Gross primary production(GPP)is a crucial indicator representing the absorption of atmospheric CO_(2) by vegetation.At present,the estimation of GPP by remote sensing is mainly based on leaf-related vegetation indexes...Gross primary production(GPP)is a crucial indicator representing the absorption of atmospheric CO_(2) by vegetation.At present,the estimation of GPP by remote sensing is mainly based on leaf-related vegetation indexes and leaf-related biophysical para-meter leaf area index(LAI),which are not completely synchronized in seasonality with GPP.In this study,we proposed chlorophyll content-based light use efficiency model(CC-LUE)to improve GPP estimates,as chlorophyll is the direct site of photosynthesis,and only the light absorbed by chlorophyll is used in the photosynthetic process.The CC-LUE model is constructed by establishing a linear correlation between satellite-derived canopy chlorophyll content(Chlcanopy)and FPAR.This method was calibrated and validated utiliz-ing 7-d averaged in-situ GPP data from 14 eddy covariance flux towers covering deciduous broadleaf forest ecosystems across five dif-ferent climate zones.Results showed a relatively robust seasonal consistency between Chlcanopy with GPP in deciduous broadleaf forests under different climatic conditions.The CC-LUE model explained 88% of the in-situ GPP seasonality for all validation site-year and 56.0% of in-situ GPP variations through the growing season,outperforming the three widely used LUE models(MODIS-GPP algorithm,Vegetation Photosynthesis Model(VPM),and the eddy covariance-light use efficiency model(EC-LUE)).Additionally,the CC-LUE model(RMSE=0.50 g C/(m^(2)·d))significantly improved the underestimation of GPP during the growing season in semi-arid region,re-markably decreasing the root mean square error of averaged growing season GPP simulation and in-situ GPP by 75.4%,73.4%,and 37.5%,compared with MOD17(RMSE=2.03 g C/(m^(2)·d)),VPM(RMSE=1.88 g C/(m^(2)·d)),and EC-LUE(RMSE=0.80 g C/(m^(2)·d))model.The chlorophyll-based method proved superior in capturing the seasonal variations of GPP in forest ecosystems,thereby provid-ing the possibility of a more precise depiction of forest seasonal carbon uptake.展开更多
Aims Understanding of the ecophysiological dynamics of forest canopy photosynthesis and its spatial and temporal scaling is crucial for revealing ecological response to climate change.Combined observations and analyse...Aims Understanding of the ecophysiological dynamics of forest canopy photosynthesis and its spatial and temporal scaling is crucial for revealing ecological response to climate change.Combined observations and analyses of plant ecophysiology and optical remote sensing would enable us to achieve these studies.In order to examine the utility of spectral vegetation indices(VIs)for assessing ecosystem-level photosynthesis,we investigated the relationships between canopy-scale photosynthetic productivity and canopy spectral reflectance over seasons for 5 years in a cool,temperate deciduous broadleaf forest at‘Takayama’super site in central Japan.Methods Daily photosynthetic capacity was assessed by in situ canopy leaf area index(LAI),(LAI×Vcmax[single-leaf photosynthetic capacity]),and the daily maximum rate of gross primary production(GPPmax)was estimated by an ecosystem carbon cycle model.We examined five VIs:normalized difference vegetation index(NDVI),enhanced vegetation index(EVI),green–red vegetation index(GRVI),chlorophyll index(CI)and canopy chlorophyll index(CCI),which were obtained by the in situ measurements of canopy spectral reflectance.Important Findings Our in situ observation of leaf and canopy characteristics,which were analyzed by an ecosystem carbon cycling model,revealed that their phenological changes are responsible for seasonal and interannual variations in canopy photosynthesis.Significant correlations were found between the five VIs and canopy photosynthetic capacity over the seasons and years;four of the VIs showed hysteresis-type relationships and only CCI showed rather linear relationship.Among the VIs examined,we applied EVI–GPPmax relationship to EVI data obtained by Moderate Resolution Imaging Spectroradiometer to estimate the temporal and spatial variation in GPPmax over central Japan.Our findings would improve the accuracy of satellite-based estimate of forest photosynthetic productivity in fine spatial and temporal resolutions,which are necessary for detecting any response of terrestrial ecosystem to meteorological fluctuations.展开更多
Satellite-based remote sensed phenology has been widely used to assess global climate change.However,it is constrained by uncertain linkages with photo-synthesis activity.Two dynamic threshold methods were employed to...Satellite-based remote sensed phenology has been widely used to assess global climate change.However,it is constrained by uncertain linkages with photo-synthesis activity.Two dynamic threshold methods were employed to retrieve spring phenology metrics from four Moderate Resolution Imaging Spectro-radiometer(MODIS)products,including fraction of Absorbed Photosyntheti-cally Active Radiation(fAPAR),Leaf Area Index(LAI),Normalized Difference Vegetation Index(NDVI),and Enhanced Vegetation Index(EVI)for three temperate deciduous broadleaf forests in North America between 2001 and 2009.These MODIS-based spring phenology metrics were subsequently linked to the photosynthetic curves(daily gross primary productivity,GPP)measured by an eddy covariance flux tower.The 20% dynamic threshold spring onset metrics from MODIS products were closer to the photosynthesis onset metrics at the date of 2% GPP increase for NDVI and fAPAR,and closer to the date of 5%and 10% increase of GPP for EVI and LAI,respectively.The 50% dynamic threshold onset metrics were closer to the photosynthesis onset metrics at the date of 10%GPP increase for NDVI,and closer to the date of 20% GPP increase for fAPAR,LAI and EVI,respectively.These results can improve our knowledge on the photosynthesis activity status of remotely sensed spring phenology metrics.展开更多
基金Under the auspices of the National Key Research and Development Program of China(No.2019YFA0606603)。
文摘Gross primary production(GPP)is a crucial indicator representing the absorption of atmospheric CO_(2) by vegetation.At present,the estimation of GPP by remote sensing is mainly based on leaf-related vegetation indexes and leaf-related biophysical para-meter leaf area index(LAI),which are not completely synchronized in seasonality with GPP.In this study,we proposed chlorophyll content-based light use efficiency model(CC-LUE)to improve GPP estimates,as chlorophyll is the direct site of photosynthesis,and only the light absorbed by chlorophyll is used in the photosynthetic process.The CC-LUE model is constructed by establishing a linear correlation between satellite-derived canopy chlorophyll content(Chlcanopy)and FPAR.This method was calibrated and validated utiliz-ing 7-d averaged in-situ GPP data from 14 eddy covariance flux towers covering deciduous broadleaf forest ecosystems across five dif-ferent climate zones.Results showed a relatively robust seasonal consistency between Chlcanopy with GPP in deciduous broadleaf forests under different climatic conditions.The CC-LUE model explained 88% of the in-situ GPP seasonality for all validation site-year and 56.0% of in-situ GPP variations through the growing season,outperforming the three widely used LUE models(MODIS-GPP algorithm,Vegetation Photosynthesis Model(VPM),and the eddy covariance-light use efficiency model(EC-LUE)).Additionally,the CC-LUE model(RMSE=0.50 g C/(m^(2)·d))significantly improved the underestimation of GPP during the growing season in semi-arid region,re-markably decreasing the root mean square error of averaged growing season GPP simulation and in-situ GPP by 75.4%,73.4%,and 37.5%,compared with MOD17(RMSE=2.03 g C/(m^(2)·d)),VPM(RMSE=1.88 g C/(m^(2)·d)),and EC-LUE(RMSE=0.80 g C/(m^(2)·d))model.The chlorophyll-based method proved superior in capturing the seasonal variations of GPP in forest ecosystems,thereby provid-ing the possibility of a more precise depiction of forest seasonal carbon uptake.
基金This long-term study was partly supported by the JSPS 21st Century COE Program at Gifu Universitythe JSPS-NRF-NSFS A3 Foresight Program,a Global Change Observation Mission(GCOM-C,PI#102)of the Japan Aerospace Exploration Agency(JAXA)+2 种基金the Global Environment Research Fund(S-1)and the Environment Research&Technology Development Fund(D-0909 and S-9)of the Ministry of Environment Japan,the JSPS KAKENHI(22310008)the JSPS‘Funding Program for Next Generation World-Leading Researchers(NEXT Program)’S.N.is supported by JSPS-KAKENHI(24710021,Grant-in-Aid for Young Scientists B).
文摘Aims Understanding of the ecophysiological dynamics of forest canopy photosynthesis and its spatial and temporal scaling is crucial for revealing ecological response to climate change.Combined observations and analyses of plant ecophysiology and optical remote sensing would enable us to achieve these studies.In order to examine the utility of spectral vegetation indices(VIs)for assessing ecosystem-level photosynthesis,we investigated the relationships between canopy-scale photosynthetic productivity and canopy spectral reflectance over seasons for 5 years in a cool,temperate deciduous broadleaf forest at‘Takayama’super site in central Japan.Methods Daily photosynthetic capacity was assessed by in situ canopy leaf area index(LAI),(LAI×Vcmax[single-leaf photosynthetic capacity]),and the daily maximum rate of gross primary production(GPPmax)was estimated by an ecosystem carbon cycle model.We examined five VIs:normalized difference vegetation index(NDVI),enhanced vegetation index(EVI),green–red vegetation index(GRVI),chlorophyll index(CI)and canopy chlorophyll index(CCI),which were obtained by the in situ measurements of canopy spectral reflectance.Important Findings Our in situ observation of leaf and canopy characteristics,which were analyzed by an ecosystem carbon cycling model,revealed that their phenological changes are responsible for seasonal and interannual variations in canopy photosynthesis.Significant correlations were found between the five VIs and canopy photosynthetic capacity over the seasons and years;four of the VIs showed hysteresis-type relationships and only CCI showed rather linear relationship.Among the VIs examined,we applied EVI–GPPmax relationship to EVI data obtained by Moderate Resolution Imaging Spectroradiometer to estimate the temporal and spatial variation in GPPmax over central Japan.Our findings would improve the accuracy of satellite-based estimate of forest photosynthetic productivity in fine spatial and temporal resolutions,which are necessary for detecting any response of terrestrial ecosystem to meteorological fluctuations.
基金The authors gratefully acknowledge financial support provided for this research by the National Natural Science Foundation of China(41222008,91125003)the External Cooperation Program of the Chinese Academy of Sciences(GJH21123).
文摘Satellite-based remote sensed phenology has been widely used to assess global climate change.However,it is constrained by uncertain linkages with photo-synthesis activity.Two dynamic threshold methods were employed to retrieve spring phenology metrics from four Moderate Resolution Imaging Spectro-radiometer(MODIS)products,including fraction of Absorbed Photosyntheti-cally Active Radiation(fAPAR),Leaf Area Index(LAI),Normalized Difference Vegetation Index(NDVI),and Enhanced Vegetation Index(EVI)for three temperate deciduous broadleaf forests in North America between 2001 and 2009.These MODIS-based spring phenology metrics were subsequently linked to the photosynthetic curves(daily gross primary productivity,GPP)measured by an eddy covariance flux tower.The 20% dynamic threshold spring onset metrics from MODIS products were closer to the photosynthesis onset metrics at the date of 2% GPP increase for NDVI and fAPAR,and closer to the date of 5%and 10% increase of GPP for EVI and LAI,respectively.The 50% dynamic threshold onset metrics were closer to the photosynthesis onset metrics at the date of 10%GPP increase for NDVI,and closer to the date of 20% GPP increase for fAPAR,LAI and EVI,respectively.These results can improve our knowledge on the photosynthesis activity status of remotely sensed spring phenology metrics.
