基于环境因子的东、黄海日本鲐Pella-Tomlinson生物经济模型建立与应用

【目的】建立基于环境因子的生物经济模型,研究环境因子对鲐鱼资源的影响。【方法】根据2006—2015年中国鲐鱼生产统计鱼产卵场和索饵场海洋表面温度(SST)、索饵场海洋表面温度梯度(GSST)和索饵场海表面高度(SSH)等数据,假设产卵场和索饵场环境因子对东、黄海日本鲐剩余产量产生影响,基于剩余产量模型分析环境因子对东、黄海日本鲐资源的影响。【结果与结论】产卵场和索饵场关键因子共同影响内禀增长率r,产卵场关键因子影响环境容纳量K,进而影响剩余产量和资源量;2011、2012和2015年日本鲐遭受过度捕捞;每年的最大可持续产量(MSY)、最大经济产量(MEY)和生物经济参考点(BE)及其对应的捕捞努力量fMSY、fMEY和fBE随着环境因素的改变而变化。在渔业管理中应考虑环境因素。     

基于BP神经网络的中西太平洋鲣鱼渔场预报模型构建与比较

根据1998-2013年中西太平洋鲣鱼围网生产统计数据以及海洋环境数据,采用BP人工神经网络模型,分别以初值化后的单位捕捞努力量渔获量(CPUE,Catch per unit of effort)和捕捞努力量(Fishing Effort)作为中心渔场的表征因子,并作为BP模型的输出因子,以时间因子、空间因子、海洋环境因子(包括海表温度SST、海面高度SSH、Nino3.4区海表指标及叶绿素浓度Chl-a)等作为输入因子,构建22个BP神经网络模型,以最小拟合残差作为判断标准,比较渔场预报模型优劣。实验结果,以捕捞努力量为输出因子的模型的最小拟合残差均小于以CPUE为输出因子的模型,表明捕捞努力量更适合作为表征中心渔场的因子;同时,拟合残差的平均值随着输入因子的增加而减少,表明本研究所选的时间、空间、海洋环境因子等对鲣鱼中心渔场预报均极为重要。其中,以月份、经度、纬度、SST、SSH、Nino3.4a、Chl-a为输入因子,以初值化后的捕捞努力量为输出因子,结构为7-5-1的BP神经网络模型预报精度为最高,影响因子的重要性从高到低依次是经度、Chl-a、SST、纬度、NINO3.4a、SSH、月份。     

基于气候和环境因子的近海鲐鱼资源评估

【目的】研究环境与气候因子对鲐鱼的生长、繁殖和补充的影响。【方法】根据我国东、黄海鲐鱼灯光围网渔业捕获量、捕捞努力量建立剩余产量模型,尝试用6月产卵场(127°30′E、29°30′N)的平均海表温(SST)、Nino 3.4区海表温度距平值(Nino-SSTA)、太平洋中高纬年代际振荡(PDO)和南方涛动指数(SOI)4个因子对剩余产量模型进行优化,分析SST、Nino-SSTA、PDO和SOI对东、黄海鲐鱼资源量和最大可持续产量的影响。【结果】经过Pearson相关性分析,发现PDO对CPUE残差无影响,对SST、Nino-SSTA和SOI有影响。选取相关性较高的SST、Nino-SSTA对模型进行优化,发现优化后的模型对鲐鱼渔获量的拟合效果比优化前显著增强。【结论】6月份产卵场SST、Nino 3.4区海表温度距平值对鲐鱼资源变化有明显的影响,建议在渔业管理中应根据各年环境因子的情况确定最大可持续产量,合理制定管理策略。     

基于频度统计和神经网络的北太平洋柔鱼渔场预报模型比较

利用2004~2010年北太平洋鱿钓船队生产数据和海洋环境数据,以海表温度(SST)1℃、海面高度(SSH)为1 cm、叶绿素a浓度(CHL-a)为0.1 mg/m3的间距,分析作业产量、CPUE与SST、SSH、CHL-a的关系,得到柔鱼渔场适宜环境因子范围,并将生产数据和环境数据匹配组成样本集,建立北太平洋柔鱼空间分布BP神经网络模型;利用2011年环境数据预报柔鱼渔场,并与2011年实际生产数据进行对比。结果表明,6~10月各月实际作业位置落入基于频度统计方法预报渔场的概率达90%以上;而BP模型预报的平均精度为79.2%,最低精度为52.5%。基于多环境因子的频度统计柔鱼渔场预报模型优于神经网络模型。     

基于栖息地指数的智利外海茎柔鱼渔场预报模型优化

根据2010~2013年3-5月渔汛期间智利外海茎柔鱼生产统计数据以及海表面温(SST)、海表面盐度(SSS)、海表面高度(SSH)及叶绿素浓度(Chl-a)等海洋环境数据,以外包络法建立基于作业努力量和CPUE的各环境变量适应性指数(SI)。以SST作为建立SI的基准因子,采用算术平均法构建栖息地综合适应性指数模型(HSI),并选择最优栖息地指数模型,以用于茎柔鱼渔场预报,并利用2013年智利外海茎柔鱼生产数据进行验证。结果表明,以SST和SSS为因变量构建的HSI模型为最佳,且基于作业努力量的HSI模型要好于基于CPUE的HSI模型。以作业努力量为SI指标、基于SST和SSS为因子的HSI模型能较好预报智利外海茎柔鱼渔场。     

北部湾二长棘犁齿鲷时空分布及其与环境因子的关系

【目的】研究北部湾二长棘犁齿鲷资源密度时空分布与海洋环境因子的关系,为二长棘犁齿鲷资源利用和保护提供理论基础。【方法】基于2013年11月至2014年8月4个航次的北部湾渔业资源调查航次数据,利用广义可加模型(GeneralizedAdditiveModel,GAM)研究二长棘犁齿鲷与遥感海表水温(SST)、叶绿素a浓度(Chl-a)、海表面异常(SLA)和水深等海洋环境因子,以及经纬度等空间因子的关系,利用渔场重心分析资源分布及迁移特征。【结果与结论】北部湾二长棘犁齿鲷资源密度春夏季高于秋冬季,以春季最高。GAM模型对资源密度偏差的总解释率为51.6%,影响资源密度最重要的因子为SST,贡献率为25.9%,其次为纬度、SLA和Chl-a,贡献率分别为11.3%、9.4%和5.0%。二长棘犁齿鲷资源密度分布重心为季节性移动,秋季到冬春季从北部湾西南海域向北部湾东北部海域迁移,夏季向西南方向折返。     

基于不同BP神经网络的西南大西洋阿根廷滑柔鱼渔场预报模型比较

根据2003-2011年渔汛期间我国鱿钓船在西南大西洋海域的生产统计数据,结合海洋遥感获得的海表温度(SST)和海面高度(SSH)等数据,以单位捕捞努力量渔获量(CPUE)和作业次数作为中心渔场指标,以月份、经度、纬度、SST和SSH为输入因子,利用BP神经网络方法构建西南大西洋阿根廷滑柔鱼中心渔场预报模型。比较14种不同结构的BP神经网络模型,以CPUE作为中心渔场预报指标的BP模型均较佳,其拟合残差范围为0.004 0~0.005 5,平均值为0.004 7;而以作业次数作为中心渔场预报指标的BP模型,其拟合残差范围为0.009 3~0.011 6,平均值为0.010 4。输入因子为月份、经度、纬度、SST和SSH,输出因子为初值化后的CPUE,网络结构为5-4-1时的BP神经网络模型为最佳,其拟合残差为0.004 025,该模型可用于阿根廷滑柔鱼中心渔场的预报。BP神经网络方法可为准确渔场预报提供新途径。     

西北太平洋澳洲鲐渔业生物学研究进展

【目的】为系统掌握澳洲鲐(Scomber australasicus)的基础生物学以及资源利用现状,并为后期研究提供理论基础。【方法】对西北太平洋澳洲鲐的种群结构、洄游、年龄与生长、繁殖摄食等生物学研究进展做了初步的总结和归纳。【结果】根据外部形态和遗传分析等研究结果,澳洲鲐可分为3个地理群系,即太平洋群系、东海群系和南海群系。不同海域澳洲鲐都有明显的洄游路径,受海流影响显著,但南海群系洄游模式尚不清楚。澳洲鲐为连续产卵类型,不同群体的初次性成熟有差异,其繁殖策略需要加强研究,特别是与环境因子的关系;耳石微结构估算认为,西北太平洋海域澳洲鲐最大年龄为6龄,各群系间的生长有差异;水温对产卵场影响较大,渔场分布受到黑潮等海流影响明显。资源量的评估及其管理策略分析仍没有有效开展,仅仅局限在一个国家和地区。【结论】为合理开发和利用澳洲鲐资源,需加强各国和地区之间的合作,系统地开展西北太平洋海域澳洲鲐资源的调查和生物学研究,选择适合澳洲鲐生活史特征的资源评估模型,为该种类的可持续利用和科学管理提供理论支持。     

毛里塔尼亚海域底拖网头足类渔场与环境因子的关系研究

根据2010—2015年上海某远洋渔业公司在毛里塔尼亚的生产统计数据,结合卫星遥感资料,研究毛里塔尼亚海域底拖网头足类渔场与表温(SST)、海面高度距平均值(SSHA)、水深等海洋环境因子的关系。结果表明,头足类渔场分布与SST、SSHA、水深等因子关系密切,各月作业渔场的适宜环境范围有一定的差异;作业渔场分布在SST为15~28℃的海域,最适SST范围为16~22℃;作业渔场分布在SSHA为-50~10 cm的海域,最适SSHA范围为-20~-40 cm和-10~10 cm;作业渔场分布水深为10~90 m的海域,最适水深为50~70 m。     

东、黄海鲐鱼群体遗传差异的RAPD分析

利用随机扩增多态DNA(RAPD)技术分别分析了五岛西部日本鲐、东海西部日本鲐和澳洲鲐三群体的样本,共产生226个分子标记,其中143个为多态性标记,多态百分率达到63.3%,每条引物产生的平均标记数为7.29。五岛西部日本鲐、东海西部日本鲐和澳洲鲐群体内遗传相似度分别为0.949、0.877和0.936,而群体间遗传距离依次为:五岛西部日本鲐-东海西部日本鲐(0.2357)<东海西部日本鲐-澳洲鲐(0.3030)<五岛西部日本鲐-澳洲鲐(0.3528),五岛西部日本鲐与东海西部日本鲐个体在UPGMA系统树独立聚类为两个类群,初步支持东、黄海的日本鲐存在东海西部和五岛西部的两个种群的观点。Shannon多样性指数表明,其遗传多样性大小依次为东海西部日本鲐、澳洲鲐、五岛西部日本鲐。     

Wind stress field over the Bohai Sea,the Yellow Sea and the East China Sea

Seasonal and annual with stress fields over the Bohai Sea, the Yellow Sea and the East China Sea were computed from the wind rose data compiled in the Climatic Atlas of Chinese Offshore Areas and North-west Pacific and published by the Ocean Press in 1982. 684 wind roses in 2° latitude by 2° longitude boxes constructed from 278,815 wind reports are involved in the present study. The computations are principally intended as a data source for further research. Some oceanographic consequences are expounded on.     

The suspended sediment concentration distribution in the Bohai Sea, Yellow Sea and East China Sea

The distribution of the suspended sediment concentration (SSC) in the Bohai Sea, Yellow Sea and East China Sea (BYECS) is studied based on the observed turbidity data and model simulation results. The observed turbidity results show that (i) the highest SSC is found in the coastal areas while in the outer shelf sea areas turbid water is much more difficult to observe, (ii) the surface layer SSC is much lower than the bottom layer SSC and (iii) the winter SSC is higher than the summer SSC. The Regional Ocean Modeling System (ROMS) is used to simulate the SSC distribution in the BYECS. A comparison between the modeled SSC and the observed SSC in the BYECS shows that the modeled SSC can reproduce the principal features of the SSC distribution in the BYECS. The dynamic mechanisms of the sediment erosion and transport processes are studied based on the modeled results. The horizontal distribution of the SSC in the BYECS is mainly determined by the current-wave induced bottom stress and the fine-grain sediment distribution. The current-induced bottom stress is much higher than the wave-induced bottom stress, which means the tidal currents play a more significant role in the sediment resuspension than the wind waves. The vertical mixing strength is studied based on the mixed layer depth and the turbulent kinetic energy distribution in the BYECS. The strong winter time vertical mixing, which is mainly caused by the strong wind stress and surface cooling, leads to high surface layer SSC in winter. High surface layer SSC in summer is restricted in the coastal areas.     

Distribution of Different Biogeographical Tintinnids in Yellow Sea and Bohai Sea

There were different biogeographical tintinnids in the oceans. Knowledge of their distribution pattern and mixing was important to the understanding of ecosystem functions. Yellow Sea (YS) and Bohai Sea (BS) were semi-enclosed seas influenced by warm water intrusion and YS cold bottom water. The occurrence of tintinnids in YS and BS during two cruises (summer and winter) were investigated to find out: i) whether warm-water tintinnids appeared in YS and BS; ii) whether boreal tintinnids appeared in high summer; iii) the core area of neritic tintinnids and iv) how these different biogeographical tintinnids mixed. Our results showed that tintinnid community was dominated by neritic tintinnid. We confirmed the occurrence of warm-water tintinnids in summer and winter. In summer, they intruded into BS and mainly distributed in the upper 20 m where Yellow Sea Surface Warm Water (YSSWW) developed. In winter, they were limited in the surface water of central deep region (bottom depth >50 m) of YS where were affected by Yellow Sea Warm Water (YSWW). Boreal tintinnids occurred in YS in high summer (August) and in winter, while they were not observed in BS. In summer, the highest abundance of boreal tintinnids occurred in Yellow Sea Bottom Cold Water, indicating the presence of an oversummering stock. In winter, they were concentrated in the north of YSWW. Vertically, neritic tintinnids abundance was high in the bottom layers. Horizontally, high neritic tintinnids abundance in bottom layers occurred along the 50 m isobath coinciding with the position of front systems. Front systems were the core distribution area of neritic tintinnids. High abundance areas of warm-water and boreal tintinnids were clearly separated vertically in summer, and horizontally in winter. High abundance of neritic tintinnids rarely overlapped with that of warm-water or boreal tintinnids.     

Evaluation and fusion of SST data from MTSAT and TMI in East China Sea, Yellow Sea and Bohai Sea in 2008

Two typical satellite sea surface temperature (SST) datasets, from the Multi-functional Transport Satellite (MTSAT) and Tropical Rainfall Measuring Mission Microwave Imager (TMI), were evaluated for the East China Sea, Yellow Sea, and Bohai Sea throughout 2008. Most monthly-mean availabilities of MTSAT are higher than those of TMI, whereas the seasonal variation of the latter is less than that of the former. The analysis on the one-year data shows that the annual mean availability of MTSAT (61%) is greater than that of TMI (56%). This is mainly because MTSAT is a geostationary satellite, which achieves longer observation than the sun-synchronous TMI. The daily availability of TMI (28%-75%) is more constant than that of MTSAT (9%-93%). The signal of infrared sensors on MTSAT is easily disturbed on cloudy days. In contrast, the TMI microwave sensor can obtain information through clouds. Based on in-situ SSTs, the SST accuracy of TMI is superior to that of MTSAT. In 2008, the root mean square (RMS) error of TMI and MTSAT were 0.77 K and 0.84 K, respectively. The annual mean biases were 0.14 K (TMI) and -0.31 K (MTSAT). To attain a high availability of SSTs, we propose a fusion method to merge both SSTs. The annual mean availability of fusion SSTs increases 17% compared to MTSAT. In addition, the availabilities of the fusion SSTs become more constant. The annual mean RMS and bias of fusion SSTs (0.78 K and -0.06 K, respectively) are better than those of MTSAT (0.84 K and -0.31 K).     

南海周边国家的海洋划界立法与实践

介绍了南海周边国家根据1982年《联合国海洋法公约》精神颁布的海洋法律,并叙述了这些国家的管辖区域主张以及与海洋划界有关的领海基线和基点等方面的问题。指出:南海周边国家之间若要划出专属经济区和大陆架边界线,包括我国在内的所有周边国家政府都应当修正不适宜的划界主张,并在划界原则、理论和方法上趋向一致,为早日划好边界,促进南海地区的经济发展和和平稳定而努力。     

A THREE-DIMENSIONAL THERMOCLINE MODEL FOR THE YELLOW SEA AND NORTHERN EAST CHINA SEA

A time-dependent, three-dimensional finite difference model is presented for simulating the stratifiedYellow Sea and northem East China Sea. The mode is forced by time-dependent observed wind, surfaceflux of heat, and tidal turbulence. With this model, momentum and temperature distribution can be computed,and an approximation for the sub-grid scale effects is introduced by the use of mass and momentumexchange coefficients. The vertical exchanges are quite dependent on these assumed coefficents, whichare complicated functions of the turbulence energy of tide and wind, of the stratified strength and otherfactors. This model was applied to describe the mechanics of the variations in strength and thickness ofthe thermocline covering almost the whole Yellow Sea and northern East Chna Sea in summer. Comparisonsof the computed output with obtained survey data led to some important conclusions.     

Spatial distribution of dimethylsulfide and dimethylsulfoniopropionate in the Yellow Sea and Bohai Sea during summer

Abstrac t The distributions of dimethylsulfide(DMS) and its precursor dimethylsulfoniopropionate(DMSP) in surface water of the Yellow Sea and the Bohai Sea were studied during June 2011. The mean concentrations and ranges of DMS, dissolved DMSP(DMSPd), and particulate DMSP(DMSPp) in surface waters were 6.85(1.60–12.36), 7.25(2.28–19.05) and 61.87(6.28–224.01) nmol/L, respectively. There were strong correlations between DMSPp and chlorophyll a in the Bohai Sea and the North Yellow Sea, respectively, and concentrations of DMS and DMSP were high, with a relatively high proportion of dinoflagellates, in the region of the South Yellow Sea Cold Water Mass. Results show that phytoplankton biomass and species composition were important factors that controlled the distribution of DMS and DMSP. Complex environmental factors, including nutrients, transparency, and terrestrial runoff, might also influence the variability in DMS and DMSP. Biological production and consumption rates of DMS in the Bohai Sea were higher than those in the Yellow Sea. DMS production rates were closely correlated with DMSPd concentrations. DMS and DMSP exhibited obvious diel variations, with high concentrations occurring in the late afternoon(16:00–19:00) and low concentrations occurring during the night, implying that the intensity of solar radiation had a significant influence on these variations. Size distributions of chlorophyll a and DMSPp were also investigated and large nanoplankton(5–20 μm), mainly diatoms, contributed significantly to chlorophyll a and DMSPp at most stations. The average sea-to-air flux of DMS in the study area was estimated to be 11.07 μmol/(m2 ·d) during the summer.     

The Structure and Formation Mechanism of a Sea Fog Event over the Yellow Sea

In this paper, a heavy sea fog event occurring over the Yellow Sea on 11 April 2004 was investigated based upon observational and modeling analyses. From the observational analyses, this sea fog event is a typical advection cooling case. Sea surface temperature(SST) and specific humidity(SH) show strong gradients from south to north, in which warm water is located in the south and consequently, moisture is larger in the south than in the north due to evaporation processes. After fog formation, evaporation process provides more moisture into the air and further contributes to fog evolution. The sea fog event was reproduced by the Regional Atmospheric Modeling System(RAMS) reasonably. The roles of important physical processes such as radiation, turbulence as well as atmospheric stratification in sea fog’s structure and its formation mechanisms were analyzed using the model results. The roles of long wave radiation cooling, turbulence as well as atmospheric stratification were analyzed based on the modeling results. It is found that the long wave radiative cooling at the fog top plays an important role in cooling down the fog layer through turbulence mixing. The fog top cooling can overpower warming from the surface. Sea fog develops upward with the aid of turbulence. The buoyancy term, i.e., the unstable layer, contributes to the generation of TKE in the fog region. However, the temperature inversion layer prevents fog from growing upward.     

Recent observations and modeling study about sea fog over the Yellow Sea and East China Sea

This review presents some of the latest achievements in sea fog research,including fog climatology,fog structure in the marine atmospheric boundary layer,and numerical simulations and forecasting of fog.With the development of atmospheric observational techniques and equipments,new facts about sea fog are revealed.The mechanisms involved in the formation,development and dissipation of sea fog are further explored with the help of advanced atmospheric models.