Estimation of maize yield incorporating the synergistic effect of climatic and land use change in Jilin, China

doi:10.1007/s11442-023-2150-6

Abstract

Abstract:

Yield forecasting can give early warning of food risks and provide solid support for food security planning. Climate change and land use change have direct influence on regional yield and planting area of maize, but few studies have examined their synergistic impact on maize production. In this study, we propose an analysis framework based on the integration of system dynamic (SD), future land use simulation (FLUS) and a statistical crop model to predict future maize yield variation in response to climate change and land use change in a phaeozem region of central Jilin province, China. The results show that the cultivated land is likely to reduce by 862.84 km² from 2030 to 2050. Nevertheless, the total maize yield is expected to increase under all four RCP scenarios due to the promotion of per hectare maize yield. Among the scenarios, RCP4.5 is the most beneficial to maize production, with a doubled total yield in 2050. Notably, the yield gap between different counties will be further widened, which necessitates the differentiated policies of agricultural production and farmland protection, e.g., strengthening cultivated land protection and crop management in low-yield areas, and taking adaptation and mitigation measures to coordinate climate change and production.

Key words: maize yield forecast, land use simulation, RCP scenarios, models

WEN Xinyuan, LIU Dianfeng, QIU Mingli, WANG Yinjie, NIU Jiqiang, LIU Yaolin. Estimation of maize yield incorporating the synergistic effect of climatic and land use change in Jilin, China[J].Journal of Geographical Sciences, 2023, 33(8): 1725-1746.

Figures/Tables 21

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Table A1

Regression coefficients

Model	Unstandardized coefficient		t	Sig.
Model	B	Standard error	t	Sig.
(constant)	-6.226	7.759	-0.802	0.423
T	1.598	0.788	2.029	0.043
T²	-0.043	0.020	-2.163	0.031
P	0.006	0.003	2.254	0.025
P²	-2.622E-05	0.000	-2.146	0.032
machine	-0.006	0.001	-4.633	0.000
machine²	1.284E-04	0.000	3.153	0.002
SH	2.750E-04	8.02 E-04	0.342	0.732
Area=Dongfeng County	0.243	0.104	2.329	0.020
Area=Dongchang District	0.265	0.135	1.971	0.049
Area=Dongliao County	0.251	0.105	2.392	0.017
Area = Fengman District	0.095	0.115	0.821	0.412
Area=Jiutai City	0.035	0.104	0.342	0.733
Area = Erdao District	-0.409	0.102	-4.025	0.000
Area = Erdaojiang District	0.148	0.134	1.105	0.269
Area=Yitong County	0.267	0.102	2.623	0.009
Area=Gongzhuling City	0.652	0.105	6.212	0.000
Area=Nong'an County	0.431	0.105	4.085	0.000
Area = Nanguan District	-0.019	0.109	-0.173	0.863
Area=Shuangyang District	0.316	0.108	2.920	0.004
Area = Kuancheng District	-0.400	0.102	-3.920	0.000
Area=Dehui City	0.298	0.106	2.813	0.005
Area=Changyi District	0.092	0.103	0.888	0.375
Area=Chaoyang District	-0.106	0.113	-0.942	0.346
Area = Liuhe County	0.255	0.112	2.263	0.024
Area = Huadian City	-0.020	0.121	-0.167	0.867
Area=Meihekou City	0.087	0.104	0.834	0.405
(constant)	-6.226	7.759	-0.802	0.423
Area = Lishu County	0.724	0.105	6.916	0.000
Area = Elm City	0.313	0.104	3.019	0.003
Area=Yongji County	0.028	0.103	0.268	0.788
Area=Panshi City	0.106	0.103	1.024	0.306
Area = Green Park	0.055	0.119	0.461	0.645
Area = Shulan City	0.200	0.111	1.810	0.071
Area = Ship Camp Area	0.063	0.105	0.599	0.549
Area = Jiaohe City	0.102	0.116	0.877	0.381
Area = Xi'an District	-0.042	0.103	-0.412	0.680
Area=Huinan County	0.351	0.112	3.130	0.002
Area=Tonghua County	-0.051	0.110	-0.460	0.646
Area=Tiedong District	0.236	0.107	2.200	0.028
Area = Tiexi District	0.449	0.185	2.427	0.016
Area = Ji'an City	-0.098	0.109	-0.894	0.372
Area = Longshan District	-0.055	0.102	-0.538	0.591
Area=Longtan District	0.091	0.105	0.868	0.386

Table A1

Table A2

Table A3

The relation functions used in the SD model

Dependent variable	Independent variable
Dependent variable	Changchun	Jilin		Siping	Liaoyuan	Tonghua
Population change	Population change rate ×Total population
Agricultural population	Agricultural population ratio ×Total population
Construction land change	Population change × Construction land per capita
Construction land per capita	0.02808×(Time-2015) + 2.36822
Total grain production	196696× (Time-2015) + 7.02149e+06	38568.5× (Time-2015)+ 3.61855e+06		223246× (Time-2015)+ 5.19641e+06	17327.5× (Time-2015) + 1.213e+06	17500.5× (Time-2015)+ 1.62026e+06
Technology expenditure ratio	6.5×(Time-2015)+ 0.009628	6.38×(Time-2015)+ 0.005389		76.109× (Time-2015)- 1977.53	27.5× (Time-2015) + 1.23277e+06	1.089×(Time-2015)+ 0.008784
Forestry output value	1977.86× (Time-2015) + 8967.88	6855.19× (Time-2015) + 32268.6		765.905× (Time-2015)+ 12584	2158.23× (Time-2015) - 2693.16	11005.8× (Time-2015) - 22992.2
Technology expenditure	7437.71× (Time-2015) - 17716.6	4166.49× (Time-2015) - 10044.6		761.109× (Time-2015) - 1977.53	804.273× (Time-2015)- 2886.62	5366.08× (Time-2015) - 20759.7
Pastoral output value	144195× (Time-2015)+ 1.15857e+06	138068× (Time-2015)+ 249054		213037× (Time-2015)+ 556231	38851.8× (Time-2015)+ 118363	31078.9× (Time-2015)+ 216560
Fishery output value	4235.14× (Time-2015) - 1124.15	6211.77× (Time-2015) + 38328.4		1548.15× (Time-2015)- 5607.55	611.483× (Time-2015) - 1412.13	3972.97× (Time-2015)+ 2054.63
Proportion of expenditure on agriculture	0.0027× (Time-2015) + 0.0395	0.0027× (Time-2015)+ 0.0395		-0.001092× (Time-2015)+ 0.129638	0.000930× (Time-2015)+ 0.0866	-0.001715× (Time-2015)+ 0.1312
Total power of agricultural machinery	21.428 × (Time-2015)+ 205.236	25.8394× (Time-2015)+ 63.2892		18.9625× (Time-2015)+ 81.9124	10.4513× (Time-2015) + 2.82133	6.58964× (Time-2015)+ 84.9691
Cultivated land change	-109.732+0.0976× Total power of agricultural machinery+ 0.195929× Agricultural population- 1.25146e-06× Total grain production	-108.152+0.0896× Total power of agricultural machinery+ 0.172859× Agricultural population-1.20816e-06× Total grain production		-107.362+0.0976×Total power of agricultural machinery+ 0.29653×Agricultural population+ 1.25146e-06× Total grain production	-45+0.0976×Total power of agricultural machinery+ 0.2× Agricultural population+ 1.25146e-06×Total grain production	-52.732+0.0976× Total power of agricultural machinery+ 0.195929× Agricultural population+ 1.25146e- 06×Total grain production
Water area change	0.4719-2.48582e-05 ×Fishery output value- 9.75115× Proportion of expenditure on agriculture- 0.0114061× Unused land	0.3287+2e-05× Fishery output value- 9.7× Proportion of expenditure on agriculture+ 0.014025×Unused land		0.2693+2e-05× Fishery output value- 9.67103× Proportion of expenditure on agriculture+ 0.0100651×Unused land	0.4+2e-05×Fishery output value- 9.35115×Proportion of expenditure on agriculture+ 0.01×Unused land	0.4178+2e-05× Fishery output value- 9.5115× Proportion of expenditure on agriculture+ 0.024551×Unused land
Grassland change	71.451-0.041978× Woodland -0.0281294×Total power of agricultural machinery+ 1.83056e-07×Pastoral output value-45.069× Technology expenditure ratio	69.451-0.004× Woodland + 0.0311575× Total power of agricultural machinery+ 1.83056e-07× Pastoral output value- 38.405× Technology expenditure ratio	70.895-0.04× Woodland +0.03× Total power of agricultural machinery+ 2.0056e-07× Pastoral output value+41.036× Technology expenditure ratio		64.589-0.035× Woodland + 0.0281294×Total power of agricultural machinery- 1.83056e-07× Pastoral output value-40.853× Technology expenditure ratio	75.186-0.0066× Woodland -0.028× Total power of agricultural machinery-1.8e-07× Pastoral output value+10.853× Technology expenditure ratio
Woodland change	52.0559-0.096× Grassland+ 0.000108421× Forestry output value+ 0.0001×Technology expenditure	46.0559-0.096× Grassland+ 0.000108421× Forestry output value+ 0.0001× Technology expenditure	32.0559-0.097× Grassland- 0.000108421× Forestry output value+0.0001× Technology expenditure		28-0.1×Grassland- 0.00011×Forestry output value +0.001× Technology expenditure	40.0559-0.0966744×Grassland- 0.000108421× Forestry output value- 0.0001× Technology expenditure
Unused land	20528-Cultivated land-Grassland- Woodland -Water area- Construction land	27782.1-Cultivated land-Grassland- Woodland -Water area- Construction land	14355.2-Cultivated land-Grassland- Woodland -Water area- Construction land		5144.74-Cultivated land-Grassland- Woodland -Water area- Construction land	15568.6-Cultivated land-Grassland- Woodland -Water area- Construction land

Table A3

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Data	Data type	Original spatial resolution	Temporal coverage	Data source
Expenditure and production value of agriculture, forestry, animal husbandry and fishery	Excel	N/A	2000-2015	Jilin Province Statistical Yearbook
Total mechanical power, total grain production
The proportion of urban population, total urban and rural population
Science and technology expenditure
County-level maize yield data
Historical climate data			2000-2015	http://data.cma.cn/
Annual precipitation and annual average temperature	NetCDF	1.125°	2006-2100	https://doi.org/10.1594/WDCC/ETHr2
Land use map	TIFF	30 m	2000-2015	http://data.casearth.cn/
Spatial distribution of GDP		1 km	2000, 2015	http://www.resdc.cn/
Spatial distribution of population density		1 km
DEM		30 m
Road network	shapefile	N/A		https://www.openstreetmap.org/
Administrative boundary	shapefile	N/A	2015	http://www.resdc.cn/

Scenarios		Growth rate
RCP2.6	Level	High
RCP2.6	Growth rate	+7%
RCP4.5	Level	Relatively high
RCP4.5	Growth rate	+5%
RCP6.0	Level	Moderate
RCP6.0	Growth rate	+3%
RCP8.5	Level	Low
RCP8.5	Growth rate	0

Scenarios	2030 (megatons)	Change rate 2011-2030 (%)	2050 (megatons)	Change rate 2030-2050 (%)
RCP2.6	24.02	38.61	54.03	124.92
RCP4.5	23.50	35.61	58.52	149.01
RCP6.0	22.54	30.03	55.93	148.19
RCP8.5	20.50	18.28	53.50	161.00

Region	$Var\left( \log \left( \epsilon \right) \right)$	Region	$Var\left( \log \left( \epsilon \right) \right)$
Changyi District	0.025572075	Liuhe County	0.044541441
Chaoyang District	0.195618882	Yongsan District	0.088251022
Ship Camp Area	0.014275893	Longtan District	0.019158748
Dehui	0.033632781	Green Park	0.249584034
Dongchang District	0.014318566	Meihekou	0.009294256
Dongfeng County	0.026302486	Nanguan District	0.14462959
Dongliao County	0.049171297	Nong'an County	0.011689685
Erdaojiang District	0.031237137	rock city	0.01400162
Erdao District	0.431996676	Shulan	0.01074008
plump area	0.048536536	Shuangliao	0.038542727
Gongzhuling	0.010237088	Shuangyang District	0.072074432
Huadian	0.026221195	Tiedong District	0.039590128
Huinan County	0.070030835	Tiexi District	0.079287917
Ji'an	0.023745877	Tonghua County	0.011766734
Jiaohe	0.046481507	Xi'an District	0.344605244
Jiutai District	0.0508169	Yitong County	0.071153589
Kuancheng District	0.28749462	Yongji County	0.043845527
Lishu County	0.030609236	Elm City	0.012829379