scholarly journals Water‐level fluctuations and metapopulation dynamics as drivers of genetic diversity in populations of three Tanganyikan cichlid fish species

2013 ◽  
Vol 22 (15) ◽  
pp. 3933-3948 ◽  
Author(s):  
B. Nevado ◽  
S. Mautner ◽  
C. Sturmbauer ◽  
E. Verheyen
2016 ◽  
Author(s):  
Thijs Janzen ◽  
Rampal S. Etienne

ABSTRACTGeographic isolation that drives speciation is often assumed to slowly increase over time, for instance through the formation of rivers, the formation of mountains or the movement of tectonic plates. Cyclic changes in connectivity between areas may occur with the advancement and retraction of glaciers, with water level fluctuations in seas between islands or in lakes that have an uneven bathymetry. These habitat dynamics may act as a driver of allopatric speciation and propel local diversity. Here we present a parsimonious model of the interaction between cyclical (but not necessarily periodic) changes in the environment and speciation, and provide an ABC-SMC method to infer the rates of allopatric and sympatric speciation from a phylogenetic tree. We apply our approach to the posterior sample of an updated phylogeny of the Lamprologini, a tribe of cichlid fish from Lake Tanganyika where such cyclic changes in water level have occurred. We find that water level changes play a crucial role in driving diversity in Lake Tanganyika. We note that if we apply our analysis to the Most Credible Consensus (MCC) tree, we do not find evidence for water level changes influencing diversity in the Lamprologini, suggesting that the MCC tree is a misleading representation of the true species tree. Furthermore, we note that the signature of habitat dynamics is found in the posterior sample despite the fact that this sample was constructed using a species tree prior that ignores habitat dynamics. However, in other cases this species tree prior might erase this signature. Hence we argue that in order to improve inference of the effect of habitat dynamics on biodiversity, phylogenetic reconstruction methods should include tree priors that explicitly take into account such dynamics.


Author(s):  
Jacques Walumona ◽  
Boaz Arara ◽  
Cyprian Ogombe ◽  
James Murakaru ◽  
Phillip Raburu ◽  
...  

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


2020 ◽  
Vol 10 (17) ◽  
pp. 9410-9418
Author(s):  
Lukas Widmer ◽  
Adrian Indermaur ◽  
Bernd Egger ◽  
Walter Salzburger

Author(s):  
Krum Videnov ◽  
Vanya Stoykova

Monitoring water levels of lakes, streams, rivers and other water basins is of essential importance and is a popular measurement for a number of different industries and organisations. Remote water level monitoring helps to provide an early warning feature by sending advance alerts when the water level is increased (reaches a certain threshold). The purpose of this report is to present an affordable solution for measuring water levels in water sources using IoT and LPWAN. The assembled system enables recording of water level fluctuations in real time and storing the collected data on a remote database through LoRaWAN for further processing and analysis.


1985 ◽  
Vol 11 (1) ◽  
pp. 179-183
Author(s):  
Jean-Luc Borel ◽  
Jacques-Léopold Brochier ◽  
Karen Lundström-Baudais

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