Morphometric Variation in Introduced Populations of the Common Myna (Acridotheres tristis): An Application of the Jackknife to Principal Component Analysis

1984 ◽  
Vol 33 (4) ◽  
pp. 408-421 ◽  
Author(s):  
A. R. Gibson ◽  
A. J. Baker ◽  
A. Moeed
2020 ◽  
Vol 147 ◽  
pp. 02021
Author(s):  
Tia Aprianti Lestari ◽  
Murwantoko Murwantoko ◽  
Eko Setyobudi

This study aimed to identify the species of hairtail caught in Pengandaran waters based on morphological, meristic character and molecular approach. In total 135 fish samples were collected from Pangandaran Waters, during March-April 2017. Each sample was identified, measured on 22 morphometric and 4 meristic characters, then analyzed using Principal Component Analysis (PCA). Molecular identification was conducted by sequenced of 16S rRNA gene. The result of the research showed that hairtail characterized by III spines and 125-140 soft rays of dorsal fin (D.III, 125-140), the anal fin situated below 38th to 41th of dorsal-fin soft ray, I spine and 10 soft rays of pectoral fin (P.I.10), and I spine and 91 to 112 spinules of anal fin (A.I.91-112). Based on the morphological identification, the hairtail was belonged to Trichiurus lepturus. Principal Component Analysis showing the morphometric variation was presented in the caudal peduncle length. Molecular analysis of mitochondrial DNA of the partial 16S rRNA gene confirmed the hairtail as T. lepturus with similarity 98-99% based on previously published data. Phylogenetic analysis showed that T. lepturus from Pangandaran were closely similar to related species caught from the Southern Coast of Yogyakarta Special Territory (Indian Ocean) and Hainan China (Pacific Ocean).


1979 ◽  
Vol 57 (3) ◽  
pp. 570-584 ◽  
Author(s):  
Allan J. Baker ◽  
Abdul Moeed

Common mynas were introduced into New Zealand from Australia in the 1870's. Seventy birds released at Wellington have apparently given rise to populations that now occur almost exclusively north of latitude 40° S. Morphometric variation in 28 characters of 307 adults was assessed statistically, based on eight samples spanning their New Zealand range. Univariate analysis revealed that 17 characters of males and 13 of females varied significantly among localities and that birds tend to be larger in the north. Discriminant analysis confirmed the north–south pattern of differentiation but disclosed that the newly established northern populations are very similar morphometrically. Both sexes have differentiated among localities in size and shape. Size variation is aligned with temperature only in males, and shape differences are associated with variation in precipitation in both sexes and altitude in females, females have differentiated in fewer characters than males, but overall, they show a stronger relationship between interlocality and intralocality character variability. Although the adaptive basis of increased size in warmer climates is unclear, the consistency of character covariation in localities with different climatic conditions argues against an ecophenotypic explanation. It is therefore concluded that the New Zealand populations are in the early stages of adaptive differentiation.


1980 ◽  
Vol 50 (2) ◽  
pp. 351-363 ◽  
Author(s):  
Allan J. Baker ◽  
Abdul Moeed

Morphometric variation in 9 characters of 347 Common Mynas from 10 localities in India was analysed statistically. Both sexes have differentiated similarly among localities in all characters. Character variability within localities is not significantly correlated with that among localities. The patterns of geographic variation are not clinally ordered; contiguous localities often are not most similar morphometrically.


2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Chengcai Leng ◽  
Jinjun Xiao ◽  
Min Li ◽  
Haipeng Zhang

This paper proposes a novel robust adaptive principal component analysis (RAPCA) method based on intergraph matrix for image registration in order to improve robustness and real-time performance. The contributions can be divided into three parts. Firstly, a novel RAPCA method is developed to capture the common structure patterns based on intergraph matrix of the objects. Secondly, the robust similarity measure is proposed based on adaptive principal component. Finally, the robust registration algorithm is derived based on the RAPCA. The experimental results show that the proposed method is very effective in capturing the common structure patterns for image registration on real-world images.


2021 ◽  
Author(s):  
Dashan Huang ◽  
Fuwei Jiang ◽  
Kunpeng Li ◽  
Guoshi Tong ◽  
Guofu Zhou

This paper proposes a novel supervised learning technique for forecasting: scaled principal component analysis (sPCA). The sPCA improves the traditional principal component analysis (PCA) by scaling each predictor with its predictive slope on the target to be forecasted. Unlike the PCA that maximizes the common variation of the predictors, the sPCA assigns more weight to those predictors with stronger forecasting power. In a general factor framework, we show that, under some appropriate conditions on data, the sPCA forecast beats the PCA forecast, and when these conditions break down, extensive simulations indicate that the sPCA still has a large chance to outperform the PCA. A real data example on macroeconomic forecasting shows that the sPCA has better performance in general.


2014 ◽  
Vol 10 (S306) ◽  
pp. 330-332
Author(s):  
Lluís Galbany

AbstractWe present a Principal Component Analysis (PCA) of the V band light-curves of a sample of more than 100 nearby Core collapse supernovae (CC SNe) from [Anderson et al. (2014)]. We used different reference epochs in order to extract the common properties of these light-curves and searched for correlations to some physical parameters such as the burning of 56Ni, and morphological light-curve parameters such as the length of the plateau, the stretch of the light-curve, and the decrements in brightness after maximum and after the plateau. We also used these similarities to create SNe II light-curve templates that will be used in the future for standardize these objects and determine cosmological distances.


Author(s):  
Tali Magory Cohen ◽  
Richard E. Major ◽  
R. Suresh Kumar ◽  
Manoj Nair ◽  
Kyle M. Ewart ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document