Quantifying water stress effect on daily light use efficiency in Mediterranean ecosystems using satellite data

The capacity of six water stress factors(ε′(i))to track daily light use efficiency(ε)of water-limited ecosystems was evaluated.These factors are computed with remote sensing operational products and a limited amount of ground data:ε′1 uses ground precipitation and air temperature,and satellite incoming global solar radiation;ε′(2) uses ground air temperature,and satellite actual evapotranspiration and incoming global solar radiation;ε′_(3) uses satellite actual and potential evapotranspiration;ε′_(4) uses satellite soil moisture;ε′_(5) uses satellite-derived photochemical reflectance index;and ε′_(6) uses ground vapor pressure deficit.These factors were implemented in a production efficiency model based on Monteith’s approach in order to assess their performance for modeling gross primary production(GPP).Estimated GPP was compared to reference GPP from eddy covariance(EC)measurements(GPP EC)in three sites placed in the Iberian Peninsula(two open shrublands and one savanna).ε′_(i) were correlated to ε,which was calculated by dividing GPP EC by ground measured photosynthetically active radiation(PAR)and satellite-derived fraction of absorbed PAR.Best results were achieved by ε′(1),ε′(2),ε′(3) and ε′(4) explaining around 40% and 50% of ε variance in open shurblands and savanna,respectively.In terms of GPP,R^(2)≈0.70 were obtained in these cases.

LIGHT INTERCEPTION AND USE EFFICIENCY DIFFER WITH MAIZE PLANT DENSITY IN MAIZE-PEANUT INTERCROPPING

Intercropping increases crop yields by optimizing light interception and/or use efficiency.Although intercropping combinations and metrics have been reported,the effects of plant density on light use are not well documented.Here,we examined the light interception and use efficiency in maize-peanut intercropping with different maize plant densities in two row configurations in semiarid dryland agriculture over a two-year period.The field experiment comprised four cropping systems,i.e.,monocropped maize,monocropped peanut,maize-peanut intercropping with two rows of maize and four rows of peanut,intercropping with four rows of maize and four rows of peanut,and three maize plant densities(3.0,4.5 and 6.0 plants m^(-1) row)in both monocropped and intercropping maize.The mean total light interception in intercropping across years and densities was 779 MJ·m^(-2),5.5%higher than in monocropped peanut(737 MJ·m^(-2))and 7.6%lower than in monocropped maize(843 MJ·m^(-2)).Increasing maize density increased light interception in monocropped maize but did not affect the total light interception in the intercrops.Across years the LUE of maize was 2.9 g·MJ–1 and was not affected by cropping system but increased with maize plant density.The LUE of peanut was enhanced in intercropping,especially in a wetter year.The yield advantage of maize-peanut intercropping resulted mainly from the LUE of peanut.These results will help to optimize agronomic management and system design and provide evidence for system level light use efficiency in intercropping.

Growth,nutritional quality,and energy use efficiency in two lettuce cultivars as influenced by white plus red versus red plus blue LEDs

Red plus blue light-emitting diodes(LEDs)are commonly applied in plant factories with artificial lighting due to photosynthetic pigments,which absorb strongly in red and blue light regions of the spectrum.However,plants grown under natural environment are used to utilizing broad-wide spectrum by long-term evolution.In order to examine the effects of addition light added in red plus blue LEDs or white LEDs,green and purple leaf lettuces(Lactuca sativa L.cv.Lvdie and Ziya)were hydroponically cultivated for 20 days under white LEDs,white plus red LEDs,red plus blue LEDs,and red plus blue LEDs supplemented with ultraviolet,green or far-red light,respectively.The results indicated that the addition of far-red light in red plus blue LEDs increased leaf fresh and dry weights of green leaf lettuce by 28%and 34%,respectively.Addition of ultraviolet light did not induce any differences in growth and energy use efficiency in both lettuce cultivars,while supplementing green light with red plus blue LEDs reduced the vitamin C content of green leaf lettuce by 44%and anthocyanin content of purple leaf lettuce by 30%compared with red plus blue LEDs,respectively.Spectral absorbencies of purple leaf lettuce grown under red plus blue LEDs supplemented with green light were lower in green light region compared with those grown under red plus blue LEDs,which was associated with anthocyanin contents.White plus red LEDs significantly increased leaf fresh and dry weights of purple leaf lettuce by 25%,and no significant differences were observed in vitamin C and nitrate contents compared with white LEDs.Fresh weight,light and electrical energy use efficiencies of hydroponic green and purple leaf lettuces grown under white plus red LEDs were higher or no significant differences compared with those grown under red plus blue LEDs.In conclusion,white plus red LEDs were suggested to substitute for red plus blue LEDs in hydroponic lettuce(cv.Lvdie and Ziya)production in plant factories with artificial lighting.

Effects of LED light quality on the growth of pepper seedling in plant factory

The extensive environment,especially low temperature and weak lighting in winter and spring,which limits the growth of pepper(Capicum annuum L.)seedlings,the use of plant factory with artificial lighting technology can effectively control the lighting environment to produce high-quality seedlings.In this study,white LED lamps with R:B ratio of 0.7(L0.7)and 1.5(L1.5)and red-blue LED lamps with R:B ratio of 3.5(L3.5)were used to cultivate seedlings of“CAU-24”pepper in the light intensity of 250μmol/m^(2)·s and photoperiod of 12 h/d,white fluorescent lamps with R:B ratio of 1.7(F1.7)was used as control.The results showed that plant height,stem diameter,hypocotyl length,biomass accumulation,light energy use efficiency(LUE)and electric energy use efficiency(EUE)of pepper seedling under L1.5 were the highest.After 36 days of sowing,the dry weight of shoot reached 302.8±45.2 mg/plant.Leaf area reached maximum value of 153.5±22.0 cm^(2) under L0.7.The contents of chlorophyll a,chlorophyll b and total chlorophyll of pepper seedling leaves under all kinds of LED light were greater than F1.7,but there was no significant difference in net photosynthetic rate.The total dry weight with lamp electric power consumption of L1.5 were 3.0 g/(kW·h)which was 1.5,2,and 3 times greater than that of L3.5,L0.7,and F1.7,respectively.Therefore,compared with fluorescent lamp and other LED lamps,the white LED light quality with R:B ratio of 1.5 is suitable for pepper seedling production in plant factory because of the high LED lighting efficiency,greater LUE and EUE.

Modeling of maize gross primary production using MODIS imagery and flux tower data

Maize is one of the most important crops cultivated on the global scale.Accurate estimation of maize Gross Primary Production(GPP)can provide valuable information for regional and global carbon budget studies.From site level to regional/global scales,GPP estimation depends on remote sensing or eddy covariance flux data.In this research,the 8-day composite GPP of maize was estimated by Moderate Resolution Imaging Spectroradiometer(MODIS)and flux tower data at eight study sites using a Regional Production Efficiency Model(REG-PEM).The performance of the model was assessed by analyzing the linearly regression of GPP estimated from the REG-PEM model(GPPEST)with the GPP predicted from the eddy covariance data(GPPEC).The coefficient of determination,root mean squared error and mean absolute error of the regression model were calculated.The uncertainties of the model are also discussed in this research.The seasonal dynamics(phases and magnitudes)of the GPPEST reasonably agreed with those of GPPEC,indicating the potential of the satellite-driven REG-PEM model for up-scaling the GPP in maize croplands.Furthermore,the maize GPP estimated by this model is more accurate than the MODIS GPP products(MOD17A2).In particular,MOD17A2 significantly underestimated the GPP of maize croplands.The uncertainties in the REG-PEM model are mostly contributed by the maximum light use efficiency and the fraction of photosynthetically active radiation.

Estimation of Terrestrial Net Primary Productivity in China from Fengyun-3D Satellite Data

Currently,the satellite data used to estimate terrestrial net primary productivity(NPP)in China are predominantly from foreign satellites,and very few studies have based their estimates on data from China’s Fengyun satellites.Moreover,despite their importance,the influence of land cover types and the normalized difference vegetation index(NDVI)on NPP estimation has not been clarified.This study employs the Carnegie–Ames–Stanford approach(CASA)model to compute the fraction of absorbed photosynthetically active radiation and the maximum light use efficiency suitable for the main vegetation types in China in accordance with the finer resolution observation and monitoring-global land cover(FROM-GLC)classification product.Then,the NPP is estimated from the Fengyun-3D(FY-3D)data and compared with the Moderate Resolution Imaging Spectroradiometer(MODIS)NPP product.The FY-3D NPP is also validated with existing research results and historical field-measured NPP data.In addition,the effects of land cover types and the NDVI on NPP estimation are analyzed.The results show that the CASA model and the FY-3D satellite data estimate an average NPP of 441.2 g C m^(−2) yr^(−1) in 2019 for China’s terrestrial vegetation,while the total NPP is 3.19 Pg C yr^(−1).Compared with the MODIS NPP,the FY-3D NPP is overestimated in areas of low vegetation productivity and is underestimated in high-productivity areas.These discrepancies are largely due to the differences between the FY-3D NDVI and MODIS NDVI.Compared with historical field-measured data,the FY-3D NPP estimation results outperformed the MODIS NPP results,although the deviation between the FY-3D NPP estimate and the in-situ measurement was large and may exceed 20%at the pixel scale.The land cover types and the NDVI significantly affected the spatial distribution of NPP and accounted for NPP deviations of 17.0%and 18.1%,respectively.Additionally,the total deviation resulting from the two factors reached 29.5%.These results show that accurate NDVI products and land cover types are important prerequisites for NPP estimation.

Large-scale estimates of gross primary production on the Qinghai-Tibet plateau based on remote sensing data

Vegetation gross primary production(GPP)is an important variable for the carbon cycle on the Qinghai-Tibetan Plateau(QTP).Based on the measurements from 12 eddy covariance flux sites,we validated a light use efficiency model(i.e.EC-LUE)to evaluate the spatial-temporal patterns of GPP and the effect of environmental variables on QTP.In general,EC-LUE model performed well in predicting GPP at different time scale over QTP.Annual GPP over the entire QTP ranged from 575 to 703 Tg C,and showed a significantly increasing trend from 1982 to 2013.However,there were large spatial heterogeneities in long-term trends of GPP.Throughout the entire QTP,air temperature increase had a greater influence than solar radiation and precipitation(PREC)changes on productivity.Moreover,our results highlight the large uncertainties of previous GPP estimates due to insufficient parameterization and validations.When compared with GPP estimates of the EC-LUE model,most Coupled Model Intercomparison Project(CMIP5)GPP products overestimate the magnitude and increasing trends of regional GPP,which potentially impact the feedback of ecosystems to regional climate changes.

Higher plant photosynthetic capability in autumn responding to low atmospheric vapor pressure deficit

It has been long established that the terrestrial vegetation in spring has stronger photosynthetic capability than in autumn.However,this study challenges this consensus by comparing photosynthetic capability of terrestrial vegetation between the spring and autumn seasons based on measurements of 100 in situ eddy covariance towers over global extratropical ecosystems.At the majority of these sites,photosynthetic capability,indicated by light use efficiency(LUE)and apparent quantum efficiency,is significantly higher in autumn than in spring,due to lower atmosphere vapor pressure deficit(VPD)at the same air temperature.Seasonal VPD differences also substantially explain the interannual variability of the differences in photosynthetic capability between spring and autumn.We further reveal that VPD in autumn is significantly lower than in spring over 74.14% of extratropical areas,based on a global climate dataset.In contrast,LUE derived from a data-driven vegetation production dataset is significantly higher in autumn in over 61.02% of extratropical vegetated areas.Six Earth system models consistently projected continuous larger VPD values in spring compared with autumn,which implies that the impacts on vegetation growth will long exist and should be adequately considered when assessing the seasonal responses of terrestrial ecosystems to future climate conditions.