Use of multivariate analysis to identify phytoplankton bioindicators of stream water quality in the monomodal equatorial agroecological zone of Cameroon

被引:0
|
作者
Patricia Bi Asanga Fai
Daniel Brice Nkontcheu Kenko
Norbert Ngameni Tchamadeu
Mpoame Mbida
Krystof Korejs
Jan Riegert
机构
[1] University of Dschang,Department of Animal Biology, Dschang School of Science and Technology
[2] University of Bamenda,College of Technology
[3] University of Buea,Department of Animal Biology and Conservation, Faculty of Science
[4] University of South Bohemia in České Budějovice,Department of Zoology, Faculty of Science
来源
关键词
Aquatic biomonitoring; Diatoms; Bacillariophyta; Principal component analysis; Redundancy analysis; Biotic indices;
D O I
暂无
中图分类号
学科分类号
摘要
The aquatic ecosystem is compromised by many contaminants that may reduce ecosystem functions and severely affect human health. This study aimed at determining suitable phytoplankton bioindicators of water quality for biomonitoring of freshwater streams in the monomodal agroecological zone of Cameroon. Water physicochemical and hydrological parameters, together with phytoplankton abundance and diversity, were measured from June 2016 to May 2017 along the Benoe Stream. Principal component analysis and redundancy analysis were used to determine phytoplankton spatial and temporal distribution and identify indicator species. The Shannon–Wiener diversity and Pielou’s evenness indices indicated a clean to mildly polluted stream with a diverse phytoplankton community consisting of 84 genera belonging to 51 families that was dominated by the Bacillariophyta (64%), followed by Chlorophyta (13%) and Cyanophyta (10%). The total dissolved solids, electrical conductivity, stream water velocity, and discharge were the most important stream characteristics affecting the abundance of the dominant phytoplankton genera. Seasonal variations in the stream characteristics as well as spatial community distribution along an urban—small-scale farming – large-scale farming gradient were unveiled and their influence on the phytoplankton relative abundances. Increased abundance of Synedra ulna was indicative of low TDS and EC, which was the contrary for Gyrosigma baltium dominance. High Pleurosira laevis abundance was associated with the urban zone while high Diatoma sp. and Oscillatoria sp. abundances were related to the large-scale farming zone of the stream. These phytoplankton species have good potential for use as bioindicators for stream water quality monitoring in the monomodal agroecological zone.
引用
收藏
相关论文
共 31 条
  • [21] MULTIVARIATE-ANALYSIS OF STREAM WATER CHEMICAL-DATA - THE USE OF PRINCIPAL COMPONENTS-ANALYSIS FOR THE END-MEMBER MIXING PROBLEM
    CHRISTOPHERSEN, N
    HOOPER, RP
    WATER RESOURCES RESEARCH, 1992, 28 (01) : 99 - 107
  • [22] Evaluation of water quality near the Malanjhkhand copper mines, India, by use of multivariate analysis and a metal pollution index
    Prasad, Bably
    Soni, Abhay Kumar
    Vishwakarma, Anusha
    Trivedi, Ratnesh
    Singh, Krishna Kant Kumar
    ENVIRONMENTAL EARTH SCIENCES, 2020, 79 (11)
  • [23] GIS, Multivariate Statistics Analysis and Health Risk Assessment of Water Supply Quality for Human Use in Central Mexico
    Hernandez-Mena, Leonel
    Panduro-Rivera, Maria Guadalupe
    Diaz-Torres, Jose de Jesus
    Ojeda-Castillo, Valeria
    Real-Olvera, Jorge del
    Lopez-Cervantes, Malaquias
    Pacheco-Dominguez, Reyna Lizette
    Morton-Bermea, Ofelia
    Santacruz-Benitez, Rogelio
    Vallejo-Rodriguez, Ramiro
    Osuna-Laveaga, Daryl Rafael
    Bandala, Erick R.
    Flores-Payan, Valentin
    WATER, 2021, 13 (16)
  • [24] Evaluation of water quality near the Malanjhkhand copper mines, India, by use of multivariate analysis and a metal pollution index
    Bably Prasad
    Abhay Kumar Soni
    Anusha Vishwakarma
    Ratnesh Trivedi
    Krishna Kant Kumar Singh
    Environmental Earth Sciences, 2020, 79
  • [25] A GIS-supported multivariate statistical analysis of relationships among stream water chemistry, geology and land use in Baden-Wurttemberg, Germany
    Xie, XD
    Norra, S
    Berner, Z
    Stüben, D
    WATER AIR AND SOIL POLLUTION, 2005, 167 (1-4): : 39 - 57
  • [26] A Gis-Supported Multivariate Statistical Analysis of Relationships Among Stream Water Chemistry, Geology and Land Use in Baden-Württemberg, Germany
    Xudong Xie
    Stefan Norra
    Zsolt Berner
    Doris Stüben
    Water, Air, and Soil Pollution, 2005, 167 : 39 - 57
  • [27] Use of Principal Component Analysis for Parameter Selection to Compute Water Quality Index and Assessment of Groundwater Quality Status: A Case Study of Sanganur Stream, Coimbatore City
    Mohammed Siraj Ansari, A.
    Saraswathi, R.
    JOURNAL OF THE GEOLOGICAL SOCIETY OF INDIA, 2022, 98 (03) : 417 - 422
  • [28] Use of Principal Component Analysis for Parameter Selection to Compute Water Quality Index and Assessment of Groundwater Quality Status: A Case Study of Sanganur Stream, Coimbatore City
    A. Mohammed Siraj Ansari
    R. Saraswathi
    Journal of the Geological Society of India, 2022, 98 : 417 - 422
  • [29] Application of multivariate statistical analysis and water quality index in health risk assessment by domestic use of river water. Case study of Tana River in Kenya
    Njuguna, Samwel Maina
    Onyango, Janet Atieno
    Githaiga, Kelvin Babu
    Gituru, Robert Wahiti
    Yan, Xue
    PROCESS SAFETY AND ENVIRONMENTAL PROTECTION, 2020, 133 : 149 - 158
  • [30] Utility of multivariate statistical analysis to identify factors contributing river water quality in two different seasons in cold-arid high-altitude region of Leh-Ladakh, India
    Giri, Arup
    Bharti, Vijay K.
    Kalia, Sahil
    Kumar, Krishna
    Raj, Tilak
    Chaurasia, O. P.
    APPLIED WATER SCIENCE, 2019, 9 (02)