No abstract

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.

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.

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