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Wyszukujesz frazę "multivariate analysis" wg kryterium: Temat


Wyświetlanie 1-6 z 6
Tytuł:
Inhomogeneity detection in phytoplankton time series using multivariate analyses
Autorzy:
Muniz, O.
Rodriguez, J.G.
Revilla, M.
Laza-Martinez, A.
Seoane, S.
Franco, J.
Powiązania:
https://bibliotekanauki.pl/articles/2079181.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Instytut Oceanologii PAN
Tematy:
phytoplankton community
monitoring programme
uncertainty
multivariate analysis
inhomogeneity
Opis:
Phytoplankton communities have long been used as water quality indicators within environmental policies. This has fostered the development of national and international phytoplankton monitoring programs, but these networks are subject to sources of uncertainty due to laboratory issues. Nevertheless, studies regarding the interference associated with these aspects are not well-documented. Hence, a long time series (2003–2015) from the Basque continental shelf (southeastern Bay of Biscay) was analyzed to evaluate the uncertainty given by laboratory strategies when studying phytoplankton variability. Variability in phytoplankton communities was explained not only by environmental conditions but also by changes in fixatives (glutaraldehyde and acidic Lugol's solution) and laboratory staff. Based on Bray-Curtis distances, phytoplankton assemblages were found to be significantly dissimilar according to the effect of changes in the specialist handling the sample and the employed fixative. The pair-wise permutational multivariate analysis of variance (PERMANOVA) showed significant differences between the two fixatives utilized and also between the three taxonomists involved. Thus, laboratory-related effects should be considered in the study of phytoplankton time series.
Źródło:
Oceanologia; 2020, 62, 3; 243-254
0078-3234
Pojawia się w:
Oceanologia
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Scale-dependent environmental control of mesozooplankton community structure in three aquaculture subtropical bays of China
Autorzy:
Sun, D.
Liu, Z.
Wang, C.
Powiązania:
https://bibliotekanauki.pl/articles/48224.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Instytut Oceanologii PAN
Tematy:
zooplankton
aquaculture
pollution effect
multivariate analysis
subtropical bay
China
Źródło:
Oceanologia; 2016, 58, 2
0078-3234
Pojawia się w:
Oceanologia
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Impact of human-altered hydrographical setting on the copepod community structure in an extensive tropical estuary along the Southwest Coast of India
Autorzy:
Nagarathinam, A.
Retnamma, J.
Loganathan, J.
Singaram, P.
Arayillath, A.
Jose, A.K.
Powiązania:
https://bibliotekanauki.pl/articles/2079004.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Instytut Oceanologii PAN
Tematy:
mesozooplankton
copepod
multivariate analysis
saline water
sea water intrusion
aquatic environment
tropical estuary
India coast
Opis:
This study presents how human-altered hydrographical settings (flow restrictions) impacts the natural distribution and community structure of copepods in the Kochi Backwaters (KBW), the largest monsoonal estuary along the southwest coast of India. This study is primarily based on an extensive seasonal sampling in the KBW and their comparison with a historical data set. Thannermukkom Barrage (TB) was built in the southern section of the KBW in the 1970s to prevent saline water intrusion to the upstream during the non-monsoon periods. Thirteen locations (1—4 in the downstream, 5—9 in the midstream, and 10—13 in the upstream) were sampled in this study over the entire stretch of the KBW during the Pre-Southwest Monsoon (PRM), Southwest Monsoon (SWM), and Post-Southwest Monsoon (PSWM). The overall effect of TB in the KBW is a seaward push of mesohaline conditions during all seasons with varying intensities. In response to the seaward push of mesohaline conditions, copepods Acartiella keralensis, Acartia plumosa, Acartia sp., Pseudodiaptomus annandalei, Pseudodiaptomus serricaudatus, Euterpina acutifrons and Oithona brevicornis showed a corresponding spatial shift for their highest abundance and diversity from midstream during PRM to the downstream during the SWM/PSWM. Multivariate and IndVal analysis demarcated many indicator species of copepods of different hydrographical settings in the KBW. A comparison with the historical data set showed that there is an apparent long-term change in hydrography, copepod composition and community structure in the upstream of the KBW due to TB.
Źródło:
Oceanologia; 2021, 63, 1; 115-132
0078-3234
Pojawia się w:
Oceanologia
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multivariate statistical analysis of water quality and phytoplankton characteristics in Daya Bay, China, from 1999 to 2002
Autorzy:
Wang, Y.S.
Lou, Z.P.
Sun, C.C.
Wu, M.L.
Han, S.H.
Powiązania:
https://bibliotekanauki.pl/articles/48049.pdf
Data publikacji:
2006
Wydawca:
Polska Akademia Nauk. Instytut Oceanologii PAN
Tematy:
South China Sea
water quality
China
phytoplankton
Daya Bay
multivariate statistical analysis
Opis:
This study analyzed seasonal physicochemical and phytoplankton data collected at 12 marine monitoring stations in Daya Bay from 1999 to 2002. Cluster analysis based on water quality and phytoplankton parameters measured at the 12 stations could be grouped into three clusters: cluster I – stations S1,S2 , S7 and S11 in the southern part and the north-eastern part of Daya Bay; cluster II – stations S5, S6,S9 ,S1 0 and S12 in the central and north-eastern parts of Daya Bay; cluster III – stations S3,S 4 and S8 in the cage culture areas in the south-western part of Daya Bay and in the north-western part of the Bay near Aotou harbor. Bivariate correlations between phytoplankton density and the major physical and nutrient factors were calculated for all stations. Factor analysis shows that there were high positive loadings of pH,T IN and the ratio of TIN to PO4-P in the three clusters, which indicates that all the stations in the three clusters were primarily grouped according to their respective nutrient conditions.
Źródło:
Oceanologia; 2006, 48, 2
0078-3234
Pojawia się w:
Oceanologia
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Demonstration of a new indicator for studying upwelling in the Northern South China Sea
Autorzy:
Lin, L.
Wang, Y.-S.
Sun, C.-C.
Li, N.
Wang, H.
Mitchell, B.G.
Wu, M.-L.
Song, H.
Wu, J.-F.
Powiązania:
https://bibliotekanauki.pl/articles/48889.pdf
Data publikacji:
2011
Wydawca:
Polska Akademia Nauk. Instytut Oceanologii PAN
Tematy:
China Sea
cluster analysis
multivariate statistical analysis
principal component analysis
remote sensing
satellite monitoring
sea surface temperature
silicate
spatial distribution
upwelling
Opis:
In order to demonstrate that silicate (SiO3-Si) can be used as an indicator to study upwelling in the northern South China Sea, hierarchical cluster analysis (CA) and principle component analysis (PCA) were applied to analyse the metrics of the data consisting of 14 physical-chemical-biological parameters at 32 stations. CA categorized the 32 stations into two groups (low and high nutrient groups). PCA was applied to identify five Principal Components (PCs) explaining 78.65% of the total variance of the original data. PCA found important factors that can describe nutrient sources in estuarine, upwelling, and non-upwelling areas. PC4, representing the upwelling source, is strongly correlated to SiO3-Si. The spatial distribution of silicate from the surface to 200 m depth clearly showed the upwelling regions, which is also supported by satellite observations of sea surface temperature.
Źródło:
Oceanologia; 2011, 53, 2
0078-3234
Pojawia się w:
Oceanologia
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
DOC and POC in the Southern Baltic Sea. Part II — Evaluation of factors affecting organic matter concentrations using multivariate statistical methods
Autorzy:
Maciejewska, A.
Pempkowiak, J.
Powiązania:
https://bibliotekanauki.pl/articles/48064.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Instytut Oceanologii PAN
Tematy:
Southern Baltic Sea
dissolved organic carbon
particulate organic carbon
organic carbon source
biological activity
abiotic factor
cluster analysis
principal component analysis
multivariate statistical method
Źródło:
Oceanologia; 2015, 57, 2
0078-3234
Pojawia się w:
Oceanologia
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-6 z 6

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