Chinese Science Bulletin

, Volume 52, Issue 3, pp 289–302 | Cite as

Meta-analysis and its application in global change research

  • Lei XiangDong 
  • Peng ChangHui 
  • Tian DaLun 
  • Sun JianFeng 


Meta-analysis is a quantitative synthetic research method that statistically integrates results from individual studies to find common trends and differences. With increasing concern over global change, meta-analysis has been rapidly adopted in global change research. Here, we introduce the methodologies, advantages and disadvantages of meta-analysis, and review its application in global climate change research, including the responses of ecosystems to global warming and rising CO2 and O3 concentrations, the effects of land use and management on climate change and the effects of disturbances on biogeochemistry cycles of ecosystem. Despite limitation and potential misapplication, meta-analysis has been demonstrated to be a much better tool than traditional narrative review in synthesizing results from multiple studies. Several methodological developments for research synthesis have not yet been widely used in global climate change researches such as cumulative meta-analysis and sensitivity analysis. It is necessary to update the results of meta-analysis on a given topic at regular intervals by including newly published studies. Emphasis should be put on multi-factor interaction and long-term experiments. There is great potential to apply meta-analysis to global climate change research in China because research and observation networks have been established (e.g. ChinaFlux and CERN), which create the need for combining these data and results to provide support for governments’ decision making on climate change. It is expected that meta-analysis will be widely adopted in future climate change research.


meta-analysis global climate change 


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Copyright information

© Science in China Press 2007

Authors and Affiliations

  • Lei XiangDong 
    • 1
    • 2
  • Peng ChangHui 
    • 2
    • 3
  • Tian DaLun 
    • 4
  • Sun JianFeng 
    • 2
  1. 1.Institute of Forest Resource Information TechniquesChinese Academy of ForestryBeijingChina
  2. 2.ECO-MCS Lab, Institute of Environment SciencesUniversity of Quebec at Montreal (UQAM)MontrealCanada
  3. 3.Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
  4. 4.College of Life Science and TechnologyCentral-South University of Forestry and TechnologyChangshaChina

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