Algoa Bay, Gqeberha in the Eastern Cape Province, has become the central hub for marine research within South Africa on account of both its rich diversity and dynamic oceanographic processes. With research conducted in the Bay proving instrumental in national marine conservation and wellbeing, the current study contributes to the growing body of work through estimating the economic value of the ecosystem services, rendered by Algoa Bay, through time. The economic value of Algoa Bay’s ecosystem services was estimated over a two-decade period, between 2000 and 2020, across five timesteps. The valuation applied a range of methods in conjunction with sourced data, to calculate the ecosystem service values derived by specific beneficiary groups. The valuation forms part of the Modelling Algoa Bay Project, and acts as a vital point in moving towards developing a system dynamics model for the Bay, in which various policy scenarios can be simulated to assess the effect on the value of ecosystem services provided by Algoa Bay.
Approach
The estimation of accurate ecosystem service values revolved around three fundamental factors. These factors included beneficiaries, ecosystem services and valuation methods. Thorough research into the respective factors revealed the presence of three main beneficiary groups deriving value from the services provided by the bay. These groups were defined as the local residents (Nelson Mandela Bay), South African residents and the global citizens. These beneficiary groups proved to derive value from a total of 15 ecosystem services, categorized according to provisioning, regulating, supporting or cultural services. The period in which the study would take place was then identified as the two decades between 2000 and 2020, with datapoints established at five-year timesteps. With beneficiary groups, ecosystem services and the five timesteps identified and understood, assignment of the most applicable valuation method to each respective service was conducted. These methods included statutory payments, market prices, engineering values, benefit transfer and property values.
The outline of the adopted approach indicates the extensive data requirements of the valuation. The intemporal nature of the valuation intensified these data requirements further. In terms of gathering data, two main sources were referenced. The first was desktop review, which included sources such as academic papers, journal articles, government publications and public records, all available online. The second source was soliciting information from stakeholders, entailing correspondence such as emails and phone calls to various parties including local municipalities, private enterprises, and related parties. Furthermore, a number of PAIA processes proved to be necessary when data was not readily available to the public.
Results
Proceeding to the valuation, it is crucial to note that two scenarios were run, namely a conservative and alternative scenario. Not all ecosystem services were valued in our research due to a lack of usable data, as a result making the conservative and alternative scenario results both reflect lower bound estimates. By working with these estimated lower bound unit values, much of the uncertainties are mitigated. The conservative scenario opted for the lower unit value or narrower definition of services throughout. Application of the stated methods yielded results which have been plotted in the Sankey graphs below.
Under the conservative scenario, the local beneficiary group’s derived value grew from R1 692.3 million in 2000 to R11 374.4 million in 2020, while the global beneficiary group’s derived value grew from R3 110.1 million in 2000 to R18 698.3 million in 2020. The difference in values enjoyed by the local and global beneficiary groups can be attributed to the identification of values solely attributed to the global population group, arising from the maintenance of genetic diversity and life cycle services, as well as the existence and bequest service.
Figures 1A and 1B both present the value provided by Algoa Bay’s ecosystem services for the years 2000 and 2020 respectively, for the local beneficiary group, while Figure 2 presents the value provided by Algoa Bay’s ecosystem services for the global beneficiary group, for the year 2000. It is evident that there exists a significant difference between the monetary values and the relative proportions of services among the various services when comparing the local benefits to that of the national and global benefits. At a local level, in 2020 (Figure 1B), the value of recreation and tourism dominates and is estimated to be more than 74% of the total value derived from Algoa Bay. This is followed by the spiritual, cognitive and other value very far behind at 9.5%. At a global level, recreation and tourism remains dominant, accounting for over 70% of the total value in 2020. Existence and bequest and maintenance of genetic diversity and life cycles follow, accounting for 7.3% and 6.3% respectively. In both cases the onshore ecosystem and cultural values dominate, owing to the recreation and tourism service predominantly deriving its value from this ecosystem and being classified as a cultural service. Noticeably, the onshore and coastal ecosystems accounts for over 90% of value for local and global beneficiaries, as most of the value recreation and tourism occurs at this interface. Figure 1A then allows one to gauge how the relative proportions of value have changed over the two-decade period, when compared to Figure 1B. It is clear to see that recreation and tourism maintained its dominance across the five timesteps, resulting in the onshore ecosystem and the cultural ecosystem service category also accounting for the majority of value across all five timesteps. For example, the value of the right of access service has also increased dramatically from less than 0.67% to 4.9%, which can be attributed to the establishment of the Port of Ngqura, which became operational in 2009.
The total values, for both the local and global beneficiary groups, under the conservative scenario are presented in Table 1 for all five timesteps. It is clear to see that the value of ecosystem services, rendered by Algoa Bay, has steadily increased over the two-decade period. Interestingly, the local estimate slightly decreased between 2010 and 2015. This is attributed to the dominance of the recreation and tourism service, which slightly declined between the two timesteps, as the 2010 FIFA World Cup substantially bolstered the 2010 recreation and tourism service value. The global estimate maintained its increasing trend between these two timesteps, as the global beneficiary group is slightly less reliant on the recreation and tourism service and derives value from a greater number of ecosystem services.
Modelling the interactions between ecosystem services
The valuation of Algoa Bay’s ecosystem services provides the team with a strong foundation to move into the next phase of understanding how the ecosystems in Algoa Bay generate value for the three different beneficiary groups. With the use of a system dynamics model, the relationships between ecosystem services can be better understood. By modelling the interactions between the determinants of ecosystem services’ value, the interdependencies can be better understood and the factors, that allow for ecosystem services to provide value, can be clearly outlined. Furthermore, exogenous policy decisions and scenarios that would affect the functioning of ecosystems in Algoa Bay, in the future, can be simulated to assess how the ecosystem services of the Bay will be impacted, and thus the value which they provide.
Figure 1A: Local estimate of the economic value of the ecosystem services rendered by Algoa Bay by Ecosystem: R/year (1999/2000)
Conservative scenario: (Total value: R1 692.3 million)
Figure 1B: Local estimate of the economic value of the ecosystem services rendered by Algoa Bay by Ecosystem: R/year (2019/2020)
Conservative scenario: (Total value: R11 374.4 million)
Table 1: Total value of Algoa Bay's ecosystems, in nominal terms, across all five timesteps under the conservative scenario (R, millions)
Team
The project has been conducted by an ecologist, Matthew Orolowitz, and economist, Chase Lourens, along with Rozanne Peacock, all led by Professor James Blignaut of Asset Research and Stellenbosch University. Matthew graduated with a masters of science degree in conservation biology from the University of Cape Town in 2020, with a focus on how drinking dependency shapes the behavioural thermoregulatory trade-offs for arid zone larks. Chase graduated with a masters degree in economics from Stellenbosch university in 2023, which entailed a focus on applying economic concepts to environmental resources, as he conducted a cost-benefit assessment of seismic exploration off the Wild Coast. Both Matthew and Chase have a common love for the environment and its preservation and are therefore motivated to complete this project in a way that yields useful and accurate results. Rozanne completed her masters at the University of Pretoria, which focused on the full cost of siltation in the Ntabelanga Dam. She has experience and skills in system dynamic modelling which is crucial in this project.
We are grateful for and hereby acknowledge support from the NRF Algoa Bay Community of Practice (grant number 110612), the South African Research Chair Initiative (SARChI) in Marine Spatial Planning and the One Ocean Hub (grant number GCRF UKRI - NE/S008950/1) which have made this research possible.
