An Estimate of the Economic Value of the Marine and Coastal Ecosystem Services of Algoa Bay, South Africa
Abstract
1. Introduction
2. Marine Spatial Planning: A Review
3. Materials and Methods
3.1. Study Area
3.2. Ecosystem Services Valuation Framework
3.2.1. Right of Access
Definition and Scope
Biophysical and Monetary Boundaries and Measures
3.2.2. Food Provisioning (Non-Cultivated)
Definition and Scope
Biophysical and Monetary Boundaries and Measures
3.2.3. Food and Raw Materials (Cultivated)
Definition and Scope
Biophysical and Monetary Boundaries and Measures
3.2.4. Waste Dilution
Definition and Scope
Biophysical and Monetary Boundaries and Measures
3.2.5. Air Quality Regulation
Definition and Scope
Biophysical and Monetary Boundaries and Measures
3.2.6. Climate Regulation
Definition and Scope
Biophysical and Monetary Boundaries and Measures
3.2.7. Moderation of Extreme Events
Definition and Scope
Biophysical and Monetary Boundaries and Measures
3.2.8. Erosion Prevention
Definition and Scope
Biophysical and Monetary Boundaries and Measures
3.2.9. Nutrient Cycling
Definition and Scope
Biophysical and Monetary Boundaries and Measures
3.2.10. Water Quality
Definition and Scope
Biophysical and Monetary Boundaries and Measures
3.2.11. Maintenance and Protection of Nursery and Gene Pool and Life Cycle
Definition and Scope
Biophysical and Monetary Boundaries and Measures
3.2.12. Amenity Value
Definition and Scope
Biophysical and Monetary Boundaries and Measures
3.2.13. Recreation and Tourism
Definition and Scope
Biophysical and Monetary Boundaries and Measures
3.2.14. Spiritual, Cognitive and Other
Definition and Scope
Biophysical and Monetary Boundaries and Measures
3.2.15. Existence and Bequest
Definition and Scope
Biophysical and Monetary Boundaries and Measures
4. Results
4.1. Value of Ecosystem Services for Various Beneficiaries
4.2. Value of Ecosystem Services for Local Beneficiaries
4.3. Value of Ecosystem Services in Terms of Ecosystems
5. Discussion
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
| Beneficiaries | 2000 | 2005 | 2010 | 2015 | 2019 |
|---|---|---|---|---|---|
| Local | 1.00 | 1.09 | 1.15 | 1.24 | 1.27 |
| Global | 6108 | 6517 | 6942 | 7383 | 7805 |
| Onshore | Coastal | Offshore | Coral Reefs | Estuaries | |
|---|---|---|---|---|---|
| Right of access | Industrial site values (A1) [107,108,109,110,111,112,113]: Industrial site values = Average site value × Size ×rates Initial research into directly obtaining the actual site values were unsuccessful. A proxy was used, in which the average site values per hectare were obtained and multiplied by the size of the ports. To obtain the right to access the port for each timestep on an annual basis, the previous calculation was multiplied by industrial property rates. | Port dues (A2) [[114,115] Appendix C]: The actual port dues were obtained directly from Transnet through the Promotion of Access to Information Act (PAIA) process. Port limits were obtained from the Department of Transport and were used to calculate the per hectare value and value per ecosystem of the port dues (accounting for MPAs and mariculture). Mariculture permits (A3) [116,117,118,119,120,121]: Mariculture permits = application fee + permit fee + right to engage in mariculture Licencing and permits fees were obtained in the Marine Living Resources Act of 1998 and subsequent iterations for the past 20 years. This right-of-access ecosystem service consists of fees to conduct mariculture operations. These values were summed. Only companies that actively partook in mariculture were included. Therefore, these values were only applied to for the Knysna Oyster Company. Fishing permits (A4): See offshore ecosystem for a summary of the valuation. | Port dues (A2): See coastal ecosystem for a summary of the valuation. Fishing Permits (A4) [Appendix C, [117,118,119,120,121,122,123,124,125,126,127,128,129]]: No. of right holders in AB = No. of vessels in AB× Right holder: vessels in RSA The number of fishing vessels for the five commercial fisheries operating in Algoa Bay were obtained from the Department of Forestry, Fisheries and the Environment (DFFE) through the PAIA process. However, the right-of-access fees are based on right holders rather than on vessel. The national ratio of right holders to vessels was obtained from various sources and assumed to be constant. This ratio was multiplied by the number of vessels in Algoa Bay to obtain the number of right holders in bay. Total fees per fishery = Right holders × (Application fee + permit fee) + no. of vessels in AB*licence fees To get the total value per fishery, these right holders were subsequently multiplied by sum of the permit and application fees and added to the product of the number of vessels and licence fees of the vessels. | Industrial Site values (A1) [108,109,110,130]: Industrial Site values = Average site value × Size × rates The Coega and Baakens estuaries both occupy areas within port bounds. This area was taken out of the onshore ecosystem and reallocated to the estuary value. The same method was employed as in the onshore ecosystem. | |
| Food provisioning (non-cultivated) | Commercial fishing price (B1) [[55,129,131,132,133,134], Appendix C]: Market prices for each commercial fishery were obtained from the sources listed above. The value was deflated and inflated to the different timesteps. However, in some instances, market values were indicated in US dollars. These values were converted to rand-equivalent values using the PPP [55]. Catch data: See offshore ecosystem for a summary of the valuation. | Commercial fishing price (B1): See coastal ecosystem for a summary of the valuation. Catch data [Appendix C]: Total catch volumes (in tons) were obtained from the DFFE through the PAIA process for each fishery. | Subsistence fishing value (B2) [74]: The two estuaries identified, the Sundays and Swartkops estuaries, provide a subsistence fishing value estimate of the estuaries. The final annual estimate was used across all five timesteps by inflating and deflating the values to the various years. | ||
| Food and raw materials (cultivated) | Mariculture gross income (C1) [116]: Revenue = Total annual yield × price per yield The revenue was calculated by multiplying the total annual yield by the price per yield. These estimates were provided by the Knysna Oyster Company. | ||||
| Waste dilution | Waste dilution (D1) [[135,136,137,138,139,140,141,142,143,144], Appendix D]: Waste water dilution value = nutrient load entering coastal area × Cost of removing kg pollutant by WWTW The ocean’s ability to dilute wastewater is estimated by taking the capital replacement cost for wastewater treatment plants operating in Algoa Bay in treating the nutrient loads from untreated dissolved inorganic nitrogen and phosphorous discharged from wastewater treatment works as well as from the concentrations found at estuary mouths. | ||||
| Air quality regulation * | Air quality regulation (E1): ESVD [145]: Value = value per hectare (R/ha) × area (ha) This study calculated the amount of NOx, in the form of fine dust, captured by the ecosystem and estimated an amount per kilogram based on the cost that would have arisen from health damage. The values for the different biomes within the ecosystem were then averaged across to arrive at a final value per hectare for the onshore ecosystem. | Air quality regulation (E1): ESVD [66]: This study measured the amount of sulphur dioxide, fine particulate matter, nitrogen dioxide and ozone removed under ‘no vegetation’ and ‘current vegetation’ scenarios by assessing the change in concentration, and a monetary benefit was then estimated on the basis of health benefits. The ‘no vegetation’ monetary value was then subtracted from the ‘current vegetation’ monetary value to reach a value per hectare amount. | |||
| Climate regulation * | Climate regulation (F1): ESVD [67]: This study employed a choice experiment to derive a value for the climate regulation service. A ‘series of CE choice tasks’ were presented to the participants, in which hypothetical scenarios were posed. From the answers of the participants, the authors estimated a value for the climate regulation service using a conditional logit model. | Climate regulation (F1): ESVD [68]: This study measured carbon sequestration from biomass samples. A one-way analysis of variance (ANOVA) was then used, which took seasonal variation into account, to value the amount of carbon sequestrated and stored. | Climate regulation (F1): ESVD [69]: The paper provided an in-depth assessment of carbon sequestration of salt marshes in South Africa and gave the range of values for the annual carbon dioxide equivalent reduction per hectare in salt marshes. | ||
| Moderation of extreme events * | Moderation of extreme events (G1): ESVD [70]: This study developed a three-step approach to value the moderation of extreme events in the UK. A public survey was conducted, in which the choice experiment method was used. Participatory workshops were used to overcome the complexity of the different policy scenarios. Following the collection of responses, an ecological weighting matrix was used to pool the judgement of experts over the “relative level of ecosystem services delivered by habitats”. | Moderation of extreme events (G1): ESVD [71]: This study estimated the value provided by the Danojon Reef in the Philippines for its ability to moderate extreme events using the contingent valuation method. A questionnaire was issued to a variety of individuals, such as tourists, residents, etc. The questionnaire elicited a willingness to pay (WTP) for this ecosystem service. The WTP measure provided by respondents was then manipulated to reflect all individuals who make use of the ecosystem services. | |||
| Erosion prevention * | Erosion prevention (H1): ESVD [72]: This study used the “expert survey” method to provide values for several services for the coastal system found in Guangxi Province, China. In total, 300 questionnaires were sent out to experts in the region. From these responses, the percentage of reduction in costs attributable to the erosion prevention was calculated. | Erosion prevention (H1): ESVD [73]: This study conducted interviews with reef users in the Solomon Islands, in which the WTP of interviewees were derived to construct an “artificial market for ecosystem services”. | |||
| Nutrient cycling * | Nutrient cycling (I1) [74]: This study was used to value the top twenty temperate estuaries in terms of nursery values by observing freshwater flows, the frequency and duration of the estuary mouth openings, which are considered to be the biggest factors affecting the estuarine biota. | ||||
| Water quality* | Water quality (J1) [[75,135,136,137,138,139,140,141,142,143,144,146,147,148,149,150,151,152,153], Appendix D]: Water quality value = (pollutant concentration estuary head-pollutant concentration estuary mouth) × molar mass × Mean annual runoff × Cost of removing kg pollutant by WWTW The extent of phosphorous and nitrogen cycles operating in estuaries to remove dissolved inorganic nitrogen (DIN) and phosphorous (DIP) is estimated by taking the difference in average concentrations at the estuary mouth and head. A reduction in DIP and DIN is considered the treatment of the estuary in sinking these pollutants. The equivalent cost of treating similar nutrient loads with wastewater treatment plants is used to estimate value. | ||||
| Maintenance and protection of nursery and gene pool and life cycle * | Maintenance and protection of nursery and gene pool and life cycle (K1): ESVD [72]: This study focused on an area spanning 876 hectares in the Cairns Harbour Bay in Australia. A deterministic simulation model was employed to estimate the ability of the coastal system to maintain the stocks of different species living in the Bay. | Maintenance and protection of nursery and gene pool and life cycle (K1): ESVD [78]: This study estimated the value of the offshore ecosystem in the UK, arising from its ability to maintain its level of marine biodiversity. Using a goods and services approach, in which the goods and services produced by the offshore ecosystem’s marine biodiversity are valued. | |||
| Amenity value | Statutory payments (L1) [130,154,155,156]: Premium in property value = (amenity premium × Housing Price Index) × suburb extent The amenity values were adjusted using the FNB Housing Price Index. These premiums were summed providing a total amenity premium. The total amenity premium was multiplied by the total extent of three suburbs (Humewood, Northend and Summerstrand). Statutory payment = Premium in property value × ratio. Statutory payments were calculated by multiplying the premium in property value that was calculated in the previous step by the ratio of property rates to land value. Willingness to pay [108,109,157,158]: The willingness to pay premium for amenity values was calculated by collating sales transactions data from Property24 for each of the three suburbs where properties sold were counted and property value for each year summed. The number of properties sold was multiplied by the average property size to give the total extent of properties sold for that year. This extent of properties sold was then multiplied by the amenity value to provide the premium paid in the property sale (willingness to pay). | Amenity value (L1) [58,59,74,107,108,109,158]: Estimates for property values were obtained from Turpie and Clark [74] for the Sundays and Swartkops estuaries and were subsequently inflated/deflated. Amenity value = property value× ratio of property rate to land value × municipal rates Property rates were multiplied by the ratio of property rate to land value and then by the municipal rates to obtain the amenity value. | |||
| Recreation and tourism | Travel cost (M3) [101,102,103,104,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175]: Travel cost = total distance travel × rate per km The travel cost was calculated by measuring the total distance travelled by all domestic tourists each year from each of their respective provinces and multiplying it with the cost per distance (R/km). Opportunity cost (Residents)(M2) [52,105,176]: Opportunity cost = Residents using the beach × hours spent at beach × GDP/capita/hour The number of residents using the beach was multiplied by hours spent at the beach and cost of time (measured by the GDP per capita per hour). Opportunity cost (Domestic) (M2) [160,176]: Opportunity cost = domestic bed nights or visitor days × GDP/capita/day × moderation value GDP per capita per day was multiplied by both the visitor days and bed nights to give a total opportunity cost value. The opportunity cost of overnight visitors was moderated by 70% since had the tourists been at work, income would have been earned strictly during working hours, and not 24 h per day. Day visitors were moderated by 20%. Direct recreational spend (M1): See offshore ecosystem for a summary of the valuation. | Direct recreational spend Travel cost (M1) [160]: Direct recreational spend: Overnight value = overnight visitors× average spend overnight visitors. The total overnight spend value was calculated by multiplying the total number of overnight visitors multiplied with the average spend per overnight visitor. Tourists were separated into domestic and foreign tourists, with the average spend and duration of stay differing between the two. | Direct recreational spend (M1): See offshore ecosystem for a summary of the valuation. | Direct recreational spend (M1): See offshore ecosystem for a summary of the valuation. | Recreational fishing (M4) [177,178]: Fishing value = annual no. of hours × ratio of population To calculate the value of fishing along the estuaries, the annual number of fishing hours for the Sundays and Swartkops estuaries was then multiplied by the ratio of the year of interest to the population of NMB in 2007. The opportunity cost method was used to value this service to these fishermen. The GDP per capita per hour value was multiplied by the total annual fishing hours to generate an annual value per estuary. Recreational boating (M4) [179,180]: Annual no. of boating hours = boats per weekend day × boating days per year × people per boat × hours per trip To calculate the value of boating along the Swartkops and Sundays estuaries, the number of boats was multiplied by the number of boating days (weekend days and public holidays for each year) and then multiplied by both the average number of people per boat and the assumed duration of the trip (2 h). Value of boating = annual no. of boating hours × GDP/capita/hour The same opportunity cost method was applied to the total annual number of boating hours as was performed with the annual fishing hours (see the previous section) to obtain the annual value per estuary. |
| Spiritual, cognitive and other * | Spiritual, cognitive and other (N1): ESVD [67]: See onshore climate regulation for more detail explanation. This study employed a “series of CE choice tasks”, where hypothetical scenarios were posed to participants. From their answers, a value for the sense of place individuals felt using a conditional logit model was estimated. | Spiritual, cognitive and other (N1): ESVD [175]: This study gathered information about a knowledge network of universities, NGOs and public authority companies that made use of the coastal systems. The authors estimated the annual revenue of this knowledge network and calculated a percentage of this revenue that could be attributed to the coastal systems ecosystem in Holland. | Spiritual, cognitive and other (N1): ESVD [79]: This study investigated the opportunities that coral reefs provide for research and education in Martinique. They assessed the level of public spending that was directed towards providing opportunities for research and maintaining the reef so that knowledge could be gained from a well-functioning reef. | ||
| Existence and bequest * | Existence and bequest (O1): ESVD [80]: This study employed a contingent valuation method to provide a value for the coastal systems located in Spain. Both an “open format” survey, in which participants were only asked their WTP, as well as a “binary format”, in which interviewers offer a “guideline value” and participants indicate whether or not they would be willing to pay this amount for the continued existence of the coastal system, were used. From these responses, the authors estimated a binary logit model to derive values. | Existence and bequest (O1) [81]: This study estimated the value placed on the marine biome in the Western Cape, arising from individuals knowing the marine ecosystems are healthy. They used the contingent valuation method to elicit individual’s WTP to maintain the condition of the marine biome. Participants were asked how much they would be willing to contribute towards conservation efforts aimed at preserving the biodiversity in South Africa. | Existence and bequest (O1): ESVD [79,82,83,84,85]: Analogous studies on coral reefs found in Algoa Bay were not found. Therefore, values from a suite of different papers estimating the existence and bequest values for coral reefs around the world was used. Thus, an array of values was created. Quartiles were then calculated from the distribution of values, from which the second and third quartiles were used for the conservative and alternative values. |
Appendix B
Appendix B.1. Local Beneficiaries





Appendix B.2. Global Beneficiaries





Appendix C. Data and Values Used to Estimate the Right-of-Access Values with Respect to the Fishing Values
| Year | Annual Catch of Shallow-Water Hake Merluccius capensis and Deep-Water Hake M. paradoxus | Squid Jig | Small Pelagic | Shark Longline | Inshore Trawl | Licence | Permits | Levy | Application Fees |
|---|---|---|---|---|---|---|---|---|---|
| Tons | No. of Vessels | No. of Vessels | No. of Vessels | No. of Vessels | ZAR | ZAR | ZAR | ZAR | |
| a | b | c | d | e | (b + c + d + e) × Licence Fee of ZAR1318 | (b + c + d + e) × Permit Fee of ZAR831 | (a) × Offshore Hake Trawl Levy of ZAR227 | (b + C + e) × Commercial Permit of ZAR 240 + (d) × Large Pelagic Licence of ZAR9123 | |
| 2000 | 710.0 | 60 | 2 | 1 | 7 | 92,260 | 58,170 | 161,170 | 25,683 |
| 2001 | 790.0 | 64 | 2 | 0 | 11 | 101,486 | 63,987 | 179,330 | 18,480 |
| 2002 | 1000.0 | 68 | 5 | 0 | 9 | 108,076 | 68,142 | 227,000 | 19,680 |
| 2003 | 850.0 | 72 | 8 | 3 | 9 | 121,256 | 76,452 | 192,950 | 48,729 |
| 2004 | 700.0 | 76 | 10 | 4 | 8 | 129,164 | 81,438 | 158,900 | 59,052 |
| 2005 | 400.0 | 80 | 8 | 4 | 7 | 130,482 | 82,269 | 90,800 | 59,292 |
| 2006 | 338.6 | 82 | 15 | 6 | 16 | 156,842 | 98,889 | 76,857 | 81,858 |
| 2007 | 310.8 | 87 | 14 | 4 | 18 | 162,114 | 102,213 | 70,551 | 65,052 |
| 2008 | 1415.3 | 101 | 9 | 4 | 15 | 170,022 | 107,199 | 321,282 | 66,492 |
| 2009 | 1042.3 | 111 | 8 | 5 | 13 | 180,566 | 113,847 | 236,611 | 77,295 |
| 2010 | 1011.4 | 117 | 9 | 4 | 11 | 185,838 | 117,171 | 229,587 | 69,372 |
| 2011 | 824.6 | 121 | 6 | 3 | 9 | 183,202 | 115,509 | 187,173 | 60,009 |
| 2012 | 482.4 | 112 | 7 | 1 | 9 | 170,022 | 107,199 | 109,512 | 39,843 |
| 2013 | 286.7 | 94 | 7 | 1 | 8 | 144,980 | 91,410 | 65,080 | 35,283 |
| 2014 | 529.3 | 94 | 5 | 4 | 4 | 141,026 | 88,917 | 120,157 | 61,212 |
| 2015 | 1198.4 | 100 | 5 | 3 | 3 | 146,298 | 92,241 | 272,036 | 53,289 |
| 2016 | 1531.4 | 101 | 3 | 3 | 6 | 148,934 | 93,903 | 347,617 | 53,769 |
| 2017 | 2024.3 | 97 | 4 | 2 | 3 | 139,708 | 88,086 | 459,510 | 43,206 |
| 2018 | 2945.6 | 99 | 9 | 3 | 6 | 154,206 | 97,227 | 668,647 | 54,729 |
| 2019 | 934.3 | 113 | 5 | 3 | 8 | 170,022 | 107,199 | 212,096 | 57,609 |
| 2020 | 543.9 | 98 | 7 | 2 | 13 | 158,160 | 99,720 | 123,465 | 46,566 |
Appendix D. Data and Values Used to Estimate the Waste Dilution Values
| Physical Data | Nutrient Data | ||||||
|---|---|---|---|---|---|---|---|
| Sample ID | Date | Site | Phosphate (umol/L) | Silicate (umol/L) | Nitrate (umol/L) | Nitrite (umol/L) | Ammonium (umol/L) |
| Swartkops S1S1 | 2019/04/24 | S1 | 0.73 | 5.50 | 1.69 | 0.30 | 1.89 |
| Swartkops S1S2 | 2019/04/24 | S1 | 0.71 | 4.30 | 2.01 | 0.24 | 1.76 |
| Swartkops S1S3 | 2019/04/24 | S1 | 0.76 | 4.24 | 2.09 | 0.21 | 1.68 |
| Swartkops S1M1 | 2019/04/24 | M1 | 0.85 | 4.61 | 2.46 | 0.25 | 2.65 |
| Swartkops S1M2 | 2019/04/24 | M1 | 0.66 | 4.79 | 2.54 | 0.23 | 2.17 |
| Swartkops S1M3 | 2019/04/24 | M1 | 0.67 | 4.43 | 2.57 | 0.21 | 1.83 |
| Swartkops S1B1 | 2019/04/24 | B1 | 0.61 | 4.63 | 2.26 | 0.23 | 2.09 |
| Swartkops S1B2 | 2019/04/24 | B1 | 0.56 | 4.18 | 2.53 | 0.25 | 1.36 |
| Swartkops S1B3 | 2019/04/24 | B1 | 0.46 | 4.53 | 2.45 | 0.19 | 1.78 |
| Swartkops S6S1 | 2019/04/24 | S6 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Swartkops S6S2 | 2019/04/24 | S6 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Swartkops S6S3 | 2019/04/24 | S6 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
| Swartkops S1S1 | 2019/07/24 | S1 | 0.55 | 4.86 | 3.17 | 0.49 | 3.24 |
| Swartkops S1S2 | 2019/07/24 | S1 | 0.91 | 5.04 | 3.60 | 0.45 | 2.70 |
| Swartkops S1S3 | 2019/07/24 | S1 | 0.70 | 4.21 | 3.15 | 0.37 | 3.35 |
| Swartkops S1M1 | 2019/07/24 | M1 | 0.67 | 3.62 | 2.78 | 0.36 | 2.46 |
| Swartkops S1M2 | 2019/07/24 | M1 | 0.71 | 5.05 | 3.62 | 0.45 | 3.26 |
| Swartkops S1M3 | 2019/07/24 | M1 | 0.78 | 5.42 | 4.04 | 0.44 | 2.60 |
| Swartkops S1B1 | 2019/07/24 | B1 | 0.87 | 4.84 | 3.53 | 0.39 | 3.16 |
| Swartkops S1B2 | 2019/07/24 | B1 | 0.73 | 4.92 | 3.61 | 0.44 | 3.65 |
| Swartkops S1B3 | 2019/07/24 | B1 | 0.85 | 5.11 | 3.92 | 0.44 | 3.04 |
| Swartkops S6S1 | 2019/07/24 | S6 | 55.64 | 63.59 | 91.40 | 8.69 | 13.12 |
| Swartkops S6S2 | 2019/07/24 | S6 | 58.89 | 58.79 | 97.17 | 9.96 | 23.64 |
| Swartkops S6S3 | 2019/07/24 | S6 | 52.83 | 44.70 | 56.92 | 5.39 | 26.82 |
| Swartkops S1S1 | 2019/11/04 | S1 | 0.75 | 3.01 | 0.96 | 0.16 | 1.57 |
| Swartkops S1S2 | 2019/11/04 | S1 | 0.75 | 2.78 | 1.04 | 0.13 | 1.50 |
| Swartkops S1S3 | 2019/11/04 | S1 | 0.81 | 3.13 | 1.26 | 0.19 | 1.31 |
| Swartkops S1M1 | 2019/11/04 | M1 | 0.79 | 2.85 | 0.97 | 0.15 | 1.99 |
| Swartkops S1M2 | 2019/11/04 | M1 | 0.75 | 2.89 | 1.14 | 0.17 | 1.43 |
| Swartkops S1M3 | 2019/11/04 | M1 | 0.75 | 4.49 | 1.12 | 0.16 | 1.13 |
| Swartkops S1B1 | 2019/11/04 | B1 | 0.80 | 3.73 | 1.12 | 0.19 | 1.79 |
| Swartkops S1B2 | 2019/11/04 | B1 | 0.74 | 3.06 | 1.06 | 0.17 | 1.36 |
| Swartkops S1B3 | 2019/11/04 | B1 | 0.83 | 3.19 | 1.16 | 0.19 | 1.80 |
| Swartkops S6S1 | 2019/11/04 | S6 | 93.06 | 35.00 | 16.07 | 7.19 | 3.75 |
| Swartkops S6S2 | 2019/11/04 | S6 | 94.15 | 35.01 | 15.33 | 7.49 | 0.90 |
| Swartkops S6S3 | 2019/11/04 | S6 | 75.91 | 34.41 | 12.10 | 5.92 | 1.54 |
| Swartkops S1S1 | 2020/02/04 | S1 | 0.70 | 2.42 | 1.92 | 0.68 | 1.52 |
| Swartkops S1S2 | 2020/02/04 | S1 | 0.77 | 2.14 | 2.15 | 0.74 | 1.29 |
| Swartkops S1S3 | 2020/02/04 | S1 | 0.79 | 1.71 | 1.90 | 0.67 | 1.51 |
| Swartkops S1M1 | 2020/02/04 | M1 | 0.70 | 1.59 | 1.81 | 0.63 | 1.20 |
| Swartkops S1M2 | 2020/02/04 | M1 | 0.70 | 1.56 | 1.87 | 0.63 | 1.33 |
| Swartkops S1M3 | 2020/02/04 | M1 | 0.72 | 1.20 | 2.01 | 0.66 | 1.31 |
| Swartkops S1B1 | 2020/02/04 | B1 | 0.67 | 1.10 | 1.60 | 0.59 | 0.97 |
| Swartkops S1B2 | 2020/02/04 | B1 | 0.65 | 1.21 | 1.73 | 0.63 | 0.98 |
| Swartkops S1B3 | 2020/02/04 | B1 | 0.68 | 1.35 | 1.80 | 0.64 | 1.03 |
| Swartkops S6S1 | 2020/02/04 | S6 | 73.85 | 35.62 | 59.50 | 25.51 | 8.46 |
| Swartkops S6S2 | 2020/02/04 | S6 | 74.33 | 42.75 | 72.14 | 26.36 | 11.44 |
| Swartkops S6S3 | 2020/02/04 | S6 | 86.07 | 43.18 | 73.95 | 25.73 | 11.52 |
| Swartkops S1S1 | 2020/06/05 | S1 | 7.86 | 23.04 | 10.42 | 1.91 | 9.05 |
| Swartkops S1S2 | 2020/06/05 | S1 | 7.90 | 23.09 | 10.39 | 1.91 | 9.35 |
| Swartkops S1S3 | 2020/06/05 | S1 | 7.96 | 23.23 | 10.53 | 1.97 | 9.79 |
| Swartkops S1M1 | 2020/06/05 | M1 | 7.77 | 22.38 | 9.96 | 1.76 | 8.59 |
| Swartkops S1M2 | 2020/06/05 | M1 | 7.84 | 22.48 | 10.05 | 1.78 | 8.18 |
| Swartkops S1M3 | 2020/06/05 | M1 | 7.92 | 22.50 | 10.12 | 1.80 | 8.21 |
| Swartkops S1B1 | 2020/06/05 | B1 | 7.71 | 21.87 | 10.21 | 1.92 | 9.17 |
| Swartkops S1B2 | 2020/06/05 | B1 | 7.75 | 21.77 | 10.03 | 1.91 | 7.75 |
| Swartkops S1B3 | 2020/06/05 | B1 | 7.52 | 21.77 | 9.93 | 1.89 | 8.21 |
| Swartkops S6S1 | 2020/06/05 | S6 | 71.01 | 147.94 | 61.19 | 24.02 | 61.87 |
| Swartkops S6S2 | 2020/06/05 | S6 | 69.72 | 148.96 | 60.51 | 23.29 | 62.50 |
| Swartkops S6S3 | 2020/06/05 | S6 | 70.47 | 148.87 | 59.75 | 23.68 | 61.13 |
| Swartkops S1S1 | 2020/06/25 | S1 | 1.57 | 7.52 | 4.54 | 0.65 | 2.30 |
| Swartkops S1S2 | 2020/06/25 | S1 | 1.51 | 7.85 | 4.26 | 0.60 | 1.19 |
| Swartkops S1S3 | 2020/06/25 | S1 | 1.56 | 7.52 | 4.39 | 0.62 | 2.24 |
| Swartkops S1M1 | 2020/06/25 | M1 | 1.55 | 7.65 | 4.06 | 0.56 | 1.52 |
| Swartkops S1M2 | 2020/06/25 | M1 | 1.52 | 7.80 | 4.16 | 0.58 | 3.19 |
| Swartkops S1M3 | 2020/06/25 | M1 | 1.54 | 7.93 | 4.46 | 0.60 | 2.37 |
| Swartkops S1B1 | 2020/06/25 | B1 | 1.46 | 8.20 | 4.23 | 0.59 | 1.11 |
| Swartkops S1B2 | 2020/06/25 | B1 | 1.42 | 7.84 | 4.27 | 0.60 | 1.43 |
| Swartkops S1B3 | 2020/06/25 | B1 | 1.38 | 7.83 | 4.31 | 0.59 | 1.19 |
| Swartkops S6S1 | 2020/06/25 | S6 | 63.09 | 128.08 | 65.68 | 23.89 | 60.61 |
| Swartkops S6S2 | 2020/06/25 | S6 | 62.90 | 129.02 | 64.91 | 23.92 | 61.18 |
| Swartkops S6S3 | 2020/06/25 | S6 | 62.36 | 129.30 | 67.17 | 24.00 | 56.54 |
| Swartkops S1S1 | 2020/09/22 | S1 | 0.97 | 6.19 | 4.30 | 0.68 | 2.88 |
| Swartkops S1S2 | 2020/09/22 | S1 | 1.03 | 6.61 | 4.63 | 0.71 | 2.96 |
| Swartkops S1S3 | 2020/09/22 | S1 | 1.04 | 6.52 | 4.66 | 0.70 | 2.92 |
| Swartkops S1M1 | 2020/09/22 | M1 | 1.00 | 6.31 | 4.49 | 0.65 | 2.82 |
| Swartkops S1M2 | 2020/09/22 | M1 | 1.01 | 6.50 | 4.64 | 0.67 | 3.03 |
| Swartkops S1M3 | 2020/09/22 | M1 | 1.09 | 7.13 | 5.10 | 0.74 | 2.91 |
| Swartkops S1B1 | 2020/09/22 | B1 | 1.00 | 7.56 | 4.59 | 0.64 | 3.40 |
| Swartkops S1B2 | 2020/09/22 | B1 | 1.04 | 6.50 | 4.39 | 0.64 | 2.99 |
| Swartkops S1B3 | 2020/09/22 | B1 | 1.03 | 6.30 | 4.31 | 0.65 | 3.01 |
| Swartkops S6S1 | 2020/09/22 | S6 | 78.43 | 28.64 | 136.74 | 24.98 | 73.34 |
| Swartkops S6S2 | 2020/09/22 | S6 | 81.35 | 28.53 | 136.54 | 24.51 | 78.93 |
| Swartkops S6S3 | 2020/09/22 | S6 | 77.49 | 28.67 | 126.92 | 24.01 | 77.94 |
| Swartkops S1S1 | 2020/11/12 | S1 | 4.17 | 10.64 | 3.29 | 0.32 | 0.66 |
| Swartkops S1S2 | 2020/11/12 | S1 | 4.45 | 11.11 | 3.51 | 0.34 | 0.79 |
| Swartkops S1S3 | 2020/11/12 | S1 | 4.44 | 10.27 | 2.62 | 0.36 | 0.16 |
| Swartkops S1M1 | 2020/11/12 | M1 | 3.77 | 8.92 | 2.02 | 0.25 | 0.30 |
| Swartkops S1M2 | 2020/11/12 | M1 | 3.87 | 12.04 | 3.16 | 0.27 | 0.88 |
| Swartkops S1M3 | 2020/11/12 | M1 | 3.82 | 8.72 | 1.87 | 0.22 | 0.30 |
| Swartkops S1B1 | 2020/11/12 | B1 | 4.37 | 10.19 | 2.26 | 0.29 | 0.38 |
| Swartkops S1B2 | 2020/11/12 | B1 | 4.86 | 11.97 | 2.78 | 0.34 | 0.50 |
| Swartkops S1B3 | 2020/11/12 | B1 | 4.88 | 11.89 | 2.70 | 0.34 | 0.46 |
| Swartkops S6S1 | 2020/11/12 | S6 | 62.00 | 59.35 | 68.13 | 23.83 | 98.75 |
| Swartkops S6S2 | 2020/11/12 | S6 | 62.35 | 59.51 | 67.11 | 23.48 | 95.79 |
| Swartkops S6S3 | 2020/11/12 | S6 | 61.80 | 58.70 | 66.51 | 23.26 | 97.04 |
| Swartkops S1S1 | 2021/01/26 | S1 | 10.46 | 24.83 | −0.45 | 0.24 | 1.16 |
| Swartkops S1S2 | 2021/01/26 | S1 | 10.49 | 24.43 | −0.22 | 0.20 | 1.14 |
| Swartkops S1S3 | 2021/01/26 | S1 | 10.69 | 24.60 | −0.61 | 0.16 | 0.94 |
| Swartkops S1M1 | 2021/01/26 | M1 | 10.58 | 25.67 | 0.99 | 0.19 | 0.74 |
| Swartkops S1M2 | 2021/01/26 | M1 | 10.86 | 25.46 | 0.91 | 0.18 | 1.13 |
| Swartkops S1M3 | 2021/01/26 | M1 | 10.39 | 24.21 | 0.75 | 0.16 | 0.78 |
| Swartkops S1B1 | 2021/01/26 | B1 | 10.22 | 26.76 | −0.55 | 0.15 | 0.94 |
| Swartkops S1B2 | 2021/01/26 | B1 | 10.30 | 23.44 | −0.63 | 0.13 | 0.94 |
| Swartkops S1B3 | 2021/01/26 | B1 | 10.12 | 23.91 | −0.76 | 0.14 | 1.14 |
| Swartkops S6S1 | 2021/01/26 | S6 | 94.69 | 130.09 | 41.99 | 18.84 | 196.84 |
| Swartkops S6S2 | 2021/01/26 | S6 | 95.97 | 123.32 | 37.17 | 17.68 | 198.14 |
| Swartkops S6S3 | 2021/01/26 | S6 | 98.47 | 123.84 | 33.71 | 16.19 | 195.07 |
| Sunday’s S1S1 | 2021/03/26 | S1 | 1.58 | 98.92 | 3.31 | 0.30 | 2.88 |
| Sunday’s S1S2 | 2021/03/26 | S1 | 1.10 | 77.62 | 3.57 | 0.27 | 1.65 |
| Sunday’s S1S3 | 2021/03/26 | S1 | 1.74 | 75.95 | 4.06 | 0.29 | 1.77 |
| Sunday’s S1B1 | 2021/03/26 | B1 | 1.56 | 73.21 | 4.46 | 0.31 | 1.34 |
| Sunday’s S1B2 | 2021/03/26 | B1 | 1.48 | 77.12 | 3.30 | 0.22 | 0.95 |
| Sunday’s S1B3 | 2021/03/26 | B1 | 1.29 | 71.28 | 3.07 | 0.31 | 1.30 |
| Sunday’s S6S1 | 2021/03/26 | S6 | 3.68 | 127.53 | 22.48 | 0.58 | 1.05 |
| Sunday’s S6S2 | 2021/03/26 | S6 | 3.76 | 154.67 | 32.82 | 0.65 | 1.23 |
| Sunday’s S6S3 | 2021/03/26 | S6 | 4.08 | 224.58 | 35.31 | 0.73 | 1.24 |
| Sunday’s S6B1 | 2021/03/26 | B6 | 3.96 | 289.23 | 31.69 | 1.07 | 1.97 |
| Sunday’s S6B2 | 2021/03/26 | B6 | 3.28 | 261.72 | 16.88 | 0.53 | 0.96 |
| Sunday’s S6B3 | 2021/03/26 | B6 | 4.08 | 284.38 | 29.21 | 0.73 | 1.36 |
| Swartkops S1S1 | 2021/05/07 | S1 | 5.40 | 17.41 | 5.02 | 1.06 | 4.30 |
| Swartkops S1S2 | 2021/05/07 | S1 | 4.67 | 14.13 | 4.48 | 0.85 | 3.85 |
| Swartkops S1S3 | 2021/05/07 | S1 | 5.88 | 18.60 | 5.68 | 1.11 | 4.58 |
| Swartkops S1M1 | 2021/05/07 | M1 | 8.47 | 27.05 | 7.87 | 1.51 | 6.01 |
| Swartkops S1M2 | 2021/05/07 | M1 | 9.12 | 29.64 | 8.59 | 1.63 | 6.46 |
| Swartkops S1M3 | 2021/05/07 | M1 | 10.36 | 34.06 | 9.60 | 1.83 | 7.14 |
| Swartkops S1B1 | 2021/05/07 | B1 | 2.49 | 8.54 | 2.75 | 0.46 | 2.55 |
| Swartkops S1B2 | 2021/05/07 | B1 | 2.18 | 5.84 | 2.38 | 0.41 | 2.26 |
| Swartkops S1B3 | 2021/05/07 | B1 | 2.63 | 6.84 | 2.82 | 0.48 | 2.58 |
| Swartkops S6S1 | 2021/05/07 | S6 | 117.97 | 208.28 | 26.09 | 20.65 | 93.93 |
| Swartkops S6S2 | 2021/05/07 | S6 | 118.27 | 223.37 | 19.95 | 17.11 | 91.92 |
| Swartkops S6S3 | 2021/05/07 | S6 | 116.87 | 213.69 | 24.09 | 19.86 | 91.63 |
| Sunday’s S1S1 | 2021/06/10 | S1 | 0.65 | 34.22 | 2.64 | 0.27 | 1.54 |
| Sunday’s S1S2 | 2021/06/10 | S1 | 1.07 | 66.19 | 4.27 | 0.45 | 1.12 |
| Sunday’s S1S3 | 2021/06/10 | S1 | 1.02 | 58.42 | 3.74 | 0.37 | 1.58 |
| Sunday’s S1B1 | 2021/06/10 | B1 | 0.87 | 43.62 | 3.37 | 0.33 | 1.46 |
| Sunday’s S1B2 | 2021/06/10 | B1 | 0.77 | 34.79 | 2.74 | 0.26 | 1.30 |
| Sunday’s S1B3 | 2021/06/10 | B1 | 0.97 | 61.01 | 3.90 | 0.41 | 1.38 |
| Sunday’s S6S1 | 2021/06/10 | S6 | 2.53 | 219.99 | 27.02 | 0.33 | 0.99 |
| Sunday’s S6S2 | 2021/06/10 | S6 | 2.33 | 183.35 | 24.30 | 0.28 | 1.16 |
| Sunday’s S6S3 | 2021/06/10 | S6 | 2.01 | 158.78 | 24.39 | 0.30 | 1.07 |
| Sunday’s S6B1 | 2021/06/10 | B6 | 2.59 | 221.48 | 24.29 | 0.31 | 1.02 |
| Sunday’s S6B2 | 2021/06/10 | B6 | 2.38 | 210.05 | 19.06 | 0.26 | 1.04 |
| Sunday’s S6B3 | 2021/06/10 | B6 | 2.43 | 226.63 | 18.97 | 0.26 | 1.22 |
| Swartkops S1S1 | 2021/07/12 | S1 | 1.18 | 4.63 | 2.05 | 0.37 | 3.88 |
| Swartkops S1S2 | 2021/07/12 | S1 | 1.23 | 4.84 | 2.49 | 0.32 | 3.58 |
| Swartkops S1S3 | 2021/07/12 | S1 | 1.28 | 4.91 | 2.88 | 0.33 | 3.92 |
| Swartkops S1M1 | 2021/07/12 | M1 | 1.37 | 5.35 | 2.92 | 0.33 | 3.02 |
| Swartkops S1M2 | 2021/07/12 | M1 | 1.34 | 4.97 | 3.17 | 0.32 | 3.49 |
| Swartkops S1M3 | 2021/07/12 | M1 | 1.16 | 4.39 | 2.46 | 0.27 | 2.87 |
| Swartkops S1B1 | 2021/07/12 | B1 | 0.90 | 2.82 | 1.58 | 0.17 | 2.31 |
| Swartkops S1B2 | 2021/07/12 | B1 | 1.22 | 5.06 | 2.43 | 0.30 | 3.00 |
| Swartkops S1B3 | 2021/07/12 | B1 | 1.48 | 5.50 | 3.52 | 0.36 | 4.23 |
| Swartkops S6S1 | 2021/07/12 | S6 | 102.28 | 151.85 | 102.21 | 30.28 | 61.79 |
| Swartkops S6S2 | 2021/07/12 | S6 | 101.26 | 124.84 | 92.49 | 27.97 | 60.26 |
| Swartkops S6S3 | 2021/07/12 | S6 | 105.42 | 165.33 | 94.12 | 29.73 | 62.07 |
| Sunday’s S1S1 | 2021/09/28 | S1 | 0.40 | 8.49 | 0.24 | 0.08 | 0.79 |
| Sunday’s S1S2 | 2021/09/28 | S1 | 0.46 | 22.72 | 0.26 | 0.07 | 0.66 |
| Sunday’s S1S3 | 2021/09/28 | S1 | 0.32 | 10.00 | 0.17 | 0.05 | 0.48 |
| Sunday’s S1B1 | 2021/09/28 | B1 | 0.28 | 4.57 | 0.11 | 0.05 | 0.30 |
| Sunday’s S1B2 | 2021/09/28 | B1 | 0.28 | 5.43 | 0.17 | 0.05 | 0.30 |
| Sunday’s S1B3 | 2021/09/28 | B1 | 0.25 | 4.64 | 0.03 | 0.03 | 0.52 |
| Sunday’s S6S1 | 2021/09/28 | S6 | 2.78 | 132.82 | 15.82 | 0.22 | 1.72 |
| Sunday’s S6S2 | 2021/09/28 | S6 | 2.87 | 132.05 | 15.86 | 0.47 | 2.38 |
| Sunday’s S6S3 | 2021/09/28 | S6 | 2.82 | 134.16 | 15.41 | 0.49 | 1.85 |
| Sunday’s S6B1 | 2021/09/28 | B6 | 2.86 | 132.48 | 15.12 | 0.51 | 1.91 |
| Sunday’s S6B2 | 2021/09/28 | B6 | 2.84 | 137.34 | 14.88 | 0.50 | 1.97 |
| Sunday’s S6B3 | 2021/09/28 | B6 | 2.81 | 132.50 | 14.79 | 0.50 | 1.95 |
| Swartkops S1S1 | 2021/10/20 | S1 | 3.52 | 2.65 | 0.42 | 0.23 | 2.55 |
| Swartkops S1S2 | 2021/10/20 | S1 | 4.62 | 6.49 | 0.90 | 0.28 | 2.33 |
| Swartkops S1S3 | 2021/10/20 | S1 | 3.66 | 2.88 | 0.36 | 0.09 | 2.21 |
| Swartkops S1M1 | 2021/10/20 | M1 | 4.15 | 4.80 | 0.67 | 0.16 | 1.80 |
| Swartkops S1M2 | 2021/10/20 | M1 | 4.67 | 5.88 | 0.92 | 0.29 | 2.65 |
| Swartkops S1M3 | 2021/10/20 | M1 | 4.55 | 6.20 | 1.11 | 0.26 | 2.66 |
| Swartkops S1B1 | 2021/10/20 | B1 | 4.80 | 6.70 | 0.67 | 0.20 | 1.83 |
| Swartkops S1B2 | 2021/10/20 | B1 | 4.98 | 7.05 | 0.75 | 0.23 | 1.95 |
| Swartkops S1B3 | 2021/10/20 | B1 | 4.13 | 4.00 | 0.45 | 0.11 | 1.83 |
| Swartkops S6S1 | 2021/10/20 | S6 | 126.35 | 121.31 | 88.16 | 40.80 | 107.97 |
| Swartkops S6S2 | 2021/10/20 | S6 | 131.09 | 91.53 | 73.90 | 34.83 | 95.39 |
| Swartkops S6S3 | 2021/10/20 | S6 | 135.23 | 124.38 | 80.91 | 39.08 | 107.69 |
| Swartkops S1S1 | 2022/01/27 | S1 | 0.37 | 3.77 | 0.24 | 0.27 | 8.95 |
| Swartkops S1S2 | 2022/01/27 | S1 | 0.25 | 3.63 | −0.07 | 0.16 | 13.60 |
| Swartkops S1S3 | 2022/01/27 | S1 | 0.18 | 0.68 | −0.19 | 0.14 | 4.31 |
| Swartkops S1M1 | 2022/01/27 | M1 | 0.27 | 2.58 | −0.44 | 0.10 | 3.49 |
| Swartkops S1M2 | 2022/01/27 | M1 | 0.85 | 5.31 | −0.48 | 0.21 | 35.79 |
| Swartkops S1M3 | 2022/01/27 | M1 | 0.73 | 5.07 | −0.17 | 0.18 | 24.13 |
| Swartkops S1B1 | 2022/01/27 | B1 | 0.29 | 1.32 | −0.67 | 0.07 | 3.41 |
| Swartkops S1B2 | 2022/01/27 | B1 | 0.84 | 3.50 | −0.65 | 0.12 | 10.90 |
| Swartkops S1B3 | 2022/01/27 | B1 | 0.56 | 2.91 | −0.39 | 0.11 | 5.78 |
| Swartkops S6S1 | 2022/01/27 | S6 | 85.71 | 118.59 | 44.45 | 13.66 | 152.02 |
| Swartkops S6S2 | 2022/01/27 | S6 | 92.12 | 96.86 | 68.65 | 14.00 | 151.57 |
| Swartkops S6S3 | 2022/01/27 | S6 | 84.95 | 105.04 | 73.57 | 12.81 | 156.09 |
| Sunday’s S1S1 | 2022/03/16 | S1 | 45.74 | 0.87 | 0.22 | 9.20 | |
| Sunday’s S1S2 | 2022/03/16 | S1 | 34.76 | 0.21 | 0.08 | 3.03 | |
| Sunday’s S1S3 | 2022/03/16 | S1 | 43.73 | 0.29 | 0.12 | 3.96 | |
| Sunday’s S1B1 | 2022/03/16 | B1 | 36.67 | 0.18 | 0.11 | 3.01 | |
| Sunday’s S1B2 | 2022/03/16 | B1 | 42.72 | 0.29 | 0.14 | 4.20 | |
| Sunday’s S1B3 | 2022/03/16 | B1 | 47.83 | 0.29 | 0.14 | 5.60 | |
| Sunday’s S6S1 | 2022/03/16 | S6 | 115.06 | 2.57 | 0.27 | 2.33 | |
| Sunday’s S6S2 | 2022/03/16 | S6 | 82.71 | 2.83 | 0.36 | 3.20 | |
| Sunday’s S6S3 | 2022/03/16 | S6 | 94.56 | 2.22 | 0.22 | 2.02 | |
| Sunday’s S6B1 | 2022/03/16 | B6 | 93.82 | 2.42 | 0.25 | 1.69 | |
| Sunday’s S6B2 | 2022/03/16 | B6 | 75.49 | 0.85 | 0.12 | 1.65 | |
| Sunday’s S6B3 | 2022/03/16 | B6 | 160.25 | 3.49 | 0.32 | 1.80 | |
| Swartkops S1S1 | 2022/05/05 | S1 | 0.56 | 7.63 | −0.33 | 0.11 | 1.28 |
| Swartkops S1S2 | 2022/05/05 | S1 | 0.38 | 13.38 | 0.14 | 0.12 | 0.24 |
| Swartkops S1S3 | 2022/05/05 | S1 | 0.59 | 13.45 | −1.02 | 0.01 | -0.43 |
| Swartkops S1M1 | 2022/05/05 | M1 | 0.54 | 6.17 | −0.88 | 0.11 | 0.82 |
| Swartkops S1M2 | 2022/05/05 | M1 | 0.17 | 5.49 | 0.24 | 0.18 | 4.09 |
| Swartkops S1M3 | 2022/05/05 | M1 | 0.02 | 3.45 | −0.72 | -0.15 | -0.37 |
| Swartkops S6S1 | 2022/05/05 | S6 | 100.65 | 190.21 | 62.12 | 48.74 | 136.77 |
| Swartkops S6S2 | 2022/05/05 | S6 | 101.22 | 192.12 | 65.34 | 50.58 | 141.13 |
| Swartkops S6S3 | 2022/05/05 | S6 | 102.68 | 189.87 | 63.56 | 49.03 | 140.10 |
| Sunday’s S1S1 | 2022/06/22 | S1 | 2.65 | 119.31 | 1.49 | 0.36 | 2.75 |
| Sunday’s S1S2 | 2022/06/22 | S1 | 3.12 | 147.11 | 1.83 | 0.46 | 2.90 |
| Sunday’s S1S3 | 2022/06/22 | S1 | 2.22 | 92.16 | 1.20 | 0.24 | 1.89 |
| Sunday’s S1B1 | 2022/06/22 | B1 | 2.56 | 103.39 | 1.39 | 0.28 | 2.17 |
| Sunday’s S1B2 | 2022/06/22 | B1 | 2.95 | 124.36 | 2.95 | 0.44 | 2.89 |
| Sunday’s S1B3 | 2022/06/22 | B1 | 2.99 | 128.60 | 2.94 | 0.45 | 2.82 |
| Sunday’s S6S1 | 2022/06/22 | S6 | 2.76 | 273.49 | 3.98 | 0.33 | 0.90 |
| Sunday’s S6S2 | 2022/06/22 | S6 | 3.22 | 267.05 | 3.87 | 0.32 | 0.92 |
| Sunday’s S6S3 | 2022/06/22 | S6 | 2.90 | 275.85 | 4.20 | 0.39 | 0.88 |
| Sunday’s S6B1 | 2022/06/22 | B6 | 3.01 | 271.77 | 3.75 | 0.34 | 0.88 |
| Sunday’s S6B2 | 2022/06/22 | B6 | 3.18 | 266.07 | 4.06 | 0.40 | 0.92 |
| Sunday’s S6B3 | 2022/06/22 | B6 | 3.09 | 272.63 | 4.63 | 0.41 | 0.98 |
| Swartkops S1S1 | 2022/07/15 | S1 | 5.14 | 16.38 | 23.80 | 1.73 | 6.13 |
| Swartkops S1S2 | 2022/07/15 | S1 | 2.36 | 13.49 | 2.01 | 1.05 | 6.73 |
| Swartkops S1S3 | 2022/07/15 | S1 | 2.75 | 11.13 | 1.90 | 1.10 | 5.11 |
| Swartkops S1M1 | 2022/07/15 | M1 | 3.16 | 12.77 | 2.13 | 1.34 | 6.15 |
| Swartkops S1M2 | 2022/07/15 | M1 | 2.28 | 14.35 | 2.39 | 1.37 | 4.32 |
| Swartkops S1M3 | 2022/07/15 | M1 | 2.36 | 11.43 | 1.76 | 1.06 | 4.74 |
| Swartkops S6S1 | 2022/07/15 | S6 | 113.70 | 173.14 | 92.04 | 56.40 | 134.94 |
| Swartkops S6S2 | 2022/07/15 | S6 | 112.81 | 192.17 | 112.56 | 56.34 | 143.43 |
| Swartkops S6S3 | 2022/07/15 | S6 | 119.07 | 171.56 | 113.49 | 58.06 | 147.76 |
| Sunday’s S1S1 | 2022/09/19 | S1 | 21.95 | 0.62 | 0.21 | 3.87 | |
| Sunday’s S1S2 | 2022/09/19 | S1 | 22.06 | 0.57 | 0.18 | 2.84 | |
| Sunday’s S1S3 | 2022/09/19 | S1 | 42.22 | 1.68 | 0.57 | 7.84 | |
| Sunday’s S1B1 | 2022/09/19 | B1 | 16.36 | 0.68 | 0.20 | 3.22 | |
| Sunday’s S1B2 | 2022/09/19 | B1 | 16.06 | 0.65 | 0.21 | 4.02 | |
| Sunday’s S1B3 | 2022/09/19 | B1 | 21.63 | 1.02 | 0.34 | 6.62 | |
| Sunday’s S6S1 | 2022/09/19 | S6 | 152.80 | 8.12 | 0.86 | 3.09 | |
| Sunday’s S6S2 | 2022/09/19 | S6 | 168.35 | 7.69 | 0.74 | 3.19 | |
| Sunday’s S6S3 | 2022/09/19 | S6 | 180.79 | 7.89 | 0.72 | 3.14 | |
| Sunday’s S6B1 | 2022/09/19 | B6 | 165.66 | 7.06 | 0.77 | 3.37 | |
| Sunday’s S6B2 | 2022/09/19 | B6 | 85.24 | 4.81 | 0.96 | 4.85 | |
| Sunday’s S6B3 | 2022/09/19 | B6 | 168.24 | 5.69 | 0.58 | 2.67 | |
| Swartkops S1S1 | 2023/06/07 | S1 | 1.68 | 8.31 | 5.26 | 0.89 | 13.45 |
| Swartkops S1S2 | 2023/06/07 | S1 | 1.79 | 7.54 | 7.06 | 0.78 | 8.67 |
| Swartkops S1S3 | 2023/06/07 | S1 | 1.66 | 6.52 | 5.49 | 0.70 | 7.29 |
| Swartkops S1B1 | 2023/06/07 | B1 | 1.67 | 7.91 | 7.24 | 0.87 | 20.41 |
| Swartkops S1B2 | 2023/06/07 | B1 | 1.48 | 6.90 | 6.62 | 0.79 | 8.98 |
| Swartkops S1B3 | 2023/06/07 | B1 | 1.42 | 6.60 | 6.53 | 0.76 | 8.66 |
| Swartkops S6S1 | 2023/06/07 | S6 | 30.85 | 126.55 | 69.22 | 22.62 | 164.55 |
| Swartkops S6S2 | 2023/06/07 | S6 | 26.25 | 105.49 | 56.27 | 18.19 | 149.43 |
| Swartkops S6S3 | 2023/06/07 | S6 | 39.58 | 135.82 | 65.38 | 21.70 | 165.06 |
| Swartkops S1S1 | 2023/08/01 | S1 | 7.69 | 25.66 | 22.52 | 4.53 | 15.11 |
| Swartkops S1S2 | 2023/08/01 | S1 | 8.26 | 28.62 | 22.25 | 4.15 | 13.92 |
| Swartkops S1S3 | 2023/08/01 | S1 | 7.46 | 26.23 | 25.39 | 4.59 | 14.75 |
| Swartkops S1B1 | 2023/08/01 | B1 | 7.63 | 27.18 | 26.28 | 4.72 | 15.56 |
| Swartkops S1B2 | 2023/08/01 | B1 | 9.08 | 32.78 | 33.67 | 6.05 | 19.83 |
| Swartkops S1B3 | 2023/08/01 | B1 | 8.77 | 26.50 | 29.32 | 5.01 | 16.31 |
| Swartkops S6S1 | 2023/08/01 | S6 | 11.36 | 107.70 | 48.70 | 10.62 | 35.17 |
| Swartkops S6S2 | 2023/08/01 | S6 | 11.41 | 105.50 | 46.88 | 10.30 | 34.62 |
| Swartkops S6S3 | 2023/08/01 | S6 | 11.33 | 105.22 | 48.37 | 10.69 | 34.72 |
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| Year | 2000 | 2005 | 2010 | 2015 | 2019 |
|---|---|---|---|---|---|
| Total revenue | - | 824,270 | 1,129,550 | 1,391,124 | 1,623,039 |
| Total expenditure | - | 843,543 | 1,238,408 | 1,431,320 | 1,621,015 |
| Difference | - | −19,273 | −108,858 | −40,196 | 2024 |
| Ecosystem Service | Valuation Method | Onshore | Coastal System | Offshore | Coral Reefs | Estuaries | |
|---|---|---|---|---|---|---|---|
| Provisioning | Right of access (human habitat) | SP | L and G | L and G | L and G | L and G | |
| Food provisioning (non-cultivated) | MP | L and G | L and G | L and G | |||
| Food and raw materials (cultivated) | MP | L and G | |||||
| Regulating | Waste dilution | RC | L and G | ||||
| Air quality regulation | BT | L and G | L and G | ||||
| Climate regulation | BT | L and G | L and G | L and G | |||
| Moderation of extreme events | BT | L and G | L and G | ||||
| Erosion prevention | BT | L and G | L and G | ||||
| Nutrient cycling | BT | L and G | |||||
| Water quality | BT | L and G | |||||
| Supporting | Maintenance and protection of nursery and gene pool and life cycle | BT | G** | G** | |||
| Cultural | Amenity value | PV | L and G | L and G | |||
| Recreation and tourism | MP | L and G* | L and G* | L and G* | L and G* | L and G* | |
| Spiritual, cognitive and other | BT | L and G | L and G | L and G | L and G | ||
| Existence and bequest | BT | G** | G** | G** |
| Year | Conservative | Alternative | ||
|---|---|---|---|---|
| Local | Global | Local | Global | |
| 2000 | 613.4 | 1127.3 | 724.7 | 1848.4 |
| 2005 | 805.7 | 1454.0 | 923.3 | 2203.8 |
| 2010 | 1257.3 | 2073.0 | 1386.3 | 2892.7 |
| 2015 | 1037.1 | 1932.3 | 1180.6 | 2796.6 |
| 2019 | 1695.9 | 2787.9 | 1859.1 | 3761.2 |
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Share and Cite
Orolowitz, M.; Blignaut, J.; Lourens, C.; Bentley, M.; Twekye, T.; Rees, P.; Miltz, E.; Peacock, R.; Snow, B.; Lombard, A.T. An Estimate of the Economic Value of the Marine and Coastal Ecosystem Services of Algoa Bay, South Africa. Sustainability 2025, 17, 11055. https://doi.org/10.3390/su172411055
Orolowitz M, Blignaut J, Lourens C, Bentley M, Twekye T, Rees P, Miltz E, Peacock R, Snow B, Lombard AT. An Estimate of the Economic Value of the Marine and Coastal Ecosystem Services of Algoa Bay, South Africa. Sustainability. 2025; 17(24):11055. https://doi.org/10.3390/su172411055
Chicago/Turabian StyleOrolowitz, Matthew, James Blignaut, Chase Lourens, Matthew Bentley, Twesigye Twekye, Pablo Rees, Estee Miltz, Rozanne Peacock, Bernadette Snow, and Amanda T. Lombard. 2025. "An Estimate of the Economic Value of the Marine and Coastal Ecosystem Services of Algoa Bay, South Africa" Sustainability 17, no. 24: 11055. https://doi.org/10.3390/su172411055
APA StyleOrolowitz, M., Blignaut, J., Lourens, C., Bentley, M., Twekye, T., Rees, P., Miltz, E., Peacock, R., Snow, B., & Lombard, A. T. (2025). An Estimate of the Economic Value of the Marine and Coastal Ecosystem Services of Algoa Bay, South Africa. Sustainability, 17(24), 11055. https://doi.org/10.3390/su172411055

