Volume 9, Issue 4 (2-2021)                   2021, 9(4): 1-14 | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Haghi Vayghan A. Distribution Modeling of Bigeye Tuna (Thunnus obesus Lowe, 1839), Using Satellite Derived Environmental Variables in Indian Ocean. Iranian Journal of Applied Ecology 2021; 9 (4) :1-14
URL: http://ijae.iut.ac.ir/article-1-1016-en.html
Urmia University
Abstract:   (2870 Views)
Understanding effects of environment on the distribution of economic fish is a fundamental step in the ecosystem-based management and ultimately a standard approach in management policies. Bigeye tuna (Thunnus obesus) is one of the most important aquatic species harvested in the Indian Ocean. The present study investigated the association of different variables effecting the rate of catch and distribution of bigeye tune, using generalized additive model (GAM) and maximum entropy (MaxEnt) and satellite derived environmental variables in the Indian Ocean. Results highlighted the importance of temporal and spatial variables along with the eddy kinetic energy, sea level height, depth of 20°C isotherm and sea surface temperature on the distribution of the species. The most suitable habitat predicted by MaxEnt model was observed around the latitudes of 0 to 5 degrees of north and south, mainly in the western part of the Indian Ocean and longitude of 45 to 70 degrees east. Using satellite data, the present study determinied the important factors and suitable habitats for the species, which can be useful for Iranian fisheries managers to increase the fishing efficiency and implementing of ecosystem-based fisheries management in the shared exploited stocks of the Indian Ocean.
Full-Text [PDF 857 kb]   (1235 Downloads)    
Type of Study: Research | Subject: General

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | Iranian Journal of Applied Ecology

Designed & Developed by : Yektaweb