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Risk analysis of maize yield losses in mainland China at the county level
- Source :
- Scientific Reports, Vol 10, Iss 1, Pp 1-12 (2020), Scientific Reports
- Publication Year :
- 2020
- Publisher :
- Nature Publishing Group, 2020.
-
Abstract
- Food security in China is under additional stress due to climate change. The risk analysis of maize yield losses is crucial for sustainable agricultural production and climate change impact assessment. It is difficult to quantify this risk because of the constraints on the high-resolution data available. Moreover, the current results lack spatial comparability due to the area effect. These challenges were addressed by using long-term county-level maize yield and planting area data from 1981 to 2010. We analyzed the spatial distribution of maize yield loss risks in mainland China. A new comprehensive yield loss risk index was established by combining the reduction rate, coefficient of variation, and probability of yield reduction after removing the area effect. A total of 823 counties were divided into areas of lowest, low, moderate, high, and highest risk. High risk in maize production occurred in Heilongjiang and Jilin Provinces, the eastern part of Inner Mongolia, the eastern part of Gansu-Xinjiang, west of the Loess Plateau, and the western part of the Xinjiang Uygur Autonomous Region. Most counties in Northeast China were at high risk, while the Loess Plateau, middle and lower reaches of the Yangtze River and Gansu-Xinjiang were at low risk.
- Subjects :
- Crops, Agricultural
Risk
Mainland China
Risk analysis
China
010504 meteorology & atmospheric sciences
Climate Change
Yield (finance)
Climate change
lcsh:Medicine
010502 geochemistry & geophysics
Zea mays
01 natural sciences
Article
Agricultural productivity
lcsh:Science
Probability
0105 earth and related environmental sciences
Multidisciplinary
Food security
Ecology
lcsh:R
Natural hazards
Sowing
Agriculture
Geography
Risk analysis (engineering)
Food Security
lcsh:Q
Climate sciences
Subjects
Details
- Language :
- English
- ISSN :
- 20452322
- Volume :
- 10
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Scientific Reports
- Accession number :
- edsair.doi.dedup.....cf7f85b2147d8f4ba833bc87a7ab9154