Globally, the COVID-19 pandemic bought devastating impacts to multiple economic sectors, with a major downfall observed in the tourism sector owing to explicit travel bans on foreign and domestic tourism. In Nelson Mandela Bay (NMB), South Africa, tourism plays an important role; however, negative effects from the pandemic and resulting restrictions has left the sector dwindling and in need of a path to recovery. Working together with local government and stakeholders, this study applied system dynamics modelling to investigate the impacts of COVID-19 on coastal tourism in NMB to provide decision-support and inform tourism recovery strategies. Through model analysis, a suite of management interventions was tested under two ‘what-if’ scenarios, with reference to the business-as-usual governance response scenario. Scenario one specifically aimed to investigate a desirable tourism recovery strategy assuming governance control, whereas scenario two investigated a scenario where the effects of governance responses were impeded on by the exogenous effects from the virus. Results suggest that uncertainty remained prevalent in the trajectory of the infection rate as well as in associated trends in tourism; however, through the lifting of travel restrictions and the continual administration of vaccines, a path to recovery was shown to be evident.

This study aimed to examine the impacts of COVID-19 on coastal tourism in Nelson Mandela Bay (NMB), South Africa, and propose effective management interventions to enable swift recovery. A participatory system dynamics modelling approach was applied through a qualitative causal mapping processes to support a quantitative model. Multiple stakeholder perspectives were incorporated to gain a holistic understanding of the local impacts. The study revealed that the effects of the pandemic on tourism in NMB were dynamic and accompanied by shifts in governance responses and traveller behaviour. Uncertainty surrounding the rate of recovery in different sectors was observed. Through collaboration with local stakeholders, recovery interventions were identified and tested according to short-to-long-term tourism needs in stages of recovery, revival and growth. The findings highlight the importance of cross-sectoral collaboration in facilitating informed decision-making for sustainable tourism recovery. Moreover, it is encouraged that participatory, multi-stakeholder approaches are adopted to explore the impacts of exogenous factors on the tourism sector, such as those arising from public health, climate, and social–political change. This inclusive and dynamic approach can be used to develop management strategies that are responsive and adaptable to complex and evolving circumstances that can impact the tourism industry.

The Agulhas Current Time-series Experiment mooring array (ACT) measured transport of the Agulhas Current at 34^∘ S for a period of 3 years. Using along-track satellite altimetry data directly above the array, a proxy of Agulhas Current transport was developed based on the relationship between cross-current sea surface height (SSH) gradients and the measured transports. In this study, the robustness of the proxy is tested within a numerical modelling framework using a 34-year-long regional hindcast simulation from the Hybrid Coordinate Ocean Model (HYCOM). The model specifically tested the sensitivity of the transport proxy to (1) changes in the vertical structure of the current and to (2) different sampling periods used to calculate the proxy. Two reference proxies were created using HYCOM data from 2010 to 2013 by extracting model data at the mooring positions and along the satellite altimeter track for the box (net) transport and the jet (southwestward) transport. Sensitivity tests were performed where the proxy was recalculated from HYCOM for (1) a period where the modelled vertical stratification was different compared to the reference proxy and (2) different lengths of time periods: 1, 3, 6, 12, 18, and 34 years. Compared to the simulated (native) transports, it was found that the HYCOM proxy was more capable of estimating the box transport of the Agulhas Current compared to the jet transport. This was because the model is unable to resolve the dynamics associated with meander events, for which the jet transport algorithm was developed. The HYCOM configuration in this study contained exaggerated levels of offshore variability in the form of frequently impinging baroclinic anticyclonic eddies. These eddies consequently broke down the linear relationship between SSH slope and vertically integrated transport. Lastly, results showed that calculating the proxy over shorter or longer time periods in the model did not significantly impact the skill of the Agulhas transport proxy. Modelling studies of this kind provide useful information towards advancing our understanding of the sensitivities and limitations of transport proxies that are needed to improve long-term ocean monitoring approaches.