中国海洋大学数字化校园建设实践

在各高校网络基础设施建设初具规模的情况下,数字化校园建设是当前信息化建设的重要任务。文中以中国海洋大学数字化校园系统为例介绍了1个数字化校园系统,并分析其建设目标、总体应用框架、部署方案以及建设中存在的主要问题。     

山东省三次暖切变线极强降水的对比分析

应用加密观测、常规观测、卫星云图和雷达探测的资料及NCEP/NCAR(1°×1°)再分析资料,对山东省三次极强降水天气进行了诊断和对比分析。结果表明,低层暖式切变线和500 hPa西风槽是三次强降水的主要影响系统。强降水前低层大气高温、高湿、对流不稳定,有较高的对流不稳定能量。低层暖式切变线辐合和暖湿平流产生的上升运动与地面辐合线附近产生的上升运动相叠加,触发对流不稳定能量释放,产生强对流,造成强降水。较强的风垂直切变使得对流有组织地发展。强降水期间,中高层弱的干冷空气侵入,使得对流不稳定加强,中高层具有高位涡的干冷空气入侵诱发低层中尺度涡旋发展, 辐合上升运动加强。低层暖湿气流螺旋式辐合上升与中高层入侵的干冷空气相遇,水汽凝结率增大,降水强度增强。中高层干冷空气侵入的时段与极强降水的时段相对应。有利的地形对局地短时极强降水有重要作用。低层暖式切变线和500 hPa低槽的位置、强弱不同,中高层冷空气的强度和入侵路径不同,对流云团的发生发展、内部结构和移动方向不同,造成强降水的地理位置和强度不同。     

浅析专题地图中的底图数据处理方法——以大比例尺陆地交通图为例

专题地图的应用越来越广泛,但其生产和制作却存在若干问题。很多制图软件偏重于专题要素的处理与表达,对底图要素的研究较少。针对这一问题,文章介绍了专题地图的底图要素确定原则,分析了影响底图要素的因素,进而确定了底图要素的处理方法,包括坐标转换、投影变换、分类分级、显示处理等。最后以大比例尺陆地交通图为例,结合笔者所做工作,...     

陆态网络CORS站观测时间序列分析方法研究

以陆态网络CORS站中的武汉站为切入点,分别采用ARIMA模型和傅里叶拟合模型对武汉站10 a左右的观测时间序列进行分析拟合。实验表明,ARIMA模型和傅里叶拟合模型都能较好地拟合武汉站测站时间序列,但从细节来讲,ARIMA模型理论严密,拟合效果稳定;而傅里叶拟合模型更有利于直观分析时间序列中的各种周期频谱特性。     

浒苔(Ulva prolifera)共附生细菌群落结构分析的引物优化

海藻共附生细菌密切参与宿主的生长发育、营养吸收等重要过程,浒苔(Ulva prolifera)是构成黄海绿潮的唯一优势种,对其共附生细菌开展群落结构分析,有望为成灾机制研究提供重要线索。由于植物叶绿体基因组同时具备原核特征和高拷贝数,会严重干扰共附生细菌基于16S rDNA的序列扩增。高等植物中开发了通用引物799F,利用其3′末端与植物同源区的非配对双碱基,可实现对细菌来源序列的特异性扩增。本文针对多个浒苔群体样本,首次评价了引物799F在藻类中的适用性,发现799F的3′末端与浒苔叶绿体同源区仅存在非配对单碱基,其扩增仍会受到浒苔叶绿体严重干扰。在引物799F的基础上,设计了新引物800F,与通用反向引物1492R配对扩增细菌16S rDNA中具高分辨率的V5-V9可变区,配合使用具热启动功能、同时不具校对功能的DNA聚合酶,可基本完全避免浒苔叶绿体来源序列的扩增,并阐明了方法的原理。优化的引物扩增方案可用于浒苔共附生细菌群落结构分析。     

Ulva and Enteromorpha (Ulvaceae, Chlorophyta) from two sides of the Yellow Sea: analysis of nuclear rDNA ITS and plastid rbcL sequence data

Ulvacean green seaweeds are common worldwide; they formed massive green tides in the Yellow Sea in recent years, which caused marine ecological problems as well as a social issue. We investigated two major genera of the Ulvaceae, Ulva and Enteromorpha, and collected the plastid rbcL and nuclear ITS sequences of specimens of the genera in two sides of the Yellow Sea and analyzed them. Phylogenetic trees of rbcL data show the occurrence of five species of Enteromorpha (E. compressa, E. flexuosa, E. intestinalis, E. linza and E. prolifera) and three species of Ulva (U. pertusa, U. rigida and U. ohnoi). However, we found U. ohnoi, which is known as a subtropical to tropical species, at two sites on Jeju Island, Korea. Four ribotypes in partial sequences of 5.8S rDNA and ITS2 from E. compressa were also found. Ribotype network analysis revealed that the common ribotype, occurring in China, Korea and Europe, is connected with ribotypes from Europe and China/Japan. Although samples of the same species were collected from both sides of the Yellow Sea, intraspecific genetic polymorphism of each species was low among samples collected worldwide.     

Inhibitory activity of an extract from a marine bacterium Halomonas sp. HSB07 against the red-tide microalga Gymnodinium sp. （Pyrrophyta）

In recent years, red tides occurred frequently in coastal areas worldwide. Various methods based on the use of clay, copper sulfate, and bacteria have been successful in controlling red tides to some extent. As a new defensive agent, marine microorganisms are important sources of compounds with potent inhibitory bioactivities against red-tide microalgae, such as Gymnodinium sp. （Pyrrophyta）. In this study, we isolated a marine bacterium, HSB07, from seawater collected from Hongsha Bay, Sanya, South China Sea. Based on its 16S rRNA gene sequence and biochemical characteristics, the isolated strain HSB07 was identified as a member of the genus Halomonas. A crude ethyl acetate extract of strain HSB07 showed moderate inhibition activity against Gymnodinium sp. in a bioactive prescreening experiment. The extract was further separated into fractions A, B, and C by silica gel column chromatography. Fractions B and C showed strong inhibition activities against Gymnodinium. This is the first report of inhibitory activity of secondary metabolites of a Halomonas bacterium against a red-tide-causing microalga.     

中国西南地区农业干旱灾害风险空间特征

21世纪,中国西南地区干旱灾害农业综合损失率远超过全国平均水平,给人类生活带来了巨大的风险。本文依据灾害系统理论,利用遥感、气象和地理信息数据与技术建立致灾因子危险性、孕灾环境脆弱性、承灾体易损性和防灾减灾能力可靠性等4个因子的风险指数和模型,基于4个因子建立农业干旱灾害综合风险评估模型,在GIS平台下计算了干旱灾害综合风险指数。结果表明:西南地区干旱灾害风险格局模式具有明显的地带性和复杂性,全区并不一致,高风险区主要位于四川盆地和云贵川三省交界处,北部高于南部,东部高于西部,从西南到东北依次增加。随着干旱灾害综合风险指数的变化,干旱灾害风险的模式具有不同的格局。西南地区干旱灾害风险主要受复杂地形和多样气候带的影响,还受植被盖度、农业经济水平、土壤状况等地理环境影响,同时,喀斯特地貌和相对薄弱的抗旱能力也使得西南地区农业干旱灾害风险较高。