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Biological assessment tools in wetlands
Barbour et al. (1999) defined a biological assessment as “an evaluation of the condition of a waterbody using biological surveys and other direct measurements of the resident biota in surface waters”. Water quality assessments using biota were first practised at the turn of the twentieth century. Kolkwitz & Marsson (1902, 1908, 1909) developed a system to monitor the effects of point source pollution from sewage discharges on aquatic fauna and flora (including diatoms) in Central Europe. This system, known as the Saprobic system, was based on observations of temporal and spatial changes in abundance and distribution of biological taxa in response to organic pollution. Subsequently, techniques using aquatic biota to assess pollution in rivers were developed and the approach of biological indicators was developed.
Biological indicators are taxa or functional groups which are sensitive to changes (biochemical, physiological, or behavioural) within their ecosystem and whose function, population or status provides an integrated record of the ecological integrity of the system (e.g., the cumulative impacts of various pollutants on the ecosystem and the timescale the system has been impacted) (Karr, 1981). Since the 1960’s, the use of multiple biological indicators in biological assessment and monitoring techniques of aquatic resources has become widespread (Gerhardt, 2002). Species composition of major taxonomic groups (from different trophic levels) incorporating a wide range of environmental tolerances can provide multiple data sources to evaluate the resource condition in a “biotic index” or “multimetric” approach (Karr & Chu, 1999). Karr (1981) proposed the index of biological integrity, or IBI, which was antecedent to the development of multimetric indices (MMIs).
MMIs are commonly used in biological assessments because they include a collection of individual community metrics that reflect the effects of human disturbance on biological condition (Karr, 1991). Fish, macroinvertebrates, macrophytes and diatom communities have been widely used as a tool for biologically monitoring aquatic ecosystems (Allen et al., 1999; Hering et al., 2006a; Johnson & Hering, 2009) although Stevenson et al. (2013) highlighted the fact that diatoms are the only group used in all three freshwater habitats (rivers/streams, lakes and wetlands) of the National Aquatic Resource Surveys by the US Environmental Protection Agency (USEPA). The development of MMIs using diatom assemblages are well documented in North America as effective assessment tools for streams, lakes and wetlands at varying geographic scales, from states and ecoregions (e.g., Wang et al., 2005, 2006; Miller et al., 2016) to national-scale assessments (Stevenson et al., 2013).
In South Africa, biological assessment techniques for river health assessments are well established (e.g., Dickens & Graham, 2002; Taylor et al., 2005; Dallas et al., 2010). In the case of South African wetlands, however, there is currently no definitive, well developed method for assessing ecological condition (Rountree et al., 2013). This is fundamental to the effective management, monitoring and rehabilitation of wetlands, and is also a requirement of the South African National Water Act (NWA, 1998). The NWA describes the framework that allows for water resource protection and use in a sustainable manner. The ecological condition of an aquatic habitat needs to be ascertained for effective implementation of the NWA.
CHAPTER 1: GENERAL INTRODUCTION
1.1 BACKGROUND .
1.1.1 Biological assessment tools in wetlands
1.1.2 Rationale for using diatoms in wetland assessments
1.1.4 Depressional wetlands and their importance, both ecologically and socio-economically.
1.1.5 Depressional wetlands of the Mpumalanga Highveld region and current threats
1.2 OUTLINE OF THESIS
1.2.1 Chapter Description
1.2.2 Chapter structure .
CHAPTER 2: DIATOM-BASED MODELS FOR INFERRING WATER CHEMISTRY
AND HYDROLOGY IN TEMPORARY DEPRESSIONAL WETLANDS
ABSTRACT
2.1 INTRODUCTION
2.2 MATERIALS AND METHODS
2.2.1 Study area
2.2.2 Sampling and laboratory methods .
2.2.3 Statistical analysis.
2.3 RESULTS .
2.3.1 Physical and chemical characteristics of sites
2.3.2 Composition
2.3.3 Environmental predictors
2.3.4 Effects of ionic composition and concentration vs. hydrological factor
2.3.5 Diatom Inference models
2.3.6 Indicator taxa
2.4 DISCUSSION .
2.4.1 Diatom species composition
2.4.2 Environmental predictor
2.4.3 Diatom inference models
2.4.4 Indicator taxa
2.5 CONCLUSIONS
CHAPTER 3: A DIATOM FUNCTIONAL-BASED APPROACH TO ASSESS
CHANGING ENVIRONMENTAL CONDITIONS IN TEMPORARY
DEPRESSIONAL WETLANDS
ABSTRACT
3.1 INTRODUCTION
3.2 MATERIALS AND METHODS
3.2.1 Study area
3.2.2 Sampling and laboratory methods .
3.2.3 Data Analysis .
3.3 RESULTS
3.3.1 Functional group composition
3.3.2 Seasonal patterns in functional group composition
3.3.3 Environmental predictors
3.4 DISCUSSION
3.4.1 Taxonomical challenges and benefits of using diatom functional groups
3.4.2 Most sensitive functional groups to environmental changes in temporal wetlands
3.5 CONCLUSION
CHAPTER 4: DEVELOPMENT OF A DIATOM-BASED MULTIMETRIC INDEX
FOR ACID MINE DRAINAGE IMPACTED DEPRESSIONAL
WETLANDS
ABSTRACT
4.1 INTRODUCTION .
4.2 MATERIALS AND METHODS
4.2.1 Study area and site selection
4.2.2 Data collection
4.2.3 Classification of reference sites
4.2.4 Development of MMIs
4.2.4.1 Candidate diatom metrics .
4.2.4.2 Metric selection
4.2.4.3 Metric re-scaling and MMI scoring
4.2.5 Evaluating performance of MMI
4.3 RESULTS
4.3.1 Physical-chemical and diatom data
4.3.2 Metric screening and selection of final metrics
4.3.3 MMI performance .
4.4 DISCUSSION
4.4.1 Metric selection
4.4.2 MMI performance
4.4.3 Priorities for future research .
4.5 CONCLUSIONS
CHAPTER 5: DIATOMS AND DEPRESSIONAL WETLANDS: SYNTHESIS &
CONCLUSIONS
5.1 INTRODUCTION .
5.2 OVERVIEW.
5.3 GENERAL DISCUSSION .
5.3.2 Diatoms and AMD polluted permanent depressional wetlands
5.4 CONSERVATION IMPLICATIONS
5.5 CONCLUSIONS
LITERATURE CITED
SUPPLEMENTARY TABLES
