In this study we have worked on the evaluation of heavy metal contamination in the sediments taken from the Tisza River and its tributaries, and thereby used the sequential extraction method, geochemical normalization, the calculation of the enrichment factor (EF), and the methods of statistical analysis. The chemical fractionation of Ni, Cu, Zn, Cr, Pb, Fe, and Mn, carried out by using the modified Tessier method, points to different substrates and binding mechanisms of Cu, Zn and Pb in sediments of the tributaries and sediments of the Tisza River. The similarities in the distributions of Fe and Ni in all types of sediments are the result of geochemical similarity as well as of the fact that natural sources mainly affect the concentration levels of these elements. The calculated enrichment factors (EF, measured metal vs. background concentrations) indicated that metal contamination (Cu, Pb, Zn and Cr) was recorded in the sediments of the Tisza River, while no indications of pollution were detected in the tributaries of the Tisza River and the surrounding pools. The maximum values of the EF were close to 6 for Cu and Pb (moderately severe enrichment) and close to 4.5 for Zn (indicating moderate enrichment). It can be said that the Tisza River is slightly to moderately severely polluted with Cu, Zn, and Pb, and minorly polluted with Cr. It is concluded that sediments of the Tisza serve as a repository for heavy metal accumulation from adjacent urban and industrial areas.
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http://dx.doi.org/10.1016/j.jenvman.2009.05.013 | DOI Listing |
Ecol Evol
June 2024
Instituto de Investigación en Recursos Cinegéticos (IREC)-(CSIC-UCLM-JCCM) Ciudad Real Spain.
In the intricate web of plant-animal interactions, granivore birds can play a dual antagonist-mutualist role as seed predators and dispersers. This study delves into the ecological significance of the house sparrow () as seed disperser by endozoochory. A sample of individual droppings and faecal pools were collected from a communal roost in central Spain to examine the presence of seeds.
View Article and Find Full Text PDFSci Data
June 2024
Department of River Ecology and Conservation, Senckenberg Research Institute and Natural History Museum Frankfurt, Gelnhausen, 63571, Germany.
Nat Ecol Evol
June 2024
University of Paris-Saclay, INRAE, HYCAR, Antony, France.
Inland navigation in Europe is proposed to increase in the coming years, being promoted as a low-carbon form of transport. However, we currently lack knowledge on how this would impact biodiversity at large scales and interact with existing stressors. Here we addressed this knowledge gap by analysing fish and macroinvertebrate community time series across large European rivers comprising 19,592 observations from 4,049 sampling sites spanning the past 32 years.
View Article and Find Full Text PDFJ Environ Manage
May 2024
Institute of Hydrobiology and Aquatic Ecosystem Management, University of Natural Resources and Life Sciences, Gregor-Mendel-Straße 33, 1180 Vienna, Austria; Christian Doppler Laboratory for Meta Ecosystem Dynamics in Riverine Landscapes - Research for Sustainable River Management, Institute of Hydrobiology and Aquatic Ecosystem Management, University of Natural Resources and Life Sciences, Gregor-Mendel-Straße 33, 1180 Vienna, Austria.
Floodplains provide an extraordinary quantity and quality of ecosystem services (ES) but are among the most threatened ecosystems worldwide. The uses and transformations of floodplains differ widely within and between regions. In recent decades, the diverse pressures and requirements for flood protection, drinking water resource protection, biodiversity, and adaptation to climate change have shown that multi-functional floodplain management is necessary.
View Article and Find Full Text PDFSensors (Basel)
November 2023
Department of Geoinformatics, Physical and Environmental Geography, University of Szeged, 6722 Szeged, Hungary.
Rivers transport terrestrial microplastics (MP) to the marine system, demanding cost-effective and frequent monitoring, which is attainable through remote sensing. This study aims to develop and test microplastic concentration (MPC) models directly by satellite images and indirectly through suspended sediment concentration (SSC) as a proxy employing a neural network algorithm. These models relied upon high spatial (26 sites) and temporal (198 samples) SSC and MPC data in the Tisza River, along with optical and active sensor reflectance/backscattering.
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