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Investigating the Patterns and Controls of Ecosystem Light Use Efficiency with the Data from the Global Farmland Fluxdata Network

Author

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  • Fei Chen

    (State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource and Hydropower, Sichuan University, Chengdu 610065, China)

  • Ningbo Cui

    (State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource and Hydropower, Sichuan University, Chengdu 610065, China
    Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Xianyang 712100, China)

  • Yaowei Huang

    (State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource and Hydropower, Sichuan University, Chengdu 610065, China)

  • Xiaotao Hu

    (Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Xianyang 712100, China)

  • Daozhi Gong

    (State Engineering Laboratory of Efficient Water Use of Crops and Disaster Loss Mitigation, Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agriculture Science, Beijing 100081, China)

  • Yaosheng Wang

    (State Engineering Laboratory of Efficient Water Use of Crops and Disaster Loss Mitigation, Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agriculture Science, Beijing 100081, China)

  • Min Lv

    (State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource and Hydropower, Sichuan University, Chengdu 610065, China)

  • Shouzheng Jiang

    (State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource and Hydropower, Sichuan University, Chengdu 610065, China)

Abstract

Ecosystem light use efficiency (ELUE) is generally defined as the ratio of gross primarily productivity (GPP) to photosynthetically active radiation (PAR), which is an important ecological indictor used in dry matter prediction. Herein, investigating the dynamics of ELUE and its controlling factors is of great significance for simulating ecosystem photosynthetic production. Using 35 site-years eddy covariance fluxes and meteorological data collected at 11 cropland sites globally, we investigated the dynamics of ELUE and its controlling factors in four agroecosystems with paddy rice, soybean, summer maize and winter wheat. A “U” diurnal pattern of hourly ELUE was found in all the fields, and daily ELUE varied with crop growth. The ELUE for the growing season of summer maize was highest with 0.92 ± 0.06 g C MJ −1 , followed by soybean (0.80 ± 0.16 g C MJ −1 ), paddy rice (0.77 ± 0.24 g C MJ −1 ) and winter wheat (0.72 ± 0.06 g C MJ −1 ). Correlation analysis showed that ELUE positively correlated with air temperature (T a ), normalized difference vegetation index (NDVI), evaporative fraction (EF) and canopy conductance (g c , except for paddy rice sites), while it negatively correlated with the vapor water deficit (VPD). Besides, ELUE decreased in the days after a precipitation event during the active growing seasons. The path analysis revealed that the controlling variables considered in this study can account for 73.7%, 85.3%, 75.3% and 65.5% of the total ELUE variation in the rice, soybean, maize and winter wheat fields, respectively. NDVI is the most confident estimators for ELUE in the four ecosystems. Water availability plays a secondary role controlling ELUE, and the vegetation productivity is more constrained by water availability than T a in summer maize, soybean and winter wheat. The results can help us better understand the interactive influences of environmental and biophysical factors on ELUE.

Suggested Citation

  • Fei Chen & Ningbo Cui & Yaowei Huang & Xiaotao Hu & Daozhi Gong & Yaosheng Wang & Min Lv & Shouzheng Jiang, 2021. "Investigating the Patterns and Controls of Ecosystem Light Use Efficiency with the Data from the Global Farmland Fluxdata Network," Sustainability, MDPI, vol. 13(22), pages 1-19, November.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:22:p:12673-:d:680451
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    References listed on IDEAS

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    1. Yuzhe Li & Jiangwen Fan & Zhongmin Hu, 2018. "Comparison of Carbon-Use Efficiency Among Different Land-Use Patterns of the Temperate Steppe in the Northern China Pastoral Farming Ecotone," Sustainability, MDPI, vol. 10(2), pages 1-17, February.
    2. Qi’ao Zhang & Wei Chen, 2021. "Ecosystem Water Use Efficiency in the Three-North Region of China Based on Long-Term Satellite Data," Sustainability, MDPI, vol. 13(14), pages 1-17, July.
    3. Wang, Tongxin & Tang, Xuguang & Zheng, Chen & Gu, Qing & Wei, Jin & Ma, Mingguo, 2018. "Differences in ecosystem water-use efficiency among the typical croplands," Agricultural Water Management, Elsevier, vol. 209(C), pages 142-150.
    4. Campoy, Jaime & Campos, Isidro & Plaza, Carmen & Calera, María & Jiménez, Nuria & Bodas, Vicente & Calera, Alfonso, 2019. "Water use efficiency and light use efficiency in garlic using a remote sensing-based approach," Agricultural Water Management, Elsevier, vol. 219(C), pages 40-48.
    5. Ligita Baležentienė & Ovidijus Mikša & Tomas Baležentis & Dalia Streimikiene, 2019. "Seasonal Net Carbon Exchange in Rotation Crops in the Temperate Climate of Central Lithuania," Sustainability, MDPI, vol. 11(7), pages 1-8, April.
    6. Feiyan Chen & Aiwen Lin & Hongji Zhu & Jiqiang Niu, 2018. "Quantifying Climate Change and Ecological Responses within the Yangtze River Basin, China," Sustainability, MDPI, vol. 10(9), pages 1-19, August.
    7. Meetpal S. Kukal & Suat Irmak, 2020. "Evidence of Arithmetical Uncertainty in Estimation of Light and Water Use Efficiency," Sustainability, MDPI, vol. 12(6), pages 1-9, March.
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