Improved mapping of nitrogen loss and surplus in China's maize belt. (31st August 2022)
- Record Type:
- Journal Article
- Title:
- Improved mapping of nitrogen loss and surplus in China's maize belt. (31st August 2022)
- Main Title:
- Improved mapping of nitrogen loss and surplus in China's maize belt
- Authors:
- Tian, Xingshuai
Zhuang, Minghao
Yin, Yulong
Cong, Jiahui
Ying, Hao
Wang, Yingcheng
Cui, Zhenling - Abstract:
- Abstract: Comprehensive, spatially explicit understanding of N loss from N input in China's maize ( Zea mays L.) belt is needed to improve N management and develop N loss mitigation measures for specific locations. However, accurate estimation of N loss remains uncertain mainly because of spatial heterogeneity of emission factors (EFs) and activity data. Here, we built random‐forest models to predict EFs for each N loss pathway (dinitrogen, nitric oxide, nitrous oxide and ammonia emissions, nitrate leaching, and N runoff) considering soil and climate factors. We then used location‐ and crop‐specific activity data to understand N loss and surplus on a 1‐ × 1‐km grid. Results showed that the N surplus and total N loss averaged 135.4 (95% confidence interval [CI], 36.6–261.5) and 87.6 (95% CI, 32.9–162.5) kg N ha –1, respectively, and nitrate leaching and ammonia emissions were primary loss pathways. There was a significant correlation between N surplus and total N loss in spatial distribution, and regions with high N surplus and total N loss were mainly in the northern China Plain and Sichuan Basin, while regions with low surplus and loss could be found in Heilongjiang and Jilin provinces. Our results are beneficial to understand specific crop N budget and develop location‐specific N management strategies. Core Ideas: A spatially explicit assessment of N loss from N input was mapped in China's maize belt. The N surplus and total N loss averaged 135.4 and 87.6 kg N ha ‐1,Abstract: Comprehensive, spatially explicit understanding of N loss from N input in China's maize ( Zea mays L.) belt is needed to improve N management and develop N loss mitigation measures for specific locations. However, accurate estimation of N loss remains uncertain mainly because of spatial heterogeneity of emission factors (EFs) and activity data. Here, we built random‐forest models to predict EFs for each N loss pathway (dinitrogen, nitric oxide, nitrous oxide and ammonia emissions, nitrate leaching, and N runoff) considering soil and climate factors. We then used location‐ and crop‐specific activity data to understand N loss and surplus on a 1‐ × 1‐km grid. Results showed that the N surplus and total N loss averaged 135.4 (95% confidence interval [CI], 36.6–261.5) and 87.6 (95% CI, 32.9–162.5) kg N ha –1, respectively, and nitrate leaching and ammonia emissions were primary loss pathways. There was a significant correlation between N surplus and total N loss in spatial distribution, and regions with high N surplus and total N loss were mainly in the northern China Plain and Sichuan Basin, while regions with low surplus and loss could be found in Heilongjiang and Jilin provinces. Our results are beneficial to understand specific crop N budget and develop location‐specific N management strategies. Core Ideas: A spatially explicit assessment of N loss from N input was mapped in China's maize belt. The N surplus and total N loss averaged 135.4 and 87.6 kg N ha ‐1, respectively. High N surplus and total N loss was recorded in the northern China Plain and Sichuan Basin. … (more)
- Is Part Of:
- Agronomy Journal. Volume 114:Number 5(2022)
- Journal:
- Agronomy Journal
- Issue:
- Volume 114:Number 5(2022)
- Issue Display:
- Volume 114, Issue 5 (2022)
- Year:
- 2022
- Volume:
- 114
- Issue:
- 5
- Issue Sort Value:
- 2022-0114-0005-0000
- Page Start:
- 2811
- Page End:
- 2821
- Publication Date:
- 2022-08-31
- Subjects:
- Agronomy -- Periodicals
630 - Journal URLs:
- http://onlinelibrary.wiley.com/ ↗
- DOI:
- 10.1002/agj2.21172 ↗
- Languages:
- English
- ISSNs:
- 0002-1962
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24004.xml