A fuzzy rule-based model to assess the effects of global warming, pollution and harvesting on the production of Hilsa fishes

Abstract In South Asian countries, Tenualosa ilisha, well known as Hilsa, is considered as one of the most economically important fish species. Production of Hilsa fishes depends on many factors including global warming, water pollution and harvesting. This article proposes a new mathematical model using fuzzy inferences to investigate the impacts of global warming, water pollution and harvesting of juvenile fishes on the production of mature Hilsa fishes. Mamdani inference method has been applied for the fuzzy rule-based model. The model is executed by using the Fuzzy Logic Toolbox of MATLAB.

[1]  Anisur Rahman,et al.  Impact Assessment of Twenty-Two Days Fishing Ban in the Major Spawning Grounds of Tenualosa ilisha (Hamilton, 1822) on its Spawning Success in Bangladesh , 2017 .

[2]  P. K. Katiha,et al.  The environment and fishery status of the River Ganges , 2010 .

[3]  Wayne Woldt,et al.  Evaluating Modelling Techniques for Cattle Heat Stress Prediction , 2005 .

[4]  Monirul Islam,et al.  Economic incentives for sustainable hilsa fishing in Bangladesh: An analysis of the legal and institutional framework , 2016 .

[5]  A. Salski,et al.  Fuzzy knowledge- and data-based models of damage to reeds by grazing of Greylag Geese , 2009, Ecol. Informatics.

[6]  Luis Pastor Sánchez Fernández,et al.  Air quality assessment using a weighted Fuzzy Inference System , 2016, Ecol. Informatics.

[7]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[8]  Laécio C. Barros,et al.  A First Course in Fuzzy Logic, Fuzzy Dynamical Systems, and Biomathematics - Theory and Applications , 2016, Studies in Fuzziness and Soft Computing.

[9]  F. F. Putti,et al.  A Fuzzy mathematical model to estimate the effects of global warming on the vitality of Laelia purpurata orchids. , 2017, Mathematical biosciences.

[10]  Tony Prato,et al.  Increasing resilience of natural protected areas to future climate change: A fuzzy adaptive management approach , 2012 .

[11]  Md. Nazmul Hassan,et al.  Present status of hilsa shad (Tenualosa ilisha) in Bangladesh: A review , 2017, Journal of Entomology and Zoology Studies.

[12]  Stefan Kohek,et al.  Fuzzy modelling of growth potential in forest development simulation , 2018, Ecol. Informatics.

[13]  F. F. Putti,et al.  FUZZY LOGIC TO EVALUATE VITALITY OF CATASETUM FIMBIRATUM SPECIES (Orchidacea) , 2014 .

[14]  Fisheries of Indian Shad (Tenualosa ilisha) in the Hooghly–Bhagirathi stretch of the Ganga River system , 2017 .

[15]  Mohammad Fazle Azeem,et al.  Fuzzy Inference System - Theory and Applications , 2012 .

[16]  Lily G C Genevier,et al.  Biology and fisheries of Hilsa shad in Bay of Bengal. , 2019, The Science of the total environment.

[17]  Chung-Chiang Chen,et al.  Fishery policy when considering the future opportunity of harvesting. , 2007, Mathematical biosciences.

[18]  M. Miah.  Climatic and anthropogenic factors changing spawning pattern and production zone of Hilsa fishery in the Bay of Bengal , 2015 .

[19]  C. Clark.  Mathematical Bioeconomics: The Mathematics of Conservation , 2010 .

[20]  T. K. Kar,et al.  Effect of harvesting and infection on predator in a prey–predator system , 2015 .

[21]  M. S. Sultana,et al.  Seasonal Variations in Water Quality of the Ganges and Brahmaputra River, Bangladesh , 2013 .

[22]  Camila Pires Cremasco,et al.  Application of fuzzy logic for the evaluation of livestock slaughtering , 2011 .