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Estimation of net primary productivity using a process-based model in Gansu Province, Northwest China

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Abstract

The ecological structure in the arid and semi-arid region of Northwest China with forest, grassland, agriculture, Gobi, and desert, is complex, vulnerable, and unstable. It is a challenging and sustaining job to keep the ecological structure and improve its ecological function. Net primary productivity (NPP) modeling can help to improve the understanding of the ecosystem, and therefore, improve ecological efficiency. The boreal ecosystem productivity simulator (BEPS) model provides the possibility of NPP modeling in terrestrial ecosystem, but it has some limitations for application in arid and semi-arid regions. In this paper, we improve the BEPS model, in terms of its water cycle by adding the processes of infiltration and surface runoff, to be applicable in arid and semi-arid regions. We model the NPP of forest, grass, and crop in Gansu Province as an experimental area in Northwest China in 2003 using the improved BEPS model, parameterized with moderate resolution remote sensing imageries and meteorological data. The modeled NPP using improved BEPS agrees better with the ground measurements in Qilian Mountain than that with original BEPS, with a higher R 2 of 0.746 and lower root mean square error (RMSE) of 46.53 gC m−2 compared to R 2 of 0.662 and RMSE of 60.19 gC m−2 from original BEPS. The modeled NPP of three vegetation types using improved BEPS shows evident differences compared to that using original BEPS, with the highest difference ratio of 9.21 % in forest and the lowest value of 4.29 % in crop. The difference ratios between different vegetation types lie on the dependence on natural water sources. The modeled NPP in five geographic zones using improved BEPS is higher than those with original BEPS, with higher difference ratio in dry zones and lower value in wet zones.

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Notes

  1. Source: Ministry of Commerce of the People’s Republic of China Website (http://english.mofcom.gov.cn/aroundchina/Gansu.shtml).

  2. Refer to: Baidu (http://baike.baidu.com/view/8461.htm) and Wikipedia (http://en.wikipedia.org/wiki/Gansu).

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Acknowledgments

We would like to thank Prof. J. Chen and his group in affording the initial BEPS model. We also gratefully acknowledge the anonymous reviewers for their valuable comments on the manuscript. The study was funded by the National Natural Science Foundation of China (No. 40901170 and 41071224), the Basic Research and Operating Expenses of CAMS (No. 2010Y004), and the National Basic Research Program of China (No. 2010CB951304).

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Authors and Affiliations

  1. Chinese Academy of Meteorological Sciences, Beijing, 100081, China

    Peijuan Wang & Youhao E

  2. State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing Applications of Chinese Academy of Sciences, Beijing, 100875, China

    Donghui Xie & Qijiang Zhu

  3. Joint Global Change Research Institute, 5825 University Research Court, Suite 3500, College Park, MD, 20740, USA

    Yuyu Zhou

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  1. Peijuan Wang
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  2. Donghui Xie
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  3. Yuyu Zhou
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  4. Youhao E
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  5. Qijiang Zhu
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Correspondence to Peijuan Wang.

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Wang, P., Xie, D., Zhou, Y. et al. Estimation of net primary productivity using a process-based model in Gansu Province, Northwest China. Environ Earth Sci 71, 647–658 (2014). https://doi.org/10.1007/s12665-013-2462-4

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  • DOI: https://doi.org/10.1007/s12665-013-2462-4

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