A Study on the Spatial–Temporal Evolution and Driving Factors of Non-Grain Production in China’s Major Grain-Producing Provinces
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Sources
2.2.1. Non-Grain Production Ratio
2.2.2. Share of Grain Production
2.2.3. Hot Spot Analysis
2.2.4. Spatial Durbin Model
3. Results and Discussion
3.1. Temporal Evolutionary Characteristics of Non-Grain Production
3.2. Spatial Evolutionary Characteristics of Non-Grain Production
3.3. Spatial–Temporal Characteristics of Changes in Non-Grain Production
3.4. Driving Factors of Non-Grain Production
4. Conclusions
- (1)
- Non-grain production showed an upward trend from 2011 to 2020 in the thirteen major grain-producing provinces of China. From 2011 to 2020, Heilongjiang, Henan, and Shandong provinces were the top three provinces in the thirteen major grain-producing provinces of China in terms of grain production, with an average share of 11.20%, 9.75%, and 7.98% of the national grain production, respectively. Hubei, Jiangxi, and Liaoning provinces were the last three provinces in the thirteen major grain-producing provinces of China in terms of grain production, with an average share of 4.16%, 3.34%, and 3.42% of the national grain production, respectively. From 2011 to 2020, Hubei, Hunan, Jiangxi, and Sichuan provinces had a level of non-grain production above 30%, while Jilin and Heilongjiang provinces had a level of non-grain production below 10%. The share of grain production in the thirteen provinces was not significantly related to the level of non-grain production.
- (2)
- The regions with high ratios of grain production to total national production were concentrated in the Northeast Plain, the North China Plain, and the Middle and Lower Yangtze River Plain of China. The areas with high non-grain production were mainly concentrated in the central and western regions of Inner Mongolia, the middle and lower reaches of the Yangtze River, and Sichuan, while the areas with low non-grain production were mainly distributed in the Northeast Plain. The hot spot areas of non-grain production changes were mainly distributed in the Sichuan region and Alashan League City in Inner Mongolia, and the cold spot regions were mainly distributed in Hebei, Shandong, Henan, and other regions.
- (3)
- There was a significant spatial spillover effect of influencing factors in China’s major grain-producing regions, with regions being influenced by non-grain production in their neighboring regions. The analysis of the SDM indicates that the average air temperature of natural environmental factors, the ratio of the sum of gross secondary and tertiary industries to GDP, the ratio of gross primary industry to the GDP of economic development level, the urbanization rate of social development, and the difference in disposable income per capita between urban and rural residents of the urban–rural gap showed positive spillover effects and affected the non-grain production of neighboring areas. In addition, the grain production resource endowment of grain yield per unit of grain crop sown area, the total population of social development, and the area sown to grain crops per capita of grain production resource endowment all but significantly and negatively affected the non-grain production of neighboring areas.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Factors | Variables | Definition | Unit |
---|---|---|---|
Natural environment | AA | The average altitude of a region | M |
AS | The average slope of a region | Degree | |
AAT | The average air temperature of a region | K (Kelvin temperature) | |
AR | The average rainfall of a region | Mm | |
Resource endowment for grain production | ASG | The ratio of sown area of grain crops to total population in a region | Hectare/person |
GYG | The ratio of grain yield to grain crop sown area in a region | Ton/ha | |
Agricultural science and technology | PAMC | The ratio of the power of agricultural machinery to crop sown area | kW/ha |
Urban–rural gap | DIUR | The difference in disposable income per capita between urban and rural residents in a region | CNY |
Agricultural production benefits | GOF | The gross output value of farming in a region | 10,000 CNY |
Social development | RU | The rate of urbanization in a region | % |
TP | The population in a region | 10,000 people | |
Economic development | GDP | The GDP in a region | Billion CNY |
PGDP | The ratio of gross primary industry to GDP | % | |
STGDP | The ratio of the sum of gross secondary and tertiary industries to GDP | % |
Year | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 |
---|---|---|---|---|---|---|---|---|---|---|
China | 29.55% | 29.43% | 29.20% | 28.89% | 28.69% | 28.58% | 29.06% | 29.45% | 30.05% | 30.28% |
Year | Moran’s I | z | p-Value |
---|---|---|---|
2011 | 0.628 | 13.360 | 0.000 |
2012 | 0.599 | 12.727 | 0.000 |
2013 | 0.602 | 12.805 | 0.000 |
2014 | 0.623 | 13.263 | 0.000 |
2015 | 0.597 | 12.718 | 0.000 |
2016 | 0.631 | 13.444 | 0.000 |
2017 | 0.656 | 13.970 | 0.000 |
2018 | 0.674 | 14.344 | 0.000 |
2019 | 0.672 | 14.306 | 0.000 |
2020 | 0.675 | 14.354 | 0.000 |
Variables | SEM | p-Value | SLM | p-Value |
---|---|---|---|---|
Lagrange multiplier | 716.051 | 0.000 | 672.099 | 0.000 |
Robust Lagrange multiplier | 112.933 | 0.000 | 68.981 | 0.000 |
Test | Non-Grain Production | p-Value | |
---|---|---|---|
LR test | Spatial error | 150.64 | 0.000 |
Spatial lag | 85.21 | 0.000 | |
Wald test | Spatial error | 33.39 | 0.0008 |
Spatial lag | 24.96 | 0.0150 | |
Hausman test | 301.06 | 0.000 |
Factors | Explanatory Variables | Direct Effect | Indirect Effect | Total Effect |
---|---|---|---|---|
Natural environment | AA | 0.15321 *** | 0.03565 | 0.18885 *** |
(0.0000) | (0.4613) | (0.0000) | ||
AS | −0.14312 *** | −0.01796 | −0.16109 *** | |
(0.0000) | (0.7550) | (0.0014) | ||
AAT | 4.16136 | 23.78788 *** | 27.94924 *** | |
(0.1600) | (0.0000) | (0.0000) | ||
AR | −0.13728 | −0.08466 | −0.22194 *** | |
(0.1229) | (0.4621) | (0.0019) | ||
Resource endowment for grain production | ASG | −0.53242 *** | −0.28612 *** | −0.81854 *** |
(0.0000) | (0.0001) | (0.0000) | ||
GYG | 0.17654 *** | −0.49140 *** | −0.31486 ** | |
(0.0016) | (0.0001) | (0.0190) | ||
Agricultural science and technology level | PAMC | −0.21141 *** | −0.01112 | −0.22252 *** |
(0.0000) | (0.8630) | (0.0007) | ||
Urban–rural gap | DIUY | 0.39398 *** | 0.23858 * | 0.63256 *** |
(0.0000) | (0.0965) | (0.0000) | ||
Agricultural production benefits | GOF | 0.50878 *** | 0.01442 | 0.52320 *** |
(0.0000) | (0.9194) | (0.0006) | ||
Social development | RU | 0.04470 | 0.47215 *** | 0.51685 *** |
(0.5230) | (0.0024) | (0.0014) | ||
TP | −0.45521 *** | −0.38623 *** | −0.84143 *** | |
(0.0000) | (0.0013) | (0.0000) | ||
Economic development | GDP | −0.07417 | 0.25401 | 0.17985 |
(0.2550) | (0.1177) | (0.2936) | ||
PGDP | 0.29213 *** | 0.52132 *** | 0.81345 *** | |
(0.0000) | (0.0015) | (0.0000) | ||
STGDP | 2.44747 *** | 1.75502 *** | 4.20250 *** | |
(0.0000) | (0.0015) | (0.0000) |
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Ran, D.; Zhang, Z.; Jing, Y. A Study on the Spatial–Temporal Evolution and Driving Factors of Non-Grain Production in China’s Major Grain-Producing Provinces. Int. J. Environ. Res. Public Health 2022, 19, 16630. https://doi.org/10.3390/ijerph192416630
Ran D, Zhang Z, Jing Y. A Study on the Spatial–Temporal Evolution and Driving Factors of Non-Grain Production in China’s Major Grain-Producing Provinces. International Journal of Environmental Research and Public Health. 2022; 19(24):16630. https://doi.org/10.3390/ijerph192416630
Chicago/Turabian StyleRan, Duan, Zhanlu Zhang, and Yuhan Jing. 2022. "A Study on the Spatial–Temporal Evolution and Driving Factors of Non-Grain Production in China’s Major Grain-Producing Provinces" International Journal of Environmental Research and Public Health 19, no. 24: 16630. https://doi.org/10.3390/ijerph192416630