《贵州地质》关于电子与网络出版著作权的声明

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寄生性病原血卵涡鞭虫(Hematodinium sp.)感染山东半岛养殖梭子蟹的初步研究

寄生性病原血卵涡鞭虫(Hematodinium sp.)逐渐成为危害我国沿海养殖三疣梭子蟹、锯缘青蟹、脊尾白对虾等蟹虾类的致病性病原。为研究血卵涡鞭虫在我国北方的感染、流行情况,2012年7—11月间,作者从山东半岛三疣梭子蟹的主要养殖区域和邻近海域随机采集梭子蟹样品,进行了血淋巴、组织病理、电镜和分子生物学检测,首次在从胶南和莱州湾养殖区采集的梭子蟹中发现了血卵涡鞭虫感染。在感染血卵涡鞭虫的梭子蟹血淋巴中,共发现了该寄生性病原的四个生活史阶段:丝状滋养体、单细胞滋养体、滋养体聚合体和多核孢子体;该区域发现的血卵涡鞭虫(Hematodinium sp.)形态上与其他报道Hematodinium spp.类似,与在我国东南沿海报道发现的血卵涡鞭虫有亲密的遗传关系;人工感染实验表明该寄生性虫具感染性并对宿主的主要器官造成显著的病理变化。该研究表明血卵涡鞭虫感染养殖蟹类不仅局限于我国东南沿海,在我国北方的养殖蟹类中也存在;这些养殖区普遍采用的混合养殖模式可能一定程度上加剧了该寄生性病原的传播、扩散,因此其传播扩散方式亟需进一步调查研究。     

《海洋学报》作者投稿须知

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《海洋学报》作者投稿须知

<正>版权问题:敬请投稿本刊的作者:投稿中没有侵犯他人著作权或其他权利的内容;投稿给本刊的稿件自发表之日起,其专有出版权和网络传播权即授予本刊,并许可本刊在本刊网站或本刊授权的其他数据库收录。设置栏目:学术论文、研究报道、综述、学术争鸣。     

Using a mesoscale ensemble to predict forecast error and perform targeted observation

Using NCEP short range ensemble forecast（SREF） system,demonstrated two fundamental on-going evolutions in numerical weather prediction（NWP） are through ensemble methodology.One evolution is the shift from traditional single-value deterministic forecast to flow-dependent（not statistical） probabilistic forecast to address forecast uncertainty.Another is from a one-way observation-prediction system shifting to an interactive two-way observation-prediction system to increase predictability of a weather system.In the first part,how ensemble spread from NCEP SREF predicting ensemble-mean forecast error was evaluated over a period of about a month.The result shows that the current capability of predicting forecast error by the 21-member NCEP SREF has reached to a similar or even higher level than that of current state-of-the-art NWP models in predicting precipitation,e.g.,the spatial correlation between ensemble spread and absolute forecast error has reached 0.5 or higher at 87 h（3.5 d） lead time on average for some meteorological variables.This demonstrates that the current operational ensemble system has already had preliminary capability of predicting the forecast error with usable skill,which is a remarkable achievement as of today.Given the good spread-skill relation,the probability derived from the ensemble was also statistically reliable,which is the most important feature a useful probabilistic forecast should have.The second part of this research tested an ensemble-based interactive targeting（E-BIT） method.Unlike other mathematically-calculated objective approaches,this method is subjective or human interactive based on information from an ensemble of forecasts.A numerical simulation study was performed to eight real atmospheric cases with a 10-member,bred vector-based mesoscale ensemble using the NCEP regional spectral model（RSM,a sub-component of NCEP SREF） to prove the concept of this E-BIT method.The method seems to work most effective for basic atmospheric state variables,moderately effective for convective instabilities and least effective for precipitations.Precipitation is a complex result of many factors and,therefore,a more challenging field to be improved by targeted observation.     

An Improved Coupling of Numerical and Physical Models for Simulating Wave Propagation简

An improved coupling of numerical and physical models for simulating 2D wave propagation is developed in this paper. In the proposed model, an unstructured finite element model （FEM） based Boussinesq equations is applied for the numerical wave simulation, and a 2D piston-type wavemaker is used for the physical wave generation. An innovative scheme combining fourth-order Lagrange interpolation and Runge-Kutta scheme is described for solving the coupling equation. A Transfer function modulation method is presented to minimize the errors induced from the hydrodynamic invalidity of the coupling model and/or the mechanical capability of the wavemaker in area where nonlinearities or dispersion predominate. The overall performance and applicability of the coupling model has been experimentally validated by accounting for both regular and irregular waves and varying bathymetry. Experimental results show that the proposed numerical scheme and transfer function modulation method are efficient for the data transfer from the numerical model to the physical model up to a deterministic level.     

《测绘学报》变更为月刊的公告

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