前胡和紫花前胡在中国的潜在分布区预测

采用最大熵(MaxEnt)生态位模型,结合前胡和紫花前胡大量已有的地理分布数据,基于20个环境变量对其在中国的潜在分布区进行了预测.结果表明:最冷季度平均温度,最冷月最低温和最干季度平均温度为前胡分布限制性因子.而对紫花前胡影响最大的环境因子为最干月降水量,最冷季度平均温度和昼夜温差月均值.预测结果显示,前胡和紫花前胡的潜在分布区比现实分布区更广泛,其中中国秦岭地区、浙江省、湖南省等部分山区为其最佳适生区(适生指数0.71).在台湾、甘肃和西藏等地区分布的差异能为在地域上分辨两者提供理论依据.随着野生资源减少和中药材前胡和紫花前胡需求量的增加,在该地区进行栽培是增加产量,保护野生资源多样性的可行途径.     

基于Maxent模型的原种红椿适生区变迁预测及在引种区划上的应用

利用原种红椿(Toona.ciliata Roem.var.ciliate)在云南实际分布数据及19个生物气象因子数据MaxEnt软件对其在当代、未来(2050、2070 s)气候条件下的适生区分布及面积(包括云南省和全国2种区域尺度)进行预测.原种红椿最大熵模型平均训练AUC值、测试AUC值分别为0.820、0.826,表明该模型对它们适生区的预测精度能达较好水平.最暖季度降水量、昼夜温差月均值、年均温变化范围、最暖季度平均温度、最湿季度降水量、最冷季度平均温度、最冷月最低温、最湿季度平均温度、年均温原种红椿分布的主要因子,在云南省尺度下原种红椿的适生区,特别是中、高度适生区与实际分布高度一致,对它们在该区域内的人工林发展区域的选择具有直接指导意义.在全国尺度下,适生区范围和面积可能大于实际分布,但中、高度适生区与实际分布记录相似度较高,可为其物种保护、异地引种保存提供借鉴作用.另外,与当代相比未来的适生面积变化不大,但有一定幅度增加,说明全球变暖有利于原种红椿繁衍(至少无负面影响).     

基于MaxEnt模型的濒危植物朝鲜崖柏中国潜在适生区预测

将MaxEnt生态位模型与ArcGis技术相结合,根据朝鲜崖柏在我国的准确有效地理分布地点,采用气候、地形和土壤3种环境因子(28个环境变量指标)预测潜在适生区,划分适生区等级,评价适应性.结果表明:朝鲜崖柏在我国的潜在适生分布区可划分为高、中、低适生区,面积分别为3.67×104、6.99×104、33.12×104 km2,分别占中国国土面积的0.38％、0.73％和3.45％.其中,高适生区主要包括吉林省、黑龙江省、辽宁省和新疆维吾尔自治区,主体呈带状分布.影响朝鲜崖柏分布的主导环境因子由大到小依次为最干季度平均温度、最暖季度降水量、海拔、温度季节性变化标准差和最干月降水量.     

基于MaxEnt模型预测马来鳄在中国的潜在生境

为探究马来鳄在中国的潜在适宜生存区及各环境变量对其地理分布的影响，文章基于马来鳄地理分布记录和7个环境变量，应用最大熵(maximum entropy, MaxEnt)模型模拟马来鳄在中国的潜在分布，利用贡献率、置换重要性及Jackknife检验来评估制约马来鳄地理分布的环境变量。结果表明：马来鳄在中国的高度适宜区主要位于广西西南部、广东南部、福建西南部及台湾东北部；影响马来鳄分布的主要气候因子为最暖季度降水量、最冷月份最低温度及最干月份降水量，满足最冷月份最低温度大于21.4℃、最干月份降水量大于116 mm、年气温变化范围在6.6～11.0℃之间、最暖季度降水量保持在550～1 530 mm之间的环境最适宜马来鳄的生存。该研究结果可为马来鳄生物资源的保护和在适宜分布区进行人工繁育提供理论依据。     

珍稀濒危物种金斑喙凤蝶在我国潜在适生区预测

为了明确珍稀濒危物种金斑喙凤蝶(Teinopalpus aureus Mell)在我国的潜在地理分布，基于我国已有的分布记录，结合环境数据，采用MaxEnt模型和ArcGIS软件对其在我国的潜在适生区进行预测分析。结果表明，最暖季平均降水量(bio18)、最冷月份最低温(bio6)、最热月最高气温(bio5)和最湿月降水量(bio13)在金斑喙凤蝶的地理分布中起主要作用。在最暖季平均降水量(bio18)为423~ 1172 mm，最冷月份最低温(bio6)为-7 ~ 14 ℃，最热月最高气温(bio5)为21~39 ℃，最湿月降水量(bio13)为186~ 479 mm的环境条件下适合金斑喙凤蝶生长；在当前气候情景下，预测金斑喙凤蝶主要适生区分布在我国长江以南地区，及台湾和海南等地，面积约为133.27万km2，其中高适生区分布集中在福建、广东、广西、江西、浙江等南亚热带地区，约为39.93万km2面积。本研究模型预测精度高，对金斑喙凤蝶的保护具有较高的参考价值。     

外来观赏植物大花金鸡菊在中国的 潜在地理分布预测

大花金鸡菊(Coreopsis grandiflora Hogg.)被引种后,因具有较强繁殖和适应能力,在我国山东等地区成为入侵物种,对当地植物多样性造成了一定威胁。笔者运用Maxent生态学模型,基于全球海拔变量及19个生物环境变量,结合地理信息系统ArcGIS,对大花金鸡菊在中国的潜在地理分布区做了预测。结果表明,大花金鸡菊在我国的适生范围主要集中在98°～125°E、21.5°～43°N水分充沛、温度适宜的暖温带、亚热带地区。其中,华东、华中大部,即江苏、安徽、上海市、山东等地为大花金鸡菊的集中分布区,为高适生区; 西南、华南北部与华东、华中地区相接的区域,以及华北南部邻接华东地区的局部地区为中适生区,西南、华南南部地区则为低适生区; 其他地区不适于大花金鸡菊生长。ROC 曲线分析表明,Maxent 生态位模型预测大花金鸡菊潜在地理分布的训练数据和测试数据的AUC值分别为0.960和0.965,达到了极高的精度。各环境变量重要性的刀切法检验表明,影响大花金鸡菊地理分布的环境变量依次为年均温、年平均降水量和最冷季平均温度。根据 Maxent 模型预测结果,以及大花金鸡菊的生物学特性和在中国的入侵现状,在我国中东部地区需要采取一定的有效措施对该物种的扩张进行控制。     

暖地大叶藓的气候适应性及其在中国的潜在分布区预测

基于13个环境因子(海拔、植被覆盖率和11个气候因子)和51个地理分布记录数据,预测了暖地大叶藓在中国的潜在地理分布区和其他对13个环境因子的需求特点.结果发现:暖地大叶藓在贵州、云南、重庆、福建、浙江、湖北、四川、湖南、台湾和江西有很高的气候适应性,而在西北、东北和华北的适生能力低;在最冷季节、最干季节、最暖季节的平均温度分别为5~10℃、5~10℃和20~24℃,以及季节雨量变化、植被覆盖度和海拔分别为55~60mm、30%~60%和600~2 500m的区域下,暖地大叶藓具有高的潜在分布概率;随着最湿月份雨量增加和平均昼夜温差的下降,暖地大叶藓的分布概率上升.     

基于MaxEnt模型的小黄花茶在中国的适生区域研究

珍稀植物小黄花茶(Camellia luteoflora Y.K.Li)在自然分布区内数量缩减,存在濒临灭绝的风险.为分析当前气候环境条件下小黄花茶的潜在适宜分布区,本研究运用最大熵(MaxEnt)生态位模型和地理信息系统(ArcGIS)软件对小黄花茶在我国的适生区进行预测,探讨影响其分布的主要环境因子.结果显示,四川泸州、宜宾,贵州遵义,云南昭通、昆明以及重庆江津、綦江是小黄花茶的高度适生区(适生指数0.54),黔、川、渝交界处是其核心分布地.刀切法(Jackknife)检测结果表明,影响小黄花茶分布区的主要环境因子包括最热季平均气温(Bio10)、最热季降水量(Bio18)以及最冷季降水量(Bio19),累计贡献率高达90.8%.适生区环境因子的统计分析结果显示,最热月最高气温为22.5～27.5℃,最热季平均气温为11.1～18.0℃,最湿月降水量为290～500mm,最热季降水量为4.4～6.6mm,最冷季降水量为16.7～24.8mm,海拔为450～1 000m,坡向在-40°～190°范围内,而坡度在20°～64°之间是小黄花茶最适宜生长的生态位参数.本次研究预测了小黄花茶适生区,除已知报道的三处自然分布区外,预测结果显示可能还存在尚未发现的小黄花茶生长地,有待进行实地勘测.     

中国干旱状况的时空分布特征及影响因素

基于高分辨率CRU数据集1950-2009年的逐月资料,计算湿润指数,采用回归分析和偏相关方法分析中国区域干湿变化特征及原因.结果表明,1950-2009年中国总体呈现明显的干旱化趋势,以秋季最为显著;中国降水量呈现微弱的增加趋势(0.04 mm/10 a),潜在蒸发量呈现显著增加趋势(0.71 mm/10 a),潜在蒸发量的显著增加促进了中国干旱化.湿润指数变化的空间分布在东部和西部地区呈相反的趋势,降水量减少而潜在蒸发量增加的共同作用成为东部地区干旱化的直接原因;降水量增加而潜在蒸发量减少(微弱增加)为西部地区干旱适度缓解的直接原因.太阳短波辐射对潜在蒸发量的影响最大,其次为平均温度、水汽压、温度日较差、云量和降水量.     

河南红豆杉属植物地理分布初探

分析了河南境内红豆杉和南方红豆杉分布与年平均温度、最冷月平均温度、最热月平均温度、≥１０℃积温、年降水量等５项气候指标的关系,结果表明：限制其分布的主要气候因子是≥１０℃积温和年降水量,适宜积温约３５００－５０００℃,年降水量７００ｍｍ以上,红豆杉和南方红豆杉分布区北界为南太行山一中条山。     

Characterization of Ordovician carbonate reservoirs, southeastern Saskatchewan, Canada

The discovery of the prolific Ordovician Red River reservoirs in 1995 in southeastern Saskatchewan was the catalyst for extensive exploration activity which resulted in the discovery of more than 15 new Red River pools. The best yields of Red River production to date have been from dolomite reservoirs. Understanding the processes of dolomitization is, therefore, crucial for the prediction of the connectivity, spatial distribution and heterogeneity of dolomite reservoirs.The Red River reservoirs in the Midale area consist of 3～4 thin dolomitized zones, with a total thickness of about 20 m, which occur at the top of the Yeoman Formation. Two types of replacement dolomite were recognized in the Red River reservoir: dolomitized burrow infills and dolomitized host matrix. The spatial distribution of dolomite suggests that burrowing organisms played an important role in facilitating the fluid flow in the backfilled sediments. This resulted in penecontemporaneous dolomitization of burrow infills by normal seawater. The dolomite in the host matrix is interpreted as having occurred at shallow burial by evaporitic seawater during precipitation of Lake Almar anhydrite that immediately overlies the Yeoman Formation. However, the low δ18O values of dolomited burrow infills (-5.9‰～ -7.8‰, PDB) and matrix dolomites (-6.6‰～ -8.1‰, avg. -7.4‰ PDB) compared to the estimated values for the late Ordovician marine dolomite could be attributed to modification and alteration of dolomite at higher temperatures during deeper burial, which could also be responsible for its 87Sr/86Sr ratios (0.7084～0.7088) that are higher than suggested for the late Ordovician seawaters (0.7078～0.7080). The trace amounts of saddle dolomite cement in the Red River carbonates are probably related to "cannibalization" of earlier replacement dolomite during the chemical compaction.     

A computer generator for randomly layered structures

AcomputergeneratorforrandomlylayeredstructuresYUJia shun1,2,HEZhen hua2(1.TheInstituteofGeologicalandNuclearSciences,NewZealand;2.StateKeyLaboratoryofOilandGasReservoirGeologyandExploitation,ChengduUniversityofTechnology,China)Abstract:Analgorithmisintrod…     

An Index mechanism for multi-scale view in spatial databases

There are numerous geometric objects stored in the spatial databases. An importance function in a spatial database is that users can browse the geometric objects as a map efficiently. Thus the spatial database should display the geometric objects users concern about swiftly onto the display window. This process includes two operations:retrieve data from database and then draw them onto screen. Accordingly, to improve the efficiency, we should try to reduce time of both retrieving object and displaying them. The former can be achieved with the aid of spatial index such as R-tree, the latter require to simplify the objects. Simplification means that objects are shown with sufficient but not with unnecessary detail which depend on the scale of browse. So the major problem is how to retrieve data at different detail level efficiently. This paper introduces the implementation of a multi-scale index in the spatial database SISP (Spatial Information Shared Platform) which is generalized from R-tree. The difference between the generalization and the R-tree lies on two facets: One is that every node and geometric object in the generalization is assigned with a importance value which denote the importance of them, and every vertex in the objects are assigned with a importance value,too. The importance value can be use to decide which data should be retrieve from disk in a query. The other difference is that geometric objects in the generalization are divided into one or more sub-blocks, and vertexes are total ordered by their importance value. With the help of the generalized R-tree, one can easily retrieve data at different detail levels.Some experiments are performed on real-life data to evaluate the performance of solutions that separately use normal spatial index and multi-scale spatial index. The results show that the solution using multi-scale index in SISP is satisfying.     

海南岛地体及其毗邻陆缘晚中生代—新生代古地磁研究和构造演化

本文叙述了对海南岛及其毗邻大陆边缘白垩纪到第四纪地层岩石进行古地磁研究的全部工作过程。通过分析岩石中剩余磁矢量的磁偏角及磁倾角的变化,提出海南岛白垩纪以来经历的构造演化模式如下:早期伴随顺时针旋转而向南迁移,后期伴随逆时针转动并向北运移。联系该地区及邻区的地质、地球物理资料,对海南岛上述的构造地体运动提出以下认识:北部湾内早期有一拉张作用,主要是该作用使湾内地壳显著伸长减薄,形成北部湾盆地。从而导致了海南岛的早期构造运动,而海南岛后期的构造运动则主要是受南海海底扩张的影响。海南地体运动规律的阐明对于了解北部湾油气盆地的形成演化有重要的理论和实际意义。     

Exciton Seebeck in Molecular Systems

Various applications relevant to the exciton dynamics,such as the organic solar cell,the large-area organic light-emitting diodes and the thermoelectricity,are operating under temperature gradient.The potential abnormal behavior of the exicton dynamics driven by the temperature difference may affect the efficiency and performance of the corresponding devices.In the above situations,the exciton dynamics under temperature difference is mixed with     

Achieving Unusual States of Matter Under High Pressure

The elongation method,originally proposed by Imamura was further developed for many years in our group.As a method towards O(N)with high efficiency and high accuracy for any dimensional systems.This treatment designed for one-dimensional(ID)polymers is now available for three-dimensional(3D)systems,but geometry optimization is now possible only for 1D-systems.As an approach toward post-Hartree-Fock,it was also extended to     

《Chinese Science Bulletin》SUBJECT INDEX TO VOLUME 59(2014)

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An on-line scaling method for improving scalability of a database cluster

The explosive growth of the Internet and database applications has driven database to be more scalable and available, and able to support on-line scaling without interrupting service. To support more client's queries without downtime and degrading the response time, more nodes have to be scaled up while the database is running. This paper presents the overview of scalable and available database that satisfies the above characteristics. And we propose a novel on-line scaling method. Our method improves the existing on-line scaling method for fast response time and higher throughputs. Our proposed method reduces unnecessary network use, i.e. , we decrease the number of data copy by reusing the backup data. Also, our on-line scaling operation can be processed parallel by selecting adequate nodes as new node. Our performance study shows that our method results in significant reduction in data copy time.     

An improved R-tree based on childnode''s probability

R-Tree is a good structure for spatial searching. But in this indexing structure,either the sequence of nodes in the same level or sequence of traveling these nodes when queries are made is random. Since the possibility that the object appears in different MBR which have the same parents node is different, if we make the subnode who has the most possibility be traveled first, the time cost will be decreased in most of the cases. In some case, the possibility of a point belong to a rectangle will shows direct proportion with the size of the rectangle. But this conclusion is based on an assumption that the objects are symmetrically distributing in the area and this assumption is not always coming into existence. Now we found a more direct parameter to scale the possibility and made a little change on the structure of R-tree, to increase the possibility of founding the satisfying answer in the front sub trees. We names this structure probability based arranged R-tree (PBAR-tree).     

Integrating GIS Web services based on mediating architecture

The geographic information service is enabled by the advancements in general Web service technology and the focused efforts of the OGC in defining XML-based Web GIS service. Based on these models, this paper addresses the issue of services chaining,the process of combining or pipelining results from several interoperable GIS Web Services to create a customized solution. This paper presents a mediated chaining architecture in which a specific service takes responsibility for performing the process that describes a service chain. We designed the Spatial Information Process Language (SIPL) for dynamic modeling and describing the service chain, also a prototype of the Spatial Information Process Execution Engine (SIPEE) is implemented for executing processes written in SIPL. Discussion of measures to improve the functionality and performance of such system will be included.