Trophic organisation and predator–prey interactions among commercially exploited demersal finfishes in the coastal waters of the southeastern Arabian Sea

Trophic interactions in commercially exploited demersal finfishes in the southeastern Arabian Sea of India were studied to understand trophic organization with emphasis on ontogenic diet shifts within the marine food web. In total, the contents of 4716 stomachs were examined from which 78 prey items were identified. Crustaceans and fishes were the major prey groups to most of the fishes. Based on cluster analysis of predator feeding similarities and ontogenic diet shift within each predator, four major trophic guilds and many sub-guilds were identified. The first guild ‘detritus feeders’ included all size groups of Cynoglossus macrostomus, Pampus argenteus, Leiognathus bindus and Priacanthus hamrur. Guild two, named ‘Shrimp feeders’, was the largest guild identified and included all size groups of Rhynchobatus djiddensis and Nemipterus mesoprion, medium and large Nemipterus japonicus, P. hamrur and Grammoplites suppositus, small and medium Otolithes cuvieri and small Lactarius lactarius. Guild three, named ‘crab and squilla feeders’, consisted of few predators. The fourth trophic guild, ‘piscivores’, was mainly made up of larger size groups of all predators and all size groups of Pseudorhombus arsius and Carcharhinus limbatus. The mean diet breadth and mean trophic level showed strong correlation with ontogenic diet shift. The mean trophic level varied from 2.2 ± 0.1 in large L. bindus to 4.6 ± 0.2 in large Epinephelus diacanthus and the diet breadth from 1.4 ± 0.3 in medium P. argenteus to 8.3 ± 0.2 in medium N. japonicus. Overall, the present study showed that predators in the ecosystem have a strong feeding preference for the sergestid shrimp Acetes indicus, penaeid shrimps, epibenthic crabs and detritus.     

基于融合U-Net及ConvLSTM的海面高度异常预报方法研究

海面高度异常是反映海洋环境状况的主要变量之一。本文使用1993—2019年的融合月均海面高度异常数据,建立了基于深度学习的海面高度异常预测神经网络模型,提出了基于融合U型网络(U-Net)和卷积长短记忆网络(ConvLSTM)的中长期海面高度异常预报模型。在研究海域0.25°×0.25°的空间分辨率下,模型测试集预报结果的均方根误差和平均绝对误差分别为0.039 m和0.027 m,均优于全连接LSTM预报模型和ConvLSTM+CNN预报模型,为大中尺度的海面高度异常预报提供了新的方法。     

北冰洋高纬度区域海冰及气象特征分析

基于2018年8月至2019年5月布放在北极随海冰漂流的自动气象站和温度链浮标获取的观测数据,分析了北极高纬度区域的大气特征和海冰生消过程。根据海冰的漂移轨迹分为两个阶段分析,第1阶段,海冰主要向东南漂移;第2阶段,海冰主要向东北漂移。第1阶段观测的平均气温和平均相对湿度分别为–6.6℃和93%,第2阶段观测的平均气温和平均相对湿度分别为–29.3℃和76%,第2阶段平均气压高于第1阶段。海冰的漂移轨迹主要受到波弗特高压外围气流的影响。利用自动气象站漂移轨迹计算得到海冰漂移速度,与美国国家冰雪数据中心海冰漂移速度比较显示,两者纬向速度更为接近。海冰在第1阶段以融化为主,海冰厚度略有减小,8月份海冰生长率为–0.11 cm/d;海冰的生长过程主要发生在第2阶段,1–3月生长率均超过0.9 cm/d,2019年3月海冰生长最快,平均生长率为1.3 cm/d,海冰的增长一直持续至观测结束。     

海泥环境中阴极保护的边界元计算

根据阴极保护的特点,建立了用于数值计算的模型;采用边界元方法对海泥介质中的阴极保护系统进行了计算,获得了海泥中钢管表面以及海泥介质内部的电位分布。将计算的结果与测量的数据进行比较,两者具有较好的一致性。     

复杂结构形式的海堤波浪力及波浪形态数值模拟

依据雷诺方程和k-ε紊流模型,按流体体积(VOF)法追踪波浪自由表面,采用源造波法,建立数值波浪水槽,数值模拟波浪对复杂结构形式海堤的作用.数值模拟结果与经验公式、物理模型试验结果基本符合,说明所建立的数值波浪水槽合理可行.揭示了不规则波作用下复杂结构形式海堤波浪力分布规律,模拟了堤前波浪形态变化,为探讨合理的海堤结构形式提供了依据.     

平面无结节网衣水阻力系数的试验研究

通过物理模型试验,统计分析得到了无结节网衣的水阻力系数在不同状态下随雷诺数、倾角和布置状态的变化规律,并通过网衣沉子的组合试验验证了所得经验公式的正确性和适用性,为深水网箱等渔具的水动力计算提供了依据.     

山东省近50年海洋气象灾害特征分析

本文通过大量的文献和资料查阅,系统的统计分析了近50a山东省沿海及责任海区海雾、风暴潮、风暴海浪、海冰等几种主要海洋气象灾害的海洋、气象及分布特征和灾害情况,进一步分析了它们的变化规律和产生原因,为海洋气象业务、服务、科研提供有益的参考。     

海浪数值模式研究回顾与进展

本文简单介绍了海浪的生成、发展理论,以及海浪数值模式的分类;回顾总结了国内外在海浪数值模式研究方面取得的成果。     

棉粕蛋白酶解物对异育银鲫(Carassius auratus gibelio)消化、生长和胰蛋白酶mRNA表达量的影响

以棉粕蛋白为酶解底物,用枯草杆菌蛋白酶对其进行酶解,以酶解产物1.5%和3.0%两个梯度等量替代鱼饲料配方中棉粕,在室内流水养殖系统中喂养异育银鲫鱼种[体重为(30±2)g]65天。测定鱼的生长、营养物质表观消化率、消化蛋白酶活性及肝胰脏中胰蛋白酶mRNA表达水平等指标。结果表明,添加1.5%和3.0%棉粕酶解产物的鱼在饲养35天后的特定增长率(SGR)分别比对照组高32.5%和56.7%,且差异显著(P<0.05);在饲养65天后,两组特定增长率分别比对照组高8.0%和21.0%,且差异极显著(P<0.01),肝胰脏中胰蛋白酶mRNA表达水平也随棉粕酶解产物添加梯度提高而相应提高,表明鱼的生长与消化蛋白酶mRNA表达水平相关。同时棉粕蛋白酶解物对肠道蛋白酶的活性和营养物质表观消化率都有促进作用,而棉粕蛋白酶解物对鱼肌肉成分并没有改变,这也表明棉粕蛋白酶解物在促进鱼生长、内源酶活性同时并未降低鱼的品质。     

Evidence That Sea State Bias is Different for Ascending and Descending Tracks

Jason-1 and TOPEX/Poseidon (T/P) measured sea-surface heights (SSHs) are compared for five regions during the verification tandem phase. The five regions are of similar latitude and spatial extent and include the Gulf of Mexico, Arabian Sea, Bay of Bengal, and locations in the Pacific and Atlantic Oceans away from land. In all five regions, a bias, defined as Jason SSH—TOPEX-B SSH, exists that is different for ascending and descending tracks. For example, in the Gulf of Mexico the bias for ascending tracks was ?0.13 cm and the bias for descending tracks was 2.19 cm. In the Arabian Sea the bias for ascending tracks was ?2.45 cm and the bias for descending tracks was ?1.31 cm. The bias was found to depend on track orientation and significant wave height (SWH), indicating an error in the sea state bias (SSB) model for one or both altimeters. The bias in all five regions can be significantly reduced by calculating separate corrections for ascending and descending tracks in each region as a function of SWH. The correction is calculated by fitting a second-order polynomial to the bias as a function of SWH separately for ascending and descending tracks. An additional constraint is required to properly apply the correction, and we chose to minimize the sum of the TOPEX-B and Jason-1 root-mean-square (rms) crossover differences to be consistent with present SSB models. Application of this constraint shows that the correction, though consistent within each region, is different for each region and that each satellite contributes to the bias. One potential source that may account for a portion of the difference in bias is the leakage in the wave forms in TOPEX-B due to differing altitude rates for ascending and descending tracks. Global SSB models could be improved by separating the tracks into ascenders and descenders and calculating a separate SSB model for each track.