Effects of lake-level changes on water quality and fisheries production of Lake Baringo, Kenya

被引:4
|
作者
Walumona, Jacques Riziki [1 ,2 ]
Kaunda-Arara, Boaz [1 ]
Odoli Ogombe, Cyprian [3 ]
Murakaru, James Mugo [3 ]
Raburu, Philip [1 ]
Muvundja Amisi, Fabrice [2 ,4 ]
Nyakeya, Kobingi [3 ]
Kondowe, Benjamin N. [1 ,5 ]
机构
[1] Univ Eldoret, Dept Fisheries & Aquat Sci, POB 1125-30100, Eldoret, Kenya
[2] Inst Super Pedag Bukavu ISP, Dept Biol Chim, Unite Enseignement & Rech Hydrobiol Appl UERHA, Bukavu, DEM REP CONGO
[3] Kenya Marine & Fisheries Res Inst, Baringo Stn, Marigat, Kenya
[4] Catholic Univ Bukavu UCB, Ctr Rech Environm & Georessources, Bukavu, DEM REP CONGO
[5] Mzuzu Univ, Dept Fisheries & Aquat Sci, Luwinga Mzuzu 2, Malawi
关键词
watershed management; fisheries; water quality parameters; waveform and Gaussian models; GREAT-LAKES; FLUCTUATIONS; FISH; MANAGEMENT; MOVEMENT; CLIMATE; WETLAND; MODEL;
D O I
10.1002/eco.2368
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
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.
引用
收藏
页数:12
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