogeochemical Cycles, 22(3): GB3010. doi: 10.1029/2007GB002935CrossRefGoogle Scholar
  32. Ju W M, Chen J M, Black T A et al., 2010. Spatially simulating changes of soil water content and their effects on carbon sequestration in Canada’s forests and wetlands. Tellus, 62(3): 140–159. doi: 10.1111/j.1600-0889.2010.00459.xCrossRefGoogle Scholar
  33. Kaipainen T, Liski J, Pussinen A et al., 2004. Managing carbon sinks by changing rotation length in European forests. Environmental Science and Policy, 7(3): 205–219. doi: 10.1016/j.envsci.2004.03.001CrossRefGoogle Scholar
  34. Karjalainen T, Pussinen A, Liski J et al., 2003. Scenario analysis of the impacts of forest management and climate change on the European forest sector carbon budget. Forest Policy and Economics, 5(2): 141–155. doi: 10.1016/S1389-9341(03)00021-2CrossRefGoogle Scholar
  35. Kindermann G, Obersteiner M, Rametsteiner E et al., 2006. Predicting the Deforestation-Trend under Different Carbon-Prices. Carbon Balance and Management, 1(15): 1–17. doi: 10.1186/1750-0680-1-15Google Scholar
  36. Kindermann G, Obersteiner M, Sohngen B et al., 2008. Global cost estimates of reducing carbon emissions through avoided deforestation. Proceedings of the National Academy of Sciences of the United States of America, 105(30): 10302–10307. doi: 10.1073/pnas.0710616105CrossRefGoogle Scholar
  37. Kindermann G, Schörghuber S, Linkosalo T et al., 2011. Potential Woody Biomass and Increments in the European Union until 2100. Austria: International Institute for Applied Systems Analysis.Google Scholar
  38. Liski J, Pussinen A, Pingoud K et al., 2001. Which rotationlength is favourable for carbon sequestration. Canadian Journal of Forest Research, 31(11): 2004–2013. doi: 10.1139/x01-140CrossRefGoogle Scholar
  39. Liu Z L, Fang S Z, Liu D et al., 2011. Influence of thinning time and density on sprout development, biomass production and energy stocks of sawtooth oak stumps. Forest Ecology and Management, 262(2): 299–306. doi: 10.1016/j.foreco.2011.03.035CrossRefGoogle Scholar
  40. Long S P, Ainsworth E A, Rogers A et al., 2004. Rising atmospheric carbon dioxide: plants face the future. Annual Review of Plant Biology, 55: 591–628. doi: 10.1146/annurev.arplant.55.031903.141610CrossRefGoogle Scholar
  41. Luo T X, Li W H, Zhu H Z, 2002. Estimated biomass and productivity of natural vegetation on the Tibetan plateau. Ecological Applications, 12(4): 980–997. doi: 10.2307/3061031CrossRefGoogle Scholar
  42. Luo Tianxiang, 1996. Patterns of Net Primary Productivity for Chinese Major Forest Types and Its Mathematical Models. Beijing: Commission for Integrated Survey of Natural Resources, Chinese Academy of Sciences. (in Chinese)Google Scholar
  43. Mäkipää R, Karjalainen T, Pussinen A et al., 1999. Effects of climate change and nitrogen deposition on the carbon sequestration of a forest ecosystem in the boreal zone. Canadian Journal of Forest Research, 29(10): 1490–1501. doi: 10.1139/cjfr-29-10-1490CrossRefGoogle Scholar
  44. McGuire A D, Sitch S, Clein J S et al., 2001. Carbon balance of the terrestrial biosphere in the twentieth century: Analyses of CO2, climate, and land-use effects with four process-based ecosystem models. Global Biogeochemical Cycles, 15(1): 183–206. doi: 10.1029/2000GB001298CrossRefGoogle Scholar
  45. Melillo J M, Mcguire A D, Kicklighter D W et al., 1993. Global climate-change and terrestrial net primary production. Nature, 363(6426): 234–240. doi: 10.1038/363234a0CrossRefGoogle Scholar
  46. Norby R J, DeLucia E H, Gielen B et al., 2005. Forest response to elevated CO2 is conserved across a broad range of productivity. Proceedings of the National Academy of Sciences of the United States of America, 102(50): 18052–18056. doi: 10.1073/pnas.0509478102CrossRefGoogle Scholar
  47. Pacala S W, Socolow R, 2004. Stabilization wedges: Solving the climate problem for the next 50 years with current technologies. Science, 305(5686): 968–972. doi: 10.1126/science.1100103CrossRefGoogle Scholar
  48. Parton W J, Scurlock J M O, Ojima D S et al., 1993. Observations and modeling of biomass and soil organic matter dynamics for the grassland biome worldwide. Global Biogeochemical Cycles, 7(4): 785–809. doi: 10.1029/93GB02042CrossRefGoogle Scholar
  49. Pussinen A, Karjalainen T, Mäkipää R et al., 2002. Forest carbon sequestration and harvest in Scots pine stand under different climate and nitrogen deposition scenarios. Forest Ecology and Management, 158(1–3): 103–115. doi: 10.1029/93GB02042CrossRefGoogle Scholar
  50. Ranatunga K, Keenan R J, Wullshchleger S D et al., 2008. Effects of harvest management practices on forest biomass and soil carbon in eucalypt forests in New South Wales, Australia: Simulations with the forest succession model LINKAGES. Forest Ecology and Management, 255(7): 2407–2415. doi: 10.1016/j.foreco.2008.01.002CrossRefGoogle Scholar
  51. Rathgeber C, Nicault A, Guiot J et al., 2000. Simulated responses of Pinus halepensis forest productivity to climatic change and CO2 increase using a statistical model. Global and Planetary Change, 26(4): 405–421. doi: 10.1016/S0921-8181(00)00053-9CrossRefGoogle Scholar
  52. Seely B, Welham C, Kimmins H, 2002. Carbon sequestration in a boreal forest ecosystem: Results from the ecosystem simulation model. Forest Ecology and Management, 169(1–2): 123–135. doi: 10.1016/S0378-1127(02)00303-1CrossRefGoogle Scholar
  53. Shang Z B, He H S, Xi W M et al., 2012. Integrating LANDIS model and a multi-criteria decision-making approach to evaluate cumulative effects of forest management in the Missouri Ozarks, USA. Ecological Modelling, 229: 50–63. doi: 10.1016/j.ecolmodel.2011.08.014CrossRefGoogle Scholar
  54. Shanin V N, Komarov A S, Mikhailov A V et al., 2011. Modelling carbon and nitrogen dynamics in forest ecosystems of Central Russia under different climate change scenarios and forest management regimes. Ecological Modelling, 222(14): 2262–2275. doi: 10.1016/j.ecolmodel.2010.11.009CrossRefGoogle Scholar
  55. Shao Y, Pan J, Yang L et al., 2007. Tests of soil organic carbon density modeled by InTEC model in China’s forest ecosystems. Journal of Environmental Management, 85(3): 696–701. doi: 10.1016/j.jenvman.2006.09.006CrossRefGoogle Scholar
  56. Simioni G, Ritson P, Kirschbaum M U F et al., 2009. The carbon budget of pinus radiata plantations in south-western Australia under four climate change scenarios. Tree Physiology, 29(9): 1081–1093. doi: 10.1093/treephys/tpp049.CrossRefGoogle Scholar
  57. State Forestry Administration, 1999. China Forestry Yearbook: 1998–2003. Beijing: China Forestry Publishing House, 1–783. (in Chinese)Google Scholar
  58. Thomas S C, Malczewski G, Saprunoff M, 2007. Assessing the potential of native tree species for carbon sequestration forestry in Northeast China. Journal of Environmental Management, 85(3): 663–671. doi: 10.1016/j.jenvman.2006.04.027CrossRefGoogle Scholar
  59. Thornton P E, Lamarque J F, Rosenbloom N A et al., 2007. Influence of carbon-nitrogen cycle coupling on land model response to CO2 fertilization and climate variability. Global Biogeochemical Cycles, 21(4): GB4018. doi:10.1029/2006GB002868CrossRefGoogle Scholar
  60. Wang S Q, Chen J M, Ju W M et al., 2007. Carbon sinks and sources in China’s forests during 1901–2001. Journal of Environmental Management, 85(3): 524–537. doi: 10.1016/j.jenvman.2006.09.019CrossRefGoogle Scholar
  61. Wang S Q, Zhou L, Chen J M et al., 2011. Relationships between net primary productivity and stand age for several forest types and their influence on China’s carbon balance. Journal of Environmental Management, 92(6): 1651–1662. doi: 10.1016/j.jenvman.2011.01.024CrossRefGoogle Scholar
  62. Wang W F, Wei X H, Liao W M et al., 2012. Evaluation of the effects of forest management strategies on carbon sequestration in evergreen broad-leaved (Phoebe bournei) plantation forests using FORECAST ecosystem model. Forest Ecology and Management, in press. doi: 10.1016/j.foreco.2012.06.044Google Scholar
  63. White A, Cannell M G R, Friend A D, 2000. The high-latitude terrestrial carbon sink: A model analysis. Global Change Biology, 6(2): 227–245. doi: 10.1046/j.1365-2486.2000.00302.xCrossRefGoogle Scholar
  64. Xu Y, Gao X J, Giorgi F, 2009. Upgrades to the reliability ensemble averaging method for producing probabilistic climate change projections. Climate Research, 41(1): 61–81. doi: 10.3354/cr00835Google Scholar
  65. Yang L X, Pan J J, Shao Y H et al., 2007. Soil organic carbon decomposition and carbon pools in temperate and sub-tropical forests in China. Journal of Environmental Management, 85(3): 690–695. doi: 10.1016/j.jenvman.2006.09.011CrossRefGoogle Scholar
  66. Yao J, He X, Wang A et al., 2012. Influence of Forest Management Regimes on Forest Dynamics in the Upstream Region of the Hun River in Northeastern China. PLoS ONE, 7(6): e39058. doi: 10.1371/journal.pone.0039058CrossRefGoogle Scholar
  67. Yu Guirui, He Honglin, Liu Xinan et al., 2004. Atlas for Spatialized Information of Terrestrial Ecosystem in China: Volume of Climatological Elements. Beijing: China Meteorological Press, 1–317. (in Chinese)Google Scholar
  68. Zeeman M J, Hiller R, Gilgen A K et al., 2010. Management and climate impacts on net CO2 fluxes and carbon budgets of three grasslands along an elevational gradient in Switzerland. Agricultural and Forest Meteorology, 150(4): 519–530. doi: 10.1016/j.agrformet.2010.01.011CrossRefGoogle Scholar
  69. Zeng N, Qian H, Rödenbeck C et al., 2005. Impact of 1998–2002 midlatitude drought and warming on terrestrial ecosystem and the global carbon cycle. Geophysical Research Letters, 32(22): L22709. doi: 10.1029/2005GL024607CrossRefGoogle Scholar
  70. Zhang J B, Shangguan T L, Meng Z Q, 2011. Changes in soil carbon flux and carbon stock over a rotation of poplar plantations in northwest China. Ecological research, 26(1): 153–161. doi: 10.1007/s11284-010-0772-5CrossRefGoogle Scholar
  71. Zhao M F, Xiang W H, Deng X W, 2013. Application of TRIPLEX model for predicting Cunninghamia lanceolata and Pinus massoniana forest stand production in Hunan Province, southern China. Ecological Modelling, 250: 58–71. doi: 10.1016/j.ecolmodel.2012.10.011CrossRefGoogle Scholar
  72. Zhou L X, Conway T J, White J W C et al., 2005. Long-term record of atmospheric CO2 and stable isotopic ratios at Waliguan observatory: Background features and possible drivers, 1991–2002. Global Biogeochemical Cycles, 19(2): GB3021. doi: 10.1029/2004GB002430Google Scholar

Copyright information

© Science Press, Northeast Institute of Geography and Agricultural Ecology, CAS and Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Lei Zhou
    • 1
    • 2
  • Shaoqiang Wang
    • 1
  • Georg Kindermann
    • 3
  • Guirui Yu
    • 1
  • Mei Huang
    • 1
  • Robert Mickler
    • 4
  • Florian Kraxner
    • 3
  • Hao Shi
    • 1
    • 2
  • Yazhen Gong
    • 5
  1. 1.Key Laboratory of Ecosystem Network Observation and ModellingInstitute of Geographic Sciences and Natural Resources ResearchBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.Ecosystems Services and ManagementInternational Institute for Applied Systems AnalysisLaxenburgAustria
  4. 4.Alion Science and Technology, Inc. RaleighNorth CarolinaUSA
  5. 5.Renmin University of ChinaBeijingChina

Personalised recommendations