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Citation link: http://nbn-resolving.de/urn:nbn:de:gbv:46-00105485-16
00105485-1.pdf
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Population and Ecosystem-based Fisheries Assessment of the Rift Valley Lake Koka, Ethiopia


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Other Titles: Bevölkerungs- und Ökosystembasierte Fischereibewertung des Rift Valley Lake Koka , Äthiopien
Authors: Tesfaye Chekol, Gashaw  
Supervisor: Wolff, Matthias
1. Expert: Wolff, Matthias
2. Expert: Reuter, Hauke
Abstract: 
The Ethiopian fishery serves as the main source of affordable protein-rich food and essential macro-nutrients, and is the primary source of livelihood for many households, particularly for those who are residing in the vicinity of major water bodies. Despite its importance, the resources are facing multifaceted challenges including high fishing pressure, use of destructive fishing methods, influences arising from land-based activities, and limited scientific information for proper fishery management. Lake Koka, an important lake for the Ethiopian fishery, has been subjected to intensive fishing over the decades, yet little is known about the present state of fishery target resources. Therefore, this study aims to provide baseline information for proper management of the Lake Koka fishery resources that allows sustainability for both the fish stocks and the society. This dissertation is comprised of eight chapters an introductory chapter, six chapters organized in the form of scientific publications that include both populationa and ecosystem-based fisheries assessment and addresses the research questions highlighted in the 1st chapter, and a chapter which gives a synopsis of the major findings and outlooks.
Keywords: African catfish, Beach seine, Biomass dynamic model, Cohort analysis, Common carp, Ecopath, Ecosystem maturity, Ethiopia, Fish biomass, Gear selectivity, Gillnet, Growth, Labeobarbus, Lake Koka, Longline, Mortality, Mixed trophic impact, Niche overlap, Population dynamics, Potential yield, Rift Valley, Size at maturity, Size selectivity, SELECT method, Stock assessment, Thompson and Bell model, Tilapia, Trophic model, Trophic level, Yield per recruit model
Issue Date: 25-Aug-2016
Type: Dissertation
URN: urn:nbn:de:gbv:46-00105485-16
Institution: Universität Bremen 
Faculty: FB2 Biologie/Chemie 
Appears in Collections:Dissertationen

  

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