Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/54731
Title: Trophic network and food web characteristics in a tropical monsoonal estuary: A comparison with other estuarine systems
Authors: Sreekanth, G B
Chakraborty, S K
Jaiswar, A K
Zacharia, P U
Mohamed, K S
Francour, P
Keywords: Ecosystem maturity;Ecosystem model;Keystone species;Monsoonal estuary;Trophic organization;Zuari
Issue Date: May-2020
Publisher: NISCAIR-CSIR, India
Abstract: A mass-balance trophic model for Zuari, a monsoon-influenced tropical Indian estuary, was constructed to understand trophic organization, to measure the ecosystem indicators and to assess the state of the ecosystem maturity and stability. Twenty-two functional groups were identified in the model starting from primary producers (trophic level = 1) to top predators (trophic level = 4.7). The estuarine food web is controlled by bottom-up control based on primary producers and detritus. Phytoplankton, zooplankton, clupeids & anchovies and heterotrophic benthos were observed as keystone species in the food web. A higher total system throughput (23333.9 t km-2 year-1), and lower dimensions for recycling capacity (Finn’s cycling index: 2.78 %), system omnivory index (0.25), and relative ascendency (39.9 %) were observed. Based on the ecosystem indices, Zuari estuary is relatively small, and developing ecosystem, which is resilient to the external disturbances on the system. This trophic model is the first Ecopath model for tropical monsoonal estuaries and fourth model for the estuaries along the Indian coast. The Zuari estuary model showed resemblance to the sub-tropical and tropical estuarine Ecopath models and differed from estuaries of India and temperate estuaries. This Ecopath model would be also useful for simulating the variations in trophic flows and biomass for functional groups under the impact of fishing and anthropogenic activities on the ecosystem.
Page(s): 774-789
URI: http://nopr.niscair.res.in/handle/123456789/54731
ISSN: 0975-1033 (Online); 0379-5136 (Print)
Appears in Collections:IJMS Vol.49(05) [May 2020]

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