基于GIS的北京山区优势林分生态位分析

应用生态位理论,以北京山区森林资源为研究对象,分析优势林分的空间分布及其资源利用和环境适应能力的差异。基于GIS方法,建立优势林分空间分布数据库以及资源梯度信息数据库,分别采用Levins公式和Smith公式,在水分、热量、光照和土壤质量4维环境因子梯度上测定了研究区8个优势林分的生态位宽度,采用Pianka公式测定生态位重叠。结果表明:Smith公式考虑资源可利用性,得到的生态位宽度更能客观地反映优势林分资源空间利用程度;研究区各优势林分重叠度普遍较大,反映了对环境要求的相似性及资源共享的趋势性。     

Seasonal change of ice algal and phytoplankton assemblages in the Nella Fjord near Zhongshan Station, East Antarctica

The ice algal and phytoplankton assemblages were studied from Nella Fjord near Zhongshan Station, East Antarctica from April 12 to December 30, 1992. Algal blooms occurred about 3 cm thick on the bottom of sea ice in late April and mid November to early December respectively, and a phytoplankton bloom appeared in the underlying surface water in mid December following the spring ice algal bloom. The biomass in ice bottom was 1 to 3 orders of magnitude higher than that of surface water. Amphiprora kjellmanii, Berkeleya sp., Navicula glaciei, Nitzschia barkelyi, N. cylindrus /N. curta, N. lecointei and Nitzschia sp. were common in the sea ice temporarily or throughout the study period. The biomass in a certain ice segment was decreased gradually and the dominant species were usually succeeded as the season went on. Nitzschia sublineata and Dactyliosolen antarctica were two seasonal dominant species only observed in underlying water column. The assemblages between bottom of ice and underlying surface water were different except when spring ice algae bloomed. The evidence shows that the ice algal blooms occurred mainly by in situ growth of ice algae, and the phytoplankton bloom was mostly caused by the release of ice algae.     

基于周仲瑛外感热病学术思想构建中医急诊诊治思路探析

目的：阐述周仲瑛教授外感热病学术思想对江苏中医急诊诊治思路的指导作用。方法：通过文献整理,归纳总结周教授外感热病学术思想;通过病案分析与数据挖掘的方法,分析周教授学术思想在中医急诊外感热病中的运用。结果：周教授创建的中医病机辨证理论是外感热病中医急诊辨治新体系的重要特征,主张审证求机,重视病机演变,提出截断逆转、祛邪外出两大治则。数据分析结果显示,江苏中医急诊学临床运用的外感热病诊治思路、方法与周教授的学术观点、学术理论相一致,学术思想一脉相承。结论：以周教授中医病机辨证理论为特征的外感热病中医急诊辨治新体系为临床诊治提供了纲领性指导,对中医急诊临床的学术影响举足轻重。     

滇东北松梁铅锌矿床控矿断裂构造岩微量元素的R型因子分析及其地质意义

通过因子分析这种常用的多元统计方法来揭示元素之间、样品之问以及与地质作用之间的相互关系,了解其中蕴藏着丰富的成矿信息,为研究成矿物质来源和矿床成因提供依据.在研究滇东北巧家松梁铅锌矿床地质特征的基础,以其中Ⅰ号矿体的控矿断裂(F5断裂)内的构造岩为R型因子,得到4组元素组合因子并综合成矿地质条件因子进行分析,结果表明:该矿床严格受构造控制,碳酸盐化蚀变和铅、锌矿化发生在不同的成矿阶段;成矿流体并非完全来自地层,主要来源于深源流体;铅锌等成矿物质具有"多源性",部分来自于地层(白云岩),部分来自于与基底岩石有联系的成矿流体.客矿断裂带内的构造岩裂隙发育,铅锌成矿流体有选择性地沿碎基多、破碎强烈的裂隙充填胶结成矿,矿床应该属赋存于碳酸盐岩中的热液型铅锌矿床.     

塔里木盆地西部古岩盐地质地球化学特征与成钾条件分析

塔里木盆地是我国重要的成盐盆地,为我国最有远景的找古钾矿地区之一。本文通过多年野外实地调查和大量岩盐样品的化学分析,特别是岩盐中可以指示沉积阶段的Br×103/Cl系数等区域分布特征,联系前人研究资料,分别从构造环境、地层和岩相古地理、地球化学特征等方面进行了成钾条件分析。结果表明,莎车盆地西部喀什坳陷和库车盆地中部拜城坳陷宏观地质特征均有利于钾盐沉积;岩盐地球化学组成相对于正常海相沉积表现出明显的贫Br特征,属海陆交互相或海源陆相沉积。相比之下,莎车盆地的喀什次级坳陷是目前最有前景的找钾远景区。     

0～6 h定量降雪(雨)预报技术及其在温哥华冬奥会中的应用

利用中尺度数值预报模式与雷达回波外推技术相结合,围绕SNOWV10项目的科学目标,在自动判识降水相态(雨、雪或雨雪混合物)基础上,利用雷达反演降雪(雨)关系,建立短时(0～6 h)定量降雪(雨)预报方法,并集成到GRAPES-SWIFT临近预报系统,为温哥华冬奥会提供实时场馆预报产品.从2010年2月冬奥会使用情况看,所建立的定量降雪(雨)预报技术,一定程度满足高纬度冬季降雪(雨)临近预报预警的需求,但降水(雨或雪)预报量级偏小,针对场馆的降水预报起止时间节奏偏差较大,各时次预报一致性有待改进.     

黑麦草在净化富营养化水的人工湿地生态工程中的作用

在人工湿地生态工程中利用黑麦草(Lolium perenne L．)净化污水，得到了较好的效果。结果表明：利用黑麦草在冬春季节的生长，可使亚热带地区人工湿地常年运行，黑麦草在3—4月份对水体就有明显的净化作用。在春夏季节，特别在5月份黑麦草可以获得较高的生物量和N、P的积累量，因而净化贡献最大。从产草量方面考虑，延长黑麦草的生长期能获得较高的生物量；从植物体所含营养物质状况和饲用价值看，增加收割次数的黑麦草N、P含量高，饲用价值高；但从黑麦草对污水中N、P的吸收和积累量方面考虑，收割次数过高则不利于黑麦草对污水的净化及N、P的累积。从上述几方面综合考虑，在黑麦草整个生长期收割次数以2．3次为宜。     

峨眉山大火成岩省太和花岗岩的成因及构造意义

攀西地区的太和花岗质岩体和赋存超大型钒钛磁铁矿矿床的辉长岩体在空间上共生,成因上均与峨眉山地幔柱头的上升密切相关.太和花岗质岩体主要由超碱质花岗岩和石英正长岩及少量正长岩组成;富含高场强元素并具高Ga/Al值(3.74～5.63),显示典型A型花岗岩的特征.花岗岩、正长岩和辉长岩的Nb/Ta和Zr/Hf值与洋岛玄武岩(OIB)的相应比值近似.花岗质岩石具较低的87Sr/86Sr初始值(0.7025～0.7049)和正的εNd(t)值(1.9～3.5),与辉长岩的值相近[(87Sr/86Sr)i =0.7049～0.7052; εNd(t) =2.4～3.3].太和花岗质岩体的εNd(t)为正值,显示地幔柱来源的底侵玄武质岩浆对其形成起主要作用.辉长质和花岗质岩石具相似的钕同位素组成,表明其母岩浆来自于同一源区.我们认为太和花岗质侵入体主要由底侵于下地壳的玄武质岩浆分异出的花岗质熔体侵位及随后经结晶分异而形成.因此,晚古生代时幔源岩浆底侵造成的地壳增生在峨眉山大火成岩省中表现极为显著.     

用多角度遥感数据反演混合像元组分温度的可行性分析

利用多通道信息反演陆面温度的传统方法,由于通道间信息的高度相关使反演结果的精度难以提高,并且无法得到混合像元中的组分温度。文中以非同温混合像元热红外辐射方向性规律为基础,建立了连续植被类型非同温混合像元热红外辐射模型,用蒙特卡罗方法模拟分析了连续植被的组分有效比辐射率与变量的关系。结果表明:连续植被热辐射亮度值是组分温度T_v、T_s,叶面积指数LAI,叶倾角分布LAD,以及单叶面比辐射率ε_v(θ)和土壤表面比辐射率ε_v(θ)的函数。利用先验知识对变量进行分析后表明,6个变量中只有T_v、T_s、LAI、ε_v(0)需要反演。由于多角度间组分辐射亮度的相关性低,从理论上讲只需要4个角度的辐射亮度观测值就可以解出4个未知量而达到反演组分温度的目的。这4个角度数据除选择垂直方向上辐射亮度数据外,应在30°～50°视角范围内选择另外3个热辐射亮度数据。     

A CLOUD-RESOLVING MODELING STUDY OF SURFACE RAINFALL PROCESSES ASSOCIATED WITH LANDFALLING TYPHOON KAEMI(2006)

The detailed surface rainfall processes associated with landfalling typhoon Kaemi(2006) are investigated based on hourly data from a two-dimensional cloud-resolving model simulation. The model is integrated for 6 days with imposed large-scale vertical velocity, zonal wind, horizontal temperature and vapor advection from National Center for Environmental Prediction (NCEP) / Global Data Assimilation System (GDAS) data. The simulation data are validated with observations in terms of surface rain rate. The Root-Mean-Squared (RMS) difference in surface rain rate between the simulation and the gauge observations is 0.660 mm h^-1, which is smaller than the standard deviations of both the simulated rain rate (0.753 mm h^-1) and the observed rain rate (0.833 mm h^-1). The simulation data are then used to study the physical causes associated with the detailed surface rainfall processes during the landfall. The results show that time averaged and model domain-mean P_s mainly comes from large-scale convergence (Q_WVF) and local vapor loss (positive Q_WVT). Large underestimation (about 15%) of P_s will occur if Q_WVT and Q_CM (cloud source/sink) are not considered as contributors to P_s. Q_WVF accounts for the variation of P_s during most of the integration time, while it is not always a contributor to P_s. Sometimes surface rainfall could occur when divergence is dominant with local vapor loss to be a contributor to P_s. Surface rainfall is a result of multi-timescale interactions. Q_WVE possesses the longest time scale and the lowest frequency of variation with time and may exert impact on P_s in longer time scales. Q_WVF possesses the second longest time scale and lowest frequency and can explain most of the variation of P_s. Q_WVT and Q_CM possess shorter time scales and higher frequencies, which can explain more detailed variations in P_s. Partitioning analysis shows that stratiform rainfall is dominant from the morning of 26 July till the late night of 27 July. After that, convective rainfall dominates till about 1000 LST 28 July. Before 28 July, the variations of in rainfall-free regions contribute less to that of the domain-mean Q_WVT while after that they contribute much, which is consistent to the corresponding variations in their fractional coverage. The variations of Q_WVF in rainfall regions are the main contributors to that of the domain-mean Q_WVF, then the main contributors to the surface rain rate before the afternoon of 28 July.