广西英罗港红树植物群落的非线性排序

采用主分量分析 (PCA)、无偏主分量 (DPC)和非度量多维调节 (NMDS)等方法对广西英罗港 2 2个红树植物群落样地进行了排序。PCA和 DPC分析结果表明 ,取样数据具有明显的非线性结构。通过 NMDS分析 ,得到二维 NMDS排序格局 ,它能较好地反映了红树植物群落与环境因子之间的相互关系。     

Bootstrapped ordination: a method for estimating sampling effects in indirect gradient analysis

Indirect gradient analysis, or ordination, is primarily a method of exploratory data analysis. However, to support biological interpretations of resulting axes as vegetation gradients, or later confirmatory analyses and statistical tests, these axes need to be stable or at least robust into minor sampling effects. We develop a computer-intensive bootstrap (resampling) approach to estimate sampling effects on solutions from nonlinear ordination.We apply this approach to simulated data and to three forest data sets from North Carolina, USA and examine the resulting patterns of local and global instability in detrended correspondence analysis (DCA) solutions. We propose a bootstrap coefficient, scaled rank variance (SRV), to estimate remaining instability in species ranks after rotating axes to a common global orientation. In analysis of simulated data, bootstrap SRV was generally consistent with an equivalent estimate from repeated sampling. In an example using field data SRV, bootstrapped DCA showed good recovery of the order of common species along the first two axes, but poor recovery of later axes. We also suggest some criteria to use with the SRV to decide how many axes to retain and attempt to interpret.Abbreviations DCA= detrended correspondence analysis - SRV= scaled rank variance     

Elements of metacommunity structure of Paraguayan bats: multiple gradients require analysis of multiple ordination axes

Techniques to evaluate elements of metacommunity structure (EMS; coherence, species turnover and range boundary clumping) have been available for several years. Such approaches are capable of determining which idealized pattern of species distribution best describes distributions in a metacommunity. Nonetheless, this approach rarely is employed and such aspects of metacommunity structure remain poorly understood. We expanded an extant method to better investigate metacommunity structure for systems that respond to multiple environmental gradients. We used data obtained from 26 sites throughout Paraguay as a model system to demonstrate application of this methodology. Using presence–absence data for bats, we evaluated coherence, species turnover and boundary clumping to distinguish among six idealized patterns of species distribution. Analyses were conducted for all bats as well as for each of three feeding ensembles (aerial insectivores, frugivores and molossid insectivores). For each group of bats, analyses were conducted separately for primary and secondary axes of ordination as defined by reciprocal averaging. The Paraguayan bat metacommunity evinced Clementsian distributions for primary and secondary ordination axes. Patterns of species distribution for aerial insectivores were dependent on ordination axis, showing Gleasonian distributions when ordinated according to the primary axis and Clementsian distributions when ordinated according to the secondary axis. Distribution patterns for frugivores and molossid insectivores were best described as random. Analysis of metacommunities using multiple ordination axes can provide a more complete picture of environmental variables that mold patterns of species distribution. Moreover, analysis of EMS along defined gradients (e.g., latitude, elevation and depth) or based on alternative ordination techniques may complement insights based on reciprocal averaging because the fundamental questions addressed in analyses are contingent on the ordination technique that is employed.     

Vegetative Community Compositional Gradients of Tropical Hardwood Hammocks along the Florida Keys

Tropical hardwood hammocks, among the rarest and most threatened vegetative communities in the United States, occur throughout the 225-km Florida Keys archipelago as it extends toward the Caribbean from the southeast tip of peninsular Florida. Compounding their critical conservation status, tropical hardwood hammocks and the dynamics that support their peculiar species diversity in the region are poorly understood. The goal of this study was to explore the dynamics of the species compositional gradient of the hammocks along the Florida Keys, and to identify significant ecological units within the gradient. The primary data for this research were assembled from the Institute for Regional Conservation's floristic database of South Florida. We were able to extract presence/absence data for 295 species from comprehensive surveys of 23 study sites. Nonmetric multidimensional scaling was used to deconstruct the compositional trends into a reduced ordination space. Cluster analysis was subsequently used to identify discrete ecological units. Additionally, we used vector fitting to interpret the significant correlated ancillary variables. Our main results were three well-fitted nonmetric multidimensional scaling axes with three nonoverlapping ecological units. Of the ancillary variables, latitude, longitude, percent composition from biogeographical regions, richness, and area were correlated to the nonmetric multidimensional scaling results. These results increase our understanding of the community structure of the hammocks along the Florida Keys, and can contribute to increasing our ability to adequately protect and restore tropical hardwood hammocks and other similar tropical dry forest communities throughout the Caribbean.     

On non-metric multidimensional scaling ordination and interpretation of the matorral vegetation in lowland Murcía

The plant-environment relationships in a range of matorral communities, having different rainfall conditions in semi-arid lowland habitats in Murcía, S.E. Spain, were examined using the non-metric multidimensional scaling ordination technique. Hypotheses on floristic variations were derived based on an interpretative strategy which involved a site configuration rotation, followed by stepwise multiple regression analysis. An environmental data set was used to isolate variables associated with site co-ordinate trends. Results showed that floristic variation in these communities was mainly determined by aspect induced radiation receipt. Besides, most environmental trends in the study areas were found to be oblique to original site ordination axes and configuration rotation seemed to be a prerequisite in quantitative interpretation. The interpretative strategy introduced in this study was effective. It enhanced straightforward, quantitative and objective interpretation whereby inductive inferences on environmental trends could be readily formulated.Abbreviations ARAD radiation receipt surrogate - DEPTH soil depth - DISTURB disturbance index - NMDS non-metric multidimensional scaling - NUT nutrient scalar - SLOPE slope angle - TEXTIN texture index     

CHLfuzzy: a spreadsheet tool for the fuzzy modeling of chlorophyll concentrations in coastal lagoons

Our purpose was to explore relationships of freshwater planktonic and benthic community species richness with water chemistry parameters using a dataset of biological, chemical, and physical data from 550 lakes. This was done using multivariate (ordination), graphical, and correlation analyses. Although the lakes are rather similar in location (Belarus) and in being mostly eutrophic, they do show variations in water chemistry. We ordinated lakes by water chemistry variables, and then looked for correlations between the ordination axes and species richness in 10 taxonomic groups: Cyanobacteria, Chlorophyta, Bacillariophyta, Cladocera, Copepoda, Rotatoria, Mollusca, Trichoptera, Chironomidae, and aquatic macrophytes. The first four Principal Components Analysis (PCA) axes explained about 67% of the total variability in water chemistry. The axes represent water hardness (DIC, dissolved inorganic carbon), organic content (DOC, dissolved organic carbon), nutrients, and chlorides and sulfates. The PCA ordination revealed environmental gradients, but not the distinctive clusters of lakes. Species richness was most strongly correlated with the first PCA axis (DIC), which accounted for 29% of the total variation in water chemistry. Species richness was positively correlated with DIC for eight of 10 taxonomic categories. The second PCA axis (DOC), which accounted for 20% of total variation in water chemistry, was correlated with species richness in the three phytoplankton groups, and with chironomid species richness. The third PCA axis (nutrients, especially nitrogen, 11%) was correlated with species richness of copepoda, chironomids, and macrophytes. The fourth PCA axis (chloride and sulfate) accounted for only 7% of the total variance in water chemistry, and was significantly negatively correlated with species richness of rotifers, molluscs, and chironomids. In addition to these linear correlations, there were several significant non-linear relationships. DIC variables showed curvilinear (hump-shaped) relationship with benthos (all groups combined) and especially with molluscs, and DOC variables—with phytoplankton and benthos. Each community, and often separate taxonomic groups within community have their own optimal ranges of chemical concentrations, and various water chemistry variables showed significant curvilinear relationships with biodiversity, suggesting that the diversity of different major aquatic groups may be influenced by different chemicals. Handling editor: S. Declerck     

Ordination methods and chironomid species in stony bottom streams

Stony bottom streams in Italy were sampled in 369 sites in different years, and 174 chironomid species (or species groups) were identified.The species by sites matrix was submitted to different ordination methods, with the aim of outlining the major factors that are responsible of the observed species composition.The methods considered were principal component analysis (PCA), detrended correspondence analysis (DCA) and non-metric multidimensional scaling (MDSCAL). These methods assume different models describing the species-responses to the environmental gradients.PCA gave poor results, the best species ordination was given by MDSCAL. DCA gave results in agreement with MDSCAL. DCA results were useful as a starting point to perform MDSCAL. MDSCAL was performed with different options. At last Procrustean analysis was carried out to have a single fitted configuration, that summarized the results given by the different MDSCAL methods.All multivariate analyses emphasized that the first ordination axis can be interpreted as a crenonrithron-potamon gradient, probably an oxygen availability and/or a water temperature gradient, whereas the second axis can be considered a water speed gradient, separating lotic from lentic sites.The 3rd and 4th ordination axes had apparently no ecological meaning.Separated clusters of species were never evident, so well defined chironomid species assemblages could not be outlined in this analysis.     

Performance of four ordination techniques assuming three different non-linear species response models

Summary The performances of four ordination techniques (reciprocal averaging, parametric mapping, gaussian ordination and non-metric multidimensional scaling) are evaluated using artificial data based on three vegetation models: the gaussian response curve, -function curves, and an ecological response model. No technique performs well with the artificial data not based on a gaussian model. Non-metric multidimensional scaling seemed marginally better than other techniques. Some of the implications of this failure are discussed.     

An analysis of epiphytic lichen communities in Tasmanian cool temperate rainforest

A three-dimensional compositional pattern in the epiphytic lichen vegetation in Tasmanian cool temperate rainforest is demonstrated using the robust ordination technique, hybrid multidimensional scaling (HMDS). The first two dimensions are correlated with the age of the host tree (and the concomitant change in bark texture) and wetness of the substrate. No measured environmental variable is related to the third dimension, which is tentatively attributed to a gradient in the constancy of the microclimate. Patterns of richness of lichen growth forms and the cover of bryophytes are correlated with the three putative environmental gradients. Possible successional trends between 12 community groups derived by numerical classification are described with respect to changes in substrate age, wetness and microclimatic constancy. Temporal variation of these factors due to tree growth, together with the slow establishment and long persistence of some lichen species, make succession in epiphytic communities very complex. This study demonstrates the value of HMDS in identifying compositional patterns and generating hypotheses about the causal ecological factors. The existence of the postulated microclimatic constancy gradient was not appreciated before the analysis and its discovery illustrates the risk of relying on constrained ordination methods, such as canonical correspondence analysis.Abbreviations HMDS Hybrid multidimensional scaling - NMDS Non-metric multidimensional scaling     

On the variation explained by ordination and constrained ordination axes

Abstract. Total inertia (TI), the sum of eigenvalues for all ordination axes, is often used as a measure of total variation in a data set. By use of simulated data sets, I demonstrate that lack-of-fit of data to the response model implicit in any eigenvector ordination method results in polynomial distortion ordination axes, with eigenvalues that normally contribute 30–70% to TI (depending on data set properties). The amount of compositional variation extracted on ecologically interpretable ordination axes (structure axes) is thus underestimated by the eigenvalue-to-total-inertia ratio. I recommend that the current use of total inertia as a measure of compositional variation is discontinued. Eigenvalues of structure axes can, however, be used with some caution to indicate their relative importance. I also demonstrate that when the total inertia is partitioned on different sets of explanatory variables and unexplained variation by use of (partial) constrained ordination, (35) 50–85% of the variation ‘unexplained’ by the supplied explanatory variables represents lack-of-fit of data to model. Thus, the common interpretation of ‘unexplained variation’ as random variation (‘noise’) or coenoclinal variation caused by unmeasured explanatory variables, is generally inappropriate. I recommend a change of focus from the variation-explained-to-total inertia ratio and ‘unexplained’ variation to relative amounts of variation explained by different sets of explanatory variables.     

A multivariate analysis of geographic variation in morphology inPersoonia mollis (Proteaceae)

This study highlights the utility and limitations of multivariate procedures for the analysis and taxonomic interpretation of geographic variation within a complex species. Morphological data from herbarium specimens ofPersoonia mollis (Proteceae) were analyzed by two ordination procedures, multidimensional scaling (MDS) and canonical variate analysis (CVA). Support for the earlier recognition of nine infraspecific taxa was found. However, plots of canonical variate scores against latitute or longitude across parapatric subspecies boundaries revealed unexpected phenetic homogeneity within subspecies with sharp transitions between subspecies. The geographic variation in morphology withinP. mollis can be best described as a mosaic of nine recognisably distinct and internally homogeneous allopatric or parapatric taxa, where neighbouring taxa share surprisingly narrow zones of morphological transition at ecotones. The utility of these procedures was highlighted by the recovery of unexpected patterns of variation. However, questions of rank remain unresolved by phenetic analysis alone.     

Trajectory analysis of NMR structure calculations

Summary NMR as well as X-ray crystallography are used to determine the three-dimensional structures of macromolecules at atomic resolution. Structure calculation generates coordinates that are compatible with NMR data from randomly generated initial structures. We analyzed the trajectory taken by structures during NMR structure calculation in conformational space, assuming that the distance between two structures in conformational space is the root-mean-square deviation between the two structures. The coordinates of a structure in conformational space were obtained by applying the metric multidimensional scaling method. As an example, we used a 22-residue peptide, -Conotoxin GIIIA, and a simulated annealing protocol of XPLOR. We found that the three-dimensional solution of the multidimensional scaling analysis is sufficient to describe the overall configuration of the trajectories in conformational space. By comparing the trajectories of the entire calculation with those of the converged calculation, random sampling of conformational space is readily discernible. Trajectory analysis can also be used for optimization of protocols of NMR structure calculation, by examining individual trajectories.Abbreviations MD molecular dynamics - MDS multidimensional scaling - rmsd root-mean-square deviation - armsd angular rmsd - R multiple correlation coefficient - YASAP yet another simulated annealing protocol - PCA principal component analysis     

Detrended correspondence analysis: An improved ordination technique

Summary Detrended correspondence analysis (DCA) is an improvement upon the reciprocal averaging (RA) ordination technique. RA has two main faults: the second axis is often an arch or horseshoe distortion of the first axis, and distances in the ordination space do not have a consistent meaning in terms of compositional change (in particular, distances at the ends of the first RA axis are compressed relative to the middle). DCA corrects these two faults. Tests with simulated and field data show DCA superior to RA and to nonmetric multidimensional sealing in giving clear, interpretable results. DCA has several advantages. (a) Its performance is the best of the ordination techniques tested, and both species and sample ordinations are produced simultaneously. (b) The axes are scaled in standard deviation units with a definite meaning, (c) As implemented in a FORTRAN program called DECORANA, computing time rises only linearly with the amount of data analyzed, and only positive entries in the data matrix are stored in memory, so very large data sets present no difficulty. However, DCA has limitations, making it best to remove extreme outliers and discontinuities prior to analysis. DCA consistently gives the most interpretable ordination results, but as always the interpretation of results remains a matter of ecological insight and is improved by field experience and by integration of supplementary environmental data for the vegetation sample sites.This research was supported by the Institute of Terrestrial Ecology, Bangor, Wales, and by a grant from the National Science Foundation to R.H. Whittaker. We thank R.H. Whittaker for encouragement and comments, S.B. Singer for assistance with the Cornell computer, and H.J.B. Birks, S.R. Sabo, T.C.E. Wells, and R.H. Whittaker for data sets used for ordination tests.     

非度量多维测度及其在群落分类中的应用

排序与聚类分析法是近代最为常用的植被数量分析方法。原理上,排序较之于聚类法,一般具有较为严格的数学基础。在植被研究的应用方面,排序比聚类法能更好反映植被的连续性。同时,在反映植被分类结果上,排序图不仅象聚类树形图一样,使全部实体之间的划分关系得以反映,而且两两实体间的关系可以通过排序图上彼此间的距离比较而得以较好的反映。然而常规的排序方法主要适用于具有线性结构的数据分析,在2—3维排序图上常难以充分反映这些实体的生态学关系,造成大量生态学数据信息的损失。非度量多维测度(Non-metric multidimensional scaling)是近期发展起来的适用于非线性数据结构分析的一种复杂的迭代排序方法。它的基本思想是通过排序,n个实体在尽可能低维(t相似文献   

四川江津四面山常绿阔叶林永久样地的非线性排序

 本文以四川省江津四面山1 ha永久样地的常绿阔叶林为研究对象,利用样地内20个样方优势乔木种的重要值数据,采用主分量分析(PCA),无偏主分量分析(DPC)和非度量多维调节(NMDS)等方法进行分类和排序。PCA分析结果发现样方坐标数据具有非线性,DPC检测证实其非线性相当明显。通过NMDS分析,经过39次反复迭代,获得结果清楚地反映了群落优势种与环境因子的相互关系,为以后的次生演替研究提供了基础资料。     

Spatial and temporal heterogeneity of the bacterial communities in stream epilithic biofilms

The spatial and temporal variability in bacterial communities within freshwater systems is poorly understood. The bacterial composition of stream epilithic biofilms across a range of different spatial and temporal scales both within and between streams and across the profile of individual stream rocks was characterised using a community DNA-fingerprinting technique (Automated Ribosomal Intergenic Spacer Analysis, ARISA). The differences in bacterial community structure between two different streams were found to be greater than the spatial variability within each stream site, and were larger than the weekly temporal variation measured over a 10-week study period. Greater variations in bacterial community profiles were detected on different faces of individual stream rocks than between whole rocks sampled within a 9-m stream section. Stream temperature was found to be the most important determinant of bacterial community variability using distance-based redundancy analysis (dbRDA) of ARISA data, which may have broad implications for riparian zone management and ecological change as a consequence of global warming. The combination of ARISA with multivariate statistical methods and ordination, such as multidimensional scaling (MDS), permutational manova and RDA, provided rapid and effective methods for quantifying and visualising variation in bacterial community structure, and to identify potential drivers of ecological change.     

Effects of reindeer grazing on understorey vegetation in dry Pinus sylvestris forests

Abstract. Data on floristic composition and environmental variables were collected in floristically homogeneous oligotrophic pine (Pinus sylvestris) forests with heath-like under- storey vegetation in eastern Fennoscandia, and ordinated by non-linear multidimensional scaling (NMDS) in order to study the effect of lichen grazing by reindeer on the understorey vegetation. The study sites included areas with varying grazing pressure, as well as 50-yr old grazing exclosures. Sites rich in respectively bryophytes and lichens were placed at opposite ends of the ordination axes, and heavily grazed sites were placed in between them. Reindeer grazing increased the abundance of bryophytes, especially Dicranum spp. and Pleurozium schreberi. Grazing changed the vegetation to the extent that it resembled more mesotrophic sites, but this did not show any relationship with tree volume or other site productivity indicators. This was observed both in the ordination and, in a more compelling way, when exclosures with adjacent grazed areas were compared. No such signs were evident at ungrazed sites, where especially Cladina spp. spatially replace Cladonia spp. and tiny bryophytes like Barbilophozia spp., Polytrichum spp. and Pohlia nutans during succession. Cladina stellaris had almost disappeared from the most intensively grazed sites. The soil at ungrazed sites was characterized by high Al and Fe concentrations and bryophyte-rich sites by high Mn concentrations. Shannon's diversity index, depth of humus layer and proportion of bare ground also increased in sites getting richer in bryophytes.     

A new methodology for reconstructing climate and vegetation from modern pollen assemblages: an example from British Columbia

Aim We used modern pollen assemblages to develop a method for climate reconstruction that reduces the spatial autocorrelation of residuals and accounts for the strong topographic and climatic variation that occurs in British Columbia, Canada. Location British Columbia, Canada, including sites both on the mainland and on adjacent islands (Queen Charlotte Islands and Vancouver Island). Methods New pollen assemblages from surface‐sediment samples collected in British Columbia were combined with other published and unpublished samples (n = 284). Multivariate rank‐distances between sample sites and a randomized set of sites within the province were calculated for climate parameters to determine whether gaps in the current network of present‐day pollen sample sites exist. Lacustrine surface‐sediment pollen assemblages (n = 145) were ordinated using non‐metric multidimensional scaling (NMDS), and a generalized additive model (GAM) was used to reconstruct modern mean warmest month temperature (MWMT) and mean annual precipitation (MAP) from the NMDS ordination. The results were compared with standard climate reconstruction techniques, including the modern analogue technique, partial least squares, weighted averaging, weighted averaging–partial least squares and factor analysis. Results Reconstructions of MWMT and MAP using NMDS and GAM were comparable to those of existing models. When reconstructing MWMT, the NMDS/GAM method had a lower root‐mean‐squared error of prediction (RMSEP), lower spatial autocorrelation and higher correlation with observed temperature values than the other methods tested. When reconstructing MAP, the partial least squares method performed better than the NMDS/GAM method for RMSEP and correlation with observed values; however, the NMDS/GAM method had a lower spatial autocorrelation of residuals. Main conclusions NMDS reveals strong relationships among modern pollen assemblages, vegetation and climate parameters. Climate models using NMDS and GAM are comparable to other palaeoecological reconstruction models, but provide lower spatial autocorrelation of residuals for both parameters tested. An inverse distance‐weighted surface of multivariate rank‐climate distances generated from the network of pollen sample sites indicates that greater sampling intensity in north‐western and central‐interior British Columbia is required in order to obtain an accurate representation of climatic and vegetation diversity in the province.     

Beta diversity as the variance of community data: dissimilarity coefficients and partitioning

Beta diversity can be measured in different ways. Among these, the total variance of the community data table Y can be used as an estimate of beta diversity. We show how the total variance of Y can be calculated either directly or through a dissimilarity matrix obtained using any dissimilarity index deemed appropriate for pairwise comparisons of community composition data. We addressed the question of which index to use by coding 16 indices using 14 properties that are necessary for beta assessment, comparability among data sets, sampling issues and ordination. Our comparison analysis classified the coefficients under study into five types, three of which are appropriate for beta diversity assessment. Our approach links the concept of beta diversity with the analysis of community data by commonly used methods like ordination and anova . Total beta can be partitioned into Species Contributions (SCBD: degree of variation of individual species across the study area) and Local Contributions (LCBD: comparative indicators of the ecological uniqueness of the sites) to Beta Diversity. Moreover, total beta can be broken up into within‐ and among‐group components by manova , into orthogonal axes by ordination, into spatial scales by eigenfunction analysis or among explanatory data sets by variation partitioning.     

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.