中国葡萄属植物形态学聚类分组研究

对《中国葡萄志》描述的38个中国葡萄属野生种和1个栽培种,按照《葡萄种质资源描述规范和数据标准》的要求,对18个描述符用代码数量化并进行聚类分析,根据形态特征的相似程度,将我国葡萄属野生种和欧亚种划分为8个组和5个亚组。第1组包含毛葡萄、腺枝葡萄、龙泉葡萄、美丽葡萄和庐山葡萄,第2组包含麦黄葡萄和小叶葡萄,第3组包含5个亚组21个种类,其中亚组1包含山葡萄、陕西葡萄、浙江蘡薁、蘡薁和湖北葡萄,亚组2包含绵毛葡萄和勐海葡萄,亚组3包含小果葡萄、云南葡萄和葛藟葡萄,亚组4包含毛脉葡萄、华东葡萄、武汉葡萄和井冈葡萄,亚组5包含刺葡萄、秋葡萄、桦叶葡萄、网脉葡萄、蒙自葡萄、凤庆葡萄和河口葡萄,第4组仅包含欧洲葡萄,第5组包含温州葡萄、红叶葡萄、复叶葡萄、乳源葡萄和狭叶葡萄,第6组包含东南葡萄、罗城葡萄和闽赣葡萄,第7组仅包含菱叶葡萄,第8组仅包含鸡足葡萄一个种。     

Multivariate regression trees for analysis of abundance data

Multivariate regression tree methodology is developed and illustrated in a study predicting the abundance of several cooccurring plant species in Missouri Ozark forests. The technique is a variation of the approach of Segal (1992) for longitudinal data. It has the potential to be applied to many different types of problems in which analysts want to predict the simultaneous cooccurrence of several dependent variables. Multivariate regression trees can also be used as an alternative to cluster analysis in situations where clusters are defined by a set of independent variables and the researcher wants clusters as homogeneous as possible with respect to a group of dependent variables.     

Vegetation patterns at the alpine treeline ecotone: the influence of tree cover on abrupt change in species composition of alpine communities

Aims: The upper elevation limit of forest vegetation in mountain ranges (the alpine treeline ecotone) is expected to be highly sensitive to global change. Treeline shifts and/or ecotone afforestation could cause fragmentation and loss of alpine habitat, and are expected to trigger considerable alterations in alpine vegetation. We performed an analysis of vegetation structure at the treeline ecotone to evaluate whether distribution of the tree population determines the spatial pattern of vegetation (species composition and diversity) across the transition from subalpine forest to alpine vegetation. Location: Iberian eastern range of the Pyrenees. Methods: We studied 12 alpine Pinus uncinata treeline ecotones. Rectangular plots ranging from 940 to 1900 m² were placed along the forest‐alpine vegetation transition, from closed forest to the treeless alpine area. To determine community structure and species distribution in the treeline ecotone, species variation along the forest‐alpine vegetation transition was sampled using relevés of 0.5 m² set every 2 m along the length of each plot. Fuzzy C‐means clustering was performed to assess the transitional status of the relevés in terms of species composition. The relation of P. uncinata canopy cover to spatial pattern of vegetation was evaluated using continuous wavelet transform analysis. Results: Vegetation analyses revealed a large degree of uniformity of the subalpine forest between all treeline ecotone areas studied. In contrast, the vegetation mosaic found upslope displayed great variation between sites and was characterized by abrupt changes in plant community across the treeline ecotone. Plant richness and diversity significantly increased across the ecotone, but tree cover and diversity boundaries were not spatially coincident. Conclusions: Our results revealed that no intermediate communities, in terms of species composition, are present in the treeline ecotone. Ecotone vegetation reflected both bedrock type and fine‐scale heterogeneity at ground level, thereby reinforcing the importance of microenvironmental conditions for alpine community composition. Tree cover did not appear to be the principal driver of alpine community changes across the treeline ecotone. Microenvironmental heterogeneity, together with effects of past climatic and land‐use changes on ecotone vegetation, may weaken the expected correlation between species distribution and vegetation structure.     

Hydrophobic cluster analysis and classification of sixteen bacterial alginate lyases

Sixteen alginate lyases whose primary sequences have been reported were compared, and classified into the following three groups on the basis of the identity of their primary sequences. Strong homology (>50%): A-AlgL, A-AlgL*, P-AlgL, P-AlgL*, and AlgA; weak homology (>20%): ALY, AlxM, P-Aly, K-Aly, AlyPG, AlgVGI, AlgVGII, and AlgVGIII; little homology (<20%): ALYII, Al-III, and AlgVMI. Using hydrophobic cluster analysis (HCA), a secondary structure prediction method, the sixteen alginate lyases were placed into the following classes. Class 1: AlgA, A-AlgL, A-AlgL*, P-AlgL, and P-AlgL*; Class 2: AlgVMI and Al-III; Class 3: ALY and AlxM; Class 4A: ALYII, K-Aly, P-Aly, and AlyPG; Class 4B: AlgVGI and AlgVGII; Class 5: AlgVGIII, which is put in a class of its own, because it is unlike any of the other alginate lyases.     

聚类分析在黄霉素发酵过程中的应用

【目的】将聚类分析的方法应用于黄霉素摇瓶发酵条件的优化过程中。【方法】通过系统聚类算法、K均值聚类算法和模糊C均值聚类算法对不同批次黄霉素发酵的摇瓶数据的聚类分析进行比较,发现模糊C均值聚类算法优于其他聚类算法,确定了以模糊C均值聚类算法对黄霉素摇瓶发酵数据进行聚类分析。【结果】然后利用模糊C均值聚类算法选取优质组样本,并利用优质样本优化了黄霉素摇瓶发酵的控制参数分布范围。【结论】这充分证明了聚类分析在发酵过程的优化过程中有良好的实用性。     

The use of most predictable surfaces for the classification and mapping of taxon assemblages

Most Predictable Surface (MPS) analysis provides a spatially explicit, multivariate technique for the classification and contour maping of taxon assemblages. In this paper, the technique of producing Most Predictable Surfaces is outlined and the application of MPS for the classification and mapping of taxon assemblages is demonstrated using modern pollen spectra from western Canada. The MPS maps are compared with maps of scores from principal components analysis. The strength of MPS is that it provides a classification of sites, a local mapped surface of assemblage distribution, and a global model of the relationship between taxon assemblages and geographic coordinates. The global model relating taxon assemblages to geographic coordinates may be used for indirect gradient analysis if the geographic coordinates can be related to specific environmental factors. Alternatively, independent environmental variables may be used directly in place of geographic coordinates. Potential limitations of MPS include (1) the assumption that the distribution of sites with similar assemblages can be approximated by a polynomial (2) the assumption that only two major taxon assemblages are present in the study area and further subdivision of the assemblages is hierarchical, (3) the assumption of a linear relationship between the taxa, and (4) the requirement of a relatively high ratio of sample sites to taxa. However, the results presented here indicate that MPS can have wide application in analysis of vegetation or any other types of taxon assemblages.Abbreviations MPS Most Predictable Surface     

A vegetation-ecological approach to the classification and evaluation of potential natural vegetation of the Fagetea crenatae region in Tohoku (northern Honshu), Japan

A new vegetation-ecological approach is proposed for classification and evaluation of vegetation zones by means of phytosociological landscape analysis, based on the potential natural vegetation. The study area is the “Fagetea crenatae region” of the cool-temperate zone of Tohoku (northern Honshu) and the northern parts of Kanto. The area was divided into 953 geographic quadrats on a base map at a scale of 1 ∶ 500000. Based on climax complexes of vegetation in each quadrat, 55 community sub-groups were distinguished as basic units of community complex and vegetation landscapes. The community sub-groups were then grouped into 17 larger community groups by the phytosociological table method. As a result, three phytogeographic vegetation zones (Japan Sea side, inland areas and Pacific side) were classified. For each of these community sub-groups, five geographical and climatic variables (average altitude, mean annual temperature, Kira's warmth index, annual precipitation and mean annual maximum snow depth) were averaged, and the community sub-groups in the same community group, which resembled each other ecologically, were assembled into 28 clusters. The clusters were combined into 11 ecological groups by means of Pearson's similarity ratio of geographical and climatic characteristics. By comparing these ecological groups as a vegetation complex, four phytogeographic vegetation zones (Japan Sea side, inland areas, Pacific side and northern Honshu) corresponding to each potential natural vegetation region with distinct environmental characteristics, were newly classified.     

Marginal analysis of correlated failure time data with informative cluster sizes

We consider modeling correlated survival data when cluster sizes may be informative to the outcome of interest based on a within-cluster resampling (WCR) approach and a weighted score function (WSF) method. We derive the large sample properties for the WCR estimators under the Cox proportional hazards model. We establish consistency and asymptotic normality of the regression coefficient estimators, and the weak convergence property of the estimated baseline cumulative hazard function. The WSF method is to incorporate the inverse of cluster sizes as weights in the score function. We conduct simulation studies to assess and compare the finite-sample behaviors of the estimators and apply the proposed methods to a dental study as an illustration.     

Multivariate analysis of anthropometric data and classifications of British Columbian natives

Anthropometric data collected in native populations of British Columbia in the late 19th century by Franz Boas were analyzed by two multivariate techniques. Multivariate analysis of variance was used to test physical classificatory units devised by Boas and an ad hoc classification based on local cultural units. Both were found to have some empirical validity. Mahalanobis' D (Mahalanobis, '30) was computed between pairs of local groups, for both sexes. From these a matrix of differences was prepared and diagrams drawn to illustrate phenetic relationships among samples. By this means one cluster of groups, Interior B.C. peoples, could be distinguished and other local samples appeared distinctly different from each other. It was concluded that in the absence of genealogical data by which to identify local populations, local cultural units are preferable to more inclusive units for making empirical comparisons and classifications.     

Hierarchical classification of microorganisms based on high‐dimensional phenotypic data

The classification of microorganisms by high‐dimensional phenotyping methods such as FTIR spectroscopy is often a complicated process due to the complexity of microbial phylogenetic taxonomy. A hierarchical structure developed for such data can often facilitate the classification analysis. The hierarchical tree structure can either be imposed to a given set of phenotypic data by integrating the phylogenetic taxonomic structure or set up by revealing the inherent clusters in the phenotypic data. In this study, we wanted to compare different approaches to hierarchical classification of microorganisms based on high‐dimensional phenotypic data. A set of 19 different species of molds (filamentous fungi) obtained from the mycological strain collection of the Norwegian Veterinary Institute (Oslo, Norway) is used for the study. Hierarchical cluster analysis is performed for setting up the classification trees. Classification algorithms such as artificial neural networks (ANN), partial least‐squared discriminant analysis and random forest (RF) are used and compared. The 2 methods ANN and RF outperformed all the other approaches even though they did not utilize predefined hierarchical structure. To our knowledge, the RF approach is used here for the first time to classify microorganisms by FTIR spectroscopy.      

优势种植被分类系统的逻辑分析与示例方案化

逻辑学原理是各种分类系统科学性及规范性的必要检验工具。本文采用逻辑学原理检验基于优势种的《中国植被》的植被分类系统, 结果发现目前常用的植被分类系统存在较多逻辑错误, 需要予以纠正。于是, 在强调植物生活型分类系统和植被分类系统一致性的基础上, 依据逻辑学原理给出建立植被分类系统的步骤和方法, 提出规范的植物生活型分类系统和植被分类系统示例方案。鉴于多建群种植被的客观存在及其存在形式多样, 在分类系统中给出相应的位置——多建群种植被纲。同时, 针对国内植被分类学界从未形成统一的植被命名规则, 且又有多种命名方式并存的现状, 提出了函数命名法。     

Genetic diversity in Australian wheat varieties and breeding material based on RFLP data

 Restriction fragment length polymorphisms (RFLPs) have been used to characterise the genetic diversity of wheat (Triticum aestivum) germplasm. One hundred and twenty-four accessions comprising all major Australian wheat varieties and lines important for breeding purposes were assayed for RFLPs with clones of known genetic location and selected to give uniform genome coverage. The objectives of this study were to determine RFLP-based genetic similarity between accessions and to derive associations between agronomically significant traits and RFLP phenotypes. Ninety-eight probes screened against genomic DNA digested with five restriction endonucleases detected a total of 1968 polymorphic fragments. Genetic similarity (GS) calculated from the RFLP data ranged from 0.004 to 0.409 between accessions, with a mean of 0.18. Cluster analysis based on GS estimates produced four groupings that were generally consistent with available pedigree information. Comparisons of the RFLP phenotypes of accessions containing disease resistance genes present on introgressed alien segments enabled the identification of specific alleles characteristic of these regions. Associations were derived for a range of stem-rust, leaf-rust and yellow-rust resistance genes. These results suggest that RFLP analysis can be used for the characterisation and grouping of elite breeding material of wheat and RFLP profiling can identify chromosome segments associated with agronomic traits. Received: 10 March 1997 / Accepted: 28 July 1997     

Intrinsic mode entropy based on multivariate empirical mode decomposition and its application to neural data analysis

Entropy, a measure of the regularity of a time series, has long been used to quantify the complexity of brain dynamics. Given the multiple spatiotemporal scales inherent in the brain, traditional entropy analysis based on a single scale is not adequate to accurately describe the underlying nonlinear dynamics. Intrinsic mode entropy (IMEn) is a recent development with appealing properties to estimate entropy over multiple time scales. It is a multiscale entropy measure that computes sample entropy (SampEn) over different scales of intrinsic mode functions extracted by empirical mode decomposition (EMD) method. However, it suffers from both mode-misalignment and mode-mixing problems when applied to multivariate time series data. In this paper, we address these two problems by employing the recently introduced multivariate empirical mode decomposition (MEMD). First, we extend the MEMD to multi-channel multi-trial neural data to ensure the IMEn matched at different scales. Second, for the discriminant analysis of IMEn, we propose to improve the discriminative ability by including variance that has not been used before in entropy analysis. Finally, we apply the proposed approach to the multi-electrode local field potentials (LFPs) simultaneously collected from visual cortical areas of macaque monkeys while performing a generalized flash suppression task. The results have shown that the entropy of LFP is indeed scale-dependent and is closely related to the perceptual conditions. The discriminative results of the perceptual conditions, revealed by support vector machine, show that the accuracy based on IMEn and variance reaches 83.05%, higher than that only by IMEn (76.27%). These results suggest that our approach is sensitive to capture the complex dynamics of neural data.     

Discrimination of higher plant calluses based on embryogenic capacity and taxonomic classification by pyrolysis mass spectrometry

Pyrolysis mass spectrometry (PyMS) is a rapid, simple, high-resolution analytical method based on thermal degradation of complex material in a vacuum, and has been widely applied to the discrimination of closely related microbial strains. Minimally prepared samples of embryogenic and non-embryogenic calluses derived from various higher plants (sweet potato, morning glory, Korean ginseng, Siberian ginseng, and balloon flower) were subjected to PyMS for spectral fingerprinting. A dendrogram based on the unweighted pair group method, with arithmetic mean of pyrolysis mass spectra, divided the calluses into Siberian ginseng embryogenic callus and the others, which were subsequently divided into embryogenic and non-embryogenic callus groups, regardless of plant species from which the calluses were derived. In the non-embryogenic callus group, the dendrogram was in agreement with the known taxonomy of the plants. These results indicate that PyMS analysis could be applied for discriminating plant calluses based on embryogenic capacity and taxonomic classification.     

Assessment of a method for cultivar selection based on regional trial data

Summary In this study a method for analyzing regional trial data is investigated for its effectiveness in cultivar selection. The method is a synthesis of three procedures: (1) regression analysis for genotype × environment (GE) interaction, and subsequent cluster analysis for grouping cultivars for similarity of response; (2) superiority measure analysis of cultivar performance based on the distance mean square between the test cultivar and the maximum response; (3) type 4 stability analysis for three-way classification data (cultivar × location × year), to measure a cultivar's stability. Each of these three procedures is aimed at different aspects of the selection problem: the first obtains an overview of the types of cultivar response; the second measures a cultivar's general adaptability within the region; the third assesses a cultivar's ability to withstand unpredictable variation, namely that caused by year effects. Four sets of published data, each originally analyzed by a univariate or a multivariate approach, were used as examples. The results suggest that the present method provides direct and useful information for selection purposes. The superiority measure, which is the core of the method, can be used even if the data do not fit the linear model for GE interaction. Plotting the data with a fixed standard represented by the maximum response provides a simple visual tool for identifying environments where a cultivar performs well.Contribution No. C-035 from Research Program Service, Research Branch, Agriculture Canada, Ottawa, Ontario, K1A 0C6     

Guild structure of wood-rotting fungi based on volume and decay stage of coarse woody debris

Wood-rotting fungi are major organisms exploiting coarse woody debris (CWD) in forests. Here, guild structure of wood-rotting fungi was investigated in cool temperate (Chichibu) and warm temperate (Chiba) forests in central Japan, based on their occurrence on CWD of different volumes and decay stages. Analysis with the program partitioning around medoids (PAM) recognized two clusters in Chichibu and four in Chiba, and their silhouette coefficients (an index for reliability of clustering) were adequately high, suggesting the existence of non-random clustering structure. To examine whether the clustering structure observed in this study was based on fungal preference for CWD or discontinuities in the distribution of CWD characteristics (decay stage and volume), null model analyses were made in which all fungal species were randomly redistributed among CWD. Silhouette coefficients based on the null model were reasonably high in both localities, indicating the observed clustering structure was at least partly attributable to the discontinuity in the distribution of CWD characteristics. In addition, the silhouette coefficient of the observed clustering structure was significantly higher than that of the null model in both localities. This result suggests that guild structure was present in the wood-rotting fungal communities, and the difference in CWD preference among wood-rotting fungi contributed to the structuralization of the communities.     

基于MFA和DEA的区域经济环境效率评价-以辽宁省为例

对经济与环境效率的科学评价是实现区域可持续发展的前提。运用物质流分析将辽宁省经济系统中数据进行物质化处理,再利用改进的数据包络分析模型对环境和经济效率进行综合评价。结果表明:辽宁省物资消费不主要依赖于进口,向其它地区物质输出量大;环境效率评价的综合效率主要受规模因素影响而显著低于纯技术效率,而整体经济的综合效率却主要受纯技术效率影响而下降。第二产业比重依然偏大的产业结构特征是导致上述结果的主因。进一步改造提升传统产业,发展战略性新兴产业,提高第三产业发展水平,扩大环保规模,促进居民生活质量水平全面提升,将是辽宁省以及与之相似的资源依赖型区域可持续发展的方向。