大院资源冷杉种群的空间分布格局分析

资源冷杉是极度濒危的我国特有植物,其中的湖南省炎陵县大院资源冷杉种群是种群规模最大的种 群.该研究采用点格局分析方法分析了该种群的种群分布格局,用计盒维数和信息维数研究了种群格局的分形特征.结果表明:大院资源冷杉种群的空间分布格局总体上呈聚集分布;种群的计盒维数在1.047～1.354 之间,种群占据空间程度较弱;...     

应用d2检验分析植物分布格局

个体在群落中的随机分布等价于随机点在二维平面上的分布。因此Gruenberger和Mark的d~2检验也可以应用于种群分布格局检验。本文应用这个方法,研究了荒漠超旱生植物红砂的种群分布格局,得到了红砂的分布格局是均匀的。     

鄂尔多斯高原油蒿种群分布格局对降水梯度的反应

应用方差均值比率法、聚块性指数及点格局方法,沿着鄂尔多斯高原从东至西的降水梯度(336～249 mm·a^-1),设置5个采样点,对油蒿种群分布格局及其对降水梯度的反应进行了研究.结果表明：随着降水梯度的递减,在小尺度上研究区油蒿种群分布格局表现为由均匀分布向随机分布转变;在大尺度上则表现为由随机分布向聚集分布转变.降雨的减少显著改变了油蒿种群的空间分布格局,在进行生态恢复时需对植物个体进行合理配置.     

长白松自然同龄种群分布格局的研究

以长白松（Ｐｉｎｕｓｓｙｌｖｅｓｔｒｉｆｏｒｍｉｓ）种群为例,通过种群发展历史、种群大小结构研究,发现种群的胸径服从正态分布Ｎ（１６．８７,６．８０２）,确认该种群为自然同龄种群．种群的空间分布格局呈很高的均匀性,趋于随机分布甚至均匀分布,分布格局动态表现出由均匀分布向随机分布变化的趋势．     

祁连山北坡高寒草地狼毒种群格局

在祁连山北坡高寒退化草地,采用空间序列代替时间序列与点格局相结合的分析方法,研究了小尺度上狼毒种群的组成特征和分布格局.结果表明:伴随狼毒分盖度的增加,狼毒植株数总体上呈现先增大后减小的分布规律;幼株分布格局由随机分布向聚集分布过渡,聚集强度表现出先增强后减弱的规律,成株分布格局基本表现为随机分布;狼毒分盖度较低时,不同大小级狼毒种群在0～100 cm尺度上均表现为随机分布,狼毒分盖度较高时,随着种群的发育,分布格局由聚集分布向随机分布过渡.种群的分布格局与种群的扩散阶段存在密切的关系,狼毒种群通过斑块合并、斑块吞并以及竞争作用和协同作用的相互转化实现种群的扩散.     

浙江仙居俞坑森林群落优势种群结构与分布格局研究

以浙江仙居俞坑森林群落为研究对象,用“空间序列代替时间变化”的方法,对该群落优势种群的结构和动态进行了分析,结果是：各优势种群中常绿阔叶树种的大小级分布图的形状基本相似,种群存活曲线均表现为极显著的线性关系,种群的年龄结构为稳定型。地树种拟赤杨的年龄结构为衰退型。甜槠、青冈栎、红楠种群的分布格局均呈集群分布,木荷、虎皮楠种群的分布格局多为随机分布,拟赤杨呈随机分布或均匀分布。甜槠种群的幼苗、幼树的     

植物群落种群分布格局研究的新方法

本文给出一种研究植物群落种群分布格局的新方法。该方法与英国著名生态学家Greig-Smith提出的“邻接格子样方法”相比较,具有如下优点: 1.用计算机算出的结果,具有令人满意的精度。当计算完毕后,机器能打印输出植物种群斑块大小、斑块在样地平面上分布的状况,样地上某种植物斑块的总面积,种群个体的总数等有关信息。 2.适用于天然植物群落种群分布格局的研究。 本文讨论了处理数据时采用的计算公式,所依据的数学原理以及如何确定输出界限(舍入界限)等问题。 此外,文中还叙述了用该法对随机相嵌几何斑块图形,人工模拟草地样方进行处理的过程和计算结果分析。 源程序是用BASIC语言编制的。     

云南元谋干热河谷膏桐天然更新种群结构与分布格局研究

研究了云南元谋干热河谷膏桐(Jatropha curcas L.)天然更新种群结构及其分布格局,旨在分析此生境下该种群的年龄结构类型、分布格局特点及其影响因素。采用空间序列代替时间变化的方法,分析了种群的大小级结构;应用扩散系数、Morisita 指数、Green 指数、平均拥挤度、负二项式参数K判断分析了种群格局状况;应用Greith-Smith方法分析了种群格局规模。结果表明:(1)膏桐种群的幼苗数量众多,占总体数量的79.84%左右,远远超过其它4个发育阶段(幼树、小树、中树、大树)的数量,而大树数量非常稀少。种群大小级结构呈金字塔形,属于增长型种群。(2)总体而言,该种群的空间分布格局为集群分布。不同发育阶段种群的分布格局有差异。随着年龄增长,总体上表现为由集群分布向随机分布转变,并且这种转变多发生在中树以及大树这两个阶段。(3)不同样地种群的分布格局规模不尽相同,本研究揭示出的斑块规模为50 m²和100 m²左右。     

小兴安岭阔叶红松林物种组成及主要种群的空间分布格局

研究了黑龙江省凉水国家自然保护区阔叶红松林的物种组成和径级结构,并应用点格局分析方法对其主要种群的空间分布格局及空间关联性进行了研究.结果表明: 该保护区内阔叶红松林中胸径≥1 cm的乔木共有16种,种群密度差异性很大,针叶树种红松和冷杉处于明显的优势地位;种群的径级结构近似倒“J”形,林分更新良好;主要种群的分布格局多呈聚集分布,只有红松在19～21 m和44 m尺度上以及青楷槭在接近所研究的最大尺度上时才呈现出随机分布.其中,红松在所研究尺度上一直都接近于随机分布,聚集强度也最小,冷杉、紫椴和青楷槭的分布格局都呈现出随机分布的趋势;除红松和冷杉在2～3 m的小尺度上,以及冷杉和青楷槭在37～81 m尺度上呈显著正相关外,其余种群的空间关联性均不显著.所有树种的总体联结关系均表现为不显著的正关联.
     

安徽黄山甜槠种群的结构与分布格局

通过对安徽黄山甜槠〔Ｃａｓｔａｎｏｐｓｉｓｅｙｒｅｉ（Ｃｈａｍｐ．ｅｘＢｅｎｔｈ．）Ｔｕｒｔｃｈ．〕种群大小级、存活曲线和分布格局的研究,探讨了该地区甜槠种群的结构和分布格局特征。结果表明甜槠种群具有增长型和平稳增长型的动态特征;同时,甜槠种群呈集聚分布格局,这可能与甜槠的生物学特性有关;但在不同发育阶段,种群分布格局不同,随着种群年龄的增加和径级的增大,分布格局由集聚分布变为随机分布,这可能主要由于种内和种间竞争引起的种群数量动态变化所致。或许这也是甜槠种群的生存策略之一。     

芦芽山亚高山草甸优势种群和群落的二维格局分析

种群和群落的二维空间格局研究能够更好地揭示群落的空间和结构特征,但在分析方法上有较大的困难。用垂直相交的两条样带在两个方向上同时取样的二维取样法,获得数据,用一维格局分析方法分别分析,可以得到各个种不同格局规模斑块的长、宽及面积,实现二维格局研究。用DCA排序和格局分析方法相结合,可以完成群落的二维格局分析。在山西芦芽山亚高山草甸应用的结果表明这样的垂直样带二维取样及分析方法较好地反映了种群和群落的空间特性,是非常有效的,并且该方法简单易做,具有较大的可操作性。所研究的草甸主要优势种格局斑块的形状比较规则,面积也较大。次要种斑块多为不规则形,面积也较小。群落格局与主要优势种的格局关系密切。     

Two-dimensional pattern analysis on dominant species and community in subalpine meadow of Luya Mountain,Shanxi Province,China

The spatial pattern analysis of population and community is important to understand community structure and has become one key topic in modern plant ecology.There are many techniques for analyzing one-dimensional pattern in ecological literature.Two-dimensional pattern analysis is better than one-dimensional analysis in the study on community spatial characteristics and structure.However,it is hard to analyze these two-dimensional patterns due to poor effective methodology.The two-dimensional sampling using two transects that meet at right angles was applied to get quadrat data in this work.And then the data from the two transects were analyzed separately by one-dimensional pattern analysis method,two-term local quadrat variance.The length,width,and area of patches at different scales of pattern for populations were obtained from the analysis.For community pattern,detrended correspondence analysis (DCA)was employed to summarize the species information firstly,and then the first DCA axis scores were analyzed to check its pattern.The application of this method to the pattern analysis on dominant populations and community for subalpine meadow (Comm.Polygonum viviparum+Carex rigescens+Kobresia bellardii)in the Luya mountains showed that it could release the characteristics of spatial pattern clearly and was a very effective technique.The method is easy to use and saves time with obvious advantages,compared with the twodimensional pattern analysis methods presented in the literatures.In the study meadow,the patterns of the main dominant species,Polygonum viviparum,Carex rigescens,and Kobresia bellardii,were apparent and comparatively regular in shape with large areas of patches at the same scale compared with other species such as Festuca sp.and Thalictrum petaloideum.There were two or three scales of patterns for each plant population studied.This was related to population features,the interaction with environmental factors,and their dominant position in the community.The two scales of patterns for the meadow community were clear.The pattern of community was closely correlated with that of the main dominant species.The patches of dominant species were inter-distributed and overlapped,and formed the community pattern together.This is beneficial for utilization of resources,and keeping the community stable.     

A graphical method to determine the ordering of moult,illustrated with data from the Blackshouldered Kite Elanus caeruleus

When the order in which feathers moult is not constant and the pattern is complex, it is difficult to discover the usual pattern simply by inspecting the data. This paper illustrates a method, the Gower analysis, that produces a graphical plot from which it is relatively easy to deduce the usual ordering.     

Two-dimensional pattern analysis on dominant species and community in subalpine meadow of Luya Mountain, Shanxi Province, China

The spatial pattern analysis of population and community is important to understand community structure and has become one key topic in modern plant ecology. There are many techniques for analyzing one-dimensional pattern in ecological literature. Two-dimensional pattern analysis is better than one-dimensional analysis in the study on community spatial characteristics and structure. However, it is hard to analyze these two-dimensional patterns due to poor effective methodology. The two-dimensional sampling using two transects that meet at right angles was applied to get quadrat data in this work. And then the data from the two transects were analyzed separately by one-dimensional pattern analysis method, two-term local quadrat variance. The length, width, and area of patches at different scales of pattern for populations were obtained from the analysis. For community pattern, detrended correspondence analysis (DCA) was employed to summarize the species information firstly, and then the first DCA axis scores were analyzed to check its pattern. The application of this method to the pattern analysis on dominant populations and community for subalpine meadow (Comm. Polygonum viviparum + Carex rigescens + Kobresia bellardii) in the Luya mountains showed that it could release the characteristics of spatial pattern clearly and was a very effective technique. The method is easy to use and saves time with obvious advantages, compared with the two-dimensional pattern analysis methods presented in the literatures. In the study meadow, the patterns of the main dominant species, Polygonum viviparum, Carex rigescens, and Kobresia bellardii, were apparent and comparatively regular in shape with large areas of patches at the same scale compared with other species such as Festuca sp. and Thalictrum petaloideum. There were two or three scales of patterns for each plant population studied. This was related to population features, the interaction with environmental factors, and their dominant position in the community. The two scales of patterns for the meadow community were clear. The pattern of community was closely correlated with that of the main dominant species. The patches of dominant species were inter-distributed and overlapped, and formed the community pattern together. This is beneficial for utilization of resources, and keeping the community stable. __________ Translated from Acta Ecologica Sinica, 2005, 25(6): 1264–1268 [译自: 生态学报]     

Computational genetics: from mouse to human?

In this article, we describe a novel computational-analysis method that rapidly identified the genetic basis for several trait differences among inbred mouse strains. This approach enables researchers to identify a causative genetic factor by correlating a pattern of observable physiological or pathological differences among selected inbred strains with a pattern of genetic variation. Compared with conventional methods used for mouse genetic analysis, which require many years to produce results, this haplotype-based computational analysis can be rapidly performed. We discuss the factors affecting the performance and precision of this computational method. Although it currently can analyze traits of limited genetic complexity in mouse, the potential application of this genetic-analysis method to other experimental organisms, and possibly humans, is evaluated.     

IKONOS影像景观格局特征尺度的小波与半方差分析

建立不同方向和尺度下景观格局的小波分析方法,并以IKONOS PAN 1m 影像为例,对城市景观和农田景观格局进行了实例研究,并与半方差函数的分析结果进行比较分析。试验结果发现试验区的城市景观图像表现出不同层次和方向的结构特征,主要是阴影－单个楼房－楼房与道路的组合3个尺度的特征,分别出现在2m,16m和128m以及256m分析尺度上,农田景观主要是树木行－农田2个层次和方向尺度特征组合,分别为2m,128m和256m。半方差分析结果对试验区景观结构的多层次和方向不敏感,但可发现景观结构的总体平均特征。城市景观总体结构在空间上的变程为135m,反映的是楼房与道路组合的总体平均特征;农田景观总体结构在空间上的变程为152m。通过改变半方差函数的分析范围和计算间距可以克服半方差对多尺度分析的不足,如该试验通过缩小城市景观和农田分析范围,也发现城市景观有一个在空间结构上15m的变程,与小波分析的特征尺度16m非常接近,而农田景观出现空穴效应的周期一半长度大约为2m,正好是小波分析出种植树木的行距结构特征尺度的大小。这要分析者对研究有一定的先验知识才能够做到选择合适的分析范围,而这恰是景观格局特征尺度分析服务的目的。通过试验区研究证明小波分析是一非常有应用前景的景观格局研究方法,与半方差分析相比,对在解释多尺度结构和不同方向的结构具有明显的优势,且不受分析数据统计平稳假设的约束,但由于对图像分解是基于2进制,导致分析尺度以2的幂函数变化,不像半方差分析可通过理论模型拟合,对特征尺度的估计可以是连续的。     

Principal component analysis of complex multijoint coordinative movements

Principal components analysis (PCA) has not been very much in vogue within the field of movement coordination even though it is useful to reduce data dimensionality and to reveal underlying data structures. Traditionally, studies of coordination between two joints have predominantly made use of relative phase analyses. This has resulted in the identification of principal constraints that govern the Central Nervous System’s organization and the control of coordination patterns. However, relative phase analyses on pairwise joints have some drawbacks because they are not optimal for revealing convergent patterns among multijoint coordination modes and for unraveling generic control strategies.In this paper, we present a method to analyze multijoint coordination based on the properties of PC, more specifically the eigenvalues and eigenvectors of the covariance matrix.The comparison between relative phase analysis and PCA shows that both provide similar and consistent results, underscoring the latter technique’s sensitivity to the study of coordination performance. In addition, it provides a method for automatic pattern detection as well as an index of performance for each joint within the context of the global coordination pattern.Finally, the merit of the PCA technique within the context of central pattern generators (CPG) will be discussed.     

用模式识别方法预测膜蛋白RC、BR和RH的二级结构

膜蛋白的结构预测在目前比较困难.本文利用已建立的模式识别方法预测了三个典型的膜蛋白RC,BR和RH的二级结构,预测结果与实验资料的符合率与该方法用于球蛋白时的结果相仿,是成功的.本文进一步完善了模式识别预测蛋白质二级结构的方法.建立了针对球蛋白二级结构预测的多分类方法,预测精度大于60%.事实证明这是一种较好的结构预测方法,鉴于目前国内外运用模式识别方法进行结构预测研究的还不多见,我们拟进一步发展完善这一方法.     

Recognition of characteristic patterns in sets of functionally equivalent DNA sequences

An algorithm has been developed for the identification of unknownpatterns which are distinctive for a set of short DNA sequencesbelieved to be functionally equivalent. A pattern is definedas being a string, containing fully or partially specified nucleotidesat each position of the string. The advantage of this ‘vague’definition of the pattern is that it imposes minimum constraintson the characterization of patterns. A new feature of the approachdeveloped here is that it allows a ‘fair’ simultaneoustesting of patterns of all degrees of degeneracy. This analysisis based on an evaluation of inhomogeneity in the empiricaloccurrence distribution of any such pattern within a set ofsequences. The use of the nonparametric kernel density estimationof Parzen allows one to assess small disturbances among thesequence alignments. The method also makes it possible to identifysequence subsets with different characteristic patterns. Thisalgorithm was implemented in the analysis of patterns characteristicof sets of promoters, terminators and splice junction sequences.The results are compared with those obtained by other methods. Received on November 17, 1986; accepted on June 15, 1987     

南亚热带森林种群分布格局取样技术研究

森林群落中植物种群分布格局测定和分析的结果,密切依赖于野外取样的技术手段及资料的可靠性。本文通过鼎湖山自然保护区三个不同森林群落类型的取样,比较了随机样方、相邻格子样方、中心点四分法、最近相邻法和最近个体法在野外操作、数据整理以及种群分布格局测定分析中的效用,对各方法在南亚热带森林群落中进行种群分布格局研究中的适用性予以客观评价。研究表明,同一样地中不同取样方法和测定方法会导致不同结果。随机样方取样数据的测定结果受样方大小影响,而几种无样地方法在种类复杂的群落中,应用受到限制。相邻格子样方适用于各群落类型中种群分布格局的测定与分析。