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4. High-frequency modeling of dissolved oxygen and net ecosystem metabolism using STELLA

Author

Eryiğit Miraç, Evrendilek Fatih, and Karakaya Nusret

Subjects
Pharmacology (medical)
Abstract

This paper proposes a high-frequency process model for estimating Dissolved Oxygen (DO) and net ecosystem metabolism (NEM) in streams. The model was implemented by using STELLA to predict DO concentrations at one-minute intervals downstream of a 150-m headwater reach of the Abant Creek (Bolu, Turkey). NEM was also predicted at each interval by using a two-station method along the reach. DO, water temperature and other environmental variables used in the model were measured during 17 months between August 2015 and December 2016. The model was run for a day representing every month of the year. Model parameters were calibrated and validated according to mean absolute error (MAE) between measured and simulated values of DO and NEM. The results showed that the model appeared to be promising in terms of high-frequency estimations of DO.

Published
2023

5. Delving deeper : Metabolic processes in the metalimnion of stratified lakes

Author

Giling, Darren P., Staehr, Peter A., Grossart, Hans Peter, Andersen, Mikkel René, Boehrer, Bertram, Escot, Carmelo, Evrendilek, Fatih, Gómez-Gener, Lluís, Honti, Mark, Jones, Ian D., Karakaya, Nusret, Laas, Alo, Moreno-Ostos, Enrique, Rinke, Karsten, Scharfenberger, Ulrike, Schmidt, Silke R., Weber, Michael, Woolway, R. Iestyn, Zwart, Jacob A., and Obrador, Biel

Published
2017

7. Eutrophication potential of the stream network of the Danube Basin

Author

Nagy, Eszter, Honti, Márk, Istvánovics, Vera, Gulbeyaz, Önder, Karakaya, Nusret, and Evrendilek, Fatih

Subjects
stream network, eutrophication potential, Danube Basin
Abstract

Eutrophication management is a more complicated task in running waters than in lakes and reservoirs, as network topology and longitudinal transport modulate system response to nutrient supply through dilution and short water residence time. The paradigm of lake eutrophication management is to force nutrient limitation of algal biomass by the reduction of nutrient loads. In streams, however, application of this paradigm was obviously unsuccessful in many cases, while it worked in others. Complex catchment modelling revealed that proliferation of phytoplankton in streams required the coincidence of three independent factors: adequately high nutrient supply, an inoculum of algae from the upstream environment, and a suitable downstream hydromorphology that provides sufficiently long time for algal growth. Standing water bodies in the stream network are not optimal habitats for fluvial algae and may disrupt phytoplankton development along the flow. At the same time, algae adapted to standing water conditions get washed out into the streams and may temporarily determine the trophic status of the downstream network. These phenomena suggest that eutrophication at the basin level is determined by the interaction of various factors, so its modelling requires a complex approach. The application of detailed, dynamic eutrophication models in large river basins needs immense amounts of data and computational power. To overcome this obstacle, we elaborated a novel, simplified steady-state network eutrophication model that targets to approximately quantify eutrophication potential of rivers in large basins. The model focuses only on the most important drivers of stream eutrophication and its data requirements can be covered from online databases. A case study is presented for the Danube Basin.

Published
2023
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9. Decision Making, Policy And Financing

Author

Wolflin, John P., Russo, Rosemarie C., Burak, Selmin, Karakaya, Nusret, Orbi, Abdellatif, Razinkovas, Arturas, Toktoraliev, Biimyrza, Uzun, Guven, Salas, Jessica, Amanaliev, Mars, Messahel, Mekki, Haci, Mihriban, Lagutov, Viktor, Torun, Yasin, Gönenç, İ. Ethem, editor, Vadineanu, Angheluta, editor, Wolflin, John P., editor, and Russo, Rosemarie C., editor

Published
2008
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12. Groundwater dependent ecosystems. Part II. Ecosystem services and management in Europe under risk of climate change and land use intensification

Author

Kløve, Bjørn, Allan, Andrew, Bertrand, Guillaume, Druzynska, Elzbieta, Ertürk, Ali, Goldscheider, Nico, Henry, Sarah, Karakaya, Nusret, Karjalainen, Timo P., Koundouri, Phoebe, Kupfersberger, Hans, Kvœrner, Jens, Lundberg, Angela, Muotka, Timo, Preda, Elena, Pulido-Velazquez, Manuel, and Schipper, Peter

Published
2011
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13. Groundwater dependent ecosystems. Part I: Hydroecological status and trends

Author

Kløve, Bjørn, Ala-aho, Pertti, Bertrand, Guillaume, Boukalova, Zuzana, Ertürk, Ali, Goldscheider, Nico, Ilmonen, Jari, Karakaya, Nusret, Kupfersberger, Hans, Kvœrner, Jens, Lundberg, Angela, Mileusnić, Marta, Moszczynska, Agnieszka, Muotka, Timo, Preda, Elena, Rossi, Pekka, Siergieiev, Dmytro, Šimek, Josef, Wachniew, Przemysław, Angheluta, Vadineanu, and Widerlund, Anders

Published
2011
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16. Stratification strength and light climate explain variation in chlorophyll a at the continental scale in a European multilake survey in a heatwave summer

Author

Donis, Daphne, primary, Mantzouki, Evanthia, additional, McGinnis, Daniel F., additional, Vachon, Dominic, additional, Gallego, Irene, additional, Grossart, Hans‐Peter, additional, de Senerpont Domis, Lisette N., additional, Teurlincx, Sven, additional, Seelen, Laura, additional, Lürling, Miquel, additional, Verstijnen, Yvon, additional, Maliaka, Valentini, additional, Fonvielle, Jeremy, additional, Visser, Petra M., additional, Verspagen, Jolanda, additional, van Herk, Maria, additional, Antoniou, Maria G., additional, Tsiarta, Nikoletta, additional, McCarthy, Valerie, additional, Perello, Victor C., additional, Machado‐Vieira, Danielle, additional, de Oliveira, Alinne Gurjão, additional, Maronić, Dubravka Špoljarić, additional, Stević, Filip, additional, Pfeiffer, Tanja Žuna, additional, Vucelić, Itana Bokan, additional, Žutinić, Petar, additional, Udovič, Marija Gligora, additional, Plenković‐Moraj, Anđelka, additional, Bláha, Luděk, additional, Geriš, Rodan, additional, Fránková, Markéta, additional, Christoffersen, Kirsten Seestern, additional, Warming, Trine Perlt, additional, Feldmann, Tõnu, additional, Laas, Alo, additional, Panksep, Kristel, additional, Tuvikene, Lea, additional, Kangro, Kersti, additional, Koreivienė, Judita, additional, Karosienė, Jūratė, additional, Kasperovičienė, Jūratė, additional, Savadova‐Ratkus, Ksenija, additional, Vitonytė, Irma, additional, Häggqvist, Kerstin, additional, Salmi, Pauliina, additional, Arvola, Lauri, additional, Rothhaupt, Karl, additional, Avagianos, Christos, additional, Kaloudis, Triantafyllos, additional, Gkelis, Spyros, additional, Panou, Manthos, additional, Triantis, Theodoros, additional, Zervou, Sevasti‐Kiriaki, additional, Hiskia, Anastasia, additional, Obertegger, Ulrike, additional, Boscaini, Adriano, additional, Flaim, Giovanna, additional, Salmaso, Nico, additional, Cerasino, Leonardo, additional, Haande, Sigrid, additional, Skjelbred, Birger, additional, Grabowska, Magdalena, additional, Karpowicz, Maciej, additional, Chmura, Damian, additional, Nawrocka, Lidia, additional, Kobos, Justyna, additional, Mazur‐Marzec, Hanna, additional, Alcaraz‐Párraga, Pablo, additional, Wilk‐Woźniak, Elżbieta, additional, Krztoń, Wojciech, additional, Walusiak, Edward, additional, Gagala‐Borowska, Ilona, additional, Mankiewicz‐Boczek, Joana, additional, Toporowska, Magdalena, additional, Pawlik‐Skowronska, Barbara, additional, Niedźwiecki, Michał, additional, Pęczuła, Wojciech, additional, Napiórkowska‐Krzebietke, Agnieszka, additional, Dunalska, Julita, additional, Sieńska, Justyna, additional, Szymański, Daniel, additional, Kruk, Marek, additional, Budzyńska, Agnieszka, additional, Goldyn, Ryszard, additional, Kozak, Anna, additional, Rosińska, Joanna, additional, Szeląg‐Wasielewska, Elżbieta, additional, Domek, Piotr, additional, Jakubowska‐Krepska, Natalia, additional, Kwasizur, Kinga, additional, Messyasz, Beata, additional, Pełechata, Aleksandra, additional, Pełechaty, Mariusz, additional, Kokocinski, Mikolaj, additional, Madrecka‐Witkowska, Beata, additional, Kostrzewska‐Szlakowska, Iwona, additional, Frąk, Magdalena, additional, Bańkowska‐Sobczak, Agnieszka, additional, Wasilewicz, Michał, additional, Ochocka, Agnieszka, additional, Pasztaleniec, Agnieszka, additional, Jasser, Iwona, additional, Antão‐Geraldes, Ana M., additional, Leira, Manel, additional, Vasconcelos, Vitor, additional, Morais, Joao, additional, Vale, Micaela, additional, Raposeiro, Pedro M., additional, Gonçalves, Vítor, additional, Aleksovski, Boris, additional, Krstić, Svetislav, additional, Nemova, Hana, additional, Drastichova, Iveta, additional, Chomova, Lucia, additional, Remec‐Rekar, Spela, additional, Elersek, Tina, additional, Hansson, Lars‐Anders, additional, Urrutia‐Cordero, Pablo, additional, Bravo, Andrea G., additional, Buck, Moritz, additional, Colom‐Montero, William, additional, Mustonen, Kristiina, additional, Pierson, Don, additional, Yang, Yang, additional, Richardson, Jessica, additional, Edwards, Christine, additional, Cromie, Hannah, additional, Delgado‐Martín, Jordi, additional, García, David, additional, Cereijo, Jose Luís, additional, Gomà, Joan, additional, Trapote, Mari Carmen, additional, Vegas‐Vilarrúbia, Teresa, additional, Obrador, Biel, additional, García‐Murcia, Ana, additional, Real, Monserrat, additional, Romans, Elvira, additional, Noguero‐Ribes, Jordi, additional, Duque, David Parreño, additional, Fernández‐Morán, Elísabeth, additional, Úbeda, Bárbara, additional, Gálvez, José Ángel, additional, Catalán, Núria, additional, Pérez‐Martínez, Carmen, additional, Ramos‐Rodríguez, Eloísa, additional, Cillero‐Castro, Carmen, additional, Moreno‐Ostos, Enrique, additional, Blanco, José María, additional, Rodríguez, Valeriano, additional, Montes‐Pérez, Jorge Juan, additional, Palomino, Roberto L., additional, Rodríguez‐Pérez, Estela, additional, Hernández, Armand, additional, Carballeira, Rafael, additional, Camacho, Antonio, additional, Picazo, Antonio, additional, Rochera, Carlos, additional, Santamans, Anna C., additional, Ferriol, Carmen, additional, Romo, Susana, additional, Soria, Juan Miguel, additional, Özen, Arda, additional, Karan, Tünay, additional, Demir, Nilsun, additional, Beklioğlu, Meryem, additional, Filiz, Nur, additional, Levi, Eti, additional, Iskin, Uğur, additional, Bezirci, Gizem, additional, Tavşanoğlu, Ülkü Nihan, additional, Çelik, Kemal, additional, Ozhan, Koray, additional, Karakaya, Nusret, additional, Koçer, Mehmet Ali Turan, additional, Yilmaz, Mete, additional, Maraşlıoğlu, Faruk, additional, Fakioglu, Özden, additional, Soylu, Elif Neyran, additional, Yağcı, Meral Apaydın, additional, Çınar, Şakir, additional, Çapkın, Kadir, additional, Yağcı, Abdulkadir, additional, Cesur, Mehmet, additional, Bilgin, Fuat, additional, Bulut, Cafer, additional, Uysal, Rahmi, additional, Latife, Köker, additional, Akçaalan, Reyhan, additional, Albay, Meriç, additional, Alp, Mehmet Tahir, additional, Özkan, Korhan, additional, Sevindik, Tuğba Ongun, additional, Tunca, Hatice, additional, Önem, Burçin, additional, Paerl, Hans, additional, Carey, Cayelan C., additional, and Ibelings, Bastiaan W., additional

Published
2021
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18. Setting Measures for Tackling Agricultural Diffuse Pollution of Küçük Menderes Basin

Author

Çankaya, Burhan Fuat, Güneş, Elçin, Görgün, Erdem, Karakaya, Nusret, Gökdereli, Gökçen, Tanık, Ayşegül, and Karaaslan, Yakup

Abstract

We explained the methodology used in setting the basic and supplementary measures for diffuse pollutants at Küçük Menderes Basin. As the majority of diffuse pollutants arise from livestock breeding and agricultural activities, we focused to propose measures regarded with tackling the pollution from agricultural activities. The types and distribution of diffuse loads were expressed by total nitrogen and phosphorous parameters. We used the results of a yearlong surface water quality monitoring involving physico-chemical, chemical and biological parameters with specific pollutants and priority substances, set in the European Union Water Framework Directive as the AquaTool input data. The AquaTool model was run for attaining the outcomes of a series of measures determined according to the ecological sensitivity of each water body. The removal efficiency of pollution loads provided by the best management practices in agricultural activities and livestock breeding were compiled from literature, and typical removal rates were further determined for the basin. We produced nine alternative scenarios at first cycle for determining compliance measures for mitigating point and diffuse sources of pollution in surface water bodies, and water quality improvements observed in the Model were reported. A number of exemptions were defined for some of the water bodies that could not achieve the environmental objectives at the end of first implementation cycle. 759 proposed measures for tackling diffuse pollution were 81% of the total measures considered. Additionally, the measures for mitigating diffuse agricultural pollution were almost equal to half of the diffuse pollutant measures, and 40% of the overall measures listed

Published
2021

19. Temperature effects explain continental scale distribution of cyanobacterial toxins

Author

Mantzouki, Evanthia, Lürling, Miquel, Fastner, Jutta, Domis, Lisette de Senerpont, Wilk-Woźniak, Elżbieta, Koreiviene, Judita, Seelen, Laura, Teurlincx, Sven, Verstijnen, Yvon, Krztoń, Wojciech, Walusiak, Edward, Karosienė, Jūratė, Kasperovičienė, Jūratė, Savadova, Ksenija, Vitonytė, Irma, Cillero-Castro, Carmen, Budzyńska, Agnieszka, Goldyn, Ryszard, Kozak, Anna, Rosińska, Joanna, Szeląg-Wasielewska, Elżbieta, Domek, Piotr, Jakubowska-Krepska, Natalia, Kwasizur, Kinga, Messyasz, Beata, Pełechata, Aleksandra, Pełechaty, Mariusz, Kokocinski, Mikolaj, García-Murcia, Ana, Real, Monserrat, Romans, Elvira, Noguero-Ribes, Jordi, Duque, David Parreño, Fernández-Morán, Elísabeth, Karakaya, Nusret, Häggqvist, Kerstin, Beklioğlu, Meryem, Filiz, Nur, Levi, Eti E., Iskin, Uğur, Bezirci, Gizem, Tavşanoğlu, Ülkü Nihan, Özhan, Koray, Gkelis, Spyros, Panou, Manthos, Fakioglu, Özden, Avagianos, Christos, Kaloudis, Triantafyllos, Çelik, Kemal, Yilmaz, Mete, Marcé, Rafael, Catalán, Nuria, Bravo, Andrea G., Buck, Moritz, Colom-Montero, William, Mustonen, Kristiina, Pierson, Don, Yang, Yang, Raposeiro, Pedro M., Gonçalves, Vítor, Antoniou, Maria G., Tsiarta, Nikoletta, McCarthy, Valerie, Perello, Victor C., Feldmann, Tõnu, Laas, Alo, Panksep, Kristel, Tuvikene, Lea, Gagala, Ilona, Mankiewicz-Boczek, Joana, Yağcı, Meral Apaydın, Çınar, Şakir, Çapkın, Kadir, Yağcı, Abdulkadir, Cesur, Mehmet, Bilgin, Fuat, Bulut, Cafer, Uysal, Rahmi, Obertegger, Ulrike, Boscaini, Adriano, Flaim, Giovanna, Salmaso, Nico, Cerasino, Leonardo, Richardson, Jessica, Visser, Petra M., Verspagen, Jolanda M. H., Karan, Tünay, Soylu, Elif Neyran, Maraşlıoğlu, Faruk, Napiórkowska-Krzebietke, Agnieszka, Ochocka, Agnieszka, Pasztaleniec, Agnieszka, Antão-Geraldes, Ana M., Vasconcelos, Vitor, Morais, João, Vale, Micaela, Köker, Latife, Akçaalan, Reyhan, Albay, Meriç, Maronić, Dubravka Špoljarić, Stević, Filip, Pfeiffer, Tanja Žuna, Fonvielle, Jeremy, Straile, Dietmar, Rothhaupt, Karl-Otto, Hansson, Lars-Anders, Urrutia-Cordero, Pablo, Bláha, Luděk, Geriš, Rodan, Fránková, Markéta, Koçer, Mehmet Ali Turan, Alp, Mehmet Tahir, Remec-Rekar, Spela, Elersek, Tina, Triantis, Theodoros, Zervou, Sevasti-Kiriaki, Hiskia, Anastasia, Haande, Sigrid, Skjelbred, Birger, Madrecka, Beata, Nemova, Hana, Drastichova, Iveta, Chomova, Lucia, Edwards, Christine, Sevindik, Tuğba Ongun, Tunca, Hatice, Önem, Burçin, Aleksovski, Boris, Krstić, Svetislav, Vucelić, Itana Bokan, Nawrocka, Lidia, Salmi, Pauliina, Machado-Vieira, Danielle, Oliveira, Alinne Gurjão De, Delgado-Martín, Jordi, García, David, Cereijo, Jose Luís, Gomà, Joan, Trapote, Mari Carmen, Vegas-Vilarrúbia, Teresa, Obrador, Biel, Grabowska, Magdalena, Karpowicz, Maciej, Chmura, Damian, Úbeda, Bárbara, Gálvez, José Ángel, Özen, Arda, Christoffersen, Kirsten Seestern, Warming, Trine Perlt, Kobos, Justyna, Mazur-Marzec, Hanna, Pérez-Martínez, Carmen, Ramos-Rodríguez, Eloísa, Arvola, Lauri, Alcaraz-Párraga, Pablo, Toporowska, Magdalena, Pawlik-Skowronska, Barbara, Niedźwiecki, Michał, Pęczuła, Wojciech, Leira, Manel, Hernández, Armand, Moreno-Ostos, Enrique, Blanco, José María, Rodríguez, Valeriano, Montes-Pérez, Jorge Juan, Palomino, Roberto L., Rodríguez-Pérez, Estela, Carballeira, Rafael, Camacho, Antonio, Picazo, Antonio, Rochera, Carlos, Santamans, Anna C., Ferriol, Carmen, Romo, Susana, Soria, Juan Miguel, Dunalska, Julita, Sieńska, Justyna, Szymański, Daniel, Kruk, Marek, Kostrzewska-Szlakowska, Iwona, Jasser, Iwona, Žutinić, Petar, Udovič, Marija Gligora, Plenković-Moraj, Anđelka, Frąk, Magdalena, Bańkowska-Sobczak, Agnieszka, Wasilewicz, Michał, Özkan, Korhan, Maliaka, Valentini, Kangro, Kersti, Grossart, Hans-Peter, Paerl, Hans W., Carey, Cayelan C., and Ibelings, Bas W.

Subjects
ddc:610, 610 Medizin und Gesundheit, Institut für Biochemie und Biologie
Abstract

Insight into how environmental change determines the production and distribution of cyanobacterial toxins is necessary for risk assessment. Management guidelines currently focus on hepatotoxins (microcystins). Increasing attention is given to other classes, such as neurotoxins (e.g., anatoxin-a) and cytotoxins (e.g., cylindrospermopsin) due to their potency. Most studies examine the relationship between individual toxin variants and environmental factors, such as nutrients, temperature and light. In summer 2015, we collected samples across Europe to investigate the effect of nutrient and temperature gradients on the variability of toxin production at a continental scale. Direct and indirect effects of temperature were the main drivers of the spatial distribution in the toxins produced by the cyanobacterial community, the toxin concentrations and toxin quota. Generalized linear models showed that a Toxin Diversity Index (TDI) increased with latitude, while it decreased with water stability. Increases in TDI were explained through a significant increase in toxin variants such as MC-YR, anatoxin and cylindrospermopsin, accompanied by a decreasing presence of MC-LR. While global warming continues, the direct and indirect effects of increased lake temperatures will drive changes in the distribution of cyanobacterial toxins in Europe, potentially promoting selection of a few highly toxic species or strains., Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe; 1105

Published
2021
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20. Stratification strength and light climate explain variation in chlorophyll a at the continental scale in a European multilake survey in a heatwave summer

Author

Donis, Daphne, Mantzouki, Evanthia, McGinnis, Daniel F., Vachon, Dominic, Gallego, Irene, Grossart, Hans-Peter, de Senerpont Domis, Lisette N., Teurlincx, Sven, Seelen, Laura, Lürling, Miquel, Verstijnen, Yvon, Maliaka, Valentini, Fonvielle, Jeremy, Visser, Petra M., Verspagen, Jolanda, van Herk, Maria, Antoniou, Maria G., Tsiarta, Nikoletta, McCarthy, Valerie, Perello, Victor C., Machado-Vieira, Danielle, de Oliveira, Alinne Gurjão, Maronić, Dubravka Špoljarić, Stević, Filip, Pfeiffer, Tanja Žuna, Vucelić, Itana Bokan, Žutinić, Petar, Udovič, Marija Gligora, Plenković-Moraj, Anđelka, Bláha, Luděk, Geriš, Rodan, Fránková, Markéta, Christoffersen, Kirsten Seestern, Warming, Trine Perlt, Feldmann, Tõnu, Laas, Alo, Panksep, Kristel, Tuvikene, Lea, Kangro, Kersti, Koreivienė, Judita, Karosienė, Jūratė, Kasperovičienė, Jūratė, Savadova-Ratkus, Ksenija, Vitonytė, Irma, Häggqvist, Kerstin, Salmi, Pauliina, Arvola, Lauri, Rothhaupt, Karl, Avagianos, Christos, Kaloudis, Triantafyllos, Gkelis, Spyros, Panou, Manthos, Triantis, Theodoros, Zervou, Sevasti-Kiriaki, Hiskia, Anastasia, Obertegger, Ulrike, Boscaini, Adriano, Flaim, Giovanna, Salmaso, Nico, Cerasino, Leonardo, Haande, Sigrid, Skjelbred, Birger, Grabowska, Magdalena, Karpowicz, Maciej, Chmura, Damian, Nawrocka, Lidia, Kobos, Justyna, Mazur-Marzec, Hanna, Alcaraz-Párraga, Pablo, Wilk-Woźniak, Elżbieta, Krztoń, Wojciech, Walusiak, Edward, Gagala-Borowska, Ilona, Mankiewicz-Boczek, Joana, Toporowska, Magdalena, Pawlik-Skowronska, Barbara, Niedźwiecki, Michał, Pęczuła, Wojciech, Napiórkowska-Krzebietke, Agnieszka, Dunalska, Julita, Sieńska, Justyna, Szymański, Daniel, Kruk, Marek, Budzyńska, Agnieszka, Goldyn, Ryszard, Kozak, Anna, Rosińska, Joanna, Szeląg-Wasielewska, Elżbieta, Domek, Piotr, Jakubowska-Krepska, Natalia, Kwasizur, Kinga, Messyasz, Beata, Pełechata, Aleksandra, Pełechaty, Mariusz, Kokocinski, Mikolaj, Madrecka-Witkowska, Beata, Kostrzewska-Szlakowska, Iwona, Frąk, Magdalena, Bańkowska-Sobczak, Agnieszka, Wasilewicz, Michał, Ochocka, Agnieszka, Pasztaleniec, Agnieszka, Jasser, Iwona, Antão-Geraldes, Ana M., Leira, Manel, Vasconcelos, Vitor, Morais, Joao, Vale, Micaela, Raposeiro, Pedro M., Gonçalves, Vítor, Aleksovski, Boris, Krstić, Svetislav, Nemova, Hana, Drastichova, Iveta, Chomova, Lucia, Remec-Rekar, Spela, Elersek, Tina, Hansson, Lars-Anders, Urrutia-Cordero, Pablo, Bravo, Andrea G., Buck, Moritz, Colom-Montero, William, Mustonen, Kristiina, Pierson, Don, Yang, Yang, Richardson, Jessica, Edwards, Christine, Cromie, Hannah, Delgado-Martín, Jordi, García, David, Cereijo, Jose Luís, Gomà, Joan, Trapote, Mari Carmen, Vegas-Vilarrúbia, Teresa, Obrador, Biel, García-Murcia, Ana, Real, Monserrat, Romans, Elvira, Noguero-Ribes, Jordi, Duque, David Parreño, Fernández-Morán, Elísabeth, Úbeda, Bárbara, Gálvez, José Ángel, Catalán, Núria, Pérez-Martínez, Carmen, Ramos-Rodríguez, Eloísa, Cillero-Castro, Carmen, Moreno-Ostos, Enrique, Blanco, José María, Rodríguez, Valeriano, Montes-Pérez, Jorge Juan, Palomino, Roberto L., Rodríguez-Pérez, Estela, Hernández, Armand, Carballeira, Rafael, Camacho, Antonio, Picazo, Antonio, Rochera, Carlos, Santamans, Anna C., Ferriol, Carmen, Romo, Susana, Soria, Juan Miguel, Özen, Arda, Karan, Tünay, Demir, Nilsun, Beklioğlu, Meryem, Filiz, Nur, Levi, Eti, Iskin, Uğur, Bezirci, Gizem, Tavşanoğlu, Ülkü Nihan, Çelik, Kemal, Ozhan, Koray, Karakaya, Nusret, Koçer, Mehmet Ali Turan, Yilmaz, Mete, Maraşlıoğlu, Faruk, Fakioglu, Özden, Soylu, Elif Neyran, Yağcı, Meral Apaydın, Çınar, Şakir, Çapkın, Kadir, Yağcı, Abdulkadir, Cesur, Mehmet, Bilgin, Fuat, Bulut, Cafer, Uysal, Rahmi, Latife, Köker, Akçaalan, Reyhan, Albay, Meriç, Alp, Mehmet Tahir, Özkan, Korhan, Sevindik, Tuğba Ongun, Tunca, Hatice, Önem, Burçin, Paerl, Hans, Carey, Cayelan C., Ibelings, Bastiaan W., Donis, Daphne, Mantzouki, Evanthia, McGinnis, Daniel F., Vachon, Dominic, Gallego, Irene, Grossart, Hans-Peter, de Senerpont Domis, Lisette N., Teurlincx, Sven, Seelen, Laura, Lürling, Miquel, Verstijnen, Yvon, Maliaka, Valentini, Fonvielle, Jeremy, Visser, Petra M., Verspagen, Jolanda, van Herk, Maria, Antoniou, Maria G., Tsiarta, Nikoletta, McCarthy, Valerie, Perello, Victor C., Machado-Vieira, Danielle, de Oliveira, Alinne Gurjão, Maronić, Dubravka Špoljarić, Stević, Filip, Pfeiffer, Tanja Žuna, Vucelić, Itana Bokan, Žutinić, Petar, Udovič, Marija Gligora, Plenković-Moraj, Anđelka, Bláha, Luděk, Geriš, Rodan, Fránková, Markéta, Christoffersen, Kirsten Seestern, Warming, Trine Perlt, Feldmann, Tõnu, Laas, Alo, Panksep, Kristel, Tuvikene, Lea, Kangro, Kersti, Koreivienė, Judita, Karosienė, Jūratė, Kasperovičienė, Jūratė, Savadova-Ratkus, Ksenija, Vitonytė, Irma, Häggqvist, Kerstin, Salmi, Pauliina, Arvola, Lauri, Rothhaupt, Karl, Avagianos, Christos, Kaloudis, Triantafyllos, Gkelis, Spyros, Panou, Manthos, Triantis, Theodoros, Zervou, Sevasti-Kiriaki, Hiskia, Anastasia, Obertegger, Ulrike, Boscaini, Adriano, Flaim, Giovanna, Salmaso, Nico, Cerasino, Leonardo, Haande, Sigrid, Skjelbred, Birger, Grabowska, Magdalena, Karpowicz, Maciej, Chmura, Damian, Nawrocka, Lidia, Kobos, Justyna, Mazur-Marzec, Hanna, Alcaraz-Párraga, Pablo, Wilk-Woźniak, Elżbieta, Krztoń, Wojciech, Walusiak, Edward, Gagala-Borowska, Ilona, Mankiewicz-Boczek, Joana, Toporowska, Magdalena, Pawlik-Skowronska, Barbara, Niedźwiecki, Michał, Pęczuła, Wojciech, Napiórkowska-Krzebietke, Agnieszka, Dunalska, Julita, Sieńska, Justyna, Szymański, Daniel, Kruk, Marek, Budzyńska, Agnieszka, Goldyn, Ryszard, Kozak, Anna, Rosińska, Joanna, Szeląg-Wasielewska, Elżbieta, Domek, Piotr, Jakubowska-Krepska, Natalia, Kwasizur, Kinga, Messyasz, Beata, Pełechata, Aleksandra, Pełechaty, Mariusz, Kokocinski, Mikolaj, Madrecka-Witkowska, Beata, Kostrzewska-Szlakowska, Iwona, Frąk, Magdalena, Bańkowska-Sobczak, Agnieszka, Wasilewicz, Michał, Ochocka, Agnieszka, Pasztaleniec, Agnieszka, Jasser, Iwona, Antão-Geraldes, Ana M., Leira, Manel, Vasconcelos, Vitor, Morais, Joao, Vale, Micaela, Raposeiro, Pedro M., Gonçalves, Vítor, Aleksovski, Boris, Krstić, Svetislav, Nemova, Hana, Drastichova, Iveta, Chomova, Lucia, Remec-Rekar, Spela, Elersek, Tina, Hansson, Lars-Anders, Urrutia-Cordero, Pablo, Bravo, Andrea G., Buck, Moritz, Colom-Montero, William, Mustonen, Kristiina, Pierson, Don, Yang, Yang, Richardson, Jessica, Edwards, Christine, Cromie, Hannah, Delgado-Martín, Jordi, García, David, Cereijo, Jose Luís, Gomà, Joan, Trapote, Mari Carmen, Vegas-Vilarrúbia, Teresa, Obrador, Biel, García-Murcia, Ana, Real, Monserrat, Romans, Elvira, Noguero-Ribes, Jordi, Duque, David Parreño, Fernández-Morán, Elísabeth, Úbeda, Bárbara, Gálvez, José Ángel, Catalán, Núria, Pérez-Martínez, Carmen, Ramos-Rodríguez, Eloísa, Cillero-Castro, Carmen, Moreno-Ostos, Enrique, Blanco, José María, Rodríguez, Valeriano, Montes-Pérez, Jorge Juan, Palomino, Roberto L., Rodríguez-Pérez, Estela, Hernández, Armand, Carballeira, Rafael, Camacho, Antonio, Picazo, Antonio, Rochera, Carlos, Santamans, Anna C., Ferriol, Carmen, Romo, Susana, Soria, Juan Miguel, Özen, Arda, Karan, Tünay, Demir, Nilsun, Beklioğlu, Meryem, Filiz, Nur, Levi, Eti, Iskin, Uğur, Bezirci, Gizem, Tavşanoğlu, Ülkü Nihan, Çelik, Kemal, Ozhan, Koray, Karakaya, Nusret, Koçer, Mehmet Ali Turan, Yilmaz, Mete, Maraşlıoğlu, Faruk, Fakioglu, Özden, Soylu, Elif Neyran, Yağcı, Meral Apaydın, Çınar, Şakir, Çapkın, Kadir, Yağcı, Abdulkadir, Cesur, Mehmet, Bilgin, Fuat, Bulut, Cafer, Uysal, Rahmi, Latife, Köker, Akçaalan, Reyhan, Albay, Meriç, Alp, Mehmet Tahir, Özkan, Korhan, Sevindik, Tuğba Ongun, Tunca, Hatice, Önem, Burçin, Paerl, Hans, Carey, Cayelan C., and Ibelings, Bastiaan W.

Abstract

To determine the drivers of phytoplankton biomass, we collected standardized morphometric, physical, and biological data in 230 lakes across the Mediterranean, Continental, and Boreal climatic zones of the European continent. Multilinear regression models tested on this snapshot of mostly eutrophic lakes (median total phosphorus [TP] = 0.06 and total nitrogen [TN] = 0.7 mg L−1), and its subsets (2 depth types and 3 climatic zones), show that light climate and stratification strength were the most significant explanatory variables for chlorophyll a (Chl a) variance. TN was a significant predictor for phytoplankton biomass for shallow and continental lakes, while TP never appeared as an explanatory variable, suggesting that under high TP, light, which partially controls stratification strength, becomes limiting for phytoplankton development. Mediterranean lakes were the warmest yet most weakly stratified and had significantly less Chl a than Boreal lakes, where the temperature anomaly from the long-term average, during a summer heatwave was the highest (+4°C) and showed a significant, exponential relationship with stratification strength. This European survey represents a summer snapshot of phytoplankton biomass and its drivers, and lends support that light and stratification metrics, which are both affected by climate change, are better predictors for phytoplankton biomass in nutrient-rich lakes than nutrient concentrations and surface temperature.

Published
2021

23. Setting Measures for Tackling Agricultural Diffuse Pollution of Küçük Menderes Basin

Author

TANIK, Ayşegül, HANEDAR, Asude, GİRGİN, Emine, GÜNEŞ, Elçin, GÖRGÜN, Erdem, KARAKAYA, Nusret, GÖKDERELİ, Gökçen, ÇANKAYA, Burhan Fuat, KİMENCE, Taner, and KARAASLAN, Yakup

Subjects
Diffuse pollutants,Basic measures,Total nitrogen,Total phosphorus, Engineering, Multidisciplinary, Mühendislik, Ortak Disiplinler
Abstract

We explained the methodology used in setting the basic and supplementary measures for diffuse pollutants at Küçük Menderes Basin. As the majority of diffuse pollutants arise from livestock breeding and agricultural activities, we focused to propose measures regarded with tackling the pollution from agricultural activities. The types and distribution of diffuse loads were expressed by total nitrogen and phosphorous parameters. We used the results of a yearlong surface water quality monitoring involving physico-chemical, chemical and biological parameters with specific pollutants and priority substances,set in the European Union Water Framework Directive as the AquaTool input data. The AquaTool model was run for attaining the outcomes of a series of measures determined according to the ecological sensitivity of each water body. The removal efficiency of pollution loads provided by the best management practices in agricultural activities and livestock breeding were compiled from literature,and typical removal rates were further determined for the basin. We produced nine alternative scenariosat first cycle for determining compliance measures for mitigating point and diffuse sources of pollution in surface water bodies, and water quality improvements observed in the Model were reported. A number of exemptions were defined for some of the water bodies that could not achieve the environmental objectives at the end of first implementation cycle. 759 proposed measures for tackling diffuse pollution were 81% of the total measures considered. Additionally, the measures for mitigating diffuse agricultural pollution were almost equal to half of the diffuse pollutant measures, and 40% of the overall measures listed

Published
2020

24. Optimum Water Resources Allocation by Artificial Immune Systems

Author

ERYİĞİT, Mirac and KARAKAYA, Nusret

Subjects
Engineering, Mühendislik, Water resources,water allocation,optimization,modified Clonalg,modeling
Abstract

This study proposes an optimization model using Artificial Immune Systems (AIS) for allocation of water resources among different sectors such as agriculture, industry, livestock production, drinking and environmental water demands, energy, tourism, mining, aquaculture and commercial water. The modified Clonal Selection Algorithm (modified Clonalg) which is a class of AIS, was used in the study. An objective function of the model was based on both maximum benefit (income) and maximum water satisfaction of the sectors. The model was implemented to a scenario including the mentioned sectors for testing its performance. The results demonstrated that the model is applicable for the water resources allocation.

Published
2020

25. Setting Measures for Tackling Agricultural Diffuse Pollution of Inland Surface Water Bodies: Towards Achieving Environmental Objectives in Turkey

Author

TANIK, Ayşegül, primary, HANEDAR, Asude, additional, GİRGİN, Emine, additional, GÜNEŞ, Elçin, additional, GÖRGÜN, Erdem, additional, KARAKAYA, Nusret, additional, GÖKDERELİ, Gökçen, additional, ÇANKAYA, Burhan Fuat, additional, KİMENCE, Taner, additional, and KARAASLAN, Yakup, additional

Published
2021
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26. Optimizing water use in agriculture to preserve soil and water resources. The WATER4EVER project

Author

Neves, Ramiro, primary, Ramos, Tiago, additional, Simionesei, Lucian, additional, Oliveira, Ana, additional, Grosso, Nuno, additional, Santos, Filipe, additional, Moura, Pedro, additional, Stefan, Vivien, additional, Escorihuela, M. Jose, additional, Gao, Qi, additional, Pérez-Pastor, Alejandro, additional, Riquelme, Juan, additional, Forcén, Manuel, additional, Biddoccu, Marcella, additional, Rabino, Danilo, additional, Bagagiolo, Giorgia, additional, and Karakaya, Nusret, additional

Published
2020
Full Text
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28. Temperature Effects Explain Continental Scale Distribution of Cyanobacterial Toxins: Data descriptor

Author

Mantzouki, Evanthia, Lürling, Miquel, Fastner, Jutta, de Senerpont Domis, Lisette, Wilk-Woźniak, Elżbieta, Koreivienė, Judita, Seelen, Laura, Teurlincx, Sven, Verstijnen, Yvon, Krztoń, Wojciech, Walusiak, Edward, Karosienė, Jūratė, Kasperovičienė, Jūratė, Savadova, Ksenija, Vitonytė, Irma, Cillero-Castro, Carmen, Budzyńska, Agnieszka, Goldyn, Ryszard, Kozak, Anna, Rosińska, Joanna, Szeląg-Wasielewska, Elżbieta, Domek, Piotr, Jakubowska-Krepska, Natalia, Kwasizur, Kinga, Messyasz, Beata, Pełechaty, Aleksandra, Pełechaty, Mariusz, Kokocinski, Mikolaj, García-Murcia, Ana, Real, Monserrat, Romans, Elvira, Noguero-Ribes, Jordi, Duque, David Parreño, Fernández-Morán, Elísabeth, Karakaya, Nusret, Häggqvist, Kerstin, Demir, Nilsun, Beklioğlu, Meryem, Filiz, Nur, Levi, Eti E., Iskin, Uğur, Bezirci, Gizem, Tavşanoğlu, Ülkü Nihan, Özhan, Koray, Gkelis, Spyros, Panou, Manthos, Fakioglu, Özden, Avagianos, Christos, Kaloudis, Triantafyllos, Çelik, Kemal, Yilmaz, Mete, Marcé, Rafael, Catalán, Nuria, Bravo, Andrea G., Buck, Moritz, Colom-Montero, William, Mustonen, Kristiina, Pierson, Don, Yang, Yang, Raposeiro, Pedro M., Gonçalves, Vítor, Antoniou, Maria G., Tsiarta, Nikoletta, McCarthy, Valerie, Perello, Victor C., Feldmann, Tõnu, Laas, Alo, Panksep, Kristel, Tuvikene, Lea, Gagala, Ilona, Mankiewicz-Boczek, Joana, Yağcı, Meral Apaydın, Çınar, Şakir, Çapkın, Kadir, Yağcı, Abdulkadir, Cesur, Mehmet, Bilgin, Fuat, Bulut, Cafer, Uysal, Rahmi, Obertegger, Ulrike, Boscaini, Adriano, Flaim, Giovanna, Salmaso, Nico, Cerasino, Leonardo, Richardson, Jessica, Visser, Petra M, Verspagen, Jolanda M. H., Karan, Tünay, Soylu, Elif Neyran, Maraşlıoğlu, Faruk, Napiórkowska-Krzebietke, Agnieszka, Ochocka, Agnieszka, Pasztaleniec, Agnieszka, Antão-Geraldes, Ana M., Vasconcelos, Vitor, Morais, João, Vale, Micaela, Köker, Latife, Akçaalan, Reyhan, Albay, Meriç, Špoljarić Maronić, Dubravka, Stević, Filip, Žuna Pfeiffer, Tanja, Fonvielle, Jeremy, Straile, Dietmar, Rothhaupt, Karl-Otto, Hansson, Lars-Anders, Urrutia-Cordero, Pablo, Bláha, Luděk, Geriš, Rodan, Fránková, Markéta, Koçer, Mehmet Ali Turan, Alp, Mehmet Tahir, Remec-Rekar, Spela, Elersek, Tina, Triantis, Theodoros, Zervou, Sevasti-Kiriaki, Hiskia, Anastasia, Haande, Sigrid, Skjelbred, Birger, Madrecka, Beata, Nemova, Hana, Drastichova, Iveta, Chomova, Lucia, Edwards, Christine, Sevindik, Tuğba Ongun, Tunca, Hatice, Önem, Burçin, Aleksovski, Boris, Krstić, Svetislav, Vucelić, Itana Bokan, Nawrocka, Lidia, Salmi, Pauliina, Machado-Vieira, Danielle, de Oliveira, Alinne Gurjão, Delgado-Martín, Jordi, García-García, David, Cereijo, Jose Luís, Gomà, Joan, Trapote, Mari Carmen, Vegas-Vilarrúbia, Teresa, Obrador, Biel, Grabowska, Magdalena, Karpowicz, Maciej, Chmura, Damian, Úbeda, Bárbara, Gálvez, José Ángel, Özen, Arda, Christoffersen, Kirsten Seestern, Warming, Trine Perlt, Kobos, Justyna, Mazur-Marzec, Hanna, Pérez-Martínez, Carmen, Ramos-Rodríguez, Eloísa, Arvola, Lauri, Alcaraz-Párraga, Pablo, Toporowska, Magdalena, Pawlik-Skowronska, Barbara, Niedźwiecki, Michał, Pęczuła, Wojciech, Leira, Manel, Hernández, Armand, Moreno-Ostos, Enrique, Blanco, José María, Rodríguez, Valeriano, Montes-Pérez, Jorge Juan, Palomino, Roberto L., Rodríguez-Pérez, Estela, Carballeira, Rafael, Camacho, Antonio, Picazo, Antonio, Rochera, Carlos, Santamans, Anna C., Ferriol, Carmen, Romo, Susana, Soria, Juan Miguel, Dunalska, Julita, Sieńska, Justyna, Szymański, Daniel, Kruk, Marek, Kostrzewska-Szlakowska, Iwona, Jasser, Iwona, Žutinić, Petar, Gligora Udovič, Marija, Plenković-Moraj, Anđelka, Frąk, Magdalena, Bańkowska-Sobczak, Agnieszka, Wasilewicz, Michał, Özkan, Korhan, Maliaka, Valentini, Kangro, Kersti, Grossart, Hans-Peter, Paerl, Hans W., Carey, Cayelan C., Ibelings, Bas W., Aquatic Ecology (AqE), and AKWA

Subjects
international, Journal Article
Abstract

situ Insight into how environmental change determines the production and distribution of cyanobacterial toxins is necessary for risk assessment. Management guidelines currently focus on hepatotoxins (microcystins). Increasing attention is given to other classes, such as neurotoxins (e.g., anatoxin-a) and cytotoxins (e.g., cylindrospermopsin) due to their potency. Most studies examine the relationship between individual toxin variants and environmental factors, such as nutrients, temperature and light. In summer 2015, we collected samples across Europe to investigate the effect of nutrient and temperature gradients on the variability of toxin production at a continental scale. Direct and indirect effects of temperature were the main drivers of the spatial distribution in the toxins produced by the cyanobacterial community, the toxin concentrations and toxin quota. Generalized linear models showed that a Toxin Diversity Index (TDI) increased with latitude, while it decreased with water stability. Increases in TDI were explained through a significant increase in toxin variants such as MC-YR, anatoxin and cylindrospermopsin, accompanied by a decreasing presence of MC-LR. While global warming continues, the direct and indirect effects of increased lake temperatures will drive changes in the distribution of cyanobacterial toxins in Europe, potentially promoting selection of a few highly toxic species or strains.

Published
2018

29. Data Descriptor : A European Multi Lake Survey dataset of environmental variables, phytoplankton pigments and cyanotoxins

Author

Mantzouki, Evanthia, Campbell, James, Loon, Emiel van, Visser, Petra, Konstantinou, Iosif, Antoniou, Maria G., Giuliani, Grégory, Machado-Vieira, Danielle, Oliveira, Alinne Gurjão de, Maronić, Dubravka Špoljarić, Stević, Filip, Fakioglu, Özden, Soylu, Elif Neyran, Yağcı, Meral Apaydın, Çınar, Şakir, Çapkın, Kadir, Yağcı, Abdulkadir, Cesur, Mehmet, Bilgin, Fuat, Bulut, Cafer, Fránková, Markéta, Vasconcelos, Vitor, Uysal, Rahmi, Köker, Latife, Akçaalan, Reyhan, Albay, Meriç, Alp, Mehmet Tahir, Özkan, Korhan, Sevindik, Tuğba Ongun, Tunca, Hatice, Önem, Burçin, Richardson, Jessica, Morais, João, Christoffersen, Kirsten Seestern, Edwards, Christine, Bergkemper, Victoria, O'Leary, Sarah, Beirne, Eilish, Cromie, Hannah, Ibelings, Bastiaan W., Warming, Trine Perlt, Feldmann, Tõnu, Laas, Alo, Vale, Micaela, Panksep, Kristel, Tuvikene, Lea, Kangro, Kersti, Häggqvist, Kerstin, Salmi, Pauliina, Arvola, Lauri, Fastner, Jutta, Straile, Dietmar, Rothhaupt, Karl-Otto, Fonvielle, Jeremy, Raposeiro, Pedro M., Grossart, Hans-Peter, Avagianos, Christos, Kaloudis, Triantafyllos, Triantis, Theodoros, Zervou, Sevasti-Kiriaki, Hiskia, Anastasia, Gkelis, Spyros, Panou, Manthos, McCarthy, Valerie, Perello, Victor C., Gonçalves, Vítor Manuel da Costa, Obertegger, Ulrike, Boscaini, Adriano, Flaim, Giovanna, Salmaso, Nico, Cerasino, Leonardo, Koreivienė, Judita, Karosienė, Jūratė, Kasperovičienė, Jūratė, Savadova, Ksenija, Vitonytė, Irma, Aleksovski, Boris, Haande, Sigrid, Skjelbred, Birger, Grabowska, Magdalena, Karpowicz, Maciej, Chmura, Damian, Nawrocka, Lidia, Kobos, Justyna, Mazur-Marzec, Hanna, Alcaraz-Párraga, Pablo, Wilk-Woźniak, Elżbieta, Krstić, Svetislav, Krztoń, Wojciech, Walusiak, Edward, Gagala, Ilona, Mankiewicz-Boczek, Joana, Toporowska, Magdalena, Pawlik-Skowronska, Barbara, Niedźwiecki, Michał, Pęczuła, Wojciech, Napiórkowska-Krzebietke, Agnieszka, Dunalska, Julita, Nemova, Hana, Sieńska, Justyna, Szymański, Daniel, Kruk, Marek, Budzyńska, Agnieszka, Goldyn, Ryszard, Kozak, Anna, Rosińska, Joanna, Szeląg-Wasielewska, Elżbieta, Domek, Piotr, Jakubowska-Krepska, Natalia, Drastichova, Iveta, Kwasizur, Kinga, Messyasz, Beata, Pełechata, Aleksandra, Pełechaty, Mariusz, Kokocinski, Mikolaj, Madrecka, Beata, Kostrzewska-Szlakowska, Iwona, Frąk, Magdalena, Bańkowska-Sobczak, Agnieszka, Wasilewicz, Michał, Chomova, Lucia, Ochocka, Agnieszka, Pasztaleniec, Agnieszka, Jasser, Iwona, Geraldes, Ana Maria, Leira, Manel, Hernández, Armand, Pfeiffer, Tanja Žuna, Remec-Rekar, Spela, Elersek, Tina, Delgado-Martín, Jordi, García, David, Cereijo, Jose Luís, Gomà, Joan, Trapote, Mari Carmen, Vegas-Vilarrúbia, Teresa, Obrador, Biel, García-Murcia, Ana, Vucelić, Itana Bokan, Real, Monserrat, Romans, Elvira, Noguero-Ribes, Jordi, Duque, David Parreño, Fernández-Morán, Elísabeth, Úbeda, Bárbara, Gálvez, José Ángel, Marcé, Rafael, Catalán, Núria, Pérez-Martínez, Carmen, Žutinić, Petar, Ramos-Rodríguez, Eloísa, Cillero-Castro, Carmen, Moreno-Ostos, Enrique, Blanco, José María, Rodríguez, Valeriano, Montes-Pérez, Jorge Juan, Palomino, Roberto L., Rodríguez-Pérez, Estela, Carballeira, Rafael, Camacho, Antonio, Udovič, Marija Gligora, Picazo, Antonio, Rochera, Carlos, Santamans, Anna C., Ferriol, Carmen, Romo, Susana, Soria, Juan Miguel, Hansson, Lars-Anders, Urrutia-Cordero, Pablo, Özen, Arda, Bravo, Andrea G., Plenković-Moraj, Anđelka, Buck, Moritz, Colom-Montero, William, Mustonen, Kristiina, Pierson, Don, Yang, Yang, Verspagen, Jolanda M.H., Domis, Lisette N. de Senerpont, Seelen, Laura, Teurlincx, Sven, Verstijnen, Yvon, Tsiarta, Nikoletta, Lürling, Miquel, Maliaka, Valentini, Faassen, Elisabeth J., Latour, Delphine, Carey, Cayelan C., Paerl, Hans W., Torokne, Andrea, Karan, Tünay, Demir, Nilsun, Beklioğlu, Meryem, Bláha, Luděk, Filiz, Nur, Levi, Eti E., Iskin, Uğur, Bezirci, Gizem, Tavşanoğlu, Ülkü Nihan, Çelik, Kemal, Özhan, Koray, Karakaya, Nusret, Koçer, Mehmet Ali Turan, Yilmaz, Mete, Geriš, Rodan, Maraşlıoğlu, Faruk, and Institute of Agricultural and Environmental Sciences

Subjects
Europe, ddc:570, Settore BIO/07 - ECOLOGIA, datasets, lakes, articles, Phytoplankton pigments, Institut für Biochemie und Biologie, Dataset
Abstract

Under ongoing climate change and increasing anthropogenic activity, which continuously challenge ecosystem resilience, an in-depth understanding of ecological processes is urgently needed. Lakes, as providers of numerous ecosystem services, face multiple stressors that threaten their functioning. Harmful cyanobacterial blooms are a persistent problem resulting from nutrient pollution and climate-change induced stressors, like poor transparency, increased water temperature and enhanced stratification. Consistency in data collection and analysis methods is necessary to achieve fully comparable datasets and for statistical validity, avoiding issues linked to disparate data sources. The European Multi Lake Survey (EMLS) in summer 2015 was an initiative among scientists from 27 countries to collect and analyse lake physical, chemical and biological variables in a fully standardized manner. This database includes in-situ lake variables along with nutrient, pigment and cyanotoxin data of 369 lakes in Europe, which were centrally analysed in dedicated laboratories. Publishing the EMLS methods and dataset might inspire similar initiatives to study across large geographic areas that will contribute to better understanding lake responses in a changing environment. The authors acknowledge COST Action ES 1105 “CYANOCOST – Cyanobacterial blooms and toxins in water resources: Occurrence impacts and management” and COST Action ES 1201 “NETLAKE – Networking Lake Observatories in Europe” for contributing to this study through networking and knowledge sharing with European experts in the field. Evanthia Mantzouki was supported by a grant from the Swiss State Secretariat for Education, Research and Innovation (SERI) to Bas Ibelings and by supplementary funding from University of Geneva. We thank Wendy Beekman for the nutrient analysis and the University of Wageningen for covering the costs of this analysis from the personal funding of dr. Miquel Lürling. We thank Pieter Slot for assisting with the pigment analysis and the University of Amsterdam for covering the costs of the analysis through funding from the group of Prof. Jef Huisman and dr. Petra Visser (IBED). We would like to thank the Environmental Data Initiative for covering the cost of archiving the EMLS dataset. We would like to thank the Leibniz Institute of Freshwater Ecology and Inland Fisheries, Dept. of Experimental Limnology and the Aquatic Microbial Ecology Group for logistic and technical support of J. Fonvielle and H.-P. Grossart; and the Leibniz Association for financial support. The collection of data for Lough Erne and Lough Neagh were funded by the Department of Agriculture, Environment and Rural Affairs, Northern Ireland. The authors acknowledge COST Action ES 1105 “CYANOCOST – Cyanobacterial blooms and toxins in water resources: Occurrence impacts and management” and COST Action ES 1201 “NETLAKE – Networking Lake Observatories in Europe” for contributing to this study through networking and knowledge sharing with European experts in the field. Evanthia Mantzouki was supported by a grant from the Swiss State Secretariat for Education, Research and Innovation (SERI) to Bas Ibelings and by supplementary funding from University of Geneva. We thank Wendy Beekman for the nutrient analysis and the University of Wageningen for covering the costs of this analysis from the personal funding of dr. Miquel Lürling. We thank Pieter Slot for assisting with the pigment analysis and the University of Amsterdam for covering the costs of the analysis through funding from the group of Prof. Jef Huisman and dr. Petra Visser (IBED). We would like to thank the Environmental Data Initiative for covering the cost of archiving the EMLS dataset. We would like to thank the Leibniz Institute of Freshwater Ecology and Inland Fisheries, Dept. of Experimental Limnology and the Aquatic Microbial Ecology Group for logistic and technical support of J. Fonvielle and H.-P. Grossart; and the Leibniz Association for financial support. The collection of data for Lough Erne and Lough Neagh were funded by the Department of Agriculture, Environment and Rural Affairs, Northern Ireland.

Published
2018

30. Stratification strength and light climate explain variation in chlorophyll aat the continental scale in a European multilake survey in a heatwave summer

Author

Donis, Daphne, Mantzouki, Evanthia, McGinnis, Daniel F., Vachon, Dominic, Gallego, Irene, Grossart, Hans‐Peter, Senerpont Domis, Lisette N., Teurlincx, Sven, Seelen, Laura, Lürling, Miquel, Verstijnen, Yvon, Maliaka, Valentini, Fonvielle, Jeremy, Visser, Petra M., Verspagen, Jolanda, Herk, Maria, Antoniou, Maria G., Tsiarta, Nikoletta, McCarthy, Valerie, Perello, Victor C., Machado‐Vieira, Danielle, Oliveira, Alinne Gurjão, Maronić, Dubravka Špoljarić, Stević, Filip, Pfeiffer, Tanja Žuna, Vucelić, Itana Bokan, Žutinić, Petar, Udovič, Marija Gligora, Plenković‐Moraj, Anđelka, Bláha, Luděk, Geriš, Rodan, Fránková, Markéta, Christoffersen, Kirsten Seestern, Warming, Trine Perlt, Feldmann, Tõnu, Laas, Alo, Panksep, Kristel, Tuvikene, Lea, Kangro, Kersti, Koreivienė, Judita, Karosienė, Jūratė, Kasperovičienė, Jūratė, Savadova‐Ratkus, Ksenija, Vitonytė, Irma, Häggqvist, Kerstin, Salmi, Pauliina, Arvola, Lauri, Rothhaupt, Karl, Avagianos, Christos, Kaloudis, Triantafyllos, Gkelis, Spyros, Panou, Manthos, Triantis, Theodoros, Zervou, Sevasti‐Kiriaki, Hiskia, Anastasia, Obertegger, Ulrike, Boscaini, Adriano, Flaim, Giovanna, Salmaso, Nico, Cerasino, Leonardo, Haande, Sigrid, Skjelbred, Birger, Grabowska, Magdalena, Karpowicz, Maciej, Chmura, Damian, Nawrocka, Lidia, Kobos, Justyna, Mazur‐Marzec, Hanna, Alcaraz‐Párraga, Pablo, Wilk‐Woźniak, Elżbieta, Krztoń, Wojciech, Walusiak, Edward, Gagala‐Borowska, Ilona, Mankiewicz‐Boczek, Joana, Toporowska, Magdalena, Pawlik‐Skowronska, Barbara, Niedźwiecki, Michał, Pęczuła, Wojciech, Napiórkowska‐Krzebietke, Agnieszka, Dunalska, Julita, Sieńska, Justyna, Szymański, Daniel, Kruk, Marek, Budzyńska, Agnieszka, Goldyn, Ryszard, Kozak, Anna, Rosińska, Joanna, Szeląg‐Wasielewska, Elżbieta, Domek, Piotr, Jakubowska‐Krepska, Natalia, Kwasizur, Kinga, Messyasz, Beata, Pełechata, Aleksandra, Pełechaty, Mariusz, Kokocinski, Mikolaj, Madrecka‐Witkowska, Beata, Kostrzewska‐Szlakowska, Iwona, Frąk, Magdalena, Bańkowska‐Sobczak, Agnieszka, Wasilewicz, Michał, Ochocka, Agnieszka, Pasztaleniec, Agnieszka, Jasser, Iwona, Antão‐Geraldes, Ana M., Leira, Manel, Vasconcelos, Vitor, Morais, Joao, Vale, Micaela, Raposeiro, Pedro M., Gonçalves, Vítor, Aleksovski, Boris, Krstić, Svetislav, Nemova, Hana, Drastichova, Iveta, Chomova, Lucia, Remec‐Rekar, Spela, Elersek, Tina, Hansson, Lars‐Anders, Urrutia‐Cordero, Pablo, Bravo, Andrea G., Buck, Moritz, Colom‐Montero, William, Mustonen, Kristiina, Pierson, Don, Yang, Yang, Richardson, Jessica, Edwards, Christine, Cromie, Hannah, Delgado‐Martín, Jordi, García, David, Cereijo, Jose Luís, Gomà, Joan, Trapote, Mari Carmen, Vegas‐Vilarrúbia, Teresa, Obrador, Biel, García‐Murcia, Ana, Real, Monserrat, Romans, Elvira, Noguero‐Ribes, Jordi, Duque, David Parreño, Fernández‐Morán, Elísabeth, Úbeda, Bárbara, Gálvez, José Ángel, Catalán, Núria, Pérez‐Martínez, Carmen, Ramos‐Rodríguez, Eloísa, Cillero‐Castro, Carmen, Moreno‐Ostos, Enrique, Blanco, José María, Rodríguez, Valeriano, Montes‐Pérez, Jorge Juan, Palomino, Roberto L., Rodríguez‐Pérez, Estela, Hernández, Armand, Carballeira, Rafael, Camacho, Antonio, Picazo, Antonio, Rochera, Carlos, Santamans, Anna C., Ferriol, Carmen, Romo, Susana, Soria, Juan Miguel, Özen, Arda, Karan, Tünay, Demir, Nilsun, Beklioğlu, Meryem, Filiz, Nur, Levi, Eti, Iskin, Uğur, Bezirci, Gizem, Tavşanoğlu, Ülkü Nihan, Çelik, Kemal, Ozhan, Koray, Karakaya, Nusret, Koçer, Mehmet Ali Turan, Yilmaz, Mete, Maraşlıoğlu, Faruk, Fakioglu, Özden, Soylu, Elif Neyran, Yağcı, Meral Apaydın, Çınar, Şakir, Çapkın, Kadir, Yağcı, Abdulkadir, Cesur, Mehmet, Bilgin, Fuat, Bulut, Cafer, Uysal, Rahmi, Latife, Köker, Akçaalan, Reyhan, Albay, Meriç, Alp, Mehmet Tahir, Özkan, Korhan, Sevindik, Tuğba Ongun, Tunca, Hatice, Önem, Burçin, Paerl, Hans, Carey, Cayelan C., and Ibelings, Bastiaan W.

Abstract

To determine the drivers of phytoplankton biomass, we collected standardized morphometric, physical, and biological data in 230 lakes across the Mediterranean, Continental, and Boreal climatic zones of the European continent. Multilinear regression models tested on this snapshot of mostly eutrophic lakes (median total phosphorus [TP] = 0.06 and total nitrogen [TN] = 0.7 mg L−1), and its subsets (2 depth types and 3 climatic zones), show that light climate and stratification strength were the most significant explanatory variables for chlorophyll a(Chl a) variance. TN was a significant predictor for phytoplankton biomass for shallow and continental lakes, while TP never appeared as an explanatory variable, suggesting that under high TP, light, which partially controls stratification strength, becomes limiting for phytoplankton development. Mediterranean lakes were the warmest yet most weakly stratified and had significantly less Chl athan Boreal lakes, where the temperature anomaly from the long‐term average, during a summer heatwave was the highest (+4°C) and showed a significant, exponential relationship with stratification strength. This European survey represents a summer snapshot of phytoplankton biomass and its drivers, and lends support that light and stratification metrics, which are both affected by climate change, are better predictors for phytoplankton biomass in nutrient‐rich lakes than nutrient concentrations and surface temperature.

Published
2021
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31. Temperature Effects Explain Continental Scale Distribution of Cyanobacterial Toxins

Author

Mantzouki, Evanthia, Lurling, Miquel, Fastner, Jutta, Domis, Lisette de Senerpont, Wilk-Wozniak, Elzbieta, Koreiviene, Judita, Seelen, Laura, Teurlincx, Sven, Verstijnen, Yvon, Krzton, Wojciech, Walusiak, Edward, Karosiene, Jurate, Kasperoviciene, Jurate, Savadova, Ksenija, Vitonyte, Irma, Cillero-Castro, Carmen, Budzynska, Agnieszka, Goldyn, Ryszard, Kozak, Anna, Rosinska, Joanna, Szelag-Wasielewska, Elzbieta, Domek, Piotr, Jakubowska-Krepska, Natalia, Kwasizur, Kinga, Messyasz, Beata, Pelechata, Aleksandra, Pelechaty, Mariusz, Kokocinski, Mikolaj, Garcia-Murcia, Ana, Real, Monserrat, Romans, Elvira, Noguero-Ribes, Jordi, Parreno Duque, David, Fernandez-Moran, Elisabeth, Karakaya, Nusret, Haggqvist, Kerstin, Demir, Nilsun, Beklioglu, Meryem, Filiz, Nur, Levi, Eti E., Iskin, Ugur, Bezirci, Gizem, Tavsanoglu, Ulku Nihan, Ozhan, Koray, Gkelis, Spyros, Panou, Manthos, Fakioglu, Ozden, Avagianos, Christos, Kaloudis, Triantafyllos, Celik, Kemal, Yilmaz, Mete, Marce, Rafael, Catalán, Núria, Bravo, Andrea Garcia, Buck, Moritz, Colom-Montero, William, Mustonen, Kristiina, Pierson, Don, Yang, Yang, Raposeiro, Pedro M., Goncalves, Vitor, Antoniou, Maria G., Tsiarta, Nikoletta, McCarthy, Valerie, Perello, Victor C., Feldmann, Tonu, Laas, Alo, Panksep, Kristel, Tuvikene, Lea, Gagala, Ilona, Mankiewicz-Boczek, Joana, Yagci, Meral Apaydin, Cinar, Sakir, Capkin, Kadir, Yagci, Abdulkadir, Cesur, Mehmet, Bilgin, Fuat, Bulut, Cafer, Uysal, Rahmi, Obertegger, Ulrike, Boscaini, Adriano, Flaim, Giovanna, Salmaso, Nico, Cerasino, Leonardo, Richardson, Jessica, Visser, Petra M., Verspagen, Jolanda M. H., Karan, Tunay, Soylu, Elif Neyran, Maraslioglu, Faruk, Napiorkowska-Krzebietke, Agnieszka, Ochocka, Agnieszka, Pasztaleniec, Agnieszka, Antao-Geraldes, Ana M., Vasconcelos, Vitor, Morais, Joao, Vale, Micaela, Koker, Latife, Akcaalan, Reyhan, Albay, Meric, Maronic, Dubravka Spoljaric, Stevic, Filip, Pfeiffer, Tanja Zuna, Fonvielle, Jeremy, Straile, Dietmar, Rothhaupt, Karl-Otto, Hansson, Lars-Anders, Urrutia Cordero, Pablo, Blaha, Ludek, Geris, Rodan, Frankova, Marketa, Kocer, Mehmet Ali Turan, Alp, Mehmet Tahir, Remec-Rekar, Spela, Elersek, Tina, Triantis, Theodoros, Zervou, Sevasti-Kiriaki, Hiskia, Anastasia, Haande, Sigrid, Skjelbred, Birger, Madrecka, Beata, Nemova, Hana, Drastichova, Iveta, Chomova, Lucia, Edwards, Christine, Sevindik, Tugba Ongun, Tunca, Hatice, OEnem, Burcin, Aleksovski, Boris, Krstic, Svetislav, Vucelic, Itana Bokan, Nawrocka, Lidia, Salmi, Pauliina, Machado-Vieira, Danielle, de Oliveira, Alinne Gurjao, Delgado-Martin, Jordi, Garcia, David, Cereijo, Jose Luis, Goma, Joan, Trapote, Mari Carmen, Vegas-Vilarrubia, Teresa, Obrador, Biel, Grabowska, Magdalena, Karpowicz, Maciej, Chmura, Damian, Ubeda, Barbara, Angel Galvez, Jose, Ozen, Arda, Christoffersen, Kirsten Seestern, Warming, Trine Perlt, Kobos, Justyna, Mazur-Marzec, Hanna, Perez-Martinez, Carmen, Ramos-Rodriguez, Eloisa, Arvola, Lauri, Alcaraz-Parraga, Pablo, Toporowska, Magdalena, Pawlik-Skowronska, Barbara, Niedzwiecki, Michal, Peczula, Wojciech, Leira, Manel, Hernandez, Armand, Moreno-Ostos, Enrique, Maria Blanco, Jose, Rodriguez, Valeriano, Juan Montes-Perez, Jorge, Palomino, Roberto L., Rodriguez-Perez, Estela, Carballeira, Rafael, Camacho, Antonio, Picazo, Antonio, Rochera, Carlos, Santamans, Anna C., Ferriol, Carmen, Romo, Susana, Miguel Soria, Juan, Dunalska, Julita, Sienska, Justyna, Szymanski, Daniel, Kruk, Marek, Kostrzewska-Szlakowska, Iwona, Jasser, Iwona, Zutinic, Petar, Udovic, Marija Gligora, Plenkovic-Moraj, Andelka, Frak, Magdalena, Bankowska-Sobczak, Agnieszka, Wasilewicz, Michal, Ozkan, Korhan, Maliaka, Valentini, Kangro, Kersti, Grossart, Hans-Peter, Paerl, Hans W., Carey, Cayelan C., Ibelings, Bas W., Mantzouki, Evanthia, Lurling, Miquel, Fastner, Jutta, Domis, Lisette de Senerpont, Wilk-Wozniak, Elzbieta, Koreiviene, Judita, Seelen, Laura, Teurlincx, Sven, Verstijnen, Yvon, Krzton, Wojciech, Walusiak, Edward, Karosiene, Jurate, Kasperoviciene, Jurate, Savadova, Ksenija, Vitonyte, Irma, Cillero-Castro, Carmen, Budzynska, Agnieszka, Goldyn, Ryszard, Kozak, Anna, Rosinska, Joanna, Szelag-Wasielewska, Elzbieta, Domek, Piotr, Jakubowska-Krepska, Natalia, Kwasizur, Kinga, Messyasz, Beata, Pelechata, Aleksandra, Pelechaty, Mariusz, Kokocinski, Mikolaj, Garcia-Murcia, Ana, Real, Monserrat, Romans, Elvira, Noguero-Ribes, Jordi, Parreno Duque, David, Fernandez-Moran, Elisabeth, Karakaya, Nusret, Haggqvist, Kerstin, Demir, Nilsun, Beklioglu, Meryem, Filiz, Nur, Levi, Eti E., Iskin, Ugur, Bezirci, Gizem, Tavsanoglu, Ulku Nihan, Ozhan, Koray, Gkelis, Spyros, Panou, Manthos, Fakioglu, Ozden, Avagianos, Christos, Kaloudis, Triantafyllos, Celik, Kemal, Yilmaz, Mete, Marce, Rafael, Catalán, Núria, Bravo, Andrea Garcia, Buck, Moritz, Colom-Montero, William, Mustonen, Kristiina, Pierson, Don, Yang, Yang, Raposeiro, Pedro M., Goncalves, Vitor, Antoniou, Maria G., Tsiarta, Nikoletta, McCarthy, Valerie, Perello, Victor C., Feldmann, Tonu, Laas, Alo, Panksep, Kristel, Tuvikene, Lea, Gagala, Ilona, Mankiewicz-Boczek, Joana, Yagci, Meral Apaydin, Cinar, Sakir, Capkin, Kadir, Yagci, Abdulkadir, Cesur, Mehmet, Bilgin, Fuat, Bulut, Cafer, Uysal, Rahmi, Obertegger, Ulrike, Boscaini, Adriano, Flaim, Giovanna, Salmaso, Nico, Cerasino, Leonardo, Richardson, Jessica, Visser, Petra M., Verspagen, Jolanda M. H., Karan, Tunay, Soylu, Elif Neyran, Maraslioglu, Faruk, Napiorkowska-Krzebietke, Agnieszka, Ochocka, Agnieszka, Pasztaleniec, Agnieszka, Antao-Geraldes, Ana M., Vasconcelos, Vitor, Morais, Joao, Vale, Micaela, Koker, Latife, Akcaalan, Reyhan, Albay, Meric, Maronic, Dubravka Spoljaric, Stevic, Filip, Pfeiffer, Tanja Zuna, Fonvielle, Jeremy, Straile, Dietmar, Rothhaupt, Karl-Otto, Hansson, Lars-Anders, Urrutia Cordero, Pablo, Blaha, Ludek, Geris, Rodan, Frankova, Marketa, Kocer, Mehmet Ali Turan, Alp, Mehmet Tahir, Remec-Rekar, Spela, Elersek, Tina, Triantis, Theodoros, Zervou, Sevasti-Kiriaki, Hiskia, Anastasia, Haande, Sigrid, Skjelbred, Birger, Madrecka, Beata, Nemova, Hana, Drastichova, Iveta, Chomova, Lucia, Edwards, Christine, Sevindik, Tugba Ongun, Tunca, Hatice, OEnem, Burcin, Aleksovski, Boris, Krstic, Svetislav, Vucelic, Itana Bokan, Nawrocka, Lidia, Salmi, Pauliina, Machado-Vieira, Danielle, de Oliveira, Alinne Gurjao, Delgado-Martin, Jordi, Garcia, David, Cereijo, Jose Luis, Goma, Joan, Trapote, Mari Carmen, Vegas-Vilarrubia, Teresa, Obrador, Biel, Grabowska, Magdalena, Karpowicz, Maciej, Chmura, Damian, Ubeda, Barbara, Angel Galvez, Jose, Ozen, Arda, Christoffersen, Kirsten Seestern, Warming, Trine Perlt, Kobos, Justyna, Mazur-Marzec, Hanna, Perez-Martinez, Carmen, Ramos-Rodriguez, Eloisa, Arvola, Lauri, Alcaraz-Parraga, Pablo, Toporowska, Magdalena, Pawlik-Skowronska, Barbara, Niedzwiecki, Michal, Peczula, Wojciech, Leira, Manel, Hernandez, Armand, Moreno-Ostos, Enrique, Maria Blanco, Jose, Rodriguez, Valeriano, Juan Montes-Perez, Jorge, Palomino, Roberto L., Rodriguez-Perez, Estela, Carballeira, Rafael, Camacho, Antonio, Picazo, Antonio, Rochera, Carlos, Santamans, Anna C., Ferriol, Carmen, Romo, Susana, Miguel Soria, Juan, Dunalska, Julita, Sienska, Justyna, Szymanski, Daniel, Kruk, Marek, Kostrzewska-Szlakowska, Iwona, Jasser, Iwona, Zutinic, Petar, Udovic, Marija Gligora, Plenkovic-Moraj, Andelka, Frak, Magdalena, Bankowska-Sobczak, Agnieszka, Wasilewicz, Michal, Ozkan, Korhan, Maliaka, Valentini, Kangro, Kersti, Grossart, Hans-Peter, Paerl, Hans W., Carey, Cayelan C., and Ibelings, Bas W.

Abstract

Insight into how environmental change determines the production and distribution of cyanobacterial toxins is necessary for risk assessment. Management guidelines currently focus on hepatotoxins (microcystins). Increasing attention is given to other classes, such as neurotoxins (e.g., anatoxin-a) and cytotoxins (e.g., cylindrospermopsin) due to their potency. Most studies examine the relationship between individual toxin variants and environmental factors, such as nutrients, temperature and light. In summer 2015, we collected samples across Europe to investigate the effect of nutrient and temperature gradients on the variability of toxin production at a continental scale. Direct and indirect effects of temperature were the main drivers of the spatial distribution in the toxins produced by the cyanobacterial community, the toxin concentrations and toxin quota. Generalized linear models showed that a Toxin Diversity Index (TDI) increased with latitude, while it decreased with water stability. Increases in TDI were explained through a significant increase in toxin variants such as MC-YR, anatoxin and cylindrospermopsin, accompanied by a decreasing presence of MC-LR. While global warming continues, the direct and indirect effects of increased lake temperatures will drive changes in the distribution of cyanobacterial toxins in Europe, potentially promoting selection of a few highly toxic species or strains.

Published
2018
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32. A European Multi Lake Survey dataset of environmental variables, phytoplankton pigments and cyanotoxins

Author

Mantzouki, Evanthia, Campbell, James, van Loon, Emiel, Visser, Petra, Konstantinou, Iosif, Antoniou, Maria, Giuliani, Grégory, Machado-Vieira, Danielle, Gurjão de Oliveira, Alinne, Maronić, Dubravka Špoljarić, Stević, Filip, Pfeiffer, Tanja Žuna, Vucelić, Itana Bokan, Žutinić, Petar, Udovič, Marija Gligora, Plenković-Moraj, Anđelka, Tsiarta, Nikoletta, Bláha, Luděk, Geriš, Rodan, Fránková, Markéta, Christoffersen, Kirsten Seestern, Warming, Trine Perlt, Feldmann, Tõnu, Laas, Alo, Panksep, Kristel, Tuvikene, Lea, Kangro, Kersti, Häggqvist, Kerstin, Salmi, Pauliina, Arvola, Lauri, Fastner, Jutta, Straile, Dietmar, Rothhaupt, Karl-Otto, Fonvielle, Jeremy, Grossart, Hans-Peter, Avagianos, Christos, Kaloudis, Triantafyllos, Triantis, Theodoros, Zervou, Sevasti-Kiriaki, Hiskia, Anastasia, Gkelis, Spyros, Panou, Manthos, McCarthy, Valerie, Perello, Victor C, Obertegger, Ulrike, Boscaini, Adriano, Flaim, Giovanna, Salmaso, Nico, Cerasino, Leonardo, Koreivienė, Judita, Karosienė, Jūratė, Kasperovičienė, Jūratė, Savadova, Ksenija, Vitonytė, Irma, Haande, Sigrid, Skjelbred, Birger, Grabowska, Magdalena, Karpowicz, Maciej, Chmura, Damian, Nawrocka, Lidia, Kobos, Justyna, Mazur-Marzec, Hanna, Alcaraz-Párraga, Pablo, Wilk-Woźniak, Elżbieta, Krztoń, Wojciech, Walusiak, Edward, Gagala, Ilona, Mankiewicz-Boczek, Joana, Toporowska, Magdalena, Pawlik-Skowronska, Barbara, Niedźwiecki, Michał, Pęczuła, Wojciech, Napiórkowska-Krzebietke, Agnieszka, Dunalska, Julita, Sieńska, Justyna, Szymański, Daniel, Kruk, Marek, Budzyńska, Agnieszka, Goldyn, Ryszard, Kozak, Anna, Rosińska, Joanna, Szeląg-Wasielewska, Elżbieta, Domek, Piotr, Jakubowska-Krepska, Natalia, Kwasizur, Kinga, Messyasz, Beata, Pełechata, Aleksandra, Pełechaty, Mariusz, Kokocinski, Mikolaj, Madrecka, Beata, Kostrzewska-Szlakowska, Iwona, Frąk, Magdalena, Bańkowska-Sobczak, Agnieszka, Wasilewicz, Michał, Ochocka, Agnieszka, Pasztaleniec, Agnieszka, Jasser, Iwona, Antão-Geraldes, Ana M, Leira, Manel, Hernández, Armand, Vasconcelos, Vitor, Morais, João, Vale, Micaela, Raposeiro, Pedro M, Gonçalves, Vítor, Aleksovski, Boris, Krstić, Svetislav, Nemova, Hana, Drastichova, Iveta, Chomova, Lucia, Remec-Rekar, Spela, Elersek, Tina, Delgado-Martín, Jordi, García, David, Cereijo, Jose Luís, Gomà, Joan, Trapote, Mari Carmen, Vegas-Vilarrúbia, Teresa, Obrador, Biel, García-Murcia, Ana, Real, Monserrat, Romans, Elvira, Noguero-Ribes, Jordi, Duque, David Parreño, Fernández-Morán, Elísabeth, Úbeda, Bárbara, Gálvez, José Ángel, Marcé, Rafael, Catalán, Núria, Pérez-Martínez, Carmen, Ramos-Rodríguez, Eloísa, Cillero-Castro, Carmen, Moreno-Ostos, Enrique, Blanco, José María, Rodríguez, Valeriano, Montes-Pérez, Jorge Juan, Palomino, Roberto L, Rodríguez-Pérez, Estela, Carballeira, Rafael, Camacho, Antonio, Picazo, Antonio, Rochera, Carlos, Santamans, Anna C, Ferriol, Carmen, Romo, Susana, Soria, Juan Miguel, Hansson, Lars-Anders, Urrutia-Cordero, Pablo, Özen, Arda, Bravo, Andrea G, Buck, Moritz, Colom-Montero, William, Mustonen, Kristiina, Pierson, Don, Yang, Yang, M H Verspagen, Jolanda, de Senerpont Domis, Lisette N, Seelen, Laura, Verstijnen, Yvon, Lürling, Miquel, Maliaka, Valentini, Faassen, Elisabeth J, Latour, Delphine, Carey, Cayelan C, W Paerl, Hans, Torokne, Andrea, Karan, Tünay, Demir, Nilsun, Beklioğlu, Meryem, Filiz, Nur, E Levi, Eti, Iskin, Uğur, Bezirci, Gizem, Tavşanoğlu, Ülkü Nihan, Çelik, Kemal, Özhan, Koray, Karakaya, Nusret, Koçer, Mehmet Ali Turan, Yilmaz, Mete, Maraşlıoğlu, Faruk, Fakioglu, Özden, Soylu, Elif Neyran, Yağcı, Meral Apaydın, Çınar, Şakir, Çapkın, Kadir, Yağcı, Abdulkadir, Cesur, Mehmet, Bilgin, Fuat, Bulut, Cafer, Uysal, Rahmi, Köker, Latife, Akçaalan, Reyhan, Albay, Meriç, Alp, Mehmet Tahir, Özkan, Korhan, Sevindik, Tuğba Ongun, Tunca, Hatice, Önem, Burçin, Richardson, Jessica, Edwards, Christine, Bergkemper, Victoria, O'Leary, Sarah, Beirne, Eilish, Cromie, Hannah, Ibelings, Bastiaan W, Mantzouki, Evanthia, Campbell, James, van Loon, Emiel, Visser, Petra, Konstantinou, Iosif, Antoniou, Maria, Giuliani, Grégory, Machado-Vieira, Danielle, Gurjão de Oliveira, Alinne, Maronić, Dubravka Špoljarić, Stević, Filip, Pfeiffer, Tanja Žuna, Vucelić, Itana Bokan, Žutinić, Petar, Udovič, Marija Gligora, Plenković-Moraj, Anđelka, Tsiarta, Nikoletta, Bláha, Luděk, Geriš, Rodan, Fránková, Markéta, Christoffersen, Kirsten Seestern, Warming, Trine Perlt, Feldmann, Tõnu, Laas, Alo, Panksep, Kristel, Tuvikene, Lea, Kangro, Kersti, Häggqvist, Kerstin, Salmi, Pauliina, Arvola, Lauri, Fastner, Jutta, Straile, Dietmar, Rothhaupt, Karl-Otto, Fonvielle, Jeremy, Grossart, Hans-Peter, Avagianos, Christos, Kaloudis, Triantafyllos, Triantis, Theodoros, Zervou, Sevasti-Kiriaki, Hiskia, Anastasia, Gkelis, Spyros, Panou, Manthos, McCarthy, Valerie, Perello, Victor C, Obertegger, Ulrike, Boscaini, Adriano, Flaim, Giovanna, Salmaso, Nico, Cerasino, Leonardo, Koreivienė, Judita, Karosienė, Jūratė, Kasperovičienė, Jūratė, Savadova, Ksenija, Vitonytė, Irma, Haande, Sigrid, Skjelbred, Birger, Grabowska, Magdalena, Karpowicz, Maciej, Chmura, Damian, Nawrocka, Lidia, Kobos, Justyna, Mazur-Marzec, Hanna, Alcaraz-Párraga, Pablo, Wilk-Woźniak, Elżbieta, Krztoń, Wojciech, Walusiak, Edward, Gagala, Ilona, Mankiewicz-Boczek, Joana, Toporowska, Magdalena, Pawlik-Skowronska, Barbara, Niedźwiecki, Michał, Pęczuła, Wojciech, Napiórkowska-Krzebietke, Agnieszka, Dunalska, Julita, Sieńska, Justyna, Szymański, Daniel, Kruk, Marek, Budzyńska, Agnieszka, Goldyn, Ryszard, Kozak, Anna, Rosińska, Joanna, Szeląg-Wasielewska, Elżbieta, Domek, Piotr, Jakubowska-Krepska, Natalia, Kwasizur, Kinga, Messyasz, Beata, Pełechata, Aleksandra, Pełechaty, Mariusz, Kokocinski, Mikolaj, Madrecka, Beata, Kostrzewska-Szlakowska, Iwona, Frąk, Magdalena, Bańkowska-Sobczak, Agnieszka, Wasilewicz, Michał, Ochocka, Agnieszka, Pasztaleniec, Agnieszka, Jasser, Iwona, Antão-Geraldes, Ana M, Leira, Manel, Hernández, Armand, Vasconcelos, Vitor, Morais, João, Vale, Micaela, Raposeiro, Pedro M, Gonçalves, Vítor, Aleksovski, Boris, Krstić, Svetislav, Nemova, Hana, Drastichova, Iveta, Chomova, Lucia, Remec-Rekar, Spela, Elersek, Tina, Delgado-Martín, Jordi, García, David, Cereijo, Jose Luís, Gomà, Joan, Trapote, Mari Carmen, Vegas-Vilarrúbia, Teresa, Obrador, Biel, García-Murcia, Ana, Real, Monserrat, Romans, Elvira, Noguero-Ribes, Jordi, Duque, David Parreño, Fernández-Morán, Elísabeth, Úbeda, Bárbara, Gálvez, José Ángel, Marcé, Rafael, Catalán, Núria, Pérez-Martínez, Carmen, Ramos-Rodríguez, Eloísa, Cillero-Castro, Carmen, Moreno-Ostos, Enrique, Blanco, José María, Rodríguez, Valeriano, Montes-Pérez, Jorge Juan, Palomino, Roberto L, Rodríguez-Pérez, Estela, Carballeira, Rafael, Camacho, Antonio, Picazo, Antonio, Rochera, Carlos, Santamans, Anna C, Ferriol, Carmen, Romo, Susana, Soria, Juan Miguel, Hansson, Lars-Anders, Urrutia-Cordero, Pablo, Özen, Arda, Bravo, Andrea G, Buck, Moritz, Colom-Montero, William, Mustonen, Kristiina, Pierson, Don, Yang, Yang, M H Verspagen, Jolanda, de Senerpont Domis, Lisette N, Seelen, Laura, Verstijnen, Yvon, Lürling, Miquel, Maliaka, Valentini, Faassen, Elisabeth J, Latour, Delphine, Carey, Cayelan C, W Paerl, Hans, Torokne, Andrea, Karan, Tünay, Demir, Nilsun, Beklioğlu, Meryem, Filiz, Nur, E Levi, Eti, Iskin, Uğur, Bezirci, Gizem, Tavşanoğlu, Ülkü Nihan, Çelik, Kemal, Özhan, Koray, Karakaya, Nusret, Koçer, Mehmet Ali Turan, Yilmaz, Mete, Maraşlıoğlu, Faruk, Fakioglu, Özden, Soylu, Elif Neyran, Yağcı, Meral Apaydın, Çınar, Şakir, Çapkın, Kadir, Yağcı, Abdulkadir, Cesur, Mehmet, Bilgin, Fuat, Bulut, Cafer, Uysal, Rahmi, Köker, Latife, Akçaalan, Reyhan, Albay, Meriç, Alp, Mehmet Tahir, Özkan, Korhan, Sevindik, Tuğba Ongun, Tunca, Hatice, Önem, Burçin, Richardson, Jessica, Edwards, Christine, Bergkemper, Victoria, O'Leary, Sarah, Beirne, Eilish, Cromie, Hannah, and Ibelings, Bastiaan W

Abstract

Under ongoing climate change and increasing anthropogenic activity, which continuously challenge ecosystem resilience, an in-depth understanding of ecological processes is urgently needed. Lakes, as providers of numerous ecosystem services, face multiple stressors that threaten their functioning. Harmful cyanobacterial blooms are a persistent problem resulting from nutrient pollution and climate-change induced stressors, like poor transparency, increased water temperature and enhanced stratification. Consistency in data collection and analysis methods is necessary to achieve fully comparable datasets and for statistical validity, avoiding issues linked to disparate data sources. The European Multi Lake Survey (EMLS) in summer 2015 was an initiative among scientists from 27 countries to collect and analyse lake physical, chemical and biological variables in a fully standardized manner. This database includes in-situ lake variables along with nutrient, pigment and cyanotoxin data of 369 lakes in Europe, which were centrally analysed in dedicated laboratories. Publishing the EMLS methods and dataset might inspire similar initiatives to study across large geographic areas that will contribute to better understanding lake responses in a changing environment.

Published
2018

33. Delving deeper:Metabolic processes in the metalimnion of stratified lakes

Author

Giling, Darren P., Staehr, Peter A., Grossart, Hans Peter, Andersen, Mikkel René, Boehrer, Bertram, Escot, Carmelo, Evrendilek, Fatih, Gómez-Gener, Lluís, Honti, Mark, Jones, Ian D., Karakaya, Nusret, Laas, Alo, Moreno-Ostos, Enrique, Rinke, Karsten, Scharfenberger, Ulrike, Schmidt, Silke R., Weber, Michael, Woolway, R. Iestyn, Zwart, Jacob A., and Obrador, Biel

Subjects
MODEL, DYNAMICS, ORGANIC-MATTER, RESPIRATION, DISSOLVED-OXYGEN, WATER LAKE, PHYTOPLANKTON, PATTERNS, AQUATIC ECOSYSTEM METABOLISM, HIGH-ELEVATION LAKE, Institut für Biochemie und Biologie
Abstract

Many lakes exhibit seasonal stratification, during which they develop strong thermal and chemical gradients. An expansion of depth-integrated monitoring programs has provided insight into the importance of organic carbon processing that occurs below the upper mixed layer. However, the chemical and physical drivers of metabolism and metabolic coupling remain unresolved, especially in the metalimnion. In this depth zone, sharp gradients in key resources such as light and temperature co-occur with dynamic physical conditions that influence metabolic processes directly and simultaneously hamper the accurate tracing of biological activity. We evaluated the drivers of metalimnetic metabolism and its associated uncertainty across 10 stratified lakes in Europe and North America. We hypothesized that the metalimnion would contribute highly to whole-lake functioning in clear oligotrophic lakes, and that metabolic rates would be highly variable in unstable polymictic lakes. Depth-integrated rates of gross primary production (GPP) and ecosystem respiration (ER) were modelled from diel dissolved oxygen curves using a Bayesian approach. Metabolic estimates were more uncertain below the epilimnion, but uncertainty was not consistently related to lake morphology or mixing regime. Metalimnetic rates exhibited high day-to-day variability in all trophic states, with the metalimnetic contribution to daily whole-lake GPP and ER ranging from 0% to 87% and

Published
2017

34. Determining Lake Metabolism Using Diel Oxygen Technique: A Case Study Of Lake Abant

Author

Turan, Gonca Silahan and Karakaya, Nusret

Abstract

Recently, diel oxygen technique has been intensively used to estimate gross primary production (GPP), net ecosystem production (NEP), and ecosystem respiration (R) from lakes, rivers, and lagoons. This study (1) estimated GPP, NEP, and R of Lake Abant using diel oxygen technique at three locations over the period of 2012 to 2014; and (2) built empirical models to predict temporal changes in GPP, NEP, and R. To estimate the lake metabolism components, dissolved oxygen concentration (DO, mg L-1), saturated dissolved oxygen value (O-2sat, %), and water temperature (T-w, degrees C) were continuously measured using in situ water quality monitoring probes, while solar radiation (SR, W m(-2)) and wind speed (WS, m s(-1)) were monitored using a meteorological station set up by the lake. Lake Abant was found to be of a net heterotrophic character (GPP/R < 1 and NEP < 0) for 2012, 2013 and 2014. Also, temporal GPP and R dynamics were modelled and validated on a monthly basis.

Published
2017

35. A European Multi Lake Survey dataset of environmental variables, phytoplankton pigments and cyanotoxins

Author

Mantzouki, Evanthia, primary, Campbell, James, additional, van Loon, Emiel, additional, Visser, Petra, additional, Konstantinou, Iosif, additional, Antoniou, Maria, additional, Giuliani, Grégory, additional, Machado-Vieira, Danielle, additional, Gurjão de Oliveira, Alinne, additional, Maronić, Dubravka Špoljarić, additional, Stević, Filip, additional, Pfeiffer, Tanja Žuna, additional, Vucelić, Itana Bokan, additional, Žutinić, Petar, additional, Udovič, Marija Gligora, additional, Plenković-Moraj, Anđelka, additional, Tsiarta, Nikoletta, additional, Bláha, Luděk, additional, Geriš, Rodan, additional, Fránková, Markéta, additional, Christoffersen, Kirsten Seestern, additional, Warming, Trine Perlt, additional, Feldmann, Tõnu, additional, Laas, Alo, additional, Panksep, Kristel, additional, Tuvikene, Lea, additional, Kangro, Kersti, additional, Häggqvist, Kerstin, additional, Salmi, Pauliina, additional, Arvola, Lauri, additional, Fastner, Jutta, additional, Straile, Dietmar, additional, Rothhaupt, Karl-Otto, additional, Fonvielle, Jeremy, additional, Grossart, Hans-Peter, additional, Avagianos, Christos, additional, Kaloudis, Triantafyllos, additional, Triantis, Theodoros, additional, Zervou, Sevasti-Kiriaki, additional, Hiskia, Anastasia, additional, Gkelis, Spyros, additional, Panou, Manthos, additional, McCarthy, Valerie, additional, Perello, Victor C., additional, Obertegger, Ulrike, additional, Boscaini, Adriano, additional, Flaim, Giovanna, additional, Salmaso, Nico, additional, Cerasino, Leonardo, additional, Koreivienė, Judita, additional, Karosienė, Jūratė, additional, Kasperovičienė, Jūratė, additional, Savadova, Ksenija, additional, Vitonytė, Irma, additional, Haande, Sigrid, additional, Skjelbred, Birger, additional, Grabowska, Magdalena, additional, Karpowicz, Maciej, additional, Chmura, Damian, additional, Nawrocka, Lidia, additional, Kobos, Justyna, additional, Mazur-Marzec, Hanna, additional, Alcaraz-Párraga, Pablo, additional, Wilk-Woźniak, Elżbieta, additional, Krztoń, Wojciech, additional, Walusiak, Edward, additional, Gagala, Ilona, additional, Mankiewicz-Boczek, Joana, additional, Toporowska, Magdalena, additional, Pawlik-Skowronska, Barbara, additional, Niedźwiecki, Michał, additional, Pęczuła, Wojciech, additional, Napiórkowska-Krzebietke, Agnieszka, additional, Dunalska, Julita, additional, Sieńska, Justyna, additional, Szymański, Daniel, additional, Kruk, Marek, additional, Budzyńska, Agnieszka, additional, Goldyn, Ryszard, additional, Kozak, Anna, additional, Rosińska, Joanna, additional, Szeląg-Wasielewska, Elżbieta, additional, Domek, Piotr, additional, Jakubowska-Krepska, Natalia, additional, Kwasizur, Kinga, additional, Messyasz, Beata, additional, Pełechata, Aleksandra, additional, Pełechaty, Mariusz, additional, Kokocinski, Mikolaj, additional, Madrecka, Beata, additional, Kostrzewska-Szlakowska, Iwona, additional, Frąk, Magdalena, additional, Bańkowska-Sobczak, Agnieszka, additional, Wasilewicz, Michał, additional, Ochocka, Agnieszka, additional, Pasztaleniec, Agnieszka, additional, Jasser, Iwona, additional, Antão-Geraldes, Ana M., additional, Leira, Manel, additional, Hernández, Armand, additional, Vasconcelos, Vitor, additional, Morais, João, additional, Vale, Micaela, additional, Raposeiro, Pedro M., additional, Gonçalves, Vítor, additional, Aleksovski, Boris, additional, Krstić, Svetislav, additional, Nemova, Hana, additional, Drastichova, Iveta, additional, Chomova, Lucia, additional, Remec-Rekar, Spela, additional, Elersek, Tina, additional, Delgado-Martín, Jordi, additional, García, David, additional, Cereijo, Jose Luís, additional, Gomà, Joan, additional, Trapote, Mari Carmen, additional, Vegas-Vilarrúbia, Teresa, additional, Obrador, Biel, additional, García-Murcia, Ana, additional, Real, Monserrat, additional, Romans, Elvira, additional, Noguero-Ribes, Jordi, additional, Duque, David Parreño, additional, Fernández-Morán, Elísabeth, additional, Úbeda, Bárbara, additional, Gálvez, José Ángel, additional, Marcé, Rafael, additional, Catalán, Núria, additional, Pérez-Martínez, Carmen, additional, Ramos-Rodríguez, Eloísa, additional, Cillero-Castro, Carmen, additional, Moreno-Ostos, Enrique, additional, Blanco, José María, additional, Rodríguez, Valeriano, additional, Montes-Pérez, Jorge Juan, additional, Palomino, Roberto L., additional, Rodríguez-Pérez, Estela, additional, Carballeira, Rafael, additional, Camacho, Antonio, additional, Picazo, Antonio, additional, Rochera, Carlos, additional, Santamans, Anna C., additional, Ferriol, Carmen, additional, Romo, Susana, additional, Soria, Juan Miguel, additional, Hansson, Lars-Anders, additional, Urrutia-Cordero, Pablo, additional, Özen, Arda, additional, Bravo, Andrea G., additional, Buck, Moritz, additional, Colom-Montero, William, additional, Mustonen, Kristiina, additional, Pierson, Don, additional, Yang, Yang, additional, M. H. Verspagen, Jolanda, additional, de Senerpont Domis, Lisette N., additional, Seelen, Laura, additional, Teurlincx, Sven, additional, Verstijnen, Yvon, additional, Lürling, Miquel, additional, Maliaka, Valentini, additional, Faassen, Elisabeth J., additional, Latour, Delphine, additional, Carey, Cayelan C., additional, W. Paerl, Hans, additional, Torokne, Andrea, additional, Karan, Tünay, additional, Demir, Nilsun, additional, Beklioğlu, Meryem, additional, Filiz, Nur, additional, E. Levi, Eti, additional, Iskin, Uğur, additional, Bezirci, Gizem, additional, Tavşanoğlu, Ülkü Nihan, additional, Çelik, Kemal, additional, Özhan, Koray, additional, Karakaya, Nusret, additional, Koçer, Mehmet Ali Turan, additional, Yilmaz, Mete, additional, Maraşlıoğlu, Faruk, additional, Fakioglu, Özden, additional, Soylu, Elif Neyran, additional, Yağcı, Meral Apaydın, additional, Çınar, Şakir, additional, Çapkın, Kadir, additional, Yağcı, Abdulkadir, additional, Cesur, Mehmet, additional, Bilgin, Fuat, additional, Bulut, Cafer, additional, Uysal, Rahmi, additional, Köker, Latife, additional, Akçaalan, Reyhan, additional, Albay, Meriç, additional, Alp, Mehmet Tahir, additional, Özkan, Korhan, additional, Sevindik, Tuğba Ongun, additional, Tunca, Hatice, additional, Önem, Burçin, additional, Richardson, Jessica, additional, Edwards, Christine, additional, Bergkemper, Victoria, additional, O'Leary, Sarah, additional, Beirne, Eilish, additional, Cromie, Hannah, additional, and Ibelings, Bastiaan W., additional

Published
2018
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38. Predicting Diel, Diurnal And Nocturnal Dynamics Of Dissolved Oxygen And Chlorophyll-A Using Regression Models And Neural Networks

Author

Karakaya, Nusret, Evrendilek, Fatih, Gungor, Kerem, and Onal, Deniz

Abstract

Human-induced and natural interruptions with continuous streams of observational data necessitate the development of gap-filling and prediction strategies towards better understanding, monitoring and management of aquatic systems. This study quantified the efficacy of multiple non-linear regression (MNLR) versus artificial neural network (ANN) models as well as the temporal partitioning of diurnal versus nocturnal data for the predictions of chlorophyll-a (chl-a) and dissolved oxygen (DO) dynamics. The temporal partitioning increased the predictive performances of the best MNLR models of diurnal DO by 45% and nocturnal DO by 4%, relative to the best diel MNLR model of diel DO (r(adj)(2) = 68.8%). The ANN-based predictions had a higher predictive power than the MNLR-based predictions for both chl-a and DO except for diurnal DO dynamics. The best ANNs based on independent validations were multilayer perceptron (MLP) for diel chl-a, generalized feedforward (GFF) for diurnal and nocturnal chl-a, MLP for diel DO, GFF for diurnal DO, and MLP for nocturnal DO.

Published
2013

43. Türkiye’de havzalar arası su transferi için bir karar destek sistemi önerisi

Author

KARAKAYA, Nusret and GÖNENÇ, İ. Ethem

Subjects
Su Kaynakları, Water Resources, Havzalar arası su transferi,çevresel ve sosyoekonomik etkiler,karar desteksistemi
Abstract

Mevcut su kaynaklarının endüstriyel, tarımsal ve kentsel su ihtiyacını karşılayamaması, su kaynaklarının restorasyonu, kuraklık, mevcut su temin sisteminin performansının ve esnekliğinin artırılması, enerji üretimi vb. gerekçeler ile Türkiye dahil birçok ülkede su transfer projeleri hayata geçirilmiştir. Havza içerisinde diğer doğal kaynaklarla birlikte bir bütünü oluşturan su kaynaklarının yapay yollarla bir bölgeden bir başka bölgeye transfer edilmesi, dikkatli bir şekilde değerlendirilmesi ve analiz edilmesi gereken çevresel, sosyal ve ekonomik sorunları da beraberinde getirmektedir. Su kaynaklarının planlanması ve yönetiminde mevcut kurumsal yapı nedeniyle ciddi sıkıntılar yaşayan Türkiye’nin havzalar arası su transferi ile ilgili, karar vericilere yardımcı olabilecek, bilimsel verilerle desteklenmiş bir “karar destek sistemine” ivedilikle ihtiyacı vardır. Bu nedenle su ihtiyacının karşılanması için başka bir havzadan su transfer edilmesi seçeneğinin bilimsel verilerin ışığında irdelenebilmesi amacıyla bu çalışmada; güvenilir, basit ve Türkiye’nin mevcut kısıtlı veri birikimine uygun, konuyu sadece çevresel boyutu ile alan bir karar destek sistemi önerilmiştir. Önerilen karar destek sistemi, bir örnek olmak üzere Büyük Melen Su Transfer Projesi için uygulanmıştır.

Published
2006

44. Havzalar arası su transferine sistematik bir yaklaşım

Author

Karakaya, Nusret, Gönenç, İ. Ethem, and Çevre Mühendisliği Ana Bilim Dalı

Subjects
Environmental Engineering, Çevre Mühendisliği
Abstract

Gereksinim duyulan yerde ve/veya havza içinde mevcut su kaynaklarının endüstriyel,tarımsal ve kentsel su ihtiyacını karşılayamaması, su kaynaklarının restorasyonu,kuraklık, mevcut su temin sisteminin performansını ve esnekliğini artırmak, enerjiüretimi vb. gerekçelerle Güney Afrika, Almanya, ABD, Çin, Japonya, İran, Türkiye vedaha birçok ülkede su transfer projeleri hayata geçirilmiştir. Havza içerisinde diğerdoğal kaynaklarla birlikte bir bütünü oluşturan su kaynaklarının yapay yollarla birbölgeden bir başka bölgeye transfer edilmesi, dikkatli bir şekilde değerlendirilmesi veanaliz edilmesi gereken çevresel, sosyal ve ekonomik sorunları da beraberindegetirmektedir. Bu çalışmada, iki farklı su havzası arasında su transferinin yapılıpyapılamayacağı, transfer yapılacak ise ne kadar suyun transfer edilebileceği vb.kararların verilebilmesine yardımcı olabilecek güvenilir, basit ve ülkemizin koşullarınauyarlanabilecek, çevresel su ihtiyacı yaklaşımını esas alan bir karar destek sistemigeliştirilmiştir. Geliştirilen karar destek sistemi bir örnek olmak üzere Büyük Melen SuTransfer Projesi için uygulanmıştır.Anahtar Kelimeler: Havzalar arası su transferi, Kara destek sistemi, Çevresel suihtiyacı Interbasin water transfer projects have been carried out in many countries like SouthAfrica, Germany, USA, China, Japan, Iran and Turkey to supply water for industries,agricultural areas and urban, restoration of water resources, drought, energyproduction and improvement reliability and performance of current water supplysystem. Transfer of water from one basin to another causes environmental, social andeconomical problems that should be analyzed and evaluated carefully. In this study, areliable and simple decision support system was developed which will be adapted toTurkey?s condition for interbasin water transfer. To help decision makers to decide onthe subjects like whether the interbasin transfer is possible or not, and if it is, whatwould be the amount of water transferred between one basin to another. Furthermore,the developed system was applied to Büyük Melen water transfer project as anexample.Keywords: Interbasin water transfer, Decision support system, Environmental waterrequirement 108

Published
2006

45. Decision Making, Policy And Financing

Author

Wolflin, John P., primary, Russo, Rosemarie C., additional, Burak, Selmin, additional, Karakaya, Nusret, additional, Orbi, Abdellatif, additional, Razinkovas, Arturas, additional, Toktoraliev, Biimyrza, additional, Uzun, Guven, additional, Salas, Jessica, additional, Amanaliev, Mars, additional, Messahel, Mekki, additional, Haci, Mihriban, additional, Lagutov, Viktor, additional, and Torun, Yasin, additional

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47. Efteni Havzasında Su Kalitesi Yönetimi

Author

Karakaya, Nusret, Gönenç, İ. Ethem, Çevre Mühendisliği, Environmental Engineering, and Diğer

Subjects
Water resources, kirletici yükler, Environmental Engineering, waste load, su kaynakları, su kalitesi yönetimi, water resources, water quality, Water quality, Çevre Mühendisliği, point and diffuse sources, noktasal ve yayılı kaynaklar, Great Melen stream, Drinking water, water quality management, Quality management, su kalitesi
Abstract

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2000, Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2000, İçme suyu ihtiyacının karşılanabileceği kaynakların; insanın yaşamını kolaylaştırmak amacıyla giriştiği faaliyetler sonucu giderek kirlenmesi, kaynakların azalması veya nüfus artışından dolayı ihtiyacı karşılayamayacak olması insanları, mevcut ve potansiyel su kaynaklarının etkin kullanımı ve korunmasına yönelik kapsamlı ve uzun vadeli çözümler aramaya itmiştir. Bu bakımdan su kalitesi yönetimi; kaynakların etkin bir şekilde kullanımı ve korunması için vazgeçilmez olmuştur. Bu çalışma kapsamında; Büyük Melen Çayı’nın da içinde yer aldığı Efteni Havzası’ coğrafi, meteorolojik, hidrolojik, sosyal ve ekonomik yapı gibi kimi özellikleri özetlenmiş, Efteni Havzası’nda su kaynaklarına noktasal ve yayılı kaynaklardan gelebilecek kirletici yükler tanımlanmıştır. Havza içinde bulunan su kaynaklarının kalitesi ortaya konularak, Efteni Havzası’ nda su kalitesi yönetimi için uygulanabilir bir yaklaţým tartýţýlmýţtýr.., Pollution of the resources from which the need for potable water can be met as a result of activities carried out by the human beings in order to make their lives easier, running short of the sources or insufficient sources for needs due to population increase directed people towards the researches into the comprehensive and long-term solution concerning the protection and effective use of the present and potential water resources. Because of these facts, water quality management became mandatory for the protection and effective use of the resources. In this thesis: created data for planning, modelling has been made/to be made giving some futures of Efteni Catchment Area such as geographical, meteorological, hydrological, social and economical, climate, identified the possible waste load endangers the water resources, quality classification of the water resources in the catchment area was made according to the Turkish Water Pollution Control Regulation and, an applicable approach to water quality management in the Efteni Catchment Area was discussed., Yüksek Lisans, M.Sc.

Published
2000

48. Groundwater dependent ecosystems. Part II. Ecosystem services and management in Europe under risk of climate change and land use intensification

Author

Universitat Politècnica de València. Departamento de Ingeniería Hidráulica y Medio Ambiente - Departament d'Enginyeria Hidràulica i Medi Ambient, Klöve, Björn, Allan, Andrew, Bertrand, Guillaume, Druzynska, Elzbieta, Ertürk, Ali, Goldscheider, Nico, Henry, Sarah, Karakaya, Nusret, Karjalainen, Timo P., Koundouri, Phoebe, Kupfersberger, Hans, Kvaerner, Jens, Lundberg, Angela, Muotka, Timo, Preda, Elena, Pulido-Velazquez, M., Schipper, Peter, Universitat Politècnica de València. Departamento de Ingeniería Hidráulica y Medio Ambiente - Departament d'Enginyeria Hidràulica i Medi Ambient, Klöve, Björn, Allan, Andrew, Bertrand, Guillaume, Druzynska, Elzbieta, Ertürk, Ali, Goldscheider, Nico, Henry, Sarah, Karakaya, Nusret, Karjalainen, Timo P., Koundouri, Phoebe, Kupfersberger, Hans, Kvaerner, Jens, Lundberg, Angela, Muotka, Timo, Preda, Elena, Pulido-Velazquez, M., and Schipper, Peter

Abstract

Groundwater in sufficient amounts and of suitable quality is essential for potable water supplies, crop irrigation and healthy habitats for plant and animal biocenoses. The groundwater resource is currently under severe pressure from land use and pollution and there is evidence of dramatic changes in aquifer resources in Europe and elsewhere, despite numerous policy measures on sustainable use and protection of groundwater. Little is known about how such changes affect groundwater dependent ecosystems (GDEs), which include various aquatic and terrestrial ecosystems above ground and inside the aquifer. Future management must take this uncertainty into account. This paper focuses on multiple aspects of groundwater science, policy and sustainable management. Examples of current management methods and practices are presented for selected aquifers in Europe and an assessment is made of the effectiveness of existing policies such as the European Water Framework Directive and the Habitat Directive in practice and of how groundwaters and GDEs are managed in various conditions. The paper highlights a number of issues that should be considered in an integrated and holistic approach to future management of groundwater and its dependent ecosystems. © 2011 Elsevier Ltd.

Published
2011

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