Analysis of Zooplankton Population Fluctuations in the Strait of Georgia, British Columbia

1977 ◽  
Vol 34 (8) ◽  
pp. 1196-1206 ◽  
Author(s):  
Grant A. Gardner
Keyword(s):  
Canonical Correlation ◽  
Temporal Trends ◽  
Biological Significance ◽  
Principal Component ◽  
Biological Data ◽  
Species Selection ◽  
Hydrographic Data ◽  
Strait Of Georgia ◽  
Key Species ◽  
Principal Component Analyses

Canonical correlation, cluster, multiple regression, factor, and principal component analyses were used to examine zooplankton and hydrographic data over the period of unusual fluctuations in the overwintering population sizes of Calanus plumchrus, C. marshallae, and C. pacificus in the Strait of Georgia. Additional hydrographic data were examined for relationships between physical and biological data 3 and 6 mo out of phase. Analysis indicates a recent subtle temperature and salinity shift of uncertain biological significance. Canonical correlation and principal component analyses suggest that 15% of the variance in the zooplankton is related to a temporal trend paralleling that seen in the physical characteristics of the environment.Based on the factor analysis, C. plumchrus, Pseudocalanus minutas, Acartia longiremus, Sagitta elegans, Euphausia pacifica, Limacina spp, and Oithona spinirostris are suggested as "key" species for future zooplankton monitoring programs. Statistically supported species selection can reduce the time and expense of sorting zooplankton samples without an equivalent reduction of information yield. Key words: zooplankton, populations, Calanus, statistical analysis, temporal trends

Correlated morphological and genetic patterns in Embothrium coccineum (Proteaceae) across climate and geography: can Embothrium survive patagonian climate change?

2013 ◽  
Vol 61 (7) ◽  
pp. 516 ◽  
Author(s):  
Cintia P. Souto ◽  
Peter E. Smouse
Keyword(s):  
Climate Change ◽  
Reproductive Isolation ◽  
Adaptive Radiation ◽  
Canonical Correlation ◽  
Large Fraction ◽  
Principal Component ◽  
Propagule Dispersal ◽  
Genetic Patterns ◽  
Principal Component Analyses ◽  
Climatic Regime

Adaptive radiation and reproductive isolation can determine the biogeographic structure of any species. We examine patterns of biotic variation in Embothrium coccineum, a Proteaceae tree that spans 20° of latitude and is both morphologically and genetically highly variable. We aim to (1) explore the correspondence between these biotic patterns and current geographic and climatic gradients, and (2) determine whether and how those patterns are likely to respond to changing climate. We conducted separate principal component analyses on biotic and abiotic sets of variables for 34 populations of Embothrium coccineum, accounting for a large fraction of the total variation in each. We then used canonical correlation analyses to optimise the match of those gradients onto each other. Smaller, rounder leaves and particular alleles typify the colder and drier parts of the range, whereas larger, lanceolate leaves and other alleles typify warmer and moister areas. Finally, we mapped biotic profiles onto a predicted climatic landscape, on the basis of doubling of CO2 projections. The climatic regime is predicted to shift geographically, but this lineage has successfully responded to repeated and dramatic climatic shifts since the Oligocene, and it should also be able to move and adapt quickly enough to meet the present challenge. More generally, our analytic approach can be extended to analysis of biotic and abiotic patterns in other species facing climatic challenges. Where there is enough biogeographic variation to provide adaptively relevant substrate, and where propagule dispersal is sufficiently extensive to keep up with the pace of spatial climatic shift, such taxa should be able to cope with shifting climate.

scholarly journals Fast diffusion kurtosis mapping of human brain at 7 Tesla with hybrid principal component analyses

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Fangrong Zong ◽  
Jiaxin Du ◽  
Xiaofeng Deng ◽  
Xubin Chai ◽  
Yan Zhuo ◽  
...  
Keyword(s):  
Human Brain ◽  
Principal Component ◽  
7 Tesla ◽  
Fast Diffusion ◽  
Principal Component Analyses ◽  
Diffusion Kurtosis

scholarly journals Microphytoplankton structure from the neritic and oceanic regions of Pernambuco State - Brazil

2009 ◽  
Vol 69 (4) ◽  
pp. 1037-1046 ◽  
Author(s):  
ML. Koening ◽  
BE. Wanderley ◽  
SJ. Macedo
Keyword(s):  
Principal Component ◽  
Mesh Size ◽  
Species Number ◽  
Phytoplankton Diversity ◽  
Trichodesmium Erythraeum ◽  
Species Association ◽  
Tropical Water ◽  
Key Species ◽  
Distribution And Ecology ◽  
Planktonic Species

This research was carried out to assess phytoplankton diversity, distribution and ecology on the Pernambuco Continental Shelf and Oceanic region (lat. 7º 33' 00" S to 8º 41' 50" S and long. 34º 04' 47" W to 35º 01' 20" W). Samples were collected during the Joint Oceanographics Projects (JOPS II-Leg 5) by double oblique hauls with a baby bongo net 64 µm mesh size at depth between 14 and 150 m in inshore and offshore waters respectively, in seven transects, totaling 34 stations. The temperature and salinity characterised the tropical water masses. The dissolved oxygen was oversaturated in all stations. The nutrient-low concentrations showed an oligothrophic pattern in the whole area. 173 specific and infraspecific taxa were identified: Dinophyta (103 taxa), Bacillariophyta (61 taxa), Cyanobacteria (7 taxa), Chlorophyta and Chrysophyta (1 taxon). The family Ceratiaceae presented the highest species number (47 taxa). The cyanobacteria Trichodesmium erythraeum Ehrenberg, Oscillatoria spp. and the diatom Leptocylindrus danicus Cleve had higher frequence of occurrence and abundance. Species diversity varied from 0.71 to 3.46 bits.cell-1 and this low index was due to Trichodesmium erythraeum bloom and evenness from 0.14 to 0.65, showing an unstable pattern. The oceanic planktonic species were responsible for the higher richness with 78 taxa, corresponding to 58.39% of the total microphytoplankton. The species association presented two groups. The first one divided in two subgroups: one associated to the neritic/oceanic and oceanic planktonic species and the other to the oligotrophic indicator species. The second group was composed of some key species which were the most abundant and frequent in the area. The first three Principal Component Analyses (PCAs) explained 50.91% of the data variance showing that the area is structured by two groups: one offshore composed by oligotrophic indicators, and another nearshore influenced by continental fluxes.

scholarly journals Dimension reduction of Malaria Box data allows efficient compound prioritization

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 2701
Author(s):  
Gajinder Pal Singh
Keyword(s):  
Specific Activity ◽  
Rank Correlation ◽  
Artemisinin Resistance ◽  
Principal Component ◽  
Principal Component Analyses ◽  
Systematic Strategy ◽  
Positive Correlations ◽  
Further Development ◽  
Malaria Box

Background: New anti-malarial drugs are needed to meet the challenge of artemisinin resistance and to achieve malaria elimination and eradication. The new anti-malarial compounds are expected to have many desirable properties, such as activity against multiple stages of Plasmodium, low host cytotoxicity, and low propensity for resistance development, but whether and how these properties might be linked to each other is not clear. A better understanding of the relationship between activities of compounds against different stages of Plasmodium could help in the development of strategies to prioritize compounds with maximum potential for further development. Methods: We utilized the large amount of data that has recently been generated on 400 anti-malarial Malaria Box compounds and performed statistical analyses, such as rank correlation, hierarchical clustering, and principal-component analyses, to test associations between activities against different stages of Plasmodium, other pathogens, and human cells. Results: We found significant positive correlations between the activities of compounds against different stages of Plasmodium. Our results also show toxicity associated with assays conducted at higher compound concentrations. Principal-component analyses (PCA) of the data allowed differentiation of Plasmodium-specific activity from general toxicity and predicted success in in vitro evolution of resistance. We found that a single principal-component can capture most of the desirable properties of Malaria Box compounds and can be used to rank compounds from most desirable to least desirable activity-profile. Conclusions: Here, we provide a systematic strategy to prioritize Malaria Box compounds for further development. This approach may be applied for prioritization of anti-malarial compounds in general.

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