Intraspecific variation in Licuala glabra Griff. (Palmae) in Peninsular Malaysia- a morphometric analysis

Loo, Adrian H. B.; Tan, Hugh Tiang Wah; Kumar, Prakash P.; Saw, L. G.

doi:10.1111/j.1095-8312.2001.tb01304.x

Cited by 6 publications

(8 citation statements)

References 14 publications

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“…Multivariate analysis of morphological data can be advantageous because it does not require a priori hypotheses of groups or species delimitations. This approach has been demonstrated to be a powerful method for testing species concepts in other palm groups (Loo et al ., ; Henderson, ; Henderson & Ferreira, ; Henderson, , ). Principal coordinates analysis (PCoA) using Gower's general similarity coefficient (Gower, ) was performed as it has been shown to be appropriate for mixed datasets of qualitative and quantitative characters (Legendre & Legendre, ).…”

Section: Methodsmentioning

confidence: 99%

Species limits, geographical distribution and genetic diversity inJohannesteijsmannia(Arecaceae)

et al. 2016

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Four species are recognized in the understorey palm genus Johannesteijsmannia (Arecaceae), all of which occur in close geographical proximity in the Malay Peninsula. We hypothesize that overlapping distributions are maintained by a lack of gene flow among species and that segregation along morphological trait or environmental axes confers ecological divergence and, hence, defines species limits. Although some species have sympatric distributions, differentiation was detected among species in morphological and genetic data, corroborating current species delimitation. Differences in niche breadth were not found to explain the overlapping distribution and coexistence of Johannesteijsmannia spp. Four species formed over the last 3 Mya, showing that diversity accumulated within a short time frame and wide range expansion has not occurred, potentially due to a lack of time for dispersal or the evolution of traits to facilitate movement. An assessment of genetic diversity is presented and, as expected, the widest distribution in the genus harbours the highest genetic diversity.

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Section: Methodsmentioning

confidence: 99%

Species limits, geographical distribution and genetic diversity inJohannesteijsmannia(Arecaceae)

et al. 2016

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“…The purpose of cluster analysis is to put a set of data in one group (known as clusters) in a manner that the data in one group have no severe differences and be homogeneous and inhomogeneous relative to other groups [5]. Cluster analysis puts the data in groups which are meaningful, beneficial, or both of meaningful and beneficial [12]. Maximum analogy (homogeneity) in a group and dissimilarity between groups implies optimum clustering [12].…”

Section: Cluster Analysis Methodsmentioning

confidence: 99%

“…Cluster analysis puts the data in groups which are meaningful, beneficial, or both of meaningful and beneficial [12]. Maximum analogy (homogeneity) in a group and dissimilarity between groups implies optimum clustering [12]. "Hierarchical clustering" is a method for contemporaneous grouping of data in different scales by clustered tree (dendriform).…”

Section: Cluster Analysis Methodsmentioning

confidence: 99%

Identification of Flow-units using Methods of Testerman Statistical Zonation, Flow Zone Index, and Cluster Analysis in Tabnaak Gas Field

Mahjour

Alaskari

Masihi

2015

J Pet Environ Biotechnol

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The relation between porosity and permeability parameters in carbonated rocks is complicated and indistinct. Flow units are defined with aim of better understanding reservoir unit flow behavior and relation between porosity and permeability. Flow-units reflect a group of rocks with same geological and physical properties which affect fluid flow, but they do not necessarily coincide with boundary of facies. In each flow-unit homogeneity of data preserved and this homogeneity fades in the boundaries. Here in this study three methods are used for identification of flowunits and estimation of average porosity and permeability in three wells of Tabnaak gas field located in south of Iran. These methods include Testerman statistical zonation, flow zone index (FZI), and cluster Analysis. To identify these units, compilation of core porosity and permeability are used. After comparing results of flow units developed by these three methods, a good accordance in permeable zones obtained for them, but for general evaluation of flowunits in field scale, the methods of FZI and cluster analysis are more relevant than Testerman statistical zonation. an open access journal cluster analysis in field scale is difficult if not impossible. Therefor in order to characterize general situation and flow regime of reservoir in field scale, applying flow-units identified by Testerman method is easier and faster.Only core permeability data is used in Testerman method, therefor we face more limitations for recognizing zones with more seperativity potential, and also the number of yielded flow-units is less than the two other methods.

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“…The research presented here is based on studies in systematic biology that examined patterns of correlated character evolution and shared adaptations among closely related species, and accounted for them in phylogeny reconstruction (Harvey and Rambaut, 2000; Martins and Garland, 1991; O'Keefe and Wagner, 2001). The use of principal components analysis to investigate patterns of intraspecific morphological variation also has precedent, both in biology and anthropology (Bräuer, 1984; Kennedy et al, 1984; Loo et al, 2001; Parker and Maze, 1984). This study builds on these previous bodies of research by combining their methods and applying them to the assessment of interpopulation relationships among modern humans.…”

Section: The Present Studymentioning

confidence: 99%

Impact of character correlation and variable groupings on modern human population tree resolution

Athreya

Glantz

2003

American J Phys Anthropol

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Relationships among modern human populations are often explored through the use of linear measurements taken on the cranium and expressed in the form of dendrograms. However, craniometric variables are strongly correlated and thereby violate the assumption of independence that most statistical analyses require. This study explores the relationship between differing methods of variable treatment and the statistical robustness of the outcomes they yield, as depicted in interpopulational trees of relatedness among modern humans. Three methods of grouping variables are examined. The first method leaves them ungrouped, the second groups variables on the basis of the developmental and/or functional complex of the cranium to which they are thought to belong, and the last method reduces variables by using principal components analysis. The strength of each of these methods is tested through the use of the Continuous Character Maximum Likelihood (CONTML) program in the PHYLIP phylogeny inference package. This program produces output in the form of trees, and the resolution of the branching topology is given as a log-likelihood value, with statistical confidence intervals supporting each branch placement on the tree. The results indicate that leaving variables ungrouped provides misleadingly strong results by failing to account for character correlation. Of the alternative two grouping methods, the covarying components method yields the best-resolved tree with stronger statistical support for its topology than the approach of grouping variables on the basis of their location on the cranium. Finally, the implications for interpreting population histories based on such methods are discussed.

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Intraspecific variation in Licuala glabra Griff. (Palmae) in Peninsular Malaysia- a morphometric analysis

Cited by 6 publications

References 14 publications

Species limits, geographical distribution and genetic diversity inJohannesteijsmannia(Arecaceae)

Species limits, geographical distribution and genetic diversity inJohannesteijsmannia(Arecaceae)

Identification of Flow-units using Methods of Testerman Statistical Zonation, Flow Zone Index, and Cluster Analysis in Tabnaak Gas Field

Impact of character correlation and variable groupings on modern human population tree resolution

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