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Vianny Natugonza - PhD defence

16 June 2020
Vianny Natugonza - PhD defence

Vianny Natugonza will defend his PhD dissertation on the 18th of June 2020, at 13.00 GMT.

A comparative analysis of ecosystem models of Lake Victoria (East Africa).

A unique opportunity for those not in Iceland to observe a doctoral defence of one of our scholars. In the new COVID-19 circumstances the defence will take place online, with participation from around the globe, in Uganda, the UK, Belgium and in Iceland. To join in support, or if you are interested to hear about implementation of ecosystem-based fisheries management (EBFM) for Lake Victoria, follow this link

Vianny joined the Fisheries Training Programme as a fellow in 2015 and completed the Stock Assessment line of specialisation. He worked at the University of Akureyri under the supervision of Hreidar Thor Valtysson and Steingrimur Jonsson, and completed a project titled “Improving fisheries management strategies for Lake Victoria by means of ecological modelling optimization” ( Vianny was awarded a postgraduate scholarship and begun his doctoral studies in 2017 at the University of Iceland, School of Engineering and Natural Sciences. Under the supervision and advice of Gunnar Stefansson, Erla Sturludottir, Chrispine Nyamweya, and Tumi Tomasson, and with the support of the National Fisheries Resources Research Institute (NaFIRRI) in Uganda.

Vianny is the fourteenth fellow to complete his Ph.D. under FTP scholarship. We all congratulate him on this major milestone in his professional life. His thesis will be made available online after the defence. The abstract is below.



The advent of ecosystem-based fisheries management (EBFM) in recent years has expanded the scope of fisheries management, where policies are aimed not only at maximizing production (or biological yield) but also maintaining an optimal balance between socio-economic and conservation objectives when utilizing aquatic living resources. Ecosystem models help to assimilate diverse information on the drivers of ecosystem change, thereby providing integrated assessment and advice that is needed for EBFM. Different ecosystem models, however, often provide different predictions. This uncertainty is one of the major challenges impeding their use in EBFM. This study aims to explore the effect of model complexity and data uncertainty on policy evaluations, which could impact advice for EBFM. This objective is addressed in six papers.