Skip to main content
SpringerLink
Log in

Spatial patterns of ecosystem carbon residence time in Chinese forests

  • Research Paper
  • Published:
Science China Earth Sciences Aims and scope Submit manuscript

Abstract

Capacity of carbon sequestration in forest ecosystem largely depends on the trend of net primary production (NPP) and the length of ecosystem carbon residence time. Retrieving spatial patterns of ecosystem carbon residence time is important and necessary for accurately predicting regional carbon cycles in the future. In this study, a data-model fusion method that combined a process-based regional carbon model (TECO-R) with various ground-based ecosystem observations (NPP, biomass, and soil organic carbon) and auxiliary data sets (NDVI, meteorological data, and maps of vegetation and soil texture) was applied to estimate spatial patterns of ecosystem carbon residence time in Chinese forests at steady state. In the data-model fusion, the genetic algorithm was used to estimate the optimal model parameters related with the ecosystem carbon residence time by minimizing total deviation between modeled and observed values. The results indicated that data-model fusion technology could effectively retrieve model parameters and simulate carbon cycling processes for Chinese forest ecosystems. The estimated carbon residence times were highly heterogenous over China, with most of regions having values between 24 and 70 years. The deciduous needleleaf forest and the evergreen needleleaf forest had the highest averaged carbon residence times (73.8 and 71.3 years, respectively), the mixed forest and the deciduous broadleaf forest had moderate values (38.1 and 37.3 years, respectively), and the evergreen broadleaf forest had the lowest value (31.7 years). The averaged carbon residence time of forest ecosystems in China was 57.8 years.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Solomon S, Qin D, Manning M, et al. Climate Change 2007: The Physical Science Basis. New York: Cambridge University Press, 2007

    Google Scholar 

  2. Young L M. Carbon sequestration in agriculture: The U. S. policy context. Am J Agr Econ, 2003, 85: 1164–1170

    Google Scholar 

  3. Fang J Y, Guo Z D, Piao S L, et al. Terrestrial vegetation carbon sinks in China, 1981–2000. Sci China Ser D-Earth Sci, 2007, 50: 1341–1350

    Article  Google Scholar 

  4. Andrasko K. Climate Change and Global Forests: Current Knowledge of Potential Effects, Adaption and Mitigation Options. Rome: FAO Forestry Department, 1990

    Google Scholar 

  5. Brown S, Sathaye J, Cannell M, et al. Management of forests for mitigation of greenhouse gas emissions. In: Watson R T, Zinyowera M C, Moss R H, eds. Climate Change 1995: Impacts, Adaptations and Mitigation of Climate Change. Cambridge: Cambridge University Press, 1996. 773–798

    Google Scholar 

  6. Cannell M G R, Milne R, Haigreaves K J, et al. National inventories of terrestrial carbon sources and sinks: The UK experience. Clim Change, 1999, 42: 505–530

    Article  Google Scholar 

  7. Dai M H, Zhai W D, Lu Z M, et al. Regional studies of carbon cycles in China: Progress and perspectives (in Chinese). Adv Earth Sci, 2004, 2: 120–130

    Google Scholar 

  8. Canadell J G, Corinne L Q, Raupach M R, et al. Contributions to accelerating atmospheric CO2 growth from economic activity, carbon intensity, and efficiency of natural sinks. Proc Natl Acad Sci, 2007, doi: 10.1073/pnas.0702737104

  9. Luo Y, White L, Josep G, et al. Sustainability of terrestrial carbon sequestration: A case study in Duke Forest with inversion approach. Glob Biogeochem Cycle, 2003, 17: 1021, doi: 10.1029/2002GB 001923

    Article  Google Scholar 

  10. Luo Y, Wu L, Andrews A, et al. Elevated CO2 differentiates ecosystem carbon processes: Deconvolution analysis of Duke forest FACE data. Ecol Monogr, 2001, 71: 357–376

    Google Scholar 

  11. Barrett D J. Steady state turnover time of carbon in the carbon in the Australian terrestrial biosphere. Glob Biogeochem Cycle, 2002, 16: 1108, doi: 10.1029/2002GB001860

    Article  Google Scholar 

  12. Xu T, White L, Hui D, et al. Probabilistic inversion of a terrestrial ecosystem model: Analysis of uncertainty in parameter estimation and model prediction. Glob Biogeochem Cycle, 2006, 20: GB2007, doi: 10.1029/2005GB002468

    Article  Google Scholar 

  13. Zhou T, Luo Y. Spatial patterns of ecosystem carbon residence time and NPP-driven carbon uptake in the conterminous United States. Glob Biogeochem Cycle, 2008, 22: GB3032, doi: 10.1029/2007GB 002939

    Article  Google Scholar 

  14. Hicke J A, Asner G P, Randerson J T, et al. Trends in North American net primary productivity derived from satellite observations, 1982–1998. Glob Biogeochem Cycle, 2002, 16: 1018, doi: 10.1029/ 2001GB001550

    Article  Google Scholar 

  15. Nemani R R, Keeling C D, Hashimoto H, et al. Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science, 2003, 300: 1560–1563

    Article  Google Scholar 

  16. Piao S, Fang J, Zhou L M, et al. Changes in vegetation net primary productivity from 1982 to 1999 in China. Glob Biogeochem Cycle, 2005, 19: GB2027, doi: 10.1029/2004GB002274

    Article  Google Scholar 

  17. Vogt K A, Vogt D J, Palmiotto P A, et al. Review of root dynamics in forest ecosystems grouped by climate, climatic forest type and species. Plant Soil, 1996, 187: 159–219

    Article  Google Scholar 

  18. Gaudinski J B, Trumbore S E, Davidson E A, et al. The age of fine-root carbon in three forests of the eastern United States measured by radiocarbon. Oecologia, 2001, 129: 420–429

    Google Scholar 

  19. Raupach M R, Rayner P J, Barrett D J, et al. Model-data synthesis in terrestrial carbon observation: Methods, data requirements and data uncertainty specification. Glob Change Biol, 2005, 11: 378–397

    Article  Google Scholar 

  20. Potter C S, Randerson J T, Field C B, et al. Terrestrial ecosystem production: A process model based on global satellite and surface data. Glob Biogeochem Cycle, 1993, 7: 811–841

    Article  Google Scholar 

  21. Field C B, Randerson J T, Malmstrom C M. Global net primary production: Combining ecology and remote sensing. Remote Sens Environ, 1995, 51: 74–88

    Article  Google Scholar 

  22. Ruimy A, Saugier B. Methodology for estimation of terrestrial net primary production from remotely sensed data. J Geophys Res, 1994, 97: 18515–18521

    Google Scholar 

  23. Randerson J T, Thompson M V, Malmstrom C M, et al. Substrate limitations for heterotrophs: Implications for models that estimate the seasonal cycle of atmospheric CO2. Glob Biogeochem Cycle, 1996, 10: 585–602

    Article  Google Scholar 

  24. Schimel D S, Braswell B H, Holland E A, et al. Climatic, edaphic, and biotic controls over storage and turnover of carbon in soils. Glob Biogeochem Cycle, 1994, 8: 279–293

    Article  Google Scholar 

  25. Parton W J, Schimel D S, Cole C V, et al. Analysis of factors controlling soil organic matter levels in Great Plains grasslands. Soil Sci Soc Am J, 1987, 51: 1173–1179

    Article  Google Scholar 

  26. Luo T X. Patterns of net primary productivity for Chinese major forest types and its mathematical models (in Chinese). Doctoral Dissertation. Beijing: Institute of Geographic Sciences and Natural Resources Research, Chines Academy of Sciences, 1996

    Google Scholar 

  27. Wang S, Zhou C, Li K, et al. Study on spatial distribution character analysis of the soil organic Carbon Reservoir in China. J Geogr Sci, 2001, 11: 3–13

    Article  Google Scholar 

  28. Wang S, Tian H, Liu J, et al. Pattern and change of soil organic carbon storage in China: 1960s–1980s. Tellus Ser B-Chem Phys Meteorol, 2003, 55: 416–427

    Article  Google Scholar 

  29. Yu G R, He H L, Liu X A, et al. Atlas for Spatialized Information of Terrestrial Ecosystem in China-Volume of Climatological Elements (in Chinese). Beijing: China Meteorological Press, 2004

    Google Scholar 

  30. Deng S Q. Map of Soil Texture of China. In: Institute of Soil Science, Chinese Academy of Sciences, ed. The Soil Atlas of China (in Chinese). Beijing: Cartographic Publishing House, 1986. 23–24

    Google Scholar 

  31. Haupt R L, Haupt S E. Practical Genetic Algorithms. 2nd ed. Hoboken: John Wiley & Sons Publication Inc, 2004

    Google Scholar 

  32. White L, Luo Y, Xu T. Carbon sequestration: inversion of FACE data and prediction. Appl Math Comput, 2005, 163: 783–800

    Article  Google Scholar 

  33. Running S W, Thornton P E, Nemani R, et al. Global terrestrial gross and net primary productivity from the earth observing system. In: Sala O, Jackson R, Mooney H, eds. Methods in Ecosystem Science. New York: Springer-Verlag, 2000. 44–57

    Google Scholar 

  34. Zhu W Q, Pan Y Z, He H, et al. Simulation of maximum light use efficiency for some typical vegetation types in China. Chin Sci Bull, 2006, 51: 457–463

    Article  Google Scholar 

  35. Peng S L, Guo Z H, Wang B S. Use of GIS and RS to estimate the light utilization efficiency of the vegetation in Guangdong, China (in Chinese). Acta Ecol Sin, 2000, 20: 903–909

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China

    Tao Zhou, PeiJun Shi & XiuJuan Li

  2. Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs & Ministry of Education, Beijing, 100875, China

    Tao Zhou, PeiJun Shi & XiuJuan Li

  3. Key Laboratory of Regional Climate-Environment Research for Temperate East Asia, Chinese Academy of Sciences, Beijing, 100029, China

    GenSuo Jia

  4. Department of Botany and Microbiology, University of Oklahoma, Norman, OK, 73019, USA

    YiQi Luo

Authors
  1. Tao Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. PeiJun Shi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. GenSuo Jia
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. XiuJuan Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. YiQi Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tao Zhou.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zhou, T., Shi, P., Jia, G. et al. Spatial patterns of ecosystem carbon residence time in Chinese forests. Sci. China Earth Sci. 53, 1229–1240 (2010). https://doi.org/10.1007/s11430-010-3061-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11430-010-3061-9

Keywords

Search

Navigation