1. Assessment of benthic macroinvertebrate response to anthropogenic and natural disturbances in the Kodungallur-Azhikode estuary, southwest coast of India.
- Author
-
Jayachandran PR, Jima M, Philomina J, and Bijoy Nandan S
- Subjects
- Animals, Ecosystem, Environmental Monitoring, India, Estuaries, Invertebrates
- Abstract
Benthic biotic indices are important ecological tools extensively used to understand the ecological quality of coastal wetlands. The present study aimed to assess the ecological status of Kodungallur-Azhikode estuary for the first time by using widely used benthic indices such as species richness (S), Shannon diversity index (H'log
2 ), BENTIX, benthic opportunistic polychaetes amphipods (BOPA), AZTI's Marine Biotic Index (AMBI) and multivariate AMBI (M-AMBI). In the canonical correspondence analysis, salinity, dissolved oxygen, organic matter, sediment Eh, sediment pH and sand were identified as important variance descriptors. A single species of an opportunist, Americorophium triaeonyx, an amphipod belonging to the ecological group (EG) III, significantly contributed to the total macrofaunal density. Other dominant opportunistic species included Obelia bidentata (EGII), Arcuatula senhousia (EGIII), Cirolana fluviatilis (EGII), Prionospio cirrifera (EGIV) and Capitella sp. (EGV). The overall assessment indicated a 'good to moderate' condition in AMBI, 'good to poor' condition in M-AMBI, 'high to moderate' condition in BENTIX, 'high to poor' condition in BOPA and 'moderate to poor' condition in univariate Shannon diversity index. All the multivariate indices tested in the study were correlated with each other except BOPA and M-AMBI. The group of stations dominated with a sandy substrate and a moderate level of organic content indicated high to good conditions while other stations demonstrated moderate to poor conditions. However, no significant variation in indices tested between seasons was observed. The present study recommends long-term monitoring of benthic macroinvertebrate assemblages with proper taxonomic identification and functional trait analysis for better calibration of indices, which is the key factor for getting better results.- Published
- 2020
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