Changes in Micro-Phytoplankton Community Structure Due to Seasonal and Inter-Annual Variation in Environmental Parameters at Parangipettai Coastal Water, Bay of Bengal

Manigandan Vajravelu; Yosuva Mariasingarayan; Manivannan Natarajan; Saravanakumar Ayyappan

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Changes in Micro-Phytoplankton Community Structure Due to Seasonal and Inter-Annual Variation in Environmental Parameters at Parangipettai Coastal Water, Bay of Bengal

Manigandan Vajravelu ^[3] ; Yosuva Mariasingarayan ^[1] ; Manivannan Natarajan ^[2] ; Saravanakumar Ayyappan ^[2]
1. [1] Chulalongkorn University
  
  Chulalongkorn University
  
  Tailandia
2. [2] Annamalai University
  
  Annamalai University
  
  India
3. [3] CSIR‑ Research Associateship, Centre for Climate Change Studies, Sathyabama Institute of Science and Technology, Chennai, India
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Localización: Thalassas: An international journal of marine sciences, ISSN 0212-5919, Vol. 38, Nº. 2 (October 2022), 2022, págs. 957-976
Idioma: inglés
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Resumen
- Monthly samples were collected from 2014 to 2016 to elucidate seasonal and interannual dynamics of phytoplankton community structure, diversity, species composition and abundance in relation to physicochemical parameters. Totally, 141 phytoplankton species were identified mostly from diatoms belonging to 106 genera, dinoflagellates and blue green algae representing 29 and 6 genera, respectively. The most persistent and predominant diatoms and dinoflagellates were Asterionellopsis spp. Chaetoceros spp. Coscinodiscus spp. Nitzschia spp. Thalassionema nitzschioides, Guinardia spp. Skeletonema costatum, Ditylum brightwelli, Ceratium spp.and Dinophysis caudata.Gradual increase in phytoplankton abundance was noted in relation to nutrient enhancement from 2014 to 2016. Species diversity and composition in 2014 and 2015 found to be higher than 2016, however, the population density started elevating from 2015 to 2016 with shift in species composition. Variation in physicochemical parameters were confirmed in Principal component analysis (PCA) with distinct distribution pattern among years. Cluster and Non-metric multidimensional scaling ordination (NMDS) analyses identified four groups based on phytoplankton abundance. Diatoms and dinoflagellates that grew abundantly during 2016 formed two distinct groups in NMDS (group 1 &2) whereas; diatoms that distributed in 2014 and 2015 showed 2 separate groups (Group3&4). Canonical correspondence analysis (CCA) revealed the most influencing parameters as temperature, nitrite, silicate, and inorganic phosphate (IP) which was responsible for phytoplankton community structure changes among years especially in 2015 and 2016. The present study demonstrated that annual changes in nutrient and physical parameters can significantly alter dominations and community structure pattern of phytoplankton.