METHODOLOGICAL INSIGHTS: Increasing the value of principal components analysis for simplifying ecological data: a case study with rivers and river birds

2005 ◽  
Vol 42 (3) ◽  
pp. 487-497 ◽  
Author(s):  
I. P. VAUGHAN ◽  
S. J. ORMEROD
Keyword(s):  
Principal Components Analysis ◽  
Principal Components ◽  
Ecological Data ◽  
Components Analysis

scholarly journals Raman investigation of corrosion products on Roman copper-based artefacts

ACTA IMEKO ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 129
Author(s):  
Leila Es Sebar ◽  
Leonardo Iannucci ◽  
Yuval Goren ◽  
Peter Fabian ◽  
Emma Angelini ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Roman Period ◽  
Corrosion Products ◽  
Beer Sheva ◽  
Chemometric Technique ◽  
Components Analysis ◽  
Main Components

<p class="Abstract">This paper illustrates a case study related to the characterisation of corrosion products present on recently excavated artefacts. The archaeological findings, from the Rakafot 54 site (Beer-Sheva, Israel), consist of 23 coins and a pendant, all dating back to the Roman period. Raman spectroscopy was used to identify the corrosion products that compose the patina covering the objects. To facilitate and support their identification, spectra were then processed using principal components analysis. This chemometric technique allowed the identification of two main compounds, classified as atacamite and clinoatacamite, which formed the main components of the patinas. The results of this investigation can help in assessing the conservation state of artefacts and defining the correct restoration strategy.</p>

Using multivariate factorial kriging for multiscale ordination: a case study

2005 ◽  
Vol 35 (12) ◽  
pp. 2860-2874 ◽  
Author(s):  
Nikos Nanos ◽  
Fernando Pardo ◽  
Jesus Alonso Nager ◽  
José Alberto Pardos ◽  
Luis Gil
Keyword(s):  
Principal Components Analysis ◽  
Principal Components ◽  
Multiple Scale ◽  
Analysis Data ◽  
Vegetation Pattern ◽  
Soil Conditions ◽  
Linear Model Of Coregionalization ◽  
Factorial Kriging ◽  
Components Analysis

Vegetation ordination is usually based on classical data reduction techniques such as principal components analysis, correspondence analysis, or multidimensional scaling. The usual methods do not account for multiscale correlations among species. In this paper, we use a geostatistical method, known as multivariate factorial kriging, for studying multiple-scale correlations. The case study was carried out in a mixed broadleaf forest of central Spain. Six tree species were included in the analysis. Data analysis included (i) experimental variogram calculation and modeling with the use of the linear model of coregionalization, (ii) principal components analysis, and (iii) cokriging. The results indicate that correlations among species are different depending on the spatial scale. We conclude that competition for light is the main factor controlling the spatial distribution of species at the plot-level scale of variation. At larger scales of variation, soil conditions and (or) human intervention are the key factors in determining the observed vegetation pattern. Based on the factor scores for the largest scale of variation, we conducted a cluster analysis to identify plots with similar characteristics. The resulting clusters have the remarkable property of being spatially continuous.

scholarly journals Resolving the anomaly of Lomatium anomalum: discovery of a new species in southwestern Idaho (U.S.A.) Lomatium andrusianum (Apiaceae)

2018 ◽  
Vol 12 (1) ◽  
pp. 1-15
Author(s):  
Mckayla Stevens ◽  
Donald H. Mansfield ◽  
James F. Smith ◽  
Mary Ann E. Feist
Keyword(s):  
New Species ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Species Boundaries ◽  
Monophyletic Clade ◽  
Ecological Data ◽  
Components Analysis ◽  
Multiple Species ◽  
Vegetative Characters ◽  
A New Species

Apparent polyphyly within the unresolved clade of Lomatium (Apiaceae) containing L. triternatum, L. anomalum, L. thompsonii, and L. packardiae suggests conflict among current taxonomic classification schemes. To recover this clade and more clearly define species boundaries, we examined populations of L. anomalum from three geographic regions in Idaho and adjacent Oregon. Using phylogenetic, morphological, and ecological data, we conclude that the L. anomalum complex currently circumscribes multiple species. Phylogenetic analysis of the nuclear ribosomal ITS and ETS, and cpDNA rpl32-trnLUAG, rps-16 intron, trnD-trnT, ndhA intron, and psbA-trnH recovered populations from the Boise foothills as a distinct, monophyletic clade. Principal Components Analysis of 30 reproductive and vegetative characters show two distinct groups: one of Boise foothills and one of the combined Mann Creek and Camas Prairie vicinities. Principal Components Analysis of 16 soil characteristics show that soils occupied by Boise foothills populations are distinct from those occupied by Mann Creek and Camas Prairie populations. Based on phylogenetic, morphometric, and ecologic criteria, populations of what had been considered L. anomalum from the Boise foothills and vicinity are here described as a new species—Lomatium andrusianum. 

scholarly journals Principal Components Analysis (PCA) of Monument Stone Decay by Rainwater: A Case Study of “Basílica da Estrela” Church, Portugal

Proceedings ◽  
2018 ◽  
Vol 2 (10) ◽  
pp. 560
Author(s):  
Carlos Figueiredo ◽  
Carlos Alves
Keyword(s):  
Electrical Conductivity ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Ionic Species ◽  
Underlying Structure ◽  
Stone Decay ◽  
Extended Version ◽  
Stepwise Approach ◽  
Components Analysis

An extended version of Principal Components Analysis (PCA) of monument stone decay phenomena occurring at “Basilica da Estrela” church, Lisbon, Portugal, is now presented. The PCA rationale and general methodological procedure is presented, as a first step of a stepwise approach to the eigenvector methods of data analysis. PCA, as others “Eigenvector Methods”, seeks to reveal the underlying structure that might exist within a set of multivariate observations. Temperature, pH, electrical conductivity and main ionic species were measured on several seepage samples over three years inside the monument. PCA results are discussed in the perspective of a nondestructive tool.

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