Lacustrine and riverine ecosystems provide important goods and services, including being habitats for aquatic biodiversity, local micro-climate moderation and a source of economic livelihoods for riparian communities. At the same time, however, they fact continuing anthropogenic and natural threats that can affect their water quality, ecological integrity and biodiversity. The present study focused on assessing spatiotemporal variations in water quality and trophic status of Lake Baringo, a Ramsar site in Kenya. A number of physicochemical parameters, including nutrient loads, trophic status and organic pollution indices, were evaluated for the lake from water samples collected from March 2008 to December 2020. The results of the present study indicated five parameters (turbidity, fluoride, SiO 4 − 4 , total phosphorus and DO) exceeded the permissible limits for drinking water based on WHO standards. The water quality index (WQI) values ranged between 556.04 and 693.54, being well above the WHO recommended limit (WQI = 100), indicating Lake Baringo water to be unsuitable for human consumption. The fluoride (F − ) ions and water turbidity contributed the most relative weights to the lake's WQI. The organic pollution index (OPI) for the lake varied from 4.33 to 4.67, significantly above the organic pollution scale of 1.0-3.9 and indicating the lake is not organically polluted. A positive relationship was found between turbidity and rainfall, suggesting the influence of catchment activities on the lake. The nutrient load had less effect on both the WQI and OPI of the lake, indicating low inputs from the catchment. The lake's trophic status shifted between eutrophic and mesotrophic conditions from 2008 to 2020, based on the Carlson's trophic status index (CTSI) values. Application of a holistic and integrated lake basin management (ILBM) approach is recommended for the management of Lake Baringo and its watershed in order to sustain its ecological processes and the associated riparian community economic livelihood support from the lake.
Expansion of agriculture is particularly worrying in tropical regions of the world, where native forests have been replaced by croplands and grasslands, with severe consequences for biodiversity conservation and ecosystem functioning. However, limited data exist on the effects of agriculture on the functioning of tropical streams. We conducted a leaf litter decomposition experiment in coarse- and fine-mesh litterbags using the three species of leaves (Eucalyptus globulus [non-native], Vernonia myriantha, and Syzygium cordatum [indigenous]) in three forested and agricultural streams to determine the effect of agriculture on instream leaf litter decomposition in headwater stream sites. We also examined the functional composition of macroinvertebrates in the streams through the contents of benthic kick samples. Agricultural streams had a less dense riparian canopy and smaller abundance of coarse organic particulate matter, and higher electric conductivity and suspended solids than forested streams. In terms of the effects of litter quality on decomposition rates, Vernonia had the fastest decomposition rates while Eucalyptus had the slowest in both forested and agricultural sites. Shredder invertebrates were less abundant in agricultural streams, and in both stream types, they were less diverse and abundant than other functional groups. Overall, leaf litter decomposition rates did not respond to agricultural land-use. The hypothesized negative effects of agriculture on organic matter processing were minimal and likely modulated by intact riparian zones along agricultural streams.
The study was conducted in Lake Baringo, Kenya, and determined quantitative relationships between water‐level changes, water quality, and fishery production for purposes of evidence‐based lake basin management. Long‐term data on water level (1956–2020), water quality (2008–2021), and fisheries yields (1982–2021) from Lake Baringo were analysed using a combination of statistical methods. Linear and waveform regression analyses were used to describe patterns of lake‐level fluctuations over time, while Pearson's correlation was applied to determine the concordance of lake level changes with water quality parameters, landings, and condition of fish species. Principal components analysis (PCA) results grouped the study period into different years based on annual water quality variable levels. Locally weighted scatter plot smoothing (LOWESS) analysis showed the annual lake level amplitude declined over time with peak values in 1964 (8.6 m) and 2008 (9.4 m). The waveform regression significantly modelled lake‐level fluctuations as indexed by annual deviations from the long‐term average (DLTM) and showed a 20‐year oscillation between peak water levels in the lake. There were significant positive correlations of water‐level fluctuations (WLFs) with water quality variables and water quality index (WQI) in Lake Baringo. Linear regression analyses showed a significant concordance (p < 0.05) between the annual fishery yields and the rising WLFs (r = 0.66). Also, there was a significant (p < 0.001) relationship between the condition factor of the native species, Oreochromis niloticus, and the annual lake level amplitude (r = 0.69), while catches of the lungfish, Protopterus aethiopicus, and Labeobarbus intermedius showed a differing relationship with WLFs in the lake indicating a species‐specific influence of WLFs on catches. Overall, the results demonstrate that WLFs of Lake Baringo are a significant driver of fish species biomass, species condition, and physico‐chemical properties of the lake.
Small waterbodies are the most threatened freshwater habitats because of the large ratio between their size and the catchment they drain. The present study assessed the current and historical changes in the physical, chemical and biological variables of Lake Kanyaboli, a satellite lake on the northern shores of Lake Victoria in western Kenya. Primary and secondary data on pH, electrical conductivity (EC), dissolved oxygen (DO) concentration, temperature, Secchi depth (SD), and nitrate (NO − 3 ), nitrite (NO − 2 ), ammonium (NH + 4 ), soluble reactive phosphorus (SRP), total nitrogen (TN), and total phosphorus (TP) and chlorophyll-a (Chl-a) concentrations were utilized in the present study. The results indicated Secchi depth and chlorophyll-a were the most erratic of all the analyzed environmental variables studied, exhibiting a range of 0.69 ± 0.29-0.87 ± 0.34 m and 9.03 ± 0.81-34.97 ± 3.36 µg/L respectively. Two-way ANOVA yielded no significant interactions between sampling sites and seasons for all the variables. Except chlorophyll-a, there also were no significant differences among the sampling sites for the studied variables. Seasonality yielded significant differences for Secchi depth, dissolved oxygen and chlorophyll-a. The Carlson Trophic Index for Chl-a and SD indicated Lake Kanyaboli is currently eutrophic, while the TP concentration indicated hypereutrophic conditions. The lake, however, has fluctuated between eutrophic and hypereutrophic conditions over the past years. Although historical water quality data for the lake is scanty and infrequent, most physical and chemical variables reflected anthropogenic effects on a temporal scale. Interestingly, despite its eutrophic status, the general lake condition is still relatively good, attributable to the buffering effect from the extensive macrophytes fringing it. The present study identified nutrient loading, wetland reclamation and connectivity with the Yala River through a feeder canal as the management issues of critical concern. Accordingly continuous monitoring of the lake's water quality to detect anthropogenic effects is recommended for management intervention purposes.
The study was conducted in Lake Baringo and determined quantitative relationships between water level changes, water quality, and fishery production for informed lake basin management. Long-term (2008 to 2020) data on water level, water quality, and fisheries yields from Lake Baringo were analyzed using a combination of statistical methods. Linear and waveform regression analyses described patterns of lake level fluctuations over time while, Pearson’s correlation determined the concordance of lake level changes with water quality parameters, landings, and condition of fish species. PCA results grouped the study period into different years based on annual water quality variable levels. LOWESS analysis showed the decline of annual lake level amplitude over time with peak values in 1964 (8.6 m) and 2008 (9.4 m). The waveform regression significantly modeled lake level fluctuations as indexed by annual deviations from the long-term average (DLTM) and showed a 20-year oscillation between peak water levels in the lake. There were significant positive correlations of Water Level Fluctuations (WLFs) with water quality variables and water quality index (WQI) in Lake Baringo. Linear regression analyses showed a significant concordance (p < 0.05) between the annual fishery yield and the rising WLFs (r = 0.66). Overall, the results demonstrate that WLFs of Lake Baringo are a driver of fish species biomass and physico-chemical properties of the lake. We recommend the integration of fisheries yields, water quality assessment, and WLFs modeling at different temporal scales in the management of Afrotropical lake ecosystems
Factors influencing the spatio-temporal dynamics of plankton communities in small tropical lakes are not well-understood. This study assessed plankton communities in response to spatial (six sampling sites) and seasonal (wet vs. dry seasons) changes in environmental variables in Lake Kanyaboli, a small satellite lake on the northern shores of Lake Victoria, Kenya. Water quality variables, including pH, conductivity (EC), dissolved oxygen (DO), temperature, Secchi depth (SD), nitrates (NO3-), nitrites (NO2-), ammonium (NH4+), soluble reactive phosphorus (SRP), total nitrogen (TN), total phosphorus (TP), and chlorophyll-a (Chl-a), were monitored monthly at six sites spread throughout the lake for 1 year. Phytoplankton and zooplankton samples were collected and analyzed for taxon composition and abundance. Two-way ANOVA showed no significant interaction between site and season for all variables. Likewise, there were no significant spatial differences for all variables except Chl- a. A t-test showed significant seasonal differences in SD, DO, NH4+, NO3-, NO2-, and TN. Thirty phytoplankton genera were identified belonging to Bacillariophyceae, Chlorophyceae, Cryptophyceae, Cyanophyceae, Euglenoidae, Trebouxiophyceae, and Zygnematophyceae, with Chlorophyceae being the most dominant (42.30%). Zooplankton comprised of 15 genera, belonging to Copepoda (55.4%), Rotifera (27.9%), and Cladocera (16.7%). Two-way ANOVA for plankton abundance showed no significant interaction between site and season, but there were significant differences in community composition between the wet and dry seasons. Canonical correspondence analysis identified water clarity (Secchi depth) and concentrations of dissolved fractions of nitrogen and phosphorus as the major water quality variables driving variation in the composition of plankton communities in the lake. This study showed that seasonality was a major driver of changes in plankton community composition between dry and wet seasons through changes in the concentrations of nutrients (NH4+, NO3-, NO2-, TN, and TP). Lake Kanyaboli's phytoplankton community indicated a non-equilibrial state, perhaps due to short residence times of water, especially during the wet season, and dense macrophytes fringing the lake that increase nutrient uptake and limit the dominance of select phytoplankton species. This study shows the importance of long-term studies covering dry and wet seasons to understand the dynamics of plankton communities and their drivers in small tropical waterbodies to inform management and conservation.
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