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Delineating impact of climatic variable(s) on commercial fish landings in a tropical river through multi-species modelling

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For effective fisheries management and sustainable development of fisheries in the Indian segment of the Brahmaputra River, it is crucial to examine how fish landing patterns have been influenced by climatic factors over recent years. In this context, this study aimed to assess the impact of climatic variables, specifically precipitation, on commercial fisheries in the Brahmaputra River at Uzanbazar (Guwahati) using a multi-species modelling approach. The annual data from 1987 to 2017, encompassing precipitation and multi-species fish landings, including Indian major carps (IMC), catfishes, minor carps, featherbacks, miscellaneous fishes and hilsa was utilised for the study. To analyse this, the Dynamic Factor Analysis (DFA) technique was employed to identify common trends and quantify the effects of precipitation on the different fish groups/species. Based on the model selection criterion, the optimal DFA model revealed three distinct common trends with an unconstrained covariance matrix. Trend-1 primarily represented the landings of minor carps, catfishes, and IMC; Trend-2 wasassociated with miscellaneous fishes and featherbacks and Trend-3 corresponded to hilsa landings. Precipitation was incorporated as an explanatory variable in the optimally selected DFA model to characterise the relationship between fish landings and climatic factors. The results indicated that annual precipitation significantly influenced the landings of catfishes, hilsa, featherbacks and miscellaneous fishes. Specifically, a significant positive regression coefficient was observed for miscellaneous fish landings, whereas significant negative regression coefficients were found for hilsa, catfishes and featherbacks. The comparison between the standardised empirical fish landings and the predicted landings from the DFA model showed a good agreement. This study represents the first application of the DFA approach to explore common trends in commercial fish landings and the influence of precipitation on these landings in the Brahmaputra River. The findings can inform the development of sustainable management strategies for multispecies commercial fisheries in riverine ecosystem. Keywords: Brahmaputra, Dynamic factor analysis, Fish landings, Precipitation, Sustainable fisheries
Title: Delineating impact of climatic variable(s) on commercial fish landings in a tropical river through multi-species modelling
Description:
For effective fisheries management and sustainable development of fisheries in the Indian segment of the Brahmaputra River, it is crucial to examine how fish landing patterns have been influenced by climatic factors over recent years.
In this context, this study aimed to assess the impact of climatic variables, specifically precipitation, on commercial fisheries in the Brahmaputra River at Uzanbazar (Guwahati) using a multi-species modelling approach.
The annual data from 1987 to 2017, encompassing precipitation and multi-species fish landings, including Indian major carps (IMC), catfishes, minor carps, featherbacks, miscellaneous fishes and hilsa was utilised for the study.
To analyse this, the Dynamic Factor Analysis (DFA) technique was employed to identify common trends and quantify the effects of precipitation on the different fish groups/species.
Based on the model selection criterion, the optimal DFA model revealed three distinct common trends with an unconstrained covariance matrix.
Trend-1 primarily represented the landings of minor carps, catfishes, and IMC; Trend-2 wasassociated with miscellaneous fishes and featherbacks and Trend-3 corresponded to hilsa landings.
Precipitation was incorporated as an explanatory variable in the optimally selected DFA model to characterise the relationship between fish landings and climatic factors.
The results indicated that annual precipitation significantly influenced the landings of catfishes, hilsa, featherbacks and miscellaneous fishes.
Specifically, a significant positive regression coefficient was observed for miscellaneous fish landings, whereas significant negative regression coefficients were found for hilsa, catfishes and featherbacks.
The comparison between the standardised empirical fish landings and the predicted landings from the DFA model showed a good agreement.
This study represents the first application of the DFA approach to explore common trends in commercial fish landings and the influence of precipitation on these landings in the Brahmaputra River.
The findings can inform the development of sustainable management strategies for multispecies commercial fisheries in riverine ecosystem.
Keywords: Brahmaputra, Dynamic factor analysis, Fish landings, Precipitation, Sustainable fisheries.

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