Title: On the complementarity of ecosystem simulation models in strategic fishery planning and management
Doctoral candidate: Vianny Natugonza
Dr. Gunnar Stefansson, Professor at the Faculty of Physical Sciences at the University of Iceland (advisor).
Dr. Erla Sturludóttir, Post doc at the Science Institute – University of Iceland
Dr. Tumi Tomasson, director of the United Nations University Fisheries Training Program (UNU-FTP), Reykjavik, Iceland
Dr. Chrispine Nyamweya, Kenya Marine and Freshwater Research Institute (KMFRI), Kisumu, Kenya
The potential of multiple ecosystem simulation models to give consistent policy evaluations and recommendations is investigated in this study. The rationale is that if models with different structure and formulation give comparable results, there is an increased likelihood that they can be trusted and used in the formulation of long-term strategic policies. The study is carried out on Lake Victoria (East Africa) using two ecosystem modelling tools, Ecopath with Ecosim (EwE) and Atlantis. The progress of the study is now reported in three papers.
In the first paper, two EwE models are developed: the historical model, which is calibrated with time series data for the period 1960-2015; and the present-day model (2010-2015), which is not fitted to time series data. The two models are projected into the future, using fishing policy scenarios, and the results compared. Results suggest that uncalibrated EwE models may also be useful if: i) parameterization is rigorous, utilising adequate knowledge about the system; ii) adequate information exists on annual rate of biomass change for individual functional groups, especially for less productive groups; iii) representation of trophic interactions is precise, utilising robust stomach content data; and iv) predator-prey interactions follow mixed trophic control mechanisms. This study helps to assess the level of confidence that can be attached to policy recommendations from uncalibrated models whenever time series observational data are not available to calibrate the model.
In the second paper, EwE and Atlantis models are compared by varying fishing mortality for the key functional groups: the top predator, Nile perch (Lates niloticus) and key prey species (haplochromines). The aim is to understand how the ecosystem effects of fishing are sensitive to model structure and assumptions. Results show qualitative similarities (direction of change) for the target species; however, the cascading effects on non-target species vary across models, depending on the trophic distance from the target group. This work helps to highlight areas where different model considerations may lead to varying predictions, which can subsequently be used to improve the models.
In the third paper, trade-offs between socio-economic and conservation objectives are investigated. The aim is to weigh the relative risks against the benefits of different management objectives and promote discussion among stakeholders and the public on future management policies. The analysis is divided into two parts. The first part involves using the “optimal policy search” routine of the EwE software to configure long-term, gear-specific, fishing effort levels that can maximize economic, social, or conservation objectives. Results show that profit maximization is more compatible with conservation objectives than is the maximization of yield (or employment), but the fishing effort (and potential yield) would be reduced in every fishing gear in order to protect all the species from overfishing. The second part involves applying the resulting “optimal” fishing effort levels to both EwE and Atlantis models to predict long-term changes in the ecosystem. Here, EwE and Atlantis predict opposite results, implying that even qualitative predictions by the two models can differ depending on the question being investigated.