湖北气候与管理因素变化对棉花单产影响的区域差异

doi:10.11821/dlyj020200266

地理研究 ›› 2021, Vol. 40 ›› Issue (4): 1064-1077.doi: 10.11821/dlyj020200266

湖北气候与管理因素变化对棉花单产影响的区域差异

孙烨琳¹^,²^,³(), 樊文有³, 史培军¹^,²^,⁴^,⁵(), 王铸⁶, 孙劭⁷

1.北京师范大学地表过程与资源生态国家重点实验室,北京 100875
2.北京师范大学地理科学学部,北京 100875
3.中国地质大学（武汉）地理与信息工程学院,武汉 430074
4.北京师范大学应急管理部-教育部减灾与应急管理研究院,北京 100875
5.青海师范大学高原科学与可持续发展研究院,西宁 810008
6.国家气象中心,北京 100081
7.国家气候中心,北京 100081

收稿日期:2020-04-03 接受日期:2020-09-07 出版日期:2021-04-19 发布日期:2021-04-10
通讯作者: 史培军
作者简介:孙烨琳（1996-）,女,福建南平人,博士研究生,主要从事气候变化与灾害风险研究。 E-mail: sunyl2019@foxmail.com
基金资助:
国家重点研发计划项目(2016YFA0602404);国家自然科学基金创新研究群体项目(41621061)

The regional difference of the influence of climate change and management factors on cotton yield in Hubei province

SUN Yelin¹^,²^,³(), FAN Wenyou³, SHI Peijun¹^,²^,⁴^,⁵(), WANG Zhu⁶, SUN Shao⁷

1. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China
2. Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
3. School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China
4. Academy of Disaster Reduction and Emergency Management, Ministry of Emergency Management & Ministry of Education, Beijing 100875, China
5. Academy of Plateau Science and Sustainability, Qinghai Normal University, Xining 810008, China
6. National Meteorological Center, Beijing 100081, China
7. National Climate Center, Beijing 100081, China

Received:2020-04-03 Accepted:2020-09-07 Online:2021-04-19 Published:2021-04-10
Contact: SHI Peijun

摘要/Abstract

摘要：

湖北省是中国重要的植棉省份之一,气候和管理因素变化对棉花生长产生重要影响。因此,本文采用1986—2016年湖北气温、降水量和太阳辐射量3个气候因子数据,有效灌溉面积、农用化肥施用量和棉花品种3个管理因素数据,构建了面板回归模型,定量计算得到气候因子和管理因素的趋势和波动变化对棉花单产的影响及其相对贡献率。结果表明：① 气候和管理因素的波动变化大于气候和管理因素的趋势变化对棉花单产的影响。② 气温和太阳辐射量对湖北省大部分地级市的棉花单产呈现正影响,降水量对湖北省大部分地级市的棉花单产呈现负影响;有效灌溉面积、农用化肥施用量和棉花品种都对湖北省大部分地级市的棉花单产呈现正影响。③ 气温、降水量和有效灌溉面积是影响湖北省大部分地级市棉花单产的主导因子。④ 1986—2016年武汉市等地级市棉花增产的主要原因是管理因素变化主导的增产抵消了气候因子变化的减产影响。

关键词: 气候变化, 趋势, 波动, 棉花, 区域差异, 湖北

Abstract:

Hubei is one of the most important cotton production provinces in China. Climate change and management factors have great impacts on cotton growth. Therefore, based on the data of temperature, precipitation, solar radiation, effective irrigated area, agricultural fertilizer application and cotton varieties in Hubei province from 1986 to 2016, a panel regression model is established to calculate the impact and relative contribution rate of the trend and fluctuation of climatic factors and management factors on cotton yield. The results show that: (1) The fluctuation of climatic factors and management factors has a greater impact on cotton yield, compared with the trend of climatic factors and management factors. (2) Temperature and solar radiation have a positive impact on cotton yield of most cities in Hubei, while precipitation has a negative impact on it. Effective irrigated area, agricultural fertilizer application and cotton varieties also have a positive impact on the cotton yield of most cities. (3) Temperature, precipitation and effective irrigated area are the leading factors affecting the cotton yield of most cities. (4) The main reason for the increase in cotton yield of Wuhan and other cities during 1986-2016 is that the positive impact of management factors on cotton yield counteracts the negative impact of climatic factors on cotton yield.

Key words: climate change, trend, fluctuation, cotton, regional differences, Hubei

孙烨琳, 樊文有, 史培军, 王铸, 孙劭. 湖北气候与管理因素变化对棉花单产影响的区域差异[J]. 地理研究, 2021, 40(4): 1064-1077.

SUN Yelin, FAN Wenyou, SHI Peijun, WANG Zhu, SUN Shao. The regional difference of the influence of climate change and management factors on cotton yield in Hubei province[J]. GEOGRAPHICAL RESEARCH, 2021, 40(4): 1064-1077.

图/表 11

图1

表1

表2

表3

表4

表5

变系数面板数据回归模型统计量"

统计量	值
$R 2$	0.7277
调整后的 $R 2$	0.6456
F统计量	8.8661
F统计量的显著性	0.0000

表5

图2

图3

图4

图5

表6

参考文献 40

[1]	IPCC. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge and New York: Cambridge University Press, 2013.
[2]	IPCC. Climate Change 2014. Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Geneva, 2014.
[3]	Liepert B G. Observed reductions of surface solar radiation at sites in the United States and worldwide from 1961 to 1990. Geophysical Research Letters, 2002, 29(10): 61-1-61-4. DOI: 10.1029/2002GL014910.
[4]	Wild M, Gilgen H, Roesch A, et al. From dimming to brightening: Decadal changes in solar radiation at Earth's surface. Science, 2005,308(5723):847-850. DOI: 10.1126/science.1103215. doi: 10.1126/science.1103215 pmid: 15879214
[5]	陈隆勋, 周秀骥, 李维亮, 等. 中国近80年来气候变化特征及其形成机制. 气象学报, 2004,62(5):634-646.
	[ Chen Longxun, Zhou Xiuji, Li Weiliang, et al. Characteristics of the climate change and its formation mechanism in China in last 80 year. Acta Meteorologica Sinica, 2004,62(5):634-646.] DOI: 10.11676/qxxb2004.062.
[6]	王遵娅, 丁一汇, 何金海, 等. 近50年来中国气候变化特征的再分析. 气象学报, 2004,62(2):228-236.
	[ Wang Zunya, Ding Yihui, He Jinhai, et al. An updating analysis of the climate change in China in recent 50 years. Acta Meteorologica Sinica, 2004,62(2):228-236.] DOI: 10.11676/qxxb2004.023.
[7]	周秀杰, 王凤玲, 吴玉影, 等. 近60年来黑龙江省与东北及全国气温变化特点分析. 自然灾害学报, 2013,22(2):124-129.
	[ Zhou Xiujie, Wang Fengling, Wu Yuying, et al. Analysis of temperature change characteristics of Heilongjiang province, Northeast China and whole country in recent 60 years. Journal of Natural Disasters, 2013,22(2):124-129.] DOI: 10.13577/j.jnd.2013.0217.
[8]	第三次气候变化国家评估报告. 第三次气候变化国家评估报告, 北京: 科学出版社, 2015.
	[ Third National Assessment Report on Climate Change. Third National Assessment Report on Climate Change. Beijing: Science Press, 2015.]
[9]	王英, 曹明奎, 陶波, 等. 全球气候变化背景下中国降水量空间格局的变化特征. 地理研究, 2006,25(6):1031-1040.
	[ Wang Ying, Cao Mingkui, Tao Bo, et al. The characteristics of spatio-temporal patterns in precipitation in China under the background of global climate change. Geographical Research, 2006,25(6):1031-1040.] DOI: 10.3321/j.issn:1000-0585.2006.06.010.
[10]	Liang F, Xia X A. Long-term trends in solar radiation and the associated climatic factors over China for 1961-2000. Annales Geophysicae, 2005,23(7):2425-2432. DOI: 10.5194/angeo-23-2425-2005.
[11]	喻树迅. 我国棉花生产现状与发展趋势. 中国工程科学, 2013,15(4):9-13.
	[ Yu Shuxun. Present situation and development trend of cotton production in China. Engineering Sciences, 2013,15(4):9-13.] DOI: 10.3969/j.issn.1009-1742.2013.04.004.
[12]	别墅, 王孝刚, 张教海, 等. 湖北省棉花产业链发展现状与展望. 中国棉花, 2011,38(11):7-14.
	[ Bie Shu, Wang Xiaogang, Zhang Jiaohai, et al. The status and development tendency of cotton industry chain in Hubei province. China Cotton, 2011,38(11):7-14.] DOI: 10.3969/j.issn.1000-632X.2011.11.002.
[13]	孙艳玲, 王宏志, 黄碧捷. 湖北棉花生产格局的时空变化及原因分析. 湖北大学学报: 自然科学版, 2005,27(4):385-388.
	[ Sun Yanling, Wang Hongzhi, Huang Bijie. Analys is on the temporal and spatial change of cotton production of Hubei province. Journal of Hubei University: Natural Science, 2005,27(4):385-388.] DOI: 10.3969/j.issn.1000-2375.2005.04.022.
[14]	岳伟, 曹雯, 姚筠, 等. 安徽省沿江地区棉花生长季气候变化特征及其对产量的影响. 长江流域资源与环境, 2014,23(9):1308-1314.
	[ Yue Wei, Cao Wen, Yao Yun, et al. Climate changes in cotton growing season along the Yangtze river in Anhui province and its influence on cotton yield. Resources and Environment in the Yangtze Basin, 2014,23(9):1308-1314.] DOI: 10.11870/cjlyzyyhj201409018.
[15]	李景林, 普宗朝, 张山清, 等. 近52年北疆气候变化对棉花种植气候适宜性分区的影响. 棉花学报, 2015,27(1):22-30.
	[ Li Jinglin, Pu Zongchao, Zhang Shanqing, et al. Impact of climate change on cotton-planting zoning in northern Xinjiang during 1961-2012. Cotton Science, 2015,27(1):22-30.]
[16]	玉苏甫·买买提, 买合皮热提·吾拉木, 满苏尔·沙比提. 气候变暖对渭干河-库车河三角洲绿洲棉花生产的影响. 地理研究, 2014,33(2):251-259.
	[ Yusuf Mamat, Mahpiret Ulam, Mansur Sabit. Impact of climate warming on cotton production of Ugan-Kuqa River delta oasis. Geographical Research, 2014,33(2):251-259.] DOI: 10.11821/dlyj201402005.
[17]	王太祥, 董舒婷. 气候变化对我国棉花产量的影响: 基于C-D-C模型的实证分析. 江苏农业科学, 2018,46(24):383-386.
	[ Wang Taixiang, Dong Shuting. Impact of climate change on cotton yield in China: An empirical analysis based on C-D-C model. Jiangsu Agricultural Sciences, 2018,46(24):383-386.] DOI: 10.15889/j.issn.1002-1302.2018.24.098.
[18]	陶磊, 褚贵新, 刘涛, 等. 有机肥替代部分化肥对长期连作棉田产量、土壤微生物数量及酶活性的影响. 生态学报, 2014,34(21):6137-6146.
	[ Tao Lei, Zhu Guixin, Liu Tao, et al. Impacts of organic manure partial substitution for chemical fertilizer on cotton yield, soil microbial community and enzyme activities in mono-cropping system in drip irrigation condition. Acta Ecologica Sinica, 2014,34(21):6137-6146.] DOI: 10.5846/stxb201301290184.
[19]	李茂松, 李章成, 王道龙, 等. 50年来我国自然灾害变化对粮食产量的影响. 自然灾害学报, 2005,14(2):55-60.
	[ Li Maosong, Li Zhangcheng, Wang Daolong, et al. Impact of natural disasters change on grain yield in China in the past 50 years. Journal of Natural Disasters, 2005,14(2):55-60.] DOI: 10.3969/j.issn.1004-4574.2005.02.010.
[20]	姜逢清, 杨德刚. 新疆棉花产量构成要素分析. 干旱区研究, 2003,20(2):104-109.
	[ Jiang Fengqing, Yang Degang. Analysis on the factors affecting the cotton yield in Xinjiang. Arid Zone Research, 2003,20(2):104-109.] DOI: 10.13866/j.azr.2003.02.005.
[21]	黄国勤, 王兴祥, 钱海燕, 等. 施用化肥对农业生态环境的负面影响及对策. 生态环境, 2004,13(4):656-660.
	[ Huang Guoqin, Wang Xingxiang, Qian Haiyan, et al. Negative impact of inorganic fertilizes application on agricultural environment and its countermeasures. Ecology and Environment, 2004,13(4):656-660.] DOI: 10.3969/j.issn.1674-5906.2004.04.055.
[22]	冯颖, 姚顺波, 郭亚军. 基于面板数据的有效灌溉对中国粮食单产的影响. 资源科学, 2012,34(9):1734-1740.
	[ Feng Ying, Yao Shunbo, Guo Yajun. Unit area crop yield response to effective irrigation in China based on a Panel Data model. Resources Science, 2012,34(9):1734-1740.]
[23]	潘奕, 王丰, 涂建华. 湖北省棉花生产变化影响因子研究. 资源开发与市场, 2008,24(2):110-111, 192.
	[ Pan Yi, Wang Feng, Tu Jianhua. Study on changing trends and effect factors of cotton production in Hubei province. Resource Development &Market, 2008,24(2):110-111, 192.] DOI: 10.3969/j.issn.1005-8141.2008.02.006.
[24]	刘定富. 湖北省棉花种业现状与发展探讨. 作物研究, 2012,26(5):565-570.
	[ Liu Dingfu. Discussion on the current situation and development of cotton seed industry in Hubei province. Crop Research, 2012,26(5):565-570.] DOI: 10.3969/j.issn.1001-5280.2012.05.43.
[25]	罗毅, 郭伟. 作物模型研究与应用中存在的问题. 农业工程学报, 2008,24(5):307-312.
	[ Luo Yi, Guo Wei. Development and problems of crop models. Transactions of the Chinese Society of Agricultural Engineering, 2008,24(5):307-312] DOI: 10.3321/j.issn:1002-6819.2008.05.069.
[26]	靳庭良, 郭建军. 面板数据模型设定存在的问题及对策分析. 数量经济技术经济研究, 2004,21(10):131-135.
	[ Ji Tingliang, Guo Jianjun. Analysis of problems in panel data model setting and countermeasures. The Journal of Quantitative & Technical Economics, 2004,21(10):131-135.] DOI: 10.3969/j.issn.1000-3894.2004.10.018.
[27]	Schlenker W, Roberts M J. Nonlinear temperature effects indicate severe damages to U.S. crop yields under climate change. Proceedings of the National Academy of Sciences of the United States of America, 2009,106(37):15594-15598. DOI: 10.1073/pnas.0906865106.
[28]	Lobell D B, Schlenker W, Costa-Roberts J. Climate trends and global crop production since 1980. Science, 2011,333(6042):616-620. DOI: 10.1126/science.1204531. doi: 10.1126/science.1204531 pmid: 21551030
[29]	林佳, 陈欢, 阳园燕, 等. 基于面板数据模型的渝西地区县域气象灾害累积天数对粮食产量的影响. 中国农业气象, 2013,34(2):210-214.
	[ Lin Jia, Chen Huan, Yang Yuan-yan, et al. Impact of cumulative meteorological disasters days on crop yields in counties of western Chongqing based on panel data model. Chinese Journal of Agrometeorology, 2013,34(2):210-214.] DOI: 10.3969/j.issn.1000-6362.2013.02.013.
[30]	Yang G Z, Zhou M Y. Multi-location investigation of optimum planting density and boll distribution of high-yielding cotton (G.hirsutum L.) in Hubei province, China. Agricultural Sciences in China, 2010,9(12):1749-1757. DOI: 10.1016/S1671-2927(09)60273-X.
[31]	胡庆芳, 杨大文, 王银堂, 等. Angstrom公式参数对ET₀的影响及FAO建议值适用性评价. 水科学进展, 2010,21(5):644-652.
	[ Hu Qingfang, Yang Dawen, Wang Yintang, et al. Effects of Angstrom coefficients on ET_o estimation and the applicability of FAO recommended coefficient values in China. Advances In Water Science, 2010,21(5):644-652.] DOI: 10.14042/j.cnki.32.1309.2010.05.001.
[32]	王静爱, 左伟. 中国地理图集. 北京: 中国地图出版社, 2009: 137.
	[ Wang Jingai, Zuo Wei. Geographic Atlas of China. Beijing: China Cartographic Publishing House, 2009: 137.]
[33]	史培军, 孙劭, 汪明, 等. 中国气候变化区划: 1961—2010年. 中国科学: 地球科学, 2014,44(10):2294-2306.
	[ Shi Peijun, Sun Shao, Wang Ming, et al. Climate Change Regionalization in China: 1961-2010. Science China: Earth Sciences, 2014,44(10):2294-2306.] DOI: 10.1007/s11430-014-4889-1.
[34]	Larson R, Farber B. Elementary Statistics. Boston: Pearson Custom Pub, 2006: 88.
[35]	Wang Z, Shi P J, Zhang Z, et al. Separating out the influence of climatic trend, fluctuations, and extreme events on crop yield: A case study in Hunan province, China. Climate Dynamics, 2018,51(11-12):4469-4487. DOI: 10.1007/s00382-017-3831-6.
[36]	Lobell D B, Gourdji S M. The influence of climate change on global crop productivity. Plant Physiology, 2012,160(4):1686-1697. DOI: 10.1104/pp.112.208298. doi: 10.1104/pp.112.208298 pmid: 23054565
[37]	肖风劲, 张海东, 王春乙, 等. 气候变化对我国农业的可能影响及适应性对策. 自然灾害学报, 2006,15(6):327-331.
	[ Xiao Fengjin, Zhang Haidong, Wang Chunyi, et al. Impact of climate change on agriculture and its adaptation countermeasures in China. Journal of Natural Disasters, 2006,15(6):327-331.] DOI: 10.13577/j.jnd.2006.S122.
[38]	郭建平. 气候变化对中国农业生产的影响研究进展. 应用气象学报, 2015,26(1):1-11.
	[ Guo Jianping. Advances in impacts of climate change on agricultural production in China. Journal of Applied Meteorological Science, 2015,26(1):1-11.] DOI: 10.11898/1001-7313.20150101.
[39]	王志勇, 白由路, 杜君, 等. 我国棉花的施肥现状、存在问题及对策. 安徽农业科学, 2010,38(32):18177-18178.
	[ Wang Zhiyong, Bai Youlu, Du Jun, et al. Research on cotton fertilize situation, problems and strategy in China. Journal of Anhui Agricultural Sciences, 2010,38(32):18177-18178.] DOI: 10.13989/j.cnki.0517-6611.2010.32.121.
[40]	梁子云. 棉花生产中存在问题及对策. 农业与技术, 2019, 39(2): 116, 124.
	[ Liang Ziyun. Problems and strategy in cotton production. Agriculture and Technology, 2019, 39(2): 116, 124.] DOI: 10.19754/j.nyyjs.20190130066.

统计量	播种期	停止生长期
平均数	4月15日	10月18日
最大值	5月8日	11月16日
最小值	3月28日	9月13日
中位数	4月14日	10月18日
众数	4月8日	10月18日

地级市名称	气候因子贡献(%)	管理因子贡献(%)	总贡献(%)
武汉市	-14.0892	30.7057	16.6165
黄石市	-6.4178	53.0933	46.6755
十堰市	20.5015	56.6868	77.1883
宜昌市	-11.1868	58.3444	47.1577
襄阳市	3.1716	59.6281	62.7997
鄂州市	1.8019	46.4367	48.2386
荆门市	7.4437	28.5022	35.9459
孝感市	-22.2687	61.4440	39.1753
荆州市	-13.9305	51.6440	37.7134
黄冈市	-19.3719	45.2710	25.8992
咸宁市	-18.2419	69.1419	50.9001
随州市	-28.6634	18.1602	-10.5032
潜江市	2.2023	81.0556	83.2579
仙桃市	-32.5449	32.7785	0.2336
天门市	-20.9155	40.6434	19.7279

湖北气候与管理因素变化对棉花单产影响的区域差异

The regional difference of the influence of climate change and management factors on cotton yield in Hubei province

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

图/表 11

参考文献 40

相关文章 15

Metrics

本文评价

推荐阅读 0

序列	Levin,Lin &Chu t^*	Im, Pesaran and Shin W-stat	ADF-Fisher Chi-Square	PP-Fisher Chi-Square
气温	0.0000	0.0000	0.0000	0.0000
降水量	0.0000	0.0000	0.0000	0.0000
太阳辐射量	0.0000	0.0000	0.0000	0.0000
有效灌溉面积	0.7819	0.7812	0.9236	0.9265
农用化肥施用量	0.2280	0.0083	0.0158	0.0068
棉花单产	0.0000	0.0000	0.0000	0.0000

[1]	田庆春, 裴瑜, 石培宏. 可可西里地区中更新世以来气候演化周期特征分析[J]. 地理研究, 2021, 40(3): 900-911.
[2]	刘桂芳, 诸云强, 关瑞敏, 冯亚飞, 刘情, 夏梦琳, 张亚星, 卢鹤立. 大数据时代中国气候变化科学数据共享服务的发展现状与趋势分析[J]. 地理研究, 2021, 40(2): 571-582.
[3]	马超, 崔培培, 钟广睿, 孟梦, 杨城, 马雯思. 气候变化和工程活动对青藏铁路沿线植被指数时空变化的影响[J]. 地理研究, 2021, 40(1): 35-51.
[4]	付阳, 陈辉, 张斯琦, 杨祎, 赵元杰. 基于群落类型的寒区旱区物候特征及其对气候因子的响应——以2000—2019年柴达木盆地为例[J]. 地理研究, 2021, 40(1): 52-66.
[5]	熊思鸿, 阎建忠, 吴雅. 农户生计对气候变化的恢复力研究综述[J]. 地理研究, 2020, 39(8): 1934-1946.
[6]	刘晓琼, 孙曦亮, 刘彦随, 张健, 赵新正, 芮旸. 基于REOF-EEMD的西南地区气候变化区域分异特征[J]. 地理研究, 2020, 39(5): 1215-1232.
[7]	张立娟, 李艳红, 任涵, 王丽园, 朱文博, 朱连奇. 气候变化背景下青冈分布变化及其对中国亚热带北界的指示意义[J]. 地理研究, 2020, 39(4): 990-1001.
[8]	张生瑞, 王英杰, 鞠洪润, 钟林生. 中国陆地边境旅游发展区域差异及其影响因素[J]. 地理研究, 2020, 39(2): 414-429.
[9]	谢舒笛, 莫兴国, 胡实, 陈学娟. 三北防护林工程区植被绿度对温度和降水的响应[J]. 地理研究, 2020, 39(1): 152-165.
[10]	王灵恩,韩禹文,高俊,吕宁,Chris Ryan. 气候变化背景下青藏高原地区游客决策与体验分析[J]. 地理研究, 2019, 38(9): 2314-2329.
[11]	张凡, 宁越敏, 娄曦阳. 中国城市群的竞争力及对区域差异的影响[J]. 地理研究, 2019, 38(7): 1664-1677.
[12]	高超, 李学文, 许莹, 李德. 淮河流域蚌埠闸以上地区夏玉米生育阶段水分供需时空变化特征研究[J]. 地理研究, 2019, 38(7): 1833-1846.
[13]	白孟鑫, 郑景云, 郝志新, 张学珍. 20世纪以来美国树木生长响应气候变化敏感度的时空差异[J]. 地理研究, 2019, 38(4): 822-830.
[14]	高新月, 戴君虎, 张明庆. 1965-2014年北京西郊地区植物观赏期对气候变化的响应[J]. 地理研究, 2018, 37(12): 2420-2432.
[15]	吴卓, 戴尔阜, 林媚珍. 气候变化和人类活动对南方红壤丘陵区森林生态系统影响模拟研究——以江西泰和县为例[J]. 地理研究, 2018, 37(11): 2141-2152.