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Magyari EK, Szabó Z, Falus G, Móra A, Szalai Z, Hamerlik L, Tóth M, Farkas Á, Pomogyi P, Somogyi B, Vörös L, Korponai J. Large shallow lake response to anthropogenic stressors and climate change: Missing macroinvertebrate recovery after oligotrophication (Lake Balaton, East-Central Europe). THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 946:174191. [PMID: 38945249 DOI: 10.1016/j.scitotenv.2024.174191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 06/20/2024] [Accepted: 06/20/2024] [Indexed: 07/02/2024]
Abstract
East-Central Europe's largest shallow lake, Balaton, experienced strong eutrophication in the 1970-80s, followed by water quality improvement and oligotrophication by 2010 CE. Recently however, repeated cyanobacterial blooms occurred and warned that internal P-recycling can act similarly to external P load, therefore we need a better understanding of past water level (WL) and trophic changes in the lake. In this study we discuss the last 500-yr trophic, WL and habitat changes of the lake using paleoecological (chironomids, pollen) and geochemical (sediment chlorophyll, TOC, TS, TN, C/H ratio, major and trace element) methods. We demonstrate that the most intensive and irreversible change in the macroinvertebrate fauna occurred during the period of economic boom between the First and Second World War (∼1925-1940 CE), when large-scale built-in and leisure use of the lake has intensified. At that time, the Procladius-Microchironomus-Stempellina dominated community transformed to Procladius-Chironomus plumosus-type-Microchironomus community that coincided with land use changes, intensified erosion and water-level regulation in the lake with the maintenance of year-round high WL. This was followed by the impoverishment and population size decrease of the chironomid fauna and Procladius dominance since 1940 CE, without any recovery after 1994 CE despite the ongoing oligotrophication. Accelerated rate of change and turnover of the fauna was connected to an increase in the benthivorous fish biomass and eutrophication. The basin lost almost completely its once characteristic Stempellina species between 1927 and 1940 CE due to trophic level increase and seasonal anoxia in the Szemes Basin. Reference conditions for ecosystem improvement were assigned to 1740-1900 CE. We conclude that in spite of the ongoing oligotrophication, the re-establishment of the Procladius-Microchironomus-Stempellina assemblage is hampered, and requires fish population regulation.
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Affiliation(s)
- E K Magyari
- Department of Environmental and Landscape Geography, Eötvös Loránd University, Pázmány Péter str. 1/C, Budapest H-1117, Hungary; HUN-REN-MTM-ELTE Research group for Palaeontology, Pázmány Péter str. 1/C, Budapest H-1117, Hungary.
| | - Z Szabó
- Department of Environmental and Landscape Geography, Eötvös Loránd University, Pázmány Péter str. 1/C, Budapest H-1117, Hungary
| | - Gy Falus
- Mining and Geological Survey of Hungary, Columbus str. 17-23., Budapest H-1145, Hungary
| | - A Móra
- University of Pécs, Department of Hydrobiology, Ifjúság útja 6, Pécs H-7624, Hungary
| | - Z Szalai
- Department of Environmental and Landscape Geography, Eötvös Loránd University, Pázmány Péter str. 1/C, Budapest H-1117, Hungary; Geographical Institute, Research Centre for Astronomy and Earth Sciences, Budaörsi út 45, Budapest H-1112, Hungary
| | - L Hamerlik
- Matej Bel University, Faculty of Natural Sciences, Tajovskeho 40, 97401 Banská Bystrica, Slovakia; Institute of Zoology, Slovak Academy of Sciences, Dúbravská cesta 9, Bratislava, Slovakia
| | - M Tóth
- Balaton Limnological Research Institute, Klebelsberg Kuno utca 3., Tihany H-8237, Hungary
| | - Á Farkas
- HUN-REN ATOMKI, Bem tér 18/c, Debrecen H-4026, Hungary
| | - P Pomogyi
- Mid-Transdanubian Water Directorate, Balatoni út 6, Székesfehérvár H-8000, Hungary
| | - B Somogyi
- HUN-REN Balaton Limnological Research Institute, Klebelsberg Kuno utca 3, Tihany H-8237, Hungary
| | - L Vörös
- HUN-REN Balaton Limnological Research Institute, Klebelsberg Kuno utca 3, Tihany H-8237, Hungary
| | - J Korponai
- Department of Environmental and Landscape Geography, Eötvös Loránd University, Pázmány Péter str. 1/C, Budapest H-1117, Hungary; University of Public Service, Faculty of Water Sciences, Department of Water Supply and Sewerage, Bajcsy-Zsilinszky utca 12-14, Baja H-6500, Hungary; Department of Environmental Science, Sapientia Hungarian University of Transylvania, Calea Turzii 4, 400193 Cluj-Napoca, Romania
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Volf G, Žutinić P, Gligora Udovič M, Kulaš A, Mustafić P. Describing and simulating phytoplankton of a small and shallow reservoir using decision trees and rule-based models. ENVIRONMENTAL MONITORING AND ASSESSMENT 2023; 195:508. [PMID: 36964248 DOI: 10.1007/s10661-023-11060-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 02/25/2023] [Indexed: 06/18/2023]
Abstract
Phytoplankton represents one of the most important biological components of primary production, trophic interactions, and circulation of organic matter in lakes and reservoirs. To contribute to the understanding of eutrophication processes and ecological status of the small, shallow Butoniga reservoir, a machine learning tool for induction of models in form of decision trees and rule-based models was applied on a dataset comprising physical, chemical, and biological variables measured at four stations. Two types of models were successfully elaborated, i.e., (1) model describing phytoplankton Phylum, which describes and connects phytoplankton Phylum with phytoplankton abundance and biomass, and (2) model simulating phytoplankton biomass according to environmental variables which could be used in management purposes. Such models and their presentation contribute to a better understanding of the Butoniga reservoir ecosystem functioning.
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Affiliation(s)
- Goran Volf
- Department of Hydraulic Engineering, Faculty of Civil Engineering, University of Rijeka, Radmile Matejčić 3, 51000, Rijeka, Croatia.
| | - Petar Žutinić
- Department of Biology, Faculty of Science, University of Zagreb, Rooseveltov trg 6, 10000, Zagreb, Croatia
| | - Marija Gligora Udovič
- Department of Biology, Faculty of Science, University of Zagreb, Rooseveltov trg 6, 10000, Zagreb, Croatia
| | - Antonija Kulaš
- Department of Biology, Faculty of Science, University of Zagreb, Rooseveltov trg 6, 10000, Zagreb, Croatia
| | - Perica Mustafić
- Department of Biology, Faculty of Science, University of Zagreb, Rooseveltov trg 6, 10000, Zagreb, Croatia
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Li X, Zhao Y, Chai F, Yu H, Sun X, Liu D. Phytoplankton Community Structure Dynamics in Relation to Water Environmental Factors in Zhalong Wetland. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:14996. [PMID: 36429711 PMCID: PMC9690911 DOI: 10.3390/ijerph192214996] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 11/07/2022] [Accepted: 11/08/2022] [Indexed: 06/16/2023]
Abstract
Phytoplankton, as the primary producer of the wetland water ecosystem's food chain, are very sensitive to environmental changes. In order to explore the significance of phytoplankton in protecting ecosystem integrity, the wetland ecosystem in Zhalong wetland, one of the most important international wetlands, was selected as the research area. For the study, 81 sampling sites were set up in the whole wetland, and phytoplankton samples and water quality environmental factors were measured in spring, summer, and autumn of 2019. The phytoplankton community structure and water environmental factors were evaluated by canonical correspondence analysis (CCA). The main research findings are as follows: a total of 292 species and variants of phytoplankton belonging to 8 phyla and 110 genera were identified within Zhalong wetland in spring, summer, and autumn 2019. The total phytoplankton abundance and biomass in summer were higher than in spring and autumn, and Cyclotella meneghiniana was the most dominant species in three seasons and three areas. The results of random forest are generally consistent with the results of CCA in spring, when the main environmental factors affecting phytoplankton were NTU and WT; the result in summer and autumn agreed with those of CCA, which awaits further study. In addition, the phytoplankton is mainly affected by WT, depth, and DO in the lake area, TP, DO, and NTU in the river area, and WT in the wetland area.
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Affiliation(s)
- Xiaoyu Li
- School of Fishery, Zhejiang Ocean University, Zhoushan 316022, China
- College of Wildlife and Protected Area, Northeast Forestry University, Harbin 150040, China
| | - Yuxi Zhao
- Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China
| | - Fangying Chai
- School of Management, Heilongjiang University of Science and Technology, Harbin 150020, China
| | - Hongxian Yu
- College of Wildlife and Protected Area, Northeast Forestry University, Harbin 150040, China
| | - Xu Sun
- College of Wildlife and Protected Area, Northeast Forestry University, Harbin 150040, China
- College of Fisheries and Life Science, Dalian Ocean University, Dalian 116023, China
| | - Di Liu
- Heilongjiang Provincial Water Conservancy and Hydroelectric Power Investigation Design and Research Institute, Harbin 150080, China
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Song W, Li J, Zhang X, Fu C, Wang Z, Wang Z. Algae-containing raw water treatment and by-products control based on ClO 2 preoxidation-assisted coagulation/precipitation process. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2022; 44:3837-3851. [PMID: 34713368 DOI: 10.1007/s10653-021-01055-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Accepted: 07/26/2021] [Indexed: 06/13/2023]
Abstract
Eutrophication has become a great concern in recent years with the algae blooms in source water resulting in a serious threat posing to the safety of drinking water. Chlorine dioxide (ClO2) has been served as an alternative oxidant for preoxidation or disinfection during drinking water treatment process due to its high oxidation efficiency and low risk of organic by-products formation. However, the generation of inorganic by-products including chlorite (ClO2-) and chlorate (ClO3-) has become a potential problem when applied in drinking water treatment. In this study, ClO2 preoxidation-assisted coagulation/precipitation process was applied to improve the raw water quality, especially algae, turbidity, chemical oxygen demand (CODMn), and UV254, and explore the formation mechanisms of inorganic by-products. It was found that the polymeric aluminum chloride (PAC) and ClO2 have shown the best raw water treatment performance with the optimal dosage of 10 mg/L and 0.8 mg/L, respectively. Moreover, the initial pH also has exhibited a notable influence on pollutants treatment and by-products generation. Due to the adverse influence of algae and natural organic matters (NOM) and the generation of by-products, it was significant to investigate their inhibition effect on the water quality and the production of ClO2- and ClO3- in the ClO2 preoxidation-assisted coagulation/precipitation process. Moreover, it was applicable of this process to apply for the algae-containing raw water (calculated as Chl.a lower than 50 μg/L) treatment with the ClO2 dosage of less than 0.8 mg/L to achieve optimum treatment performance and minimum by-products generation.
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Affiliation(s)
- Wei Song
- School of Civil and Transportation Engineering, Guangdong University of Technology, Guangzhou, 510006, People's Republic of China
| | - Ji Li
- School of Civil and Environmental Engineering, Key Laboratory of Water Resource Application and Environmental Pollution Control, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, China
| | - Xiaolei Zhang
- School of Civil and Environmental Engineering, Key Laboratory of Water Resource Application and Environmental Pollution Control, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, China
| | - Caixia Fu
- School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China.
| | - Zhihong Wang
- School of Civil and Transportation Engineering, Guangdong University of Technology, Guangzhou, 510006, People's Republic of China
| | - Zhuoyue Wang
- School of Civil and Environmental Engineering, Key Laboratory of Water Resource Application and Environmental Pollution Control, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, China
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Joint Spatial Modeling of Nutrients and Their Ratio in the Sediments of Lake Balaton (Hungary): A Multivariate Geostatistical Approach. WATER 2022. [DOI: 10.3390/w14030361] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Eutrophication, water quality, and environmental status of lakes is a global issue that depends not only on external loadings from industrial, agricultural, and municipal sources but often also on internal loadings from lake sediments. In the latter case, in addition to the quality and quantity of nutrients stored in sediments, their relative content may be an important factor. In the example of Lake Balaton, we jointly modeled the spatial distribution of the nutrients nitrogen (N) and phosphorus (P) and their ratio (i.e., N:P) in the sediments of the lake and then provided spatial predictions at different scales (i.e., point, basin, and entire lake) with the associated uncertainty. Our aim was to illustrate the merits of applying multivariate geostatistics when spatial modeling of more than one variable is targeted at various scales in water ecosystems. Variography confirmed that there is a spatial interdependence between the nutrients. The results revealed that multivariate geostatistics allows this interdependence to be taken into account and exploited to provide coherent and accurate spatial models. Additionally, stochastic realizations, reproducing the joint spatial variability, can be generated that allow providing spatially aggregated predictions with the associated uncertainty at various scales. Our study highlighted that it is worthy of applying multivariate geostatistics in case spatial modeling of two or more variables, which jointly vary in space, is targeted in water ecosystems.
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