Biggs, R., C. Rhode, S. Archibald, L. M. Kunene, S. S. Mutanga, N. Nkuna, P. O. Ocholla, and L. J. Phadima. 2015. Strategies for managing complex social-ecological systems in the face of uncertainty: examples from South Africa and beyond. Ecology and Society 20(1): 52.http://dx.doi.org/10.5751/ES-07380-200152

In order to fulfill multiple sustainable development targets, most prominently human development, poverty eradication and climate change mitigation, African countries need infrastructure that cover basic needs while at the same time promote industrialization and value creation. G20 countries can support African countries by: (1) aligning and cementing the G20 Agenda for Africa with African initiatives, SDGs and the Paris Agreement, (2) mitigating economic risks of climate change through supporting low carbon development pathways in Africa, (3) incentivizing low carbon development by phasing out subsidies and eventually putting a price on carbon and (4) creating and enabling a level playing field for low carbon technologies, which includes integrated strategies for de-risking renewable energy investments.

Background: Many countries in the world are still struggling to control COVID-19 pandemic. As of April 28, 2020, South Africa reported the highest number of COVID-19 cases in Sub- Sahara Africa. The country took aggressive steps to control the spread of the virus including setting a national command team for COVID-19 and putting the country on a complete lockdown for more than 100 days. Evidence across most countries has shown that, it is vital to monitor the progression of pandemics and assess the effects of various public health measures, such as lockdowns. Countries need to have scientific tools to assist in monitoring and assessing the effectiveness of mitigation interventions. The objective of this study was thus to assess the extent to which a systems dynamics model can forecast COVID-19 infections in South Africa and be a useful tool in evaluating government interventions to manage the epidemic through ‘what if’ simulations. Design and methods: This study presents a systems dynamics model (SD) of the COVID-19 infection in South Africa, as one of such tools. The development of the SD model in this study is grounded in design science research which fundamentally builds on prior research of modelling complex systems. Results: The SD model satisfactorily replicates the general trend of COVID-19 infections and recovery for South Africa within the first 100 days of the pandemic. The model further confirms that the decision to lockdown the country was a right one, otherwise the country's health capacity would have been overwhelmed. Going forward, the model predicts that the level of infection in the country will peak towards the last quarter of 2020, and thereafter start to decline. Conclusions: Ultimately, the model structure and simulations suggest that a systems dynamics model can be a useful tool in monitoring, predicting and testing interventions to manage COVID-19 with an acceptable margin of error. Moreover, the model can be developed further to include more variables as more facts on the COVID-19 emerge.

There is a lack of long-term greenhouse gas (GHG) measurement infrastructures in Africa. This limits our understanding of the temporal dynamics of the biosphere-atmosphere exchange of carbon in response to climate change. Where relevant infrastructures have been established in externally funded research projects, they have often not been successfully transferred to local institutions at project termination, nor maintained in the long term. This leads to loss of capacity and continuity in primary data. We describe a collaborative approach where eddy-covariance (EC) towers for continuous long-term observation of carbon dioxide and energy fluxes were constructed under two consecutive German-funded research projects and designed to complement existing South African infrastructures. They will be transferred to partner institutions at project termination, supported by deliberate capacity building actions for long term sustainability. Joint activities were implemented to i) strengthen technical expertise for infrastructure maintenance, ii) introduce new generation of academic scientists to the topic, iii) co-develop a training concept to enhance local capacity to continue teaching the topic, iv) improve the uptake and use of data by the research community, v) improve data use and access by stakeholders, and vi) facilitate knowledge exchange between institutions. Co-designed activities included training, apprenticeships and knowledge exchange, student exchange, co-supervision, and public outreach. Following a similar model in international research projects could significantly benefit 1) national capacity for emission inventories, 2) development of long-term GHG observation networks, and 3) the global scientific community via improved availability of data. While we specifically focus on a network of GHG observations, the principles are applicable for the infrastructure to observe other surface/atmosphere exchange processes or other long term observational infrastructure.