Time scale of an early to mid-Paleozoic orogenic cycle of the long-lived Central Asian Orogenic Belt, Inner Mongolia of China: Implications for continental growth

We present a detailed, new time scale for an orogenic cycle (oceanic accretion–subduction–collision) that provides significant insights into Paleozoic continental growth processes in the southeastern segment of the long-lived Central Asian Orogenic Belt (CAOB). The most prominent tectonic feature in Inner Mongolia is the association of paired orogens. A southern orogen forms a typical arc-trench complex, in which a supra-subduction zone ophiolite records successive phases during its life cycle: birth (ca. 497–477 Ma), when the ocean floor of the ophiolite was formed; (2) youth (ca. 473–470 Ma), characterized by mantle wedge magmatism; (3) shortly after maturity (ca. 461–450 Ma), high-Mg adakite and adakite were produced by slab melting and subsequent interaction of the melt with the mantle wedge; (4) death, caused by subduction of a ridge crest (ca. 451–434 Ma) and by ridge collision with the ophiolite (ca. 428–423 Ma). The evolution of the magmatic arc exhibits three major coherent phases: arc volcanism (ca. 488–444 Ma); adakite plutonism (ca. 448–438 Ma) and collision (ca. 419–415 Ma) of the arc with a passive continental margin. The northern orogen, a product of ridge-trench interaction, evolved progressively from coeval generation of near-trench plutons (ca. 498–461 Ma) and juvenile arc crust (ca. 484–469 Ma), to ridge subduction (ca. 440–434 Ma), microcontinent accretion (ca. 430–420 Ma), and finally to forearc formation. The paired orogens followed a consistent progression from ocean floor subduction/arc formation (ca. 500–438 Ma), ridge subduction (ca. 451–434 Ma) to microcontinent accretion/collision (ca. 430–415 Ma); ridge subduction records the turning point that transformed oceanic lithosphere into continental crust. The recognition of this orogenic cycle followed by Permian–early Triassic terminal collision of the CAOB provides compelling evidence for episodic continental growth.     

赣南淘锡坑钨多金属矿床花岗岩和云英岩岩石特征及云英岩中白云母40Ar/39Ar定年

赣南崇义县淘锡坑钨矿位于南岭东西向构造带东段,属于以黑钨矿石英脉型为主的钨多金属矿床。矿床形成与燕山期中酸性岩浆作用有密切关系,石英矿脉受一组北西向断裂控制,穿切新元古界。本文在淘锡坑钨矿区3个揭露到花岗岩体顶部的中段（206、106、56中段）采集到岩体顶部云英岩样品,利用40Ar/39Ar同位素定年测得云英岩中的白云母的坪年龄分别为152.7 ± 1.5 Ma（206中段）,153.4 ± 1.3 Ma（106中段）,155.0 ± 1.4 Ma（56中段）。与前人用其他方法测定的花岗岩成岩和成矿年龄几乎一致。花岗岩和云英岩全岩稀土元素均具有M型四分组效应和强烈的Eu亏损特征,反映出花岗质岩浆经历了高度分异演化及其岩体结晶晚期流体/熔体相互作用。综合前人在南岭地区同类矿床的研究资料,可知南岭地区160～150Ma成岩成矿作用主要分布于南岭中-东段,可能为大陆边缘弧后岩石圈伸展的构造动力学背景的产物。     

Wind wave-forced fine sediment erosion during the slack water periods in Hangzhou Bay,China

The shallow water wave simulation model-SWAN incorporated with a simple fine sediment erosion model is applied to Hangzhou Bay, China, to model the horizontal distribution of the maximum bottom orbital velocity and corresponding fine sediment erosion rates induced by: (1) southeasterly steady winds (5, 20 and 30 m/s), (2) southwesterly steady winds (5 and 20 m/s); (3) northwesterly steady winds (5 and 20 m/s); (4) east-southeasterly steady winds (5 and 20 m/s); (5) easterly steady winds (5 and 20 m/s) under closed and unclosed boundaries; and (6) unsteady winds during the slack water periods. Results suggest: (1) the steady wind wave-induced maximum bottom orbital velocities and corresponding fine sediment erosion rates generally increased with the increasing steady winds; (2) closed and unclosed boundary conditions had more significant influences on modeled fine sediment erosion rates under 5 m/s easterly steady winds than 20 m/s; and (3) steady and unsteady wind wave-induced maximum bottom currents could be significant in eroding fine sediment bed in Hangzhou Bay. The results show implications for geomorphology, sedimentology, coastal erosion, and environmental pollution mitigation in Hangzhou Bay.     

基于主成分分析的东江流域水资源承载能力评价

本文分别介绍了主成分分析法的原理和算法,并将其运用到东江流域水资源承载能力评价中,并且与模糊综合评价结果进行比较。结果表明：两评价方法的评价结果都是东江流域水资源承载能力呈现中上游高下游低的分布趋势,对此提出水资源可持续利用的对策,以促进流域水资源与社会经济的协调发展。     

济南岩溶地下水化学成分的形成

本文研究济南岩溶排泄区地下水化学成分的形成。先用Cl-和NO3-浓度作为示踪剂分析补给区的大气降水输入,鉴别出西郊和平安店排泄区地下水没有被明显污染,市区和东郊排泄区地下水受到明显污染,污染主要来自当地浅层地下水或近地面土层。之后,利用西郊排泄区的测试数据进行了横向径流带的水-岩作用定量分析,与示踪剂研究结果一致,市区和东郊排泄区地下水被明显污染,同时提出地下水在径流过程中发生脱白云石化过程的趋势线。     

Tetraploid induced by physical and chemical methods in Jinjiang oyster(Crassostrea rivularis)

ＴｅｔｒａｐｌｏｉｄｉｎｄｕｃｅｄｂｙｐｈｙｓｉｃａｌａｎｄｃｈｅｍｉｃａｌｍｅｔｈｏｄｓｉｎＪｉｎｊｉａｎｇｏｙｓｔｅｒ（Ｃｒａｓｓｏｓｔｒｅａｒｉｖｕｌａｒｉｓ）￥ＲｏｎｇＳｈｏｕｂａｉ，ＳｈｉＳｈｕｍｅｉ，ＭｃＱｉｒｏｎｇ，ＬｉｕＳｈａｅｑｉｏ...     

福建海岛潮间带软体动物群落分布特征

福建海岛潮间带软体动物共鉴定248种，隶属于5纲78科161属，应用群落系数，等级聚类分析和极坐标排序研究软体动物落分布，结果表明，软体动物群落可分为3种类型，即河口型群落，近岸港湾群落和开阔海域群落，群落分布与海岛所处地理位置及其生境类型密切相关，盐度和水动力是重要的影响因子。     

浙江省海岛沿岸水域微生物生态分布

文章报道了浙江海岛沿岸水域中异养细菌、氨化细菌和反硝化细菌的数量分布及异养细菌的种群组成。结果表明：本调查海区异养细菌的数量较多，其数量分布范围在２．０４×１０４～８．３６×１０６个／ｄｍ３之间；氨化细菌数量分布范围在３．０×１０３～１．１×１０６个／ｄｍ３之间；反硝化细菌的数量分布范围在３．０×１０２～１．１－１０６个／ｄｍ３之间。细菌的数量与环境中营养盐的浓度之间存在密切关系。在不同的海区异养细菌的种群组成存在一定的差异，在浙北海区，革兰氏阴性菌所占比例为４１．６％，在浙中海区为４６．９％，在浙南海区为６４．９％。     

Relationships between chlorophyll a, bacteria, ATP, POC and respiration rates in the Changjiang Estuary and the plume

Bacteria abundance, chlorophyll a, ATP and POC concentrations and respiration rates of microorganisms in the Changjiang Estuary and the plume were determined in July 1986. The high values of bacteria abundance occurred in the river mouth in association with suspended matter. It is assumed that bacteria were the major contributor to ATP and the main consumer of dissolved oxygen, and that the relationship between ATP and POC was present in that area. In the dilution zone (salinity; 25-30), instead of bacteria, phytoplankton was the major contributor to ATP and respiration rates, due to diatom bloom. Close relationships between Chi a and ATP, and ATP and POC were observed. Contribution of microbial carbon to POC was also estimated.     

Application of Monte-Carlo statistical experiments in design of ocean engineering——Estimating the parameters, models and probabilities

Recently, some results have been acquired with the Monte- Carlo statistical experiments in the design of ocean en gineering. The results show that Monte-Carlo statistical experiments can be widely used in estimating the parameters of wave statistical distributions, checking the probability model of the long- term wave extreme value distribution under a typhoon condition and calculating the failure probability of the ocean platforms.