With the passage of time, it has become important to investigate new methods for updating data to better fit the trends of the grey prediction model. The traditional GM（1,1） usually sets the grey action quantity as ...With the passage of time, it has become important to investigate new methods for updating data to better fit the trends of the grey prediction model. The traditional GM（1,1） usually sets the grey action quantity as a constant. Therefore, it cannot effectively fit the dynamic characteristics of the sequence, which results in the grey model having a low precision. The linear grey action quantity model cannot represent the index change law. This paper presents a grey action quantity model, the exponential optimization grey model（EOGM（1,1））, based on the exponential type of grey action quantity; it is constructed based on the exponential characteristics of the grey prediction model. The model can fully reflect the exponential characteristics of the simulation series with time. The exponential sequence has a higher fitting accuracy. The optimized result is verified using a numerical example for the fluctuating sequence and a case study for the index of the tertiary industry＇s GDP. The results show that the model improves the precision of the grey forecasting model and reduces the prediction error.展开更多
Chemometric approach based on principal component analysis（PCA） was utilized to examine the spatial variances of environmental and ecological characteristics in the Zhujiang River（Pearl River） Estuary and adjacent...Chemometric approach based on principal component analysis（PCA） was utilized to examine the spatial variances of environmental and ecological characteristics in the Zhujiang River（Pearl River） Estuary and adjacent waters（ZREAW） in the South China Sea. The PCA result shows that the ZREAW can be divided into different zones according to the principal components and geographical locations of the study stations,and indicates that there are distinct regional variances on environmental features and the corresponding phytoplankton biomass and community structures among different areas. The spatial distribution of ecological features was implied to be influenced by various degrees of the different water resources,such as the Pearl River discharges,the coastal current and the oceanic water from the South China Sea. The variation of the biomass maximum zone and the complex impacts on the spatial distributions of phytoplankton biomass and production were also evaluated.展开更多
The impoundment of the Three Gorges Dam(TGD)has altered downstream hydrological characteristics and sediment discharge,and it has caused ecological impacts,such as changes in chlorophyll-a(Chl-a)in estuaries and coast...The impoundment of the Three Gorges Dam(TGD)has altered downstream hydrological characteristics and sediment discharge,and it has caused ecological impacts,such as changes in chlorophyll-a(Chl-a)in estuaries and coastal oceans.To investigate the TGD's influence on Chl-a's interannual and seasonal variations in the Changjiang Estuary and the adjacent coastal East China Sea,a physical-biogeochemical model was developed with numerical experiments covering a decade,including TGD's preperiod(pre-TGD,1999–2003)and post-period(post-TGD,2004–2008).The modeling results demonstrate an annual increase in the regional average Chl-a from pre-to post-TGD,with the largest increase reaching up to 20.8%in spring in the nearshore region beyond the Changjiang mouth.The spatial variations in Chl-a are high,with the largest variation being observed around the 20–40 m isobaths.The increase in Chl-a is influenced by improved light and nutrient conditions,which is attributed to dam construction and fertilization by human activities.A decline in nitrogen-phosphorus fertilizer usage ratio along the Changjiang River watershed after the TGD's impoundment is another factor that influences the Chl-a's variation.The modeling results also show severe NO3 and PO4 imbalances with a larger N/P ratio during the post-TGD period,especially in regions with large Chl-a increases.Moreover,the greater increase in the usage of phosphorus fertilizer than nitrogen fertilizer influences Chl-a's variation and has potential promotion effects on the outbreak of harmful algal bloom events.展开更多
Solar ultraviolet radiation B (UVB) is known to have inhibitive effects on phytoplankton photosynthesis. UVB light decreases rapidly with increasing depth in the water column and exerts different degrees of UVB inhibi...Solar ultraviolet radiation B (UVB) is known to have inhibitive effects on phytoplankton photosynthesis. UVB light decreases rapidly with increasing depth in the water column and exerts different degrees of UVB inhibitive effects on phytoplankton photosynthesis. In this study, the objectives were to quantify effects of UVB on phytoplankton photosynthesis and quantum yield, and to examine UVB effects on phytoplankton photosynthesis when light varies. The insitu experiments were conducted in Da Ya Bay, which is a semienclosed area in the subtropical South China. The results showed a significant reduction of photosynthetic rates and quantum yield in the presence of UVB. Maximum photosynthetic rates (Pmax) and maximum quantum yield (Φmax) were 11%-22% and 17%-49% less under solar radiation with UVB than without UVB. A simplified model was developed to describe the UVB biologically effective fluence rate (E*inh) as an exponential decay function of depth. Light-shift experiments, in which water samples from the surface and at depth of 4 m were divided into several subsamples, and each subsamples were then incubated at different depths with and without UVB in the water column, showed that phytoplankton from the deeper water (4 m) had more inhibitive rates by UVB than that from the surface when exposed to the same light condition.展开更多
基金supported by the National Key Research and Development Program of China(2016YFC1402000)the National Science Foundation of China(41701593+2 种基金7137109871571157)the National Social Science Fund Major Project(14ZDB151)
文摘With the passage of time, it has become important to investigate new methods for updating data to better fit the trends of the grey prediction model. The traditional GM（1,1） usually sets the grey action quantity as a constant. Therefore, it cannot effectively fit the dynamic characteristics of the sequence, which results in the grey model having a low precision. The linear grey action quantity model cannot represent the index change law. This paper presents a grey action quantity model, the exponential optimization grey model（EOGM（1,1））, based on the exponential type of grey action quantity; it is constructed based on the exponential characteristics of the grey prediction model. The model can fully reflect the exponential characteristics of the simulation series with time. The exponential sequence has a higher fitting accuracy. The optimized result is verified using a numerical example for the fluctuating sequence and a case study for the index of the tertiary industry＇s GDP. The results show that the model improves the precision of the grey forecasting model and reduces the prediction error.
基金The Knowledge Innovation Project of Chinese Academy of Sciences under contract Nos KZCX2-YW-Q07, KZCX2-YW-T001, KZCX2-YW-213 and SQ200805the National Natural Science Foundation of China under contract Nos U0633007, 40906057 and 40531006
文摘Chemometric approach based on principal component analysis（PCA） was utilized to examine the spatial variances of environmental and ecological characteristics in the Zhujiang River（Pearl River） Estuary and adjacent waters（ZREAW） in the South China Sea. The PCA result shows that the ZREAW can be divided into different zones according to the principal components and geographical locations of the study stations,and indicates that there are distinct regional variances on environmental features and the corresponding phytoplankton biomass and community structures among different areas. The spatial distribution of ecological features was implied to be influenced by various degrees of the different water resources,such as the Pearl River discharges,the coastal current and the oceanic water from the South China Sea. The variation of the biomass maximum zone and the complex impacts on the spatial distributions of phytoplankton biomass and production were also evaluated.
基金supported by grants from the GuangdongNSFC Joint Theme Project(No.U1701247)the National Natural Science Foundation of China(No.91328203)+1 种基金the Southern Marine Science and Engineering–Guangdong Laboratory(Zhuhai)(No.311019006)the Sun Yat-sen University Supercomputing Funding(No.42000-52603700)。
文摘The impoundment of the Three Gorges Dam(TGD)has altered downstream hydrological characteristics and sediment discharge,and it has caused ecological impacts,such as changes in chlorophyll-a(Chl-a)in estuaries and coastal oceans.To investigate the TGD's influence on Chl-a's interannual and seasonal variations in the Changjiang Estuary and the adjacent coastal East China Sea,a physical-biogeochemical model was developed with numerical experiments covering a decade,including TGD's preperiod(pre-TGD,1999–2003)and post-period(post-TGD,2004–2008).The modeling results demonstrate an annual increase in the regional average Chl-a from pre-to post-TGD,with the largest increase reaching up to 20.8%in spring in the nearshore region beyond the Changjiang mouth.The spatial variations in Chl-a are high,with the largest variation being observed around the 20–40 m isobaths.The increase in Chl-a is influenced by improved light and nutrient conditions,which is attributed to dam construction and fertilization by human activities.A decline in nitrogen-phosphorus fertilizer usage ratio along the Changjiang River watershed after the TGD's impoundment is another factor that influences the Chl-a's variation.The modeling results also show severe NO3 and PO4 imbalances with a larger N/P ratio during the post-TGD period,especially in regions with large Chl-a increases.Moreover,the greater increase in the usage of phosphorus fertilizer than nitrogen fertilizer influences Chl-a's variation and has potential promotion effects on the outbreak of harmful algal bloom events.
基金Supported by National Outstanding Youth Fund (Grant No. 40125016)Major Grant of the National Natural Science Foundation of China (Grant No. 40490000)+2 种基金Innova-tion Project of South China Sea Institute of Oceanology (Grant No. LYQY200301)the National Natural Science Foundation of China (Grant No. 40076012)Guang-dong Provincial Project (Grant No. 2002A3050103).
文摘Solar ultraviolet radiation B (UVB) is known to have inhibitive effects on phytoplankton photosynthesis. UVB light decreases rapidly with increasing depth in the water column and exerts different degrees of UVB inhibitive effects on phytoplankton photosynthesis. In this study, the objectives were to quantify effects of UVB on phytoplankton photosynthesis and quantum yield, and to examine UVB effects on phytoplankton photosynthesis when light varies. The insitu experiments were conducted in Da Ya Bay, which is a semienclosed area in the subtropical South China. The results showed a significant reduction of photosynthetic rates and quantum yield in the presence of UVB. Maximum photosynthetic rates (Pmax) and maximum quantum yield (Φmax) were 11%-22% and 17%-49% less under solar radiation with UVB than without UVB. A simplified model was developed to describe the UVB biologically effective fluence rate (E*inh) as an exponential decay function of depth. Light-shift experiments, in which water samples from the surface and at depth of 4 m were divided into several subsamples, and each subsamples were then incubated at different depths with and without UVB in the water column, showed that phytoplankton from the deeper water (4 m) had more inhibitive rates by UVB than that from the surface when exposed to the same light condition.
