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MAO Dehua, WANG Zongming, WU Changshan, SONG Kaishan, REN Chunying. Examining Forest Net Primary Productivity Dynamics and Driving Forces in Northeastern China During 1982-2010[J]. Chinese Geographical Science, 2014, (6): 631-646. doi: 10.1007/s11769-014-0662-9
Citation: MAO Dehua, WANG Zongming, WU Changshan, SONG Kaishan, REN Chunying. Examining Forest Net Primary Productivity Dynamics and Driving Forces in Northeastern China During 1982-2010[J]. Chinese Geographical Science, 2014, (6): 631-646. doi: 10.1007/s11769-014-0662-9
shu

Examining Forest Net Primary Productivity Dynamics and Driving Forces in Northeastern China During 1982-2010

doi: 10.1007/s11769-014-0662-9
  • 1.

    Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China;

  • 2.

    University of Chinese Academy of Sciences, Beijing 100049, China;

  • 3.

    Department of Geography, University of Wisconsin-Milwaukee, Milwaukee WI 53201, USA

Funds:  Under the auspices of Key Program of Chinese Academy of Sciences (No. KZZD-EW-08-02), CAS/SAFEA (Chinese Academy of Science/State Administration of Foreign Experts Affairs) International Partnership Program for Creative Research Teams (No. KZZD-EW-TZ-07), Strategic Frontier Program of Chinese Academy of Sciences-Climate Change: Carbon Budget and Relevant Issues (No. XDA05050101)
More Information
  • Corresponding author: WANG Zongming. E-mail: zongmingwang@neigae.ac.cn
  • Received Date: 2012-11-27
  • Rev Recd Date: 2013-03-11
  • Publish Date: 2014-09-27
  • Forest net primary productivity (NPP) is a key parameter for forest monitoring and management. In this study, monthly and annual forest NPP in the northeastern China from 1982 to 2010 were simulated by using Carnegie-Ames-Stanford Approach (CASA) model with normalized difference vegetation index (NDVI) sequences derived from Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) products. To address the problem of data inconsistency between AVHRR and MODIS data, a per-pixel unary linear regression model based on least squares method was developed to derive the monthly NDVI sequences. Results suggest that estimated forest NPP has mean relative error of 18.97% compared to observed NPP from forest inventory. Forest NPP in the northeastern China increased significantly during the twenty-nine years. The results of seasonal dynamic show that more clear increasing trend of forest NPP occurred in spring and autumn. This study also examined the relationship between forest NPP and its driving forces including the climatic and anthropogenic factors. In spring and winter, temperature played the most pivotal role in forest NPP. In autumn, precipitation acted as the most important factor affecting forest NPP, while solar radiation played the most important role in the summer. Evaportranspiration had a close correlation with NPP for coniferous forest, mixed coniferous broadleaved forest, and broadleaved deciduous forest. Spatially, forest NPP in the Da Hinggan Mountains was more sensitive to climatic changes than in the other ecological functional regions. In addition to climatic change, the degradation and improvement of forests had important effects on forest NPP. Results in this study are helpful for understanding the regional carbon sequestration and can enrich the cases for the monitoring of vegetation during long time series.
  • [1] Allen R G, Pereira L S, Raes D, 1998. Crop evapotranspiration-Guidelines for computing crop water requirements. In: FAO Irrigation and Drainage. Rome: FAO, 13-56.
    [2] Bai Z, Dent D, 2009. Recent land degradation and improvement in China. AMBIO, 38(3): 150-156. doi: 10.1579/0044-7447- 38.3.150
    [3] EBVMC (Editorial Board of Vegetation Map of China, Chinese Academy of Sciences), 2001. Vegetation Regionalization Map of China. Beijing: Science Press. (in Chinese)
    [4] Fang J, Chen A, Peng C et al., 2001a. Changes in forest biomass carbon storage in China between 1949 and 1998. Science, 292(5525): 2320-2322. doi:  10.1126/science.1058629
    [5] Fang J, Piao S, Tang Z et al., 2001b. Interannual variability in net primary production and precipitation. Science, 293(5536): 1723. doi:  10.1126/science.293.5536.1723a
    [6] Field C B, Randerson J T, Malmstrom C M, 1995. Global net primary production: Combining ecology and remote sensing. Remote Sensing of Environment, 51(1): 74-88. doi:  10.1016/0034-4257(94)00066-V
    [7] Fu Bojie, Liu Guohua, Chen Liding et al., 2001. Scheme of ecological regionalization in China. Acta Ecologica Sinica, 21(1): 1-6. (in Chinese)
    [8] Guo Zhixing, Wang Zongming, Song Kaishan et al., 2007. Correlations between forest vegetation NDVI and water-thermal condition in Northeast China forest regions in 1982-2003. Chinese Journal of Ecology, 26(12): 1930-1936. (in Chinese)
    [9] Guo Zhixing, Wang Zongming, Zhang Bai et al., 2008. Analysis of temporal-spatial characteristics and factors influencing vegetation NPP in Northeast China from 2000 to 2006. Resources Science, 30(8): 1226-1235. (in Chinese)
    [10] Huang N, Niu Z, Wu C et al., 2010. Modeling net primary production of a fast-growing forest using a light use efficiency model. Ecological Modelling, 221(24): 2938-2948. doi:  10.1016/j.ecolmodel.2010.08.041
    [11] Jin H, Li S, Cheng G et al., 2000. Permafrost and climatic change in China. Global and Planetary Change, 26(4): 387-404. doi:  10.1016/S0921-8181(00)00051-5
    [12] Liu J, Li S, Ouyang Z et al., 2008. Ecological and socioeconomic effects of China's policies for ecosystem services. PNAS, 105(28): 9477-9482. doi:  10.1073/pnas.0706436105
    [13] Liu Jiyuan, Zhang Zengxiang, Xu Xinliang et al., 2009. Spatial patterns and driving forces of land use change in China in the early 21st century. Acta Geographica Sinica, 64(12): 1411- 1420. (in Chinese)
    [14] Liu Jiyuan, Zhang Zengxiang, Zhuang Dafang et al., 2003. A study on the spatial-temporal dynamics changes of land-use and driving forces analyses of China in the 1990s. Geographical Research, 22(1): 1-12. (in Chinese)
    [15] Liu Yansui, Peng Liuying, Chen Yufu, 2005. Conversion of land use types and ecological effect in Northeast China. Transactions of the CSAE, 21(10): 175-178. (in Chinese)
    [16] Long Huiling, Li Xiaobing, Wang Hong et al., 2010. Net primary productivity (NPP) of grassland ecosystem and its relationship with climate in Inner Mongolia. Acta Ecologica Sinica, 30(5): 1367-1378. (in Chinese)
    [17] Lu D, Xu X, Tian H et al., 2010. The effects of urbanization on net primary productivity in southeastern China. Environment Management, 46(3): 404-410. doi:  10.1007/s00267-010-9542-y
    [18] Luo Tianxiang, 1996. Patterns of Biological Production and Its Mathematical Models for Main Forest Types of China. Beijing: Graduate School, Chinese Academy of Sciences. (in Chinese)
    [19] Mao D, Wang Z, Luo L et al., 2012. Integrating AVHRR and MODIS data to monitor NDVI changes and their relationships with climatic parameters in Northeast China. International Journal of Applied Earth Observation and Geoinformation, 18: 528-536. doi:  10.1016/j.jag.2011.10.007
    [20] Mao Dehua, Wang Zongming, Luo Ling et al., 2010. Growing-season normalized difference vegetation index, NDVI, response to climate changes and increased carbon dioxide concentration in frozen areas of Northeast China during 1982- 2008. Acta Scientiae Circumstantiae, 30(11): 2332-2342. (in Chinese)
    [21] Melillo J M, McGurie A D, Kicklighter D W et al., 1993. Global climate change and terrestrial net primary production. Nature, 363(6426): 234-240. doi:  10.1038/363234a0.
    [22] Nemani R R, Keeling C D, Hashimoto H et al., 2003. Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science, 300(5625): 1560-1563. doi:  10.1126/science.1082750
    [23] Pan Y, Birdsey R, Fang J et al., 2011. A large and persistent carbon sink in the world's forests. Science, 333(6045): 988-993. doi:  10.1126/science.1201609
    [24] Peng D, Huang J, Huete A R et al., 2010. Spatial and seasonal
    [25] charac­terization of net primary productivity and climate variables in southeastern China using MODIS data. Journal of Zhejiang University, 11(4): 275-285. doi: 10.1631/jzus. B0910501
    [26] Piao S, Fang J, Ciais P et al., 2009. The carbon balance of terrestrial ecosystems in China. Nature, 458(7241): 1009-1014. doi:  10.1038/nature07944
    [27] Piao S, Fang J, Zhou L et al., 2003. Interannual variations of monthly and seasonal normalized difference vegetation index (NDVI) in China from 1982 to 1999. Journal of Geophysical Research: Atmospheres, 108(D14). doi:  10.1029/2002JD002848
    [28] Piao S, Fang J, Zhou L, 2005. Changes in vegetation net primary productivity from 1982 to 1999 in China. Global Biogeochemical Cycles, 19(2): GB2027. doi:  10.1029/004GB002274
    [29] Piao Shilong, Fang Jingyun, Chen Anping, 2003. Seasonal dynamics of terrestrial net primary production in responses to climate changes in China. Acta Botanica Sinica, 45(3): 269- 275. (in Chinese)
    [30] Piao Shilong, Fang Jingyun, Guo Qinghua, 2001. Application of CASA model to the estimation of Chinese terrestrial net primary productivity. Acta Phytoecologica Sinica, 25(5): 603- 608. (in Chinese)
    [31] Potter C S, Klooster S, Genovese V, 2012. Net primary production of terrestrial ecosystems from 2000 to 2009. Climatic Change, 115(2): 365-378. doi:  10.1007/s10584-01200460-2
    [32] Potter C S, Randerson J T, Field C B et al., 1993. Terrestrial ecosystem production: A process model based on global satellite and surface data. Global Biogeochemical Cycles, 7(4): 811- 841. doi:  10.1029/93GB02725
    [33] Seaquist J W, Olsson L, Ardo J, 2003. A remote sensing based primary production model for grassland biomass. Ecological Modeling, 169(1): 131-155. doi: 10.1016/S0304-3800(03) 00267-9
    [34] Sun Rui, Zhu Qijiang, 2001. Effect of climate change of terrestrial net primary productivity in China. Journal of Remote Sensing, 5(1): 58-61. (in Chinese)
    [35] Tagesson T, Smith B, Lofgren A, 2009. Estimating net primary production of Swedish forest landscapes by combining mechanistic modeling and remote sensing. AMBIO, 38(6): 316-324. doi:  10.1579/08-A-513.1
    [36] Tan K, Piao S, Peng C 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): 114-121. doi:  10.1016/j.foreco.2006.12.018
    [37] Wang Zongming, Zhang Bai, Song Kaishan et al., 2009. Land use changes in Northeast China driven by human activities and climatic variation. Chinese Geographical Science, 19(3): 225-230. doi:  10.1007/s11769-009-0225-7
    [38] Xu Xinliang, Liu Jiyuan, Zhuang Dafang et al., 2004a. Analysis on spatial-temporal characteristics and driving factors of woodland change in Northeastern China based on 3S technology. Scientia Geographica Sinica, 24(1): 55-60. (in Chinese)
    [39] Xu Xinliang, Liu Jiyuan, Zhuang Dafang et al., 2004b. Spatial-Temporal characteristics and driving factors of woodland resource changes in China. Journal of Beijing Forest University, 26(1): 41-46. (in Chinese)
    [40] Yan Q, Zhu J, Hu Z et al., 2011. Environmental impacts of the shelter forests in Horqin sandy land, Northeast China. Journal of Environmental Quality, 40(3): 815-824. doi:  10.2134/jeq2010.0137
    [41] Yang Z, Ouyang Y, Xu X et al., 2010. Effects of permafrost degradation on ecosystems. Acta Ecologica Sinica. 30(1): 33-39. doi:  10.1016/j.chnaes.2009.12.006
    [42] Yao J, He X, Li X et al., 2011. Monitoring responses of forest to climate variations by MODIS NDVI: A case study of Hun River upstream, northeastern China. European Journal of Forest Research, 131(3): 705-716. doi: 10.1007/s10342-011- 0543-z
    [43] Yu D, Shao H, Shi P et al., 2009a. How does the conversion of land cover to urban use affect net primary productivity? A case study in Shenzhen city, China. Agricultural and Forest Meteorology, 149(11): 2054-2060. doi: 10.1016/j.agrformet.2009. 07.012
    [44] Yu D, Shi P, Shao H et al., 2009b. Modeling net primary productivity of terrestrial ecosystems in East Asia based on an improved CASA ecosystem model. International Journal of Remote Sensing, 30(18): 4851-4866. doi: 10.1080/0143116080 2680552
    [45] Yuan Jinguo, Niu Zheng, Wang Chenli, 2006. Vegetation NPP distribution based on MODIS data and CASA model—A case study of Northern Heibei province. Chinese Geographical Science, 16(4): 334-341. doi:  10.1007/s11769-006-0334-5
    [46] Zhang Pingyu, 2008. Revitalizing old industrial base of Northeast China: Process, policy and challenge. Chinese Geographical Science, 18(2): 109-118. doi:  10.1007/s11769-008-0109-2
    [47] Zhao Guoshuai, Wang Junbang, Fan Wenyi et al., 2011. Vegetation net primary productivity in Northeast China in 2000-2008: Simulation and seasonal change. Chinese Journal of Applied Ecology, 22(3): 621-630. (in Chinese)
    [48] Zhou Guangsheng, Zhang Xinshi, 1995. A natural vegetation NPP model. Acta Phytoecologica Sinica, 19(3): 193-200. (in Chinese)
    [49] Zhou Youwu, Guo Dongxin, Qiu Guoqing et al., 2000. Geocryo­logy in China. Beijing: Science Press, 26-30, 40-42. (in Chinese)
    [50] Zhu W, Pan Y, Liu X et al., 2006a. Spatio-temporal distribution of net primary productivity along the Northeast China transect and its responses to climatic change. Journal of Forestry Research, 17(2): 93-98. doi:  10.1007/s11676-006-0022-4
    [51] Zhu Wenquan, Pan Yaozhong, He Hap et al., 2006b. Simulation of the maximum light use efficiency for typical vegetation in China. Chinese Science Bulletin, 51(6): 700-706. (in Chinese)
    [52] Zhu Wenquan, Pan Yaozhong, Yang Xiaoqiong et al., 2007a. Influence analysis of climatic changes on terrestrial vegetation net primary productivity in China. Chinese Science Bulletin, 52(21): 2535-2541. (in Chinese)
    [53] Zhu Wenquan, Pan Yaozhong, Zhang Jinshui, 2007b. Estimation of net primary productivity of Chinese terrestrial vegetation based on remote sensing. Journal of Plant Ecology, 31(3): 413-424. (in Chinese)
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Examining Forest Net Primary Productivity Dynamics and Driving Forces in Northeastern China During 1982-2010

doi: 10.1007/s11769-014-0662-9
  • 1. Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China;
  • 2. University of Chinese Academy of Sciences, Beijing 100049, China;
  • 3. Department of Geography, University of Wisconsin-Milwaukee, Milwaukee WI 53201, USA
Funds:  Under the auspices of Key Program of Chinese Academy of Sciences (No. KZZD-EW-08-02), CAS/SAFEA (Chinese Academy of Science/State Administration of Foreign Experts Affairs) International Partnership Program for Creative Research Teams (No. KZZD-EW-TZ-07), Strategic Frontier Program of Chinese Academy of Sciences-Climate Change: Carbon Budget and Relevant Issues (No. XDA05050101)
    Corresponding author: WANG Zongming. E-mail: zongmingwang@neigae.ac.cn
  • Received Date: 2012-11-27
  • Rev Recd Date: 2013-03-11
  • Publish Date: 2014-09-27

Abstract: Forest net primary productivity (NPP) is a key parameter for forest monitoring and management. In this study, monthly and annual forest NPP in the northeastern China from 1982 to 2010 were simulated by using Carnegie-Ames-Stanford Approach (CASA) model with normalized difference vegetation index (NDVI) sequences derived from Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) products. To address the problem of data inconsistency between AVHRR and MODIS data, a per-pixel unary linear regression model based on least squares method was developed to derive the monthly NDVI sequences. Results suggest that estimated forest NPP has mean relative error of 18.97% compared to observed NPP from forest inventory. Forest NPP in the northeastern China increased significantly during the twenty-nine years. The results of seasonal dynamic show that more clear increasing trend of forest NPP occurred in spring and autumn. This study also examined the relationship between forest NPP and its driving forces including the climatic and anthropogenic factors. In spring and winter, temperature played the most pivotal role in forest NPP. In autumn, precipitation acted as the most important factor affecting forest NPP, while solar radiation played the most important role in the summer. Evaportranspiration had a close correlation with NPP for coniferous forest, mixed coniferous broadleaved forest, and broadleaved deciduous forest. Spatially, forest NPP in the Da Hinggan Mountains was more sensitive to climatic changes than in the other ecological functional regions. In addition to climatic change, the degradation and improvement of forests had important effects on forest NPP. Results in this study are helpful for understanding the regional carbon sequestration and can enrich the cases for the monitoring of vegetation during long time series.

MAO Dehua, WANG Zongming, WU Changshan, SONG Kaishan, REN Chunying. Examining Forest Net Primary Productivity Dynamics and Driving Forces in Northeastern China During 1982-2010[J]. Chinese Geographical Science, 2014, (6): 631-646. doi: 10.1007/s11769-014-0662-9
Citation: MAO Dehua, WANG Zongming, WU Changshan, SONG Kaishan, REN Chunying. Examining Forest Net Primary Productivity Dynamics and Driving Forces in Northeastern China During 1982-2010[J]. Chinese Geographical Science, 2014, (6): 631-646. doi: 10.1007/s11769-014-0662-9
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