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Uncertainty of forest biomass carbon patterns simulation on provincial scale: A case study in Jiangxi Province, China

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Abstract

Forest vegetation carbon patterns are significant for evaluating carbon emission and accumulation. Many methods were used to simulate patterns of forest vegetation carbon stock in previous studies, however, uncertainty apparently existed between results of different methods, even estimates of same method in different studies. Three previous methods, including Atmosphere-vegetation interaction model 2 (AVIM2), Kriging, Satellite-data Based Approach (SBA), and a new method, High Accuracy Surface Modeling (HASM), were used to simulate forest vegetation carbon stock patterns in Jiangxi Province in China. Cross-validation was used to evaluate methods. The uncertainty and applicability of the four methods on provincial scale were analyzed and discussed. The results showed that HASM had the highest accuracy, which improved by 50.66%, 33.37% and 28.58%, compared with AVIM2, Kriging and SBA, respectively. Uncertainty of simulation of forest biomass carbon stock was mainly derived from modeling error, sampling error and statistical error of forest area. Total forest carbon stock, carbon density and forest area of Jiangxi were 288.62 Tg, 3.06 kg/m2 and 94.32×109 m2 simulated by HASM, respectively.

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References

  • Brown Sandra, Lugo Ariel E, 1984. Biomass of tropical forests: A new estimate based on forest volumes. Science, 223(4642): 1290–1293.

    Article  Google Scholar 

  • Cao Mingkui, Woodward F IaN, 1998. Net primary and ecosystem production and carbon stocks of terrestrial ecosystems and their responses to climate change. Global Change Biology, 4: 185–198.

    Article  Google Scholar 

  • Chen Chuanfa, Yue Tianxiang, 2010. A method of DEM construction and related error analysis. Computers & Geosciences, 36: 717–725.

    Article  Google Scholar 

  • Chen Chuanfa, Li Yanyan, Yue Tianxiang, 2013a. Surface modeling of DEMs based on a sequential adjustment method. International Journal of Geographical Information Science, 27: 1272–1291.

    Article  Google Scholar 

  • Chen Chuanfa, Yue Tianxiang, Dai Honglei et al., 2013b. The smoothness of HASM. International Journal of Geographical Information Science, 27: 1651–1667.

    Article  Google Scholar 

  • Dixon R K, Brown S, Houghton R A et al., 1994. Carbon pools and flux of global forest ecosystems. Science, 263: 185–188.

    Article  Google Scholar 

  • Fan Zemeng, Li Jing, Yue Tianxiang, 2013. Land-cover changes of biome transition zones in Loess Plateau of China. Ecological Modelling, 252: 129–140.

    Article  Google Scholar 

  • Fang Jingyun, Chen Anping, Peng Changhui et al., 2001. Changes in forest biomass carbon storage in China between 1949 and 1998. Science, 292(5525): 2320–2322.

    Article  Google Scholar 

  • Fang Jingyun, Guo Zhaodi, Piao Shilong et al., 2007. Terrestrial vegetation carbon sinks in China, 1981–2000. Science in China Series D-Earth Sciences, 50(9): 1341–1350.

    Article  Google Scholar 

  • Fang Jingyun, Liu Guohua, Xu Songling, 1996, Biomass and net production of forest vegetation in China. Acta Ecologica Sinica, 16(5): 497–508. (in Chinese)

    Google Scholar 

  • Fang Jingyun, Wang G Geoff, Liu Guohua et al., 1998. Forest biomass of China: An estimate based on the biomass-volume relationship. Ecological Applications, 8(4): 1084–1091.

    Google Scholar 

  • Foody Giles M, Boyd Doreen S, Cutler Mark E J, 2003. Predictive relations of tropical forest biomass from Landsat TM data and their transferability between regions. Remote Sensing of Environment, 85(4): 463–474.

    Article  Google Scholar 

  • Huang Mei, 2005. Simulation of water, heat flux and carbon cycle of terrestrial ecosystem in China [D]. Beijing: Institute of Geographic Sciences and Natural Resources Research, CAS. (in Chinese)

    Google Scholar 

  • IPCC, 2007. Climate Change 2007: Impacts, Adaptation, and Vulnerability. New York: Cambridge University Press.

    Google Scholar 

  • Ji Jinjun, Huang Mei, Li Kerang, 2008. Prediction of carbon exchanges between China terrestrial ecosystem and atmosphere in 21st century. Science in China, Series D-Earth Sciences, 51(6): 885–898.

    Article  Google Scholar 

  • Kleijnen Jack P C, 2009. Kriging metamodeling in simulation: A review. European Journal of Operational Research, 192(3): 707–716.

    Article  Google Scholar 

  • Krige D G, 1951. A statistical approach to some basic mine valuation problems on the Witwatersrand. The Journal of the Chemical, Metallurgical and Mining Society of South Africa, 52(6): 119–139.

    Google Scholar 

  • Li Haikui, Lei Yuancai, Zeng Weisheng, 2011. Forest carbon storage in China estimated using forestry inventory data. Scientia Silvae Sinicae, 47(7): 7–12. (in Chinese)

    Google Scholar 

  • Li Kerang, Wang Shaoqiang, Cao Mingkui, 2003. Vegetation and soil carbon stock of China. Science in China, Series D-Earth Sciences, 33(1): 72–80. (in Chinese)

    Google Scholar 

  • Li Xin, Ouyang Xunzhi, Liu Qijing, 2011. Carbon storage of forest vegetation and its geographical pattern in China’s Jiangxi Province during 2001–2005. Journal of Natural Resources, 26(4): 655–665. (in Chinese)

    Google Scholar 

  • Nie Daoping, 1994. Structural dynamics of bamboo forest stands. Scientia Silvae Sinicae, 30(3): 201–208. (in Chinese)

    Google Scholar 

  • Pan Yude, Birdsey Richard A, Fang Jingyun et al., 2011. A large and persistent carbon sink in the world’s forests. Science, 333(6045): 988–993.

    Article  Google Scholar 

  • Pan Yude, Luo Tianxiang, Birdsey Richard A et al., 2004. New estimates of carbon storage and sequestration in China’s forests: Effects of age-class and method on inventory-based carbon estimation. Climatic Change, 67(2/3): 211–236.

    Article  Google Scholar 

  • Parton W J, Schimel D S, Cole C V et al., 1987. Analysis of factors controlling soil organic-matter levels in great-plains grasslands. Soil Science Society of America Journal, 51(5): 1173–1179.

    Article  Google Scholar 

  • 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.

    Article  Google Scholar 

  • Piao Shilong, Fang Jingyun, Zhu Biao et al., 2005. Forest biomass carbon stocks in China over the past 2 decades: Estimation based on integrated inventory and satellite data. Journal of Geophysical Research-Biogeosciences, 110(G1): 12.

    Article  Google Scholar 

  • Ren Yin, Wei Xiaohua, Zhang Li et al., 2011. Potential for forest vegetation carbon storage in Fujian Province, China, determined from forest inventories. Plant and Soil, 345(1/2): 125–140.

    Article  Google Scholar 

  • Running Steven W, 1994. Testing forest: BGC ecosystem process simulations across a climatic gradient in Oregon. Ecological Applications, 4(2): 238–247.

    Article  Google Scholar 

  • Sales Marcio H, Souza Carlos M, Kyriakidis Phaedon C et al., 2007. Improving spatial distribution estimation of forest biomass with geostatistics: A case study for Rondonia, Brazil. Ecological Modelling, 205(1/2): 221–230.

    Article  Google Scholar 

  • Shi Wenjiao, Liu Jiyuan, Du Zhengping et al., 2009. Surface modelling of soil pH. Geoderma, 150(1/2): 113–119.

    Article  Google Scholar 

  • Shi Wenjiao, Liu Jiyuan, Du Zhengping et al., 2011. Surface modeling of soil properties based on land use information. Geoderma, 162: 347–357.

    Article  Google Scholar 

  • Shi Wenjiao, Liu Jiyuan, Du Zhengping et al., 2012. Development of a surface modeling method for mapping soil properties. International Journal of Geographical Information Science, 2012, 22(4): 752–760.

    Google Scholar 

  • Sitch S, Smith B, Prentice I C et al., 2003. Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ Dynamic Global Vegetation Model. Global Change Biology, 9(2): 161–185.

    Article  Google Scholar 

  • Sun Xiaofang, Yue Tianxiang, Wang Qing, 2013. High accuracy surface modeling of grassland aboveground biomass. Journal of Remote Sensing, 17(5): 1060–1076. (in Chinese)

    Google Scholar 

  • Tan Kun, Piao Shilong, Peng Changhui et al., 2007. Satellite-based estimation of biomass carbon stocks for northeast China’s forests between 1982 and 1999. Forest Ecology and Management, 240(1–3): 114–121.

    Article  Google Scholar 

  • Wang Bin, Liu Moucheng, Zhang Biao, 2009. Dynamics of net production of Chinese forest vegetation based on forest inventory data. Forest Resource Management, 1: 35–43. (in Chinese)

    Google Scholar 

  • Wang Xiaoke, Feng Zongwei, Ouyang Zhixun, 2001. The impact of human disturbance on vegetative carbon storage in forest ecosystems in China. Forest Ecology and Management, 148(1–3): 117–123.

    Article  Google Scholar 

  • Xu Xinliang, Cao Mingkui, Li Kerang, 2007. Temporal-spatial dynamics of carbon storage of forest vegetation in China. Progress in Geography, 26(6): 1–10. (in Chinese)

    Google Scholar 

  • Yao Z Y, Liu J J, Zhao X W et al., 2015. Spatial dynamics of aboveground carbon stock in urban green space: A case study of Xi’an, China. Journal of Arid Land, 7(3): 350–360.

    Article  Google Scholar 

  • Yue Tianxiang, Du Zhengping, Song Dunjiang et al., 2007. A new method of surface modeling and its application to DEM construction. Geomorphology, 91: 161–172.

    Article  Google Scholar 

  • Yue Tianxiang, Tian Yongzhong, Liu Jiyuan et al., 2008. Surface modeling of human carrying capacity of terrestrial ecosystems in China. Ecological Modelling, 214(2–4): 168–180.

    Article  Google Scholar 

  • Yue Tianxiang, Song Dinjiang, Du Zhengping et al., 2010. High-accuracy surface modelling and its application to DEM generation. International Journal of Remote Sensing, 31(8): 2205–2226.

    Article  Google Scholar 

  • Yue Tianxiang, 2011. Surface Modelling: High Accuracy and High Speed Methods. New York: CRC Press.

    Book  Google Scholar 

  • Yue Tianxiang, Fan Zemeng, Chen Chuanfa et al., 2011. Surface modelling of global terrestrial ecosystems under three climate change scenarios. Ecological Modelling, 222(14): 2342–2361.

    Article  Google Scholar 

  • Yue Tianxiang, Zhao Na, Ramsey R Douglas et al., 2013a. Climate change trend in China, with improved accuracy. Climatic Change, 120(1/2): 137–151.

    Article  Google Scholar 

  • Yue Tianxiang, Zhao Na, Yang Hai et al., 2013b. The multi-grid method of high accuracy surface modelling and its validation. Trans GIS, 17(6): 943–952.

    Article  Google Scholar 

  • Zhang Chunhua, Ju Weimin, Chen Jing M et al., 2013. China’s forest biomass carbon sink based on seven inventories from 1973 to 2008. Climatic Change, 118(3/4): 933–948.

    Article  Google Scholar 

  • Zhao Mingwei, Yue Tianxiang, Zhao Na et al., 2014. Combining LPJ-guess and HASM to simulate the spatial distribution of forest vegetation carbon stock in China. Journal of Geographical Sciences, 24(2): 249–268.

    Article  Google Scholar 

  • Zhao Na, Yue Tianxiang, 2014a. A modification of HASM for interpolating precipitation in China. Theoretical and Applied Climatology, 116: 273–285.

    Article  Google Scholar 

  • Zhao Na, Yue Tianxiang, 2014b. Sensitivity studies of a high accuracy surface modelling method. Science China-Earth Sciences, 57: 1–11.

    Google Scholar 

Download references

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Authors and Affiliations

  1. State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing, 100101, China

    Yifu Wang, Tianxiang Yue & Zhengping Du

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Yifu Wang & Tianxiang Yue

  3. Chinese Academy of Forestry, Beijing, 100091, China

    Yuancai Lei

  4. Anhui Center for Collaborative Innovation in Geographical Information Integration and Application, Chuzhou University, Chuzhou, 239012, Anhui, China

    Mingwei Zhao

Authors
  1. Yifu Wang
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  2. Tianxiang Yue
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  3. Yuancai Lei
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  4. Zhengping Du
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  5. Mingwei Zhao
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Corresponding author

Correspondence to Tianxiang Yue.

Additional information

Foundation: National Fundamental R&D Program of the Ministry of Science and Technology of the People’s Republic of China, No.2013FY111600-4

Author: Wang Yifu (1990–), PhD Candidate, specialized in ecological modeling and system simulation.

Yue Tianxiang (1963–), PhD and Professor

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Wang, Y., Yue, T., Lei, Y. et al. Uncertainty of forest biomass carbon patterns simulation on provincial scale: A case study in Jiangxi Province, China. J. Geogr. Sci. 26, 568–584 (2016). https://doi.org/10.1007/s11442-016-1286-z

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  • DOI: https://doi.org/10.1007/s11442-016-1286-z

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