Developing taxonomic and trait-based approaches for assessing and predicting macroinvertebrate responses to elevated fine sediments in the Tsitsa River and its tributaries, South Africa
- Authors: Ntloko, Pindiwe
- Date: 2022-04-08
- Subjects: Water quality South Africa Mzimvubu River Watershed , Sedimentation and deposition South Africa Mzimvubu River Watershed , Aquatic invertebrates Effect of sediments on South Africa Mzimvubu River Watershed , Aquatic invertebrates Classification , Environmental monitoring South Africa Mzimvubu River Watershed , Analysis of variance , Multivariate analysis
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/294692 , vital:57245 , DOI 10.21504/10962/294692
- Description: Sedimentation of freshwater systems is one of the leading causes of water quality deterioration. The Mzimvubu River catchment, which includes the Tsitsa River and its tributaries, in the Eastern Cape is prone to elevated sediment impact due to dispersive soils that are easily erodible. In this study, taxonomy and trait-based approaches were used to assess the responses of macroinvertebrates to fine sediments in the Tsitsa River and its tributaries. Macroinvertebrates and environmental variables were sampled seasonally in winter, spring, summer and autumn of 2016 to 2018 in six selected sites, using the South African Scoring System version 5 as a collecting protocol. The sites were selected to represent a decreasing gradient of sediment influence from the highly impacted Sites 1 (Tsitsa upstream) 2 (Tsitsa downstream), and 3 (Qurana River) to moderately impacted Sites 4 (Millstream upstream) and 5 (Millstream downstream) and the least impacted Sites 6 (Pot River upstream), 7 (Little Pot River) and 8 (Pot River downstream), which were collectively referred to as the control sites. Analysis of basic physico-chemical variables, dissolved oxygen, pH, electrical conductivity, turbidity, total suspended solids, temperature and nutrients were undertaken seasonally over the study period. Sediments grain sizes were also analysed. All collected data were subjected to appropriate statistical tests – univariate and multivariate techniques. A fine-sediment-specific multimetric index was developed to monitor the impact of fine sediments on macroinvertebrate assemblages of the Tsitsa River and its tributaries. A total of 12 traits, resolved into 48 trait attributes, were selected to explore their distribution in relation to a fine-sediment stress gradient, and identify the trait-based signature of fine-sediment impact. A trait-based approach was then developed to classify South African macroinvertebrates into two groups: taxa that are potentially vulnerable to fine-sediment impact and those potentially resilient, based on the combination of traits possessed. Two-way analysis of variance (ANOVA) indicated that electrical conductivity, turbidity, embeddedness and total suspended solids were statistically significantly different between the sites. Apart from Dissolved oxygen, the remaining variables were statistically significantly lower at the control sites (P < 0.05). The two-way multivariate analysis of variance (MANOVA) indicated global significant differences between sites and seasons. The two-way MANOVA also revealed that the interaction between the sites and seasons were statistically significant. The MANOVA indicated global combined interactive effects across the sites for suspended fine-sediment grain sizes, two-way ANOVA, followed by a Tukey’s post-hoc test, was carried out to indicate where the significant differences lay. The one-way ANOVA results indicated that very fine sand, very coarse silt, medium silt, and fine silt were significantly higher at Tsitsa upstream, Tsitsa downstream, Qurana tributary that is at Millstream upstream, Millstream downstream and Control sites. The rest of the grain sizes did not differ statistically between the sites. In terms of the settled sediment grain sizes, the volumetric analysis did not show considerable differences across the sites. Settled fine-sediment grain sizes were evenly distributed across the sites. Statistically, MANOVA results indicated no significant differences across sites or across seasons. The developed Sediment Multimetric Index indicated that the sites in the Tsitsa River and those in the Qurana River were highly sedimented during the wet season, but became moderately sedimented during the dry season, indicating that the index responded to seasonality. The sediment multimetric index indicated that the control sites were less sedimented during both the wet season and dry seasons, suggesting minimal seasonal effects at the control sites. Traits such as an exposed and soft body, collector-filterers, shredding, feeding on coarse particulate organic matter and a high sensitivity to dissolved oxygen were identified as fine- sediment-sensitive indicator traits. Identified fine-sediment-tolerant traits and ecological preferences included complete sclerotisation, a cased/tubed body, a preference for fine particulate organic matter, a high tolerance to dissolved oxygen depletion, and climbing and skating behaviours. Regarding the trait-based approach followed for classifying macroinvertebrates into vulnerable taxa and resilient taxa, the results revealed that the relative abundance and richness of the vulnerable taxa decreased predictably along the increasing gradient of sediment impact. However, the relative abundance and richness of resilient taxa showed no marked response to the impact of an increasing gradient of fine sediments. Overall, the present study makes a contribution to the complementary application of trait-and taxonomy-based approaches to freshwater biomonitoring. The trait-based approach enables predictions to be made and tested based on the mechanistic understanding of the mediating roles of traits in organism- environment interaction. A fundamental challenge, which showcases the limitation of the current study, is the sparse trait data on Afrotropical macroinvertebrates at the species or generic levels. In this regard, the iv trait-based approaches developed here were the family level instead of species or genus. This is the first study in South Africa to develop explicit trait-based indicators of elevated fine sediments as well as an approach for predicting macroinvertebrate vulnerability and resilience to fine-sediment effects, thus advancing the science and practice of freshwater biomonitoring. , Thesis (PhD) -- Faculty of Science, Institute for Water Research, 2022
- Full Text:
- Date Issued: 2022-04-08
- Authors: Ntloko, Pindiwe
- Date: 2022-04-08
- Subjects: Water quality South Africa Mzimvubu River Watershed , Sedimentation and deposition South Africa Mzimvubu River Watershed , Aquatic invertebrates Effect of sediments on South Africa Mzimvubu River Watershed , Aquatic invertebrates Classification , Environmental monitoring South Africa Mzimvubu River Watershed , Analysis of variance , Multivariate analysis
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/294692 , vital:57245 , DOI 10.21504/10962/294692
- Description: Sedimentation of freshwater systems is one of the leading causes of water quality deterioration. The Mzimvubu River catchment, which includes the Tsitsa River and its tributaries, in the Eastern Cape is prone to elevated sediment impact due to dispersive soils that are easily erodible. In this study, taxonomy and trait-based approaches were used to assess the responses of macroinvertebrates to fine sediments in the Tsitsa River and its tributaries. Macroinvertebrates and environmental variables were sampled seasonally in winter, spring, summer and autumn of 2016 to 2018 in six selected sites, using the South African Scoring System version 5 as a collecting protocol. The sites were selected to represent a decreasing gradient of sediment influence from the highly impacted Sites 1 (Tsitsa upstream) 2 (Tsitsa downstream), and 3 (Qurana River) to moderately impacted Sites 4 (Millstream upstream) and 5 (Millstream downstream) and the least impacted Sites 6 (Pot River upstream), 7 (Little Pot River) and 8 (Pot River downstream), which were collectively referred to as the control sites. Analysis of basic physico-chemical variables, dissolved oxygen, pH, electrical conductivity, turbidity, total suspended solids, temperature and nutrients were undertaken seasonally over the study period. Sediments grain sizes were also analysed. All collected data were subjected to appropriate statistical tests – univariate and multivariate techniques. A fine-sediment-specific multimetric index was developed to monitor the impact of fine sediments on macroinvertebrate assemblages of the Tsitsa River and its tributaries. A total of 12 traits, resolved into 48 trait attributes, were selected to explore their distribution in relation to a fine-sediment stress gradient, and identify the trait-based signature of fine-sediment impact. A trait-based approach was then developed to classify South African macroinvertebrates into two groups: taxa that are potentially vulnerable to fine-sediment impact and those potentially resilient, based on the combination of traits possessed. Two-way analysis of variance (ANOVA) indicated that electrical conductivity, turbidity, embeddedness and total suspended solids were statistically significantly different between the sites. Apart from Dissolved oxygen, the remaining variables were statistically significantly lower at the control sites (P < 0.05). The two-way multivariate analysis of variance (MANOVA) indicated global significant differences between sites and seasons. The two-way MANOVA also revealed that the interaction between the sites and seasons were statistically significant. The MANOVA indicated global combined interactive effects across the sites for suspended fine-sediment grain sizes, two-way ANOVA, followed by a Tukey’s post-hoc test, was carried out to indicate where the significant differences lay. The one-way ANOVA results indicated that very fine sand, very coarse silt, medium silt, and fine silt were significantly higher at Tsitsa upstream, Tsitsa downstream, Qurana tributary that is at Millstream upstream, Millstream downstream and Control sites. The rest of the grain sizes did not differ statistically between the sites. In terms of the settled sediment grain sizes, the volumetric analysis did not show considerable differences across the sites. Settled fine-sediment grain sizes were evenly distributed across the sites. Statistically, MANOVA results indicated no significant differences across sites or across seasons. The developed Sediment Multimetric Index indicated that the sites in the Tsitsa River and those in the Qurana River were highly sedimented during the wet season, but became moderately sedimented during the dry season, indicating that the index responded to seasonality. The sediment multimetric index indicated that the control sites were less sedimented during both the wet season and dry seasons, suggesting minimal seasonal effects at the control sites. Traits such as an exposed and soft body, collector-filterers, shredding, feeding on coarse particulate organic matter and a high sensitivity to dissolved oxygen were identified as fine- sediment-sensitive indicator traits. Identified fine-sediment-tolerant traits and ecological preferences included complete sclerotisation, a cased/tubed body, a preference for fine particulate organic matter, a high tolerance to dissolved oxygen depletion, and climbing and skating behaviours. Regarding the trait-based approach followed for classifying macroinvertebrates into vulnerable taxa and resilient taxa, the results revealed that the relative abundance and richness of the vulnerable taxa decreased predictably along the increasing gradient of sediment impact. However, the relative abundance and richness of resilient taxa showed no marked response to the impact of an increasing gradient of fine sediments. Overall, the present study makes a contribution to the complementary application of trait-and taxonomy-based approaches to freshwater biomonitoring. The trait-based approach enables predictions to be made and tested based on the mechanistic understanding of the mediating roles of traits in organism- environment interaction. A fundamental challenge, which showcases the limitation of the current study, is the sparse trait data on Afrotropical macroinvertebrates at the species or generic levels. In this regard, the iv trait-based approaches developed here were the family level instead of species or genus. This is the first study in South Africa to develop explicit trait-based indicators of elevated fine sediments as well as an approach for predicting macroinvertebrate vulnerability and resilience to fine-sediment effects, thus advancing the science and practice of freshwater biomonitoring. , Thesis (PhD) -- Faculty of Science, Institute for Water Research, 2022
- Full Text:
- Date Issued: 2022-04-08
Development of an antiretroviral solid dosage form using multivariate analysis
- Authors: Nqabeni, Luxolo
- Date: 2007
- Subjects: Analysis of variance , Experimental design , Multivariate analysis , Antiretroviral agents -- South Africa
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:10145 , http://hdl.handle.net/10948/705 , Analysis of variance , Experimental design , Multivariate analysis , Antiretroviral agents -- South Africa
- Description: The aim of pharmaceutical development is to design a quality product and the manufacturing process to deliver the product in a reproducible manner. The development of a new and generic formulation is based on a large number of experiments. Statistics provides many tools for studying the conditions of formulations and processes and enables us to optimize the same while being able to minimize our experimentation. The purpose of this study was to apply experimental design methodology (DOE) and multivariate analysis to the development and optimization of tablet formulations containing 150 mg lamivudine manufactured by direct compression.
- Full Text:
- Date Issued: 2007
- Authors: Nqabeni, Luxolo
- Date: 2007
- Subjects: Analysis of variance , Experimental design , Multivariate analysis , Antiretroviral agents -- South Africa
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:10145 , http://hdl.handle.net/10948/705 , Analysis of variance , Experimental design , Multivariate analysis , Antiretroviral agents -- South Africa
- Description: The aim of pharmaceutical development is to design a quality product and the manufacturing process to deliver the product in a reproducible manner. The development of a new and generic formulation is based on a large number of experiments. Statistics provides many tools for studying the conditions of formulations and processes and enables us to optimize the same while being able to minimize our experimentation. The purpose of this study was to apply experimental design methodology (DOE) and multivariate analysis to the development and optimization of tablet formulations containing 150 mg lamivudine manufactured by direct compression.
- Full Text:
- Date Issued: 2007
On using AMOS, EQS, LISREL, Mx, RAMONA and SEPATH for structural equation modeling
- Authors: Peprah, Syvester
- Date: 2000
- Subjects: Latent variables , Multivariate analysis , Mathematical statistics -- computer programs
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:11082 , http://hdl.handle.net/10948/279 , Latent variables , Multivariate analysis , Mathematical statistics -- computer programs
- Description: Structural Equation Modeling is a common name for the statistical analysis of Structural Equation Models. Structural Equation Models are models that specify relationships between a set of variables and can be specified by means of path diagrams. A number of Structural Equation Modeling programs have been developed. These include, amongst others, AMOS, EQS, LISREL, Mx, RAMONA and SEPATH. A number of studies have been published on the use of some of the applications mentioned above. They include, amongst others, Brown (1986), Waller (1993) and Kano (1997). Structural Equation Models are increasingly being used in the social, economic and behavioral sciences. More and more people are therefore making use of one or more of the Structural Equation Modeling applications on the market. This study is performed with the aim of using each of the Structural Equation Modeling applications AMOS, EQS, LISREL, Mx, RAMONA and SEPATH for the first time and document the experience, joy and the difficulties encountered while using them. This treatise is different from the comparisons already published in that it is based on the use of AMOS, EQS, LISREL, Mx, RAMONA and SEPATH to fit a Structural Equation Model for peer influences on ambition, which is specified for data obtained by Duncan, Haller and Portes (1971), by myself as a first time user of each of the programs mentioned. The impressive features as well as the difficulties encountered are listed for each application. Recommendations for possible improvements to the various applications are also proposed. Finally, recommendations for future studies on the use of Structural Equation Modeling programs are made.
- Full Text:
- Date Issued: 2000
- Authors: Peprah, Syvester
- Date: 2000
- Subjects: Latent variables , Multivariate analysis , Mathematical statistics -- computer programs
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:11082 , http://hdl.handle.net/10948/279 , Latent variables , Multivariate analysis , Mathematical statistics -- computer programs
- Description: Structural Equation Modeling is a common name for the statistical analysis of Structural Equation Models. Structural Equation Models are models that specify relationships between a set of variables and can be specified by means of path diagrams. A number of Structural Equation Modeling programs have been developed. These include, amongst others, AMOS, EQS, LISREL, Mx, RAMONA and SEPATH. A number of studies have been published on the use of some of the applications mentioned above. They include, amongst others, Brown (1986), Waller (1993) and Kano (1997). Structural Equation Models are increasingly being used in the social, economic and behavioral sciences. More and more people are therefore making use of one or more of the Structural Equation Modeling applications on the market. This study is performed with the aim of using each of the Structural Equation Modeling applications AMOS, EQS, LISREL, Mx, RAMONA and SEPATH for the first time and document the experience, joy and the difficulties encountered while using them. This treatise is different from the comparisons already published in that it is based on the use of AMOS, EQS, LISREL, Mx, RAMONA and SEPATH to fit a Structural Equation Model for peer influences on ambition, which is specified for data obtained by Duncan, Haller and Portes (1971), by myself as a first time user of each of the programs mentioned. The impressive features as well as the difficulties encountered are listed for each application. Recommendations for possible improvements to the various applications are also proposed. Finally, recommendations for future studies on the use of Structural Equation Modeling programs are made.
- Full Text:
- Date Issued: 2000
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