温度、pH对缢蛏(Sinonovacula constricta)消化酶活力的影响

本文研究了温度、pH对缢蛏(Sinonovacula constricta(Lamarck))三种主要消化酶(蛋白酶、淀粉酶和纤维素酶)活力的影响。结果表明：当温度在5～75℃之间时，蛋白酶、纤维素酶和淀粉酶的最适温度分别为为55℃、45℃和65℃；在不同的pH范围内，蛋白酶的最适PH值为9．2，淀粉酶的最适PH值为6．3和7．7，纤维素酶的最适PH值为5．2。缢蛏的淀粉酶和蛋白酶活力较大，纤维素酶活力极微。     

台湾海峡上升流区底栖生物数量动态的初步研究

不同季节底梄生物数量的动态由其组成种的种群特点所决定。在一些生命周期短(一年左右)、生长速度快(新生个体当年可以长成)的种处于优势的情况下,生物数量的季节变化就比较显著;而生命周期长、其种群由多个年龄组的个体构成的种占优势的情况下，一年之中种群数量就相对稳定。另一方面,底栖生物数量的急剧改变又决定于经济种的捕食活动和优势种的生物学过程。台湾海峡系经济鱼、虾类的集中分布区,尤以上升流区范围内的集群最密集。为了便于深入研究上升流与经济鱼、虾类资源的关系,本文着重探讨上升流范围内底栖生物数量的动态特点。     

大亚湾海域锥状斯氏藻赤潮及其与孢囊的关系

用沉积物捕捉器取样，研究了大亚湾海域２０００年６～９月孢囊（Ｃｙｓｔ）种群动态，同时 分析了浮游植物种群动态。研究期间（８～９月）该海域发生了一起大规模的锥状斯氏藻赤潮。 赤潮前一个月，锥状斯氏藻孢囊的平均日形成率为２．０５× １０５ｃｙｓｔｓ／（ｍ２·ｄ），丰度为５０．２２％， 该时期以有性生殖产生的静止期孢囊为主；在赤潮盛期的８，９月初，孢囊的平均日形成率达到 ２．０１ ×１０６ｃｙｓｔｓ／（ｍ２·ｄ），丰度为９６．９７％，此时期的孢囊多为营养细胞所形成的暂时性孢囊； 赤潮结束后，由于环境条件的恶化，暂时性孢囊的形成达到高峰，平均日形成率为１．２４×ｌ０７ ｃｙｓｔｓ／（ ｍ２·ｄ），丰度为９９.５３％。结果表明大亚湾丰富的孢囊是潜在的种源（Ｓｅｅｄ　ｂｅｄ），２０００年 的夏季、秋李持续高温（＞２５℃），台风减少及风力减弱等有利锥状斯氏藻的环境条件诱发孢 囊萌发，开始了该种类的赤潮。     

Atmospheric input of trace elements to the western Pacific Ocean and the Kuroshio ocean area

ＡｔｍｏｓｐｈｅｒｉｃｉｎｐｕｔｏｆｔｒａｃｅｅｌｅｍｅｎｔｓｔｏｔｈｅｗｅｓｔｅｒｎＰａｃｉｆｉｃＯｃｅａｎａｎｄｔｈｅＫｕｒｏｓｈｉｏｏｃｅａｎａｒｅａ￥ＱｉａｎＦｅｎｌａｎ；ＹｕＨｏｎｇｊｉａｎ；ＬａｎＹｏｕｃｈａｎｇ；ＣｈｅｎＺｈｉ；Ｚｈｏｕ...     

2，3，4－三氟硝基苯的合成研究

提出以２，６－二氯苯胺为原料，经重氮化、氟硼酸重氮盐热分解、硝化、氟化等步骤，制成２，３，４－三氟硝基苯。优点是工艺简单，收率较高．     

大窑湾海域水化要素分布及相关关系的探讨

本文依据大窑湾的环境调查资料为基础，系统地阐述了水体中化学要素ｐＨ、盐度、透明度、ＤＯ、ＣＯＤ、ＴＯＣ、浊度、悬浮物、ＮＨ４－Ｎ、ＮＯ２－Ｎ、ＮＯ３－Ｎ、ＰＯ４－Ｐ、ＳｉＯ３－Ｓｉ、Ｃｕ、Ｐｂ、Ｚｎ、Ｃｄ、Ａｓ、Ｈｇ、Ｃｒ、硫化物、六六六、石油等分布规律。诸要素主要是在潮流水动力支配下，形成扩散带。各要素中仅有无机氮和ＰＯ４－Ｐ两项含量超标，其余要素含量范围都是处于海水正常浓度水平，属于一类海水水质。文章并对各要素进行相关关系分析。     

济州岛南部海区的双跃层现象

本文分析了济州岛南部区域温度双跃层现象的类型及其成因。特别阐明了双跃层的波状现象,指出:强流锋区的侧向效应,黑潮次—中层混合水的爬升,黄海冷水团边缘密度环流引起的侧向流动,以及上、下层流速、流向不一致引起的剪切作用,是导致双跃层波状现象的主要原因。发现上、下跃层之间存在着“跃层间环流”,这是一个有趣的海洋学现象,它将导致双扩散的发生和有利于双跃层的维持。     

Morphology, reproduction, ecology and isoenzyme electrophoresis of Capitella complex in Qingdao

-Morphology, reproduction, ecology and isoenzyme electrophoresis of a Capitella complex in Qingdao were examined from 1983 to 1984. We determined that the Capitella complex in Qingdao was composed of at least three sibling species: Capitella cf capitata, Capitella sp. I and Capitella sp. IT. Although these three species are very similar in morphology, they differ in: three kinds of isoenzyme electrophoresis, staining reactions, developmental pattern, larval morphology and dispersal, reproductive strategies, breeding season and population ecology. In addition, they show a series of minor quantitative variations in adult morphology, especially in number and morphology of setae. Such differences can be detected only at the population level. Some ecological data such as density, growth rate, mortality and sex distribution are also provided in this paper.     

Cross-equatorial flow and its effects on the hurricanes occurrence over the Southern Hemisphere

Channels of cross - equatorial flow and their characteristics Winds at every 5 deg. grid point from 30°E to 180° over the equator at 850 hPa and 200hPa from December 1984 to February 1985 have been separated into U(zonal wind) andV(meridional wind).The V component has been used to represent cross- equatorial flow. FromFig. 1 we obtained that as during the Northern summer,there are also severa1 regions in which     

A dipole mode at thermocline layer in the tropical Indian Ocean

Temperature data at different layers of the past 45 years were studied and we found adiploe mode in the thermocline layer (DMT): anomalously cold sea temperature off the coast of Sumatra and warm sea temperature in the western Indian Ocean. First, we analyzed the temperature and the temperature anomaly (TA) along the equatorial Indian Ocean in different layers. This shows that stronger cold and warm TA signals appeared at subsurface than at the surface in the tropical Indian O-cean. This result shows that there may be a strong dipole mode pattern in the subsurface tropical Indian Ocean. Secondly we used Empirical Orthogonal Functions (EOF) to analyze the TA at thermocline layer. The first EOF pattern was a dipole mode pattern. Finally we analyzed the correlations between DMT and surface tropical dipole mode (SDM), DMT and Nino 3 SSTA, etc. and these correlations are strong.