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不同降水年型下温度升高对旱地春小麦产量的影响

本站小编 Free考研考试/2022-01-01
聂志刚1,,
冯仰强1,,,
董莉霞1,
王钧1,
李广2
1.甘肃农业大学信息科学技术学院 兰州 730070
2.甘肃农业大学林学院 兰州 730070
基金项目: 甘肃省高等学校创新基金项目2020B-121
国家自然科学基金项目31660348
甘肃省自然科学基金项目20JR10RA509
甘肃农业大学科技创新基金项目GAU-STS-2018-12
甘肃农业大学青年导师扶持基金项目GAU-QDFC-2020-13
甘肃省财政专项GSCZZ-20160909

详细信息
作者简介:聂志刚, 主要研究方向为农业生态模型。E-mail: niezg@gsau.edu.cn
通讯作者:冯仰强, 主要研究方向为农业信息化。E-mail: 1826519669@qq.com
中图分类号:S153

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收稿日期:2020-12-29
录用日期:2021-03-31
刊出日期:2021-07-01

Effect of temperature increase on dryland spring wheat yield in different precipitation years

NIE Zhigang1,,
FENG Yangqiang1,,,
DONG Lixia1,
WANG Jun1,
LI Guang2
1. College of Information Science and Technology, Gansu Agricultural University, Lanzhou 730070, China
2. College of Forestry, Gansu Agricultural University, Lanzhou 730070, China
Funds: the Innovation Fund of Colleges and Universities in Gansu Province2020B-121
the National Natural Science Foundation of China31660348
the Natural Science Foundation of Gansu Province20JR10RA509
the Science and Technology Innovation Fund of Gansu Agricultural UniversityGAU-STS-2018-12
the Youth Tutor Support Fund of Gansu Agricultural UniversityGAU-QDFC-2020-13
the Special Fiscal Project in Gansu ProvinceGSCZZ-20160909

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Corresponding author:FENG Yangqiang, E-mail: 1826519669@qq.com


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摘要
摘要:为探究不同降水年型下温度升高对黄土丘陵区旱地春小麦产量的影响效应，本研究以甘肃省定西市安定区1979-2018年历史气象数据为基础，运用APSIM模型对不同降水年型下日最高、最低温度在0~2℃范围内耦合变化时旱地春小麦的产量进行模拟，并采用二次多项式回归、单因素分析和通径分析研究了不同降水年型下温度升高对旱地春小麦产量的影响机制。结果表明：在试验设计范围内，不同降水年型下旱地春小麦产量与日最低温度、日最高温度呈开口向上的二次抛物线变化且无阈值出现。日最高温度不变、日最低温度升高对产量呈正效应，其增产效果表现为干旱年>平水年>湿润年，日最低温度每增加0.5℃，最大增产幅度为3.99%；日最低温度不变、日最高温度升高对产量呈负效应，其减产效果表现为干旱年>湿润年>平水年，日最高温度每增加0.5℃，最大减产幅度为9.18%。不同降水年型下温度升高导致了旱地春小麦减产，日最高、最低温度升高对产量存在负交互关系，日最高温度升高带来的减产效应远大于日最低温度升高带来的增产效应。
关键词:APSIM/
旱地春小麦/
产量/
降水年型/
温度
Abstract:Climate change significantly affects crop production. To explore the effects of temperature increase on dryland spring wheat yield in different precipitation years in the hilly regions of the Loess Plateau, this study incorporated the meteorological data of Dingxi City, Gansu Province, from 1979 to 2018. Dryland spring wheat yield was simulated with the Agricultural Production Systems Simulator (APSIM) model when the daily maximum and minimum temperatures changed in the range of 0-2℃ in different precipitation years. Quadratic polynomial regression, single-factor analysis, and path analysis were used to study the influence mechanisms of temperature increase on dryland spring wheat yield. The results showed that the relationships between dryland spring wheat yield and daily minimum temperature, and between dryland spring wheat yield and daily maximum temperature were quadratic parabolas with an upward opening in different precipitation years, without a threshold value. When the daily maximum temperature was constant, an increase in the daily minimum temperature had a positive effect on the yield. The effect of increasing production was as follows: drought year > normal year > wet year. For every 0.5℃ increase in the daily minimum temperature, the average dryland spring wheat yield increased by 1.32% in wet years, 3.06% in normal years, and 3.99% in drought years. When the daily minimum temperature was constant, an increase in the daily maximum temperature had a negative effect on yield. The effect of production reduction was as follows: drought year > wet year > normal year. For every 0.5℃ increase in the daily maximum temperature, the average dryland spring wheat yield decreased by 9.08% in wet years, 7.98% in normal years, and 9.18% in drought years. The yield thresholds reached 798.61 kg·hm-2 in wet years when the daily maximum temperature increased by 7.1℃, 1118.21 kg·hm-2 in normal years when the daily maximum temperature increased by 3.9℃, and 1026.88 kg·hm-2 in drought years when the daily maximum temperature increased by 3.1℃. Increased temperature led to a decrease in dryland spring wheat yield in different precipitation years. There was a negative interaction between the daily maximum temperature and daily minimum temperature. The effect of reduced production caused by increased daily maximum temperature was much greater than the effect of increased production caused by increased daily minimum temperature.
Key words:Agricultural Production Systems Simulator (APSIM)/
Dryland spring wheat/
Yield/
Precipitation year/
Temperature

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图1湿润年型(a)、平水年型(b)和干旱年型(c)下日最高温度和最低温度变化对春小麦产量的单因素效应
Figure1.Single factor effects of changes in daily maximum temperature and minimum temperature on spring wheat yield in wet year (a), normal year (b) and drought year (c)


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图2湿润年型(a)、平水年型(b)和干旱年型(c)下日最低温度(X1)和最高温度(X2)对春小麦产量(Y)的通径分析
Figure2.Path analysis of daily minimum temperature (X1) and maximum temperature (X2) on spring wheat yield (Y) in wet years (a), normal years (b) and drought years (c)


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表11979—2018年研究区降水年型划分
Table1.Classification of precipitation years from 1979 to 2018 in the study area
降水年型
Precipitation year		年均降水量
Average annual precipitation (mm)		合计
Total		年份
Year
湿润年
Wet year		223.1161979, 1981, 1984, 1985, 1986, 1990, 1991, 1993, 1994, 1998, 1999, 2003, 2005, 2012, 2013, 2014
平水年
Normal year		179.6111980, 1983, 1987, 1988, 1992, 1996, 2002, 2007, 2010, 2015, 2016
干旱年
Drought year		119.6131982, 1989, 1995, 1997, 2000, 2001, 2004, 2006, 2008, 2009, 2011, 2017, 2018


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表2APSIM模型模拟的不同降水年型日最高温度和最低温度不同幅度升高对春小麦产量的影响
Table2.Simulated yields of spring wheat under different increase ranges of daily maximum and minimum temperatures in differentprecipitation years with APSIM model?kg?hm–2
降水年型
Precipitation year		日最低温度增幅
Increase in daily minimum temperature (℃)		日最高温度增幅Increase in daily maximum temperature (℃)
00.51.01.52.0
湿润年
Wet year		02242.212040.381864.791705.281557.08
0.52287.532087.631900.921726.971569.34
1.02313.462104.181919.901740.531576.51
1.52340.432127.261950.641758.481592.34
2.02387.322165.211978.181785.341611.15
平水年
Normal year		01794.961642.261499.071378.481290.80
0.51838.731693.741532.761418.791317.96
1.01898.791734.751582.651459.341360.25
1.51972.971780.971632.941508.561400.35
2.02011.171845.081698.931568.461452.76
干旱年
Drought year		01587.011424.571289.691178.671091.06
0.51644.631475.731337.521218.491128.92
1.01718.561535.651384.181263.551163.54
1.51793.471594.471443.631306.891215.36
2.01881.761676.381510.081360.541265.67
春小麦产量为同一降水年型的模拟产量的平均值。The yield of spring wheat is the average value of simulated yield in the same precipitation years.


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表3不同降水年型日最低温度(X1)和最高温度(X2)对春小麦产量单因素方程
Table3.Single factor equations of daily minimum (X1) and maximum (X2) temperatures on spring wheat yield in different precipitation years
降水年型
Precipitation year		日最低温度
Daily minimum temperature		日最高温度
Daily maximum temperature
湿润年Wet year$Y{\rm{ = 2243}}{\rm{.18 + 67}}{\rm{.94}}{X_1} + 1.32{X_1}^2$$Y{\rm{ = 2243}}{\rm{.18}} - {\rm{400}}{\rm{.01}}{X_2} + 27.69{X_2}^2$
平水年Normal year$Y{\rm{ = 1798}}{\rm{.65 + 88}}{\rm{.93}}{X_1} + 11.12{X_1}^2$$Y{\rm{ = 17978}}{\rm{.65}} - {\rm{342}}{\rm{.54}}{X_2} + 43.11{X_2}^2$
干旱年Drought year$Y{\rm{ = 1588}}{\rm{.65 + 115}}{\rm{.32}}{X_1} + 13.76{X_1}^2$$Y{\rm{ = 1588}}{\rm{.65}} - {\rm{360}}{\rm{.98}}{X_2} + 57.99{X_2}^2$


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