基于文献计量分析的生态修复现状研究

以中国知网学术期刊网络出版总库和WEB OF SCIENCE中1997—2015年的期刊论文为数据源,以"生态修复(ecological remediation和ecological restoration)"为关键词进行检索,利用共词分析方法,同时结合Bibexcel软件对检索结果进行分析,利用Ucinet和Netdraw软件绘制出共词网络可视图,并通过SPSS软件进行多维尺度分析,以此来研究高频关键词之间的内在联系,探讨国内外生态修复领域中的研究热点以及研究现状。以文献计量学的分析方法客观的评价国内外生态修复的研究概况及研究热点,明确生态修复技术研究探索的方向,从而为加强生态修复技术的研究提供理论依据。     

Trajectory analysis of Chinese vegetation types in a multidimensional climatic space

Abstract. The concept of trajectory of a vegetation type is used as a tool to study the position of vegetation types in a multidimensional climatic space. This space was obtained by Principal Component Analysis based on climatic data - based on monthly means. The positions of the main vegetation types distinguished in China were plotted in the climatic space and trajectory lengths and shapes of the types were compared. Three main groups were found, which correspond to: (1) cold and temperate, (2) alpine and mountain, and (3) subtropical and tropical conditions. Within each main category sub-categories were distinguished on the basis of trajectory length and direction. In total, seven trajectory shapes were defined. Based on the correlation between climatic variables and PCA-axes temperature is suggested to be the overriding factor in determining the trajectory shape. But, trajectories can also be affected by the combination of other climatic variables.     

AURELIA,a program for computer-aided analysis of multidimensional NMR spectra

Summary AURELIA is an advanced program for the computer-aided evaluation of two-, three- and four-dimensional NMR spectra of any type of molecule. It can be used for the analysis of spectra of small molecules as well as for evaluation of complicated spectra of biological macromolecules such as proteins. AURELIA is highly interactive and offers a large number of tools, such as artefact reduction, cluster and multiplet analysis, spin system searches, resonance assignments, automated calculation of volumes in multidimensional spectra, calculation of distances with different approaches, including the full relaxation matrix approach, Bayesian analysis of peak features, correlation of molecular structures with NMR data, comparison of spectra via spectral algebra and pattern match techniques, automated sequential assignments on the basis of triple resonance spectra, and automatic strip calculation. In contrast to most other programs, many tasks are performed automatically.     

Population structure in the Connecticut Valley: II. A comparison of multidimensional scaling solutions of migration matrices and isonymy

In a previous paper (Swedlund et al., 1984) we have described the population structure of the historical Connecticut River Valley of Massachusetts in terms of matrimonial migration matrices. Using procedures described by Morton (1973), Harpending and Jenkins (1974), Jorde (1980), and others the exchanges between subdivisions which make up the matrices are made column stochastic and analyzed to predict genetic kinship. Subsequently the kinship estimates within and between subdivisions can be interpreted as genetic covariance and compared to the actual geographic distances between the respective subdivisions using a principal components analysis. In the present paper we extend these results by applying nonmetric multidimensional scaling to the migration matrices, and to isonymy matrices based on the same communities. We demonstrate that the multidimensional scaling configurations of marital migration represent the actual geographic relationships between the communities quite effectively for this particular case study from historical Massachusetts. Moreover, we argue that while these migration data may provide good estimates of social and genetic exchange between the subdivisions, surname analysis may also be informative of processes not revealed in the migration matrices alone.     

Multidimensional scaling and the analysis of human biological diversity in Subsaharan Africa

Much information concerning intergroup variation in Subsaharan Africa has been collected by Hiernaux, who has calculated measures of biological distance (Δg) between pairs of 101 African human populations. The resulting very large matrix of distances is not easily interpreted through simple inspection. Therefore non-metric multidimensional scaling is here applied in order to produce a configuration of 60 selected groups in a space of reduced dimensionality. A three dimensional solution shows acceptable stress, and this map of populations is used to support and extend Hiernaux's earlier conclusions.     

Wavelet analysis of human DNA

This paper studies the human DNA in the perspective of signal processing. Six wavelets are tested for analyzing the information content of the human DNA. By adopting real Shannon wavelet several fundamental properties of the code are revealed. A quantitative comparison of the chromosomes and visualization through multidimensional and dendograms is developed.     

Improved efficiency of protein structure calculations from NMR data using the program DIANA with redundant dihedral angle constraints

Summary A new strategy for NMR structure calculations of proteins with the variable target function method (Braun, W. and Go, N. (1985)J. Mol. Biol.,186, 611) is described, which makes use of redundant dihedral angle constraints (REDAC) derived from preliminary calculations of the complete structure. The REDAC approach reduces the computation time for obtaining a group of acceptable conformers with the program DIANA 5-100-fold, depending on the complexity of the protein structure, and retains good sampling of conformation space.Dedicated to the memory of Professor V.F. Bystrov     

Spatial information analysis of chemotactic trajectories

During bacterial chemotaxis, a cell acquires information about its environment by sampling changes in the local concentration of a chemoattractant, and then uses that information to bias its motion relative to the source of the chemoattractant. The trajectory of a chemotaxing bacteria is thus a spatial manifestation of the information gathered by the cell. Here we show that a recently developed approach for computing spatial information using Fourier coefficient probabilities, the k-space information (kSI), can be used to quantify the information in such trajectories. The kSI is shown to capture expected responses to gradients of a chemoattractant. We then extend the k-space approach by developing an experimental probability distribution (EPD) that is computed from chemotactic trajectories collected under a reference condition. The EPD accounts for connectivity and other constraints that the nature of the trajectories imposes on the k-space computation. The EPD is used to compute the spatial information from any trajectory of interest, relative to the reference condition. The EPD-based spatial information also captures the expected responses to gradients of a chemoattractant, although the results differ in significant ways from the original kSI computation. In addition, the entropy calculated from the EPD provides a useful measure of trajectory space. The methods developed are highly general, and can be applied to a wide range of other trajectory types as well as non-trajectory data.     

Early seral trends in plant community diversity on a recontoured surface mine

The initial floristic composition and structure of vegetation on a recontoured surface mine in southwestern Wyoming was experimentally manipulated to test ideas concerning successional convergence. Experimental treatments involving the planting pattern and density of shrubs and the storage of topsoil were evaluated on the basis of their ability to divert the successional trajectories of the redeveloping vegetation and to increase species diversity. The change in compositional similarity along a topographic gradient was also monitored.The influence of initial composition and soil storage generally declined with time; successional convergence among treatments over the four years of the study was largely monotonic. The planting of shrubs and the storage of topsoil did, however, influence the rate of plant succession. There were no persistent differences in alpha diversity among the experimental treatments. Compositional dissimilarity along the topographic gradient, as expressed by beta diversity, increased with time.     

Application of 2D and 3D NMR experiments to the conformational study of a diantennary oligosaccharide

Summary By the application of homonuclear 3D NOE-HOHAHA and heteronuclear 3D HMQC-NOE experiments in studies of complex oligosaccharides. NOEs can be investigated which are hidden in conventional 2D NOE spectra. In the 3D NOE-HOHAHA spectrum ₃ cross sections were considered to be the most suitable for assignment of NOEs. Alternatively, these cross sections could be measured separately in selective 2D HOHAHA-NOE spectroscopy. The advantages and limitations of the 2D alternative are compared with those of the 3D NOE-HOHAHA approach. In 3D HMQC-NOE spectroscopy the larger chemical shift displacement of the carbon spectrum with respect to the proton spectrum can be used to unmask NOEs hidden in the bulk region. If the extra proton dimension is not needed, 2D HMQC-NOE is a good alternative.The suitability of 2D and 3D NOE-HOHAHA and HMQC-NOE experiments for the estimation of proton-proton distances is demonstrated by comparing the results of these experiments on a diantennary asparagine-linked oligosaccharide with those of a conventional 2D NOE experiment. NOEs identified in the 2D and 3D NOE-HOHAHA as well as HMQC-NOE experiments, so far not identified or not quantified in 2D NOE experiments, are discussed in relation to each glycosidic linkage. The flexibility of the Man(1-3)Man linkage is demonstrated, confirming the existence of an ensemble of conformations for this linkage.     

The Influence of Habitat Complexity on Reef Fish Communities in the Northeastern Gulf of Mexico

Several previous studies have attempted to correlate habitat complexity and reef fish species diversity. These studies have mostly examined natural reef systems, but results differed. To examine this relation, we built 1 m² habitats with 20 replicates of five complexity levels from July to August 2001 in the northeastern Gulf of Mexico (n=100). In June and July 2002, we built new habitats using the 2001 design, but also added a sixth complexity level (n=120). In order of increasing complexity these included: cage, shell, cage-shell, block-shell, cage-block-shell, and shell-block-pyramid habitats. Most fish in both years were juveniles and included species common to reef structures in the northeastern Gulf of Mexico. In 2001, we identified 26 fish species, and the dominant species was red snapper, Lutjanus campechanus (41%), followed by rock sea bass, Centropristis philadelphica (23%), and sand perch, Diplectrum spp. (14%). In 2002 we identified 36 species, and the dominant species was tomtate, Haemulon aurolineatum (36%), followed by Diplectrum spp. (19%), and L. campechanus (13%). In 2001, species diversity and richness were significantly (P<0.05) higher on more complex habitats (H′=1.7, S=11–12) compared to less complex habitats (H′=0.8–1.0, S=4–9). In 2002, patterns among diversity, richness and reef complexity were less apparent with only the least complex habitats shell and cage showing significantly lower values. In both years, multidimensional scaling grouped by complexity levels with cage and shell habitats showing the clearest separation from other habitat types. Also, with few exceptions (only 8%) analysis of similarities showed significant (P<0.05) differences in fish communities across complexity levels. Although community composition varied between years, this study provided evidence to support the hypothesis that habitat complexity increased reef fish species diversity.     

Assessing three methods for identification of desirable genotypes in white cabbage (Brassica oleracea L. var. capitata)

Summary A desirable genotype is a genotype performing well in a chosen set of environments. Three methods for identification of desirable genotypes were assessed in two cabbage data sets: regression analysis, multidimensional scaling of dissimilarity matrices, and biplot of deviation matrices. Using the regression approach is not recommended mainly for two reasons: (1) it is difficult to identify the desirable genotypes since one has to unify three parameters into one decision; (2) the regression method failed to identify the most desirable genotypes in one of the data sets. Multidimensional scaling and the biplot method were in accordance with each other and with the mean tables when different subsets where compared. Consequently, they were considered more adequate for identifying desirable genotypes. In cases where rank 2 approximation of the analysed matrix was justified, the biplot revealed more information in one display and was, therefore, considered particularly useful in plant breeding for larger target areas.     

Trajectory log file sensitivity: A critical analysis using DVH and EPID

Aim

The aim of this study was to investigate the sensitivity of the trajectory log file based quality assurance to detect potential errors such as MLC positioning and gantry positioning by comparing it with EPID measurement using the most commonly used criteria of 3%/3?mm.

NMR restraint analysis of transforming growth factor alpha: a key component for NMR structure refinement.

Structures of the protein, transforming growth factor alpha (TGF-alpha), have been derived from NMR data using distance geometry and subsequent energy refinement. Analysis of the sequential NOE distance bounds using a template algorithm provides a check for consistency in the calculation of bounds, stereospecific assignment of prochiral centers, and secondary structure assignment. Application of the template algorithm to the long range NOEs found within the NMR data sets collected at pH 6.3 and pH 3.4 is used to assess the confidence levels for the accuracy of the structures obtained from modeling. The method also provides critical insight in differentiating regions of the structure that are well defined from those that are not. Use of the restraint analysis protocol is shown to be a powerful adjunct to currently used methods for the assignment of protein structures from NMR data.     

Extended dissimilarity: a method of robust estimation of ecological distances from high beta diversity data

It is widely accepted that reliable ordination of ecological data requires a strong linear or ordinal relationship between the dissimilarity of sites, based on species composition, and the ecological distance between them. Certain dissimilarity measures, having the property that they take a fixed maximum value when sites have no species in common, have been shown to be strongly correlated with ecological distance. For ecological gradients of moderate length (moderate beta diversity), such measures, in conjunction with non-metric multidimensional scaling, will reliably yield successful ordinations. However, as beta diversity increases, more sites have no species in common, and such measures invariably under-estimate ecological distance for such sites. Thus ordinations of data with high species turnover (high beta diversity) may fail.Extended dissimilarities are defined using an iterative adaptation of flexible shortest path adjustment applied to the matrix of dissimilarities with fixed maximum values. By means of theoretical argument and simulations, this is shown to lead to far stronger correlations between the adjusted site dissimilarity and ecological distance for ecological gradients of greater length than previously considered. Hence ordinations of extended dissimilarities, by means of either metric or non-metric scaling techniques, are shown to outperform corresponding ordinations of unadjusted dissimilarities, with the difference increasing with increasing beta diversity.     

Principal components analysis of protein structure ensembles calculated using NMR data

One important problem when calculating structures of biomolecules from NMR data is distinguishing converged structures from outlier structures. This paper describes how Principal Components Analysis (PCA) has the potential to classify calculated structures automatically, according to correlated structural variation across the population. PCA analysis has the additional advantage that it highlights regions of proteins which are varying across the population. To apply PCA, protein structures have to be reduced in complexity and this paper describes two different representations of protein structures which achieve this. The calculated structures of a 28 amino acid peptide are used to demonstrate the methods. The two different representations of protein structure are shown to give equivalent results, and correct results are obtained even though the ensemble of structures used as an example contains two different protein conformations. The PCA analysis also correctly identifies the structural differences between the two conformations.     

Estimating the Mahalanobis distance from mixed continuous and discrete data

We present a method for estimating the Mahalanobis distance between two multivariate normal populations when a subset of the measurements is observed as ordered categorical responses. Asymptotic properties of the proposed estimator are developed. Two examples are discussed.     

An easy way to include weak alignment constraints into NMR structure calculations

We have recently shown that an energy penalty for the incorporation of residual tensorial constraints into molecular structure calculations can be formulated without the explicit knowledge of the Saupe orientation tensor (Moltke and Grzesiek, J. Biomol. NMR, 1999, 15, 77–82). Here we report the implementation of such an algorithm into the program X-PLOR. The new algorithm is easy to use and has good convergence properties. The algorithm is used for the structure refinement of the HIV-1 Nef protein using 252 dipolar coupling restraints. The approach is compared to the conventional penalty function with explicit knowledge of the orientation tensor's amplitude and rhombicity. No significant differences are found with respect to speed, Ramachandran core quality or coordinate precision.     

Proximity structure in a captive colony of Japanese monkeys (Macaca fuscata fuscata): An application of multidimensional scaling

Spatial proximity was used to investigate the social structure of a group of 14 Japanese macaques (Macaca fuscata fuscata) living in Cavriglia Park (Arezzo, Italy). Instantaneous sampling was used to collect data. From April 1984 to March 1985, 273 hr of observation were accumulated. Time spent in proximity by any two monkeys was transformed into a similarity index. Two triangular matrices were created with these indices (one for the non-breeding and the other for the breeding season) and submitted to nonmetric multidimensional scaling (MDS). During the non-breeding season proximity proved closely related to hierarchical relationships and the existence of two real social classes was suggested. Tendency to loneliness was associated in this period with old age in females and low rank in both females and males. Moreover, socially stable versus socially unstable animals had different spacing patterns. Almost the same central-peripheral structure was outlined in both seasons, consistently with a stableoikia hypothesis for this group under these conditions. During the breeding season social organization was influenced by individual sexual interest. A male spacing pattern emerged, probably in correlation with female homosexuality, which played a preeminent role in the sexual context. The relative loneliness of sexually immature individuals was evident in this season.     

Effects of subpopulation structure on probability calculations of DNA profiles from forensic PCR analysis

DNA typing for forensic identification is a two-step process. The first step involves determining the profiles of samples collected at the crime scene and comparing them with the profiles obtained from suspects and the victims. In the case of a match that includes the suspect as the potential source of the material collected at the crime scene, the last step in the process is to answer the question, what is the likelihood that someone in addition to the suspect could match the profile of the sample studied? This likelihood is calculated by determining the frequency of the suspect's profile in the relevant population databases. The design of forensic databases and the criteria for comparison has been addressed by the NRC report of 1996 (National Research Council, 1996). However, the fact that geographical proximity, migrational patterns, and even cultural and social practices have effects on subpopulation structure establishes the grounds for further study into its effects on the calculation of probability of occurrence values. The issue becomes more relevant in the case of discrete polymorphic markers that show higher probability of occurrence in the reference populations, where several orders of magnitude difference between the databases may have an impact on the jury. In this study, we calculated G values for all possible pairwise comparisons of allelic frequencies in the different databases from the races or subpopulations examined. In addition, we analyzed a set of 24 unrelated Caucasian, 37 unrelated African-American, and 96 unrelated Sioux/Chippewa individuals for seven polymorphic loci (DQA1, LDLR, GYPA, HBGG, D7S8, GC, and D1S80). All three sets of individuals where sampled from Minnesota. The probability of occurrence for all seven loci were calculated with respect to nine different databases: Caucasian, Arabic, Korean, Sioux/Chippewa, Navajo, Pueblo, African American, Southeastern Hispanic, and Southwestern Hispanic. Analysis of the results demonstrated marked differences in the probabilities of occurrence when individuals were compared to the different populations and subpopulation databases. The possible genetic and forensic consequences of subpopulation structure on probability calculations are discussed.