Leaf pigments are critical indicators of plant photosynthesis,stress,and physiological conditions.Inversion of radiative transfer models(RTMs)is a promising method for robustly retrieving leaf biochem-ical traits from...Leaf pigments are critical indicators of plant photosynthesis,stress,and physiological conditions.Inversion of radiative transfer models(RTMs)is a promising method for robustly retrieving leaf biochem-ical traits from canopy observations,and adding prior information has been effective in alleviating the“ill-posed”problem,a major challenge in model inversion.Canopy structure parameters,such as leaf area index(LAI)and average leaf inclination angle(ALA),can serve as prior information for leaf pigment retrie-val.Using canopy spectra simulated from the PROSAIL model,we estimated the effects of uncertainty in LAI and ALA used as prior information for lookup table-based inversions of leaf chlorophyll(C _(ab))and car-otenoid(C_(ar)).The retrieval accuracies of the two pigments were increased by use of the priors of LAI(RMSE of C_(ab) from 7.67 to 6.32μg cm^(-2),C_(ar) from 2.41 to 2.28μg cm^(-2))and ALA(RMSE of C_(ab) from 7.67 to 5.72μg cm^(-2),C_(ar) from 2.41 to 2.23μg cm^(-2)).However,this improvement deteriorated with an increase of additive and multiplicative uncertainties,and when 40% and 20% noise was added to LAI and ALA respectively,these priors ceased to increase retrieval accuracy.Validation using an experimental winter wheat dataset also showed that compared with C_(ar),the estimation accuracy of C_(ab) increased more or deteriorated less with uncertainty in prior canopy structure.This study demonstrates possible limita-tions of using prior information in RTM inversions for retrieval of leaf biochemistry,when large uncer-tainties are present.展开更多
Increased global vegetation gross primary productivity(GPP)over the past decades has led to an enhanced terrestrial carbon sink,an important factor in mitigating global warming.However,the global spatiotemporal evolut...Increased global vegetation gross primary productivity(GPP)over the past decades has led to an enhanced terrestrial carbon sink,an important factor in mitigating global warming.However,the global spatiotemporal evolution of GPP trends is still under debate,largely limiting our understanding of the sustainability in terrestrial carbon sink.Here in this study,based on a dozen of long-term global GPP datasets,we found that global GPP trends fell significantly from 0.43 PgC year^(−2) in 1982–1999 to 0.17 PgC year^(−2) in 2000–2016,a signal detected across>68%of the terrestrial surface.The decrease in GPP trends was more pronounced from satellite-based GPP datasets than from process-based models,which may result from a decline in the CO_(2) fertilization effect.This finding therefore indicates that the terrestrial carbon sink may become saturated in the future,and highlights the urgent need of stricter strategies for reducing carbon emissions to mitigate global warming.展开更多
Background The savannah ecosystems of Sahel have experienced continuous and heavy grazing of livestock for centuries but still,their vegetation response to grazing pressure remains poorly understood.In this study,we a...Background The savannah ecosystems of Sahel have experienced continuous and heavy grazing of livestock for centuries but still,their vegetation response to grazing pressure remains poorly understood.In this study,we analysed the herbaceous plant dynamics,measured by species diversity,composition,cover,and biomass in response to grazing pressure in the savannah ecosystems of Sahel.In Senegal,we selected four savannah sites represented with high,moderate,light and no grazing intensity levels.Transect survey methods were used for sampling the vegetation data within each of the sites.Species richness and composition were analysed using species accumulation curve and multivariate analyses.Furthermore,we used General Linear Models and a piecewise Structural Equation Model(pSEM)to examine the relationships between grazing intensity,vegetation cover,diversity and biomass.Results The herbaceous species diversity and composition varied significantly among the different grazing intensity levels(p<0.001).The plant species composition shifted from the dominance of grass cover to the dominance of forb cover with increasing grazing pressure.Moreover,the attributes of species diversity,herbaceous biomass,and ground cover were higher on sites with low grazing than sites with high and moderate grazing intensity.Across all sites,species diversity was positively related to total biomass.The pSEM explained 37%of the variance in total biomass and revealed that grazing intensity negatively influenced total biomass both directly and indirectly through its negative influence on species diversity.Conclusions Managing grazing intensity may lead to higher plant production and higher mixed forage establishment in the dryland savannah ecosystems.This information can be used to support land management strategies and promote sustainable grazing practices that balance the needs of livestock with the conservation of ecosystem health and biodiversity.展开更多
The ratio of leaf carotenoid to chlorophyll(Car/Chl)is an indicator of vegetation photosynthesis,development and responses to stress.However,the correlation between Car and Chl,and their overlapping absorption in the ...The ratio of leaf carotenoid to chlorophyll(Car/Chl)is an indicator of vegetation photosynthesis,development and responses to stress.However,the correlation between Car and Chl,and their overlapping absorption in the visible spectral domain pose a challenge for optical remote sensing of their ratio.This study aims to investigate combinations of vegetation indices(VIs)to minimize the influence of Car-Chl correlation,thus being more sensitive to the variability in the ratio across vegetation species and sites.VIs sensitive to Car and Chl variability were combined into four candidates of combinations,using a simulated dataset from the PROSPECT model.The VI combinations were then tested using six simulated datasets with different Car-Chl correlations,and evaluated against four independent datasets.The ratio of the carotenoid triangle ratio index(CTRI)with the red-edge chlorophyll index(CIred-edge)was found least influenced by the Car-Chl correlation and demonstrated a superior ability for estimating Car/Chl variability.Compared with published VIs and two machine learning algorithms,CTRI/CIred-edge also showed the optimal performance in the fourfield datasets.This new VI combination could be useful to provide insights in spatiotemporal variability in the leaf Car/Chl ratio,applicable for assessing vegetation physiology,phenology,and response to environmental stress.展开更多
基金supported by the National Natural Science Foundation of China (41975044)the Open Research Fund of the State Laboratory of Information Engineering in Surveying,Mapping,Remote Sensing,Wuhan University (20R02)+2 种基金the Fundamental Research Funds for the Central Universities,China University of Geosciences (Wuhan)(111-G1323520290)funded by SNSA (Dnr 96/16)the EU-Aid funded CASSECS Project。
文摘Leaf pigments are critical indicators of plant photosynthesis,stress,and physiological conditions.Inversion of radiative transfer models(RTMs)is a promising method for robustly retrieving leaf biochem-ical traits from canopy observations,and adding prior information has been effective in alleviating the“ill-posed”problem,a major challenge in model inversion.Canopy structure parameters,such as leaf area index(LAI)and average leaf inclination angle(ALA),can serve as prior information for leaf pigment retrie-val.Using canopy spectra simulated from the PROSAIL model,we estimated the effects of uncertainty in LAI and ALA used as prior information for lookup table-based inversions of leaf chlorophyll(C _(ab))and car-otenoid(C_(ar)).The retrieval accuracies of the two pigments were increased by use of the priors of LAI(RMSE of C_(ab) from 7.67 to 6.32μg cm^(-2),C_(ar) from 2.41 to 2.28μg cm^(-2))and ALA(RMSE of C_(ab) from 7.67 to 5.72μg cm^(-2),C_(ar) from 2.41 to 2.23μg cm^(-2)).However,this improvement deteriorated with an increase of additive and multiplicative uncertainties,and when 40% and 20% noise was added to LAI and ALA respectively,these priors ceased to increase retrieval accuracy.Validation using an experimental winter wheat dataset also showed that compared with C_(ar),the estimation accuracy of C_(ab) increased more or deteriorated less with uncertainty in prior canopy structure.This study demonstrates possible limita-tions of using prior information in RTM inversions for retrieval of leaf biochemistry,when large uncer-tainties are present.
基金financially supported by the National Key R&D Program of China(2022YFF0803100)the Fundamental Research Funds for the Central Universities(KJJQ2024002)+11 种基金the National Natural Science Foundation of China(32322064,32471675,42071050&32101340)the financial support from Jiangsu Provincial Natural Science Foundation for Dis tinguished Young Scholars(BK20220083)the Young Elite Scientists Sponsorship Program by China Association for Science and Technology(2021QNRC001)the Carbon Peak and Carbon Neutralization Key Science and technology Program of Suzhou(ST202228)funding from the Swedish National Space Agency(Dnr 95/16&F2022/497)Formas,and the Eu-Adid funded CASSECS projectsupport from the NASA SMAP(grant 80NSSC20K1805)NASA CCE(80NSSC21K1709)the financial support from the National Natural Science Foundation of China(41901266)the financial support from the Spanish Government grant PID2019-110521GB-I00the Fundación Ramón Areces grant ELEMENTAL-CLIMATEthe Catalan Government grant SGR 2017-1005
文摘Increased global vegetation gross primary productivity(GPP)over the past decades has led to an enhanced terrestrial carbon sink,an important factor in mitigating global warming.However,the global spatiotemporal evolution of GPP trends is still under debate,largely limiting our understanding of the sustainability in terrestrial carbon sink.Here in this study,based on a dozen of long-term global GPP datasets,we found that global GPP trends fell significantly from 0.43 PgC year^(−2) in 1982–1999 to 0.17 PgC year^(−2) in 2000–2016,a signal detected across>68%of the terrestrial surface.The decrease in GPP trends was more pronounced from satellite-based GPP datasets than from process-based models,which may result from a decline in the CO_(2) fertilization effect.This finding therefore indicates that the terrestrial carbon sink may become saturated in the future,and highlights the urgent need of stricter strategies for reducing carbon emissions to mitigate global warming.
基金funded by the New Zealand Government to support the objectives of the Global Research Alliance on Agricultural Greenhouse Gasesthe CaSSECS project(Carbon Sequestration and Green-house Gas Emissions in(Agro)Sylvopastoral Ecosystems in the Sahelian CILSS States)[FOOD/2019/410-169]+1 种基金Tagesson was additionally funded by the Swedish National Space Agency(SNSA 2021-001442021-00111)and FORMAS(Dnr.2021-00644).
文摘Background The savannah ecosystems of Sahel have experienced continuous and heavy grazing of livestock for centuries but still,their vegetation response to grazing pressure remains poorly understood.In this study,we analysed the herbaceous plant dynamics,measured by species diversity,composition,cover,and biomass in response to grazing pressure in the savannah ecosystems of Sahel.In Senegal,we selected four savannah sites represented with high,moderate,light and no grazing intensity levels.Transect survey methods were used for sampling the vegetation data within each of the sites.Species richness and composition were analysed using species accumulation curve and multivariate analyses.Furthermore,we used General Linear Models and a piecewise Structural Equation Model(pSEM)to examine the relationships between grazing intensity,vegetation cover,diversity and biomass.Results The herbaceous species diversity and composition varied significantly among the different grazing intensity levels(p<0.001).The plant species composition shifted from the dominance of grass cover to the dominance of forb cover with increasing grazing pressure.Moreover,the attributes of species diversity,herbaceous biomass,and ground cover were higher on sites with low grazing than sites with high and moderate grazing intensity.Across all sites,species diversity was positively related to total biomass.The pSEM explained 37%of the variance in total biomass and revealed that grazing intensity negatively influenced total biomass both directly and indirectly through its negative influence on species diversity.Conclusions Managing grazing intensity may lead to higher plant production and higher mixed forage establishment in the dryland savannah ecosystems.This information can be used to support land management strategies and promote sustainable grazing practices that balance the needs of livestock with the conservation of ecosystem health and biodiversity.
基金supported by the National Natural Science Foundation of China(42001314)the Open Research Fund of the State Laboratory of Information Engineering in Surveying,Mapping,and Remote Sensing,Wuhan University(grant number 20R02)+1 种基金Torbern Tagesson was additionally funded by the Swedish National Space Agency(SNSA 2021-00144)FORMAS(Dnr.2021-00644).
文摘The ratio of leaf carotenoid to chlorophyll(Car/Chl)is an indicator of vegetation photosynthesis,development and responses to stress.However,the correlation between Car and Chl,and their overlapping absorption in the visible spectral domain pose a challenge for optical remote sensing of their ratio.This study aims to investigate combinations of vegetation indices(VIs)to minimize the influence of Car-Chl correlation,thus being more sensitive to the variability in the ratio across vegetation species and sites.VIs sensitive to Car and Chl variability were combined into four candidates of combinations,using a simulated dataset from the PROSPECT model.The VI combinations were then tested using six simulated datasets with different Car-Chl correlations,and evaluated against four independent datasets.The ratio of the carotenoid triangle ratio index(CTRI)with the red-edge chlorophyll index(CIred-edge)was found least influenced by the Car-Chl correlation and demonstrated a superior ability for estimating Car/Chl variability.Compared with published VIs and two machine learning algorithms,CTRI/CIred-edge also showed the optimal performance in the fourfield datasets.This new VI combination could be useful to provide insights in spatiotemporal variability in the leaf Car/Chl ratio,applicable for assessing vegetation physiology,phenology,and response to environmental stress.
