自然资源学报 ›› 2022, Vol. 37 ›› Issue (1): 263-276.doi: 10.31497/zrzyxb.20220118

• 其他研究论文 • 上一篇    

北方冬小麦主产区的高产与稳产关联性及其影响因素

陈晓琳1(), 谭晓悦2, 李露凝1, 陈晋1, 李强1()   

  1. 1.北京师范大学地理科学学部,北京 100875
    2.香港理工大学土地测量及地理资讯学系,香港 999077
  • 收稿日期:2020-09-10 修回日期:2020-11-16 出版日期:2022-01-28 发布日期:2022-03-28
  • 通讯作者: 李强(1967- ),女,内蒙古呼和浩特人,博士,教授,博士生导师,研究方向为区域规划与资源管理。E-mail: liqiang@bnu.edu.cn
  • 作者简介:陈晓琳(1996- ),女,福建龙岩人,硕士,研究方向为土地资源与区域发展。E-mail: 201921051120@mail.bnu.edu.cn
  • 基金资助:
    国家重点研发计划(2017YFD0300201)

The association between high-yield and stable-yield characteristics of winter wheat and its influencing factors in the main producing areas in Northern China

CHEN Xiao-lin1(), TAN Xiao-yue2, LI Lu-ning1, CHEN Jin1, LI Qiang1()   

  1. 1. Beijing Normal University, Faculty of Geographical Science, Beijing 100875, China
    2. The Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong 999077, China
  • Received:2020-09-10 Revised:2020-11-16 Online:2022-01-28 Published:2022-03-28

摘要:

冬小麦产量高低及稳定性对于保障我国粮食安全同等重要。鉴于北方冬小麦主产区受气候变化的负面影响显著,有必要从高产—稳产关联特征入手,探究全面提升冬小麦产量及稳定性的途径。基于598个县1985—2014年的单产数据,分析了冬小麦高产与稳产关联性时空分异特征,并结合气象、物候观测、农业生产要素等数据,应用无序多分类Logistic模型揭示了冬小麦高产—稳产关联特征的影响因素。主要结论为:(1)冬小麦产量随时间不断提高的同时稳定性也增强,高产性和稳产性均呈东北向西南降低的特征。(2)冬小麦高产与稳产、低产与不稳产密切关联,在研究区占据主导地位,且这两种关联类型的分布区域相对稳定,空间聚集性强。(3)灌溉条件是促进冬小麦高产—稳产的关键因素,影响随时间逐渐增强;具备灌溉条件的情况下,研究区的光温水等气象条件均比较适合冬小麦生产,但不同物候期气象要素的波动对高产和稳产均有负向影响。研究结果可为划定冬小麦优质产区和制定气候变化应对策略提供依据。

关键词: 北方冬小麦主产区, 高产—稳产关联性;, 时空分异, 无序多分类Logistic模型

Abstract:

The high yield and stable yield of winter wheat are of equal importance to ensure food security in China. In view of the significant negative impacts of climate change on winter wheat production in the main producing areas in Northern China, it is necessary to start from the association between high-yield and stable-yield characteristics to explore effective ways to improve and stabilize the yield. Based on the yield data of 598 counties from 1985 to 2014, we analyze the association between high-yield and stable-yield characteristics of winter wheat and its spatiotemporal differentiation. Combined with the meteorological data, the phenological data and the agricultural production factors data, we apply the Unordered Multinomial Logistic Model to reveal the main influencing factors that affect the high-yield and stable-yield characteristics of winter wheat. The main results show that: (1) The yield of winter wheat has increased over time while stability has also enhanced, and both high productivity and stable productivity show a decrease from northeast to southwest. (2) The high yield and stable yield, low yield and unstable yield of winter wheat are closely correlated. These two association types dominate in the study area, and their spatial distribution presents a relatively stable and aggregated pattern. (3) Among the influencing factors, the irrigation conditions are the key factors promoting the high yield and stable yield of winter wheat, with the influence gradually increasing during the study period. With irrigation conditions available, meteorological conditions such as light, temperature and water in the study area are suitable for the production of winter wheat. However, fluctuations of meteorological factors during different phenological periods have negative impacts on both high yield and stable yield of winter wheat. These findings of our study can provide references for the delineation of high-quality winter wheat producing areas and the formulation of adaptation strategies in response to climate change in China.

Key words: main producing areas of winter wheat in Northern China, high-yield and stable-yield association, spatio-temporal differentiation, Unordered Multinomial Logistic Model