小球藻对不同盐度海水养殖尾水的净化效果研究

微藻处理养殖尾水已成为热点研究方向,有关一定盐度范围内海水养殖尾水的微藻处理研究较少。本试验调配了两种盐度(16和26)的海水养殖尾水,以空白组作对照,设置小球藻(Chlorella salina)初始接种密度梯度(5×10⁵、1×10⁶、2×10⁶和3×10⁶个/mL),研究小球藻对海水养殖尾水中不同形态氮和磷的去除效果。结果表明,小球藻在海水养殖尾水中生长良好,可有效去除尾水中的氮磷营养盐,16盐度组中各初始藻密度组对NH₄⁺、NO₃^-和总溶解态氮(total dissolved nitrogen,TDN)的去除率分别为85.03%~85.87%、60.87%~63.70%和54.53%~57.64%,组间无显著差异(P>0.05);26盐度组中除5×10⁵组外,其余藻密度组对NH₄⁺、NO₃^-和TDN的去除率分别为87.23%~88.16%、56.70%~57.79%和53.31%~54.62%,且组间无显著差异(P>0.05),表明小球藻初始接种密度对尾水中氮盐的去除无显著影响。除5×10⁵个/mL组外,16与26盐度组中对TDN的去除率无显著差异,表明盐度变化对氮的去除无影响。随着初始藻密度的升高,16和26处理组对总溶解态磷(total dissolved phosphorus,TDP)的去除率均上升,分别为76.13%~99.53%和63.72%~96.83%,表明藻初始接种密度的升高可促进尾水中磷的去除,且盐度升高没有影响小球藻对磷的去除。本研究获得了不同初始接种密度小球藻对一定盐度范围的海水养殖尾水的吸收利用特点,可为海水养殖尾水的生态化处理提供一定的理论基础。     

增殖放流影响下东海北部海域三疣梭子蟹(Portunus trituberculatus)最大可持续产量评估

当渔业资源出现衰退时,加强资源增殖放流以养护渔业资源、提高渔业产量对于渔业资源可持续利用具有重要意义;与此同时,增殖放流的实施会对基于资源开发与管理的评估的结果产生影响。基于2001~2015年间东海北部海域三疣梭子蟹(Portunus trituberculatus)渔业数据,采用增殖剩余产量模型,对东海北部海域三疣梭子蟹的最大可持续产量(MSY)及取得MSY时所需捕捞努力量(E_MSY)和原存生物量(B_MSY)进行了评估,并与传统Schaefer模型评估结果进行了比较。结果表明,当年增殖放流量约在3×10⁶~95×10⁶尾之间时,三疣梭子蟹年产量逐渐增加, MSY在14.2×10⁴ t和14.6×10⁴ t之间, E_MSY基本在15×10⁴吨位左右。增殖放流量增加,其对应的MSY也越高,能承受的E_MSY也越高(从15×10⁴~15.4×10⁴吨位之间),相反B_MSY则减小(从188.4×10⁴ t降至186.6×10⁴ t)。与传统的Schaefer模型评估结果相比,增殖剩余产量模型由于考虑了增殖放流生物量的因素,得到了MSY和E_MSY有所增加,而B_MSY有所下降的结论。研究结果有望为该研究海域三疣梭子蟹可持续地捕捞、放流与管理提供科学依据。     

The Luzon Strait transport variations during 1997～2000

Based on the output data from 1997 to 2000 obtained by the MITgcm's (general circulation model) adjoint assimilation method, volume, heat and salt transports through the Luzon Strait are calculated. The results indicate that there are obvious different characteristics between 1997 and 1998～2000 on the transports through the Luzon Strait. During 1997, theLuzon Strait had a mean net westward transport of 3.93×10⁶ m³/s with a maximum transport of 7.34×10⁶ m³/s in October. During 1998～2000, the Luzon Strait possessed an annual mean eastward transport of 0.93×10⁶, 1.80×10⁶ and 1.00×10⁶ m³/s respectively with a maximum eastward transport of 4.10×10⁶/3.31×10⁶ m³/s in July 1998/1999 and 2.06×10⁶ m³/s in April 2000, respectively. Moreover, the transports in 1997 indicated a difference from the other years, i.e.,that the ranges of westward inflows expanded more obviously to north of the Luzon Strait and downwards exceedingthose of the other years. The westward inflows expanded horizontally to the north part of the Luzon Strait until 21°N.     

獐子岛海域和胶州湾表层微微型浮游植物丰度和生物量的季节变化比较

为全面了解黄海典型海区微微型浮游植物的季节变化特征,于2009年7月至2010年6月在北黄海獐子岛海域和2010年1~12月在南黄海胶州湾进行逐月调查采样,利用流式细胞仪检测了表层海水中微微型浮游植物(picophytoplankton)的丰度,包括聚球藻(Synechococcus,SYN)和微微型真核浮游植物(picoeukaryotes,PEUK),并分析了其与环境因子的关系。獐子岛海域和胶州湾SYN和PEUK全年广泛分布,獐子岛海域SYN丰度范围在0.05×10³~120.00×10³cells/mL之间,丰度在秋季最高;胶州湾SYN丰度范围在0.02×10³~61.80×10³cells/mL之间,丰度在夏季最高。獐子岛海域PEUK丰度范围在0.01×10³~18.76×10³cells/mL之间,丰度在秋季最高;胶州湾PEUK丰度范围在0.25×10³~95.57×10³ cells/mL之间,丰度在春季最高。獐子岛海域微微型浮游植物丰度组成以SYN为主;而胶州湾以PEUK为主。PEUK是两海区微微型浮游植物生物量的主要贡献者。相关性分析结果表明,温度是影响两海区SYN丰度季节变化的最主要因素;影响PEUK季节分布的因素不完全一致,獐子岛海域PEUK丰度主要受温度调控;胶州湾PEUK丰度主要受温度和营养盐浓度影响。与已有研究比较,这两个海区的微微型浮游植物生物量对浮游植物生物量的贡献明显高于其他温带沿岸海域,预示微微型浮游植物在獐子岛海域和胶州湾生态系统中的重要作用,值得进一步深入研究。     

哈维氏弧菌浸泡感染下泥蚶(Tegillarca granosa)不同组织弧菌载量的变化规律分析

为明确哈维氏弧菌感染下,泥蚶（Tegillarca granosa）不同组织弧菌载量的变化规律,通过哈维氏弧菌浸泡感染泥蚶的方法,建立弧菌浓度计数标准曲线,记录攻毒水体和泥蚶组织中的哈维氏弧菌含量的动态变化及相关关系。结果显示,弧菌感染浓度为1×10⁷CFU/mL,泥蚶血液中弧菌载量显著高于鳃、闭壳肌、外套膜和肝胰腺,各组织中的弧菌载量呈现先上升,后下降,最后维持较低水平的变化规律。持续感染6 d,泥蚶血液中弧菌载量降至10²-10⁴ CFU/mL,其他组织中弧菌载量降至10⁰-10² CFU/mg。检测不同浓度弧菌（1×10⁵,1×10⁶,1×10⁷,5×10⁷ CFU/mL）浸泡感染后泥蚶肝胰腺的弧菌载量变化,结果显示,1 d时各感染组肝胰腺弧菌载量均较对照组显著增加（81.0-667.8倍）,且与浸泡水体中弧菌浓度呈显著正相关（Spearman''s ρ=0.762,P<0.001）,5 d时各侵染组肝胰腺弧菌载量均较1 d明显降低,但仍然高于对照组。研究结果为泥蚶感染弧菌发病过程中,免疫识别及免疫响应机制的研究提供了参考。     

A remote sensing environmental study of Haiko Bay——Ⅰ Tidal influx and its changes

Through the water areas extracted from remote sensing images and the combination of the methods for establishing the formula for calculating tidal influx with tidal data, the tidal influx of the Haikou Bay, Hainan Province was found to be 5.14×10⁷m³ in 1990, 5.80×10⁷m³ in 1984 and 5.05×10⁷m³ in 1965, respectively.After the analysis of the morphological and tidal range factors which determine tidal influx, this paper presents the trend of the changes in tidal influx caused by the changes in the morphological factors of the Haikou Bay.It is found that a decreasing trend was shown with a depressive rate of 2×10^-3during the period from 1965 to 1984, and an increasing trend with an incremental rate of 1×10^-3 during the period of 1984-1990.The main reason for the appearance of the decreasing trend before 1984 is the natural deposition and silting-up of the bay sediments; after 1984, the dredging and expansion of the Haikou Port and the Haikou New Port which caused an increase in water area at the mean low tide are the leading factor which causes the increase in tidal influx.     

基于海洋气候数据集的区域海平面变化非线性预测

本文基于中国首套长时间序列、高精度、高时空一致性的全球海洋气候数据集产品, 利用1993年1月至2015年12月的山东半岛近海海平面异常数据, 构建了基于集合经验模式分解(EEMD)和长短期记忆神经网络(LSTM)的海平面非线性变化组合预测模型。EEMD可以得到海平面异常的各周期项、线性趋势及残差部分, LSTM模型可对其进行逐个预测并重构得到最终的海平面异常预测结果。EEMD-LSTM组合模型海平面异常预测的均方根误差仅为25.87 mm, 取得了令人满意的效果。基于该组合模型预测2016-2025年山东半岛近海海平面上升速率将达到3.54 mm·a^-1。     

2012年南海西北陆架冬季水文特征的观测分析

本文基于2012年12月南海西北部陆架海区的温盐和流速实测资料,分析了粤西和琼东陆架海区冬季三维温、盐结构和流场特征,给出沿陆架和跨陆架方向的水体和热盐通量。结果表明：（1）在50m以浅,粤西和琼东海区温度均由近岸向外海递增,深层则相反;冬季近岸海区混合层较深,外海密度跃层位于60—120m深度且层结较强,浮力频率大于10^–2/s;（2）海流大致沿等深线向西南流动,30m以深流速大小在0.03—0.40m/s之间,且随着深度增加而略有减小;琼东海区100m等深线附近在60m以浅水层观测到水体辐聚并有明显温度锋面存在;（3）沿陆架方向的水体和热盐输送均大于跨陆架方向,其中粤西单位面积沿/跨陆架水体通量平均值为0.13×10^–6/0.03×10^–6Sv/m²,低于琼东海区的0.91×10^–6/0.56×10^–6Sv/m²。     

A potential source of recruitment of Acartia pacifica nauplii: viable benthic resting eggs

Many estuarine and coastal planktonic copepods depend on the hatching of benthic resting eggs for recruitment of nauplii to the water column population. The distribution and abundance of viable resting eggs of Acartia pacifica in the Xiamen Bay were determined by the presence of nauplii in the laboratory. The number of viable eggs varied temporally and spatially. The maximum number (9.2×10⁴m^-2) of viable eggs was in summer. In spring the average abundance of viable eggs was 5.6×10⁴ m^-2. The abundances of viable eggs in fall and winter were similar, respectively 2.7×10⁴ and 3.3×10⁴ m^-2, which were the lowest in the year. The numbers of viable eggs inside the stations of the Xiamen Bay were higher than those outside the stations. The viable eggs were found at all depths (0～10 cm),although not in every station. The maximin number did not necessarily occur in the uppermost centimeter of the sediments but often occurred several centimeters below the water-sediment interface. The accumulation of viable eggs in the seabed of a subtropical bay constitutes a potential source of recruitment of nauplii into the pelagic population.     

Incorporation rate measurements of <Superscript>10</Superscript>Be, <Superscript>230</Superscript>Th, <Superscript>231</Superscript>Pa,and <Superscript>239,240</Superscript>Pu radionuclides in manganese crust in the Pacific Ocean: A search for extraterrestrial material

In order to estimate the deposition rate of extraterrestrial material onto a manganese crust in a search for supernova debris, we analyzed the contents of ¹⁰Be, ²³⁰Th, ²³¹Pa, and ^239,240Pu in a sample of manganese crust collected from the North Pacific Ocean. On the basis of the depth profile of ¹⁰Be, the growth rate of the manganese crust was determined to be 2.3 mm Myr⁻¹. The uptake rates of ¹⁰Be, ²³⁰Th, and ²³¹Pa onto the manganese crust were estimated to be 0.22–0.44%, 0.11–0.73%, and 1.4–4.5%, respectively, as compared to the deposition rates onto the deep-sea sediments near the sampling station, while that for ^239,240Pu was 0.14% as compared to the total inventory of seawater and sediment column. Assuming that sinking particles represent 0.11–4.5% of the uptake rates, the deposition rate of extraterrestrial material onto the manganese crust was estimated to be 2–800 μg cm⁻²Myr⁻¹ according to the uptake of ¹⁰Be onto the manganese crust. Further, our estimate is similar to the value of 9–90 μg cm^{− 2}Myr⁻¹ obtained using the integrated global production rate of ¹⁰Be and the deposition rate of ¹⁰Be onto the manganese crust.     

基于小波变换和LSTM神经网络的格陵兰岛近海海域海平面变化预测

海平面变化包含多种不同时间尺度信息，传统的预测方法仅对海平面变化趋势项、周期项进行拟合，难以利用海平面变化的不同时间尺度信号，使得预测精度不高。本文基于深度学习的预测模型，提出一种融合小波变换（wavelet transform，WT）与LSTM （long short-term memory，LSTM）神经网络的海平面异常组合预测模型。首先利用小波分解得到反映海平面变化总体趋势的低频分量和刻画主要细节信息的高频分量；然后通过LSTM神经网络对代表不同时间尺度的各个分量预测和重构，实现海平面变化的非线性预测。基于该模型的海平面变化预测的均方根误差、平均绝对误差和相关系数分别为12.76 mm、9.94 mm和0.937，预测精度均优于LSTM和EEMD-LSTM预测模型，WT-LSTM组合模型对区域海平面变化预测具有较好的应用价值。     

Multi-step ahead short-term predictions of storm surge level using CNN and LSTM network

Storm surges pose significant danger and havoc to the coastal residents' safety, property, and lives, particularly at offshore locations with shallow water levels. Predictions of storm surges with hours of warning time are important for evacuation measures in low-lying regions and coastal management plans. In addition to experienced predictions and numerical models, artificial intelligence (AI) techniques are also being used widely for short-term storm surge prediction owing to their merits in good level of prediction accuracy and rapid computations. Convolutional neural network (CNN) and long short-term memory (LSTM) are two of the most important models among AI techniques. However, they have been scarcely utilised for surge level (SL) forecasting, and combinations of the two models are even rarer. This study applied CNN and LSTM both individually and in combination towards multi-step ahead short-term storm surge level prediction using observed SL and wind information. The architectures of the CNN, LSTM, and two sequential techniques of combining the models (LSTM–CNN and CNN–LSTM) were constructed via a trial-and-error approach and knowledge obtained from previous studies. As a case study, 11 a of hourly observed SL and wind data of the Xiuying Station, Hainan Province, China, were organised as inputs for training to verify the feasibility and superiority of the proposed models. The results show that CNN and LSTM had evident advantages over support vector regression (SVR) and multilayer perceptron (MLP), and the combined models outperformed the individual models (CNN and LSTM), mostly by 4％–6％. However, on comparing the model computed predictions during two severe typhoons that resulted in extreme storm surges, the accuracy was found to improve by over 10％ at all forecasting steps.     

预测有效波高的深度学习模型研究

研究基于RNN、LSTM、GRU深度学习模型,针对NOAA浮标数据集中的44013、44014、44017浮标的数据,通过斯皮尔曼相关性分析提高模型预测效果。实验结果表明,在进行相关性分析后,S-RNN、S-LSTM、 S-GRU的预测效果均比原始RNN、LSTM、GRU模型预测效果好。此外,提出一种基于LSTM的LSTM-Attention 波高预测模型,并进行相关实验,量化LSTM-Attention模型的预测效果,实验结果表明LSTM-Attention模型有更好的预测效果。为评估模型的泛化能力,研究还提出了一种采用邻近浮标数据进行学习,预测浮标缺失数据的方 法。实验结果表明,该方法的预测精度可以达到97.93%。本研究为海浪预测提供了新的方法和思路,也为未来深 度学习模型在海浪预测中的应用提供了参考。     

我国对虾养殖净收益影响因素分析

海水养殖是海洋经济重要的组成部分。中国是世界上最大的对虾养殖国,对虾养殖净收益直接影响对虾养殖户的生产积极性,进而影响对虾养殖产业持续稳定健康发展。文章以山东省、江苏省和广东省对虾养殖户的调查数据为依据,运用多元线性回归模型,对对虾养殖净收益的影响因素进行实证分析。结果表明,影响对虾养殖净收益的3个主要因素是:①每年对虾养殖的造数;②是否参加对虾养殖农业合作社;③对虾出塘的销售价格。对虾养殖者的年龄,受教育程度,是否混养其他品种生物,养殖模式,养殖面积对对虾养殖净收益影响不显著。基于回归结果,笔者提出完善对虾养殖基础设施;发展对虾养殖农业合作社和养殖协会;建立稳定的对虾市场价格调控体系等政策建议。     

瑞利参数在海浪波高机器学习预测中的应用

海浪直接影响海上活动和航行安全,同时也蕴藏着巨大的可再生能源,对海浪核心参数之一波高预测至关重要。基于2015年7月～2022年6月山东小麦岛(36°N,120.6°E)站点实测的波高数据,利用反向传播神经网络(back-propagation neural network,BPNN)、长短记忆网络(long short-term memory, LSTM)和支持向量机回归(support vector regression, SVR)三种机器学习模型对波高进行预测,并分析了瑞利参数的引入对预测结果的影响。结果显示,模型输入项引入瑞利参数后,对1 h和6 h波高预测提升效果有限,预测值与测试集的相关性提升不超过0.02,均方根误差的降低不超过0.01 m;在12h和24h的预测中,BPNN和LSTM模型预测结果相关性提升0.03～0.07,均方根误差降低0.02～0.03m,而SVR模型预测结果变化不显著。说明瑞利参数有助改善BPNN和LSTM模型中长期海浪预报。此外,特征扰动方法(机器学习中特征重要性的计算方法之一)验证了瑞利参数在波高预测中的重要性,瑞利参数的引入为波高的机器学习预...     

基于LSTM的海洋表面短期风速预测研究

为实现对海面风速精确的短期预测,提出了一种基于长短期记忆(LSTM,longshort-termmemory)神经网络的短期风速预测模型,选取OceanSITES数据库中单个浮标站点采集的风速历史数据作为模型输入,经过训练设置最佳参数等步骤,实现了以LSTM方法,对该站点所在海区海面风速在各季节性代表月份海面风速的24 h短期预测。同时通过不同预测时长的实验以及与BP(back propagation)神经网络神经网络和径向基函数神经网络(radialbasisfunctionneuralnetwork,RBF)的预测效果对比实验,证明了LSTM预测方法相比上述两种神经网络预测方法,在海表面风速预测应用中的优越性。最后通过多个海域对应的站点风速数据预测实验,证明了LSTM神经网络模型的普遍适用性,由相关系数和预测误差的分析可知该方法具备应对急剧变化数据的预测稳定性,可以作为海洋表面风速短期预测的一种可靠方法。     

A forecasting model for wave heights based on a long short-term memory neural network

To explore new operational forecasting methods of waves, a forecasting model for wave heights at three stations in the Bohai Sea has been developed. This model is based on long short-term memory(LSTM) neural network with sea surface wind and wave heights as training samples. The prediction performance of the model is evaluated,and the error analysis shows that when using the same set of numerically predicted sea surface wind as input, the prediction error produced by the proposed LSTM model at S...     

基于深度学习RCF模型的三都澳筏式养殖区提取研究

三都澳是中国重要的海水养殖海湾,在水产养殖中占有较高的经济地位。快速准确地获取养殖区的分布范围、数量以及面积等信息,对养殖区规划、产值估计、生态调查、风暴潮灾害预防等具有重要的意义。然而,随着养殖区域的扩大,海水背景状态愈发复杂多样,光谱特征差异较大,为养殖区提取带来困难。在本实验中,利用高分辨率遥感卫星GF-2图像,引入深度学习RCF（Richer Convolutional Features）网络模型对海湾内的筏式养殖区进行了提取。结果显示:该方法无需事先对区域进行水陆分离处理,且对水中泥沙较多的区域以及海浪较大的区域有很好的提取效果,提取精度达93%以上,适合进行大规模海水养殖区提取应用。     

山东省沿海健康养殖带科技发展战略研究

针对目前海水养殖业养殖规模盲目扩大，种质衰退、病害肆虐、滥用药物、养殖环境污染严重等问题日益突出的状况，提出在山东沿海构建健康养殖带的发展战略。介绍了健康养殖和健康养殖带的概念，分析了山东省海水养殖业存在的问题以及建设健康养殖带的必要性和优势条件。提出了山东省沿海健康养殖带发展战略的基本思路和目标，论述了山东省沿海的区域发展布局以及建设健康养殖带需要的关键技术。     

基于多变量LSTM神经网络模型的PDO指数预测研究

利用1921–2020年的海平面气压、海平面高度、热含量数据以及海冰密集度作为太平洋年代际振荡（Pacific Decadal Oscillation, PDO）指数的预报要素,建立了关于PDO指数时间序列预测的多变量长短期记忆（Long Short Term Memory, LSTM）神经网络模型,对比分析了2011–2020年不同时间序列预测模型的PDO指数预测结果,最后利用多变量LSTM神经网络模型实现了2021–2030年的PDO指数预测。结果显示,多变量LSTM神经网络模型的预测值与观测值经过交叉验证后的平均相关系数和均方根误差分别为0.70和0.62;PDO未来10年将一直处于冷位相,PDO神经网络指数出现两次波动,于2025年出现最小值。相比于其他时间序列预测模型,本文采用的多变量LSTM神经网络模型预测结果误差小、拟合效果好,可以作为一种新型的预测PDO指数的手段。