|
OceanDocs >
Africa >
African Marine Science - Oceanography - Fishery >
Miscellaneous >
Please use this identifier to cite or link to this item:
http://hdl.handle.net/1834/670
|
| Title: | Environmental influence on marine pelagic fish: Evidence from bioeconomic modelling |
| Authors: | Agbesi, E.N. |
| ASFA Terms: | Pelagic fish Fishery economics Environmental impact |
| Issue Date: | 2000 |
| Citation: | Presented at the University of Rhode Island (USA) February 2002 |
| Abstract: | Environmental factors other than fishing effort, contribute to influencing marine pelagic fish population
dynamics and abundance. There is evidence from environmental modelling and bioeconomic analysis of the
Ghanaian marine inshore pelagic fisheries. Ghana is a West African country and lies on the Greenwich Meridian.
It is bordered at the South by the Gulf of Guinea. The official language of Ghana is English, but is surrounded by
French speaking countries. The inshore fishery is a multi-specie, multi-fleet fishery, consisting of artisanal and
inshore purse seine fleets. The coastal inhabitants depend mainly on the marine fisheries as source of
employment and livelihood. Fisheries constitute 5% of Agriculture GDP. The two fisheries types in the inshore
sector comprise the artisanal and inshore commercial fleet. The artisanal fleet are highly labour intensive and use
dugout canoes with average engine power of 40HP. The purse seine fleet are relatively capital intensive and
more commercial. The boats have wooden hull and have average horsepower of 230 HP. The average vessel
capacity unit of a boat is estimated to be 136.8. Both canoes and the commercial purse seine fleet compete to
exploit the same inshore pelagic fish resources within the Ghanaian EEZ. The problem is that the current stock
level has dwindled and this is attributed to overexploitation and influences of the environment. Bioeconomic
models using aggregated landings and effort data help to capture changes in multi-species fisheries (Hilborn and
Walters, 1992). Environmental factors such as temperature and salinity are feasible when jointly incorporated in
bioeconomic models. The mean monthly and annual variables and deviations from the mean are attached
(Appendix A1 and A2) for comparison. |
| URI: | http://hdl.handle.net/1834/670 |
| Appears in Collections: | Miscellaneous
|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
|