Epilithic diatom flora in contrasting landuse settings in tropical streams, Manyame Catchment, Zimbabwe Tinotenda Mangadze, Taurai Bere & Tongayi Mwedzi
Hydrobiologia The International Journal of Aquatic Sciences ISSN 0018-8158 Volume 753 Number 1 Hydrobiologia (2015) 753:163-173 DOI 10.1007/s10750-015-2203-7
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PRIMARY RESEARCH PAPER
Epilithic diatom flora in contrasting land-use settings in tropical streams, Manyame Catchment, Zimbabwe Tinotenda Mangadze • Taurai Bere Tongayi Mwedzi
Received: 11 July 2014 / Revised: 6 January 2015 / Accepted: 29 January 2015 / Published online: 13 February 2015 Ó Springer International Publishing Switzerland 2015
Abstract The objective of this study was to evaluate the response of stream diatom assemblages to changes in water quality in different land-use settings. Water quality sampling and benthic diatom community data were collected in April and September 2013 at 95 sampling stations in the Manyame Catchment, Zimbabwe. The data collected were subjected to multivariate statistical techniques; CCA and cluster analysis to determine environmental gradients along which the diatom species were distributed as well as to elucidate hypothesized differences in community structure per land-use type. Three land-use categories were identified in this study: commercial agricultural, communal agricultural and urban-mining areas in order of increasing human disturbance. No significant differences in physical and chemical variables were recorded between the two sampling periods. Study sites were grouped into roughly three broad categories based on CCA and cluster analysis. As pollution
Handling editor: Jasmine Saros
Electronic supplementary material The online version of this article (doi:10.1007/s10750-015-2203-7) contains supplementary material, which is available to authorized users. T. Mangadze T. Bere (&) T. Mwedzi Department of Water and Fishery Sciences, School of Wildlife, Ecology and Conservation, Chinhoyi University of Technology, Off Harare-Chirundu Rd., Private Bag 7724, Chinhoyi, Zimbabwe e-mail: [email protected]; [email protected]
increased, low to moderate pollution tolerant species such as Cocconeis placentula, Surirella linearis and Surirella robusta were replaced by high pollution tolerant species such as Pinnularia braunii, Tryblionella coarcata, Luticola goeppertiana and Stauroneis smithii. This shows that diatom assemblages are potential indicators of changes in water quality due to changes in catchment land-use. Keywords Agriculture Urban settlement Mining Water quality Community structure Introduction The Manyame catchment is the most urbanized catchment in Zimbabwe and has undergone substantial land-use changes in the past 60 years (Masere et al., 2012). This has been coupled with significant impacts on water quality (Zwane, 2004), a rather not surprising development as land-use change is a key influencer of water quality (Pan et al., 1996). An increasing number of studies have shown substantial land-use effects on natural water quality due to activities such as agriculture, urban development, domestic, and industrial wastewater discharge (Bere & Tundisi, 2011a, b; Tuck et al., 2014). This is often common in most developing countries due to high population growth and development coupled with inadequate effluent handling infrastructure and lack of comprehensive environmental policies (James, 2005; Bere, 2007; Bere & Tundisi, 2011a, b).
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Changes in water quality of lotic systems due to surrounding land-use patterns affect the resulting biotic communities, as the patterns of these biota are responsive to the nature of the prevailing physical and chemical conditions (Walsh & Wepener, 2009; Bere & Tundisi, 2010a, b; Bere & Mangadze, 2014). Alterations in species (e.g., diatoms in this case) composition can thus be used to reflect changes in water quality in a more integrated manner than traditional monitoring of water chemistry which provides just a snapshot of the water quality at the time of sampling (Karr, 1991; Rocha, 1992; Buss et al., 2002; Bonada et al., 2006; Stevenson, 2006, Bere & Tundisi, 2010a, b). For this reason, studies in other regions have investigated changes in diatom communities in relation to land-use induced changes in water quality (Lobo et al., 1995; Winter & Duthie, 2000; Belore et al., 2002; Gurbuz & Kivrak, 2002; Walsh & Wepener, 2009; Bere & Tundisi, 2011a, b). Besides anthropogenic activities, natural factors are also important determinants of water quality and hence biotic assemblages in lotic systems. For example, Manyame catchment has certain streams draining part of the Great Dyke of Zimbabwe; a layered magma system largely composed of ultramafic rocks which have larger deposits of chromite, platinum, nickel, copper, cobalt, and gold. There is evidence that regional geology may set up ultimate constrains on overall regional diatom species diversity (Pan et al., 1999). However, Pan et al. (2000) reported that the regional/catchment determinants such as geology poorly predicted stream-reach periphyton assemblages. Therefore, better understanding of the relative importance of both regional/catchment and streamreach scale determinants on diatom species assemblages is essential for interpreting changes in diatom species in relation to environmental stressors at different scales which will eventually increase accuracy and precision of diatom-based bioassessment. The response of diatom communities to changes in land-use patterns continues to be hotly debated, emphasizing the importance of precisely quantifying the effects of varying land-use patterns on aquatic biota. In addition, most of the studies relating diatom community composition to changes in land-use patterns have mainly been carried out in the temperate regions, and only a few studies have specifically focused on the effect of land-use patterns in tropical systems. The few studies that have been carried out in
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Zimbabwe have restricted the use of epilithic diatoms to indicators of specific water quality problems such as organic pollution and eutrophication (Phiri et al., 2007; Bere & Mangadze, 2014; Bere et al., 2014). Understanding the relationship between land-use patterns, water quality, and diatom composition in streams provides a useful starting point for establishing stream water quality control regulations, conservation goals, ecological restoration efforts, and necessary research hypotheses for management of tropical lotic systems in Zimbabwe. The objective of this study was to evaluate the response of stream diatom assemblages to changes in water quality in different land-use settings, i.e., commercial agricultural, communal agriculture, and urban-mining areas. A suite of environmental variables that are known to vary with changes in land-use patterns were assessed to establish the combination of variables that best explained patterns of diatom community composition. The predominance of different anthropogenic activities in the Manyame Catchment offered a unique opportunity to assess the response of stream diatom assemblages to changes in water quality in contrasting land-use settings. We hypothesized that changes in water quality of lotic systems as a result of the surrounding land-use patterns will affect the resulting diatom communities.
Materials and methods Study area and study design The study was carried out in the Manyame catchment area, Zimbabwe (Fig. 1). Mean annual precipitation in the study area is around 700 mm, with warm to high temperatures of 21–27°C (Masere et al., 2012; Meteorological Services Department of Zimbabwe, 1965–2014). A combination of field reconnaissance study and Google Earth Satellite Image System, January 2013, was used for land-use classification. Following Anderson et al. (1976), three land-use categories were identified in the study area: commercial agriculture, communal agriculture, and urbanmining areas. A spatially balanced probabilistic design (Stevens & Olsen, 2004) was used to select sampling stations among the three land-use categories. Using this method, nine sampling stations were established in commercial agricultural forested areas that were
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Fig. 1 The location of the study area and sampling stations
expected to be relatively pristine compared to the other two land-use types. Thirty-five sampling stations were established in communal agricultural areas where a combination of poor agricultural practices (stream bank cultivation, overgrazing, soil erosions) and high human population densities is expected to have negative effects on water quality of streams draining these areas. Fifty-one sampling stations were established in urban-mining areas. The stream beds in some sections of these areas are composed of ultramafic rocks strongly enriched in magnesium-bearing minerals (Makore & Zano, 2012). Mining is the major socio-economic activity along these streams. Consequently, due to the economic downturn of the past 5–10 years in Zimbabwe, small scale gold and chrome mining have become prevalent along the Great Dyke. Over the past years, the number of panners and the mined area have increased thus subjecting the environment to degradation because of the methods used which are destructive to the natural environment. Streams in the study area also flow through urban areas. Due to population growth, uncontrolled
urbanization, and industrialization, various town councils in the study area do not meet the technical standards for sewage treatment, garbage collection, and urban drainage. Streams in the study area, therefore, receive pollutants from various point and diffuse sources, and their habitats have been greatly altered resulting in stream health deterioration, eutrophication, organic, and metal pollution among other threats (Bere & Mangadze, 2014).Two samplings were carried out, once in April (at the end of the rainy season when all the streams were flowing) and September (during the dry season) 2013 to capture the two flow extremes typical of the study area. Data were collected along a length of stream equal to 40 times the mean wetted width (minimum of 150 m and maximum of 500 m) centered on each randomly chosen sampling point. Field sampling At each sampling station, electrical conductivity, dissolved oxygen (DO), total dissolved solids (TDS),
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chloride, nitrate ðNO 3 Þ, salinity, conductivity, and temperature were measured using an YSI Pro- plus Multi-Parameter Water Quality Meter (Xylem Inc, USA). The percentage of riparian vegetation cover was visually estimated at each sampling station over 20–30-m riparian width. Water samples for lead (Pb), magnesium (Mg), calcium (Ca), potassium (K), sodium (Na), zinc (Zn), iron (Fe), cadmium (Cd), chromium (Cr), copper (Cu), cobalt (Co), nickel (Ni), total hardness, total phosphate (TP), soluble reactive phosphate (SRP), total nitrogen (TN), and chemical oxygen demand (COD) were collected at each sampling station following standard methods (APHA, 1988). Epilithic diatoms were sampled on riffles at each site by brushing stones with a toothbrush. Prior to sampling of epilithic surfaces, all substrata were gently shaken in stream water to remove any loosely attached sediments and nonepilithic diatoms. At least five pebble-to-cobble sized stones were randomly collected at each sampling site and brushed, and the resulting diatom suspensions were pooled to form a single sample, which was then put in a labeled plastic bottle. Laboratory analysis In the laboratory, the concentrations of TP and SRP were determined following the nesselarization method (APHA, 1988). TN was determined by oxidizing nitrogenous compounds to nitrate by heating with alkaline persulfate solution following Koroleff (1972). COD was determined by oxidation of potassium dichromate in acid medium following Jirka & Carter (1975). Concentrations of Ni, Pb, Mg, Ca, K, Na, Zn, Fe, Cr, and Cd and total hardness were determined with a Flame atomic absorption spectrophotometer (Varian Australia Pty Ltd, Victoria, Australia). Subsamples of the diatom suspensions were cleaned of organic material using wet combustion with concentrated sulfuric acid and mounted in Naphrax (Northern Biological supplies Ltd., UK, R1 = 1.74) following Biggs & Kilroy (2000). Three replicate slides were prepared for each sample. A total of 300–650 valves per sample (based on counting efficiency determination method by Pappas & Stoermer (1996)) were identified and counted using a compound microscope (91,000; Nilcon, Alphaphot 2, Type YS2-H, China). The diatoms were identified to species level based
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mainly on studies from South Africa (Taylor et al., 2007); studies from other tropical regions were consulted where necessary (e.g., Metzeltin & LangeBertalot, 1998, 2007).
Data analysis The distributions of TDS and conductivity that were positively skewed, were natural log (x ? 1) transformed (Zar, 1984). A two-way analysis of variance (Two-Way ANOVA) with Tukey’s post hoc HSD tests was used to compare means of physical and chemical variables among the three land-use categories sampling stations and between the two sampling periods. Cluster analysis with Wards method was performed based on pooled benthic diatom community data to show main differences and similarities in community composition among 95 sampling stations sampled. Multivariate data analyses were performed on the diatom dataset to indicate the main gradients of floristic variation and to detect and visualize similarities in diatom samples. Preliminary de-trended correspondence analysis (DCA) was applied to the diatom dataset to determine the length of the gradient. This DCA revealed that the gradient was greater than 3 standard deviation units (4.2), justifying the use of unimodal ordination techniques (TerBraak & Verdonschot, 1995). Thus, canonical correspondence analysis (CCA) was used to investigate relationships between predictor variables and benthic diatom communities from different sites. Preliminary CCA identified collinear variables and selected a subset on inspection of variance inflation factors (VIF \ 20; TerBraak & Verdonschot, 1995). Monte Carlo permutation tests (999 unrestricted permutations, P B 0.05) were used to test the significance of the axis and hence determine if the selected environmental variables could explain nearly as much variation in the diatom data as all the measured environmental variables combined. Input for the program included the relative abundance of diatom taxa that were present in a minimum of 4 samples and had a relative abundance of C1% in at least 1 sample. CCA was performed using CANOCO version 5.1 (TerBraak & Smilauer, 2002). All other statistical tests were performed with Palaeontological Statistics Software (PAST) Version 2.16 (Hammer et al., 2012).
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industrial effluent as well as other diffuse sources of pollution from the city and due to heavy metal pollution from mining and underlying geology.
Water quality The values of the physiochemical variables recorded in the Manyame catchment during this study are summarized in Table 1. A total of 25 environmental variables were analyzed and of these seven metals were below the detection limit; therefore, only 18 were recorded in the study. No significant differences were observed in mean environmental variables between the two sampling periods (ANOVA, P [ 0.05). Pollution levels generally tended to increase in the order: commercial agriculture \ communal agriculture \ urban-mining. Conductivity, TDS, TP, Ni, Mg, and NO 3 were significantly high in urban-mining sampling stations (ANOVA, P \ 0.05), while DO and percentage riparian vegetation cover were significantly low in the same (ANOVA, P \ 0.05) compared to the other two land-use categories. The water quality generally tended to deteriorate in urban-mining areas due to discharge of treated and untreated domestic and
Community composition A total of 156 diatom species belonging to 33 genera were recorded. Of the 156 species observed, 90 species were retained for subsequent analysis (present in a minimum of 4 samples and had a relative abundance of [1% in at least 1 sample; Appendix S1). The cluster ordination indicated three major groups of sampling stations (Fig. 2). The separation can be attributed to pollution. Group 1 comprised less impacted commercial agricultural sampling stations having diatom species which were sensitive to pollution. Group 2 comprised communal agricultural sampling stations and was characterized by diatom communities tolerating medium levels of pollution, while group 3 comprised of urban-mining sampling stations and was characterized by diatom communities that tolerate very high levels of pollution.
Table 1 Mean (±SD) of physical and chemical variables recorded in all sampling station categories (from less impacted commercial agricultural sampling stations—highly polluted downstream urban-mining sampling stations) during the study period Parameter
Sampling stations Less impacted commercial agricultural sampling stations
Moderately impacted communal agricultural sampling stations
Highly polluted urban-mining sampling stations
51.42 ± 19.51
52.78 ± 23.34
47.76 ± 27.15
Temperature (°C) DO (mg l-1)
20.22 ± 2.02
20.13 ± 2.19
21.52 ± 2.41
5.28 ± 2.17a
3.77 ± 1.51b a
3.01 ± 2.07b a
Conductivity (lS cm-1)
138.95 ± 58.82
153.21 ± 82.58
461.77 ± 189.54b
TDS (mg l-1)
98.32 ± 37.8a
112.38 ± 66.51b
319.05 ± 132.43c
0.07 ± 0.03
TN (mg l )
2.49 ± 1.54
TP (mg l-1)
0.01 ± 0.01a
0.02 ± 0.02a
0.05 ± 0.23b
0.01 ± 0.01
0.02 ± 0.11b
1.91 ± 1.87
Salinity (ppt) -1
SRP (mg l ) -1 NO 3 (mg l ) -1
COD (mg l )
0.23 ± 0.13b
8.42 ± 1.51
5.94 ± 14.78c
0.08 ± 0.04
0.01 ± 0.01
4.44 ± 3.39b
4.16 ± 0.75 a
116.58 ± 80.62a
96.57 ± 36.97
126.18 ± 82.57
7.65 ± 4.21
18.65 ± 4.37b
0.15 ± 0.31b
0.03 ± 0.04a
0.14 ± 0.33b
Total hardness (mg l-1)
45.66 ± 26.96
61.97 ± 31.49
125.97 ± 28.52
Ca2? (mg l-1)
10.77 ± 8.51a
9.21 ± 6.89a
9.60 ± 4.37a
(mg l )
Ni (mg l-1)
5.87 ± 4.05
Different letters denote significant differences obtained through Tukey’s post hoc comparison test
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27 41 95 94 12 19 49 28 40 15 10 92 5 79 75 11 8 9 6 4 51 3 39 1
71 31 34 20 2 48 87 66 54 61 93 38 91
26 56 89 72 65 67 64 89 26 85
Fig. 2 Wards method similarity matrix based on hierarchical cluster analysis indicating the similarity between 50% of the sampling stations sampled in relation to diatom community structure at each sampling station during the two sampling periods
Diatom community–environmental relationships The results of CCA are presented in Fig. 3. The first four axes of the species-environmental plot accounted for 80.4% of the total variance in the community due to measured environmental variables (Table 2). Axis 1 and 2 explained 29.82 and 20.35%, respectively, of the diatom species variance. Monte Carlo unrestricted permutation test indicated that axis 1 (99 permutations) and axis 2 (99 permutations of axis 2 with axis 1 as a covariable) were statistically significant (P B 0.05). TP, NO 3 , and Ca were positively associated with the first axis, while TN, Ni, and Mg were negatively associated with the first axis. TN, TP, and NO 3 were positively associated with the second axis, while Ni, Mg, and Ca were negatively associated with the second axis. CCA axis 1 and 2 separated the sampling stations into 3 groups along an agricultural, mining to urban gradient as in cluster analysis (human induced increase in nutrients, organic, and metal pollution and decrease in DO). The first group generally consisted of less impacted commercial agricultural sampling stations with good to medium water quality (Fig. 3) that were positively associated
with the first axis and negatively associated with the second axis in the bottom right quadrant (Fig. 3). These sampling stations were associated with high Ca levels, and diatom species characterizing these sampling stations include species such as Cymbella minuta, Cocconeis placentula, Anomoneis serians, Surrirela linearis, Diploneis ovalis, Stauroneis gracilior, Surrirela robusta, Aulacoseira muzzanensis, Nitzschia thermalis, Epithemia sorex, Navicula angusta, and Craticula acidoclinata. The second group consisted of poor to medium water quality, communal agricultural sampling stations that were positively associated with first and second axis, respectively, in the upper right hand of the quadrant. Diatom species characterizing these sampling stations include species such as Pinnularia gibba, Gomphonema parvulum, Pinnularia divergens, Gomphonema accuminatum, Eunotia formica, Gyrosigma accuminatum, Flagillaria ulna, Frustula saxonica, Navicula cuspidate, Gomphonema affine, and Gomphonema insigne. The third group consisted of very poor water quality downstream urban-mining sampling stations that were negatively associated with the first axis, respectively, in the upper and lower left-hand quadrant. These
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Ndec Aamb Aswa Nelg Ngre Sanc Gtru Emin Fvul Nzon Rmus Efor Ctur Tﬂo Nven Nrec Ncle Nsca Pbil Gtur Pgib Ebil Epec Nmin Pvir Spup Ncon Nitrate Pdiv Nacc Erho Ggra Fell Ebid TP Pama Fsax Plat NlinAhun Mell Einc NcusGaﬀFten Tcoa Gpse Amin Gacc GparNpal Pbra Fbic Gins 29.8% Acra Frho Namp Asax Fuln Npse Nrad Nthe Nang Rgib AminSgra Cpla Dell Cmen Amuz Eadn Ngoe Csil Caci Aeut Coce Mg Slin Ca Srob Dova Ctum Asta Cmin Gpum Msmi Dsun Aser Ni Ntri Ssmi Csol Esor
Fig. 3 Ordination diagram based on canonical correspondence analysis (CCA) of 95 sampling stations: a diatom species composition with respect to six environmental variables (TN, TP, Nitrate, Ni, Mg and Ca), b the corresponding land use
patterns with circles commercial agricultural sampling stations; cross-hatch communal agricultural sampling stations and diamonds urban-mining sampling stations. Taxa codes are shown in Table 2
Table 2 Summary of the canonical correspondence analysis (CCA) of the most dominant diatom species composition at 95 sampling stations with respect to six environmental variables (TN, TP, Nitrate, Mg, Ni and Ca) Statistic
Explained variation (cumulative) Pseudo-canonical correlation
Explained fitted variation (cumulative)
sampling stations were associated with high nutrients and high nickel and magnesium levels. These sampling stations were associated with species such as Flagilaria ulna, Fragilaria biceps, Cyclotella ocellata, Sellaphora pupula, Eunotia rhomboidea, Nitzschia linearis, Cymatopleura solea, Gomphonema pseudoaugur, Fragilaria elliptica, and Gomphonema pumilum.
Discussion Water quality The results of the present study suggest that land-use pattern has an effect on water quality in surrounding
streams as has been reported in other studies (Bolstad & Swank, 1997; Tong & Chen, 2002; Bere, 2007; Broussard & Turner, 2009; Schindler, 2009; Bere & Tundisi, 2011a, b; Nielsen et al., 2012; Tuck et al., 2014). In this study, runoff from different types of land-use was expected to be enriched with different kinds of contaminants. For example, runoff from agricultural lands was enriched with nutrients ðNO 3 and TNÞ and sediments (Table 1). Walsh (2000) noted a higher amount of nitrogen and phosphorus in the agricultural areas in the Crocodile and Magalies Rivers (Gauteng and North West Province, South Africa). In another study of Coweeta Creek in western North Carolina, Bolstad & Swank (1997) observed that there were consistent changes in water quality variables, concomitant with land-use change.
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Thus, nutrients from urban activities include large inputs of phosphorus to surface waters due to point sources of sewage and industrial effluents entering river systems indicating that cumulative organic inputs of agricultural and urban impacts have synergistic effects on water quality that have severe impacts on primary producer communities such as diatoms (Dallas & Day, 2004). Diatom community structure in relation to environmental variables Diatom community structure and composition in this study closely followed the observed changes in pollution levels as a result of changing land-use patterns, with less polluted sampling stations being associated with diatom communities that were different from highly polluted sampling stations. Cluster analysis of sampling stations based on epilithic algal communities in streams of the Manyame catchment area clearly reflected the effects of land-use in the catchment. The epilithic algal communities in this study were primarily affected by metal and nutrient concentrations in the streams resulting from agricultural runoff, mineral runoff, and urban runoff as confirmed by the findings of and Bere & Tundisi (2010a, b). Diatom communities in this study responded to these changes in water quality associated with changes in land-use as has been reported in other studies (Bere & Mangadze, 2014; Bere et al., 2014). Based on the CCA, the less polluted commercial agricultural sampling stations (Group 1) were characterized by species such as C. placentula, A.serians, A.muzzanensis, C.acidoclinata, C. minuta, D.ovalis, E.sorex, S.gracilior, S.linearis, S.robusta, and N. angusta. These species are known to prefer waters of lower ionic strength and conductivity (Lowe, 1974; Taylor et al., 2007b). However, these sampling stations had high calcium levels compared to the rest of the sampling stations. Pearsall (1932) states that in calcium-rich waters, diatom species dominate. Calcium is extremely important in the carbonate-bicarbonate buffering system, and because it brings about precipitation of many heavy metals and excessive phosphates, it is often beneficial to diatom growth. Conversely, streams having a low calcium-magnesium ratio are more prolific, and water is usually rich in nitrates, carbonates, bicarbonates, and silicates (Pearsall, 1932). Communal agricultural sampling
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stations were characterized by species such as P. divergens, G. accuminatum, E. formica, F. ulna, and F. saxonica. These species are known to be tolerant of ‘extremely polluted waters’ (Lowe, 1974; Telpy & Bahls, 2006; Taylor et al., 2007b). Hill et al. (2003) also reported that diatom species richness was positively correlated with total phosphorus and nitrogen also related to land-use pattern. Urban-mining sampling stations with high levels of TN, Ni, and Mg were characterized by species such as F. biceps, E. rhomboidea, G. pseudoaugur, F. elliptica, and N. linearis. Todd et al. (1996) and Mosisch et al. (2001) found that TN stimulated attached algal production in subtropical streams with sufficient light. This was also true in our study where TN was an important factor influencing the abundance and composition of diatoms. The diatom species found in urban-mining sampling stations in this study are known to be resistant to metal pollution (Duong et al., 2010). Lange-Bertalot (1979) also stated that species are indicative of the upper limits of pollution that they can tolerate and not the lower limit. Thus, these species, which develop well in polluted zones, may also occur in fairly clean water as has been observed in this study. Their value as pollution indicators is their presence in polluted water. Diatom communities in urban-mining areas were affected by both human activities and natural factors. This was because of the underlying geology, comprising a layered magma system largely composed of ultramafic rocks, which have larger deposits of gold, nickel, copper, chrome, and high Mg:Ca ratio. Weathered ultramafic rock material which contains some dissolved metals enters the river system draining the great dyke and deposits in slow moving waters polluting sediments and ultimately impairing biotic communities (Makore & Zano, 2012). For that reason, natural factors, geology of the Great Dyke in this case, were important in explaining diatom assemblage variability as supported by studies elsewhere (Sonneman et al., 2001; Rimet et al., 2004a; Dohet et al., 2008). Geology and ecoregion have often been used to explain diatom communities in the different regions of European (Rimet et al., 2004a, b; Bona et al., 2007; Tison et al., 2007; Tornes et al., 2007), American (Weilhoefer & Pan, 2006), and arctic rivers (Antoniades et al., 2009). However, in large river basins, the effects of geology and human impacts on diatom assemblages are mixed and become more difficult to
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identify and to separate (Rimet et al., 2004a, b). Basing on studies by Potapova & Charles (2002), there is a complex downstream gradient with many factors such as slope, elevation, concentration of nutrients, landuse, and temperature being correlated. For this reason, it was difficult to separate the effects of natural and anthropogenic factors on diatom communities in some land-use settings such as urban-mining areas in this study. Further studies are required to elucidate the effects of natural and anthropogenic factors on diatom communities in certain sections of the study area. However, variations in epilithic diatom communities among the 3 land-use settings identified in this study can be broadly attributed to land-use induced changes in water quality as we hypothesized. Thus, diatom assemblages can be used as indicators of landuse induced changes in water quality of lotic systems. The information gained through this study augments previous works on the use of diatoms in other regions and is a stepping stone toward development of diatombased biomonitoring protocols for Zimbabwean streams.
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