Seasonal variations of phytoplankton/chlorophyll-a (Chl-a) distribution, sea surface wind, sea height anomaly, sea surface temperature and other oceanic environments for long periods are analyzed in the South China Sea (SCS), especially in the two typical regions off the east coast of Vietnam and off the northwest coast of Luzon, using remote sensing data and other oceanographic data. The results show that seasonal and spatial distributions of phytoplankton biomass in the SCS are primarily influenced by the monsoon winds and oceanic environments. Off the east coast of Vietnam, Chl-a concentration is a peak in August, a jet shape extending into the interior SCS, which is associated with strong southwesterly monsoon winds, the coastal upwetling induced by offshore Ekman transport and the strong offshore current in the western SCS. In December, high Chl-a concentration appears in the upwelling region off the northwest coast of Luzon and spreads southwestward. Strong mixing by the strong northeasterly monsoon winds, the cyclonic circulation, southwestward coastal currents and river discharge have impacts on distribution of phytoplankton, so that the high phytoplankton biomass extends from the coastal areas over the northern SCS to the entire SCS in winter. These research activities could be important for revealing spatial and temporal patterns of phytoplankton and their interactions with physical environments in the SCS. 相似文献
The inter-annual variability in phytoplankton summer blooms in the upper reaches of the Schelde estuary was investigated between 1996 and 2005 by monthly sampling at 10 stations. The large inter-annual variations of the chlorophyll a concentration in the freshwater tidal reaches were independent from variations in chlorophyll a in the tributary river Schelde. Summer mean chlorophyll a concentrations were significantly negatively correlated with flushing rate (Spearman correlation: r = −0.67, p = 0.05, n = 9) but not with temperature, irradiance and suspended particulate matter or dissolved silica (DSi) concentrations. During dry summers, low flushing rates permitted the development of dense phytoplankton populations in the upper part of the estuary, while during wet summers high flushing rates prevented the development of dense phytoplankton blooms. Flushing rate was also found to be important for the phytoplankton community composition. At low flushing rates, the community was dominated by diatoms that developed within the upper estuary. At high flushing rates, chlorophytes imported from the tributary river Schelde became more important in the phytoplankton community. The position of the chlorophyll a maximum shifted from the head of the estuary when flushing rates were low, to more downstream when flushing rates were high. Although DSi concentrations tended to be lower during years of high phytoplankton (mainly diatom) biomass, the relation with flushing rate was not significant. 相似文献
Distribution, variation and impact factors of biomass of bacterioplankton from April to May 1999 in Bohai Sea were studied in DAPI method with epifluorescence microscopy. The biomass in surface waters showed a small day-night variation, varying from 0.13 to 2.51μg/dm^3 with an average of 0.84μg/dm^3. The biomass in bottom waters showed, however, a large variation, changing from 0.15 to 4.18μg/dm^3 with an average of 1.36μg/dm^3. The peak values occurred at 5 and 11 a.m. The bottom water biomass showed a significant correlation with particulate organic carbon (r=0.639, P〈0.05). Heterotrophic bacterioplankton biomass was high in nearshore waters and low in offshore areas with a high biomass zone around Huanghe (Yellow) River mouth, showing the same distribution of nutrients. In vertical distribution, heterotrophic bacteria biomass in bottom waters was higher than that in surface water. 相似文献
China's national emissions trading scheme (ETS) is expected to be operational in 2017. Effectively addressing regional disparities at the provincial level in allowance allocation will greatly affect the acceptance of the allocation approach and thus deserves careful consideration. This article aims to explore possible approaches for addressing regional disparities, by introducing regional adjustment factors (RAF) in free allowance allocation. Based on the principle of ‘national unified rules?+?stricter adjustment by provincial authorities’, four single factorial and three multi-factorial methods are proposed to calculate the RAFs, through a normalization process. These methods are associated with the most acknowledged factors dealing with regional disparities, including per-capita GDP; per-capita CO2 emissions; industrial sector contribution to GDP; economy-wide emissions control targets and CO2 emissions per unit GDP, per unit power and heat output and per unit industrial added value. A comparative analysis is made for the seven methods, in regard to value distribution and level of matching regional political demand.Key policy insights
‘Allowing stricter regional adjustment’ represents a dominant feature for China's national ETS, which aims to address regional disparities and government demands.
How the adjustment plan is designed will have a major influence on the operation of the national ETS and regional business competitiveness. Provincial governments need to consider the trade-off between auction revenue and local business competitiveness.
Applying the different methods leads to more scattered results for some regions, for whom the choice of adjustment approach will therefore have a greater impact.
Based on the analysis, four adjustment methods that generate similar results – the per-capita GDP-based method, the intensity reduction target-based method, the 12th FYP target-based method and intensity-based grandfathering – are recommended for most provincial-level regions, with some exceptions.
One of the main objectives of land-use change models is to explore future land-use patterns. Therefore, the issue of addressing uncertainty in land-use forecasting has received an increasing attention in recent years. Many current models consider uncertainty by including a randomness component in their structure. In this paper, we present a novel approach for tuning uncertainty over time, which we refer to as the Time Monte Carlo (TMC) method. The TMC uses a specific range of randomness to allocate new land uses. This range is associated with the transition probabilities from one land use to another. The range of randomness is increased over time so that the degree of uncertainty increases over time. We compare the TMC to the randomness components used in previous models, through a coupled logistic regression-cellular automata model applied for Wallonia (Belgium) as a case study. Our analysis reveals that the TMC produces results comparable with existing methods over the short-term validation period (2000–2010). Furthermore, the TMC can tune uncertainty on longer-term time horizons, which is an essential feature of our method to account for greater uncertainty in the distant future. 相似文献
Ecosystem carbon allocation can indicate ecosystem carbon cycling visually through its quantification within different carbon pools and carbon exchange. Using the ecological inventory and eddy covariance measurement applied to both a mature temperate mixed forest in Changbai Mountain (CBM) and a mature subtropical evergreen forest in Dinghu Mountain (DHM), we partitioned the ecosystem carbon pool and carbon exchange into different components, determined the allocation and analyzed relationships within those components. Generally, the total carbon stock of CBM was slightly higher than that of DHM due to a higher carbon stock in the arbor layer at CBM. It was interesting that the proportions of carbon stock in vegetation, soil and litter were similar for the two mature forests. The ratio of vegetation carbon pool to soil carbon stock was 1.5 at CBM and 1.3 at DHM. However, more carbon was allocated to the trunk and root from the vegetation carbon pool at CBM, while more carbon was allocated to foliage and branches at DHM. Moreover, 77% of soil carbon storage was limited to the surface soil layer (0-20 cm), while there was still plentiful carbon stored in the deeper soil layers at DHM. The root/shoot ratios were 0.30 and 0.25 for CBM and DHM, respectively. The rates of net ecosystem productivity (NPP) to gross ecosystem productivity (GPP) were 0.76 and 0.58, and the ratios of ecosystem respiration (Re) to GPP were 0.98 and 0.87 for CBM and DHM, respectively. The net ecosystem carbon exchange/productivity (NEP) was 0.24 t C ha-1 yr-1 for CBM and 3.38 t C ha-1 yr-1 for DHM. Due to the common seasonal and inter-annual variations of ecosystem carbon exchange resulting from the influence of environmental factors, it was necessary to use the long record dataset to evaluate the ecosystem sink capacity. 相似文献
The aim of study is to map the carbon dioxide (CO2) emission of the aboveground tree biomass (AGB) in case of a fire event. The suitability of low point density, discrete, multiple-return, Airborne Laser Scanning (ALS) data and the influence of several characteristics of these data and the study area on the results obtained have been evaluated. A sample of 45 circular plots representative of Pinus halepensis Miller stands were used to fit and validate the model of AGB. The ALS point clouds were processed to obtain the independent variables and a multivariate linear regression analysis between field data and ALS-derived variables allowed estimation of AGB. Then, the influence of several characteristics on the residuals of the model was analyzed. Finally, conversion factors were applied to obtain the CO2 values. The AGB model presented a R2 value of 0.84 with a relative root-mean-square error of 27.35%. This model included ALS variables related to vegetation height variability and to canopy density. Terrain slope, aspect, canopy cover, scan angle and the number of laser returns did not influence AGB estimations at plot level. 相似文献