Aspects of the ecology of the estuarine round-herring Gilchristella aestuaria (Pisces: Clupeidae) and its small-scale fishery potential
- Zvavahera, Munetsi https://orcid.org/0000-0002-5337-1943
- Authors: Zvavahera, Munetsi https://orcid.org/0000-0002-5337-1943
- Date: 2021-05
- Subjects: Small-scale fisheries , Silversides
- Language: English
- Type: Doctoral theses , text
- Identifier: http://hdl.handle.net/10353/22765 , vital:52752
- Description: In the past two decades, there has been increasing pressure for small-scale inland fisheries to play a central role in food and nutrient security for poor communities in South Africa. For decades, South African inland fisheries have focussed on the exploitation of large fish species and generally ignored the exploitation of inland small fish species (SFS). This research aimed to assess the ecology and small-scale fishery potential of the estuarine round-herring, Gilchristella aestuaria. To understand the ecology of G. aestuaria better, morphometric trait analysis and fish condition of populations in relation to environmental variables (salinity, pH, temperature, turbidity and chlorophyll-a) were done. Fish were supplemented with samples acquired from the SAIAB collection facility for 14 sites to cover all the three South African biogeographic regions, stretching from Lake Sibaya (KZN) to the Orange River estuary in the western parts of the country. The morphometric trait analysis showed that G. aestuaria populations can be distinguished based on the trait variation, however there were many overlaps for populations that are interconnected, with distant/ geographically separated populations showing clear differences. Morphometric traits of the G. aestuaria population were significantly different, however there was no strong directional relationship with environmental variables and variation in morphometric traits. However, fish condition as measured by Fulton’s condition (K) and relative weight (Wr) showed variation between populations found in different environments. These differences suggest that these populations must be managed differently if G. aestuaria is to be exploited in managed fisheries. To determine the potential nutrient value of G. aestuaria to the human diet, samples from two freshwater sites and five estuarine sites were analysed for essential macro and micronutrients. The nutrient content of G. aestuaria revealed there is potential for exploitation, as the species has a high macro (protein and fat) and micronutrient composition (calcium, iron and zinc). Mean ± SD of selected nutrients were protein (61.7±5.0 g/100g), fat (20.4±3.7g/ 100g), calcium (3507.5±314.0mg), iron (40.37±14.0mg/ 100g), zinc (22.47±5.6mg/ 100) and vitamin A (37.3±44.4 RAE/ 100g). The nutrient composition of fish collected from freshwater sites was comparable to those collected from estuarine environments. Using the recommended dietary allowances (RDA) from literature, the mass of fish and the number of fish that would provide a minimum amount for each nutrient were calculated. A child would require only 13.4g of dry G. aestuaria or approximately 74 dried fish to meet the daily requirements of zinc. Other minerals such as iron and calcium also showed a similar low weight or number of fish required to meet daily requirements for the different categories. A small number of G. aestuaria are needed to meet RDA for groups (children, adult men, adult women, pregnant women and lactating mothers). A comparison was done for the nutrient composition of G. aestuaria with reference species that are already harvested for human consumption in some African and Asian countries. The protein content of G. aestuaria was comparable to Chisense (Microthrissa moeruensis) and Kapenta Limnothrissa miodon), while the fat composition was more than twice Chisense and Kapenta. Comparing the mineral composition, G. aestuaria had more than three times higher calcium than Mola (Amblypharyngodon mola) and Puti (Puntius sophore). Zinc composition was four times higher than M. moeruensis and L. miodon. Further exploration of the ecology of G. aestuaria was studied using the Sundays River irrigations ponds as a case study that would represent small impoundments across South Africa. Species rank abundance curve and catch per unit effort (CPUE) on the Sundays Irrigation ponds revealed that G. aestuaria dominated numerically and biomass in the Sundays River irrigation ponds. To assess the potential of harvesting G. aestuaria harvesting experiments were conducted using depletion (removal) sampling. Catchweight (kg) ranged from 2.16 (1.03; 3.28) to 61.25 (44.40; 78.09) kg and the estimated biomass from the depletion model ranged from 1.05 to 40.19 kg/ha for September 2019. The depletion model revealed that small impoundments have high biomass per hectare of G. aestuaria ranging from which indicates that the species may not support a commercial fishery but small-scale fisheries. In conclusion, G. aestuaria could become a meaningful contribution to the food and nutrient security of poor communities where available as a food source through small-scale fishery exploitation. The extent of this contribution may depend on its production potential in various regions and environments. More research is however needed to determine the long-term sustainability of harvesting of G aestuaria by looking at how populations respond to harvesting. , Thesis (PhD) -- Faculty of Science and Agriculture, 2021
- Full Text:
- Date Issued: 2021-05
- Authors: Zvavahera, Munetsi https://orcid.org/0000-0002-5337-1943
- Date: 2021-05
- Subjects: Small-scale fisheries , Silversides
- Language: English
- Type: Doctoral theses , text
- Identifier: http://hdl.handle.net/10353/22765 , vital:52752
- Description: In the past two decades, there has been increasing pressure for small-scale inland fisheries to play a central role in food and nutrient security for poor communities in South Africa. For decades, South African inland fisheries have focussed on the exploitation of large fish species and generally ignored the exploitation of inland small fish species (SFS). This research aimed to assess the ecology and small-scale fishery potential of the estuarine round-herring, Gilchristella aestuaria. To understand the ecology of G. aestuaria better, morphometric trait analysis and fish condition of populations in relation to environmental variables (salinity, pH, temperature, turbidity and chlorophyll-a) were done. Fish were supplemented with samples acquired from the SAIAB collection facility for 14 sites to cover all the three South African biogeographic regions, stretching from Lake Sibaya (KZN) to the Orange River estuary in the western parts of the country. The morphometric trait analysis showed that G. aestuaria populations can be distinguished based on the trait variation, however there were many overlaps for populations that are interconnected, with distant/ geographically separated populations showing clear differences. Morphometric traits of the G. aestuaria population were significantly different, however there was no strong directional relationship with environmental variables and variation in morphometric traits. However, fish condition as measured by Fulton’s condition (K) and relative weight (Wr) showed variation between populations found in different environments. These differences suggest that these populations must be managed differently if G. aestuaria is to be exploited in managed fisheries. To determine the potential nutrient value of G. aestuaria to the human diet, samples from two freshwater sites and five estuarine sites were analysed for essential macro and micronutrients. The nutrient content of G. aestuaria revealed there is potential for exploitation, as the species has a high macro (protein and fat) and micronutrient composition (calcium, iron and zinc). Mean ± SD of selected nutrients were protein (61.7±5.0 g/100g), fat (20.4±3.7g/ 100g), calcium (3507.5±314.0mg), iron (40.37±14.0mg/ 100g), zinc (22.47±5.6mg/ 100) and vitamin A (37.3±44.4 RAE/ 100g). The nutrient composition of fish collected from freshwater sites was comparable to those collected from estuarine environments. Using the recommended dietary allowances (RDA) from literature, the mass of fish and the number of fish that would provide a minimum amount for each nutrient were calculated. A child would require only 13.4g of dry G. aestuaria or approximately 74 dried fish to meet the daily requirements of zinc. Other minerals such as iron and calcium also showed a similar low weight or number of fish required to meet daily requirements for the different categories. A small number of G. aestuaria are needed to meet RDA for groups (children, adult men, adult women, pregnant women and lactating mothers). A comparison was done for the nutrient composition of G. aestuaria with reference species that are already harvested for human consumption in some African and Asian countries. The protein content of G. aestuaria was comparable to Chisense (Microthrissa moeruensis) and Kapenta Limnothrissa miodon), while the fat composition was more than twice Chisense and Kapenta. Comparing the mineral composition, G. aestuaria had more than three times higher calcium than Mola (Amblypharyngodon mola) and Puti (Puntius sophore). Zinc composition was four times higher than M. moeruensis and L. miodon. Further exploration of the ecology of G. aestuaria was studied using the Sundays River irrigations ponds as a case study that would represent small impoundments across South Africa. Species rank abundance curve and catch per unit effort (CPUE) on the Sundays Irrigation ponds revealed that G. aestuaria dominated numerically and biomass in the Sundays River irrigation ponds. To assess the potential of harvesting G. aestuaria harvesting experiments were conducted using depletion (removal) sampling. Catchweight (kg) ranged from 2.16 (1.03; 3.28) to 61.25 (44.40; 78.09) kg and the estimated biomass from the depletion model ranged from 1.05 to 40.19 kg/ha for September 2019. The depletion model revealed that small impoundments have high biomass per hectare of G. aestuaria ranging from which indicates that the species may not support a commercial fishery but small-scale fisheries. In conclusion, G. aestuaria could become a meaningful contribution to the food and nutrient security of poor communities where available as a food source through small-scale fishery exploitation. The extent of this contribution may depend on its production potential in various regions and environments. More research is however needed to determine the long-term sustainability of harvesting of G aestuaria by looking at how populations respond to harvesting. , Thesis (PhD) -- Faculty of Science and Agriculture, 2021
- Full Text:
- Date Issued: 2021-05
Optimizing geochemical sampling sizes and quantifying uncertainties for environmental risk assessment using Anglogold-Ashanti Gold Mines as a case study
- Authors: Chihobvu, Elizabeth
- Date: 2010-04
- Subjects: Environmental risk assessment , Geochemical prospecting
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10353/24443 , vital:62796
- Description: Generally, and particularly in South Africa, limited work done on the development of methodologies for sample sizing and quantifying uncertainties in geochemical sampling and analyses. As a result, little trust is placed on the long-term predictions of geochemical modelling for Environmental Risk Assessment (E.R.A). In addition, this leads to the slow approval of mining authorisations, water use licenses and mine closure plans. This dissertation addresses this deficiency in geochemical sampling and analyses specifically for ERA and proposes two methodologies (i) for quantifying uncertainties in geochemical sampling and analysis as a function of sample size and analyses and (ii) for determining the optimum sample size to ensure data quality. The statistical analysis approach was adopted as the best method for sample size determination. The approach is based on the premise that the size of the study sample is critical to producing meaningful results. The size of the required samples depends on a number of factors including purpose of the study, available budget, variability of the population being sampled, acceptable errors and confidence level. The methodology for estimating uncertainty is a fusion of existing methodologies for quantifying measurement uncertainty. The methodology takes a holistic view of the measurement process to include all processes involved in obtaining measurement results as possible uncertainty components. Like the statistical analysis approach, the methodology employs basic statistical principles in estimating the size of uncertainty, associated with a given measurement result. The approach identifies each component of uncertainty; estimates the size of each component and sums the contribution of each component in order to approximate the overall uncertainty value, associated with a given measurement result. The two methods were applied to Acid-Base Accounting (ABA) data derived from geochemical assessment for ERA of the West Wits and Vaal River (Ashanti Gold mines) tailings dams undertaken by Pulles and Howard de Lange Inc. on behalf of AngloGold Ltd. The study was aimed at assessing and evaluating the potential of tailings dams in the two mining areas to impact on water quality and implications of this in terms of mine closure and rehabilitation. Findings from this study show that the number of samples needed is influenced by the purpose of the study, size of the target area, nature and type of material, budget, acceptable error and the confidence level required, among other factors. Acceptable error has an exponential relationship with sample size hence one can minimize error by increasing sample size. While a low value of acceptable error value and high confidence are always desirable, a tradeoff among these competing factors must be found, given the usually limited funds and time. The findings also demonstrated that uncertainties in geochemical sampling and analysis are unavoidable. They arise from the fact that only a small portion of the population rather than a census is used to derive conclusions about certain characteristics of the target population. This is further augmented by other influential quantities that affect the accuracy of the estimates. Effects such as poor sampling design, inadequate sample size, sample heterogeneity and other factors highly affect data quality and representivity hence measurement uncertainty. Among these factors, those associated with sampling, mainly heterogeneity was found to be the strongest contributing factor toward overall uncertainty. This implies an increased proportion of expenditure should be channelled toward sampling to minimise uncertainty. Uncertainties can be reduced by adopting good sampling practices and increasing sample size, among other methods. It is recommended that more information be made available for proper uncertainty analysis. , Thesis (MSc) -- Faculty of Science and Agriculture, 2010
- Full Text:
- Date Issued: 2010-04
- Authors: Chihobvu, Elizabeth
- Date: 2010-04
- Subjects: Environmental risk assessment , Geochemical prospecting
- Language: English
- Type: Master's theses , text
- Identifier: http://hdl.handle.net/10353/24443 , vital:62796
- Description: Generally, and particularly in South Africa, limited work done on the development of methodologies for sample sizing and quantifying uncertainties in geochemical sampling and analyses. As a result, little trust is placed on the long-term predictions of geochemical modelling for Environmental Risk Assessment (E.R.A). In addition, this leads to the slow approval of mining authorisations, water use licenses and mine closure plans. This dissertation addresses this deficiency in geochemical sampling and analyses specifically for ERA and proposes two methodologies (i) for quantifying uncertainties in geochemical sampling and analysis as a function of sample size and analyses and (ii) for determining the optimum sample size to ensure data quality. The statistical analysis approach was adopted as the best method for sample size determination. The approach is based on the premise that the size of the study sample is critical to producing meaningful results. The size of the required samples depends on a number of factors including purpose of the study, available budget, variability of the population being sampled, acceptable errors and confidence level. The methodology for estimating uncertainty is a fusion of existing methodologies for quantifying measurement uncertainty. The methodology takes a holistic view of the measurement process to include all processes involved in obtaining measurement results as possible uncertainty components. Like the statistical analysis approach, the methodology employs basic statistical principles in estimating the size of uncertainty, associated with a given measurement result. The approach identifies each component of uncertainty; estimates the size of each component and sums the contribution of each component in order to approximate the overall uncertainty value, associated with a given measurement result. The two methods were applied to Acid-Base Accounting (ABA) data derived from geochemical assessment for ERA of the West Wits and Vaal River (Ashanti Gold mines) tailings dams undertaken by Pulles and Howard de Lange Inc. on behalf of AngloGold Ltd. The study was aimed at assessing and evaluating the potential of tailings dams in the two mining areas to impact on water quality and implications of this in terms of mine closure and rehabilitation. Findings from this study show that the number of samples needed is influenced by the purpose of the study, size of the target area, nature and type of material, budget, acceptable error and the confidence level required, among other factors. Acceptable error has an exponential relationship with sample size hence one can minimize error by increasing sample size. While a low value of acceptable error value and high confidence are always desirable, a tradeoff among these competing factors must be found, given the usually limited funds and time. The findings also demonstrated that uncertainties in geochemical sampling and analysis are unavoidable. They arise from the fact that only a small portion of the population rather than a census is used to derive conclusions about certain characteristics of the target population. This is further augmented by other influential quantities that affect the accuracy of the estimates. Effects such as poor sampling design, inadequate sample size, sample heterogeneity and other factors highly affect data quality and representivity hence measurement uncertainty. Among these factors, those associated with sampling, mainly heterogeneity was found to be the strongest contributing factor toward overall uncertainty. This implies an increased proportion of expenditure should be channelled toward sampling to minimise uncertainty. Uncertainties can be reduced by adopting good sampling practices and increasing sample size, among other methods. It is recommended that more information be made available for proper uncertainty analysis. , Thesis (MSc) -- Faculty of Science and Agriculture, 2010
- Full Text:
- Date Issued: 2010-04
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