使用多普勒超声成像比较栉孔扇贝与虾夷扇贝循环生理特征

将先进的多普勒超声成像技术运用于栉孔扇贝(Chlamys farreri)和虾夷扇贝(Patinopecten yessoensis)循环生理学的研究中,首次量化了扇贝心率(HR)、血流加速度(ABF)、收缩峰值速度(PS)、舒张末期速度(ED)、血液最大瞬时血流量(Max-IBF)、血液最小瞬时流量(Min-IBF)、收缩期与舒张期流速比(S/D)和阻力指数(RI)等指标,对比了两种不同耐温性扇贝的循环生理指标差异。结果表明,两种扇贝HR、ABF、PS、ED、Max-IBF、Min-IBF与水温均呈正相关;在10—25°C间,栉孔扇贝和虾夷扇贝HR范围分别为16—39、14—31次/min,ABF范围分别为1.75—15.84、0.99—7.41cm/s2,PS范围分别为3.54—8.09、2.32—8.85cm/s,ED范围分别为1.51—3.15、1.09—4.23cm/s,Max—IBF范围分别为0.051—0.193、0.137—0.316m L/s、Min—IBF范围分别为0.025—0.072、0.022—0.131m L/s、RI范围分别为0.49—0.69、0.42—0.54,S/D范围为2.28—2.83、1.75—2.12。同一温度下栉孔扇贝的HR、ABF、PS、ED指标水平均高于虾夷扇贝,Max-IBF、Min-IBF水平均低于虾夷扇贝;两种扇贝RI和S/D指标均在一定范围内波动。研究显示,虾夷扇贝在较低的心脏和血流搏动节律下保持了高效的血液流通,从而以相对较少的能量消耗维持了其机体代谢对血液循环的需求,这也与其冷水性的生态习性相适应。     

白令海夏季浮游植物的群落结构与时空变化

通过1999年和2010年夏季同期7月在白令海(169°E~166°W,50°N~67°N)获取的94份浮游植物样品分析,获得了近十年的始末两个时间节点的浮游植物群落结构与时空变化,探讨了浮游植物群落动态及其与环境因素的关联。研究结果显示,共鉴定浮游植物(>10μm)5门58属153种,分为3个生态类群。硅藻是浮游植物的主体,种类多丰度高,占总种类数目的66.7%,占总丰度的95.2%。鉴于样品属性和空间范围的不同,物种组成有细微差别,丰度有较大差异且空间分布明显不同,高丰度区受控于上层营养盐供给和表层环流系统。优势种从北方温带大洋性硅藻演变为广温广盐性与冷水性硅藻,1999年以西氏新细齿状藻为第一优势种,柔弱伪菱形藻次之;2010年以丹麦细柱藻为第一优势种,冷水性的诺登海链藻次之并在陆架和陆坡占优。浮游植物群落结构较为稳定,由深水群落和浅水群落组成。深水群落分布于太平洋西北部和白令海盆,种类组成以温带大洋性的西氏新细齿状藻、长海毛藻、大西洋角毛藻和广布性的菱形海线藻、扁面角毛藻、笔尖根管藻为主,丰度低,种间丰度分配均匀,优势种多元化,物种多样性高;浅水群落分布于白令海陆坡和陆架,主要由冷水性的诺登海链藻、叉尖角毛藻、聚生角毛藻和广布性的丹麦细柱藻、旋链角毛藻组成,丰度高,种间丰度分配不均匀,优势种突出,物种多样性低。白令海夏季浮游植物种类组成及丰度变化直接受控于表层环流、营养盐、春季冰缘线等环境因素。     

Quality control methods for KOOS operational sea surface temperature products

Sea surface temperature SST obtained from the initial version of the Korea Operational Oceanographic System(KOOS) SST satellite have low accuracy during summer and daytime. This is attributed to the diurnal warming effect. Error estimation of SST data must be carried out to use the real-time forecasting numerical model of the KOOS. This study suggests two quality control methods for the KOOS SST system. To minimize the diurnal warming effect, SSTs of areas where wind speed is higher than 5 m/s were used. Depending on the wind threshold value, KOOS SST data for August 2014 were reduced by 0.15°C. Errors in SST data are considered to be a combination of random, sampling, and bias errors. To estimate bias error, the standard deviation of bias between KOOS SSTs and climatology SSTs were used. KOOS SST data yielded an analysis error standard deviation value similar to OSTIA and NOAA NCDC(OISST) data. The KOOS SST shows lower random and sampling errors with increasing number of observations using six satellite datasets. In further studies, the proposed quality control methods for the KOOS SST system will be applied through more long-term case studies and comparisons with other SST systems.     

南海上层经向翻转环流的低频变化

The low-frequency variability of the shallow meridional overturning circulation(MOC) in the South China Sea(SCS) is investigated using a Simple Ocean Data Assimilation(SODA) product for the period of 1900–2010. A dynamical decomposition method is used in which the MOC is decomposed into the Ekman, external mode, and vertical shear components. Results show that all the three dynamical components contribute to the formation of the seasonal and annual mean shallow MOC in the SCS. The shallow MOC in the SCS consists of two cells: a clockwise cell in the south and an anticlockwise cell in the north; the former is controlled by the Ekman flow and the latter is dominated by the external barotropic flow, with the contribution of the vertical shear being to reduce the magnitude of both cells. In addition, the strength of the MOC in the south is found to have a falling trend over the past century, due mainly to a weakening of the Luzon Strait transport(LST) that reduces the transport of the external component. Further analysis suggests that the weakening of the LST is closely related to a weakening of the westerly wind anomalies over the equatorial Pacific, which leads to a southward shift of the North Equatorial Current(NEC) bifurcation and thus a stronger transport of the Kuroshio east of Luzon.     

黄海南部小黄鱼洄游分布及种群结构特征

Monthly fishery survey data of the small yellow croaker Larimichthys polyactis in the southern Yellow Sea from2003 and 2013 were employed to evaluate the variation in the resource distribution and biological characteristics(especially body length and sex ratio) in the population on a decadal scale.The results indicated that the small yellow croaker migrated from the Shawai fishing ground to the Dasha fishing ground in spring and was mainly distributed in the central and western parts of the Dasha fishing ground in April and May.Larimichthys polyactis in the Dasha fishing ground migrated eastward to offshore wintering grounds in autumn and reached the central Dasha fishing ground in October and November.The small yellow croaker entered the western waters of the Shawai fishing ground in winter.A large number of age 0+ fish occurred in the Shawai and Jiangwai fishing grounds in October of 2003 and 2013.The body lengths of the spawning stock and wintering stock in 2013 were larger than those in 2003,and the monthly sex ratios(female to male) were significantly less than 1 in both years.The monthly distribution of this fish in the southern Yellow Sea was consistent with a previous finding that "the stock migrated between the wintering grounds in the west of Jeju Island and the Lüsi spawning grounds" but tended to move more northward,with the spawning grounds extending outward.In the past decade,body length variation experienced a decline after an increase,rather than a steady decrease.The sex ratio in the single-stick stow net showed a tendency to increase over the decade,but was either less than or more than 1 depending on the fishing gear;therefore,further studies should be conducted to determine the sex structure.     

海洋生态重要性区域的内涵与识别方法研究——以黄河口为例

海洋生态环境目前正在承受来自人类活动和气候变化的巨大压力;急需必要的管理工具或决策支持系统来应对这些压力所带来的生态环境问题。对海洋生境的分类识别是开展生物多样性保护的基础和前提;海洋生态重要区识别作为一种客观、科学和灵活的生境分类评估和选划方法;已被科学界和管理者广泛接受和认可。本文首先介绍了海洋生态重要区的概念内涵以及识别方法的研究进展;给出了海洋生态重要区的定义;之后以黄河口为例;初步建立了针对该区域的生态重要区识别标准和评价方法;对黄河口及邻近海区进行了生态重要性等级划分。本文是对生态重要区识别方法在我国近海的首次应用尝试;研究结果可为我国基于生态系统的海洋管理提供科学方法和工具;也可为其他区域的研究提供借鉴。     

A statistical analysis of mesoscale eddies in the Bay of Bengal from 22–year altimetry data

本文使用一种基于SLA数据的涡旋识别方法,通过22年的AVISO高度计测高数据对孟加拉湾的中尺度涡特征进行了研究。本文主要分析了孟加拉湾涡旋的地理分布、涡旋极性、涡旋生命周期和传播距离、涡旋产生和消失位置、涡旋传播方向和移动轨迹、涡旋运动特征、涡旋属性的演化以及涡旋活动的季节和年际变化等特性。涡旋主要分布在孟加拉湾西部海域,并且大部分涡旋向西移动。涡旋极性分布显示气旋涡更经常出现在湾的西北部和南部,而反气旋涡主要出现在湾的东部。在22年间,共追踪探测到生命周期超过30天的气旋涡565个、反气旋涡389个;对所有生命周期和传播距离而言都是气旋涡数量居多。所有观测到的涡旋的运动属性分析显示气旋涡的涡旋平均振幅大于反气旋涡;对平均半径和平均移动速度而言,气旋涡和反气旋涡相差不大。而且,涡旋属性演化显示生命周期超过90天的涡旋具有明显的双阶段演化特征,包括一个前50天的涡旋成长阶段和一个50天之后的涡旋消亡阶段。针对涡旋活动的季节变化,气旋涡在春季居多而反气旋涡在夏季较多;长生命周期的涡旋季节分布显示在孟加拉湾涡旋活动具有明显的季节分布特征。涡旋数量的年际变化与EKE变化有一个明显的负相关。     

东山乌礁湾海滩表层沉积物粒度时空变化分析

为了进一步了解海岛岬湾海岸表层沉积物粒度的时空分布特征和形成机制,作者以福建东山岛乌礁湾为典型研究区,通过秋、春、夏3个不同季节海滩表层沉积物的采集和点位测量,综合应用激光法和筛析法进行粒度测定。结果表明,东山乌礁湾海滩表层沉积物以0.16～0.50 mm之间的中、细砂为主,并含有少量的粗砂和细砾,这与区域砂质沉积背景有关;湾内从南到北剖面沉积物粒径由粗砂到细砂逐渐变细,主要受剖面地形、局地物源、季节性风浪作用和近岸往复水动力的影响。时间变化上,各取样站位表现出沉积物粒径粗、细不同程度的多种变化趋势,以秋季为参考,整体上表现为由南到北粒级的变小、增大和稳定,这与东北、南南西季风影响下的浪、潮作用以及沿岸流系格局变化下的水动力环境有关。     

杜氏盐藻生长及PSⅡ对不同磷源的响应

在实验室控制条件下,研究了无机磷磷酸二氢钠(NaH_2PO_4)及3种有机磷源三磷酸腺苷二钠盐(adenosine disodium triphosphate,ATP)、β-甘油磷酸二钠(sodiumβ-glycerophosphate,G-P)和D-葡萄糖-6-磷酸(D-Glucose 6-phosphate,D-G-6-P)对杜氏盐藻(Dunaliella salina)生长及PSII系统的影响。结果表明,杜氏盐藻在ATP和NaH_2PO_4的磷环境中生长迅速,最大比生长速率(μ_(max))分别为(0.736±0.0158)/d和(0.667±0.0553)/d;而β-甘油磷酸二钠和D-葡萄糖-6-磷酸培养条件下盐藻生长则具有滞后效应,μ_(max)分别为(0.232±0.0114)/d和(0.31±0.0077)/d。ATP和NaH_2PO_4作为磷源时,盐藻最大电子传递效率(ETR_(max))和最大饱和光强(I_k)显著高于β-甘油磷酸二钠和D-葡萄糖-6-磷酸处理组(P0.05),而NPQ则呈相反。JIP-test参数可知,单位反应中心吸收的光能(ABS/RC)、t=0时单位反应中心捕获的用于还原QA的能量(TR_0/RC)和最大光化学效率(Φ_(P0))在各组间差异不显著(P0.05),但β-甘油磷酸二钠和D-葡萄糖-6-磷酸处理组单位反应中心耗散掉的能量(DI_0/RC)显著增加(P0.05),ψ_0和Φ_(E0)显著降低(P0.05)。表明β-甘油磷酸二钠和D-葡萄糖-6-磷酸作为磷源时盐藻光合系统反应活性中心(RC)部分关闭,反应活性中心的数量(RC/CS_0)减少,PSⅡ受体侧电子传递受到影响,能量耗散效率提高。综上可知,杜氏盐藻均能利用无机磷和有机磷作为磷源供其生长,但ATP作为磷源使得盐藻在最短时间进入对数期,生物量显著提高(P0.05)。     

南海中尺度涡强度的季节和年际变化分析

为了研究南海中尺度涡强度的季节和年际变化规律,利用Matlab提取50 a(1958~2007年)简单海洋资料同化(Simple Ocean Data Assimilation,SODA)月平均数据集中流场和海表面高度场数据,应用一个涡旋自动探测算法对南海中尺度涡初始生成位置进行分析,并分析了海表面高度异常均方根值的季节变化和年际变化。结果表明:50 a里南海中尺度涡主要分布在吕宋岛西北海域、吕宋岛西南海域和越南以东广大海域,秋、冬季中尺度涡能量较高,春季中尺度涡最弱,中尺度涡强度高值区年际变化明显。从季节变化上看,海面高度异常均方根春、夏季最小,秋冬季最大;从年际变化上看,与同时期Nino3指数有显著负相关,周期大约为3 a。