Training on “Ecosystem Modelling: Towards Management of Inland Fisheries” for young researchers
Barrackpore, 27th July, to 2ndAugust 2022
Inland fisheries are a vital component in the livelihoods and food security of people throughout the world, as well as contributing huge economic benefits and recreation. These valuable assets are jeopardised by a lack of research-based understanding of the long-term impacts of fisheries on inland ecosystems, and similarly the impact of human activities associated with inland waters on fisheries and aquatic biodiversity. To achieve this goal, a new research approach is needed that focuses on quantifying economic, social, and nutritional benefits of inland fisheries; improving assessments designed to evaluate fisheries exploitation potential ecosystem productivity and aquatic biodiversity. For sustainable inland Fisheries management an ecosystem-based approach is most important.

Backing this, ICAR-Central Inland Fisheries Research Institute, Barrackpore conducted a 7-day training program on “Ecosystem Modelling: Towards Management of Inland Fisheries” from 27th July to 2nd August 2022 at CIFRI HQ. In the training program, a total of 22 participants were participated including 15 males and 7 females comprising various capacities such as Scientists, Assistant Professors, Research Scholars and Young Professional of different institutes such as College of Fisheries (Raha, Assam; Kishanganj, Bihar and Dholi, Bihar); C. V. Raman University, Kota, Chhattisgarh; Dr. Shyama Prasad Mukherjee University, Ranchi, Jharkhand; ICAR-CIFE, Mumbai and ICAR-CIFRI, Barrackpore.

Dr. B. K. Das, Director ICAR-CIFRI, has inaugurated the training program and enlightened about the necessity of ecosystem modelling in open water resources and emphasized the applicability of these models for the sustainable management of these water resources. The significance of this training program is that the contribution of ecosystem-based models is imperative wherever data has a major role in estimation, interpretation and prediction of fishery resources, and success of a government policy or any other related issue. All the five Divisional In-charges of the institute along with Extension & Training Cell In-charges also attended the inaugural program and expressed their view on the importance of the program. In this training program, trainees were taught about different aspects of ecosystem modelling such as ecosystem-based fisheries management, different food web modelling, ecopath, ecosim and ecospace models, various statistical packages for inland fisheries, and other dynamic modelling in R platforms, etc. Hands-on practical was conducted by various expert resource persons from Indian Statistical Institute, Kolkata; Gushkara Mahavidyalaya, Purba Bardhaman district of West Bengal; Kyung Hee University, Korea; ICAR-CIFRI, Barrackpore, etc. In the valedictory session as a concluding remark the Director, ICAR-CIFRI urged all the participants to work hard in their respective field for quality data collection to come up suitable management measures in the inland open waters. He also assured all the participants that ICAR-CIFRI will always remain supportive for any kind of support required in research in ecosystem-based modelling. Dr. Archan Kanti Das, In-charge training and Extension Cell congratulates all the participants for successful completion of the training program.

In feedback sessions, all the participants expressed their full satisfaction about how the overall training program was being conducted and thanked the organisers for the overall hospitality rendered by the institute. The program ended with a formal vote of thanks by Dr. Dibakar Bhakta, Scientist and expressed his sincere thanks to the Director of ICAR-CIFRI, resource persons, training coordinators, participants, and one and all who were directly and indirectly associated with the program. The training program is coordinated by Dr. M. Feroz Khan, Dr. Preetha Panikkar, Dr. Dibakar Bhakta, Dr. P. K. Parida, and Ms. P. R. Swain.

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2017 Last updated on 03/08/2022