Literature DB >> 29245035

Multiple long-term trends and trend reversals dominate environmental conditions in a man-made freshwater reservoir.

Petr Znachor1, Jiří Nedoma2, Josef Hejzlar2, Jaromír Seďa2, Jiří Kopáček2, David Boukal3, Tomáš Mrkvička4.   

Abstract

Man-made reservoirs are common across the world and provide a wide range of ecological services. Environmental conditions in riverine reservoirs are affected by the changing climate, catchment-wide processes and manipulations with the water level, and water abstraction from the reservoir. Long-term trends of environmental conditions in reservoirs thus reflect a wider range of drivers in comparison to lakes, which makes the understanding of reservoir dynamics more challenging. We analysed a 32-year time series of 36 environmental variables characterising weather, land use in the catchment, reservoir hydrochemistry, hydrology and light availability in the small, canyon-shaped Římov Reservoir in the Czech Republic to detect underlying trends, trend reversals and regime shifts. To do so, we fitted linear and piecewise linear regression and a regime shift model to the time series of mean annual values of each variable and to principal components produced by Principal Component Analysis. Models were weighted and ranked using Akaike information criterion and the model selection approach. Most environmental variables exhibited temporal changes that included time-varying trends and trend reversals. For instance, dissolved organic carbon showed a linear increasing trend while nitrate concentration or conductivity exemplified trend reversal. All trend reversals and cessations of temporal trends in reservoir hydrochemistry (except total phosphorus concentrations) occurred in the late 1980s and during 1990s as a consequence of dramatic socioeconomic changes. After a series of heavy rains in the late 1990s, an administrative decision to increase the flood-retention volume of the reservoir resulted in a significant regime shift in reservoir hydraulic conditions in 1999. Our analyses also highlight the utility of the model selection framework, based on relatively simple extensions of linear regression, to describe temporal trends in reservoir characteristics. This approach can provide a solid basis for a better understanding of processes in freshwater reservoirs.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Model selection; Piecewise regression; Regime shift; Time series

Year:  2017        PMID: 29245035     DOI: 10.1016/j.scitotenv.2017.12.061

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  4 in total

1.  Light and Primary Production Shape Bacterial Activity and Community Composition of Aerobic Anoxygenic Phototrophic Bacteria in a Microcosm Experiment.

Authors:  Kasia Piwosz; Ana Vrdoljak; Thijs Frenken; Juan Manuel González-Olalla; Danijela Šantić; R Michael McKay; Kristian Spilling; Lior Guttman; Petr Znachor; Izabela Mujakić; Lívia Kolesár Fecskeová; Luca Zoccarato; Martina Hanusová; Andrea Pessina; Tom Reich; Hans-Peter Grossart; Michal Koblížek
Journal:  mSphere       Date:  2020-07-01       Impact factor: 4.389

2.  Niche-directed evolution modulates genome architecture in freshwater Planctomycetes.

Authors:  Adrian-Ştefan Andrei; Michaela M Salcher; Maliheh Mehrshad; Pavel Rychtecký; Petr Znachor; Rohit Ghai
Journal:  ISME J       Date:  2019-01-04       Impact factor: 10.302

3.  Long-Term Interannual and Seasonal Links between the Nutrient Regime, Sestonic Chlorophyll and Dominant Bluegreen Algae under the Varying Intensity of Monsoon Precipitation in a Drinking Water Reservoir.

Authors:  Ji Yoon Kim; Usman Atique; Md Mamun; Kwang-Guk An
Journal:  Int J Environ Res Public Health       Date:  2021-03-11       Impact factor: 3.390

4.  Diel changes and diversity of pufM expression in freshwater communities of anoxygenic phototrophic bacteria.

Authors:  Lívia Kolesár Fecskeová; Kasia Piwosz; Martina Hanusová; Jiří Nedoma; Petr Znachor; Michal Koblížek
Journal:  Sci Rep       Date:  2019-12-10       Impact factor: 4.379

  4 in total

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