Per Recruit Models for Stock Assessment and Management of Carp Fishes in the Pattipul Stream, Sheetalpur, Saran (Bihar)
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2021.12.1.27Keywords:
Per recruit models, Major carp, Pattipul streamDimensions Badge
Issue
Section
The Per recruit models were applied to assess Major carp stock in the Pattipul of Bihar showed rapid increment in Yield per recruit (Y/R) at low values of fishing mortality (M=0.17/year) and age at first capture (Tc=0.5 years and increasing F (0.50/year) as 1068 g per year. The Y/R above this level was constant or slightly decreased and the recent F value is higher than the biological reference points as F0.1 (0.15 per year), FSB40% (0.13 per year), FSB50% (0.08 per year) and FSB25% (0.24 per year). The Tc increase by one year resulted in slight increase in Y/R, while additional Tc increase led to decrease in Y/R values. The Tc increase in F required to obtaining the maximum Y/R until reaching a optimum state as initial recruitment at constant M, while recent F value gives small increase in recent level of F, increasing the Tc by one year would result in a small increase in biomass per recruit (B/R). The Tc increase caused a gradual increase in B/R, followed by a decline after a certain value of Tc. These results provide evidence of recruitment over-fishing at all optimum fishing levels, and so sustainable management and conservation of Major carps in Pattipul would require a decrease in F to levels less than F0.1 and FSB40%, which can be achieved through a reduction in fishing effort but not through an increase in Tc.Abstract
How to Cite
Downloads
Similar Articles
- Sampa Mondal, Nilanjana Chatterjee, Baibaswata Bhattacharjee, Positive impact of using α-Fe2O3 nanoparticles as dietary supplements on some hematological parameters of an economically important minor carp Labeo bata (Hamilton, 1822) , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- J. Fathima Fouzia, M. Mohamed Surputheen, M. Rajakumar, A Unified Consistency-Calibrated Boundary-Aware Framework for Generalizable Skin Cancer Detection , The Scientific Temper: Vol. 16 No. 12 (2025): The Scientific Temper
- Archana G, Vijayalakshmi V, Improving classification precision for medical decision systems through big data analytics application , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- Pallavi M. Shimpi, Nitin N. Pise, Comparative Analysis of Machine Learning Algorithms for Malware Detection in Android Ecosystems , The Scientific Temper: Vol. 16 No. 11 (2025): The Scientific Temper
- Amit Maru, Dhaval Vyas, Hybrid deep learning approach for pre-flood and post-flood classification of remote sensed data , The Scientific Temper: Vol. 16 No. Spl-1 (2025): The Scientific Temper
- Jayalakshmi K., M. Prabakaran, Feature selection in HR analytics: A hybrid optimization approach with PSO and GSO , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- A. Anand, A. Nisha Jebaseeli, A comparative analysis of virtual machines and containers using queuing models , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Maria D. Roopa, Nimitha John, Bayesian Optimization Phase I Design of Experiment Models , The Scientific Temper: Vol. 15 No. 02 (2024): The Scientific Temper
- Ramendra Kumar Dwivedi, Ved Prakash Tripathi, Nagendra Pratap Singh, P.N. Tripathi, Age and Growth Related Investigations on Major Carps in the Riverine Environment of River Ghaghra at and Around Faizabad , The Scientific Temper: Vol. 7 No. 1&2 (2016): THE SCIENTIFIC TEMPER
- P. J. Robinson, S. W. A. Prakash, Stochastic artificial neural network for magdm problem solving in intuitionistic fuzzy environment , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
<< < 1 2 3 4 5 6 7 8 9 10 > >>
You may also start an advanced similarity search for this article.

