Accurate estimation of gross primary production(GPP)of terrestrial vegetation is crucial for comprehending the carbon dynamics.To date,there is still no consensus on the magnitude and seasonality of global GPP among t...Accurate estimation of gross primary production(GPP)of terrestrial vegetation is crucial for comprehending the carbon dynamics.To date,there is still no consensus on the magnitude and seasonality of global GPP among the major global GPP products,underscoring the necessity to improve GPP models for higher accuracy of global GPP estimates.Here,we introduce an improved Vegetation Photosynthesis Model(VPM v3.0),which incorporates site-specific apparent optimum temperature for photosynthesis,leaf-trait-based light absorption(flat leaf vs.needle leaf),and improved water stress estimation.The global VPM simulation is driven by Moderate Resolution Imaging Spectroradiometer images and the ERA5-Land climate dataset.We evaluate VPM v3.0 using GPP from 205 eddy flux tower sites across 11 land cover types(1,658 site-years)(GPPEC),as well as the TROPOspheric monitoring instrument(TROPOMI)solar-induced fluorescence(SIF)product for 2018 to 2021.The slope,R^(2),and root mean square error between GPP from VPM v3.0(GPPVPM-v3)and GPPEC are 0.97,0.78,and 1.46 gC m^(−2) day^(−1),respectively.GPPVPM-v3 shows high temporal consistency with TROPOMI SIF.VPM v3.0 provides higher accuracy of GPP estimates at most evaluated sites than VPM v2.0.Comparisons of global GPP from VPM v3.0 with other major global GPP products reveal both spatial-temporal consistency and discrepancies.These findings clearly indicate the improved accuracy of VPM v3.0 in estimating GPP,making it suitable for generating global GPP datasets.展开更多
Canopy photosynthetic productivity is crucial for the formation of crop yields.Identifying limiting factors and adjustment targets for canopy photosynthesis in specific climates is important for yield increase.However...Canopy photosynthetic productivity is crucial for the formation of crop yields.Identifying limiting factors and adjustment targets for canopy photosynthesis in specific climates is important for yield increase.However,conducting relevant quantitative research remains challenging.In this study,two typical regions with distinct climatic characteristics were selected for a two-year trial of greenhouse tomatoes grown in different seasons.A three-dimensional canopy photosynthesis model was developed to quantify the factor contributions to the regional differences in accumulated canopy photosynthesis throughout the entire growing season(ACP),and to predict gains in ACP through three scenarios:leaf photosynthetic modifications(S1),plant layout adjustments(S2),and greenhouse film haze increase(S3).The results indicated that differences in ACP were mainly influ-enced by light environment(LE),leaf photosynthetic physiology(PP),and LE-PP interaction in spring,and canopy structure(CS),PP,LE,and LE-PP interaction in autumn.The predicted ACP enhancement showed as S1>S2>S3,with S3 showing a more limited effect.The light quantum efficiency under limiting light(κ_(2LL))and maximum electron transport rate(J_(max))were identified as key biochemical phenotypes for tomato high photo-synthetic efficiency breeding in different environments.Additionally,adjusting row spacing under current planting density could further improve ACP.Our conclusions could assist researchers in deepening their un-derstanding of canopy photosynthesis limitations under real production conditions,and provide a theoretical foundation for optimizing greenhouse tomato yield in the context of climate change.展开更多
Basic structure and algorithm of leaf mechanism photosynthesis model were described in first part of this study based on former researcher results. Then, considering some environmental factors influencing on leaf ph...Basic structure and algorithm of leaf mechanism photosynthesis model were described in first part of this study based on former researcher results. Then, considering some environmental factors influencing on leaf photosynthesis, three numerical sensitivity experiments were carried out. We simulated the sing le leaf net CO2 assimilation, which acts as a function of different light, carbo n dioxide and temperature conditions. The relationships between leaf net photosy nthetic rate of C3 and C4 plant with CO2 concentration intercellular, leaf tempe rature, and photosynthetic active radiation (PAR) were presented, respectively. The results show the numerical experiment may indicate the main characteristic o f plant photosynthesis in C3 and C4 plant, and further can be used to integrate with the regional climate model and act as land surface process scheme, and bett er understand the interaction between vegetation and atmosphere.展开更多
Basic structure and algorithm of leaf mechanism photosynthesis model were described in first part of this study based on former researcher results. Then, considering some environmental factors influencing on leaf ph...Basic structure and algorithm of leaf mechanism photosynthesis model were described in first part of this study based on former researcher results. Then, considering some environmental factors influencing on leaf photosynthesis, three numerical sensitivity experiments were carried out. We simulated the sing le leaf net CO2 assimilation, which acts as a function of different light, carbo n dioxide and temperature conditions. The relationships between leaf net photosy nthetic rate of C3 and C4 plant with CO2 concentration intercellular, leaf tempe rature, and photosynthetic active radiation (PAR) were presented, respectively. The results show the numerical experiment may indicate the main characteristic o f plant photosynthesis in C3 and C4 plant, and further can be used to integrate with the regional climate model and act as land surface process scheme, and bett er understand the interaction between vegetation and atmosphere.展开更多
CO_(2)concentration is an environmental factor affecting photosynthesis and consequently the yield and quality of tomatoes.In this study,a photosynthesis prediction model for the entire growth stage of tomatoes was co...CO_(2)concentration is an environmental factor affecting photosynthesis and consequently the yield and quality of tomatoes.In this study,a photosynthesis prediction model for the entire growth stage of tomatoes was constructed to elevate CO_(2)level on the basis of crop requirements and to evaluate the effect of CO_(2)elevation on leaf photosynthesis.The effect of CO_(2)enrichment on tomato photosynthesis was investigated using two CO_(2)enrichment treatments at the entire growth stage.A wireless sensor network-based environmental monitoring system was used for the real-time monitoring of environmental factors,and the LI-6400XT portable photosynthesis system was used to measure the net photosynthetic rate of tomato leaf.As input variables for the model,environmental factors were uniformly preprocessed using independent component analysis.Moreover,the photosynthesis prediction model for the entire growth stage was established on the basis of the support vector machine(SVM)model.Improved particle swarm optimization(PSO)was also used to search for the best parameters c and g of SVM.Furthermore,the relationship between CO_(2)concentration and photosynthetic rate under varying light intensities was predicted using the established model,which can determine CO_(2)saturation points at the various growth stages.The determination coefficients between the simulated and observed data sets for the three growth stages were 0.96,0.96,and 0.94 with the improved PSO-SVM and 0.89,0.87,and 0.86 with the original PSO-SVM.The results indicate that the improved PSO-SVM exhibits a high prediction accuracy.The study provides a basis for the precise regulation of CO_(2)enrichment in greenhouses.展开更多
Hainan Island,known as China's‘Nanfan Silicon Valley',is a vital tropical agricultural zone where double cropping rice predominates.However,fragmented farmland and poor soil quality in some regions have reduc...Hainan Island,known as China's‘Nanfan Silicon Valley',is a vital tropical agricultural zone where double cropping rice predominates.However,fragmented farmland and poor soil quality in some regions have reduced yields,threatening local food security.Identifying actual and potential yield gaps in double cropping rice and proposing targeted yield-improvement measures thus hold important theoretical and practical value.This study first precisely determined the reproductive periods of double cropping rice in Hainan Island of China,then used the Vegetation Photosynthesis Model(VPM)to estimate actual yields for 2000,2010,and 2020.Subsequently,potential yields were simulated with the Global Agro-Ecological Zones(GAEZ)model,enabling grid-scale comparison between actual and potential yields.Finally,tailored strategies for increasing rice production were proposed for areas with significant yield gaps.The results show that:1)the actual yields of early rice increased in the north but decreased in the west and south of Hainan Island,with over 95%of changes within 3000kg/ha;late rice and all-year rice yields rose across more than 80%of the island's area.2)During 2000–2020,early rice consistently showed lower potential yields and production than late rice.The potential yields of all three rice types declined in most regions,especially in the north where they fell below 3000kg/ha,while rising by 3000–6000kg/ha across much of the west and south.3)Significant yield gaps were observed in coastal regions,particularly in western and southern Hainan Island,where absolute yield gaps(AYG)of early and late rice exceeded 1000 kg/ha and 1500 kg/ha,respectively,and relative yield gaps(RYG)surpassed 100%in most coastal areas.4)To narrow yield gaps in high-gap regions,spatially tailored measures were proposed,including precision water-nutrient management,wind-erosion control via shelterbelts,land consolidation into larger contiguous blocks,and policy incentives for irrigation and fertilizer support.These integrated strategies are expected to enhance rice productivity and strengthen food security in Hainan Island.展开更多
Carbon and water fluxes of savannas and grasslands have large seasonal dynamics and inter-annual variation. In this study, we selected five savanna and grassland sites, each of them having 10+ years (11−21 years) of e...Carbon and water fluxes of savannas and grasslands have large seasonal dynamics and inter-annual variation. In this study, we selected five savanna and grassland sites, each of them having 10+ years (11−21 years) of eddy covariance (EC) data, and a total of 85 site-years at these five sites which offers a unique opportunity for data analyses and model evaluation. We ran a long-term simulation (2000−2021) of the vegetation photosynthesis model (VPM, v3.0) and vegetation transpiration model (VTM, v2.0) to investigate the seasonal dynamics, interannual variation, and decadal trends of modeled gross primary production (GPPVPM) and transpiration (TVTM) at these sites. The seasonal dynamics of daily GPPVPM and TVTM track well with the seasonal dynamics of EC-based GPP (GPPEC, R2: 0.76−0.93) and evapotranspiration (ETEC, R2: 0.69−0.92). The inter-annual variation of annual GPPVPM tracked well that of annual GPPEC, with the linear regression slopes for GPPEC versus GPPVPM-EC ranging from 0.89 to 1.11. The simulation results of GPPVPM and TVTM using two different climate data sets (in situ climate data and European Center for Medium-Range Weather Forecasts Reanalysis v5 data set (ERA5)) were similar, suggesting that ERA5 data can be used for VPM/VTM simulations at large spatial scales. From 2000 to 2021, annual GPPVPM and TVTM had no significant inter-annual trends at one savanna and three grassland sites but increased significantly at one savanna site. The results demonstrate the potential of using VPM (v3.0) and VTM (v2.0) to predict the seasonal dynamics and inter-annual variation of GPP and T in savannas and grasslands.展开更多
Given the lack of technical conditions and research methods,instruments that can measure the canopy apparent photosynthetic rate have low precision and are rarely studied.Comparative studies on canopy apparent photosy...Given the lack of technical conditions and research methods,instruments that can measure the canopy apparent photosynthetic rate have low precision and are rarely studied.Comparative studies on canopy apparent photosynthetic rate and single leaf photosynthetic rate are also relatively few.This study aims to measure and predict the canopy apparent photosynthetic rate of tomato.A canopy apparent photosynthetic rate measuring system,which was comprised of a wireless sensor network(WSN),an assimilation chamber,and a LI-6400XT photosynthetic rate instrument was established.The system was used to determine the greenhouse environmental parameters and CO2 absorptive capacity of the whole growth stage of tomato.A semi-closed assimilation chamber was designed as a side opening to conveniently measure the canopy apparent photosynthetic rate.WSN nodes were placed in the chamber to monitor environmental parameters,including air temperature,air humidity,and assimilation chamber temperature.A grid and pixel conversion method was used to measure the whole plant leaf areas of tomato.As a semi-closed measurement system,the assimilation chamber was used to calculate the canopy apparent photosynthetic rate.To conduct a comparative research on the canopy apparent photosynthetic rate and the single leaf photosynthetic rate,the LI-6400XT portable photosynthesis system was used to measure the single leaf photosynthetic rate,and the support vector machine was used to establish the prediction model of canopy apparent photosynthetic rate.The experimental results indicated that the correlation coefficients of the photosynthesis prediction model in the seeding and flowering stages were 0.9420 and 0.9226,respectively,showing the high accuracy of the SVM model.展开更多
基金supported by research grants from the U.S.National Science Foundation(OIA-1946093 and OIA-1920946)NASA(80NSSC24K0118)USDA National Institute of Food and Agriculture(2020-67014-30935).
文摘Accurate estimation of gross primary production(GPP)of terrestrial vegetation is crucial for comprehending the carbon dynamics.To date,there is still no consensus on the magnitude and seasonality of global GPP among the major global GPP products,underscoring the necessity to improve GPP models for higher accuracy of global GPP estimates.Here,we introduce an improved Vegetation Photosynthesis Model(VPM v3.0),which incorporates site-specific apparent optimum temperature for photosynthesis,leaf-trait-based light absorption(flat leaf vs.needle leaf),and improved water stress estimation.The global VPM simulation is driven by Moderate Resolution Imaging Spectroradiometer images and the ERA5-Land climate dataset.We evaluate VPM v3.0 using GPP from 205 eddy flux tower sites across 11 land cover types(1,658 site-years)(GPPEC),as well as the TROPOspheric monitoring instrument(TROPOMI)solar-induced fluorescence(SIF)product for 2018 to 2021.The slope,R^(2),and root mean square error between GPP from VPM v3.0(GPPVPM-v3)and GPPEC are 0.97,0.78,and 1.46 gC m^(−2) day^(−1),respectively.GPPVPM-v3 shows high temporal consistency with TROPOMI SIF.VPM v3.0 provides higher accuracy of GPP estimates at most evaluated sites than VPM v2.0.Comparisons of global GPP from VPM v3.0 with other major global GPP products reveal both spatial-temporal consistency and discrepancies.These findings clearly indicate the improved accuracy of VPM v3.0 in estimating GPP,making it suitable for generating global GPP datasets.
基金This work was funded by China Agriculture Research System(CARS-23-C-05)National Natural Science Foundation of China(32472816).
文摘Canopy photosynthetic productivity is crucial for the formation of crop yields.Identifying limiting factors and adjustment targets for canopy photosynthesis in specific climates is important for yield increase.However,conducting relevant quantitative research remains challenging.In this study,two typical regions with distinct climatic characteristics were selected for a two-year trial of greenhouse tomatoes grown in different seasons.A three-dimensional canopy photosynthesis model was developed to quantify the factor contributions to the regional differences in accumulated canopy photosynthesis throughout the entire growing season(ACP),and to predict gains in ACP through three scenarios:leaf photosynthetic modifications(S1),plant layout adjustments(S2),and greenhouse film haze increase(S3).The results indicated that differences in ACP were mainly influ-enced by light environment(LE),leaf photosynthetic physiology(PP),and LE-PP interaction in spring,and canopy structure(CS),PP,LE,and LE-PP interaction in autumn.The predicted ACP enhancement showed as S1>S2>S3,with S3 showing a more limited effect.The light quantum efficiency under limiting light(κ_(2LL))and maximum electron transport rate(J_(max))were identified as key biochemical phenotypes for tomato high photo-synthetic efficiency breeding in different environments.Additionally,adjusting row spacing under current planting density could further improve ACP.Our conclusions could assist researchers in deepening their un-derstanding of canopy photosynthesis limitations under real production conditions,and provide a theoretical foundation for optimizing greenhouse tomato yield in the context of climate change.
基金Natural Science Foundation of China (Grant No. 39900084)
文摘Basic structure and algorithm of leaf mechanism photosynthesis model were described in first part of this study based on former researcher results. Then, considering some environmental factors influencing on leaf photosynthesis, three numerical sensitivity experiments were carried out. We simulated the sing le leaf net CO2 assimilation, which acts as a function of different light, carbo n dioxide and temperature conditions. The relationships between leaf net photosy nthetic rate of C3 and C4 plant with CO2 concentration intercellular, leaf tempe rature, and photosynthetic active radiation (PAR) were presented, respectively. The results show the numerical experiment may indicate the main characteristic o f plant photosynthesis in C3 and C4 plant, and further can be used to integrate with the regional climate model and act as land surface process scheme, and bett er understand the interaction between vegetation and atmosphere.
基金Natural Science Foundation of China (Grant No. 39900084)
文摘Basic structure and algorithm of leaf mechanism photosynthesis model were described in first part of this study based on former researcher results. Then, considering some environmental factors influencing on leaf photosynthesis, three numerical sensitivity experiments were carried out. We simulated the sing le leaf net CO2 assimilation, which acts as a function of different light, carbo n dioxide and temperature conditions. The relationships between leaf net photosy nthetic rate of C3 and C4 plant with CO2 concentration intercellular, leaf tempe rature, and photosynthetic active radiation (PAR) were presented, respectively. The results show the numerical experiment may indicate the main characteristic o f plant photosynthesis in C3 and C4 plant, and further can be used to integrate with the regional climate model and act as land surface process scheme, and bett er understand the interaction between vegetation and atmosphere.
基金the National Key Research and Development Program(Grant No.2016YFD0200602)National Natural Science Fund(Grant No.31271619).
文摘CO_(2)concentration is an environmental factor affecting photosynthesis and consequently the yield and quality of tomatoes.In this study,a photosynthesis prediction model for the entire growth stage of tomatoes was constructed to elevate CO_(2)level on the basis of crop requirements and to evaluate the effect of CO_(2)elevation on leaf photosynthesis.The effect of CO_(2)enrichment on tomato photosynthesis was investigated using two CO_(2)enrichment treatments at the entire growth stage.A wireless sensor network-based environmental monitoring system was used for the real-time monitoring of environmental factors,and the LI-6400XT portable photosynthesis system was used to measure the net photosynthetic rate of tomato leaf.As input variables for the model,environmental factors were uniformly preprocessed using independent component analysis.Moreover,the photosynthesis prediction model for the entire growth stage was established on the basis of the support vector machine(SVM)model.Improved particle swarm optimization(PSO)was also used to search for the best parameters c and g of SVM.Furthermore,the relationship between CO_(2)concentration and photosynthetic rate under varying light intensities was predicted using the established model,which can determine CO_(2)saturation points at the various growth stages.The determination coefficients between the simulated and observed data sets for the three growth stages were 0.96,0.96,and 0.94 with the improved PSO-SVM and 0.89,0.87,and 0.86 with the original PSO-SVM.The results indicate that the improved PSO-SVM exhibits a high prediction accuracy.The study provides a basis for the precise regulation of CO_(2)enrichment in greenhouses.
基金Under the auspices of National Key R&D Program of China(No.2023YFD1900101)Hainan Provincial Natural Science Foundation of China(No.723RC466)+2 种基金Hainan Provincial Philosophy and Social Science Planning Project(No.HNSK(QN)24-17,HNSK(JD)24-08)Young Scholars Support Program of Hainan University(No.24QNFC-05)Project supported by the Education Department of Hainan Province(No.Hnky2025-4,Hnky2024-4)。
文摘Hainan Island,known as China's‘Nanfan Silicon Valley',is a vital tropical agricultural zone where double cropping rice predominates.However,fragmented farmland and poor soil quality in some regions have reduced yields,threatening local food security.Identifying actual and potential yield gaps in double cropping rice and proposing targeted yield-improvement measures thus hold important theoretical and practical value.This study first precisely determined the reproductive periods of double cropping rice in Hainan Island of China,then used the Vegetation Photosynthesis Model(VPM)to estimate actual yields for 2000,2010,and 2020.Subsequently,potential yields were simulated with the Global Agro-Ecological Zones(GAEZ)model,enabling grid-scale comparison between actual and potential yields.Finally,tailored strategies for increasing rice production were proposed for areas with significant yield gaps.The results show that:1)the actual yields of early rice increased in the north but decreased in the west and south of Hainan Island,with over 95%of changes within 3000kg/ha;late rice and all-year rice yields rose across more than 80%of the island's area.2)During 2000–2020,early rice consistently showed lower potential yields and production than late rice.The potential yields of all three rice types declined in most regions,especially in the north where they fell below 3000kg/ha,while rising by 3000–6000kg/ha across much of the west and south.3)Significant yield gaps were observed in coastal regions,particularly in western and southern Hainan Island,where absolute yield gaps(AYG)of early and late rice exceeded 1000 kg/ha and 1500 kg/ha,respectively,and relative yield gaps(RYG)surpassed 100%in most coastal areas.4)To narrow yield gaps in high-gap regions,spatially tailored measures were proposed,including precision water-nutrient management,wind-erosion control via shelterbelts,land consolidation into larger contiguous blocks,and policy incentives for irrigation and fertilizer support.These integrated strategies are expected to enhance rice productivity and strengthen food security in Hainan Island.
基金supported by research grant from the US National Science Foundation (OIA-1946093)supported in part by the US Department of Energy’s Office of Science. Data for these AmeriFlux sites can be downloaded from FLUXNET2015 website.
文摘Carbon and water fluxes of savannas and grasslands have large seasonal dynamics and inter-annual variation. In this study, we selected five savanna and grassland sites, each of them having 10+ years (11−21 years) of eddy covariance (EC) data, and a total of 85 site-years at these five sites which offers a unique opportunity for data analyses and model evaluation. We ran a long-term simulation (2000−2021) of the vegetation photosynthesis model (VPM, v3.0) and vegetation transpiration model (VTM, v2.0) to investigate the seasonal dynamics, interannual variation, and decadal trends of modeled gross primary production (GPPVPM) and transpiration (TVTM) at these sites. The seasonal dynamics of daily GPPVPM and TVTM track well with the seasonal dynamics of EC-based GPP (GPPEC, R2: 0.76−0.93) and evapotranspiration (ETEC, R2: 0.69−0.92). The inter-annual variation of annual GPPVPM tracked well that of annual GPPEC, with the linear regression slopes for GPPEC versus GPPVPM-EC ranging from 0.89 to 1.11. The simulation results of GPPVPM and TVTM using two different climate data sets (in situ climate data and European Center for Medium-Range Weather Forecasts Reanalysis v5 data set (ERA5)) were similar, suggesting that ERA5 data can be used for VPM/VTM simulations at large spatial scales. From 2000 to 2021, annual GPPVPM and TVTM had no significant inter-annual trends at one savanna and three grassland sites but increased significantly at one savanna site. The results demonstrate the potential of using VPM (v3.0) and VTM (v2.0) to predict the seasonal dynamics and inter-annual variation of GPP and T in savannas and grasslands.
基金supported by the Yunnan Academician Expert Workstation(Li Minzan,Grant No.20170907).
文摘Given the lack of technical conditions and research methods,instruments that can measure the canopy apparent photosynthetic rate have low precision and are rarely studied.Comparative studies on canopy apparent photosynthetic rate and single leaf photosynthetic rate are also relatively few.This study aims to measure and predict the canopy apparent photosynthetic rate of tomato.A canopy apparent photosynthetic rate measuring system,which was comprised of a wireless sensor network(WSN),an assimilation chamber,and a LI-6400XT photosynthetic rate instrument was established.The system was used to determine the greenhouse environmental parameters and CO2 absorptive capacity of the whole growth stage of tomato.A semi-closed assimilation chamber was designed as a side opening to conveniently measure the canopy apparent photosynthetic rate.WSN nodes were placed in the chamber to monitor environmental parameters,including air temperature,air humidity,and assimilation chamber temperature.A grid and pixel conversion method was used to measure the whole plant leaf areas of tomato.As a semi-closed measurement system,the assimilation chamber was used to calculate the canopy apparent photosynthetic rate.To conduct a comparative research on the canopy apparent photosynthetic rate and the single leaf photosynthetic rate,the LI-6400XT portable photosynthesis system was used to measure the single leaf photosynthetic rate,and the support vector machine was used to establish the prediction model of canopy apparent photosynthetic rate.The experimental results indicated that the correlation coefficients of the photosynthesis prediction model in the seeding and flowering stages were 0.9420 and 0.9226,respectively,showing the high accuracy of the SVM model.
