scholarly journals Prediction of Holocene Mercury Accumulation Trends by Combining Palynological and Geochemical Records of Lake Sediments (Black Forest, Germany)

2018 ◽  
Author(s):  
Martin Schütze ◽  
Gegeensuvd Tserendorj ◽  
Marta Pérez-Rodríguez ◽  
Manfred Rösch ◽  
Harald Biester
Keyword(s):  
Principal Component Regression ◽  
Principal Component ◽  
Terrestrial Ecosystems ◽  
Forest Vegetation ◽  
Warm Climate ◽  
Black Forest ◽  
Components Analysis ◽  
Lake Systems ◽  
Hg Accumulation

Forest vegetation plays a key role in the cycling of mercury (Hg) and organic matter (OM) in terrestrial ecosystems. Litterfall has been indicated as the major transport vector of atmospheric Hg to forest soils, which is eventually transported and stored in the sediments of forest lakes. Hence, it is important to understand how changes in forest vegetation affect Hg in soil and its biogeochemical cycling in lake systems. We investigated the pollen records and the geochemical compositions of sediments from two lakes (Schurmsee and Glaswaldsee) in the Black Forest (Germany) to evaluate whether long-term shifts in forest vegetation induced by climate or land use influenced Hg accumulation in the lakes. We were particularly interested to determine whether coniferous forests were associated with a larger export of Hg to aquatic systems than deciduous forests. Principal components analysis followed by principal component regression enabled us to describe the evolution of the weight of the latent processes determining the accumulation of Hg over time. Our results emphasize that the in-lake uptake of Hg during warm climate periods, soil erosion after deforestation and emissions from mining and other human activities triggered changes in Hg accumulation during the Holocene stronger than the changes caused by forest vegetation alone.

scholarly journals Prediction of Holocene Mercury Accumulation Trends by Combining Palynological and Geochemical Records of Lake Sediments (Black Forest, Germany)

Geosciences ◽  
2018 ◽  
Vol 8 (10) ◽  
pp. 358 ◽  
Author(s):  
Martin Schütze ◽  
Gegeensuvd Tserendorj ◽  
Marta Pérez-Rodríguez ◽  
Manfred Rösch ◽  
Harald Biester
Keyword(s):  
Principal Component Regression ◽  
Principal Component ◽  
Terrestrial Ecosystems ◽  
Forest Vegetation ◽  
Warm Climate ◽  
Black Forest ◽  
Components Analysis ◽  
Lake Systems ◽  
Hg Accumulation

Forest vegetation plays a key role in the cycling of mercury (Hg) and organic matter (OM) in terrestrial ecosystems. Litterfall has been indicated as the major transport vector of atmospheric Hg to forest soils, which is eventually transported and stored in the sediments of forest lakes. Hence, it is important to understand how changes in forest vegetation affect Hg in soil and its biogeochemical cycling in lake systems. We investigated the pollen records and the geochemical compositions of sediments from two lakes (Schurmsee and Glaswaldsee) in the Black Forest (Germany) to evaluate whether long-term shifts in forest vegetation induced by climate or land use influenced Hg accumulation in the lakes. We were particularly interested to determine whether coniferous forests were associated with a larger export of Hg to aquatic systems than deciduous forests. Principal components analysis followed by principal component regression enabled us to describe the evolution of the weight of the latent processes determining the accumulation of Hg over time. Our results emphasize that the in-lake uptake of Hg during warm climate periods, soil erosion after deforestation and emissions from mining and other human activities triggered changes in Hg accumulation during the Holocene stronger than the changes caused by forest vegetation alone.

Reliability Parameters Forecasting for Transmission Lines Based on Principal Component Regression

2013 ◽  
Vol 291-294 ◽  
pp. 2381-2386 ◽  
Author(s):  
Wen Xia Liu ◽  
Ji Kai Xu ◽  
Hong Yuan Jiang ◽  
Yong Tao Shen
Keyword(s):  
Principal Component Analysis ◽  
Transmission Lines ◽  
Principal Component Regression ◽  
Principal Component ◽  
Forecasting Accuracy ◽  
Factors Affecting ◽  
Reliability Parameters ◽  
Impacting Factors ◽  
Simulation Results

It is the foundation for evaluating the reliability of transmission lines to obtain and analyze the original reliability parameters. However, these parameters depend on long- term statistic and calculation. In the case of lacking such parameters in a new project , this paper proposes a method of Principal Component Analysis to obtain the principal component of the impacting factors ,in which various factors affecting reliability parameters are taken into account. Through this method, we can use PCR to obtain the failure rate of the unknown transmission lines on the base of the known credible lines’ rates. The simulation results show that the proposed approach possesses higher forecasting accuracy and provides references for the power system dispatching departments and transmission lines maintenance departments.

scholarly journals Ranking Cultivated Blueberry for Mummy Berry Blight and Fruit Infection Incidence Using Resampling and Principal Components Analysis

HortScience ◽  
2010 ◽  
Vol 45 (8) ◽  
pp. 1205-1210 ◽  
Author(s):  
Mark K. Ehlenfeldt ◽  
James J. Polashock ◽  
Allan W. Stretch ◽  
Matthew Kramer
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
The Other ◽  
Breeding Strategies ◽  
Relative Resistance ◽  
Term Variation ◽  
Components Analysis ◽  
Infection Stage ◽  
Selection Of

Mummy berry disease of blueberry has two distinct phases: a blighting phase that infects emerging shoots and leaves early in the spring and a flower infection phase that ultimately leads to infected (mummified) fruit. Cultivated blueberry (Vaccinium spp.) genotypes that are resistant to one phase are not necessarily resistant to the other phase. The resistance of cultivated blueberry (Vaccinium spp.) genotypes to each phase of the disease is different. A large number of cultivars were screened for resistance to each phase. Cultivar standards (cultivars with well-documented responses to the disease) were used in the screening to evaluate long-term variation and aid comparisons across years. Using nine standards for the blight phase, 125 cultivars were tested and ranked for relative resistance using a ranking system based on resampling and principal component analysis. Similarly, using six standards for the flower/fruit infection stage, 110 blueberry cultivars were tested and ranked for relative resistance. Cultivar rankings show that lowbush cultivars and other types possessing high percentages of lowbush germplasm are generally more resistant to both phases of the disease. Among highbush cultivars, Bluejay is reliably resistant to both phases. Documentation of resistance to each phase will allow selection of cultivars for planting in affected areas and will facilitate the development of breeding strategies to produce cultivars with superior resistance.

scholarly journals Multi-century tree-ring based reconstruction of the Neuquén River streamflow, northern Patagonia, Argentina

2012 ◽  
Vol 8 (2) ◽  
pp. 815-829 ◽  
Author(s):  
I. A. Mundo ◽  
M. H. Masiokas ◽  
R. Villalba ◽  
M. S. Morales ◽  
R. Neukom ◽  
...  
Keyword(s):  
Tree Ring ◽  
River Flow ◽  
Principal Component Regression ◽  
Principal Component ◽  
Southern Annular Mode ◽  
Hydroelectric Power ◽  
Economic Activities ◽  
Northern Patagonia ◽  
Decadal Scale

Abstract. In most cases, gauged river flow records in southern South America extend for only a few decades, hampering the detection of long-term, decadal to centennial-scale cycles and trends. Long streamflow series can be reconstructed from tree-ring records, offering the opportunity of extending the limited hydrological instrumental data to several centuries. In northern Patagonia, Argentina, the Neuquén River has great importance for local and national socio-economic activities such as hydroelectric power generation, agriculture and tourism. In this study, new and updated tree-ring chronologies from Araucaria araucana and Austrocedrus chilensis are used to reconstruct the October–June mean streamflow for the Neuquén River and place the period of gauged flows (1903–2009), in a long-term, multi-century context. The reconstruction covers the period 1346–2000 AD and was developed from a network of 43 tree-ring chronologies, grouped in composite series, using a nested principal component regression approach. Analyses of the frequency, intensity, and duration of droughts and pluvial events indicate that the 20th century contains some of the driest and wettest annual to decadal-scale events in the last 654 yr, but longer and more severe events were recorded in previous centuries. Blackman-Tukey and singular spectral analyses identified quasiperiodic oscillations from 3.5 to 17.5 yr. A dominant 6.8-yr cycle explains ca. 23.6% of the total variance in the Neuquén River streamflow reconstruction. Correlation analyses showed that discharges of the Neuquén River are related to variations in the Southern Annular Mode (SAM), a measure of air mass exchanges between middle and high latitudes in the Southern Hemisphere. This association is consistent with previous studies that indicate a strong correlation between rainfall in northern Patagonia and SAM variations.

scholarly journals Validation of the Psychological Insight Scale: A new scale to assess psychological insight following a psychedelic experience

2022 ◽  
pp. 026988112110667
Author(s):  
Joseph M Peill ◽  
Katie E Trinci ◽  
Hannes Kettner ◽  
Lea J Mertens ◽  
Leor Roseman ◽  
...  
Keyword(s):  
Convergent Validity ◽  
Principal Component ◽  
Well Being ◽  
Survey Study ◽  
Future Research ◽  
Item Questionnaire ◽  
High Internal Consistency ◽  
Components Analysis ◽  
The Relationship

Introduction: As their name suggests, ‘psychedelic’ (mind-revealing) compounds are thought to catalyse processes of psychological insight; however, few satisfactory scales exist to sample this. This study sought to develop a new scale to measure psychological insight after a psychedelic experience: the Psychological Insight Scale (PIS). Methods: The PIS is a six- to seven-item questionnaire that enquires about psychological insight after a psychedelic experience (PIS-6) and accompanied behavioural changes (PIS item 7). In total, 886 participants took part in a study in which the PIS and other questionnaires were completed in a prospective fashion in relation to a planned psychedelic experience. For validation purposes, data from 279 participants were analysed from a non-specific ‘global psychedelic survey’ study. Results: Principal components analysis of PIS scores revealed a principal component explaining 73.57% of the variance, which displayed high internal consistency at multiple timepoints throughout the study (average Cronbach’s α = 0.94). Criterion validity was confirmed using the global psychedelic survey study, and convergent validity was confirmed via the Therapeutic-Realizations Scale. Furthermore, PIS scores significantly mediated the relationship between emotional breakthrough and long-term well-being. Conclusion: The PIS is complementary to current subjective measures used in psychedelic studies, most of which are completed in relation to the acute experience. Insight – as measured by the PIS – was found to be a key mediator of long-term psychological outcomes following a psychedelic experience. Future research may investigate how insight varies throughout a psychedelic process, its underlying neurobiology and how it impacts behaviour and mental health.

Pemanfaatan CFSRv2 untuk Statistical Downscaling menggunakan Principal Component Regression dan Partial Least Square

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Khairunnisa Khairunnisa ◽  
Rizka Pitri ◽  
Victor P Butar-Butar ◽  
Agus M Soleh
Keyword(s):  
Statistical Downscaling ◽  
General Circulation ◽  
Principal Component Regression ◽  
Circulation Model ◽  
Principal Component ◽  
Meteorological Station ◽  
Grid Size ◽  
Partial Least Square ◽  
Least Square ◽  
Output Data

This research used CFSRv2 data as output data general circulation model. CFSRv2 involves some variables data with high correlation, so in this research is using principal component regression (PCR) and partial least square (PLS) to solve the multicollinearity occurring in CFSRv2 data. This research aims to determine the best model between PCR and PLS to estimate rainfall at Bandung geophysical station, Bogor climatology station, Citeko meteorological station, and Jatiwangi meteorological station by comparing RMSEP value and correlation value. Size used was 3×3, 4×4, 5×5, 6×6, 7×7, 8×8, 9×9, and 11×11 that was located between (-40) N - (-90) S and 1050 E -1100 E with a grid size of 0.5×0.5 The PLS model was the best model used in stastistical downscaling in this research than PCR model because of the PLS model obtained the lower RMSEP value and the higher correlation value. The best domain and RMSEP value for Bandung geophysical station, Bogor climatology station, Citeko meteorological station, and Jatiwangi meteorological station is 9 × 9 with 100.06, 6 × 6 with 194.3, 8 × 8 with 117.6, and 6 × 6 with 108.2, respectively.

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