UNU-FTP fellow Chrisphine Nyamweya to defend PhD at the University of Iceland

UNU-FTP fellow Chrisphine Nyamweya to defend PhD at the University of Iceland Chrisphine Sangara Nyamweya of Kenya first came to Iceland as a fellow of

UNU-FTP fellow Chrisphine Nyamweya to defend PhD at the University of Iceland

Chrisphine Sangara Nyamweya of Kenya first came to Iceland as a fellow of the UNU-FTP in 2012. Through funding provided by the UNU-FTP, he enrolled in a doctoral programme at the School of Engineering and Natural Sciences a the University of Iceland. He will defend his PhD in Ecological Modeling at the Hátíðarsalur in the University of Iceland's Main Building on Monday, January 30th at 10:00.

Doctoral committee includes Prof. Gunnar Stefánsson, advisor University of Iceland, Dr. Erla Sturludóttir, University of Iceland, and Dr. Tumi Tómasson Director of the United Nations University Fisheries Training Programme

Opponents are Dr. Jason Link National Oceanic and Atmospheric Administration (NOAA) Fisheries, USA, Prof. Ian G Cowx, of the University of Hull, UK.


Lake Victoria is of immense ecological and socio-economic significance for the riparian communities. However, the lake is faced with human induced pressures such as overfishing, introduction of alien species, increased eutrophication and climate change impacts. Its large spatial extent and complex ecology have also limited the understanding of the system dynamics, major processes, drivers and responses. To address this challenge, Atlantis, the first end-to-end whole ecosystem model for the lake was developed. First, a Regional Oceanographic Model System (ROMS) for the lake was developed to provide hydrodynamic forcing data for the ecosystem model. The ROMS model was based on real bathymetry, river runoff and atmospheric forcing data. Results from this model revealed diverse spatial and temporal water circulation patterns and temperature trends in Lake Victoria. The ROMS output provided water currents and temperature forcing data for the Atlantis model.

The Lake Victoria Atlantis model is spatially resolved into 12 unique dynamic areas based mainly on their biophysical attributes. A total of 38 functional groups constituted the biological model while fishing was implemented by four fleets with different targeting options. The model was validated by fitting simulated output to available observational data sets. Simulations showed elevated nutrients and primary production in inshore areas and gulfs that can be linked to point sources of pollution and limited flushing. The model also revealed complex inter-specific relationships among the biological groups. For example, the introduced Nile perch (Lates niloticus) exhibited a strong negative correlation with haplochromine cichlids (their prey) as well as most of other fish groups. This brings to fore the significance of predator-prey relationships and the impact of introduced species; information that is critical for effective fisheries and ecosystem management.

The model was then used to simulate the impact of different fishing scenarios on the ecosystem. Scenarios tested included varied fishing pressure for Nile perch (the main predator at the top of the food chain), key prey species (haplochromines) and other species. The effects of these scenarios were tested using six common ecosystem-level indicators. Predictions showed that no particular scenario excels in all the six indicators. However, halting harvesting of haplochromines results in the best overall ecosystem performance. This scenario is projected to result in the highest yield of commercially important species and possibly cause minimal disruption to fishing activities. Findings of this study reinforce the need for an ecosystem approach to fisheries management in Lake Victoria.



Fisheries training programme
Skulagata 4
IS - 121 Reykjavik,Iceland