Diversity and Distribution of Sediment NirS-Encoding Bacterial Assemblages in Response to Environmental Gradients in the Eutrophied Jiaozhou Bay, China

A gene-clone-library-based molecular approach was used to study the nirS-encoding bacteria-environment relationship in the sediments of the eutrophic Jiaozhou Bay. Diverse nirS sequences were recovered and most of them were related to the marine cluster I group, ubiquitous in estuarine, coastal, and marine environments. Some NirS sequences were unique to the Jiaozhou Bay, such as the marine subcluster VIIg sequences. Most of the Jiaozhou Bay NirS sequences had their closest matches originally detected in estuarine and marine sediments, especially from the Chesapeake Bay, indicating similarity of the denitrifying bacterial communities in similar coastal environments in spite of geographical distance. Multivariate statistical analyses indicated that the spatial distribution of the nirS-encoding bacterial assemblages is highly correlated with environmental factors, such as sediment silt content, NH4+ concentration, and OrgC/OrgN. The nirS-encoding bacterial assemblages in the most hypernutrified stations could be easily distinguished from that of the least eutrophic station. For the first time, the sedimentological condition was found to influence the structure and distribution of the sediment denitrifying bacterial community.

The environment effect on fish assemblage structure in waters adjacent to the Changjiang (Yangtze) River estuary (1998-2001)

We collected fish abundance data in the Changjiang (Yangtze River) estuary and adjacent waters in November 1998, May 1999, November 2000, and May 2001. Using the data, we evaluated the characteristics of the fish assemblages at each site and investigated the effect of several environmental factors. We used a multivariate analysis, including community ordination methods such as detrended correspondence analysis (DCA) and canonical correspondence analysis (CCA), and two-way indicator species analysis (TWINSPAN). We analyzed the biological community structure and environmental factors to determine their spatial distributions, temporal dynamics, and seasonal variations. Among the fish species, five exceeded 5% of the total abundance: Harpodon nehereus (42.82%), Benthosema pterotum (13.85%), Setipinna taty (11.64%), Thryssa kammalensis (9.17%) and Apogonichthys lineatus (6.49%). These were separated into four ecological assemblages: hypsithermal-saline, hypsithermal-brackish, hypothermal-brackish, and hypothermal-saline. We evaluated the degree of influence of environmental factors on the fish community. Our analyses suggested that environmental factors including water depth, salinity, turbidity, transparency, nutrient, and suspended matter formed a synthetic spatial gradient between the coastal and pelagic areas. Ecological and environmental factors changed temporally from 1998 to 2001, and drove the fish community succession. The environmental factors driving the fish community structure included bottom temperature, water depth, bottom and surface pH, surface total phosphorous, and bottom dissolved oxygen. This investigation was completed before completion of the Three Gorges Dam; therefore the results of this study provide an important foundation for evaluating the influence of the human activities.

Autumn net copepod abundance and assemblages in relation to water masses on the continental shelf of the Yellow Sea and East China Sea

Copepod species diversity, abundance and assemblages in relation to water masses over the continental shelf of the Yellow Sea (YS) and East China Sea (ECS) were studied extensively based on the net plankton samples in autumn 2000. Multivariate analysis based on copepod assemblage resulted in recognition of five groups (Groups 1-5) corresponding to the water masses. Groups 1 and 2 delineated from inshore stations with low salinity YS Surface Water, and offshore stations with YS Cold Water in the YS. Group 3 located in the joint area of YS and ECS mainly with Mixed Water. Groups 4 and 5 in the ECS delineated two assemblages mainly from inshore and shallow stations with ECS Mixed Water in the southeastern ECS, and offshore stations along the ECS shelf edge controlled by saline Kuroshio Water. Salinity and temperature were more important in characterizing copepod assemblage of the continental shelf than chlorophyll a. (c) 2005 Elsevier B.V. All rights reserved.

一种基于新型数据预测方法的MICA仿真研究

在多元统计过程监控中,为解决因未知过程数据统计分布而产生误报漏报的现象,提出一种结合多向独立元分析法(MICA)和广义相关系数(GCC)数据预测的综合方法,进行在线监控过程的仿真。MICA分析方法能有效分解各变量的关联关系,且不需考虑建模数据是否符合正态分布,用此方法计算的独立元变量能更好地描述过程的变化规律。为提高预报未来过程故障的能力,提出用广义相关系数法进行数据预测:确定与运行轨迹相似的监控模型库中的轨迹,并使其相应部分承接于运行轨迹之后。现场采集聚氯乙烯聚合过程的数据进行仿真,仿真结果显示:对于在线监控和在线故障诊断方面,这种新型预测方法优于其它传统处理预测问题的方法。

广义预测控制方法在网络遥操作机器人系统中的应用

Internet网络的时变时延及网络数据丢包严重影响了遥操作机器人系统的操作性能,甚至造成系统不稳定。为了解决这一问题,提出一种新的基于Internet的遥操作机器人系统控制结构。通过在主端对给定信息加入时间标签获得过去的系统回路时延,采用多元线性回归算法,预测下一时刻系统回路时延,然后在从端设计一个广义预测控制器控制远端机器人,从而改善时变时延对系统性能的影响。应用广义预测控制器产生的冗余控制信息,降低了网络数据丢包对系统的影响。最后根据预测控制稳定性定理,推导出系统的稳定性条件。仿真试验结果表明,该方法能有效解决时变时延以及网络数据丢包引起的性能下降问题。