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SPATIOTEMPORAL DISTRIBUTION PATTERNS OF BENTHIC MACROINVERTEBRATE FUNCTIONAL FEEDING GROUPS IN THE BLYDE RIVER, SOUTH AFRICA

The impacts of land use changes and differences in seasonality on benthic macroinvertebrate composition were evaluated in the Blyde River of the Olifants River. The highest taxon richness and abundance of macroinvertebrates were at S6 and S5 respectively. These could be due to the high habitat heterogeneity and availability of food resources. The abundance and richness of taxa were greater in winter and spring respectively and both were lower in summer. The composition of macroinvertebrate community and distribution of functional feeding groups (FFG) differed significantly among sites. Collector-gatherers and collector-filterers were the most abundant groups recorded. The least abundant group was the shredders. The low abundance of shredders could be attributed to the enhanced microbial activity replacing shredder activity at high temperatures. The relative abundance and richness of the functional feeding groups did not conform fully to the River Continuum Concept (RCC). This could be due to human activities in the catchment that may be causing a change in the habitat and water quality at various sites. The results suggest that policies governing changes in land use is necessary to conserve the river and the macroinvertebrate community.


Introduction
Many river systems are continuously undergoing degradation throughout their course of flow due to pollution from various anthropogenic activities, such as mining, agriculture and expanding human settlements Biological monitoring is one of the methods used to determine the effects of anthropogenic activities on water quality of rivers and it is very useful to obtain their ecological information (Merritt et al., 2017). Macroinvertebrates are widely used as bioindicators of aquatic ecosystems because they are sensitive to changes in physical and chemical variables of ecosystems and reflect environmental conditions (Rosenberg and Resh, 1993). Benthic macroinvertebrates, for example, provide a more accurate understanding of changes in aquatic conditions when compared to chemical and microbiological data, which rather present short-term fluctuation (Ghasemi and Kamali, 2014). Macroinvertebrates respond to anthropogenic disturbance and natural changes in their habitats by changing their community structure. They serve as a major components of aquatic food webs that link organic matter and nutrient resources (e.g., leaf litter, algae and detritus) with higher trophic levels (Li et al., 2010). Furthermore, macroinvertebrates are made up of many species from different taxonomic levels with a wide range of trophic levels and pollution tolerances (Qu et al., 2013).
Benthic macroinvertebrates have a high diversity and a differentiated functional form according to the given physicochemical conditions of rivers and therefore respond to changes in the various environmental variables (Jun et al., 2016;Kim et al., 2016). Hence, there has been an increase in the use of functional feeding group (FFG) of benthic macroinvertebrate assemblages to assess environments (Fu et al., 2016). The FFG approach is considered to be more appropriate and rapid for characterizing ecosystem conditions, compared with taxonomical approach (Cummins et al., 2005;Mishra and Nautiyal, 2013;Cummins, 2016). It is used to assess the effect of land use disturbances on river functioning (De Castro et al., 2016), thus FFG provides a further perspective together with other community indices to ensure a better understanding of the relationship between habitat and aquatic fauna (Townsend et al., 1997). The River Continuum Concept (RCC) is widely used to explain the functioning of lotic ecosystems and predicts how relative FFG abundance change along a river gradient (Vennote et al., 1980). The RCC proposes that community structure should shift from an allochthonous in the headwater to an autochthonous in the downstream of the river, as the river widens and algal production increases (Allan and Castillo, 2007). Functional composition is therefore necessary for management actions to enhance ecosystem functioning (Ferreira et al., 2012). This approach is seen to provide more accurate assessment of water quality and ecological integrity of rivers, which indeed could be used for conservation and restoration strategies in managing river ecosystems (Príncipe et al., 2010).
The effect of changes in environmental variability on functional feeding groups of macroinvertebrate communities has scarcely been explored in South African rivers. Most of the studies on macroinvertebrate functional composition to land-use changes have been done in the temperate regions. However, land-use impacts are regionally specific due to the strong influence of cultural, historical, climatic and landscape settings on indicator-disturbance relationships (Zhang et al., 2012). Information regarding the structure and functioning of macroinvertebrates in the Blyde River is rare. The Blyde River was selected for the study because it is one of the few rivers in the Olifants River System known to have good water quality despite the increasing number of anthropogenic activities in the catchment (Ashton and Dabrowski, 2011). The objective of this study was to assess the spatial and temporal structure of aquatic macroinvertebrate community using the FFG approach in the Blyde River and to determine if the macroinvertebrate community structure corresponds to the River Continuum Concept (RCC). It is envisaged that the results of the study would be used to design proper conservation tool in the river system.

Study area
The Blyde River rises on the western slopes of the north-south trending Drakensberg Mountains and flows northwards towards the escarpment edge where it is dammed. From the dam, the Blyde River cascades down a steep series of rapids to its lower reaches, where the river again flows northwards to join the Olifants River at the town of Hoedspruit in Limpopo Province (DWAF, 2004). The Blyde River sub-catchment is approximately 2000 km 2 in size. Geologically, the northern part of the sub-catchment is made up of crystalline gneissic and granitic rocks of the Basement Complex, underlying the catchment (DWAF, 2004). The sub-catchment lies partly on the escarpment and, as a result, experiences higher rainfall considerably than the other sub-catchments in the Olifants River Basin, with mean annual precipitation sometimes exceeding 1000 mm (DWAF, 2004). During the last decade, there has been an increase in human activities in the area, especially agriculture, which are likely to cause environmental pollution in the freshwater systems. Seven sampling sites were selected along the river (Fig. 1). S1 (24°30'59.46"S 30°47'56.14"E), S2 (24°30'14.42"S 30°50'08.49"E). S3 (24°25'52.45"S 30°50'03.59"E), S4 (24°24'19.03"S 30°47'54.19"E), S5 (24°19'30.90"S 30°49'52.00"S), S6 (24°23'04.94"S 30°48'22.09"E) and S7 (24°15'30.38"S 30°50'13.22"E). The detailed description of the sampling sites is given in Table 1.

Physicochemical parameters
The study was carried out in January (summer), April (autumn), July (winter) and November (spring), 2018. Water samples were collected in 500 ml polyethylene bottles (acid pre-treated) and stored in a cooler box in the field using ice packs before being transported to the laboratory. Four water samples were collected from each site during the study. In the laboratory, the samples were stored at 4°C prior to analyses. Three readings of environmental variables, such as pH, water temperature, dissolved oxygen, (DO), total dissolved solids (TDS) and electrical conductivity (EC) were recorded at each site using a YSI Model 554 Data logger. Laboratory measurements were conducted to determine the nutrients (NH4, NO2, NO3 and PO4) and turbidity, using a spectrophotometer (Merck Pharo 100 Spectroquant™) with Merck cell test kits in the Biodiversity Water Laboratory, University of Limpopo. Percentage riparian vegetation cover was visually estimated at each sampling station over a 20 to 30 m riparian width. The following parameters were also measured; Stream width, the distance from bank to bank at a transect representative of the stream channel using a measuring tape; (ii) water depth, the vertical distance from the water surface to stream bottom using a meter ruler and (iii) current velocity at riffles or gliding runs using a flow meter.

Sampling of macroinvertebrates
Benthic macroinvertebrate samples were collected at the seven sites of the Blyde River during the four seasons. The samples were collected within a 100-m stretch of the study sites, with substrate of biotopes consisting mainly of mud, sand, gravel or stones. Samples were collected using a 30 cm by 30 cm sampling net with a 500 µm mesh size. Benthic macroinvertebrates were collected using the kick sampling method described by Dickens and Graham (2002), whereby the substrate was disturbed by kicking to free macroinvertebrates. Each site was sampled three times for benthic macroinvertebrates. The macroinvertebrates were then separated from organic and mineral matter, counted and identified to family level using Gerber and Gabriel's field guide manual (2002). Where specimens could not be identified in the field, the samples were preserved in 70% ethanol and transported to the laboratory for further identification, with the aid of a stereomicroscope (Leica EZ4) and magnifying glass. Macroinvertebrates were further classified into functional feeding groups using the key of Cummins et al. (2005), which classified the aquatic macroinvertebrates into the following functional feeding groups: Shredders (Sh) macroinvertebrates that chew conditioned litter or live vascular plant tissue (coarse particulate organic matter); Gathering-collectors (GC), that acquire fine particulate organic matter from interstices in the bottom sediments; Filtering-collectors (FC), that capture fine particulate organic matter from the water column using silken nets and filtering fans; Scrapers (Sc), which feed on algae attached on stable surfaces; Predators (P), which feed on living prey ( Table 2). Abundance of macroinvertebrate FFGs in each site and season were then calculated.

Statistical analysis
The cumulative values of the four seasons were used as the proportional abundance of each FFG. Analysis of variance (ANOVA) was used to determine differences between the sites and seasons. Where there was a significant variation, the Turkey's Post-Hoc test was performed to determine where the difference occurred. The statistical analyses were conducted using the software package, Statistica v10.0. Canonical Correspondence analysis (CCA), a multivariate method to calculate the relationships between biological assemblages of taxa and the environment was also used (Ter Braak and Verdonschot, 1995).

Physicochemical variables
The mean values of the physicochemical parameters are summarized in Table 3. The water depth and width increased from upstream to downstream site. The mean depth varied from 0.25 m (S1) to 0.68 m (S3) and the mean width varied from 4.97 (S1) to 7.07 m (S7). The highest mean velocity was 0.37 m/s at S3 and the lowest was 0.21 m/s at S1. The pH ranged from 8.1 at S5 to 9.0 at S1. The mean temperature varied from 22.28 (S2) to 24.90 °C (S7). The lowest mean dissolved oxygen value of 8.70 mg/l and the highest mean value of 11.85 mg/l were recorded at S5 and S2 respectively. The highest mean conductivity of 442 mS/m was observed at S5 and the lowest mean conductivity of 270.85 mS/m at S1. The mean TDS ranged from 132.9 at S1 to 252 mg/l at S7. There were no significant differences in the physicochemical variables among the seven sites (p > 0.05). However, there were seasonal significant differences in temperature (ANOVA, F = 12.03; p < 0.001), DO (ANOVA, F = 8.16; p = 0.001), EC (ANOVA, F = 3.45; p = 0.032), TDS (ANOVA, F = 18.6; p < 0.001). The nutrient levels were generally higher at the upstream sites than the downstream sites. http

Abundance and diversity of macroinvertebrates
A total of 19 797 specimens belonging to 11 orders and 33 families were collected at the various sampling sites and seasons. The greatest abundance (7426) and least abundance (1023) were observed at S5 and S3 respectively. The highest taxa richness (31) and the lowest taxa richness (22) were at S6 and S7 respectively. The family Hydropsychidae (Trichoptera) was the dominant taxa, followed by Caenidae, Baetidae (Ephemeroptera) and Simuliidae (Diptera) ( Table 4). The abundance of the macroinvertebrates was significantly different among sampling sites (ANOVA, F = 8.35; p < 0.001). In terms of seasons, the most abundance occurred during winter and least abundance during summer. The highest taxa richness (32) occurred in spring, followed by winter (27), autumn (24) and then summer (23). There was no seasonal significant difference in taxa richness but there was a significant seasonal variation in abundance (ANOVA, F = 6.03; p < 0.001).

Relationships between macroinvertebrates (FFG) and physicochemical variables
The CCA ordination of macroinvertebrate FFGs with water quality variables and nutrient concentrations showed distinct patterns, where the variables correlated with specific macroinvertebrate FFG under different levels of disturbance (Fig. 3). Sites 6 and 7 were less affected by temperature, EC, TDS, turbidity and nitrate. There was an association of shredders with the upstream sites, S1 and S2, while scrapers were associated with S3 and S4. The predators and the collectors (filterers and gatherers) http Table 6).

Physicochemical variables
Generally, the high levels of dissolved oxygen and low nutrient levels indicate that the water in the Blyde River was of good quality and that the river was only slightly disturbed by human activities. Higher EC and TDS were recorded in the midstream and downstream (from S4 to S7) than upstream (S1 and S2) of the river. The dissolved oxygen was high throughout the river, an indication that the river is in good condition. The nutrient levels were generally low at all sites. Thus, the physicochemical variables and nutrients recorded at all the sites were within the guideline limits (DWAF, 1996; CCME, 2012; USEPA, 2012).

Abundance and diversity of macroinvertebrates
The highest richness and abundance of macroinvertebrates were at S6 and S5 respectively. The high abundance of macroinvertebrates at site S5 could be attributed to increased input of organic nutrients from agriculture and high habitat heterogeneity of the site. High abundance of macroinvertebrates is known to increase with higher habitat heterogeneity due to the available stable and diverse microhabitats (Braccia and Voshell, 2006). The highest macroinvertebrate taxon richness at S6 could be due good habitat condition and the canopy cover. Many studies have found higher macroinvertebrate taxon richness at shaded sites than sites with low canopy cover (Dalu et al., 2017). The improved habitat condition at S5, though at the downstream of the river further supports the importance of conservation of water resources. The observed http://www.aloki.hu •  differences in taxa compositions across the sites were most likely due to different land use characteristics (Cortes et al., 2011(Cortes et al., , 2013.

Functional feeding group composition of macroinvertebrates
The collectors (filterers and gatherers) were dominant at all the sites. The high abundance across the sites could be due to the wide range of food resources consumed by this group. The predominance of collectors throughout the river has been reported in other studies of tropical streams (Tomanova et al., 2006;Jiang et al., 2011). Collectors are commonly abundant in streams and typically increase in abundance with stream size (Vannote et al., 1980). Generally, the high abundance of collector-gatherers in the river could be attributed to enrichment of organic matter in the water (Rosenberg and Resh, 1993). The highest abundance of collector-filterers was at S5, followed by S6. This may be attributed to the relative abundance of fine particulate organic matter transported in the water column (Strand and Merritt, 1999).
The high taxa richness of predators along the whole longitudinal gradients of the river may be due to availability of food and less competition. Predators are more abundant in small intermittent streams where fishes are scarce (Rieradevall et al., 1999). The river continuum concept (RCC) proposed that the abundance of predators depend on prey availability and abundance (Vannote et al., 1980). Predators normally have a similar proportion along the entire river, according to the river continuum concept or, alternatively, their abundance may depend on prey availability (Vannote et al., 1980). In this study, the relative abundance of predators was not significantly different at all sites except at S3 and S7. The highest abundance of scrapers at S7 could be due to sufficient algal production (periphyton), which serves as their food (Grubaugh et al., 1996). The shredders abundance was generally low especially at S7. Generally, the low abundance of shredders could be attributed to the enhanced microbial activity replacing shredder activity at high temperatures. The highest abundance at S5 could be due to the presence of riparian canopy which created conditions with plenty of feeding material that supported the shredders. The shredders utilize leaf litter from the riparian zones as an energy source. On the contrary, the lowest abundance of shredders at S7 could be due to low availability of leaf litter. Similar results have been reported that shredders are intimately related to the riparian vegetation, because of their reliance on allochthonous feeding resources and as well contribute much in the degradation of leaf materials dropping into aquatic systems from overhanging vegetation (Brasil et al., 2014;Masese et al., 2014).
The variation of the different FFG at the sampling sites can be explained by the availability of the food resources and changes in the environmental variables. Studies have shown that macroinvertebrate fauna can be altered by land use practices (Miserendino and Masi, 2010;Egler et al., 2012;Fierro et al., 2015). The shredders and scrapers were very low in the river and this could also be due to the fact that these two groups are more sensitive to disturbances, while collector-gatherers and collectorfilterers are more tolerant to pollution that might alter the availability of certain food (Barbour et al., 1996). Thus, the functional groups can potentially be used to assess aquatic ecosystem health (Bhawsar et al., 2015). Studies on the distribution of FFGs and benthic macroinvertebrate assemblages according to environmental variables are increasingly being conducted (Fierro et al., 2015;Fu et al., 2016).
Seasonally, the taxon richness and abundance were highest in spring and winter respectively than in other seasons. These are the drier seasons of the year and therefore the river receives less runoff draining from the catchment. In general, factors driving macroinvertebrate seasonal variation include precipitation/discharge, temperature, and photoperiod, and each of these factors can influence disturbance regimes in streams (Bêche et al., 2006). Seasonal variation of macroinvertebrate distribution can also be caused by changes in current velocity, substrate type and organic matter. The collectorgatherers were the most dominant functional group in autumn, winter and spring, while the collector-filterers were the most dominant group in summer. According to the continuum river concept, low order rivers such as Blyde River should contain mainly collector-gatherers and shredder organisms (Vannote et al., 1980). However, in this study the predominant group was the collector-gatherer. This study supports other studies which found high abundance of only collectors' group in some rivers (Miserendino and Pizzolon, 2003).

Relationships between macroinvertebrate assemblages and water quality variables
The distribution of macroinvertebrate structural and functional assemblages was influenced by physicochemical variables and nutrients across the sites. Canonical correspondence analysis (CCA) indicated that specific site categories correlated with specific water quality variables which in turn affected the distribution of the macroinvertebrates. Shredders were mainly found in the sites with riparian influence. Increase in nutrient levels and reduction in water quality negatively impacted the distribution of the sensitive macroinvertebrate taxa. The deteriorating physicochemical variables (EC and TDS) at S4 and S7 contributed to the low richness and diversity of macroinvertebrate taxa in these sites. Macroinvertebrate distribution closely followed the observed land-use changes in the various sites which induced changes in water quality with the least disturbed sites being associated with macroinvertebrate communities that were different from sites with poor water quality. These results are consistent with many other studies that have also found abiotic factors to be significantly affecting variation in macroinvertebrate communities (Kasangaki et al., 2008;Masese et al., 2014).

Conclusion
The study determined the influence of physicochemical variables on the distribution of benthic macroinvertebrate FFG. The collector-gatherers and collector filterers dominated across all the sites. The shredder and collector co-dominance in the headwaters was not observed as predicted by RCC. The RCC predicts that shredders will decrease in abundance from headwaters to the mouth and that collector-gatherers, collector-filterers and scrapers will increase downstream (Vannotte et al., 1980). Generally, low abundance of shredders and scrapers were recorded in this study. Thus, the distribution of the functional groups did not conform fully to RCC pattern and it could be due to land use changes (degradation) occurring in sections of the river. The high richness of macroinvertebrates at S6 further supports the importance of conservation. The FFG pattern shows the influence of changing environmental conditions on macroinvertebrates along the river and therefore confirm that FFG is an effective tool to assess ecological integrity of rivers. The findings suggest that conservation and protection of the river catchment including the riparian zone are important for preservation of ecological integrity and biodiversity of rivers.