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Nutrient Cycling in Agroecosystems

, Volume 108, Issue 2, pp 231–244 | Cite as

Modeling farm nutrient flows in the North China Plain to reduce nutrient losses

  • Zhanqing Zhao
  • Zhaohai Bai
  • Sha Wei
  • Wenqi Ma
  • Mengru Wang
  • Carolien Kroeze
  • Lin Ma
Original Article
  • 481 Downloads

Abstract

Years of poor nutrient management practices in the agriculture industry in the North China Plain have led to large losses of nutrients to the environment, causing severe ecological consequences. Analyzing farm nutrient flows is urgently needed in order to reduce nutrient losses. A farm-level nutrient flow model was developed in this study based on the NUFER (NUtrient flows in Food chains, Environment and Resources use) model, and was used to analyze nitrogen (N) and phosphorus (P) flows, use efficiencies, and losses for nine representative farm types in the North China Plain. Data from 401 farms were evaluated for the years 2012–2015. The analysis showed that mixed farms were more efficient in nutrient utilization than crop-based or landless livestock farms. The efficiencies of N and P used in crop production were highest for mixed dairy farms, reaching 67% for N and 68% for P. Consistently, mixed dairy farms had the lowest N and P surpluses and losses in crop production. Mixed swine farms were 5 and 9% higher in N and P efficiency in livestock production than landless swine farms, respectively. Losses of N and P from the animal manure management chain were 20–42% lower for mixed swine and 69–78% lower for mixed poultry farms than for landless farms of the same animal type. This is at least partially due to more frequent manure removal. Integrated crop-livestock production using livestock wastes as crop fertilizer was shown to be the most sustainable model in nutrient use for the agriculture industry in the North China Plain.

Keywords

NUFER-farm model Farm system Nitrogen Phosphorus Use efficiency Losses North China Plain 

Notes

Acknowledgements

This study was supported through The Chinese National Basic Research Program (2015CB150405), the National Science Foundation of China (NSFC) (31572210), the National Science Foundation of China (NSFC) (31272247), The National Key Research and Development Program of China (2016YFE0103100), Key Research Program of the Chinese Academy Sciences (ZDRW-ZS-2016-5), The China Exchange Programme (CEP) of the Royal Netherlands Academy of Arts and Sciences (KNAW) (530-5CDP27), research fellowship of Wageningen Institute for Environment and Climate Research (WIMEK), PIFI of The Chinese Academy of Sciences (2015VEA025), and The Hundred Talent Program of the Chinese Academy of Sciences. We are specially grateful to the producers who participated in surveys, and to Yifei Ma, Zhibiao Wei, Zhengxing Wang, Dongdong Chen, Haodan Wang, and Liying Wang for their assistance in collection of data. We also thank Maryna Strokal for commenting on the initial draft of the manuscript and Dr. Zhiguo Wu for editing the manuscript.

Supplementary material

10705_2017_9856_MOESM1_ESM.docx (2.6 mb)
Supplementary material 1 (DOCX 2657 kb)

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Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  • Zhanqing Zhao
    • 1
    • 2
  • Zhaohai Bai
    • 1
  • Sha Wei
    • 3
  • Wenqi Ma
    • 4
  • Mengru Wang
    • 5
  • Carolien Kroeze
    • 5
  • Lin Ma
    • 1
  1. 1.Key Laboratory of Agricultural Water Resources, Center for Agricultural Resources Research, Institute of Genetics and Developmental BiologyChinese Academy of SciencesShijiazhuangChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.College of Resources and Environmental SciencesChina Agricultural UniversityBeijingChina
  4. 4.College of Resources and Environmental SciencesHebei Agricultural UniversityBaodingChina
  5. 5.Water Systems and Global Change GroupWageningen UniversityWageningenThe Netherlands

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