我国作物多性化时空变化特征及影响因素

doi:10.13304/j.nykjdb.2024.0086

中国农业科技导报 ›› 2025, Vol. 27 ›› Issue (6): 16-27.DOI: 10.13304/j.nykjdb.2024.0086

我国作物多性化时空变化特征及影响因素

王伟明¹(), 潘欣¹, 孔德平², 安宇¹, 郭爽¹, 孙志梅¹, 薛澄¹, 孙荣军³, 马文奇¹(), 许华森¹()

^1.河北农业大学资源与环境科学学院，河北省农田生态环境重点实验室，河北保定 071001
^2.沧州医学高等专科学校，河北沧州 061001
^3.河间市农业农村局，河北沧州 062450

收稿日期:2024-02-01 接受日期:2024-04-22 出版日期:2025-06-15 发布日期:2025-06-23
通讯作者: 马文奇,许华森
作者简介:王伟明 E-mail：wangweiming2022@126.com
基金资助:
国家重点研发计划项目(2021YFD1901004);河北省教育厅科学技术研究项目(QN2020147);河北省省属高等学校基本科研业务费项目(KY202013)

Spatiotemporal Characteristics and Their Influencing Factors of Crop Diversification in China

Weiming WANG¹(), Xin PAN¹, Deping KONG², Yu AN¹, Shuang GUO¹, Zhimei SUN¹, Cheng XUE¹, Rongjun SUN³, Wenqi MA¹(), Huasen XU¹()

^1.Key Laboratory of Farmland Ecology and Environment of Hebei Province，College of Resource and Environmental Sciences，Hebei Agricultural University，Hebei Baoding 071001，China
^2.Cangzhou Higher School of Medical Sciences，Hebei Cangzhou 061001，China
^3.Bureau of Agriculture and Rural Affairs of Hejian，Hebei Cangzhou 062450，China

Received:2024-02-01 Accepted:2024-04-22 Online:2025-06-15 Published:2025-06-23
Contact: Wenqi MA,Huasen XU

摘要/Abstract

摘要：

集约化生产造成农作物种植渐趋简单化，目前对我国作物多样化时空变异定量及其影响因素的研究比较缺乏。基于我国1949—2021年作物生产、耕地利用、社会经济和生产技术数据，利用时间序列变异位点检测和随机森林模型定量分析全国作物多样性的时空变化特征及其驱动因素。结果表明，在时间上，全国作物和粮食作物的多样化指数表现出多次明显历史变动，其中1991—2005年是历史最高时期。在空间上，作物和粮食作物的多样化指数均以四川盆地及周边地区为全国最高，华南区最低。在全国尺度上，农村居民人均可支配收入对作物和粮食作物多样化指数变化的贡献率最大，分别为21.0%和27.5%。在区域尺度上，在东北平原区，禾本科作物规模、豆科作物规模和农村居民人均可支配收入是影响作物和粮食作物多样化指数最高的因素；在北方干旱半干旱区和黄淮海平原区，禾本科作物规模和农村居民人均可支配收入是影响作物和粮食作物多样化指数最高的因素；在其他6个农业区，作物和粮食作物多样化指数明显受社会经济因素的影响。因此，在我国作物种植结构调整中，应根据农村经济的实际，进一步明确农业区作物生产功能定位、优化禾本科和豆科作物种植面积，以夯实粮食安全根基、推动农业绿色发展和提高农业应对气候变化能力。

关键词: 农业区, 种植结构, 作物多样化指数, 时空特征, 驱动因素

Abstract:

Intensive production has resulted in a gradual simplification of crop cultivation， but there is a lack of research on quantifying the spatial and temporal variation of crop diversification and evaluating their influencing factors in China. Based on multivariate data about crop production， arable land utilization， socio-economic and production technology from 1949 to 2021 in China， the spatiotemporal characteristics of crop diversification and their driving factors were quantitatively analyzed using generalized likelihood ratio test statistic and random forest model. The results showed that the crop diversification index （CDI） and grain crop diversification index （GCDI） across China showed several significant turning points in history， in which the highest values both were the period from 1991 to 2005. The CDI and GCDI were the greatest in the Sichuan basin and its surrounding areas， and the lowest in South China. On the national scale， the per capita disposable income of rural residents （OECDRR） accounted for the greatest percentage of identified contributing factors for the CDI and GCDI， by 21.0% and 27.5%， respectively. On the regional scale， the cereal scale advantage index，the legume scale advantage index and OECDRR were categorized as the paramount factor for the CDI and GCDI in the Northeast Plain Region. The cereal scale advantage index and OECDRR were the most common of the identified contributing factors for the CDI and GCDI in the Arid and Semi-arid Northern Region and the Huang-Huai-Hai Plain Region. In the other 6 agricultural regions， the CDI and GCDI were obviously driven by the OECDRR. Therefore， it was necessary for regulating planting structure in China to relocate the agricultural functions about crop production and optimize the cultivation area of cereals and legumes， according to the reality of the rural economy，which would consolidate the foundation of food security， promote the green development of agriculture and improve the ability of agriculture to cope with climate change.

Key words: agricultural regions, planting structure, crop diversification index, spatiotemporal characteristics, driving factors

中图分类号:

S5-3

王伟明, 潘欣, 孔德平, 安宇, 郭爽, 孙志梅, 薛澄, 孙荣军, 马文奇, 许华森. 我国作物多性化时空变化特征及影响因素[J]. 中国农业科技导报, 2025, 27(6): 16-27.

Weiming WANG, Xin PAN, Deping KONG, Yu AN, Shuang GUO, Zhimei SUN, Cheng XUE, Rongjun SUN, Wenqi MA, Huasen XU. Spatiotemporal Characteristics and Their Influencing Factors of Crop Diversification in China[J]. Journal of Agricultural Science and Technology, 2025, 27(6): 16-27.

图/表 6

图1 1949—2021年全国作物多样化指数和粮食作物多样化指数注：竖直虚线表示该年为时间序列变点；不同颜色的箱体表示该时间序列变化区间的作物多样化指数，箱体中的实线表示平均值；不同小写字母表示不同时间序列变化区间在P<0.05水平差异显著。

Fig. 1 CDI and GCDI in China from 1949 to 2021Note：The vertical dashed line indicates that this year is a changepoint in the time series； the different colored boxes represent the crops diversity index of the time series variation interval， the solid line in the boxes represent mean values； different lowercase letters indicate significant differences between different time series change interval at P<0.05 level.

图2 1949—2021年不同农业区作物多样化指数A：东北平原区；B：北方干旱半干旱区；C：黄淮海平原区；D：黄土高原区；E：长江中下游地区；F：四川盆地及周边地区；G：华南区；H：云贵高原区；I：青藏高原区。竖直虚线表示该年为时间序列变点；不同颜色的箱体表示该时间序列变化区间的作物多样化指数，箱体中的实线表示平均值；不同小写字母表示不同时间序列变化区间在P<0.05水平差异显著

Fig. 2 CDI in different agricultural regions from 1949 to 2021A： Northeast China Plain Region； B： Arid and Semi-arid Northern China Region； C： Huang-Huai-Hai Plain Region； D： Loess Plateau Region； E： Middle and Lower Reaches of the Yangtze River Region； F： Sichuan Basin and Its Surrounding Areas； G： South China Region； H： Yunnan-Guizhou Plateau Region； I： Tibetan Plateau Region. The vertical dashed line indicates that this year is a changepoint in the time series； the different colored boxes represent the crops diversity index of the time series variation interval， the solid line in the boxes represent mean values； different lowercase letters indicate significant differences between different time series change interval at P<0.05 level

图3 1949—2021年不同农业区粮食作物多样化指数A：东北平原区；B：北方干旱半干旱区；C：黄淮海平原区；D：黄土高原区；E：长江中下游地区；F：四川盆地及周边地区；G：华南区；H：云贵高原区；I：青藏高原区。竖直虚线表示该年为时间序列变点；不同颜色的箱体表示该时间序列变化区间的作物多样化指数，箱体中的实线表示平均值；不同小写字母表示不同时间序列变化区间在P<0.05水平差异显著

Fig. 3 GCDI in different agricultural regions from 1949 to 2021A： Northeast China Plain Region； B： Arid and Semi-arid Northern China Region； C： Huang-Huai-Hai Plain Region； D： Loess Plateau Region； E： Middle and Lower Reaches of the Yangtze River Region； F： Sichuan Basin and Its Surrounding Areas； G： South China Region； H： Yunnan-Guizhou Plateau Region； I： Tibetan Plateau Region. The vertical dashed line indicates that this year is a changepoint in the time series； the different colored boxes represent the crops diversity index of the time series variation interval， the solid line in the boxes represent mean values； different lowercase letters indicate significant differences between different time series change interval at P<0.05 level

图4 1949—2021年主要农业区作物多样化空间异质性注：图内实线表示均值。不同小写字母表示不同农业区间在P<0.05水平差异显著。

Fig. 4 Spatial heterogeneity of the crop diversification in major agricultural regions from 1949 to 2021Note：The solid line in the graph shows the mean value. Different lowercase letters indicate significant differences between different agricultural regions at P<0.05 level.

图5 全国作物和粮食作物多样化驱动因素的贡献度

Fig. 5 Contribution degree of driver factors for crop and grain crop diversification in China

图6 主要农业区作物和粮食作物多样化驱动因素的贡献度

Fig. 6 Contribution degree of driver factors for crop and grain crop diversification in major agricultural regions

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我国作物多性化时空变化特征及影响因素

Spatiotemporal Characteristics and Their Influencing Factors of Crop Diversification in China

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