An Atlantis model of the southern Benguela upwelling system: Validation, sensitivity analysis and insights into ecosystem functioning

- An application of Atlantis for the Benguela upwelling system was updated and validated against time series of biomass and catch (1990-2013).
- Univariate skill metrics were used to evaluate model performance of biomass of selected species.
- A sensitivity analysis, focused on the growth rate of phytoplankton and large zooplankton was conducted.
- Skill metrics suggest that the model captures the main emergent properties of the southern Benguela.
- The most marked differences in relative biomass among runs were attributed to changes in the growth rate of large zooplankton.

Ecosystem models are valuable tools for evaluating the effects of different environmental stressors on an ecosystem and to increase system understanding. The Atlantis modelling framework is an end-to-end model that includes information and processes from the abiotic environment to the human component of a system. An application of Atlantis for the Benguela and Agulhas Currents was updated and validated against time series of biomass and catch (1990-2013). Five univariate skill metrics were used to evaluate model performance of biomass data of selected species. A sensitivity analysis, focused on the growth rate of small and large phytoplankton and large zooplankton, was conducted to evaluate the influence of these parameters on model outputs. A total of 26 alternative model parameterisations based on a variation of ± 20% around the growth parameter of the selected groups were compared to the baseline model. Skill metrics suggest that the model captures the main emergent properties of the southern Benguela, the magnitude and trends in biomass and catch of most modelled groups. Large variations in biomass were observed among the sensitivity runs compared to the baseline. The most marked differences in relative biomass among runs seem to be attributed to changes in the growth rate of large zooplankton. The Atlantis model presented here has the capability to be used as a tool to provide strategic information for fisheries management purposes in the southern Benguela system.