Wintertime ocean conditions synchronize rockfish growth and seabird reproduction in the central California Current ecosystem

2010 ◽  
Vol 67 (7) ◽  
pp. 1149-1158 ◽  
Author(s):  
Bryan A. Black ◽  
Isaac D. Schroeder ◽  
William J. Sydeman ◽  
Steven J. Bograd ◽  
Peter W. Lawson
Keyword(s):  
Time Series ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Southern Oscillation ◽  
California Current ◽  
Data Set ◽  
Central California ◽  
Components Analysis ◽  
Ocean Conditions ◽  
Upwelling Index

Chronologies developed from annual growth-increment widths of splitnose rockfish ( Sebastes pinniger ) and yelloweye rockfish ( Sebastes ruberrimus ) otoliths were compared with time series of lay date and fledgling success for the common murre ( Uria aalge ) and Cassin’s auklet ( Ptychoramphus aleuticus ) in the north-central California Current. All time series were exactly dated and spanned 1972 through 1994. In a principal components analysis, the leading principal component (PC1bio) accounted for 64% of the variance in the data set. By entering the upwelling index, the Northern Oscillation index, sea surface temperatures, and the multivariate ENSO (El Niño Southern Oscillation) index into principal components analysis, a time series of environmental variability PC1env was developed for each month of the year. Over the interval 1972 through 1994, PC1bio most strongly correlated with PC1env for February and, to a lesser extent, January and March. Moreover, when each of the six biological time series was related to the 12 PC1env through stepwise multiple regression, February was always the most significant (p < 0.01). The same was true if upwelling index was substituted for PC1env. As upper-trophic predators, rockfish and seabirds independently corroborate that wintertime ocean conditions are critical for productivity in the California Current ecosystem.

scholarly journals Dietary patterns in UK adolescents obtained from a dual-source FFQ and their associations with socio-economic position, nutrient intake and modes of eating

2013 ◽  
Vol 17 (7) ◽  
pp. 1476-1485 ◽  
Author(s):  
Kate Northstone ◽  
Andrew DAC Smith ◽  
Victoria L Cribb ◽  
Pauline M Emmett
Keyword(s):  
Principal Components Analysis ◽  
Principal Components ◽  
Dietary Patterns ◽  
Data Set ◽  
Sociodemographic Differences ◽  
Traditional Health ◽  
Parents And Children ◽  
Components Analysis ◽  
Positive Correlations ◽  
Dietary Data

AbstractObjectiveTo derive dietary patterns using principal components analysis from separate FFQ completed by mothers and their teenagers and to assess associations with nutrient intakes and sociodemographic variables.DesignTwo distinct FFQ were completed by 13-year-olds and their mothers, with some overlap in the foods covered. A combined data set was obtained.SettingAvon Longitudinal Study of Parents and Children (ALSPAC), Bristol, UK.SubjectsTeenagers (n 5334) with adequate dietary data.ResultsFour patterns were obtained using principal components analysis: a ‘Traditional/health-conscious’ pattern, a ‘Processed’ pattern, a ‘Snacks/sugared drinks’ pattern and a ‘Vegetarian’ pattern. The ‘Traditional/health-conscious’ pattern was the most nutrient-rich, having high positive correlations with many nutrients. The ‘Processed’ and ‘Snacks/sugared drinks’ patterns showed little association with important nutrients but were positively associated with energy, fats and sugars. There were clear gender and sociodemographic differences across the patterns. Lower scores were seen on the ‘Traditional/health conscious’ and ‘Vegetarian’ patterns in males and in those with younger and less educated mothers. Higher scores were seen on the ‘Traditional/health-conscious’ and ‘Vegetarian’ patterns in girls and in those whose mothers had higher levels of education.ConclusionsIt is important to establish healthy eating patterns by the teenage years. However, this is a time when it is difficult to accurately establish dietary intake from a single source, since teenagers consume increasing amounts of foods outside the home. Further dietary pattern studies should focus on teenagers and the source of dietary data collection merits consideration.

The use of principal components analysis for the investigation of an organic air pollutants data set

1984 ◽  
Vol 18 (11) ◽  
pp. 2471-2478 ◽  
Author(s):  
J. Smeyers-Verbeke ◽  
J.C. Den Hartog ◽  
W.H. Dehker ◽  
D. Coomans ◽  
L. Buydens ◽  
...  
Keyword(s):  
Principal Components Analysis ◽  
Principal Components ◽  
Air Pollutants ◽  
Data Set ◽  
Components Analysis

scholarly journals Multivariate Characterization of Hydrogen Balmer Emission in Cataclysmic Variables

2006 ◽  
Vol 23 (3) ◽  
pp. 106-118 ◽  
Author(s):  
Gordon E. Sarty ◽  
Kinwah Wu
Keyword(s):  
Principal Components Analysis ◽  
Discriminant Function ◽  
Principal Components ◽  
Discriminant Function Analysis ◽  
Function Analysis ◽  
Cataclysmic Variables ◽  
Data Set ◽  
Analysis Methods ◽  
Wide Range ◽  
Components Analysis

AbstractThe ratios of hydrogen Balmer emission line intensities in cataclysmic variables are signatures of the physical processes that produce them. To quantify those signatures relative to classifications of cataclysmic variable types, we applied the multivariate statistical analysis methods of principal components analysis and discriminant function analysis to the spectroscopic emission data set of Williams (1983). The two analysis methods reveal two different sources of variation in the ratios of the emission lines. The source of variation seen in the principal components analysis was shown to be correlated with the binary orbital period. The source of variation seen in the discriminant function analysis was shown to be correlated with the equivalent width of the Hβ line. Comparison of the data scatterplot with scatterplots of theoretical models shows that Balmer line emission from T CrB systems is consistent with the photoionization of a surrounding nebula. Otherwise, models that we considered do not reproduce the wide range of Balmer decrements, including ‘inverted’ decrements, seen in the data.

scholarly journals Estimationof a Tax Compliance Index with Specific Application to Pay-As-You-Earn

2021 ◽  
Vol 04 (02) ◽  
Author(s):  
Cathrine T Koloane ◽  
Keyword(s):  
Time Series ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Composite Index ◽  
Tax Compliance ◽  
Upward Trend ◽  
Monthly Data ◽  
The World ◽  
The Future ◽  
Components Analysis

This article provides a composite index for Pay-As-You-Earn (PAYE)tax using Principal Components Analysis (PCA). The study uses time series from April 2012 to March 2020 (using monthly data) for the ratios derived from the four compliancemeasures namely, payments on time, registration on time, filing on time and accurate declarations. The index is computed using the weights of the four derived principal components. According to the model results, the PAYE tax compliance index averages around 75.0% for the period, with the lowest value of 72.3% in 2013/14 and the highestvalue of 77.1% achieved in 2018/19. There is a clear upward trend, indicating improving levels of compliance in PAYE. Similarly, setting the baseline index of 100 i.e. assuming 100% compliance for 2012/13, results in PAYE tax compliance index averaging around 101.6% for the period, with the lowest value of 97.72% in 2013/14 and the highest value of 104.26% achieved in 2018/19. The study recommends this methodology to be applied to all the tax products and that the overall tax compliance index be computed. This will assist tax authorities all over the world to actively monitor tax compliance levels and institute timeous corrective measures in order to address non-compliance and ultimately maximise PAYE revenue collections. Moreover, this study also serve as a base for many of the future tax compliance indices studies.

Analysing Spatial Time Series of Local Unemployment: A Graphical Approach Using Principal Components Analysis and Seasonal Adjustment Procedures

1987 ◽  
Vol 19 (2) ◽  
pp. 225-246
Author(s):  
R Dunn
Keyword(s):  
Time Series ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Seasonal Adjustment ◽  
Graphical Approach ◽  
Empirical Results ◽  
Adjustment Procedure ◽  
Graphical Displays ◽  
Components Analysis ◽  
Space Economy

In this paper, the potential of principal components analysis to analyse spatial time series of local unemployment is discussed. A seasonal adjustment procedure is also used which allows trend, seasonal, and irregular subcomponents of the unemployment series to be identified and analysed separately. It is argued that such an approach may provide important insights into the functioning of the regional space economy. Empirical results are presented from a study of local unemployment in the Severnside region. Throughout the paper emphasis is placed on graphical displays and summaries.

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