对应分析方法在粤西水东湾动力沉积环境分析的应用

本文以粤西水东湾表层沉积物样品的粒度分布为基本数据,使用对应分析方法并结合地形与波流特征,分析了海湾动力沉积环境。分析结果表明,海湾现代沉积环境可划分为4个动力沉积区。     

聚类分析法在浅海水团分析中的应用及黄、东海变性水团的分析

本文引入变性水团概念,用聚类分析确定黄、东海浅海海域变性水团的边界及其变化。根据给定的标准进行聚类,确定了水团的个数、边界及混合区。 由聚类方法所得结果看出,在该海区中有八个变性水团。根据温、盐相对指标,将这些水团分为九种不同的特征。也可以把这些水团划分为三种盐度类型。在温—盐点聚图上,不同变性水团的温盐点,分布于一条曲线附近,它体现出逐级变性的特点。各变性水团的变化范围都很大,这说明该海区中水团变性强烈。在暖季中的增温降盐和冷季中的降温增盐,可认为是整个黄海和东海水体变性的特征。所有季节性水团都经历一个形成与消亡的过程。 文中讨论了变性水团和海洋环境的相互关系。水团变性是热力因素和动力因素共同作用而产生的。通过变性水团的分析,作者认为,在该海区水团的变性中,热力因素起着主要作用。变性水团界线的舌状分布与流向之间的关系是很明显的,可作为分析环流的旁证。最后描述了变性水团和底层中心渔场之间的关系。     

鲁南近浅海沉积物样品的因子分析及其地质意义

本文提出河流携带入海的沉积物或沿岸剥蚀物中矿物的分布及再组合是受多种因素控制的。为了确定控制鲁南两城河至白马河沉积物样品中矿物分布及再组合的主要因素,作者对该区109个沉积物样品的重矿物资料进行了Q型和R型因子分析。研究指出,在诸多的河流中,白马河和两城河是控制该区沉积物分布的最上要的河流;矿物的化学稳定性是决定该区矿物再组合的主要因素。     

Molecular analysis of complete ssu to lsu rdna sequence in the harmful dinoflagellatealexandrium tamarense (korean isolate, HY970328M)

New PCR primers (N=18) were designed for the isolation of complete SSU to LSU rDNA sequences from the dinoflagellateAlexandrium tamarense. Standard PCR, employing each primer set selected for amplifications of less than 1.5 kb, successfully amplified the expected rDNA regions of A. tamarense (Korean isolate, HY970328M). Complete SSU, LSU rDNAs and ITS sequences, including 5.8S rDNA, were recorded at 1,800 bp, 520 bp and 3,393 bp, respectively. The LSU rDNA sequence was the first report inAlexandrium genus. No intron was found in the LSU rRNA coding region. Twelve D-domains within the LSU rDNA were put together into 1,879 bp (44.4% G+C), and cores into 1514 bp (42.8% G+C). The core sequence was significantly different (0.0867 of genetic distance, 91% sequence similarity) in comparison withProrocentrum micans (GenBank access. no. X16108). The D2 region was the longest in length (300 bp) and highly variable among the 12 D-domains. In a phylogenetic analysis using complete LSU rDNA sequences of a variety of phytoplankton,A tamarense was clearly separated with high resolution against other species. The result suggests that the sequence may resolve the taxonomic ambiguities ofAlexandrium genus, particularly of the tamarensis complex.     

深圳大鹏湾表层沉积物碎屑矿物空间分布特征

立足样品测试数据,利用空间分析、空间插值、地质统计以及景观生态学方法,深入分析了深圳大鹏湾表层沉积物碎屑矿物的空间分布特征,并使用球状模型对相应半变异函数进行理论建模。结果表明,碎屑矿物分布的Hurst分维数为0.28～0.97,空间几何分维数为1.03～1.72;Moran Ⅰ型空间自相关系数-0.15～0.53。在此基础上,以等值线分布所包围范围作为划分尺度,以Shannon-Wiener信息指数作为度量,得到的矿物分布所反映出的信息量或者富集程度指数为0.88～1.85。     

南海晚第四纪浮游有孔虫类群变化所表征的古海洋学特征

通过对南海4个岩心的74个样品进行Q型因子分析,求得4个浮游有孔虫组合:亚热带-热带组合,温凉组合,热带易溶组合和亚热带组合。亚热带-热带组合为优势组合,它的发育状况反映了晚第四纪西太平洋热带海水对南海的影响程度,其因子载荷作为古海流特征的参数。温凉组合的发育与南海存在冷涡有关。利用转换函数FP-12E计算了南海南部表层古水温,冰期与间冰期的表层水温平均变化冬季为4.7℃和2.9℃,夏季为3.0℃和2.1℃,季节性温差冰期最大可达8.6℃,间冰期最大可达5.0℃,均比太平洋同一纬度海区的大。冬季表层古水温波动比夏季的大。全新世的表层水温呈上升趋势,但在NS86-43柱中有一变冷现象,这可能和the younger Younger Dryas有关。     

南海北部—观测点内潮特征的初步分析

采用功率谱分析、调和分析等方法，对南海北部－观测点连续９ｄ（１９８８年５月８—１６日）的温度。盐度和海流及跨越该期间较长的（１９８８年４月２４日－７月２２日）潮位资料进行了分析研究。结果表明，观测点存在着一种内潮现象，其波动的周期在２４ｈ左右，它传播的方向大体是偏北。     

长江口及济州岛附近海域变性水团的初步分析

基于变性水团的概念,本文把聚类分析用于确定长江口及济州岛附近海域变性水团的边界。由聚类分析得到的结果表明,在该海区有十个水团。对它们的特征、分布与变化进行了初步分析。作者得出的结论是:1、在十个水团中,有四个大洋性水团,六个变性水团。2、该海域水团变性的特点为暧季增温、降盐、降氧,而冷季则相反。3、水团变性是由海区内、外因素综合作用而发生的,而后者在浅水区域起主要作用。4、水团边界的舌状分布与流向之间有明显关系。因之,海流的方向及强度,大致可依水团舌状分布而判断。5、底层中心渔场基本上位于各变性水团之间的混合区或其附近。     

Optimum Sample Size to Detect Perturbation Effects: The Importance of Statistical Power Analysis – A Critique

Abstract. The current article describes statistical power analysis as an efficient strategy for the estimation of the optimum sample size. The principle aim is constructively to criticise and enrich the results presented by Mouillot et al. (1999) , who estimate the optimum sample size for evaluating possible perturbations. The authors did not make any reference to statistical power analysis, even though their objective clearly went beyond a simple stock evaluation to assess management strategies in a particular marine ecosystem. Surprisingly, they proposed (a priori) an ANOVA design to test a hypothesis considering both space and temporal scales. However, the authors did not cover important topics related with power analysis and the precautionary principle, both used into environment impact assessment programmes for marine ecosystems. Based on their results and on statistical power analysis, it is demonstrated that the variability (dispersion statistics), a key factor they used to estimate the sample size, is less relevant than the magnitude of perturbation (effect size). Therefore, a greater effort must be devoted to estimate the effect size of a particular phenomenon rather than a desired variability.