海水对虾工厂化循环水养殖系统模式分析

对虾养殖由于受到水资源和虾病的困扰,工厂化循环水养殖已经成为今后对虾养殖的一个重要方向。对虾工厂化循环水养殖系统的结构包括了养虾池、水处理技术、消毒杀菌、增氧技术、水温调节装置等。目前,典型的养殖模式有美国德州跑道式对虾养殖系统、台南室内自动化循环水养虾系统、美国佛罗里达三阶段养殖系统和美国夏威夷基于微藻的循环水对虾养殖系统。文中对这4种典型的对虾工厂化循环水养殖系统的养殖试验情况进行分析比较。     

工厂化循环水养殖对虾研究进展

简述了国内外工厂化循环水养殖系统,对比了传统养殖模式中高位池养殖与池塘养殖模式,指出了工厂化循环水养殖对虾模式存在的问题,探讨了工厂化循环水养殖模式的推广阻力.     

人工养殖杂色鲍流行病防治技术

近几年，南方杂色鲍工产化养殖受病害困扰，养殖海区水质出现富营养化，共栖生物种群增加，病因较为复杂。工厂化养殖杂色鲍鱼采用2m以下海区砂层水，配合陆上过滤系统，或采用循环水生态系统工厂化养殖，能大幅度减少有害生物和污着生物，科学交替使用消毒丹和有益菌，能提高工厂化杂色鲍养殖成活率15～20％，减轻越冬时杂色鲍大量死亡的威胁。     

全国海水工厂化养殖与管理专题研修培训班研修战果报告

农业部针对我国近年出现的工厂化养鱼热潮，探讨今后发展工厂化养殖的技术和思路，特于今年７月份在山东省荣成举办了首期“全国海水工厂化养殖与管理专题研修培训班”，内容包括海水鱼、鲍和海参和工厂化养殖。本文综合报告了我国工厂化养殖概况、研修成果和今后的对策与建议，对我国今后工厂化养殖技术和管理水平的提高具有实际参考意义。     

鲍的人工养殖

目前鲍的养(增)殖方式，大体可分为3大类型6种形式：一是池式养殖，包括工厂化(陆地池)养殖、潮间带水池养殖；二是箱(笼)式养殖，包括网箱养殖、筏式养殖、沉箱养殖；三是岩礁增殖。除工厂化养殖将作较详细介绍外，其余养殖方式简述如下。     

罗非鱼的高密度工厂化养殖技术

如果水源充足并且土地资源较为紧张，相对于池塘养殖和网箱养殖来说，高密度工厂化养殖罗非鱼是一种较好的选择，养殖的效益也较为可观。在水质条件能持续保持良好的情况下，罗非鱼在高密度养殖条件下生长良好。不过在养殖过程中必须保持人工增氧（充气）和频繁或连续地换水，以保证水中有充足的氧气和清除水中的废物。养殖用水使用后直接排放掉的称之为流水养殖系统，养殖用水通过过滤后再次循环使用的称为循环养殖系统。     

工厂化养殖系统优化设计原则

论述了工厂化养殖系统优化设计原则,即适用性、可靠性和经济性的内涵及其实现措施,结合该原则,提出了大菱鲆工厂化养殖系统的概念设计和水处理工艺。采用该原则设计的工厂化养殖系统,1 kg商品鱼的耗水量仅为24~47 m3,虽较国外发达国家的同类养殖系统(13~15 m3水/kg鱼)略高,但大大低于流水养殖模式的耗水量(360~600 m3水/kg鱼)。     

虾类工厂化养殖现状

<正>工厂化养殖是指水产养殖以工厂化的形式组织安排生产,突显出了水产养殖的工业化生产特征,该技术的核心是水环境的人工调控^[1]。以工厂化养殖车间为主要特征的流水养殖模式是目前我国工厂化养殖的主要模式,而国际上与之相对应的是循环水养殖系统(Recirculating Aquaculture System,RAS)。一般认为,日均水利用率95%以上为循环水养殖,95%以下则为流水养殖^[1]。目前,很多水产养殖的物种已经实施了工厂化     

臭氧水处理在甲鱼工厂化养殖中的应用

水处理技术是甲鱼工厂化养殖过程中的关键技术之一，臭氧水处理是集约化水产养殖系统中较为先进的水处理技术，本文介绍了臭氧水处理的原理，对水质改善的作用机理和臭氧，臭氧水的制作工艺；着重阐述了甲鱼养殖工厂的臭氧水处理结构，臭氧水的作用，以及臭氧水应用在甲鱼工厂化养殖水处理中应注意的问题。     

罗氏沼虾的养殖技术

八、其它养殖方式养殖罗氏沼虾除了采用一般池塘养殖方式外，还有工厂化养殖、网箱养殖、稻田养殖及河道养殖等方式。现分别予以简介：１．工厂化养虾工厂化养虾就是水温、水质、溶氧量等都在人为控制下不受自然干扰，应用全价颗粒饲料，投饲、管理达到高度机械化，单位水体内虾产量较高的一种养虾方式。（１）工厂化养虾的设施　　养虾池、贮水池、加温池和水质净化设施。（２）工厂化养虾的方法①放养　　一般采用３～４级放养方法，每级养殖１个月左右，第一级（淡化苗养至２～３ｃｍ），放养密度２０００～３０００尾／ｍ２，二级（３ｃ…     

海洋渔业电子地图系统软件设计与实现

系统地介绍了海洋渔业电子地图系统软件EA2000的数据模型和主要功能的设计与实现，EA2000采用了面向对象的数据模型，紧密的矢栅数据接口，以及图层－地图－图集一体化数据组织管理方法，该软件具有开放的数据输入接口，图层创作的自动化和动态交互式编辑，双向查询检索，缩放漫游与多级比例尺联动显示，动态显示，对象信息自动显示，地理信息系统渔船动态监控管理，多媒体信息插入管理，互操作等功能。     

海洋渔业数据仓库的研究与实现

数据仓库技术作为数据库技术应用的新型手段,是海洋渔业数据集成、实现业务化管理的良好的解决方案。根据海洋渔业的特点,本文提出了构建海洋渔业数据仓库的策略、基本框架,探讨了在海洋环境数据仓库建设过程中数据集市模型设计、建立数据准备区、数据规划和数据提取等四个关键问题,用SQL Server初步建成了海洋渔业数据仓库。     

基于3S集成平台的南海渔业信息动态采集与实时自动分析系统研发

以全球定位系统(GPS)、地理信息系统(GIS)和遥感(RS)等3S技术集成平台,并结合船舶监控系统(VMS)、北斗卫星短报文信道、ARM高性能处理器、NR嵌入式操作系统等前沿技术,建立"南海渔业信息动态采集与实时自动分析系统"。该系统是一个分布式系统,包括船载捕捞信息实时采集装备、南海渔业数据集成中心、南海渔业捕捞地理信息系统及外海渔场预报系统等4个完全独立分布的子系统。本系统自主研发了具备北斗通信功能的船载捕捞实时采集装备,并创新性地利用北斗卫星短报文信道实现了海上渔船与地面数据中心的实时信息交互,此外利用VPN信道实现了数据中心与数据处理分析应用系统之间安全可靠的数据共享,从而最终建立了海上渔船与岸上数据分析系统之间的无缝连接虚拟网络。基于这一网络,海上渔船将渔业捕捞数据实时发送至南海渔业捕捞GIS系统,进行实时分析与显示海洋捕捞(分)渔区/渔船/鱼类产量的数据分析专题图;外海渔场预报系统依据多年的捕捞、渔业生物学及渔场环境数据收集与分析将南海外海鸢乌贼渔场信息发送给海上渔船,推进海上渔业捕捞的高效生产。     

金枪鱼电浮标卫星通讯与数据压缩实现

针对目前海上渔船与流放在海面的浮标远距离通讯传输时存在信息易丢失、通讯费用高以及数据显示终端不够友好等诸多问题,对卫星通讯终端(IDP)的数据结构与哈夫曼压缩算法展开研究。采用图像分级式哈夫曼编码压缩方法,利用卫星信号收发服务器提供中转,对卫星回传的40组典型数据进行编码解码试验。结果显示,通讯数据流量最高压缩比达到0.58,平均节省通讯成本40%,客户端人机界面友好,实现卫星定位与浮标各项参数的实时显示,控制命令延迟时间仅为5 s。最终将压缩算法部署在卫星通讯终端并实时接收远程数据后,控制命令收发数据包完整、无丢帧,声呐探测图像清晰可辨,数据包压缩效果显著,达到了预期效果。此浮标已经应用至南海部分金枪鱼围网渔船,渔船可以通过船载客户端与浮标实现有效通讯并实时接收金枪鱼鱼情信息,通讯成本在可接受范围内。     

A new method for assessing fish feeding rhythms using demand feeders and automated data acquisition

A new approach to monitoring fish feeding rhythms and associated environmental variables is described. This system includes demand feeders attached to load cells to monitor feed consumption, and environmental probes to monitor variables such as temperature, solar radiation, barometric pressure, dissolved oxygen, turbidity, and pH. Measurements from the load cells and probes are recorded at some desired time interval on a data logger, and the data are then analyzed for correlations between feed consumption and environmental conditions. An example of feed consumption rhythms by Chinese catfish (Clarias fuscus) is given.     

多种数据源下栖息地模型及预测结果的比较

由于多来源的海洋环境数据常以不同时间、空间分辨率呈现,并具有不同的误差,因此,有必要分析数据源的差异是否会对研究结果产生显著影响,是否会影响基于不同数据源估计的模型对其他数据的适用性。为此,本研究利用多个网站提供的叶绿素浓度与海表水温数据,采用线性回归与随机检验方法,分析了不同数据源对栖息地模型构建及其预测效果的影响。研究结果表明,不同数据源的数据之间常存在系统性偏差,从而使得模型参数的估计具有显著性差异,该模型不适合于其他数据源的数据;多源环境数据间的离散性反映数据存在随机误差,环境数据的随机误差将使模型结果具有随机性,因此本研究建议定量分析模型结果的不确定性,以使模型结果得到科学应用。     

Extending electronic length frequency analysis in R

Electronic length frequency analysis (ELEFAN) is a system of stock assessment methods using length‐frequency (LFQ) data. One step is the estimation of growth from the progression of LFQ modes through time using the von Bertalanffy growth function (VBGF). The option to fit a seasonally oscillating VBGF (soVBGF) requires a more intensive search due to two additional parameters. This work describes the implementation of two optimisation approaches (“simulated annealing” and “genetic algorithm”) for growth function fitting using the open‐source software “R.” Using a generated LFQ data set with known values, the accuracy of the soVBGF parameter estimation was evaluated. The results indicate that both optimisation approaches are capable of finding high scoring solutions, yet settings regarding the initial restructuring process for LFQ bin scoring (i.e. “moving average,”) and the fixing of the asymptotic length parameter (L_∞) are found to have significant effects on parameter estimation error. An outlook provides context as to the significance of the R‐based implementation for further testing and development, as well as the general relevance of the method for data‐limited stock assessment.     

Generic solutions for data‐limited fishery assessments are not so simple

The majority of the world's fisheries, by number, are data‐poor/limited, and there is a growing body of literature pertaining to approaches to estimate data‐limited stock status. There are at least two drivers for assessing the status of data‐limited fisheries. The first is to try to understand and report on the global or regional status of fisheries across many stocks. The second is to attempt to assess individual data‐limited stocks, for status reporting and/or guiding management decisions. These drivers have led to attempts to find simple, generic, low‐cost solutions, including the broad application of generically parameterised models, and the blanket application of a single, or limited number of possible, analytical approach(es). It is unclear that generic methods function as intended, especially when taken out of their original design context or used without care. If the intention is to resolve individual stock status for the purposes of management, there is concern with the indiscriminate application of a single method to a suite of stocks irrespective of the particular circumstances of each. We examine why caution needs to be exercised, and provide guidance on the appropriate application of data‐limited assessment methods (DLMs). We recommend: (a) obtaining better data, (b) using care in acknowledging and interpreting uncertainties in the results of DLMs, (c) embedding DLMs in harvest strategies that are robust to the higher levels of uncertainty in the output of DLMs by including precautionary management measures or buffers and (d) selecting and applying DLMs appropriate to specific species’ and fisheries’ data and context.     

Opportunities for the Herring Industry to Optimize Operations Through Information Recording,Effective Traceability Systems,and Use of Advanced Data Analysis

ABSTRACT

Two case studies of the herring industry reveal that insufficient data on processes and traceability are currently recorded onboard fishing vessels, at primary processing into marinated herring fillets and at secondary processing into small jars as pickled herring products. This means that the traceable unit of a batch of herring is at the level of a whole fishing trip, and that there is a disconnection in traceability along the chain. Data on process and product parameters are insufficient and precludes the use of modern data analysis to examine where improvements and greater efficiencies can be obtained. Suggestions and procedures to overcome these deficiencies are outlined and discussed.     

Is risk consistent across tier‐based harvest control rule management systems? A comparison of four case‐studies

There can be substantial differences in data quality and quantity among fished species. Consequently, the quality and type of assessments can also vary substantially. However, all species, especially those that are targeted, need to be managed. Several jurisdictions have developed hierarchical tier systems that categorize stocks based on, for example, the data available for assessment purposes and/or the extent to which quantities on which management advice is based can be estimated. Four case‐studies (Australia's Southern and Eastern Scalefish and Shark Fishery, the USA west coast groundfishery, the USA Alaskan crab fishery and EU fisheries) are used to contrast the types of hierarchical tier systems available, and to assess the extent to which each system constrains risk to be equivalent among the tiers (termed risk equivalency). Only the Australian system explicitly aims to achieve risk equivalency. However, this intent has not been fully operationalized. Our review reveals that best practice is not to define tiers simply on data availability, but also on what the assessments based on those data are capable of estimating. In addition, clearly differentiating the quantification of uncertainty from how decision‐makers wish to address that uncertainty would simplify justification of buffers (the gap between the assessment‐produced target catch or effort and the final management decision that accounts for uncertainty and risk). Risk equivalency can be achieved using management strategy evaluation to select the values for control variables, which determine the buffer given the uncertainty associated with the assessment.