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Bothalia - African Biodiversity & Conservation

On-line version ISSN 2311-9284
Print version ISSN 0006-8241

Bothalia (Online) vol.50 n.1 Pretoria  2020

 

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Correspondence:
Dr M.J. du Toit,
13062638@nwu.ac.za

Submitted: 1 October 2019
Accepted: 2 July 2020
Published: 24 February 2021

 

 

Supplementary material

The supplementary data is available in pdf: [Supplementary data]

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ORIGINAL RESEARCH

 

Diatom responses to river water quality in the Kruger National Park, South Africa

 

 

Purvance ShikwambanaI, II; Jonathan C. TaylorI, II; Danny GovenderI; Judith BothaI

IScientific Services, Kruger National Park, Skukuza, 1350
IINorth-West University, Unit for Environmental Sciences and Management, Private Bag X6001, NWU, Potchefstroom, 2520

Correspondence

 

 


ABSTRACT

BACKGROUND: Although the Kruger National Park (KNP) is a protected area, it is not exempted from anthropogenically induced impacts, which often compromise river water flow and quality. Measures of river water quality in South Africa have conventionally been based on water chemistry as well as different ecological indicator groups such as fish and macroinvertebrates. Diatoms have been shown to be useful indicators of changes in water quality resulting from pollution and land-use impacts.
OBJECTIVES: To determine the applicability of diatoms for hind-casting water quality in the KNP and to compare recent diatom community composition with those from the 1980s.
METHODS: In this study, pH and electrical conductivity (EC) were used to evaluate temporal changes in water quality of three rivers within the KNP Additionally, we made use of historic diatom samples from three of the five perennial rivers to evaluate if diatom communities reflected changes in water conditions between 1983 and 2015.
RESULTS: Diatom community structure was significantly different between 1983 and 2015. Diatom-based index scores (SPI) indicated an improvement in water quality for the Letaba and Olifants rivers.
CONCLUSION: Diatoms were shown to be useful indicators of current water quality and are also useful for determining temporal changes.


 

 

Introduction

Rivers are invaluable infrastructure globally. They are the main sources of available surface water in many countries including South Africa. Less than 0.3% of all the available surface water is freshwater (Griffiths et al. 2015). This portion of water is reported to be on a decline both in quality and quantity (Pillay & Buckley 2001; Roux & Nel 2012; Laine et al. 2014). Various freshwater tax-onomic groups such as diatoms, macroinvertebrates and fish are commonly used to monitor freshwater water quality (Taylor et al. 2007a; Boix et al. 2010; Bere & Mangadze 2014; Mangadze et al. 2016).

Five perennial rivers flow through the Kruger National Park (KNP) and although the KNP is a protected area, its rivers are not exempt from anthropogenical-ly induced impacts that compromise water quality and flow (Dallas & Day 2004; Pollard et al. 2011). As a result there has been a steady decline in water quality of most rivers in the KNP over time (Pollard & du Toit 2011). The main anthropogenic activities impacting water quality are point source and diffuse pollution (Roux & Nel 2012; Barnard et al. 2021). Sedimentation of river beds resulting from overgrazing, agriculture and sand-mining also impacts water quality and ecosystem health (Dallas & Day 2004). River flow is mainly impacted by impoundment and abstraction (O'Keeffe & Davies 1991; Riddell et al. 2013). Agricultural, urban and industrial activities are commonly sustained by water extracted from rivers - approximately 60% of river water supports agricultural activities, 24% goes to domestic use in urban areas and 3% of the water is used for industrial activities (DWA 2013). Water quality and quantity are crucial for sustainable freshwater ecosystems to benefit both livelihoods and the environment. Additionally, water quality is a key driver of productivity in aquatic systems - for instance if a system becomes moderately nutrient enriched, increased productivity may support several organisms depending on photosynthetic organisms. In some instances, when primary productivity is high (eu-trophication), this may lead to problems such as algae blooms with associated toxic effects and trophic disruptions (Dallas & Day 2004; Hart 2006, Tsu-Chuan & Clark 2018; Zheng et al. 2019).

An ideal water quality monitoring tool needs to be simple, quick, repeatable and preferably use aquatic organisms that are not seasonal and habitat dependent (Round 1991; De la Rey et al. 2004, Harding et al. 2005). Measures of river water quality in South Africa have conventionally been based on water chemistry as well as taxonomically different ecological indicator groups, such as fish and macroinvertebrates (De la Rey et al. 2004; Harding et al. 2004; Wepener 2008). However, water chemistry measurements are often expensive and only measure absolute values of a limited number of variables on the day of sampling (de la Rey et al. 2004), meaning that some water quality disturbances may be missed. Biotic responders, such as macroin-vertebrates, can also be limiting because they have different life stages often linked to seasons (Round 1991) and their distribution is usually variable due to habitat and flow conditions (De la Rey et al. 2004). Other concerns are that they were developed for specific types of streams, usually wade-able, low flow streams, meaning they cannot be monitored during the high flow season (Bate et al. 2004; Harding et al. 2005).

Unlike other taxonomic groups regularly used for biomonitoring, diatoms are less dependent on seasons (no larval stages), flow and habitat (Round 1991; De la Rey et al. 2004). Diatoms are in the Class Bacillar-iophyceae and are unique among algae as they have a cell wall composed of amorphous biogenic silica. Diatoms are photosynthetic, reproduce rapidly and may be attached or locally motile. Diatoms form thick biofilms in South Africa during the winter months and are major contributors to primary production. Diatoms are extremely useful ecological indicators (De la Rey 2004; Bate et al. 2004; Harding et al. 2005; Harding & Taylor 2014; Mangadze et al. 2015; Dalu & Froneman 2016). Additionally, diatoms are not geographically limited and their distribution is chiefly driven by water quality. Furthermore, diatoms' short life span and fast reproduction (Rott 1991) allow them to respond rapidly when water quality changes. The siliceous cell walls do not easily deteriorate after sampling, which allows for long-term storage and analysis of specimens (Harding & Taylor 2011). Thus, diatoms have the potential to augment the current water quality monitoring methods.

In the past three decades (1983 to 2015), the KNP substantially influenced water management practices outside of the park. Adaptive management was implemented by KNP and external stakeholders, allowing real-time monitoring data to inform dam management and releases (Venter & Deacon 1995; McLoughlin et al. 2011; Pollard et al. 2011). Some of the management strategies implemented includes the new water act, compulsory licencing and formation of catchment management agencies to provide local monitoring, enforcement and water licencing. On closing the adaptive management loop, the real-time responses worked much better with flow, a more complicated but tractable system responder than quality, a more sluggish and complex system responder (McLoughlin et al. 2011; Pollard et al. 2011; Riddell et al. 2013). This ultimately led to all rivers flowing during the 2015-2017 drought, one of the most severe droughts recorded, both in terms of MAR (mean annual rainfall) and average temperatures (Swemmer et al. 2018). Maintaining river flow generally means increased dilution capacity and therefore improvement in water quality, which in the case of the present study would be reflected by diatoms.

In the present study we investigated river eco-status of three perennial rivers of the KNP to evaluate if diatom communities changed when river eco-status changed. This is a necessary step towards integrating diatoms into river eco-status monitoring programmes as a possible diagnostic tool for assessing water quality in future, specifically in the KNP. Additionally, we made use of water quality data to evaluate change in all major KNP rivers from 1983 to 2015. We used pH and EC to evaluate changes in water conditions at our sample sites because both variables were consistently collected. We then evaluated the potential of diatoms as water quality indicators by studying changes in diatom community structure in relation to EC and pH. We specifically made use of a customised version of the Specific Pollution sensitivity Index (SPI), also referred to as the South African Diatom Index (SADI).

 

Materials and Methods

Study area

The study was conducted in three perennial rivers, the Letaba, Olifants and Sabie rivers (Figure 1), flowing through the semi-arid region of the Kruger National Park (KNP), South Africa. This part of the KNP receives approximately 537 mm average annual rainfall. The perennial rivers experience variable seasonal flow regimes and are influenced by large infrequent disturbances such as floods and droughts (O'Keefee & Rogers 2003). The Oli-fants, Letaba and Sabie rivers have different catchment sizes and origins. The Olifants originates in the Highveld, far from the KNP. The Letaba and Sabie river originate close to the KNP and flow over similar geology (O'Keefee & Rogers 2003). Land-use activities along the Olifants catchment are mainly mining, agriculture and forestry. However, land-use activities along the Letaba and Sabie rivers include agriculture and forestry. The catchment length for the Olifants, Letaba and Sabie are 840 km, 573 km and 189 km respectively. A relatively long stretch of the Olifants and Letaba rivers are outside the KNP, accounting for 89% and 82% river length respectively. The Sabie River has only 37% of the river length outside the KNP (O'Keefee & Rogers 2003; Pollard et al. 2011). The present study compared samples collected in September 2015 to historical samples collected in March 1983, river flow is often stable in both months. The average rainfall for March 1983 was 1.39 mm and 1 mm for September 2015 (SANParks data).

Data collection

Diatoms

Diatom samples were collected in 2015 in the KNP by SANParks staff members. No chordates or vertebrates were collected during the study. All historic diatom samples used in this study are part of the South African National Diatom Collection (SANDC) housed at the North-West University in Potchefstroom. These samples were collected in March 1983, using a similar sampling and slide preparation techniques as those used in the present study. Diatom samples collected in September 2015 followed the collection, preservation, preparation and analysis protocols as described in Taylor et al. (2007b). Briefly, five to ten average sized rocks (15 to 30 cm) were randomly selected. The selected rocks were located at least a meter away from the river bank in the flowing part of the river, to avoid isolated waters and eddies. The surface of the rocks was scrubbed with a small brush and the resulting suspension preserved with ethanol (> 20% final concentration). Samples were allowed to settle for 24 hours and then processed using the hot acid and KMnO4 method (Taylor et al. 2007b). Slides were mounted in Pleurax (Taylor et al. 2007b). Diatoms were viewed using an Olympus BX41 light microscope and identified according to Taylor et al. (2007a).

Water quality

Physicochemical parameters measured in situ during 2015 included pH and EC (uS/cm). Measurements were recorded from active channels of the river before diatom samples were collected. A WTW LF95 (Weilheim, Germany) handheld water quality meter was used to measure EC and a Cyberscan pH 300 meter (Eutech Instruments) to measure pH. Unlike the diatom samples, historic physicochemical measurements included each year and all major rivers from 1983 to 2015. These historic physicochemical measurements were collated from the Department of Water and Sanitation official website (http://www.dwaf.gov.za/iwqs/wms/data/accessed 06/07/2018).

Data analysis

OMNIDIA ver. 5.3 diatom interpretative software was primarily used to generate index scores using the counted and identified cells (Lecointe et al. 1993). A value between 1 and 20 was allocated to each sample based on species sensitivity values (Lecointe et al. 1993; Harding & Taylor 2011) and then translated to an ecological class as shown in Table 1. The top five dominant species per river for the time periods were considered to elucidate drivers to specific water quality changes. Student t-tests were used to assess physicochemical parameters over time and their relationship to SPI score. An ANOSIM was also performed to test whether there were significant differences in diatom species similarity between years and a two dimensional multi-dimensional scaling (MDS) approach was used to visualise the similarity between sites using Primer 5 ver. 5.2.3 (Clarke & Warwick 2001)

 

Results

Changes in water quality indicators in the three studied rivers

The pH and EC varied considerably (pH: 6.3-8.9 and EC: 9.22-205.08) over time in all three studied rivers (Figure 2). The pH remained relatively similar (p>0.05) in the Olifants River over time, however for EC, there were significant differences (P = 0.0013) between 1983 and 2015 (Table 2). From additional historical data we also observed a steady decline in EC until early 2000, but it then stabilised at less than 90 uS/m from early 2000 to 2015 (Figure 2D). The Letaba River maintained an alkaline water column throughout 1983 to 2015. The EC was also generally maintained below 140 uS/m. The Sabie River reflected a more neutral water column from the early 1980s to an alkaline level in 2015. The Sabie River became more alkaline over time, with a significantly high pH in 2015 compared to 1983 (P = 0.0004). Although the EC was quite low during the study period (<50 uS/m), it doubled between 1983 and 2015 (P = 0.0001).

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