Seasonal changes in phytoplankton biomass and dominant species in the Changjiang River Estuary and adjacent seas: General trends based on field survey data 1959–2009

The characteristics of seasonal variation in phytoplankton biomass and dominant species in the Changjiang River Estuary and adjacent seas were discussed based on field investigation data from 1959 to 2009. The field data from 1981 to 2004 showed that the Chlorophyll-a concentration in surface seawater was between 0.4 and 8.5 μg dm-3. The seasonal changes generally presented a bimodal trend, with the biomass peaks occurring in May and August, and Chlorophyll-a concentration was the lowest in winter. Seasonal biomass changes were mainly controlled by temperature and nutrient levels. From the end of autumn to the next early spring, phytoplankton biomass was mainly influenced by temperature, and in other seasons, nutrient level(including the nutrient supply from the terrestrial runoffs) was the major influence factor. Field investigation data from 1959 to 2009 demonstrated that diatoms were the main phytoplankton in this area, and Skeletonema costatum, Pseudo-nitzschia pungens, Coscinodiscus oculus-iridis, Thalassinoema nitzschioides, Paralia sulcata, Chaetoceros lorenzianus, Chaetoceros curvisetus, and Prorocentrum donghaiense Lu were common dominant species. The seasonal variations in major dominant phytoplankton species presented the following trends: 1) Skeletonema(mainly S. costatum) was dominant throughout the year; and 2) seasonal succession trends were Coscinodiscus(spring) →Chaetoceros(summer and autumn) → Coscinodiscus(winter). The annual dominance of S. costatum was attributed to its environmental eurytopicity and long standing time in surface waters. The seasonal succession of Coscinodiscus and Chaetoceros was associated with the seasonal variation in water stability and nutrient level in this area. On the other hand, long-term field data also indicated obvious interannual variation of phytoplankton biomass and community structure in the Changjiang River Estuary and adjacent seas: average annual phytoplankton biomass and dinoflagellate proportion both presented increased trends during the 1950 s-2000 s.     

A model study on dynamical processes of phytoplankton in Laizhou Bay

A three-dimensional ecosystem model, using a PIC (Particle-In-Cell) method, is developed to reproduce the annual cycle and seasonal variation of nutrients and phytoplankton biomass in Laizhou Bay. Eight state variables, i.e., DIN (dissolved inorganic nitrogen), phosphate, DON (dissolved organic nitrogen), DOP (dissolved organic phosphorus), COD (chemical oxygen demand), chlorophyll-a (Chl-a), detritus and the zooplankton biomass, are included in the model. The model successfully reproduces the observed temporal and spatial variations of nutrients and Chl-a biomass distributions in the bay. The nutrient concentrations are at high level in winter and at low level in summer. Double-peak structure of the phytoplankton (PPT) biomass exists in Laizhou Bay, corresponding to a spring and an autumn bloom respectively. Several numerical experiments are carried out to examine the nutrient limitation, and the importance of the discharges of the Yellow River and Xiaoqinghe River. Both DIN limitation and phosphate limitation exist in some areas of the bay, with the former being more significant than the latter. The Yellow River and Xiaoqinghe River are the main pollution sources of nutrients in Laizhou Bay. During the flood season, the algal growth is inhibited in the bay with the Yellow River discharges being excluded in the experiment, while in spring, the algal growth is enhanced with the Xiaoqinghe River excluded.     

Modeling the spatial distribution of above-ground carbon in Mexican coniferous forests using remote sensing and a geostatistical approach

Forest conservation is considered an option for mitigating the effect of greenhouse gases on global climate, hence monitoring forest carbon pools at global and local levels is important. The present study explores the capability of remote-sensing variables (vegetation indices and textures derived from SPOT-5; backscattering coefficient and interferometric coherence of ALOS PALSAR images) for modeling the spatial distribution of above-ground biomass in the Environmental Conservation Zone of Mexico City. Correlation and spatial autocorrelation coefficients were used to select significant explanatory variables in fir and pine forests. The correlation for interferometric coherence in HV polarization was negative, with correlations coefficients r = −0.83 for the fir and r = −0.75 for the pine forests. Regression-kriging showed the least root mean square error among the spatial interpolation methods used, with 37.75 tC/ha for fir forests and 29.15 tC/ha for pine forests. The results showed that a hybrid geospatial method, based on interferometric coherence data and a regression-kriging interpolator, has good potential for estimating above-ground biomass carbon.     

北黄海冬季沉积物中线虫个体干质量初探

对冬季采自北黄海海域4个站位沉积物中的线虫进行了分选和制片,通过对总计955条线虫的实测分析,利用体积换算法,获得4个站位线虫的个体平均干质量分别为0.091μg?0.131μg(0.006~0.545μg)、0.450μg?0.928μg(0.011~5.078μg)、0.211μg?0.385μg(0.005~3.093μg)和0.127μg?0.218μg(0.006~2.023μg),4个站位平均为0.196μg?0.140μg,个体干质量最大值是最小值的1028倍。该平均值与自长江口邻近海域所获结果接近,但较南黄海的略低。由此,在利用31μm孔径网筛分选时,中国目前普遍使用的0.4μg/个经验系数估算的线虫生物量将比实测值高一倍。Pearson相关分析显示,线虫的个体平均干质量与各项环境因子均未见有相关性。造成各站位线虫个体干质量差异的主要因素是线虫的种类组成和幼体所占比例,沉积物粒度、有机质含量、叶绿素a含量等可能是影响种类组成的主要因子,而季节则是影响线虫幼体比例的主要因子。因此,对线虫生物量的估计当以实测为最佳,如采用经验系数则建议采用0.2μg/个进行估算。然而,这一系数是否具有普遍意义尚需进一步验证。     

Measurements of CO,HCN, and C2H6 Total Columns in Smoke Plumes Transported from the 2010 Russian Boreal Forest Fires to the Canadian High Arctic

In August 2010, simultaneous enhancements of aerosol optical depth and total columns of carbon monoxide (CO), hydrogen cyanide (HCN), and ethane (C₂H₆) were observed at the Polar Environment Atmospheric Research Laboratory (PEARL, 80.05°N, ?86.42°W, 0.61 km above sea level, Eureka, Nunavut, Canada). Moderate Resolution Imaging Spectroradiometer (MODIS) hot spots, Ozone Monitoring Instrument (OMI) aerosol index maps, and Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) back-trajectories were used to attribute these enhancements to an intense boreal fire event occurring in Russia. A ground-based Fourier Transform InfraRed (FTIR) spectrometer at PEARL provided vertically integrated measurements of trace gases transported in smoke plumes. We derived HCN and C₂H₆ equivalent emission ratios with respect to CO of 0.0054?±?0.0022 and 0.0108?±?0.0036, respectively, and converted them into equivalent emission factors of 0.66?±?0.27 g kg^?1 and 1.47?±?0.50 g kg^?1 (in grams of gas per kilogram of dry biomass burnt, with one-sigma uncertainties). These emission factors add new observations to the relatively sparse datasets available and can be used to improve the simulation of biomass burning fire emissions in chemical transport models. These emission factors for the boreal forest are in agreement with the mean values recently reported in a compilation study.     

Deforestation,biomass and carbon finance in Amazonia

Biomass dynamics in Amazonia are quantified and the value that carbon finance could deliver from slowing deforestation is assessed. Above-ground forest biomass in the Legal Amazon shrank from 90 Pg to 76 Pg between 1978 and 2004. An average decrease of 0.64 Pg (standard error 0.38 Pg) per year was estimated for primary and econdary vegetation. For an improved, spatially and temporally explicit estimation, a time series of remote-sensing results and a model of secondary forest area and age distribution was combined with a large-scale forest-growth model. The observed trend of biomass decline is continuous and defines a baseline that the avoidance of deforestation could be measured against. Based on scenario calculations, the emission reductions from slightly reduced deforestation rates could be valued in the range of €1 billion annually. Carbon finance for reducing emissions from deforestation (‘avoided deforestation’), which is being discussed as an additional mechanism under the UN Framework Convention on Climate Change and its Kyoto Protocol, has the potential to alter the economic logic driving forest conversion.     

利用市政污水厂尾水培养产油微藻——营养盐去除与生物质生产

将1株产油淡水微藻——微拟球藻(Nannochloropsis sp.MASCC 11)分别接种到青岛市2家市政污水处理厂(STP)的尾水中,根据其生长、油脂产率和营养盐去除情况,评价了利用STP尾水培养微藻以生产富油的藻生物质同时深度净化尾水的可行性。结果表明,团岛污水处理厂(TD-STP)和李村河污水处理厂(LC-STP)尾水中无机氮和磷酸盐的浓度虽然远低于BG11培养基,但仍能支持微藻生长,而且以未经稀释的尾水更具优势,培养8 d后,藻生物量分别达到BG11培养基中生长微藻的65.23%和44.77%。STP尾水经稀释后处于营养盐缺乏状态,有利于藻细胞内脂质积累,但是油脂产率最大值(10.5 mg·L^-1·d^-1)仍出现在未经稀释的TD-STP尾水中,为未稀释LC-STP尾水的1.37倍。LC-STP尾水中微藻的油脂产率较低,可能与该处理厂接纳工业废水而在尾水中残留较多有害物质有关。在微藻的直接和间接作用下,TD-STP和LC-STP尾水中磷酸盐的去除率分别达到94.5%和100%;无机氮的去除率较低(分别为59.2%和45.4%),与尾水中初始N/P较高有关。上述结果表明,与接纳工业废水的污水厂相比,处理生活污水的污水厂所排尾水较适于培养产油微藻,能够实现产油微藻低耗培养与尾水深度净化相耦合。     

华北一作区马铃薯生长发育及产量对干旱胁迫响应的模拟研究——以武川县为例

为探究不同程度干旱胁迫对华北一作区马铃薯生长发育及产量的影响,以内蒙古呼和浩特市武川县为例,基于多年马铃薯生长发育资料和气象资料,对APSIM-Potato模型进行调参与验证,评价模型在武川地区的适用性。利用验证后的模型模拟马铃薯叶面积指数（LAI）、地上部生物量和产量对不同发育阶段干旱胁迫的响应。结果表明：（1） 各发育阶段天数的模拟值与实测值的均方根误差（RMSE）均在3 d内;LAI、地上部生物量和产量的模拟值与实测值的归一化均方根误差（NRMSE）分别为12.82%、17.35%和14.48%,均低于20%,表明APSIM-Potato模型在武川地区具有较好的适用性。（2） 随着干旱胁迫时间和强度的增加,马铃薯LAI、地上部生物量和产量随之减小。模拟单一发育阶段干旱胁迫时,马铃薯LAI、地上部生物量和产量对分枝-开花期水分胁迫的响应最大;模拟连续发育阶段干旱胁迫时,LAI、地上部生物量和产量对全生育期水分胁迫的响应最大。     

冻融交替对不同年代排水造林湿地土壤微生物活性及有机碳密度的影响

以小兴安岭湿地土壤为研究对象,基于室内分析和冻融实验,分析了冻融作用下不同年代排水造林湿地土壤微生物量、酶活性以及有机碳密度的变化趋势,探讨了不同年代排水造林湿地土壤微生物活性与有机碳密度之间的相关关系,以期为深入认识冻融期间高寒高纬度地区土壤碳循环过程提供参考依据。结果表明：（1）冻融次数对土壤微生物量碳、氮含量影响显著（P<0.05）,经历9次冻融循环后,土壤微生物量碳、氮含量比冻融前明显减少;在三种不同年代排水造林的湿地中,排水时间越短,土壤微生物量碳、氮含量下降幅度越大,表明长时间的反复冻融交替可能导致土壤微生物量的进一步减少。（2）冻融前后,土壤蔗糖酶和淀粉酶活性均表现为下降趋势,且多次冻融交替后,-25~5℃冻融处理比-5~5℃冻融处理酶活性更低,表明较大的冻融温差更能降低土壤酶的活性度。（3）随着冻融次数和冻融温度的变化,四种湿地的土壤有机碳密度基本保持稳定,但其与土壤微生物量、酶活性却存在着高度的正相关性,通过探究微生物活性所调控的土壤过程,可以直接或间接了解土壤有机碳密度的变化趋势,便于从本质上验证其响应机制。     

马衔山多年冻土与季节冻土区土壤微生物量及酶活性的季节动态

为了研究马衔山多年冻土区和非多年冻土区土壤微生物碳氮、土壤酶活性的差异,选取多年冻土区、季节冻土区和交界区为对象,分析了0~30 cm土层微生物碳氮和转化酶、脲酶、中性磷酸酶、淀粉酶、过氧化氢酶、多酚氧化酶酶活性不同季节的变化特征。结果表明：全氮、总有机碳、微生物量碳氮与多数土壤酶之间呈显著相关关系。在不同区域,土壤微生物碳氮均在0~10 cm含量最高,10~20 cm次之,20~30 cm最低。土壤微生物碳氮在生长季表现为含量逐渐增加,但是多年冻土区与季节冻土区差异不大。土壤酶活性在深度方面表现与微生物碳氮含量变化一致。土壤酶并无的季节变化规律。在多年冻土区,转化酶、多酚氧化酶和磷酸酶活性明显高于非多年冻土区。本研究表明,尽管多年冻土区的植被和土壤总有机碳明显高于非多年冻土区,其土壤微生物碳氮含量相当,且一些土壤酶活性也相当。说明非多年冻土区土壤的生物地球化学相对强度较大。因此,多年冻土退化后可能会导致生态系统的退化。