Classification and ordination of cryptogamic communities in Wilkes Land,Continental Antarctica

The entirely cryptogamic vegetation of Bailey and Clark Peninsulas, Windmill Islands, Budd Coast, Wilkes Land, Antarctica, is described for the first time. The vegetation of this area is exceptionally well developed and diverse and represents one of the most important botanical sites on the continent. The macroflora comprises three species of moss, one liverwort, three fruticose lichens, four foliose and over 20 crustose lichens; several macroalgae also occur. Seventy stands of relatively homogeneous vegetation were analysed and the percentage cover afforded by every species within 20 quadrats per site was recorded. A subjective classification was developed by visual ordering of the data sets and a hierarchical system erected which incorporates one moss- and one lichen-dominated sub-formation; the former includes two associations and seven sociations, while the latter comprises one association which includes four sociations. The data were then arranged by centroid linkage analysis to produce and objective classification, and subsequently ordinated by principal components analysis to generate groups of stands, the inter-relations of which were interpreted in ecological and environmental terms. The objective classification and ordination strongly support the subjectively derived groupings or sociations. Examples of plant interactions are qualitatively described.     

对中国植被分类系统的认知和建议

《中国植被志》的编写工作已经启动, 藉此征求修订《中国植被分类系统》意见之际, 提出几点看法与建议: 1)贯彻原先制定的中国植被“高级分类单位偏重于生态外貌, 而中、低级分类单位则着重种类组成和群落结构”的分类原则。这一思想与当前国际上植被分类的发展是一致的。2)中国植被分类既要符合中国植被的特点, 又要适应全球植被分类的发展, 名词概念应尽量与国际上的广泛理解相一致。3) “群丛”是《中国植被志》描述的基本对象, 其概念需要统一, 以避免歧义和可能导致的南北“群丛”的不等质。资料不足的类型应组织野外补点调查。4)植被分类等级系统是严格的, 但各等级又是开放的, 可适当地增设高级分类单位, 以适应类型扩展之需要。该文附有从植被型纲到植被型的建议草案。     

Implementation of a hierarchical global vegetation classification in ecosystem function models

Abstract. We propose an alternative approach for the currently used biogeographic global vegetation classifications. A hierarchical vegetation classification system is proposed for consistent and routine monitoring of global vegetation. Global vegetation is first defined into six classes based on plant canopy structure and dynamics observable by remote sensing from satellites. Additional biome variability is then represented through a remote sensing derived leaf area index map, and direct climate data sets driving an ecosystem model to compute and map net primary production and evapotranspiration. Simulation results from an ecosystem function model suggest that the six canopy structure-based classes are sufficient to represent global variability in these parameters, provided the spatio-temporal variations in Leaf Area Index and climate are characterized accurately. If a bioclimatically based classification is needed for other purposes, our six class approach can be expanded to a possible 21 classes using archived climatic zones. For example, tropical, subtropical, temperate and boreal labels are defined by absolute minimum temperature. Further separation in each class is possible through changes in water availability defined by precipitation and/or soils. The resulting vegetation classes correspond to many of the existing, conventional global vegetation schemes, yet retain the measure of actual vegetation possible because remote sensing first defines the six biome classes in our classification. Vegetation classifications are no longer an end product but a source of initializing data for global ecosystem function models. Remote sensing with biosphere models directly calculates the ecological functions previously inferred from vegetation classifications, but with higher spatial and temporal accuracy.     

Classification and ecology of the mid‐seral Picea mariana forests of British Columbia

Abstract. We sampled vegetation and soils of, and classified mid‐seral, even‐aged, fire‐origin, upland Picea mariana ecosystems in the Boreal White & Black Spruce and Sub‐boreal Spruce zones of British Columbia, Canada. We applied multi‐variate and tabular methods to analyse and synthesize the data from 121 plots according to the methods of biogeoclimatic ecosystem classification. We delineated seven basic vegetation units and described their vegetation and environmental features. However, the delineated units could not be related to neither of the taxonomies proposed for the North American boreal forest communities. Although species‐poor, the under‐storey vegetation in the sampled ecosystems provided for a sufficient floristic differentiation, which matched well the major edaphic differences between the units. The classification of mid‐seral boreal ecosystems may be more useful that based on old‐growth stands that are infrequent or lacking in the landscape due to wildfires.     

The value of plant functional groups in demonstrating and communicating vegetation responses to environmental flows

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A consensus view of fold space: combining SCOP, CATH, and the Dali Domain Dictionary

We have determined consensus protein-fold classifications on the basis of three classification methods, SCOP, CATH, and Dali. These classifications make use of different methods of defining and categorizing protein folds that lead to different views of protein-fold space. Pairwise comparisons of domains on the basis of their fold classifications show that much of the disagreement between the classification systems is due to differing domain definitions rather than assigning the same domain to different folds. However, there are significant differences in the fold assignments between the three systems. These remaining differences can be explained primarily in terms of the breadth of the fold classifications. Many structures may be defined as having one fold in one system, whereas far fewer are defined as having the analogous fold in another system. By comparing these folds for a nonredundant set of proteins, the consensus method breaks up broad fold classifications and combines restrictive fold classifications into metafolds, creating, in effect, an averaged view of fold space. This averaged view requires that the structural similarities between proteins having the same metafold be recognized by multiple classification systems. Thus, the consensus map is useful for researchers looking for fold similarities that are relatively independent of the method used to compare proteins. The 30 most populated metafolds, representing the folds of about half of a nonredundant subset of the PDB, are presented here. The full list of metafolds is presented on the Web.     

Vegetation of the greater Maya Mountains,Belize

This paper describes a new vegetation classification for the Greater Maya Mountains of Belize, focusing primarily on the Chiquibul Forest Reserve. Extensive use is made of GIS, remote sensing, botanical collections and field visits to provide a macro‐ and meso‐scale overview of the vegetation of this region. A total of 32 vegetation classes have been defined, both geographically and structurally, including 11 new classes. Where possible, classes have been compared with earlier classifications. A dominant scaling technique has been used to enable direct comparison between ground truthing data and a supervised Maximum Likelihood Classifier image‐based vegetation classification. The merits of such classifications and the effect of scale are discussed.     

Comparison of an intuitive mapping classification and numerical classifications of vegetation in south-east Queensland,Australia

Hierarchical agglomerative polythetic clustering of vegetation data for 51 sites from Brian Pastures Research Station, south-east Queensland, Australia, produced site and species groups that supported those formed during a previous intuitive mapping survey. On the basis of floristic composition, these analyses suggested the possible amalgamation of some map units. However, their segregation into separate units was justified on the basis of having distinct photopatterns and physiographic positions in the landscape. The classifications of the trees only (55 species) and woody plants only (115 species) data sets produced site groupings of high similarity to those constructed by the mapping survey. The addition of the herbaceous plants (266 additional species, of which 70% were annual species) tended to dominate the analyses, and produce site groupings that were less similar to the mapping groups. The distribution of many annual species appeared to be independent of the perennial plant species and underlying substrate. In wooded communities, herbaceous plants have only a minor influence on photopattern, which is the primary determinant of the mapping classification. Binary data retained a large percentage of the information contained in the quantitative data. The extra effort of gathering herbaceous data may not be justified for a broad scale mapping project, but is required for comprehensive nature conservation surveys, flora inventory, and vegetation monitoring purposes.     

Diversity of bryophyte vegetation in some forest types in Estonia: a comparison of old unmanaged and managed forests

The bryophyte vegetation of 3 pairs of unmanaged and managed forest stands, representing Oxalis drained peatland, Aegopodium and Oxalis forest site type, were compared. The total number of bryophyte species in unmanaged stands was 74 and that in managed stands 54. Out of the 20 species occurring only in unmanaged forests, 9 grow on decaying wood, and 3 on trunks or bases of big trees; 13 of them were hepatics. In unmanaged forests 11 hemerophobic species were recorded altogether. Although the difference in substrate and species diversity between unmanaged and managed stands is not statistically significant, in unmanaged forests more substrates characteristic for an old-growth stand are available, and the percentage of species preferring dryer habitats or prolonged humidity is a bit higher than in managed forests; the percentage of species associated with better illuminated habitats is higher in managed forests. Analysis of classification structure of the bryophyte layer synusia shows that the number of societies is also higher in unmanaged forests. This is associated with more numerous microhabitats; the average light and humidity indices calculated for every society, confirm this conclusion. The large discrepancy in bryophyte layer classification structure in old-growth and managed forests of the same forest site type is manifested not so much by species content in synusia as by their abundance proportions. The larger diversity of classification units in unmanaged forests is also seen at the synusia facies level; four of nine facies are confined exclusively to unmanaged stands. This is a strong argument for the informativeness of bryophyte layer classification structure for purposes of indication and monitoring as well.     

Classification of vegetation sequences in Toohey Forest,Queensland

In this paper we consider one method of mapping larger units identified from the spatial pattern of sequences of vegetation types. The basic data were presence/absence data for 6450 stands arranged in 90 transects. A second set of data was derived by averaging the species occurrences in non-overlapping groups of 5 stands. A divisive numerical classification was used to determine the primary vegetation units. In all, 5 different sets of primary types were derived, using different species suites, different sample sizes and different numerical methods. We briefly discuss the types identified and their spatial patterns in the area.Each of these types was then used to define a string of type-codes for every transect so that each transect represents a sample from the landscape containing information on the frequency and spatial distribution of the primary vegetation types. The transects may be classified using a Levenshtein dissimilarity measure and agglomerative hierarchical classification, giving 5 analyses of transects, one for each of the primary types discussed above. We then examine these transect classifications to investigate the stability of the vegetation landspace patterns under changes in species used for the primary classification, in size of sample unit and in method of primary classifications. There is a considerable degree of stability in the results. However it seems with this vegetation that the tree species and non-tree species have considerable independence. We also indicate some problems with this approach and some possible extensions.     

Stems,nodes, crown clades,and rank‐free lists: is Linnaeus dead?

Recent radical proposals to overhaul the methods of biological classification are reviewed. The proposals of phylogenetic nomenclature are to translate cladistic phylogenies directly into classifications, and to define taxon names in terms of clades. The method has a number of radical consequences for biologists: taxon names must depend rigidly on the particular cladogram favoured at the moment, familiar names may be reassigned to unfamiliar groupings, Linnaean category terms (e.g. phylum, order, family) are abandoned, and the Linnaean binomen (e.g. Homo sapiens) is abandoned. The tenets of phylogenetic nomenclature have gained strong support among some vocal theoreticians, and rigid principles for legislative control of clade names and definitions have been outlined in the PhyloCode. The consequences of this semantic maelstrom have not been worked out. In pratice, phylogenetic nomenclature will bc disastrous, promoting confusion and instability, and it should be abandoned. It is based on a fundamental misunderstanding of the difference between a phylogeny (which is real) and a classification (which is utilitarian). Under the new view, classifications are identical to phlylogenies, and so the proponents of phylogenetic nomenclature will end up abandoning classifications altogether.     

Modified TWINSPAN classification in which the hierarchy respects cluster heterogeneity

Aim: To propose a modification of the TWINSPAN algorithm that enables production of divisive classifications that better respect the structure of the data. Methods: The proposed modification combines the classical TWINSPAN algorithm with analysis of heterogeneity of the clusters prior to each division. Four different heterogeneity measures are involved: Whittaker's beta, total inertia, average Sørensen dissimilarity and average Jaccard dissimilarity. Their performance was evaluated using empirical vegetation datasets with different numbers of plots and different levels of heterogeneity. Results: While the classical TWINSPAN algorithm divides each cluster coming from the previous division step, the modified algorithm divides only the most heterogeneous cluster in each step. The four tested heterogeneity measures may produce identical or very similar results. However, average Jaccard and Sørensen dissimilarities may reach extreme values in clusters of small size and may produce classifications with a highly unbalanced cluster size. Conclusions: The proposed modification does not alter the logic of the TWINSPAN classification, but it may change the hierarchy of divisions in the final classification. Thus, unsubstantiated divisions of homogeneous clusters are prevented, and classifications with any number of terminal clusters can be created, which increases the flexibility of TWINSPAN.     

Reconciling approaches to biogeographical regionalization: a systematic and generic framework examined with a case study of the Australian continent

Aim To develop a systematic and generic framework for biogeographical regionalizations that can assist in reconciling different approaches and advance their application as a research tool. Location The Australian continent is used as a case study. Methods A review of approaches to biogeographical regionalization revealed two basic methodologies: the integrated survey method and the parametric approach. To help reconcile these different approaches, we propose a simple, four‐step, flexible and generic framework. (1) Identification of the thematic foci from the three main themes (composition and evolutionary legacy; ecosystem drivers; ecosystem responses). (2) Proposal of a theory defining the purpose. (3) Application of a numeric agglomerative classification procedure that requires the user to make explicit assumptions about attributes, the number of classification groups, the spatial unit of analysis, and the metric for measuring the similarity of these units based on their attribute values. (4) Acquisition of spatial estimates of the required input attribute data. For this case study, an agglomerative classification strategy was applied using the functions within patn 3.03, a software package facilitating large‐scale, multivariate pattern analysis. The input data to the classifications were continental coverages of 11 environmental variables and three indices of gross primary productivity stored at a grid cell resolution of c. 250 m. The spatial units of analysis were surface hydrological units (SHU), which were derived from a continental digital elevation model based on the contributing areas to stream segments or the area draining into a local sink where there is no organized drainage. The Minkowski series (Euclidean distance) was selected as the association measure to allow weightings to be applied to the variables. Results Two new biogeographical regionalizations of the Australian continent were generated. The first was an environmental domain classification, based on 11 climatic, terrain and soil attributes. This regionalization can be used to address hypotheses about the relationship between environmental distance and evolutionary processes. The classification produced 151 environmental groups. The second was a classification of primary productivity regimes based on estimates of the gross primary productivity of the vegetation cover calculated from moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data and estimates of radiation. This classification produced 50 groups, and can be used to examine hypotheses concerning productivity regimes and animal life‐history strategies. The productivity classification does not capture all the properties related to biological carrying capacity, process rates and differences in the characteristic biodiversity of ecosystems. Some of these ecologically significant properties are captured by the environmental domain classification. Main conclusions Our framework can be applied to all terrestrial regions, and the necessary data for the analyses presented here are now available at global scales. As the spatial predictions generated by the classifications can be tested by comparison with independent data, the approach facilitates exploratory analysis and further hypothesis generation. Integration of the three themes in our framework will contribute to a more comprehensive approach to biogeography.     

Can vegetation be discretely classified in species-poor environments? Testing plant community concepts for vegetation monitoring on sub-Antarctic Marion Island

The updating and rethinking of vegetation classifications is important for ecosystem monitoring in a rapidly changing world, where the distribution of vegetation is changing. The general assumption that discrete and persistent plant communities exist that can be monitored efficiently, is rarely tested before undertaking a classification. Marion Island (MI) is comprised of species-poor vegetation undergoing rapid environmental change. It presents a unique opportunity to test the ability to discretely classify species-poor vegetation with recently developed objective classification techniques and relate it to previous classifications. We classified vascular species data of 476 plots sampled across MI, using Ward hierarchical clustering, divisive analysis clustering, non-hierarchical kmeans and partitioning around medoids. Internal cluster validation was performed using silhouette widths, Dunn index, connectivity of clusters and gap statistic. Indicator species analyses were also conducted on the best performing clustering methods. We evaluated the outputs against previously classified units. Ward clustering performed the best, with the highest average silhouette width and Dunn index, as well as the lowest connectivity. The number of clusters differed amongst the clustering methods, but most validation measures, including for Ward clustering, indicated that two and three clusters are the best fit for the data. However, all classification methods produced weakly separated, highly connected clusters with low compactness and low fidelity and specificity to clusters. There was no particularly robust and effective classification outcome that could group plots into previously suggested vegetation units based on species composition alone. The relatively recent age (c. 450,000 years B.P.), glaciation history (last glacial maximum 34,500 years B.P.) and isolation of the sub-Antarctic islands may have hindered the development of strong vascular plant species assemblages with discrete boundaries. Discrete classification at the community-level using species composition may not be suitable in such species-poor environments. Species-level, rather than community-level, monitoring may thus be more appropriate in species-poor environments, aligning with continuum theory rather than community theory.     

Towards unification of national vegetation classifications: A comparison of two methods for analysis of large data sets

Abstract. In European phytosociology, national classifications of corresponding vegetation types show considerable differences even between neighbouring countries. Therefore, the European Vegetation Survey project urgently needs numerical classification methods for large data sets that are able to produce compatible classifications using data sets from different countries. We tested the ability of two methods, TWINSPAN and COCKTAIL, to produce similar classifications of wet meadows (Calthion, incl. Filipendulenion) for Germany (7909 relevés) and the Czech Republic (1287 relevés) in this respect. In TWINSPAN, the indicator ordination option was used for classification of two national data sets, and the extracted assignment criteria (indicator species) were applied crosswise from one to the other national data set. Although the data sets presumably contained similar community types, TWINSPAN revealed almost no correspondence between the groups derived from the proper classification of the national data set and the groups defined by the assignment criteria taken from the other national data set. The reason is probably the difference in structure between the national data sets, which is a typical, but hardly avoidable, feature of any pair of phytosociological data sets. As a result, the first axis of the correspondence analysis, and consequently the first TWINSPAN division, are associated with different environmental gradients; the difference in the first division is transferred and multiplied further down the hierarchy. COCKTAIL is a method which produces relevé groups on the basis of statistically formed species groups. The user determines the starting points for the formation of species groups, and groups already found in one data set can be tested for existence in the other data set. The correspondence between the national classifications produced by COCKTAIL was fairly good. For some relevé groups, the lack of correspondence to groups in the other national data set could be explained by the absence of the corresponding vegetation types in one of the countries, rather than by methodological problems.     

Towards more meaningful hierarchical classification of amino acid scoring matrices.

Hierarchical classifications of the 20 amino acids according to residue relationships within scoring matrices have not hitherto been tested for reliability. In fact, testing here of the residue groupings obtained thus from 18 published matrices shows that they vary considerably in reliability. This behaviour gives a new insight then into the matrices with respect to the relationships between the amino acid scores contained therein. For example, other than the trivial grouping of the 20 amino acids, no reliable residue groupings are present in all 18 matrix amino acid hierarchical classifications. Hierarchical classification of the 18 scoring matrices themselves is investigated in terms of matrix representation and choice of similarity and dissimilarity measures for matrix comparison. There is no absolute standard against which to compare a matrix clustering, of course, but it is possible to assess the usefulness of a measure for the purpose in terms of the reliability of the calculated tree. Matrix representation is shown to be important. Finally, a novel two-step approach for hierarchical classification of the 18 amino acid scoring matrices is described.