Assessment of pollution load and identifying bioindicator algal species using multivariate statistical techniques: A case study from Damodar River

Dora, Savana Lata, Chowdhury, Abhiroop, Maiti, Subodh Kumar and Tiwary, Rajani Kanth (2022) Assessment of pollution load and identifying bioindicator algal species using multivariate statistical techniques: A case study from Damodar River. International Journal of Environment and Pollution, 69 (3-4). pp. 151-178. ISSN 0957-4352

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Abstract

The ecological health of Damodar River is assessed and pollution indicator algal species have been identified in this study. The weathered lateritic formations of Chotanagpur resulted in high concentration of Fe (126–820 µg l–1) and Mn (10–114 µg l–1). Contamination indices indicate low to moderate pollution for Mn, Ni, and Cu in the sediment. The dominance of Chlorophyceae (29 species) has been observed. Saprobic index, ranged from oligo to beta-mesosaprobic, which promotes diversity of species with high saprobic value. Canonical Correspondence Analysis (CCA) revealed that nutrients, TDS, HCO3, EC, Fe, Mn, and Zn has been the driving factors for the distribution of phytoplankton. Geminelliaspp has been identified as biosensor for low pollution, Spirogyra, Cladophora, Nitzschia, Cyclotella, Oedogonium bioindicator for Fe, Mn and Zn, Cladophora glomerata, Oscillatoria princeps, Phacus spp., Scenedesmus spp., Synedra spp. – bioindicator of organic pollutants

Item Type: Article
Keywords: Pollution | Damodar River | Trace metals | Bioindicators | Algal biodiversity | Saprobic index | Diversity index | Contamination indices | Canonical correspondence analysis
Subjects: Physical, Life and Health Sciences > Environmental Science, Policy and Law
JGU School/Centre: Jindal School of Environment & Sustainability
Depositing User: Amees Mohammad
Date Deposited: 06 Jun 2022 04:06
Last Modified: 22 Feb 2023 09:00
Official URL: https://doi.org/10.1504/IJEP.2022.10046987
URI: https://pure.jgu.edu.in/id/eprint/3193

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