Premium
Comparison of different predictive models for estimating fish yields in Shahpur Dam, Pakistan
Author(s) -
Janjua Muhammad Yamin,
Ahmad Tahira,
Gerdeaux Daniel
Publication year - 2008
Publication title -
lakes and reservoirs: research and management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.296
H-Index - 39
eISSN - 1440-1770
pISSN - 1320-5331
DOI - 10.1111/j.1440-1770.2008.00377.x
Subject(s) - productivity , environmental science , fish <actinopterygii> , yield (engineering) , fishery , water resources , statistics , hydrology (agriculture) , ecology , mathematics , biology , engineering , geotechnical engineering , materials science , macroeconomics , metallurgy , economics
Water reservoirs and dams are major water resources, being diverse in terms of both size and fisheries potential. Reservoir productivity is variable, with significant variations being observed for reservoirs of comparable size and geology, even within the same geographical area. The ability to estimate fish yields through the application of predictive models is an important step for the effective management of fisheries resources in freshwater basins and flowing waters. Various physical, chemical and biological processes establish limits on the yield of commercial fish species. Various physicochemical parameters were measured in this present study during 2001–2002 on a monthly basis for Shahpur Dam in Pakistan. Morphoedaphic indices were derived as MEIt, MEIc and MEIa. A number of different predictive models proposed for different regions are used to predict fish production in Shahpur Dam, for comparison with the actual fish production. From a management perspective, fish yield predictive models based on MEI appeared to be most useful as fish yield predictors.