Browsing by Author "Nyamweya, Chrisphine"

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    Ecosystem modelling of data-limited fisheries: How reliable are Ecopath with Ecosim models without historical time series fitting?
    (Journal of Great Lakes Research, 2020) Natugonza, Vianny; Ainsworth, Cameron; Sturludóttir, Erla; Musinguzi, Laban; Ogutu-Ohwayo, Richard; Tomasson, Tumi; Nyamweya, Chrisphine; Stefansson, Gunnar
    Long-term time series data are not available for many of the African Great Lakes. This precludes fitting ecosystem model parameters to time series data, and we do not know how reliable non-fitted models are compared to fitted ones in terms of predicting consequences of alternative management strategies. To investigate this, we generate a historical Ecopath with Ecosim (EwE) model for Lake Victoria (East Africa), fitted to time series data (1980–2015), and a present-day EwE model (representing average conditions for the period 2010–2015). We do scenario simulations using the present-day model and the comparable 2015 end-state of the historical model, and test if incorporating information on short-term biomass trends by adjusting biomass accumulation (BA) parameter in the present-day model increases its reliability. We find that there are differences in model predictions, but those differences can be lessened by adjusting BA terms in the present-day model to reflect biomass trends from short-term empirical data. We also compare the models with and without fitted vulnerability parameters. The models generally give comparable results for the dominant commercial fisheries at low fishing pressure; when fishing mortality is increased, the models give variable predictions. This study adds to the current understanding of the limitations of EwE models that are not challenged to reproduce long-term historical fishery responses to perturbations. We conclude that for the less productive groups, as well as groups that suffer heavy mortality (either due to predation or fisheries), it may be appropriate to use negative BA as first draft assumption in present-day models.
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    Ecosystem models of Lake Victoria (East Africa): Can Ecopath with Ecosim and Atlantis predict similar policy outcomes?
    (Journal of Great Lakes Research, 2019) Natugonza, Vianny; Ainsworth, Cameron; Sturludóttir, Erla; Musinguzi, Laban; Ogutu-Ohwayo, Richard; Tomasson, Tumi; Nyamweya, Chrisphine; Stefansson, Gunnar
    Ecosystem simulation models are valuable quantitative decision tools for supporting ecosystem-based fisheries management. However, the application of ecosystem models in fisheries management is still undermined by the lack of simple procedures to test the effect of model uncertainty on policy outcomes. The use of multiple ecosystem models is viewed as ‘‘insurance” against the effects of uncertainty emanating from modelling complex systems, which calls for investigations to ascertain whether models with different structure and assumptions can give consistent policy evaluations. We compared two structurallydistinct ecosystem models, Ecopath with Ecosim (EwE) and Atlantis, for Lake Victoria by varying fishing mortality of the key functional groups: Nile perch (the top predator) and haplochromines (key prey species). We compared model behaviour at the ecosystem level and at the level of functional groups, by evaluating changes in biomass of targeted groups and the consequent effects of changes in target groups on non-target groups. Results showed qualitative similarities (direction of change) for the major harvested groups; however, the cascading effects on non-target species varied across models, depending on the species interaction feedbacks. We conclude that: EwE and Atlantis, despite the huge differences in ecological processes between the models, can give consistent qualitative advice, which is needed for strategic management decisions; consistency in the representation of trophic interactions may help to minimize variations in simulated fishery responses due to model structure. This study helps to highlight scenarios that are robust to model choice, and for which simpler models (such as EwE) could also provide reliable advice.
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    Future success and ways forward for scientific approaches on the African Great Lakes
    (Journal of Great Lakes Research, 2023) Lawrence, Ted J.; Achieng, Alfred O.; Chavula, Geoffrey; Haambiya, Lloyd Haninga; Iteba, Jacob; Kayanda, Robert; Kaunda, Emmanuel; Migenim Z. Ajode; Muvundja, Fabrice A.; Nakiyende, Herbert; Nyamweya, Chrisphine; Obiero, Kevin; Pierre, Denis Plisnier; Harris, Phiri; Claver, Sibomana; Stephanie, Smith
    The seven African Great Lakes are some of the most critical freshwater, large-lake systems in the world, providing essential services, food, drinking water, and other livelihood support to over 62 million people. Like most freshwater systems around the world, these lakes are strained by anthropogenic stressors, leading to degradation of these biologically important, and human-dependent resources. Despite their importance, these lakes suffer from insufficient research approaches which are short-term, disparate, and unharmonized. Further, a lack of monitoring, data and information exchange, education and training, and gender balance in research, all lead to insufficient knowledge on which to better manage and protect these lakes. While past efforts have resulted in some knowledge accumulation, there is a need for new approaches to understanding and managing these lakes: bottom-up, harmonized, and long-term processes. This paper, and those within this special section of the Journal of Great Lakes Research, highlight new, highly collaborative efforts of freshwater experts representing each riparian country of each African Great Lake through formal advisory groups. These papers are the result of harmonized efforts and collegial agreements as to what issues need to be addressed foremost, written by those on the ground. While each lake has specific, prioritized lists of issues, five overarching issues must be addressed to achieve success on these lakes: providing agency and coordination of African freshwater scientists; increase long-term monitoring; strengthen education and training of existing and future experts; enhance information and data exchange; and ensure stronger gender balance in science and leadership positions.