Abstract
AbstractThe 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.
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