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1.
The specialization of herbivores among tree species is poorly understood despite its fundamental importance as a factor regulating diversity. To examine the effect of tree species on larval community structure, the larval communities in 10 temperate deciduous tree species that differed in leaf emergence pattern (flush- vs. intermediate-type) were seasonally surveyed. The newly developed soft, nitrogen-rich leaves of all species became tough and nitrogen-poor as the season progressed. Following the changes in leaf quality, two distinct seasonal lepidopteran larval communities emerged, with a marked turnover in early July. The beta diversity, or dissimilarity, of species composition in the larval communities among tree species was higher in summer than in spring. These results imply that the lepidopteran larval communities as a whole were supported by alpha diversity in spring and by beta diversity in summer, demonstrating that the plant diversity of this forest could support a caterpillar community. We examined the importance of spatio-temporal variations in leaf quality within and among tree species in promoting herbivore diversity, although other factors, such as tree species phylogeny and predators, may also have a large effect on lepidopteran larval communities.  相似文献   
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Abstract. Indices of β‐diversity are of two major types, (1) those that measure among‐plot variability in species composition independently of the position of individual plots on spatial or environmental gradients, and (2) those that measure the extent of change in species composition along predefined gradients, i.e. species turnover. Failure to recognize this distinction can lead to the inappropriate use of some β‐diversity indices to measure species turnover. Several commonly‐used indices of β‐diversity are based on Whittaker's βW (βW = γ/α, where γ is the number of species in an entire study area and α is the number of species per plot within the study area). It is demonstrated that these indices do not take into account the distribution of species on spatial or environmental gradients, and should therefore not be used to measure species turnover. The terms ‘β‐diversity’ and ‘species turnover’ should not be used interchangeably. Species turnover can be measured using matrices of compositional similarity and physical or environmental distances among pairs of study plots. The use of indices of β‐diversity and similarity‐distance curves is demonstrated using simulated data sets.  相似文献   
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Classifying monoclonal antibodies, based on the similarity of their binding to the proteins (antigens) on the surface of blood cells, is essential for progress in immunology, hematology and clinical medicine. The collaborative efforts of researchers from many countries have led to the classification of thousands of antibodies into 247 clusters of differentiation (CD). Classification is based on flow cytometry and biochemical data. In preliminary classifications of antibodies based on flow cytometry data, the object requiring classification (an antibody) is described by a set of random samples from unknown densities of fluorescence intensity. An individual sample is collected in the experiment, where a population of cells of a certain type is stained by the identical fluorescently marked replicates of the antibody of interest. Samples are collected for multiple cell types. The classification problems of interest include identifying new CDs (class discovery or unsupervised learning) and assigning new antibodies to the known CD clusters (class prediction or supervised learning). These problems have attracted limited attention from statisticians. We recommend a novel approach to the classification process in which a computer algorithm suggests to the analyst the subset of the "most appropriate" classifications of an antibody in class prediction problems or the "most similar" pairs/ groups of antibodies in class discovery problems. The suggested algorithm speeds up the analysis of a flow cytometry data by a factor 10-20. This allows the analyst to focus on the interpretation of the automatically suggested preliminary classification solutions and on planning the subsequent biochemical experiments.  相似文献   
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Rao has developed quadratic entropy to measure diversity in a set of entities divided up among a fixed set of categories. This index depends on a chosen matrix of dissimilarities among categories and a frequency distribution of these categories. With certain choices of dissimilarities, this index could be maximized over all frequency distributions by eliminating several categories. This unexpected result is radically opposite to those obtained with usual diversity indices. We demonstrate that the elimination of categories to maximize the quadratic entropy depends on mathematical properties of the chosen dissimilarities. In particular, when quadratic entropy is applied to ultrametric dissimilarities, all categories are retained in order to reach its maximal value. Three examples, varying from simple one-dimensional to ultrametric dissimilarity matrices, are provided. We conclude that, as far as diversity measurement is concerned, quadratic entropy is most relevant when applied to ultrametric dissimilarities.  相似文献   
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Question: Can dissimilarity measures of individual plots be used to forecast the driving factors among various anthropogenic disturbances influencing understorey successional changes? Location: Yambulla State Forest, south‐eastern Australia (37°14'S, 149°38'E). Methods: Assessments of understorey vegetation communities were taken prior to anthropogenic disturbances and at three subsequent time periods representing a period of 15 years post‐disturbance. Dissimilarities were calculated from the original assessment and modelled in a Bayesian framework to examine the influence of logging, number of prescribed burns and time. Results: All sites underwent significant changes over time independently of the imposed management regimes. Logging resulted in an immediate change in vegetation assemblage which decreased in the subsequent assessments. The number of prescribed fires brought greater change in the shrub vegetation assemblages, but less change in the ground species vegetation assemblages. Conclusions: The anthropogenic disturbances did have some role in the changes of vegetation assemblages but these were minimal. The ongoing changes appear to be a natural response to the last wildfire, which passed through the study area in 1973 (13 years prior to the study). Forest management practices should consider the influence of wildfire succession when planning for the conservation of biodiversity.  相似文献   
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Abstract. We examined the role of playa lakes in promoting regional heterogeneity on the southern High Plains. The goals of this paper were to: (1) describe vegetation types and zonation patterns within playas, (2) evaluate patterns of species distribution and abundance within and among playas, and (3) assess patterns of heterogeneity within and among playas on a portion of the southern High Plains. Perennial grasses were the most abundant species in playa vegetation. Playa vegetation exhibited distinct and repeatable vegetation zones at the majority of sites, but the number of distinct zones varied from site to site. Agropyron smithii, Buchloë dactyloides, and Panicum obtusum were the most important species of playa interior zones, and Bouteloua gracilis, Buchloë dactyloides, and Schedonnardus paniculatus were important upland species outside of playas. Species distribution and abundance were positively correlated at 38 of 40 sites. The distributions of species occurrences among sites were unimodal both locally and regionally. The degree of heterogeneity varied from playa to playa. Local heterogeneity within playas was found to increase regional heterogeneity; therefore, playas increase both local and regional heterogeneity of vegetation. Long-term monitoring will be necessary to understand the spatial and temporal response of vegetation within and among playas to stochastic climatic factors on the southern High Plains of North America.  相似文献   
9.
This paper proposes a new method to reverse engineer gene regulatory networks from experimental data. The modeling framework used is time-discrete deterministic dynamical systems, with a finite set of states for each of the variables. The simplest examples of such models are Boolean networks, in which variables have only two possible states. The use of a larger number of possible states allows a finer discretization of experimental data and more than one possible mode of action for the variables, depending on threshold values. Furthermore, with a suitable choice of state set, one can employ powerful tools from computational algebra, that underlie the reverse-engineering algorithm, avoiding costly enumeration strategies. To perform well, the algorithm requires wildtype together with perturbation time courses. This makes it suitable for small to meso-scale networks rather than networks on a genome-wide scale. An analysis of the complexity of the algorithm is performed. The algorithm is validated on a recently published Boolean network model of segment polarity development in Drosophila melanogaster.  相似文献   
10.
In molecular biology, the issue of quantifying the similarity between two biological sequences is very important. Past research has shown that word-based search tools are computationally efficient and can find some new functional similarities or dissimilarities invisible to other algorithms like FASTA. Recently, under the independent model of base composition, Wu, Burke, and Davison (1997, Biometrics 53, 1431 1439) characterized a family of word-based dissimilarity measures that defined distance between two sequences by simultaneously comparing the frequencies of all subsequences of n adjacent letters (i.e., n-words) in the two sequences. Specifically, they introduced the use of Mahalanobis distance and standardized Euclidean distance into the study of DNA sequence dissimilarity. They showed that both distances had better sensitivity and selectivity than the commonly used Euclidean distance. The purpose of this article is to extend Mahalanobis and standardized Euclidean distances to Markov chain models of base composition. In addition, a new dissimilarity measure based on Kullback-Leibler discrepancy between frequencies of all n-words in the two sequences is introduced. Applications to real data demonstrate that Kullback-Leibler discrepancy gives a better performance than Euclidean distance. Moreover, under a Markov chain model of order kQ for base composition, where kQ is the estimated order based on the query sequence, standardized Euclidean distance performs very well. Under such a model, it performs as well as Mahalanobis distance and better than Kullback-Leibler discrepancy and Euclidean distance. Since standardized Euclidean distance is drastically faster to compute than Mahalanobis distance, in a usual workstation/PC computing environment, the use of standardized Euclidean distance under the Markov chain model of order kQ of base composition is generally recommended. However, if the user is very concerned with computational efficiency, then the use of Kullback-Leibler discrepancy, which can be computed as fast as Euclidean distance, is recommended. This can significantly enhance the current technology in comparing large datasets of DNA sequences.  相似文献   
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