应用最优分割法划分森林群落演替阶段的研究

本文以闽北山区自然状态下马尾松群落的进展演替过程为代表,讨论了定量划分群落演替阶段的方法。首先从分析树种关联、确定演替种组入手,重构其群落的演替系列,在此基础上采用有序样本的最优分割法将演替过程划分成五个演替阶段,即1．马尾松纯林阶段;2．马尾松、枢木、苦槠群落阶段：3．亮叶腊梅、马尾松、米槠群落阶段;4．米槠、黄瑞木、青冈群落阶段;5．少叶黄杞、细柄阿丁枫、米槠群落阶段。划分结果较真实地反映了马尾松群落向中生性稳定群落的发展过程,克服了主观判断划分方法的缺陷,在定量的水平上处理群落演替阶段的划分问题。     

桃园害虫及天敌群落动态研究

通过对桃园害虫天敌群落的系统调查,应用主分量分析法、最优分割法和模糊聚类分析方法进行分析．结果表明,群落具有明显的主导因素和时间格局;对桃园节肢动物群落55种节肢动物的数量变化进行模糊聚类分析,选置信水平λ＝0．47,将其分为4个时期,利用最优分割法,将害虫天敌的发生量分为3段,利用主分量分析法,明确了主要害虫及其天敌种类．     

梨园芳香植物间作区节肢动物群落时序格局

以沙地梨园间作罗勒、孔雀草、薄荷为处理,自然生草和清耕区为对照,应用最优分割法和模糊聚类法,探讨梨园节肢动物群落、害虫亚群落和天敌亚群落发生的时序格局特征及其相互联系。结果表明:总群落、害虫亚群落以及其优势种个体数时序变化趋势呈偏态分布,而天敌亚群落以及其优势种个体数的呈正态分布,高峰期出现在6月末至7月中旬,比总群落和害虫亚群落个体数发生高峰晚。在梨树年生长周期的主要时段中,芳香植物间作区较自然生草区、清耕区害虫亚群落的发生数量(4月中至8月底)少;而天敌亚群落发生数量(4月底至6月底)多。梨园各间作区节肢动物总群落和害虫亚群落时序最优格局均可划分5个时段:发展初期、发展期、稳定期、波动期和衰退期;天敌亚群落分为3个时段:发展期、稳定期、衰退期。但处理间在发生时段的时间范围、发生数量及组成特征上存在复杂的差异。梨园节肢动物总群落、害虫亚群落、天敌亚群落时序聚类结果不同,预示着处理间节肢动物总群落、害虫亚群落和天敌亚群落在各发生时段上的个体组成、物种丰富度、群落多样性指数、优势度和均匀度指数存在着差异。     

石榴园节肢动物群落的聚类分析及最优分割研究

根据群落生态学原理。为了利用天敌资源开展石榴园害虫的生物防治,明确主要害虫及其天敌发生的时间动态和数量动态,对不同时期的石榴园节肢动物总群落、亚群落进行了模糊聚类．结果表明,总群落的8次调查结果可聚为4类,D=0．05;天敌亚群落调查结果可聚为4类,D=0．10;非天敌亚群落调查结果可聚为3类,D=0．09．聚类部分反映了总群落和亚群落各自的状况。聚类交替现象则反映了群落结构在较长时间内的复杂性．最优分割结果将不同时期的总群落、各亚群落均分割为3段(4～8月、9～10月、11～11月)。表明各阶段物种种类、物种数及优势种等指标在发生时间上存在差异．     

忍冬害虫及其天敌群落的定量分析

【目的】明确泰安地区忍冬害虫与天敌的群落数量特征,为忍冬害虫的防治及其天敌的保护利用提供科学理论依据。【方法】于2017年和2018年对忍冬害虫及其天敌进行了系统抽样调查,基于害虫及其天敌的数量信息,对调查数据进行了群落主成分分析、典型相关分析和有序样本最优分割。【结果】通过主成分分析,明确了不同时期起主要作用的害虫及其天敌种类,主要害虫有胡萝卜微管蚜Semiaphis heraclei、棉蚜Aphis gossypii、烟粉虱Bemisia tabaci、金银花尺蠖Heterolocha jinyinhuaphaga和金银花叶蜂Argesimiles等,天敌主要有龟纹瓢虫Propylaeajaponica、异色瓢虫Harmoniaaxyridis、三突伊氏蛛Ebrechtella tricuspidata、黄褐新园蛛Neoscone doenitzi、鞍形花蟹蛛Xysticus ephippiafus、食虫蝽类、捕食螨类和食蚜蝇类等。典型相关分析体现出主要害虫及其天敌类群之间存在显著相关性（P<0.01）,食蚜蝇类、瓢虫类和草蛉类与蚜虫类（胡萝卜微管蚜）相关程度高;食虫蝽类与鳞翅目害虫（金银花尺蠖）和烟粉虱的相关程度高;蜘蛛类与植食性蝽类、叶蝉类、烟粉虱和鳞翅目害虫的相关程度高;捕食螨类与植食性蝽类、烟粉虱和鳞翅目害虫的相关程度高。有序样本最优分割表明,害虫与天敌群落时间格局均划分为4个时段,不同时段内害虫及其天敌的发生特点有明显差异,对各时段的害虫与相应的天敌进行了分析。【结论】研究结果对忍冬害虫的防治和天敌的保护利用具有重要指导意义。     

油茶中幼林昆虫群落结构及时序格局

[目的]明确油茶中幼林昆虫群落、害虫亚群落和天敌亚群落的结构特征、时序格局及其相互关联。[方法]于2014年6月—2015年5月,采用固定样地五点取样法对5~6年生油茶中幼林昆虫群落进行了系统调查,并运用最优分割法和模糊聚类法对收集数据进行了分析。[结果]共记录油茶中幼林昆虫1 648头,隶属10目62科137种,其中害虫83种、天敌昆虫36种。6月初和10月中旬害虫的物种数、个体数、多样性指数均达到最大值,天敌与害虫的发生出现不明显的滞后现象,传粉昆虫10月下旬活动最为频繁。将害虫亚群落划分为9个区段,发展期-波动期-稳定期-衰退期-过渡期-发展期-波动期-稳定期-衰退期;天敌亚群落被划分为6个区段,发展期-稳定期-衰弱期-发展期-稳定期-衰弱期;昆虫总群落划分为4个区段,发展期-波动期-稳定期-衰退期,各区段的特点与作物物候期和各个亚群落的发生特点均存在不同程度的关联。油茶中幼林害虫亚群落、天敌亚群落、昆虫总群落时序聚类结果基本相同,均被划分为三类:发展期、稳定期和衰弱期,只是在各个期间不同群落的发生时间略有差别。[结论]油茶中幼林昆虫物种丰富,昆虫群落结构在一年中具有间断性、连续性和复杂性,5月中旬和9月中下旬是油茶害虫管理的关键时期。     

李园节肢动物群落时间动态的聚类分析

为了了解李园节肢动物群落的结构、特征,发挥生态系统中自然因素对害虫的生态调控作用,采用系统调查方法,在分析李园节肢动物群落结构和组织水平的基础上,对李园节肢动物群落的时间动态进行聚类分析,结果表明,对不同时期的总群落、亚群落进行模糊聚类得出结果,总群落的12次调查结果可以聚为5类,D=0.2000,3、11、7和6月初各自归为一类,其余归为一类.天敌亚群落调查结果也聚为5类,D=0.2000,3、7、8月各自归为一类,9月和10月归为一类,其余归为一类.非天敌亚群落调查结果同样聚为5类,D=0.1000,4、7、6、11月各自归为一类,其余归为一类.聚类结果部分反映了群落状况的季节差异,聚类交替现象反映了群落结构复杂性.最优分割结果将总群落、各亚群落均分割为5个阶段,即4月6日为第一阶段,4月27日～6月8日为第二阶段,6月27日～8月27日为第三阶段,9月21日～10月19日为第四阶段,11月22日为第5阶段.反映了各阶段物种种类、数量等其他指标在发生时间上存在的差异.     

有序样方聚类在植被垂直划分中的应用

 本文介绍一种非等级分类方法——有序样方聚类法,并将其应用于山西绵山植被垂直带的划分,结果为：1,落叶阔叶林带(包含3个亚带：Ⅰ．落叶阔叶灌丛亚带,Ⅱ．松栎林亚带,Ⅲ．落叶阔叶林亚带),2．寒温性针叶林带和3,亚高山草甸带。基于黄金分割法(或Fisher’s法)的有序样方聚类法,是按照样方在空间(或时间)先后出现的序号和组内相似性最大,组间相似性最小的标准,对样方进行分类,因此,所得结果是最优的。与TWINSPAN的结果比较,在绵山植被遭到严重扰动的情况下,有序样方聚类要优于TWINSPAN。     

模糊聚类分析法及其在群落聚类分析中的应用

以不同种类蔬菜菜地节肢动物群落作为研究对象,介绍模糊聚类分析法在群落相似性分析中的应用。得到如下的结果：在建立模糊等价关系的基础上,根据不同的需要,当λ取０．８９９时,聚合成３个类群,当λ为０．８５２时,聚合成２个类群。而Ｆ－ＰＦＳ聚类分析法则根据群落在聚类类群之间或其中的散布情况,从所有的聚类结果中,选择最佳的聚类方案。本文材料的最佳的聚类结果为：把群落聚合成２类。类群１包括：菜心、小白菜、奶白菜、芥菜、芥兰、通菜、豇豆、四季豆上的节肢动物群落;类群２包括：藤菜与苋菜上节肢动物群落。     

有机化梨园节肢动物群落时间动态的聚类分析

对北京顺义地区有机化梨园中2个不同栽培区节肢动物总群落、害虫及天敌亚群落分别进行时间动态的系统聚类。结果表明,在同一园区内,稀植区和密植区均以木虱为优势种类,相对丰盛度分别达0.3801、0.3300。总群落的24次调查结果稀植区可聚为5类,D=1.87,密植区聚为3类,D=1.80;害虫亚群落调查结果,当两区D=1.80时,稀植区可聚为3类,密植区可聚为4类;天敌亚群落调查结果稀植区聚为4类,D=2.12,密植区聚为5类,D=1.75。在早春的密植区和入秋的稀植区木虱发生量大,应加强监测,及时防治。     

Fast optimal leaf ordering for hierarchical clustering

We present the first practical algorithm for the optimal linear leaf ordering of trees that are generated by hierarchical clustering. Hierarchical clustering has been extensively used to analyze gene expression data, and we show how optimal leaf ordering can reveal biological structure that is not observed with an existing heuristic ordering method. For a tree with n leaves, there are 2(n-1) linear orderings consistent with the structure of the tree. Our optimal leaf ordering algorithm runs in time O(n(4)), and we present further improvements that make the running time of our algorithm practical.     

RECORD: a novel method for ordering loci on a genetic linkage map

A new method, REcombination Counting and ORDering (RECORD) is presented for the ordering of loci on genetic linkage maps. The method minimizes the total number of recombination events. The search algorithm is a heuristic procedure, combining elements of branch-and-bound with local reshuffling. Since the criterion we propose does not require intensive calculations, the algorithm rapidly produces an optimal ordering as well as a series of near-optimal ones. The latter provides insight into the local certainty of ordering along the map. A simulation study was performed to compare the performance of RECORD and JoinMap. RECORD is much faster and less sensitive to missing observations and scoring errors, since the optimisation criterion is less dependent on the position of the erroneous markers. In particular, RECORD performs better in regions of the map with high marker density. The implications of high marker densities on linkage map construction are discussed.     

Dynamic assessment of environmental damage based on the optimal clustering criterion – Taking oil spill damage to marine ecological environment as an example

Aimng at the evaluation of environmental damages, we proposed a dynamic evaluation approach based on the optimal cluster criterion. Firstly, a method for sample data standardization was introduced. After determining the measurement of damage grade, we applied the system cluster analysis approach to classify the grades of corresponding environmental pollution events. Then, the optimal cluster level was evaluated based on the optimal clustering criterion. By using the marine environmental damages caused by 17 marine oil spill events as a sample, we tested the dynamic evaluation method proposed in this article with its practicability. Further, by comparing it with some traditional damage evaluation methods, we found that their evaluation results were consistent. All these have shown that the dynamic evaluation approach proposed in this paper can meet the requirement of environmental damage evaluation. Finally, directions of future researches were pointed out.     

Gene ordering in partitive clustering using microarray expressions

A central step in the analysis of gene expression data is the identification of groups of genes that exhibit similar expression patterns. Clustering and ordering the genes using gene expression data into homogeneous groups was shown to be useful in functional annotation, tissue classification, regulatory motif identification, and other applications. Although there is a rich literature on gene ordering in hierarchical clustering framework for gene expression analysis, there is no work addressing and evaluating the importance of gene ordering in partitive clustering framework, to the best knowledge of the authors. Outside the framework of hierarchical clustering, different gene ordering algorithms are applied on the whole data set, and the domain of partitive clustering is still unexplored with gene ordering approaches. A new hybrid method is proposed for ordering genes in each of the clusters obtained from partitive clustering solution, using microarray gene expressions.Two existing algorithms for optimally ordering cities in travelling salesman problem (TSP), namely, FRAG_GALK and Concorde, are hybridized individually with self organizing MAP to show the importance of gene ordering in partitive clustering framework. We validated our hybrid approach using yeast and fibroblast data and showed that our approach improves the result quality of partitive clustering solution, by identifying subclusters within big clusters, grouping functionally correlated genes within clusters, minimization of summation of gene expression distances, and the maximization of biological gene ordering using MIPS categorization. Moreover, the new hybrid approach, finds comparable or sometimes superior biological gene order in less computation time than those obtained by optimal leaf ordering in hierarchical clustering solution.     

An Objective Method for Measurement of Sedentary Behavior in 3‐ to 4‐Year Olds

Objective: To test the ability of accelerometry to quantify sedentary behavior in 3‐ to 4‐year‐old children. Research Methods and Procedures: We developed a cut‐off for accelerometry output (validation study) in 30 healthy 3 to 4 year olds, which provided highest sensitivity and specificity for the detection of sedentary behavior relative to a criterion method of measurement, direct observation using the children's physical activity form. We then cross‐validated the cut‐off in an independent sample of healthy 3 to 4 year olds (n = 52). Results: In the validation study, optimal sensitivity and specificity for the detection of sedentary behavior were obtained at an accelerometry output cut‐off of <1100 counts/min. In the cross‐validation, sensitivity was 83%: 438/528 inactive minutes were correctly classified. Specificity was 82%: 1251/1526 noninactive minutes were correctly classified using this cut‐off. Discussion: Sedentary behavior can be quantified objectively in young children using accelerometry. This new technique could be considered for a wide variety of applications in the etiology, prevention, and treatment of childhood obesity.     

MC-Net: a method for the construction of phylogenetic networks based on the Monte-Carlo method

Background  

A phylogenetic network is a generalization of phylogenetic trees that allows the representation of conflicting signals or alternative evolutionary histories in a single diagram. There are several methods for constructing these networks. Some of these methods are based on distances among taxa. In practice, the methods which are based on distance perform faster in comparison with other methods. The Neighbor-Net (N-Net) is a distance-based method. The N-Net produces a circular ordering from a distance matrix, then constructs a collection of weighted splits using circular ordering. The SplitsTree which is a program using these weighted splits makes a phylogenetic network. In general, finding an optimal circular ordering is an NP-hard problem. The N-Net is a heuristic algorithm to find the optimal circular ordering which is based on neighbor-joining algorithm.     

A New Technique Facilitating Studies of Scant Cell Specimens

A simple method is described by which multiple cytological and cytochemical studies can be done on a clinical sample that contains relatively few cells. The cells are concentrated by centrifugation. The cell pellet is fixed, frozen and embedded in plastic. Thin (2-μm) sections are cut from the plastic. Thus, each cell may appear in several sections and many slides can be made from a single specimen. The advantages of this method over cytospins and Millipore filter preparations of cell suspensions are optimal utilization of all cells, excellent morphological and immunological preservation and ease and reproducibility of this technique.     

A new method of sample application for horizontal slab polyacrylamide gel electrophoresis

A new method of sample application for horizontal slab polyacrylamide gel electrophoresis has been developed which solves the main problems associated with existing systems. A quick, simple procedure is described for placing a dry powder mixture of Celite and Sephadex into sample wells of any shape cut to the full depth of the gel slab. Samples can then be added to the powder to form a moist firm bed of material in the wells which prevents leakage of sample from the well. The method enables the quantitative electrophoresis of many samples with widely differing concentrations and volumes without the problems of electrodecantation, loss of electrical contact through the wells, or uneven penetration of sample through the full thickness of the gel.     

Sorting points into neighborhoods (SPIN): data analysis and visualization by ordering distance matrices

SUMMARY: We introduce a novel unsupervised approach for the organization and visualization of multidimensional data. At the heart of the method is a presentation of the full pairwise distance matrix of the data points, viewed in pseudocolor. The ordering of points is iteratively permuted in search of a linear ordering, which can be used to study embedded shapes. Several examples indicate how the shapes of certain structures in the data (elongated, circular and compact) manifest themselves visually in our permuted distance matrix. It is important to identify the elongated objects since they are often associated with a set of hidden variables, underlying continuous variation in the data. The problem of determining an optimal linear ordering is shown to be NP-Complete, and therefore an iterative search algorithm with O(n3) step-complexity is suggested. By using sorting points into neighborhoods, i.e. SPIN to analyze colon cancer expression data we were able to address the serious problem of sample heterogeneity, which hinders identification of metastasis related genes in our data. Our methodology brings to light the continuous variation of heterogeneity--starting with homogeneous tumor samples and gradually increasing the amount of another tissue. Ordering the samples according to their degree of contamination by unrelated tissue allows the separation of genes associated with irrelevant contamination from those related to cancer progression. AVAILABILITY: Software package will be available for academic users upon request.     

Mid‐P confidence intervals for group testing based on the total number of positive groups

In the estimation of proportions by group testing, unequal sized groups results in an ambiguous ordering of the sample space, which complicates the construction of exact confidence intervals. The total number of positive groups is shown to be a suitable statistic for ordering outcomes, provided its ties are broken by the MLE. We propose an interval estimation method based on this quantity, with a mid‐P correction. Coverage is evaluated using group testing problems in plant disease assessment and virus transmission by insect vectors. The proposed method provides good coverage in a range of situations, and compares favorably with existing exact methods.