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

2021 ◽  
Vol 13 (22) ◽  
pp. 12673
Author(s):  
Fei Chen ◽  
Ningbo Cui ◽  
Yaowei Huang ◽  
Xiaotao Hu ◽  
Daozhi Gong ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Water Availability ◽  
Vegetation Index ◽  
Paddy Rice ◽  
Controlling Factors ◽  
Precipitation Event ◽  
Canopy Conductance ◽  
Light Use Efficiency ◽  
Summer Maize ◽  
Use Efficiency

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 (Ta), normalized difference vegetation index (NDVI), evaporative fraction (EF) and canopy conductance (gc, 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 Ta in summer maize, soybean and winter wheat. The results can help us better understand the interactive influences of environmental and biophysical factors on ELUE.

scholarly journals Tree–grass phenology information improves light use efficiency modelling of gross primary productivity for an Australian tropical savanna

2017 ◽  
Vol 14 (1) ◽  
pp. 111-129 ◽  
Author(s):  
Caitlin E. Moore ◽  
Jason Beringer ◽  
Bradley Evans ◽  
Lindsay B. Hutley ◽  
Nigel J. Tapper
Keyword(s):  
Primary Productivity ◽  
Vegetation Index ◽  
Temporal Dynamics ◽  
Seasonal Pattern ◽  
Gross Primary Productivity ◽  
Perennial Grasses ◽  
Light Use Efficiency ◽  
Tropical Savanna ◽  
Flux Tower ◽  
Use Efficiency

Abstract. The coexistence of trees and grasses in savanna ecosystems results in marked phenological dynamics that vary spatially and temporally with climate. Australian savannas comprise a complex variety of life forms and phenologies, from evergreen trees to annual/perennial grasses, producing a boom–bust seasonal pattern of productivity that follows the wet–dry seasonal rainfall cycle. As the climate changes into the 21st century, modification to rainfall and temperature regimes in savannas is highly likely. There is a need to link phenology cycles of different species with productivity to understand how the tree–grass relationship may shift in response to climate change. This study investigated the relationship between productivity and phenology for trees and grasses in an Australian tropical savanna. Productivity, estimated from overstory (tree) and understory (grass) eddy covariance flux tower estimates of gross primary productivity (GPP), was compared against 2 years of repeat time-lapse digital photography (phenocams). We explored the phenology–productivity relationship at the ecosystem scale using Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices and flux tower GPP. These data were obtained from the Howard Springs OzFlux/Fluxnet site (AU-How) in northern Australia. Two greenness indices were calculated from the phenocam images: the green chromatic coordinate (GCC) and excess green index (ExG). These indices captured the temporal dynamics of the understory (grass) and overstory (trees) phenology and were correlated well with tower GPP for understory (r2 =  0.65 to 0.72) but less so for the overstory (r2 =  0.14 to 0.23). The MODIS enhanced vegetation index (EVI) correlated well with GPP at the ecosystem scale (r2 =  0.70). Lastly, we used GCC and EVI to parameterise a light use efficiency (LUE) model and found it to improve the estimates of GPP for the overstory, understory and ecosystem. We conclude that phenology is an important parameter to consider in estimating GPP from LUE models in savannas and that phenocams can provide important insights into the phenological variability of trees and grasses.

Yield Performance and Resources Use Efficiency of Winter Wheat and Summer Maize in Double Late-Cropping System

2009 ◽  
Vol 35 (9) ◽  
pp. 1708-1714 ◽  
Author(s):  
Xue-Li FU ◽  
Hui ZHANG ◽  
Ji-Zeng JIA ◽  
Li-Feng DU ◽  
Jin-Dong FU ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Cropping System ◽  
Summer Maize ◽  
Yield Performance ◽  
Use Efficiency

Effects of Tillage and Straw Returning on Biomass and Water Use Efficiency in a Winter Wheat and Summer Maize Rotation System

2014 ◽  
Vol 40 (10) ◽  
pp. 1797 ◽  
Author(s):  
Ya-Li ZHAO ◽  
Hai-Bin GUO ◽  
Zhi-Wei XUE ◽  
Xin-Yuan MU ◽  
Chao-Hai LI
Keyword(s):  
Winter Wheat ◽  
Water Use Efficiency ◽  
Water Use ◽  
Summer Maize ◽  
Rotation System ◽  
Use Efficiency

Effect of Irrigation to Winter Wheat on the Soil Moisture, Evapotranspiration, and Water Use Efficiency of Summer Maize in North China

2007 ◽  
Vol 50 (6) ◽  
pp. 2073-2080 ◽  
Author(s):  
Q. Q. Li ◽  
Y. H. Chen ◽  
M. Y. Liu ◽  
X. B. Zhou ◽  
B. D. Dong ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Winter Wheat ◽  
Water Use Efficiency ◽  
Water Use ◽  
North China ◽  
Summer Maize ◽  
Use Efficiency

Monitoring paddy rice crops through remote sensing: productivity estimation by light use efficiency model

2004 ◽  
Author(s):  
Mirco Boschetti ◽  
Emanuela Mauri ◽  
Chiara Gadda ◽  
Lorenzo Busetto ◽  
Roberto Confalonieri ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Paddy Rice ◽  
Light Use Efficiency ◽  
Use Efficiency ◽  
Productivity Estimation ◽  
Light Use Efficiency Model

scholarly journals Short-term forecasting of regional biospheric CO<sub>2</sub> fluxes in Europe using a light-use-efficiency model (VPRM, MPI-BGC version 1.2)

2020 ◽  
Vol 13 (9) ◽  
pp. 4091-4106
Author(s):  
Jinxuan Chen ◽  
Christoph Gerbig ◽  
Julia Marshall ◽  
Kai Uwe Totsche
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Vegetation Type ◽  
Weather Prediction ◽  
Shortwave Radiation ◽  
Light Use Efficiency ◽  
Co2 Fluxes ◽  
Downward Shortwave Radiation ◽  
Use Efficiency ◽  
Light Use Efficiency Model

Abstract. Forecasting atmospheric CO2 concentrations on synoptic timescales (∼ days) can benefit the planning of field campaigns by better predicting the location of important gradients. One aspect of this, accurately predicting the day-to-day variation in biospheric fluxes, poses a major challenge. This study aims to investigate the feasibility of using a diagnostic light-use-efficiency model, the Vegetation Photosynthesis Respiration Model (VPRM), to forecast biospheric CO2 fluxes on the timescale of a few days. As input, the VPRM model requires downward shortwave radiation, 2 m temperature, and enhanced vegetation index (EVI) and land surface water index (LSWI), both of which are calculated from MODIS reflectance measurements. Flux forecasts were performed by extrapolating the model input into the future, i.e., using downward shortwave radiation and temperature from a numerical weather prediction (NWP) model, as well as extrapolating the MODIS indices to calculate future biospheric CO2 fluxes with VPRM. A hindcast for biospheric CO2 fluxes in Europe in 2014 has been done and compared to eddy covariance flux measurements to assess the uncertainty from different aspects of the forecasting system. In total the range-normalized mean absolute error (normalized) of the 5 d flux forecast at daily timescales is 7.1 %, while the error for the model itself is 15.9 %. The largest forecast error source comes from the meteorological data, in which error from shortwave radiation contributes slightly more than the error from air temperature. The error contribution from all error sources is similar at each flux observation site and is not significantly dependent on vegetation type.

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