Last edited by Tagis
Thursday, August 6, 2020 | History

2 edition of A multivariate phytogeographic analysis of plant diversity in the Putorana Plateau (N Siberia) found in the catalog.

A multivariate phytogeographic analysis of plant diversity in the Putorana Plateau (N Siberia)

A multivariate phytogeographic analysis of plant diversity in the Putorana Plateau (N Siberia)

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Published by Council for Nordic Publications in Botany in Copenhagen .
Written in English

    Subjects:
  • Multivariate analysis.,
  • Phytogeography -- Russia (Federation) -- Putorana Plateau.,
  • Plant diversity -- Russia (Federation) -- Putorana Plateau.

  • Edition Notes

    Includes bibliographical references (p. 67-72).

    StatementP.L. Nimis ... [et al.].
    SeriesOpera botanica -- 136, Opera botanica -- v. 136.
    ContributionsNimis, P. L.
    Classifications
    LC ClassificationsQK375 .M85 1998
    The Physical Object
    Pagination72 p. :
    Number of Pages72
    ID Numbers
    Open LibraryOL18623158M
    ISBN 108788702642

    about half of the published studied showed a mid -elevation peak in plant species richness. Vegetation interacts with topography and soils, modifying microsites and creating ecological niches for various plants and animals. As a result, animal or insect species richness often mirrors plant species richness along elevation Size: 35KB. INTRODUCTION [5] mentioned that multivariate analysis to be a valid Mungbean (Vigna radiata L. Wilczek) is the third genotypes by multivariate methods in the study is of most important legume (pulse crop) in the Indian practical value to the breeders of mungbean.

    Developing seed zones and transfer guidelines with multivariate regression trees. Tree Genet. Genomes 7, – /s ; Hamrick J. L., Godt M. J. W., Sherman-Broyles S. L. (). Factors influencing levels of genetic diversity in woody plant species. New Forests 6, 95– /BFCited by: 5. Identifying pre-domestication cultivation using multivariate analysis. Add to My Bookmarks Export citation. Type Chapter Author(s) Sue Colledge Page start Page end Is part of Book Title The origins of agriculture and crop domestication: proceedings of the Harlan Symposium, May, , Aleppo, Syria.

    Loss of biodiversity not only disturbs the process of plant development aimed at genetic amelioration but also disrupts the fundamental services that ecosystems provided to humanity. Assessment of variability is a multidimensional problem. The multivariate statistics can help in a comparative assessment of genetic variability. A set of 66 lines of pearl millet was analyzed for .   In the summer of (28 June to 16 October), unglazed ceramic tiles (six sets, each with fifteen ‐cm 2 tiles connected in a 3 × 5 rectangular array) were staked flush with the surface of the streambed across two riffle habitats in each stream. Tiles were incubated for 15 days (SD = 1, range = 14–17), after which a randomly selected tile was collected from each of Cited by:


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A multivariate phytogeographic analysis of plant diversity in the Putorana Plateau (N Siberia) Download PDF EPUB FB2

A multivariate phytogeographic analysis of plant diversity in the Putorana Plateau (N Siberia) Article (PDF Available) in Opera Botanica. Get this from a library. A multivariate phytogeographic analysis of plant diversity in the Putorana Plateau (N Siberia). [P L Nimis;]. Phytogeographic diversity of the Putorana flora (N-Siberia) Article (PDF Available) in Annales Botanici Fennici 32(1) January with Reads How we measure 'reads'.

variance (ANOVA). Its multivariate extension allows us to address similar problems, but looking at more than one response variable at the same time.

Correlations between the plant species occurrences are accounted for in the analysis output. Figure Ordination diagram displaying the first two ordination axes of a redundancy analysis.

After an introduction concerning the tendency to shifting toward using fingerprints to evaluate herbal samples in various contexts and a brief description of the three steps when developing fingerprints, the major part of this chapter focuses on the multivariate data analysis of.

The variability of plants of tetraploid (2n = 4x = 28, AABB genome) wheat germplasm representing accessions from Ethiopia were evaluated for 23 agro-morphological traits at Debre Zeit Agricultural Research Center area, Akaki substation, during the main season using multivariate methods.

This enabled to assess the extent and pattern of variation Cited by: Search within book. Front Matter. Pages I-IX. PDF. Introduction. László Orlóci. Pages Identification. László Orlóci.

Pages Multivariate Analysis — A Discussion. László Orlóci. Pages Back Matter. Pages PDF. About this book. Keywords. biology botany plant science research statistics Vegetation. Multivariate Perspective to Understanding Plant Diversity Patterns in Ecological Communities This chapter illustrates the systematic application of a multivariate perspective using SEM to explore a topic.

In this presentation, the statistical details of the analyses will be ignored; these have been. A multivariate phytogeographic analysis of plant diversity in the Putorana Plateau (N Siberia). Opera Botanica, 72p. Friesen N. and N. Herrmann.

Taxonomy, chorology and evolution of Allium lusitanicum - the European „A. senescens„. Linzer Biologische Beiträge. PDF File. The first applications of multivariate analysis in ecology and systematics were in plant ecology (54, ) and numerical taxonomy () more than 30 years ago.

In our survey of the literature, we found 20 major summaries of recent applications. Between andbooks, proceedings of sym­File Size: 1MB. Multivariate statistical analysis techniques were used to establish the relationships between plant diversity, Topography and soil factors.

Plant community, structure and biodiversity have been shown to have a high degree of spatial variability that is controlled by both abiotic and biotic factors (Fu et al,).Cited by: 2. We examined variability in hierarchical beta diversity across ecosystems, geographical gradients, and organism groups using multivariate spatial mixed modeling analysis of two independent data sets.

The larger data set comprised reported ratios of regional species richness (RSR) to local species richness (LSR) and the second data set consisted Cited by: Hence, MULTIVARIATE ANALYSIS IN PROCESS MORPHOLOGY TABLE 2 Data matrix fi~r all process combinations analyzed, i.e.

combinations corresponding to typical and atypical or controversial structures of the vegetative region of flowering plants as well as typical structures of more primitive vascular and thallose by: Keywords: Ethiopian mustard, Genetic diversity, leaf morphological traits univariate analysis, multivariate analysis.

INTRODUCTION The genus Brassica of Brassicaceae family as a whole is believed to have originated around the Mediterranean, Eastern Afghanistan and the adjoining portion of Pakistan and North-Eastern Africa (Hemingway, ).Author: Fekadu Amsalu, Sentayehu Alamerew, Bulcha Woyessa.

Species diversity (SD) and total plant coverage (PC) are commonly used predictors of primary productivity (i.e., above ground biomass (ABG)). PC is a characteristic frequently used in remote sensing to assess land cover, land use, and vegetative condition, while species diversity serves as a measure of the existence and utilization of ecological by: 9.

() reported a phytogeographical analysis of plant species that comprise the flora of the Putorana Plateau in north Siberia. They constructed maps of the geographical distributions of all constituent species, and used numerical analysis to define species groups (chorotypes) based on similar geographical distributions of component by: 84 Association-Analysis in Plant Communities B.

Terminology, symbols and definitions (i) Association will be used throughout in its statistical sense. It is the tradi-tional term where attributes rather than quantitative measurements are con-cerned, and we prefer to reserve the term 'correlation' (etnployed by Goodall) for.

canadensis. In a multivariate analysis of the S. canadensis / complex, Semple et al. () dealt with the varieties in S. canadensis but not those within S. altissima. Solidago altiplanities and S. juliae of subsect. Triplinerviae have been included in the informal Tortifolia Group (Semple Multivariate analysis in Mungbean (Vigna radiata L.

Wilczek) for Genetic Diversity under Acidic Soils of Manipur, India Muniyandi Samuel Jeberson1*, Kadanamari Sankarappa Shashidhar2, Shabir H.

Wani3 and Amit Kumar Singh4 1Plant Breeding, 2Agronomy, AICRP on MULLaRP, DoR, Central Agricultural University, Imphal, Manipur, India. and in many other research problems the type of multivariate analysis illustrated by Steel is usually inappropriate and often actively mis-leading.

REFERENCES Dutton, A. Application of some multivariate analysis techniques to data from radiation experiments. In Statistics and Mllathematics in Biology, edited by 0. The most traditional approach to inventorying the plant diversity of a given area - e.g.

a bog, a nature reserve or a province - consists of the preparation of floristic lists, also known as floras. The term 'flora' has been variously defined, but here we follow Lawrence (): “the inventory of all the plant species recorded for a given File Size: KB.

Multivariate analysis of morphological characteristics of two species of passion flower with ornamental potential and of hybrids between them. Santos EA(1), Souza MM, Viana AP, Almeida AA, Freitas JC, Lawinscky PR.

Author information: (1)Departamento de Ciências Biológicas, Universidade Estadual de Santa Cruz, Ilhéus, BA, by: Recently, efforts to develop multivariate models of plant species richness have been extended to include systems where trees play important roles as overstory elements mediating the influences of environment and disturbance on understory richness.

We used structural equation modeling to examine the relationship of understory vascular plant species richness to understory .