To investigate the influence of human activities on limnological characteristics of Lake Victoria, we analyzed inorganic nutrient concentrations, phytoplankton diversity and biomass at three locations with different land use patterns: Mwanza (urban/industrial), Magu (agricultural) and Kayenze (sparsely populated). Mwanza had significantly higher ammonia concentration compared to Kayenze and Magu. At the shoreline stations, significantly higher nitrate concentration was observed at Mwanza compared to Kayenze and Magu. Similarly, Mwanza had significantly higher concentrations of soluble reactive phosphorous in the shoreline stations compared to Magu and Kayenze, but not in the open waters stations. Shoreline stations also showed significant differences in phytoplankton diversity among sites. The shoreline station at Mwanza also showed significantly higher levels of Chl. a compared to those at Magu and Kayenze. However, in the open water stations Chl. a concentrations did not differ significantly among sites. The results suggested that urban pollution in Mwanza and agricultural activities in River Simiyu catchment strongly influence the limnology of Lake Victoria and that the nearshore waters, which are the receiving points, were highly impacted compared to the waters outside bays. Thus, proper urban waste management and sustainable land management practices are critical for reducing point and non-point sources of pollution into Lake Victoria.
Lake Victoria, covering an area of about 69,000 km2, is the largest inland lake in Africa and the second largest freshwater in the world. The lake has a total basin area of ca. 184,000 km2 with Tanzania accounting for about 44% (Kite, 1982). However, over the past four decades or so, Lake Victoria has come under increasing and considerable pressure from a variety of interlinked human activities such as overfishing, introduction of exotic species, industrial pollution, eutrophication, and sedimentation (Odada et al., 2004). In Tanzania, the river basins polluting the lake are mainly Mara, Kagera, and Simiyu with the latter being the major contributors because of its large area and extensive agricultural activities (Rwetabula, 2007). For example, the estimated total phosphorous load produced by the Simiyu River into Magu Bay is 709 tons per year, of which 15% are contributed by agricultural land (Rwetabula, 2007).
To investigate the influence of human activities on limnological characteristics of Lake Victoria, we analyzed inorganic nutrient concentrations, phytoplankton diversity and biomass in three locations with different land use patterns: urban/industrial, agricultural and sparsely populated.
Material and Methods
The catchment basin in the study area is generally flat and dominated by wasteland, bushland, cultivated land and grassland (Rwetabula, 2007). Three sampling sites, i.e. Mwanza North Bay (MZ), Magu Bay (MG) and Kayenze Bay (KY), were established (Figure 1). Site MZ receives water from Mirongo River, which drains an industrial area and the densely populated city of Mwanza. Site MG is fed by River Simiyu (with stream flow ranging from 0–200 m3 s−1) that drains agricultural and livestock keeping areas (Rwetabula 2007). Site KY has no direct inlet and is situated in a remote area with sparse settlements. At each sampling site, three sampling stations (abbreviated MZ1, MZ2 and MZ3 for site MZ; MG1, MG2 and MG3 for site MG and KY1, KY2 and KY3 for site KY) running perpendicular to the shoreline towards the open waters were established. Station one was about 0.5 km from the shoreline while station two and three were about 6 km and 10 km from the shoreline, respectively. Sampling was conducted on average after every two months from December 2004 to December 2005. Triplicate surface water (0.5 m) samples were collected using a water bottle for determination of inorganic nutrient concentration, total suspended solids (TSS), and phytoplankton biomass. Water temperature, pH and electrical conductivity were measured in situ using a portable conductivity/pH/salinity/temperature meter (Model 1XYSI-63-100). Water transparency was measured in situ using a 20 cm diameter Secchi disc.
Water samples for analysis of inorganic nutrients were filtered using GF/C filters and kept frozen in 20 ml plastic vials. Analysis was done using a spectrophotometer according to APHA (1995). TSS was analyzed gravimetrically as described in APHA (1995). Samples for analysis of phytoplankton abundance were fixed with Lugol's solution and stored in darkness. Analysis was done using the Utermöhl method (1958). Chlorophyll a analysis was done using a spectrophotometer as described by Seeley and Jensen (1965). Samples for determination of phytoplankton species were collected by towing a 20 μm (mesh size) plankton net, and were preserved with 2.5% formalin. Phytoplankton identification was done under a light microscope following the description given by Komareck and Anagnostidis (1985); Mosille (1984) and Van Meel (1954).
To test the differences among sites and stations we used the parametric One–way ANOVA or the non parametric Kruskal–Wallis test coupled with their associated Tukey–Kramer or Dunn's multiple comparison tests, respectively. Correlations among parameters were tested using the Pearson r test.
Results for water temperature, conductivity, pH, TSS and water transparency are presented in Table 1. There was no significant difference in water temperature, conductivity and water pH values among the sampling sites (F = 0.38; p = 0.67; F = 0.32; p = 0.73 and F = 0.26, p = 0.76, respectively). However, TSS values were significantly higher at site MG compared to the other sampling sites (F = 8.26, p = 0.002). In addition, site MG showed significantly low transparency values compared to the rest of the sampling sites (F = 8.0; p = 0.003).
Site MZ had higher ammonia (NH4+) concentration compared to site KY and MG (Figure 2). The shoreline station at MZ had the highest NH4+ concentrations throughout the sampling period while KY shoreline station had consistently low values. There was a significant difference in NH4+ concentrations between the shoreline stations (KW = 25.094; p < 0.0001). The significant differences were detected between MZ1 and MG1 (p < 0.01) and between MZ1 and KY1 (p < 0.001). Similarly in the open water stations the concentrations of ammonia varied significantly among sites (KW = 6.33; P = 0.042). The significant difference was between MZ3 and KY3 (p < 0.05). Nitrate (NO3) levels were higher in the shoreline stations compared to open water stations at site MZ and MG while at site KY the levels tended to increase towards the open waters (Figure 3). There was a significant difference in nitrate concentration among the three shoreline stations (KW = 23.804; p < 0.0001) with the post hoc test revealing significantly higher nitrate levels at station MZ1 compared to station KY1 (p < 0.001) and at station MG1 compared to station KY1 (p < 0.001). Soluble Reactive Phosphorous (SRP) did not show clear trend between inshore and offshore stations at both sites (Figure 4). Site MZ had the highest concentrations of SRP in the shoreline stations that differed significantly with Magu and Kayenze Bay stations (KW = 13.559; p = 0.0011). However, in the stations outside the bays the concentrations of SRP did not vary significantly (KW = 0.300; p = 0.445) among the three sites.
A total of 131 phytoplankton taxa were encountered during the present study. 43.5% of these were Cyanophyta, 36.6% Chlorophyta, 14.5% Bacillariophyta, 3.1 Chrysophyta and 2.3% Dinophyta. A significant difference in phytoplankton diversity among the three study sites was observed (F = 4.57, p = 0.01) with the differences being between site MG and KY (p < 0.05) but not between sites MZ and KY nor between sites MZ and MG (p > 0.5). In general, phytoplankton biomass (Chl. a) did not show clear trends of variability as you move from the near shore stations to the offshore stations (Figure 5). However, significant differences in Chl. a were observed among the sampling sites (F = 4.35, p = 0.014). Post hoc tests revealed significant differences to be between site MZ and KY (P < 0.05) but not between sites MZ and MG nor between sites MG and KY. Also the shoreline station at site MZ showed significantly higher Chl. a compared to the shoreline stations at sites MG and KY (F = 5.57, p = 0.006). In the open water stations Chl. a concentrations did not differ significantly among sites (F = 1.66, p = 0.19).
Phytoplankton biomass (Chl. a) at site MZ correlated significantly and positively with TSS, water transparency and SRP (r = 0.63, p = 0.002; r = 0.43, p = 0.031 and r = 0.73, p = 0.0001; respectively) and significantly but negatively with NO3 (r = 0.46, p = 0.03). At site MG, Chl. a correlated significantly and positively with water transparency and water temperature (r = 0.32, p = 0.03 and r = 0.44, p = 0.04, respectively). Also, there was a significant but negative correlation between Chl. a with TSS and water conductivity (r = −0.50, p = 0.04 and r = −0.45, p = 0.03, respectively). At site KY Chl. a showed significant positive correlations with TSS, water transparency, temperature and NH4+ content (r = 0.47, p = 0.03; r = 0.65, p = 0.001; r = 0.47, p = 0.03 and r = 0.44, p = 0.04).
Water temperature values observed in this study were higher than those reported in the previous studies by Akiyama et al. (1977) and Worthington (1930) for example, suggesting that the lake is warming up. However, Secchi depth readings in this study were generally lower than those recorded in the above mentioned studies, which may be a sign of increased turbidity of the water. The significant higher TSS values in Magu Bay compared to those recorded in other sites may be due to Simiyu River which brings large quantities of suspended material collected from agricultural and pasture areas. Also, the significantly lower Secchi disk readings in Magu Bay were due to higher TSS values recorded at this particular site.
NO3 and SRP levels obtained in this study were generally higher compared to those reported by Talling (1965). This confirms earlier observations that inorganic nutrient levels are increasing (Hecky, 1993). The observed higher nutrient concentrations within bay stations and the fact that nutrient levels within bays stations vary significantly among sites, could be attributed to the fact that inshore stations are the receiving points for industrial effluents, municipal wastewater and runoff containing agrochemicals. The low level of inorganic nutrient concentrations at site KY was possibly due to the remoteness of this site, absence of river input and sparse population in the area.
The levels of phytoplankton biomass (Chl. a) obtained in this study were comparable to those reported by Mugidde (1993), but higher compared to those reported by Talling (1965). The shoreline station at Mwanza North Bay showed significantly higher levels of Chl. a compared to Magu and Kayenze Bay shoreline stations, conforming to the general trend in inorganic nutrient distribution. The significant positive correlation between phytoplankton biomass (Chl. a) and water transparency at all sampling sites indicate that turbid waters in the inshore stations hindered phytoplankton growth. In general, our results indicated a tendency for Chl. a to increase towards the open waters compared to the stations located within the bay. This further suggested light limitation within bay stations due to turbidity.
A comparison of our results on the floristic composition of micro-algae of Lake Victoria with previous data (Cocquyt et al., 1993; Lung’ayia et al., 2000) indicated that cyanobacteria were increasing in relation to other taxonomic groups, confirming earlier observations by Kling et al. (2001) for example. This shift in dominance from the historic algal community dominated by diatoms to cyanobacteria was suggested to be evidence of increased phosphorous loading in relation to N levels in Lake Victoria (Kling et al., 2001). Indeed, concentrations of total phosphorous in Lake Victoria are now more than double the total phosphorous concentrations reported in the early 1960s, with the main route of phosphorous loading into the lake being atmospheric deposition (Tamatamah et al., 2005).
In conclusion, results from this study suggest that urban wastes in Mwanza area and agricultural activities in Simiyu River catchment strongly influence the limnological characteristics of the south-eastern part of Lake Victoria. The receiving point inshore waters are highly impacted compared to offshore waters where dilution and other physical chemical processes possibly tend to ameliorate the problem. Thus, management measures geared to reducing sources of pollution (e.g. through proper urban waste management and sustainable land management practices) in the lake basin should be promoted in order to curb further degradation of the lake. Continued monitoring of the lake's limnology is important to elucidate the effectiveness of the management measures.
We are thankful to the Lake Victoria Environmental Management Project (LVEMP), “Support to Riparian University Component,” University of Dar es Salaam, for the financial support.