对随机效应线性模型（y,X<sub>0</sub>β,Aα,σ<sup>2</sup>V）:y=x<sub>0</sub>β+ε,E（<sub>ε</sub><sup>β</sup>）=（A<sub>α</sub>/0）,Cov（<su...对随机效应线性模型（y,X<sub>0</sub>β,Aα,σ<sup>2</sup>V）:y=x<sub>0</sub>β+ε,E（<sub>ε</sub><sup>β</sup>）=（A<sub>α</sub>/0）,Cov（<sub>ε</sub><sup>β</sup>）（?）给出了下列问题的解:当且仅当 X 满足什么条件时,才能使（y,X<sub>0</sub>β,Aα,σ<sup>2</sup>V）下任一可估函数ω′<sub>1</sub>α（或ω′<sub>2</sub>β或ω′<sub>1</sub>α+ω′<sub>2</sub>β）的所有 BLUE 都是（1）（y,xβ,Aα,σ<sup>2</sup>V）下ω′<sub>1</sub>α（或ω′<sub>2</sub>β或ω′<sub>1</sub>α+ω′<sub>2</sub>β）的线性无偏估计（LUE）或 BLUE（2）（y,Xβ,Aα,σ<sup>2</sup>V）下ω′<sub>1</sub>α（或ω′<sub>2</sub>β或ω′<sub>1</sub>α+ω′<sub>2</sub>β）的线性最小偏差估计（LIMBE）或最佳线性最小偏差估计（BLIMBE）展开更多
Background:Mangrove forests are a significant contributor to the global carbon cycle,and the accurate estimation of their gross primary productivity(GPP)is essential for understanding the carbon budget within blue car...Background:Mangrove forests are a significant contributor to the global carbon cycle,and the accurate estimation of their gross primary productivity(GPP)is essential for understanding the carbon budget within blue carbon ecosystems.Little attention has been given to the investigation of spatiotemporal patterns and ecological variations within mangrove ecosystems,as well as the quantitative analysis of the influence of geo-environmental factors on time-series estimations of mangrove GPP.Methods:This study explored the spatiotemporal dynamics of mangrove GPP from 2000 to 2020 in Gaoqiao Mangrove Reserve,China.A leaf area index(LAI)-based light-use efficiency(LUE)model was combined with Landsat data on Google Earth Engine(GEE)to reveal the variations in mangrove GPP using the Mann-Kendall(MK)test and Theil-Sen median trend.Moreover,the spatiotemporal patterns and ecological variations in mangrove ecosystems across regions were explored using four landscape indicators.Furthermore,the effects of six geo-environmental factors(species distribution,offshore distance,elevation,slope,planar curvature and profile curvature)on GPP were investigated using Geodetector and multi-scale geo-weighted regression(MGWR).Results:The results showed that the mangrove forest in the study area experienced an area loss from 766.26 ha in 2000 to 718.29 ha in 2020,mainly due to the conversion to farming,terrestrial forest and aquaculture zones.Landscape patterns indicated high levels of vegetation aggregation near water bodies and aquaculture zones,and low levels of aggregation but high species diversity and distribution density near building zone.The mean value of mangrove GPP continuously increased from 6.35 g C⋅m^(-2)⋅d^(-1) in 2000 to 8.33 g C⋅m^(-2)⋅d^(-1) in 2020,with 23.21%of areas showing a highly and significantly increasing trend(trend value>0.50).The Geodetector and MGWR analyses showed that species distribution,offshore distance and elevation contributed most to the GPP variations.Conclusions:These results provide guidelines for selecting GPP products,and the combination of Geodetector and MGWR based on multiple geo-environmental factors could quantitatively capture the mode,direction,pathway and intensity of the influencing factors on mangrove GPP variation.The findings provide a foundation for understanding the spatiotemporal dynamics of mangrove GPP at the landscape or regional scale.展开更多
Heidan disease(black jaundice)is a kind of jaundice,which is caused by lingering and chronic jaundice,often with blood stasis and damp-heat,etc.The clinical symptoms of Heidan disease(black jaundice)are similar to tho...Heidan disease(black jaundice)is a kind of jaundice,which is caused by lingering and chronic jaundice,often with blood stasis and damp-heat,etc.The clinical symptoms of Heidan disease(black jaundice)are similar to those of cirrhosis caused by multiple chronic liver diseases in Western medicine.Heidan disease(black jaundice)generally belongs to yin jaundice type,and the pathogenesis is mostly related to blood stasis and dampness stagnation,often with damp-heat residue.According to Zhongjing Zhang,the prescription Xiaoshi Fanshi powder for the treatment of Heidan disease(black jaundice)is based on the understanding that the nature of Heidan disease(black jaundice)is inseparable from the two key pathological factors of dampness and blood stasis.The treatment of jaundice should be based on removing blood stasis and dampness,supplemented by soothing the liver and promoting the transportation function of spleen,removing blood stasis and harmonizing the collaterals,and promoting diuresis and reducing jaundice.In the treatment of jaundice,removing blood stasis and purging turbidity should be stressed,and powerful tonification should be used with caution.Since blood stasis and turbidity are always intermingling and often complicated with damp heat,the method of warm drying should be used with caution.For promoting blood circulation,removing blood stasis,and dredging the liver-biliarycollaterals,drasticmedicine shouldbeused withcaution.展开更多
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
光化学植被指数PRI(photochemical reflectance index)为估算植被的光能利用率LUE(light use effi-ciency)提供了一种快速、有效的方法。越来越多的研究关注外界环境对PRI和LUE之间关系的影响,这些因素包括水分含量、CO2浓度等等。文章...光化学植被指数PRI(photochemical reflectance index)为估算植被的光能利用率LUE(light use effi-ciency)提供了一种快速、有效的方法。越来越多的研究关注外界环境对PRI和LUE之间关系的影响,这些因素包括水分含量、CO2浓度等等。文章选择了不同氮、钾施肥量处理的小麦,测量其LUE和PRI,分析不同肥料处理对二者关系的影响。实验表明,氮、钾施肥量的增加将提高冠层光谱的PRI值和叶片内部叶绿素的含量,在此基础上提高小麦的LUE。对于不同氮、钾处理的小麦,PRI和LUE之间都获得了很好的相关关系,总的相关系数R2分别是0.7104和0.8534。随着氮、钾肥量的增加,PRI和LUE之间的相关性也在增加。对1,2,3份的氮施肥量,相关系数R2分别是0.6020,0.6404和0.8014;钾施肥量为1,2,3份时,R2分别为0.3791,0.6404和0.6769。因此,PRI不仅能够获可靠精度的LUE,并且为监测小麦的肥料状况提供了一种间接方法,这将为田间管理和精细农业提供了必要的参考信息。展开更多
文摘对随机效应线性模型（y,X<sub>0</sub>β,Aα,σ<sup>2</sup>V）:y=x<sub>0</sub>β+ε,E（<sub>ε</sub><sup>β</sup>）=（A<sub>α</sub>/0）,Cov（<sub>ε</sub><sup>β</sup>）（?）给出了下列问题的解:当且仅当 X 满足什么条件时,才能使（y,X<sub>0</sub>β,Aα,σ<sup>2</sup>V）下任一可估函数ω′<sub>1</sub>α（或ω′<sub>2</sub>β或ω′<sub>1</sub>α+ω′<sub>2</sub>β）的所有 BLUE 都是（1）（y,xβ,Aα,σ<sup>2</sup>V）下ω′<sub>1</sub>α（或ω′<sub>2</sub>β或ω′<sub>1</sub>α+ω′<sub>2</sub>β）的线性无偏估计（LUE）或 BLUE（2）（y,Xβ,Aα,σ<sup>2</sup>V）下ω′<sub>1</sub>α（或ω′<sub>2</sub>β或ω′<sub>1</sub>α+ω′<sub>2</sub>β）的线性最小偏差估计（LIMBE）或最佳线性最小偏差估计（BLIMBE）
基金This work was supported by Guangdong Basic and Applied Basic Research Foundation(2019A1515010741 and 2021A1515110910)Guangdong Regional Joint Fund-Youth Fund(2020A1515111142)Shenzhen Science and Technology Program(JCYJ20210324093210029).
文摘Background:Mangrove forests are a significant contributor to the global carbon cycle,and the accurate estimation of their gross primary productivity(GPP)is essential for understanding the carbon budget within blue carbon ecosystems.Little attention has been given to the investigation of spatiotemporal patterns and ecological variations within mangrove ecosystems,as well as the quantitative analysis of the influence of geo-environmental factors on time-series estimations of mangrove GPP.Methods:This study explored the spatiotemporal dynamics of mangrove GPP from 2000 to 2020 in Gaoqiao Mangrove Reserve,China.A leaf area index(LAI)-based light-use efficiency(LUE)model was combined with Landsat data on Google Earth Engine(GEE)to reveal the variations in mangrove GPP using the Mann-Kendall(MK)test and Theil-Sen median trend.Moreover,the spatiotemporal patterns and ecological variations in mangrove ecosystems across regions were explored using four landscape indicators.Furthermore,the effects of six geo-environmental factors(species distribution,offshore distance,elevation,slope,planar curvature and profile curvature)on GPP were investigated using Geodetector and multi-scale geo-weighted regression(MGWR).Results:The results showed that the mangrove forest in the study area experienced an area loss from 766.26 ha in 2000 to 718.29 ha in 2020,mainly due to the conversion to farming,terrestrial forest and aquaculture zones.Landscape patterns indicated high levels of vegetation aggregation near water bodies and aquaculture zones,and low levels of aggregation but high species diversity and distribution density near building zone.The mean value of mangrove GPP continuously increased from 6.35 g C⋅m^(-2)⋅d^(-1) in 2000 to 8.33 g C⋅m^(-2)⋅d^(-1) in 2020,with 23.21%of areas showing a highly and significantly increasing trend(trend value>0.50).The Geodetector and MGWR analyses showed that species distribution,offshore distance and elevation contributed most to the GPP variations.Conclusions:These results provide guidelines for selecting GPP products,and the combination of Geodetector and MGWR based on multiple geo-environmental factors could quantitatively capture the mode,direction,pathway and intensity of the influencing factors on mangrove GPP variation.The findings provide a foundation for understanding the spatiotemporal dynamics of mangrove GPP at the landscape or regional scale.
基金supported by the National Natural Science Foundation of China(81403407)Special Program of the International Cooperation in Chinese Medicine of the State Administration of Traditional Chinese Medicine(China-Australia Chinese Medicine Center[Melbourne]GZYYGJ2021024)。
文摘Heidan disease(black jaundice)is a kind of jaundice,which is caused by lingering and chronic jaundice,often with blood stasis and damp-heat,etc.The clinical symptoms of Heidan disease(black jaundice)are similar to those of cirrhosis caused by multiple chronic liver diseases in Western medicine.Heidan disease(black jaundice)generally belongs to yin jaundice type,and the pathogenesis is mostly related to blood stasis and dampness stagnation,often with damp-heat residue.According to Zhongjing Zhang,the prescription Xiaoshi Fanshi powder for the treatment of Heidan disease(black jaundice)is based on the understanding that the nature of Heidan disease(black jaundice)is inseparable from the two key pathological factors of dampness and blood stasis.The treatment of jaundice should be based on removing blood stasis and dampness,supplemented by soothing the liver and promoting the transportation function of spleen,removing blood stasis and harmonizing the collaterals,and promoting diuresis and reducing jaundice.In the treatment of jaundice,removing blood stasis and purging turbidity should be stressed,and powerful tonification should be used with caution.Since blood stasis and turbidity are always intermingling and often complicated with damp heat,the method of warm drying should be used with caution.For promoting blood circulation,removing blood stasis,and dredging the liver-biliarycollaterals,drasticmedicine shouldbeused withcaution.
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.
文摘光化学植被指数PRI(photochemical reflectance index)为估算植被的光能利用率LUE(light use effi-ciency)提供了一种快速、有效的方法。越来越多的研究关注外界环境对PRI和LUE之间关系的影响,这些因素包括水分含量、CO2浓度等等。文章选择了不同氮、钾施肥量处理的小麦,测量其LUE和PRI,分析不同肥料处理对二者关系的影响。实验表明,氮、钾施肥量的增加将提高冠层光谱的PRI值和叶片内部叶绿素的含量,在此基础上提高小麦的LUE。对于不同氮、钾处理的小麦,PRI和LUE之间都获得了很好的相关关系,总的相关系数R2分别是0.7104和0.8534。随着氮、钾肥量的增加,PRI和LUE之间的相关性也在增加。对1,2,3份的氮施肥量,相关系数R2分别是0.6020,0.6404和0.8014;钾施肥量为1,2,3份时,R2分别为0.3791,0.6404和0.6769。因此,PRI不仅能够获可靠精度的LUE,并且为监测小麦的肥料状况提供了一种间接方法,这将为田间管理和精细农业提供了必要的参考信息。
