Potential promoted productivity and spatial patterns of medium- and low-yield cropland land in China

详细信息    查看全文

• 作者：Huimin Yan ; Yongzan Ji ; Jiyuan Liu ; Fang Liu…
• 关键词：food security ; light use efficiency model ; cropland productivity ; high ; medium ; and low ; yield cropland ; potential productivity
• 刊名：Journal of Geographical Sciences
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：26
• 期：3
• 页码：259-271
• 全文大小：1,121 KB
• 参考文献：Agricultural Natural Resources and Agricultural Regional Planning Institute of Chinese Academy of Agricultural Sciences, National Soil and Fertilizer Station, 1992. Chinese Arable Land Resources and Its Exploitation. Beijing: Surveying and Mapping Press. (in Chinese)
  Albrizio R, Steduto P, 2003. Photosynthesis, respiration and conservative carbon use efficiency of four field grown crops. Agricultural and Forest Meteorology, 116(1): 19–36.CrossRef
  Ball J T, 1996. Sensitivity of leaf photosynthesis to CO2 concentration is an invariant function for C3 plants: A test with experimental data and global applications. Global Biogeochemical Cycles, 10(2): 209–222.CrossRef
  Cheng W X, Sims D A, Luo Y et al., 2000. Photosynthesis, respiration, and net primary production of sunflower stands in ambient and elevated atmospheric CO2 concentrations. Global Change Biology, 6(8): 931–941.CrossRef
  Foley J A, DeFries R, Asner G P et al., 2005. Global consequences of land use. Science, 309(5734): 570–574.CrossRef
  Foley J A, Ramankutty N, Brauman K A et al., 2011. Solutions for a cultivated planet. Nature, 478(7369): 337–342.CrossRef
  Gifford R M, 1995. Whole plant respiration and photosynthesis of wheat under increased CO2 concentration and temperature: Long-term vs. short-term distinctions for modelling. Global Change Biology, 1(6): 385–396.CrossRef
  Huang M, Ji J J, Peng L L, 2008. The response of vegetation net primary productivity to climate change during 1981–2000 in the Tibetan Plateau. Climatic and Environmental Research, 13(5): 608–617. (in Chinese)
  Kalfas J L, Xiao X, Vanegas D X et al., 2011. Modeling gross primary production of irrigated and rain-fed maize using MODIS imagery and CO2 flux tower data. Agricultural and Forest Meteorology, 151(12): 1514–1528.CrossRef
  Li F L, Li B X, Cao W X, 2005. Status and prospect of crop-yield assess by remote sensing. Journal of Yunnan Agricultural University, 5(20): 680–684. (in Chinese)
  Lin P S, 2008. Study on the distribution and possible production increase of medium and low-yield farmland in China. Beijing: Chinese Academy of Agricultural Sciences. (in Chinese)
  Liu X H, Yang Q k, Tang G A, 2001. Extraction and application of relief of China based on DEM and GIS method. Bulletin of Soil and Water Conservation, 21(1): 57–62.
  Shi Q H, Wang H, Chen F et al., 2010. The spatial-temporal distribution characteristics and yield potential of medium-low yielded farmland in China. Chinese Agricultural Science Bulletin, 26(19): 369–373. (in Chinese)
  Tilman D, Balzer C, Hill J et al., 2011. Global food demand and the sustainable intensification of agriculture. Proceedings of the National Academy of Sciences, 108(50): 20260–20264.CrossRef
  Wang Y, Huang M, Wang X G, 2010. Impacts of land use and climate change on agricultural productivity in Shanghai. Acta Scientiae Circumstantiae, 30(3): 641–648. (in Chinese)
  Wang Z, Xiao X M, Yan X D, 2010. Modeling gross primary production of maize cropland and degraded grassland in northeastern China. Agricultural and Forest Meteorology, 150(9): 1160–1167.CrossRef
  Wu B F, Du X, Meng J H et al., 2009. A remote sensing method to classify high, medium and low yield cropland and its application in Huang-Huai-Hai Basin. Modern Agricultural Development and National Food Security & Huang-Huai-Hai Modern Agricultural Development Strategy Forum Proceedings, 104–108. (in Chinese)
  Xiao X M, Hollinger D, Aber J et al., 2004. Satellite-based modeling of gross primary production in an evergreen needleleaf forest. Remote Sensing of Environment, 89(4): 519–534.CrossRef
  Yan H M, Fu Y L, Xiao X M et al., 2009. Modeling gross primary productivity for winter wheat-maize double cropping system using MODIS time series and CO2 eddy flux tower data. Agriculture, Ecosystems & Environment, 129(4): 391–400.CrossRef
  Yan H M, Liu J Y, Huang H Q et al., 2012. Impacts of cropland transformation on agricultural production under urbanization and Grain for Green Project in China. Acta Geographica Sinica, 2012, 67(5): 579–588. (in Chinese)
  Zhang L, Zhang F G, Jiang G H et al., 2005. Potential improvement of medium low yielded farmland and guarantee of food safety in China. Research of Agricultural Modernization, 26(1): 22–25. (in Chinese)
  Zhang W, Li A N, 2012. Study on the optimal scale for calculating the relief amplitude in China based on DEM. Geography and Geo-Information Science, 28(4): 8–12. (in Chinese)
  
• 作者单位：Huimin Yan (1)
  Yongzan Ji (1) (2)
  Jiyuan Liu (1)
  Fang Liu (1)
  Yunfeng Hu (1)
  Wenhui Kuang (1)
  
  1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing, 100101, China
  2. University of Chinese Academy of Sciences, Beijing, 100049, China
  
• 刊物主题：Physical Geography; Nature Conservation; Geographical Information Systems/Cartography; Remote Sensing/Photogrammetry;
• 出版者：Springer Berlin Heidelberg
• ISSN：1861-9568

文摘

With a continuously increasing population and better food consumption levels, improving the efficiency of arable land use and increasing its productivity have become fundamental strategies to meet the growing food security needs in China. A spatial distribution map of medium- and low-yield cropland is necessary to implement plans for cropland improvement. In this study, we developed a new method to identify high-, medium-, and low-yield cropland from Moderate Resolution Imaging Spectroradiometer (MODIS) data at a spatial resolution of 500 m. The method could be used to reflect the regional heterogeneity of cropland productivity because the classification standard was based on the regionalization of cropping systems in China. The results showed that the proportion of high-, medium-, and low-yield cropland in China was 21%, 39%, and 40%, respectively. About 75% of the low-yield cropland was located in hilly and mountainous areas, and about 53% of the high-yield cropland was located in plain areas. The five provinces with the largest area of high-yield cropland were all located in the Huang-Huai-Hai region, and the area amounted to 42% of the national high-yield cropland area. Meanwhile, the proportion of high-yield cropland was lower than 15% in Heilongjiang, Sichuan, and Inner Mongolia, which had the largest area allocated to cropland in China. If all the medium-yield cropland could be improved to the productive level of high-yield cropland and the low-yield cropland could be improved to the level of medium-yield cropland, the total productivity of the land would increase 19% and 24%, respectively.