风浪扰动对太湖水体重金属形态的影响

对不同风浪条件下水体中的悬浮颗粒物,采用ICP-AES测定其中Co,Cr,Cu,Ni,Pb,Zn,Al,Fe和Mn不同形态的含量.研究表明,水体中Al,Fe,Co,Cr,Pb和Ni可提取态含量随风浪扰动程度的增强其含量均有不同程度的增大. Mn,Zn和Cu在7m·s-1风浪下含量最高,11m·s-1风浪次之,2m·s-1风浪最小.7m·s-1风浪与2m·s-1风浪相比,水体中Mn, Co, Cr, Zn, Cu和Ni的B1, B2, B3态含量增加3-20倍.11m·s-1风浪与7m·s-1风浪相比,Co, Cr和Ni的B1态含量分别增加31.1%-76.8%,Mn, Zn和Cu分别减少22.1%-38.6%; Cr,Zn和Ni的B2态含量增加12.1%-50.2%, Mn减少65.6%, Co和Cu的含量相当; Co和Ni的B3态含量增加15.4%-10.3%,Cr,Mn,Zn和Cu略微减少.水体中的金属主要以Fe-Mn氧化物结合态存在,且金属的三态比例随风浪的变化不明显. Mn的生物有效性最高,Zn,Cu和Ni次之,毒性较大的Pb和Cr的生物有效性较低.Al, Fe和Pb的Fe-Mn氧化物结合态比例非常高,约有74.56%-100%. Co,Cr和Ni的有机结合态比例较高,且Co和 Ni的三态比例比较均一,Cu的B3态较低.     

月湖底栖动物的空间格局及其对水草可恢复区的指示

底质适宜是富营养湖泊恢复沉水植物(水草)的重要前提。大型底栖动物可综合指示底质的污染程度,于2002~2003年在武汉月湖开展了底栖动物水平分布对水草可恢复区指示作用的研究。首先通过月湖底栖动物与环境的相关分析,选择颤蚓科寡毛类作为底质营养状况的指示类群,然后利用同类湖泊群颤蚓与水草数据分析阈值,初步确定颤蚓密度≤100 ind/m2的底质适合水草生长,最后绘制月湖颤蚓分布的水平等值线,显示水草恢复的合适区域。在此基础上构建了应用底栖动物空间格局指示水草恢复区的技术原理框架。     

武汉湖泊富营养化遥感调查与评价

利用武汉东湖各子湖多年可靠的地面监测资料和1999年9月Landsat-7的TM各波段的卫星遥感数据,建立了各子湖的营养状态指数与TMb5图像上的灰度值之间的线性关系模型,并运用该模型对武汉各湖泊进行富营养化评价。同时基于地面监测资料,用日本学者相崎守弘提出的修正富营养化指数法对武汉主要湖泊的富营养化程度进行评价。两种方法评价结果都显示,武汉大多数湖泊呈富营养化状态,一些湖泊已接近甚至达到极富营养化。在用两种方法同时评价的十个湖泊中,有四个湖泊的评价结果完全一致,其余的六个湖泊富营养化程度只相差一个级别。两种方法评价结果存在差异,可能有以下三个原因;（1）遥感方法反映了是图像所在时段的某一个区域上的平均值,营养化指数法反映的是若干个采样站的年平均值;（2）TM图像的获取时间比地面监测的时间晚;（3）遥感影像可能受到云、泥沙等悬浮物、高等水生植物以及湖泊水深等的影响。遥感评价结果与地面监测结果基本一致,利用遥感进行湖泊水体富营养化监测价是可行的,有效的,利用该方法可进行大范围的湖泊富营养化调查评价。     

玄武湖挺水植物区与敞水区浮游甲壳动物昼夜水平迁移初探

浮游甲壳动物昼夜垂直迁移(DVM)是深水湖泊中的一种常见的现象,在浅水湖泊中,没有明显的下层滞水层为浮游甲壳动物提供避护所,浮游甲壳动物的垂直迁移活动不明显。但浅水湖泊挺水植物的存在为浮游甲壳动物提供了区别于敞水带的生境,结合理化、浮游植物和鱼的因素,对浅水湖泊玄武湖挺水植物区与敞水区浮游甲壳动物的昼夜水平迁移进行了研究。结果得出：浅水湖泊玄武湖中理化环境（如温度、溶解氧和pH)在荷花区、敞水区、荷花区与敞水区的交界区差异不大,对浮游甲壳动物的昼夜水平迁移不起主导作用。荷花区的浮游植物在质量和数量上低于敞水区,浮游甲壳动物在夜间捕食压力小的情况下会向敞水区移动。敞水区、交界区浮游甲壳动物在白天被捕食的风险要大于荷花区,因而白天时间浮游甲壳动物会迁移到荷花区聚集.     

Use of a food web model to evaluate the factors responsible for high PCB fish concentrations in Lake Ellasjøen, a high Arctic Lake

Background, aim, and scope

Lake Ellasjøen, located in the Norwegian high arctic, contains the highest concentrations of polychlorinated biphenyls (PCBs) ever recorded in fish and sediment from high arctic lakes, and concentrations are more than 10 times greater than in nearby Lake Øyangen. These elevated concentrations in Ellasjøen have been previously attributed, in part, to contaminant loadings from seabirds that use Ellasjøen, but not Øyangen, as a resting area. However, other factors, such as food web structure, organism growth rate, weight, lipid content, lake morphology, and nutrient inputs from the seabird guano, also differ between the two systems. The aim of this study is to evaluate the relative influence of these factors as explanatory variables for the higher PCB fish concentrations in Ellasjøen compared with Øyangen, using both a food web model and empirical data.

Methods

The model is based on previously developed models but parameterized for Lakes Ellasjøen and Øyangen using measured data wherever possible. The model was applied to five representative PCB congeners (PCB 105, 118, 138, 153, and 180) using measured sediment and water concentrations as input data and evaluated with previously collected food web data.

Results

Modeled concentrations are within a factor of two of measured concentrations in 60% and 40% of the cases in Lakes Ellasjøen and Øyangen, respectively, and within a factor of 10 in 100% of the cases in both lakes. In many cases, this is comparable to the variability associated with the data as well as the efficacy of the predictions of other food web model applications.

Discussion

We next used the model to quantify the relative importance of five major differences between Ellasjøen and Øyangen by replacing variables representing each of these factors in the Ellasjøen model with those from Øyangen, in separate simulations. The model predicts that the elevated PCB concentrations in Ellasjøen water and sediment account for 49%–58% of differences in modeled fish PCB concentrations between lakes. These elevated sediment and, to a lesser extent, water concentrations in Ellasjøen are due to PCB loadings from seabird guano. However, sediment–water fugacity ratios of PCBs are consistently greater in Ellasjøen compared with Øyangen, which suggests that internal lake processes also contribute to differences in sediment and water concentrations. We hypothesize that the nutrients associated with guano influence sediment–water fugacity ratios of PCBs by increasing the stock of pelagic algae. As both these algae and the guano settle, their organic carbon content is degraded faster than PCBs, which causes an extra magnification step in Ellasjøen before these detrital particles are consumed by benthic organisms, which are in turn consumed by fish. The model predicts that the remaining ～50% of the differences in PCB concentrations observed between the fish of these lakes are due to other subtle differences in their food web structures.

Conclusions

In conclusion, based on the results of a food web model, we found that the most dominant factors influencing the higher PCB fish concentrations in Lake Ellasjøen compared with Øyangen are the higher sediment and water concentrations in Ellasjøen, caused by seabird guano. Together, sediment and water are predicted to account for 49%–58% of differences in fish concentrations between lakes. Although seabird guano provides a source of nutrients to the lake, in addition to contaminants, empirical data and indirect model results suggest that nutrients are not leading to decreased bioaccumulation, in contrast to what has been observed in temperate, pelagic food webs.

Recommendations and perspectives

The results of this study emphasize the importance of considering even small differences in food web structure when comparing bioaccumulation in two lakes; although the food web structures of Ellasjøen and Øyangen differ only slightly, the model predicts that these differences account for most of the remaining ～50% of the differences in PCB fish concentrations between the two lakes. This study further demonstrates the utility of food web models as we were able to predict and tease apart the influence of various factors responsible for the elevated concentrations in the fish from Lake Ellasjøen, which would have been difficult using the field data alone.     

Ra–Po–Pb isotope systematics in waters of Sambhar Salt Lake,Rajasthan (India): geochemical characterization and particulate reactivity

The Sambhar Salt Lake hydrological system, including river waters, groundwaters, evaporating pans and sub-surface brines, has been analyzed for the salt content (TDS) and naturally occurring radionuclides (²¹⁰Po, ²¹⁰Pb and ^226,228Ra). The abundance of these radionuclides and their activity ratios show a wide variation in different hydrological regimes, which helps to geochemically characterize the lake system. A significantly lower Ra to total dissolved solids (TDS) ratio in the brines (by two to three orders of magnitude), when compared to the groundwaters and river waters, suggests removal of dissolved Ra by co-precipitation with Ca–Mg minerals at an early stage of the brine evolution. The concentration of Ra in evaporating lake/pan waters saturates at a value of about 35 Bq L⁻¹ over the salinity range of 100–370 g L⁻¹; attributable to its equilibration with the clay minerals. The two distinct regimes, saline lake system (lake water, evaporating pans and sub-surface brines) and groundwaters have been identified based on their differences in the distribution of ^226,228Ra isotopes. This observation points to the conclusion that the groundwaters and the lake brines are not intimately coupled in terms of their origin and evolution. The abundances of ²¹⁰Po and ²¹⁰Pb along with their activity ratios (²¹⁰Po/²¹⁰Pb) are markedly different among the surface lake waters/evaporating pans, sub-surface lake brines and groundwaters. These differences are explained in terms of different geochemical behaviour of these nuclides in presence of algae and organic matter present in these water regimes.     

利用中巴地球资源卫星数据反演武汉市湖泊营养状态指数

以武汉市主要湖泊为例,研究了利用中巴地球资源卫星（CBERS2）数据反演水体营养状态指数（TLI）。研究旨在评估利用中巴地球资源卫星数据来估算内陆水体富营养化程度的可能性。首先利用地面水质监测数据计算武汉市某些湖泊监测点的“真实的”营养状态指数（包括综合营养状态指数和修正的Carlson营养状态指数）,同时,在事先经过辐射校正和几何校正的CBERS2图像上,以9×9像元为采样窗口,提取各个对应地点的灰度值均值（从波段1至波段4）;然后,采用多元逐步回归分析,以各波段灰度值均值为自变量,建立营养状态指数经验遥感反演模型;最后,利用模型对整个湖泊水体的营养化状态指数进行反演,并绘制了其空间分布图。 结果显示,营养状态指数的自然对数值与CBERS2图像各波段灰度值之间存在较好相关关系,回归系数平方值(R²)为0.51。利用反演模型反演得到的湖区水质分布与实际情况基本相符。由于CBERS2图像数据可以从我国许多数据分发中心免费获取,这为低成本的水质遥感监测提供了一条途径。     

洪泽湖湿地生态系统保护与修复关键技术研究

分析了洪泽湖湿地生态系统属性及其在南水北调工程实施后的演变趋势,利用野外实验研究,在生境改变条件下,适用于不同湿地退化状况的人工辅助恢复技术;在实验监测的基础上,对洪泽湖几种典型湿地生态系统的生态功能进行了定量评价,为生态恢复工程的设计提供必要的技术支持。     

典型湖泊水华特征及相关影响因素分析

通过2011-2015年对太湖、巢湖和滇池水华高发季节的连续监测,以藻类密度和水华面积为判据评价了3个湖体的水华情况及变化趋势,探讨了水华发生的主要影响因素。结果表明：太湖水华程度以"轻度水华"为主,巢湖水华程度以"轻微水华"为主,滇池水华程度以"中度水华"为主;太湖、巢湖和滇池水华规模均以"零星性水华"为主;太湖和巢湖藻类密度与水温、pH、溶解氧、总氮、总磷和高锰酸盐指数均呈显著正相关,与透明度呈显著负相关,与氨氮无显著相关性;滇池藻类密度与水温、总磷和高锰酸盐指数均呈显著正相关,与透明度和氨氮呈显著负相关,与pH、溶解氧和总氮无显著相关性。     

滇池浮游藻类群落构成调查

对滇池浮游藻类群落组成和空间分布开展了2次调查,鉴定出藻类8门66属159种及变种,绿藻种类最多,蓝藻次之。5、12月滇池全湖平均藻类密度分别为1.398×108、2.180×108个/升,蓝藻门微囊藻属为优势藻类。5月的调查中滇池外海藻类生物量呈北高南低的格局,而12月则呈现南部和中部高,北部低。外海的藻类生物量明显高于草海,草海藻类群落构成与外海明显不同,主要表现为绿藻门藻类所占比例较高。12月滇池外海及全湖藻类生物量都显著高于5月。与上一次(2006—2007年)滇池浮游藻类的系统调查相比,滇池(主要是外海)浮游藻类在物种数量、常见藻类、优势藻类及生物量水平方面与之接近。