东南亚近岸海区浮游植物光合色素和群落组成—印度尼西亚贯穿流和吉兰丹河口区的比较研究

Water samples were collected in order to study the spatial variation of photosynthetic pigments and phytoplankton community composition in the Lembeh Strait(Indonesia) and the Kelantan River Estuary(Malaysia)during July and August 2016, respectively. Phytoplankton photosynthetic pigments were detected using high performance liquid chromatography combining with the CHEMTAX software to confirm the Chl a biomass and community composition. The Chl a concentration was low at surface in the Lembeh Strait, which it was 0.580–0.682 μg/L, with the average(0.620±0.039) μg/L. Nevertheless, the Chl a concentration fluctuated violently at surface in the Kelantan River Estuary, in which the biomass was 0.299–3.988 μg/L, with the average(0.922±0.992) μg/L. The biomass at bottom water was higher than at surface in the Kelantan River Estuary, in which the Chl a concentration was 0.704–2.352 μg/L, with the average(1.493±0.571) μg/L. Chl b, zeaxanthin and fucoxanthin were three most abundant pigments in the Lembeh Strait. As a consequence, phytoplankton community composition was different in the two study areas. In the Lembeh Strait, prasinophytes(26.48%±0.83%) and Synechococcus(25.73%±4.13%) occupied ～50% of the Chl a biomass, followed by diatoms(20.49%±2.34%) and haptophytes T8(15.13%±2.42%). At surface water in the Kelantan River Estuary, diatoms(58.53%±18.44%)dominated more than half of the phytoplankton biomass, followed by Synechococcus(27.27%±14.84%) and prasinophytes(7.00%±4.39%). It showed the similar status at the bottom water in the Kelantan River Estuary,where diatoms, Synechococcus and prasinophytes contributed 64.89%±15.29%, 16.23%±9.98% and 8.91%±2.62%,respectively. The different phytoplankton community composition between the two regions implied that the bottom up control affected the phytoplankton biomass in the Lembeh Strait where the oligotrophic water derived from the West Pacific Ocean. The terrigenous nutrients supplied the diatoms growing, and pico-phytoplankton was grazed through top down control in the Kelantan River Estuary.     

算盘子的鉴别研究

目的：探讨算盘子的性状鉴别、显微鉴别和薄层鉴别方法。方法：采用显微鉴别法和薄层色谱法。结果：显微组织特征明显;薄层色谱斑点清晰,相互间分离良好。结论：该法简便快速,可用于算盘子的质量控制。     

鲁西归来庄金矿床深部外围找矿前景

鲁西地区归来庄金矿床找矿始于1987年初,历经"六进六出"的坚持不懈,探求金金属量34.8t,填补了鲁西地区无大型金矿的空白。近几年,山东省鲁南地质工程勘察院在归来庄金矿床深部及外围开展的勘查工作,扩大了归来庄主矿体的规模,并且证实归来庄主矿体沿F1构造蚀变带向深部尚未封闭,仍有良好找矿前景。目前归来庄金矿累计探明金金属量超过50t,是鲁西地区唯一的特大型金矿床。该文在系统分析以往成果资料基础上,系统归纳了归来庄主矿体地质特征,建立了铜石杂岩体周边多种金矿化类型"一体多型"成矿模式,指出了下步找矿方向:归来庄金矿床深部找矿仍以寻找隐爆角砾岩型为主,外围重点围绕"一带多区",争取早日实现铜石地区找矿新突破。     

诸城西北部碎屑岩类孔隙水裂隙水水文地质特征

中生代白垩纪砖红色、紫红色砂岩、砂页岩致密、较坚硬,一直被水文地质工作者视为弱富水岩层。该文以诸城西北部中生界白垩纪红砂岩碎屑岩类孔隙、裂隙水为研究对象,在现场调查、取样化验、水文地质钻探、抽水试验的基础上,对区内碎屑岩类孔隙、裂隙水水环境进行了初步研究。结果显示,区内碎屑岩类孔隙、裂隙水总体富水性较差,孟疃-贾悦断裂北侧受构造及阻水地层影响,形成一个带状富水区;景芝-贾悦断裂和吴家楼断裂组交会地带,受多条断裂多次强烈活动,形成断裂破碎带,形成构造富水区。地下水质量较原来趋于变差,NO_3~-呈面状污染。     

中东亚干旱区全新世气候变化的西风模式—以湖泊研究为例

综述了亚洲中部干旱区湖泊研究的古气候记录.发现湖泊记录的全新世有效湿度在大框架上具有一致性变化.据此,选择了其中年代可靠、代用指标湿度意义明确、时间分辨率较高的8个地点的记录,半定量地集成了中东亚干旱区全新世期间湿度的变化.结果表明,亚洲内陆干旱区全新世气候变化具有较清晰的阶段性变化,大约8cal kaBP以前的早全新世气候干旱,8-4cal kaBP的中全新世气候湿润,从距今5-6cal kaBP以来湿润程度逐步降低到晚全新世,但晚全新世比早全新世湿润.内陆干旱区的全新世湿度变化框架与最新获得的亚洲季风变化模式存在较大差异,因此推论出,北大西洋海洋表面的温度变化可能是中东亚干旱区湿度的主要影响因素.     

JCZ-1T超宽频带地震计常见故障分析

对JCZ-1T超宽频带地震计的多种故障进行分类,故障主要包括仪器记录波形异常、仪器标定波形异常、地震计工作状态异常等,并对故障原因进行分析,给出相应解决方法.此外,对沈阳地震基准台JCZ-1T地震计1例故障的现象、原因排查、维修方法等进行了详细介绍.     

磁化强度矢量反演新方法及其在卡拉塔格铜多金属矿床找矿中的应用

磁异常的反演是地球物理勘探的重要手段,三维磁化率反演是磁异常定量解释中的一种重要方法.由于剩磁的存在使得磁化方向与地磁场方向产生偏差,从而影响了磁异常反演与解释的精度.本文基于磁异常模量反演和磁化强度矢量反演方法得到了一种新的磁化强度矢量反演方法.与以往的磁化强度矢量反演方法相比,该方法以磁异常模量反演得到的磁化率模型为约束,采用Lp范数正则化方法求解,提高了磁化强度矢量反演的精度和效率.本文通过模拟试验的反演计算,验证了这种磁化强度矢量反演方法的有效性.最后,将本文方法应用于新疆东天山卡拉塔格地区航磁数据的解释,获得了地下空间不同磁性差异的磁性体的空间分布特征,为进一步分析研究区隐伏矿床提供了重要信息.     

古建筑保护中新技术的实践应用

随着信息化时代的到来,古建筑保护工作中也逐渐应用了建筑、测绘地理信息行业中的信息化新技术.新技术的实践与应用为古建筑保护与管理工作提供了极大的帮助.本文将三维激光扫描技术、BIM技术、GIS空间分析技术分别应用于不同的古建筑保护项目,对其应用实践进行阐述说明,并就其应用效果进行了简单分析.     

低头坝养鱼对上下游局域栖息地和鱼类群落时空格局的影响

河流鱼类的群落特征会随栖息地环境的变化而发生变化.为了解鱼类群落对低头坝养鱼的响应程度,2013—2014年共6次调查了乌龙河(长江下游支流)两个可涉水河段样点(上游坝和下游坝)的环境因子、鱼类多样性及其群落结构.共采集到5目10科21属24种鱼类,以鲤形目鲤科最多,占总数的58.3%.通过解析时空动态变化与局域栖息地条件对鱼类群落的影响,发现季节因素对鱼类群落结构无显著影响,而鱼类群落所在空间位置(上游坝,下游坝)对群落结构差异具有较显著影响,其中上游中华鳑鲏(Rhodeus sinensis)、(Hemiculter leucisculus)、棒花鱼(Abbottina rivularis)、大鳍鱊(Acheilognathus macropterus),下游食蚊鱼(Gambusia affinis)的多度决定了这种差异;而3个栖息地变量(溶解氧浓度、电导率和流速)均对鱼类群落特征具有显著性影响.栖息地环境差异对河流上、下游鱼类群落的影响较大,具体体现在下游样点鱼类的捕获重量、捕获数量、密度、多样性明显下降,推测利用低头坝养鱼是造成这些现象的重要原因.     

THE EXTRACTION OF HOUSE DISTRIBUTION BASED ON PHOTOGRAMMETRY METHOD:TAKING THE COUNTRYSIDE IN THE WEST OF CHINA FOR EXAMPLE

The key parameters of houses such as distribution, area and height play an important role for urban-rural planning, earthquake emergency and disaster mitigation. The computer automatic extraction method is an effective way to acquire large area house information using satellite-borne or airborne optical remote-sensing images. However, because of the similarity of spectral characters for different land cover types or the influence of snow coverage, the classification accuracy of house type using traditional spectral based method can be decreased. To acquire the accurate houses distribution, a method based on the height information is proposed using unmanned aerial vehicle(UAV)in this study. With UAV flying at the height of 100m above ground, the route of the UVA was planned with the heading direction overlap of 77% and side direction overlap of 50%for the nearby pictures. Taking Qionghalajun Village in Xinjiang Uygur Autonomous Region for example, 69 pictures of the study area were obtained with DJI Phantom 3 professional. With those pictures input into the EasyUAV software, the Digital Elevation Model(DEM), Digital Surface Model(DSM), and Digital Orthophoto Map(DOM)were acquired based on photogrammetry method using the overlapped optical remote-sensing images of UAV. After that, the house distribution and height were acquired with the differences between DSM and DEM images larger than 2.6m. To eliminate the influences of disintegrated pixels on the house extraction, mainly caused by the trees or noise point, the classification aggregation tool of ENVI software was used with the disintegrated pixels' area less than 4m². Compared with visual interpretation result, the user accuracy and mapping accuracy of the house extraction method proposed in this study is 88.69% and 97.42%, respectively. In addition, to evaluate the performance of the proposed method, the result of traditional supervised classification method using DOM data acquired previously was compared with the result of new method. The results show that the new method is more accurate the user accuracy and mapping accuracy of the supervised classification method, which is 43.23% and 85.30%, respectively. Besides the study area in this study, the performance of the proposed method will be evaluated at the other places in the further study.