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159 results on '"Özkundakci, Deniz"'

3. Plastic debris in lakes and reservoirs

Author

Nava, Veronica, Chandra, Sudeep, Aherne, Julian, Alfonso, María B., Antão-Geraldes, Ana M., Attermeyer, Katrin, Bao, Roberto, Bartrons, Mireia, Berger, Stella A., Biernaczyk, Marcin, Bissen, Raphael, Brookes, Justin D., Brown, David, Cañedo-Argüelles, Miguel, Canle, Moisés, Capelli, Camilla, Carballeira, Rafael, Cereijo, José Luis, Chawchai, Sakonvan, Christensen, Søren T., Christoffersen, Kirsten S., de Eyto, Elvira, Delgado, Jorge, Dornan, Tyler N., Doubek, Jonathan P., Dusaucy, Julia, Erina, Oxana, Ersoy, Zeynep, Feuchtmayr, Heidrun, Frezzotti, Maria Luce, Galafassi, Silvia, Gateuille, David, Gonçalves, Vitor, Grossart, Hans-Peter, Hamilton, David P., Harris, Ted D., Kangur, Külli, Kankılıç, Gökben Başaran, Kessler, Rebecca, Kiel, Christine, Krynak, Edward M., Leiva-Presa, Àngels, Lepori, Fabio, Matias, Miguel G., Matsuzaki, Shin-ichiro S., McElarney, Yvonne, Messyasz, Beata, Mitchell, Mark, Mlambo, Musa C., Motitsoe, Samuel N., Nandini, Sarma, Orlandi, Valentina, Owens, Caroline, Özkundakci, Deniz, Pinnow, Solvig, Pociecha, Agnieszka, Raposeiro, Pedro Miguel, Rõõm, Eva-Ingrid, Rotta, Federica, Salmaso, Nico, Sarma, S. S. S., Sartirana, Davide, Scordo, Facundo, Sibomana, Claver, Siewert, Daniel, Stepanowska, Katarzyna, Tavşanoğlu, Ülkü Nihan, Tereshina, Maria, Thompson, James, Tolotti, Monica, Valois, Amanda, Verburg, Piet, Welsh, Brittany, Wesolek, Brian, Weyhenmeyer, Gesa A., Wu, Naicheng, Zawisza, Edyta, Zink, Lauren, and Leoni, Barbara

Published
2023
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5. Simulating water balance and nutrient losses in a pastoral catchment using the SWAT+ model: added value of isotope data.

Author

Yulianti, Meti, Özkundakci, Deniz, and Ridwansyah, Iwan

Abstract

New Zealand’s freshwater is under increasing pressure from intensified dairy farming. This study assesses agricultural nitrogen loads from small pastoral catchments contributing to eutrophication and periodic algae blooms in a lake. Using the Soil and Water Assessment Tool (SWAT+), we simulated hydrological processes and nutrient loads, incorporating water (δ2H, δ18O) and nitrate (δ15N, δ18O) isotope data to improve model performance. The SWAT+ model was calibrated and validated with flow and nitrate data, achieving R2 values of 0.65–0.90, Nash-Sutcliffe efficiency (NSE) of 0.46–0.82, and percent bias (PBIAS) between 10.24% and 33.48%. The study demonstrates that stable isotope insights can enhance SWAT+ modelling accuracy and highlight the need for better fertilizer management to reduce nutrient loads. [ABSTRACT FROM AUTHOR]

Published
2024
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7. Patterns of CO2 concentration and inorganic carbon limitation of phytoplankton biomass in agriculturally eutrophic lakes

Author

Zagarese, Horacio E., Sagrario, María de los Ángeles González, Wolf-Gladrow, Dieter, Nõges, Peeter, Nõges, Tiina, Kangur, Külli, Matsuzaki, Shin-Ichiro S., Kohzu, Ayato, Vanni, Michael J., Özkundakci, Deniz, Echaniz, Santiago A., Vignatti, Alicia, Grosman, Fabián, Sanzano, Pablo, Van Dam, Bryce, and Knoll, Lesley B.

Published
2021
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13. First observations and early life-history aspects of lake rearing galaxiid larvae in the lower Waikato River Basin, New Zealand.

Author

David, Bruno O., Jarvis, Matt, Özkundakci, Deniz, Smith, Josh, Duggan, Ian C., Koh, Sung Soo, Augspurger, Jason, and King, Tania M.

Subjects
LARVAE, LAKE management, LAKES, GASTROINTESTINAL contents, FRESHWATER fishes, WATERSHEDS
Abstract

Larval behaviour for many of New Zealand's diadromous freshwater fish is inadequately described. Diadromy for many amphidromous species is not obligatory however, and where conditions are suitable, freshwater larval rearing may be facilitated. Where this occurs in lakes, opportunities to document the composition and conditions supporting larval rearing exist. Boat trawling was undertaken across nine lowland lakes in the Lower Waikato over four consecutive winters with a focus on larval galaxiids. Galaxiid larvae were captured in surface water habitats in all but one lake, with banded kōkopu (Galaxias fasciatus) and giant kōkopu (Galaxias argenteus) the most common species detected. One lake, Lake Waahi, consistently resulted in the most galaxiid captures for effort expended. Analyses of larvae from this and other lakes indicated that two sizes predominated in catches and that larger, older larvae were predominantly G. fasciatus while smaller, younger larvae were predominantly G. argenteus. Stomach contents indicated that two non-native zooplankton species predominated in the diet of larvae, the Holarctic daphnia, Daphnia galeata, and the Australian calanoid copepod Boeckella symmetrica. This study provides new information regarding the timing, movement and predicted recruitment of native fish species in this river basin that has important implications for lake and river management. [ABSTRACT FROM AUTHOR]

Published
2023
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14. Identifying control points of excessive nitrate load in a pastoral catchment to support lake management

Author

Özkundakci, Deniz, Baisden, W. Troy, Hartland, Adam, Özkundakci, Deniz, Baisden, W. Troy, and Hartland, Adam

Abstract

Excessive leaching of nitrogen (N) from pasture grazing catchments continues to challenge sustainable freshwater and lake management. However, managing contaminant export from diffuse agricultural sources is difficult due to the lack of detailed knowledge of specific sources and delivery mechanisms controlling contaminant transport over various spatial and temporal scales. This study systematically investigated nitrate dynamic flow from a small pastoral catchment into a eutrophic lake located in the central plateau of New Zealand’s North Island. This study aimed to determine where and when hot spots and hot moments can be characterised as control points for freshwater contaminant losses in the pastoral catchment. Multi-isotope analysis, high-frequency data collection, and modelling were utilised in identifying and describing potential nitrate sources and biogeochemical transformations involved that affect nitrate export from catchment to receiving waters. A distinct difference in the isotopic signature of nitrate taken during high flow compared to nitrate from low flow conditions highlights the importance of considering hydrological conditions when determining the source and dominant biogeochemical processes of N within the catchment. Nitrate in the stream was mainly derived from the mineralisation of soil organic N during low flow conditions; however, the contribution from urine and urea fertiliser sources was dominant during high flow conditions. Antecedent catchment wetness of ~95 mm was identified as a hydrological threshold influencing different sources and transport mechanisms of nutrients in the lake catchment. Above the threshold, rainfall events led to the mobilisation of nitrogen from the overland flow pathway. In contrast, events below the threshold led to pronounced organic N release from subsurface runoff. The catchment model Soil and Water Assessment Tool (SWAT) was used to simulate hydrological processes, simulate nutrient load, and investigate whethe

Published
2023

16. Applications for zoosporic parasites in aquatic systems (ParAqua)

Author

Rasconi, Serena, primary, Grossart, Hans-Peter, additional, Gsell, Alena, additional, Ibelings, Bastiaan Willem, additional, van de Waal, Dedmer, additional, Agha, Ramsy, additional, Bacu, Ariola, additional, Balode, Maija, additional, Beklioğlu, Meryem, additional, Berden Zrimec, Maja, additional, Botez, Florina, additional, Butler, Tom, additional, Cerbin, Slawomir, additional, Cortina, Angela, additional, Cunliffe, Michael, additional, Frenken, Thijs, additional, Garcés, Esther, additional, Gjyli, Laura, additional, Golan, Yonatan, additional, Guerra, Tiago, additional, Iacovides, Ayis, additional, Idà, Antonio, additional, Kagami, Maiko, additional, Kisand, Veljo, additional, Leshoski, Jovica, additional, Marco, Pini, additional, Mazalica, Natasa, additional, Miki, Takeshi, additional, Moza, Maria Iasmina, additional, Neuhauser, Sigrid, additional, Özkundakci, Deniz, additional, Panksep, Kristel, additional, Patcheva, Suzana, additional, Pestoric, Branka, additional, Petrova Stoyneva, Maya, additional, Pinto, Diogo, additional, Polle, Juergen, additional, Postolache, Carmen, additional, Pozo Dengra, Joaquín, additional, Reñé, Albert, additional, Rychtecky, Pavel, additional, Schmeller, Dirk S., additional, Scholz, Bettina, additional, Selmeczy, Géza, additional, Sime-Ngando, Télesphore, additional, Tapolczai, Kálmán, additional, Tasevska, Orhideja, additional, Trbojevic, Ivana, additional, Uzunov, Blagoy, additional, Van den Wyngaert, Silke, additional, van Donk, Ellen, additional, Vanthoor, Marieke, additional, Veljanoska Sarafiloska, Elizabeta, additional, Wood, Susie, additional, and Znachor, Petr, additional

Published
2022
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17. Exploring, exploiting and evolving diversity of aquatic ecosystem models: a community perspective

Author

Janssen, Annette B. G., Arhonditsis, George B., Beusen, Arthur, Bolding, Karsten, Bruce, Louise, Bruggeman, Jorn, Couture, Raoul-Marie, Downing, Andrea S., Alex Elliott, J., Frassl, Marieke A., Gal, Gideon, Gerla, Daan J., Hipsey, Matthew R., Hu, Fenjuan, Ives, Stephen C., Janse, Jan H., Jeppesen, Erik, Jöhnk, Klaus D., Kneis, David, Kong, Xiangzhen, Kuiper, Jan J., Lehmann, Moritz K., Lemmen, Carsten, Özkundakci, Deniz, Petzoldt, Thomas, Rinke, Karsten, Robson, Barbara J., Sachse, René, Schep, Sebastiaan A., Schmid, Martin, Scholten, Huub, Teurlincx, Sven, Trolle, Dennis, Troost, Tineke A., Van Dam, Anne A., Van Gerven, Luuk P. A., Weijerman, Mariska, Wells, Scott A., and Mooij, Wolf M.

Published
2015
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19. A framework for ensemble modelling of climate change impacts on lakes worldwide: the ISIMIP Lake Sector

Author

Golub, Malgorzata, primary, Thiery, Wim, additional, Marcé, Rafael, additional, Pierson, Don, additional, Vanderkelen, Inne, additional, Mercado-Bettin, Daniel, additional, Woolway, R. Iestyn, additional, Grant, Luke, additional, Jennings, Eleanor, additional, Kraemer, Benjamin M., additional, Schewe, Jacob, additional, Zhao, Fang, additional, Frieler, Katja, additional, Mengel, Matthias, additional, Bogomolov, Vasiliy Y., additional, Bouffard, Damien, additional, Côté, Marianne, additional, Couture, Raoul-Marie, additional, Debolskiy, Andrey V., additional, Droppers, Bram, additional, Gal, Gideon, additional, Guo, Mingyang, additional, Janssen, Annette B. G., additional, Kirillin, Georgiy, additional, Ladwig, Robert, additional, Magee, Madeline, additional, Moore, Tadhg, additional, Perroud, Marjorie, additional, Piccolroaz, Sebastiano, additional, Raaman Vinnaa, Love, additional, Schmid, Martin, additional, Shatwell, Tom, additional, Stepanenko, Victor M., additional, Tan, Zeli, additional, Woodward, Bronwyn, additional, Yao, Huaxia, additional, Adrian, Rita, additional, Allan, Mathew, additional, Anneville, Orlane, additional, Arvola, Lauri, additional, Atkins, Karen, additional, Boegman, Leon, additional, Carey, Cayelan, additional, Christianson, Kyle, additional, de Eyto, Elvira, additional, DeGasperi, Curtis, additional, Grechushnikova, Maria, additional, Hejzlar, Josef, additional, Joehnk, Klaus, additional, Jones, Ian D., additional, Laas, Alo, additional, Mackay, Eleanor B., additional, Mammarella, Ivan, additional, Markensten, Hampus, additional, McBride, Chris, additional, Özkundakci, Deniz, additional, Potes, Miguel, additional, Rinke, Karsten, additional, Robertson, Dale, additional, Rusak, James A., additional, Salgado, Rui, additional, van der Linden​​​​​​​, Leon, additional, Verburg, Piet, additional, Wain, Danielle, additional, Ward, Nicole K., additional, Wollrab, Sabine, additional, and Zdorovennova, Galina, additional

Published
2022
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20. A framework for ensemble modelling of climate change impacts on lakes worldwide: the ISIMIP Lake Sector

Author

Golub, Malgorzata, Thiery, Wim, Marcé, Rafael, Pierson, Don, Vanderkelen, Inne, Mercado-Bettin, Daniel, Woolway, R. Iestyn, Grant, Luke, Jennings, Eleanor, Kraemer, Benjamin M., Schewe, Jacob, Zhao, Fang, Frieler, Katja, Mengel, Matthias, Bogomolov, Vasiliy Y., Bouffard, Damien, Côté, Marianne, Couture, Raoul-Marie, Debolskiy, Andrey V., Droppers, Bram, Gal, Gideon, Guo, Mingyang, Janssen, Annette B.G., Kirillin, Georgiy, Ladwig, Robert, Magee, Madeline, Moore, Tadhg, Perroud, Marjorie, Piccolroaz, Sebastiano, Raaman Vinnaa, Love, Schmid, Martin, Shatwell, Tom, Stepanenko, Victor M., Tan, Zeli, Woodward, Bronwyn, Yao, Huaxia, Adrian, Rita, Allan, Mathew, Anneville, Orlane, Arvola, Lauri, Atkins, Karen, Boegman, Leon, Carey, Cayelan, Christianson, Kyle, de Eyto, Elvira, DeGasperi, Curtis, Grechushnikova, Maria, Hejzlar, Josef, Joehnk, Klaus, Jones, Ian D., Laas, Alo, Mackay, Eleanor B., Mammarella, Ivan, Markensten, Hampus, McBride, Chris, Özkundakci, Deniz, Potes, Miguel, Rinke, Karsten, Robertson, Dale, Rusak, James A., Salgado, Rui, van der Linden​​​​​​​, Leon, Verburg, Piet, Wain, Danielle, Ward, Nicole K., Wollrab, Sabine, Zdorovennova, Galina, Golub, Malgorzata, Thiery, Wim, Marcé, Rafael, Pierson, Don, Vanderkelen, Inne, Mercado-Bettin, Daniel, Woolway, R. Iestyn, Grant, Luke, Jennings, Eleanor, Kraemer, Benjamin M., Schewe, Jacob, Zhao, Fang, Frieler, Katja, Mengel, Matthias, Bogomolov, Vasiliy Y., Bouffard, Damien, Côté, Marianne, Couture, Raoul-Marie, Debolskiy, Andrey V., Droppers, Bram, Gal, Gideon, Guo, Mingyang, Janssen, Annette B.G., Kirillin, Georgiy, Ladwig, Robert, Magee, Madeline, Moore, Tadhg, Perroud, Marjorie, Piccolroaz, Sebastiano, Raaman Vinnaa, Love, Schmid, Martin, Shatwell, Tom, Stepanenko, Victor M., Tan, Zeli, Woodward, Bronwyn, Yao, Huaxia, Adrian, Rita, Allan, Mathew, Anneville, Orlane, Arvola, Lauri, Atkins, Karen, Boegman, Leon, Carey, Cayelan, Christianson, Kyle, de Eyto, Elvira, DeGasperi, Curtis, Grechushnikova, Maria, Hejzlar, Josef, Joehnk, Klaus, Jones, Ian D., Laas, Alo, Mackay, Eleanor B., Mammarella, Ivan, Markensten, Hampus, McBride, Chris, Özkundakci, Deniz, Potes, Miguel, Rinke, Karsten, Robertson, Dale, Rusak, James A., Salgado, Rui, van der Linden​​​​​​​, Leon, Verburg, Piet, Wain, Danielle, Ward, Nicole K., Wollrab, Sabine, and Zdorovennova, Galina

Abstract

Empirical evidence demonstrates that lakes and reservoirs are warming across the globe. Consequently, there is an increased need to project future changes in lake thermal structure and resulting changes in lake biogeochemistry in order to plan for the likely impacts. Previous studies of the impacts of climate change on lakes have often relied on a single model forced with limited scenario-driven projections of future climate for a relatively small number of lakes. As a result, our understanding of the effects of climate change on lakes is fragmentary, based on scattered studies using different data sources and modelling protocols, and mainly focused on individual lakes or lake regions. This has precluded identification of the main impacts of climate change on lakes at global and regional scales and has likely contributed to the lack of lake water quality considerations in policy-relevant documents, such as the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC). Here, we describe a simulation protocol developed by the Lake Sector of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) for simulating climate change impacts on lakes using an ensemble of lake models and climate change scenarios for ISIMIP phases 2 and 3. The protocol prescribes lake simulations driven by climate forcing from gridded observations and different Earth system models under various representative greenhouse gas concentration pathways (RCPs), all consistently bias-corrected on a 0.5∘ × 0.5∘ global grid. In ISIMIP phase 2, 11 lake models were forced with these data to project the thermal structure of 62 well-studied lakes where data were available for calibration under historical conditions, and using uncalibrated models for 17 500 lakes defined for all global grid cells containing lakes. In ISIMIP phase 3, this approach was expanded to consider more lakes, more models, and more processes. The ISIMIP Lake Sector is the largest international effort to project

Published
2022

21. Long-term trends and seasonal variation in host density, temperature, and nutrients differentially affect chytrid fungi parasitising lake phytoplankton

Author

Gsell, Alena S., Wolinska, Justyna, Preuß, Katrin, Teurlincx, Sven, Özkundakci, Deniz, Hilt, Sabine, van Donk, Ellen, Ibelings, Bas W., Adrian, Rita, Gsell, Alena S., Wolinska, Justyna, Preuß, Katrin, Teurlincx, Sven, Özkundakci, Deniz, Hilt, Sabine, van Donk, Ellen, Ibelings, Bas W., and Adrian, Rita

Abstract

Parasites are generally considered the most commonly occurring type of consumers, yet their biomass and population dynamics are rarely quantified at community level. Here, we used 12 years of weekly or fortnightly monitoring data (518 time points) to determine the occurrence of chytrids, fungal parasites of phytoplankton, to assess their seasonality and long-term (seasonally-detrended) dynamics in the pelagic plankton community of a temperate, eutrophic, and polymictic lake. Chytrid infections were observed in c. 75% of all samples with recurrent infections in multiple host taxa. Infection prevalence was highest in spring, but infections occurred throughout the entire year with an average of 2.3 host taxa infected per time point (ranging from 0 to 10 host taxa) and an average infection prevalence of 2.78% (ranging from 0% to 47.35%). Infected host biomass equalled that of the carnivorous zooplankton and decreased over time, while infection prevalence remained unchanged. Seasonal infection prevalence increased with phytoplankton biomass, but decreased with increasing temperature and phosphorus concentrations, reflecting that peak prevalence occurred in spring when temperature and phosphorus concentrations were relatively low. In contrast, seasonally-detrended prevalence increased with temperature, but decreased with increasing phosphorus concentrations. Chytrids are a common component of the pelagic plankton community with sizeable biomass and removing an—at times—substantial proportion of the primary production, challenging the long-standing underrepresentation of parasites in ecological studies. Chytrids responded differentially to seasonal variation and long-term trends in host density, water temperature and nutrient availability, highlighting the need to disentangle seasonal signals from long-term changes.

Published
2022

25. Plastic debris in freshwater systems worldwide

Author

Nava, Veronica, Aherne, Julian, Alfonso, María B., Geraldes, Ana Maria, Attermeyer, Katrin, Bao, Roberto, Bartrons, Mireia, Berger, Stella, Biernaczyk, Marcin, Bissen, Raphael, Brookes, Justin, Brown, David, Candian, Giulia, Cañedo-Argüelles, Miguel, Canle, Moisés, Capelli, Camilla, Cereijo, Jose Luís, Carballeira, Rafael, Chawchai, Sakonvan, Chen, Guangjie, Christensen, Søren T., Christoffersen, Kirsten Seestern, Eyto, Elvira de, Delgado, Jorge, Doubek, Jonathan, Dusaucy, Julia, Erina, Oxana, Ersoy, Zeynep, Feuchtmayr, Heidrun, Lepori, Fabio, Frezzotti, Maria Luce, Galafassi, Silvia, Gateuille, David, Gonçalves, Vítor, Grossart, Hans-Peter, Hamilton, David, Kangur, Külli, Kankılıç, Gökben Başaran, Kessler, Rebecca, Kiel, Christine, Krynak, Edward M., Leiva-Presa, Àngels, Matias, Miguel, Matsuzaki, Shin-Ichiro, McElarney, Yvonne, Mitchell, Mark, Messyasz, Beata, Mlambo, Musa, Motitsoe, Samuel N., Owens, Caroline, Özkundakci, Deniz, Pinnow, Solvig, Pociecha, Agnieszka, Raposeiro, Pedro M., Rõõm, Eva-Ingrid, Rotta, Federica, Salmaso, Nico, Scordo, Facundo, Sibomana, Claver, Siewert, Daniel, Stepanowska, Katarzyna, Sudeep, Chandra, Tavşanoğlu, Ülkü Nihan, Tereshina, Maria, Thompson, James, Tolotti, Monica, Valois, Amanda, Verburg, Piet, Wesolek, Brian, Weyhenmeyer, Gesa, Wu, Naicheng, Zawisza, Edyta, Zink, Lauren, and Leoni, Barbara

Subjects
Research Subject Categories::TECHNOLOGY, Plastic debris
Abstract

Plastic debris is widespread in freshwater ecosystems, but a rigorous assessment of its global distribution has been hindered by a lack of comprehensive and comparable data. We performed the first standardized global survey of lakes to assess the quantity and type of plastics (>250μm). We included 38 lakes located in 23 different countries distributed across five continents, spanning different environmental gradients and varying levels of anthropogenic stress. All samples were collected by horizontal trawling of a plankton net and subsequently treated with hydrogen peroxide. We identified 9425 plastic particles, which were classified based on shape, color, and size. Polymer identification was carried out using Raman micro-spectroscopy. Our results showed that the concentration of plastics spanned four orders of magnitude (10-3-101 particles/m3). Fibers (49%) and fragments (41%) were the most frequently detected particles, suggesting a secondary origin of plastic contamination. The most commonly identified polymers were polyester (30%), polypropylene (20%), and polyethylene (16%), which are widely used in short life-cycle products and account for the majority of global plastic production. Further, we found that urban-related attributes of lakes/watersheds influenced the occurrence and type of plastics in lentic systems and larger and deeper lakes with higher retention times are accumulating plastic debris at higher concentrations. info:eu-repo/semantics/publishedVersion

Published
2022

27. Supplementary material to "A framework for ensemble modelling of climate change impacts on lakes worldwide: the ISIMIP Lake Sector"

Author

Golub, Malgorzata, primary, Thiery, Wim, additional, Marcé, Rafael, additional, Pierson, Don, additional, Vanderkelen, Inne, additional, Mercado, Daniel, additional, Woolway, R. Iestyn, additional, Grant, Luke, additional, Jennings, Eleanor, additional, Schewe, Jacob, additional, Zhao, Fang, additional, Frieler, Katja, additional, Mengel, Matthias, additional, Bogomolov, Vasiliy Y., additional, Bouffard, Damien, additional, Couture, Raoul-Marie, additional, Debolskiy, Andrey V., additional, Droppers, Bram, additional, Gal, Gideon, additional, Guo, Mingyang, additional, Janssen, Annette B. G., additional, Kirillin, Georgiy, additional, Ladwig, Robert, additional, Magee, Madeline, additional, Moore, Tadhg, additional, Perroud, Marjorie, additional, Piccolroaz, Sebastiano, additional, Raaman Vinnaa, Love, additional, Schmid, Martin, additional, Shatwell, Tom, additional, Stepanenko, Victor M., additional, Tan, Zeli, additional, Yao, Huaxia, additional, Adrian, Rita, additional, Allan, Mathew, additional, Anneville, Orlane, additional, Arvola, Lauri, additional, Atkins, Karen, additional, Boegman, Leon, additional, Carey, Cayelan, additional, Christianson, Kyle, additional, de Eyto, Elvira, additional, DeGasperi, Curtis, additional, Grechushnikova, Maria, additional, Hejzlar, Josef, additional, Joehnk, Klaus, additional, Jones, Ian D., additional, Laas, Alo, additional, Mackay, Eleanor B., additional, Mammarella, Ivan, additional, Markensten, Hampus, additional, McBride, Chris, additional, Özkundakci, Deniz, additional, Potes, Miguel, additional, Rinke, Karsten, additional, Robertson, Dale, additional, Rusak, James, additional, Salgado, Rui, additional, van den Linden, Leon, additional, Verburg, Piet, additional, Wain, Danielle, additional, Ward, Nicole K., additional, Wollrab, Sabine, additional, and Zdorovennova, Galina, additional

Published
2022
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34. Restoring shallow lakes impaired by eutrophication: Approaches, outcomes, and challenges.

Author

Abell, Jonathan M., Özkundakci, Deniz, Hamilton, David P., and Reeves, Paula

Subjects
*LAKE restoration, *EUTROPHICATION, *LAKES, *BIOMANIPULATION, *CLIMATE change, *WATER quality, *HYSTERESIS
Abstract

Shallow lake ecosystems are widely impaired by eutrophication. Lake restoration projects frequently fail or are only partially successful, reflecting that environmental managers face difficult challenges in addressing this complex problem. Key uncertainties relate to selecting appropriate methods and predicting the resulting response trajectory, that is, "what should be done, how much improvement should be expected, and how long will it take?" This review critically evaluates approaches applied to address eutrophication in shallow lakes. A set of shallow lake restoration case studies from across the globe, involving moderate to high effort monitoring, was evaluated to determine common features and to identify advantages/disadvantages and drivers of successful restoration projects. Approaches are broadly grouped into four categories: 1) external nutrient load reductions, 2) internal nutrient load reductions, 3) biomanipulation, and 4) hydrological manipulations. Case studies highlight that external load reduction is an essential component of successful restoration, although supplementary measures can support restoration goals. To inform planning and help set realistic expectations, the following key challenges to the restoration of shallow lakes were identified: 1) insufficient reductions in external nutrient loads, 2) biogeochemical lags, 3) resistance of a stable, algal-dominated state due to hysteresis in the turbidity–nutrient load relationship, 4) delayed macrophyte reestablishment, 5) climate change, 6) need for lake-specific approaches, and 7) social and political shortcomings. Managing these challenges is crucial to the success of shallow lake restoration projects. [ABSTRACT FROM AUTHOR]

Published
2022
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38. QUANTIFYING INTERACTION NETWORKS AND STABILITY PROPERTIES OF PLANKTON FOOD WEBS USING MULTIVARIATE FIRST ORDER AUTOREGRESSIVE MODELLING

Author

Gsell, A.S., Özkundakci, Deniz, Hébert, Marie-Pier, Adrian, Rita, Sychev, Viktor, Mueller, Lothar, and Aquatic Ecology (AqE)

Subjects
long-term research, сети взаимодействия, international, interaction networks, network centrality, долгосрочные исследования, сетевая центральность, sense organs, community stability, skin and connective tissue diseases, стабильность сообщества
Abstract

Lakes and reservoirs have been identified as sentinels of global change as they integrate changes in the surrounding landscape. While univariate indicator variables are relatively well assessed, the lack of knowledge on temporal changes in species interactions under pressure has been identified as a major gap in the bio-monitoring sciences. Multivariate autoregressive models can be used to assess direction and strength of both direct and indirect interactions in complex communities over time. This model framework also allows calculation of network stability properties (variance, resilience and reactivity). Moreover, the interaction matrix can be further analyzed for classical network structure properties (closeness- and betweenness centrality). These measures are useful indicators of changes in ecosystem stability and help identify biotic keystone groups and/or groups of species that are particularly vulnerable to changes in the landscape., Озера и водохранилища являются стражами глобальных изменений, поскольку они интегрируют в себе изменения в окружающем ландшафте. В то время как одномерные индикаторные переменные относительно хорошо изучены, недостаток знаний об изменениях в видовом взаимодействии под антропогенным давлением является большим пробелом в науках о биологическом мониторинге. Многомерные авторегрессионные модели могут быть использованы для оценки динамики направления и силы как прямых, так и косвенных взаимодействий в сложных сообществах. Эта модельная структура также позволяет рассчитывать свойства устойчивости сети (дисперсия, устойчивость и реактивность). Более того, матрица взаимодействия может быть дополнительно проанализирована для свойств классической структуры сети (центральность по близости и посредничеству). Эти меры являются важными индикаторами изменений в стабильности экосистем и помогают определить биотические ключевые группы и/или группы видов, которые особенно уязвимы к изменениям ландшафта.

Published
2018
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39. Environmental Modelling & Software

Author

Bruce, Louise C., Frassl, Marieke A., Arhonditsis, George B., Gal, Gideon, Hamilton, David P., Hanson, Paul C., Hetherington, Amy L., Melack, John M., Read, Jordan S., Rinke, Karsten, Rigosi, Anna, Trolle, Dennis, Winslow, Luke, Adrian, Rita, Ayala, Ana I., Bocaniov, Serghei A., Boehrer, Bertram, Boon, Casper, Brookes, Justin D., Bueche, Thomas, Busch, Brendan D., Copetti, Diego, Cortés, Alicia, de Eyto, Elvira, Elliott, J. Alex, Gallina, Nicole, Gilboa, Yael, Guyennon, Nicolas, Huang, Lei, Kerimoglu, Onur, Lenters, John D., MacIntyre, Sally, Makler-Pick, Vardit, McBride, Chris G., Moreira, Santiago, Özkundakci, Deniz, Pilotti, Marco, Rueda, Francisco J., Rusak, James A., Samal, Nihar R., Schmid, Martin, Shatwell, Tom, Snorthheim, Craig, Soulignac, Frédéric, Valerio, Giulia, van der Linden, Leon, Vetter, Mark, Vinçon-Leite, Brigitte, Wang, Junbo, Weber, Michael, Wickramaratne, Chaturangi, Woolway, R. Iestyn, Yao, Huaxia, Hipsey, Matthew R., Bren School of Environmental Science and Management, University of California [Santa Barbara] (UCSB), University of California-University of California, Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), CNR Water Research Institute (IRSA), Consiglio Nazionale delle Ricerche (CNR), Histoire culturelle et sociale de l'art (HiCSA), Université Paris 1 Panthéon-Sorbonne (UP1), Centre Alpin de Recherche sur les Réseaux Trophiques et Ecosystèmes Limniques (CARRTEL), Institut National de la Recherche Agronomique (INRA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), MRC/CSO Social and Public Health Sciences Unit, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Biosystems Division [Roskilde], Risø National Laboratory for Sustainable Energy (Risø DTU), Technical University of Denmark [Lyngby] (DTU)-Technical University of Denmark [Lyngby] (DTU), Institut de Génétique Moléculaire de Montpellier (IGMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Australian Research Council (ARC) DP130104078 LP130100756, Biological Sciences, Helmholtz Centre for Environmental Research (UFZ), Université Panthéon-Sorbonne (UP1), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut National de la Recherche Agronomique (INRA), Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Centre National de la Recherche Scientifique (CNRS), University of California [Santa Barbara] (UC Santa Barbara), University of California (UC)-University of California (UC), National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Danmarks Tekniske Universitet = Technical University of Denmark (DTU)-Danmarks Tekniske Universitet = Technical University of Denmark (DTU), and Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
0106 biological sciences, Environmental Engineering, 010504 meteorology & atmospheric sciences, Network science, lake model, global observatory data, Stratification (water), Climate change, Model assessment, BAYESIAN HIERARCHICAL FRAMEWORK, 01 natural sciences, Latitude, stratification, Observatory, network science, AQUATIC BIOGEOCHEMICAL MODELS, Low correlation, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, Trophic level, CLIMATE-CHANGE, REGIME SHIFTS, 010604 marine biology & hydrobiology, Ecological Modeling, SUB-ALPINE LAKE, model assessment, TEMPERATE LAKES, THERMAL STRUCTURE, ECOLOGICAL STATE, 13. Climate action, DYRESM-CAEDYM, Global observatory data, Climatology, [SDE]Environmental Sciences, CENTRAL-EUROPEAN LAKE, GLM, Lake model, Stratification, Software, 500 Naturwissenschaften und Mathematik::570 Biowissenschaften, Biologie::577 Ökologie, Thermocline
Abstract

The modelling community has identified challenges for the integration and assessment of lake models due to the diversity of modelling approaches and lakes. In this study, we develop and assess a one-dimensional lake model and apply it to 32 lakes from a global observatory network. The data set included lakes over broad ranges in latitude, climatic zones, size, residence time, mixing regime and trophic level. Model performance was evaluated using several error assessment metrics, and a sensitivity analysis was conducted for nine parameters that governed the surface heat exchange and mixing efficiency. There was low correlation between input data uncertainty and model performance and predictions of temperature were less sensitive to model parameters than prediction of thermocline depth and Schmidt stability. The study provides guidance to where the general model approach and associated assumptions work, and cases where adjustments to model parameterisations and/or structure are required. (c) 2017 Published by Elsevier Ltd. Australian Research Council (ARC)Australian Research Council [DP130104078, LP130100756] GLM development and funding support for LCB, BDB, CB and MRH was provided by the Australian Research Council (ARC) (grants DP130104078 & LP130100756). Additional contributions from individuals and organisations as well as sources of data, provided from a variety of organisations are summarised in Appendix D. This study was made possible through the sharing of ideas, data and models across the AEMON and GLEON networks as well as discussions and working groups held during AEMON workshops and GLEON meetings. Public domain – authored by a U.S. government employee

Published
2018
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45. A multi-lake comparative analysis of the General Lake Model (GLM) : Stress-testing across a global observatory network

Author

Bruce, Louise C, Frassl, Marieke A, Arhonditsis, George B, Gal, Gideon, Hamilton, David P, Hanson, Paul C, Hetherington, Amy L, Melack, John M, Read, Jordan S, Rinke, Karsten, Rigosi, Anna, Trolle, Dennis, Winslow, Luke, Adrian, Rita, Ayala, Ana I, Bocaniov, Serghei A, Boehrer, Bertram, Boon, Casper, Brookes, Justin D, Bueche, Thomas, Busch, Brendan D, Copetti, Diego, Cortés, Alicia, de Eyto, Elvira, Elliott, J Alex, Gallina, Nicole, Gilboa, Yael, Guyennon, Nicolas, Huang, Lei, Kerimoglu, Onur, Lenters, John D, MacIntyre, Sally, Makler-Pick, Vardit, McBride, Chris G, Moreira, Santiago, Özkundakci, Deniz, Pilotti, Marco, Rueda, Francisco J, Rusak, James A, Samal, Nihar R, Schmid, Martin, Shatwell, Tom, Snorthheim, Craig, Soulignac, Frédéric, Valerio, Giulia, van der Linden, Leon, Vetter, Mark, Vinçon-Leite, Brigitte, Wang, Junbo, Weber, Michael, Wickramaratne, Chaturangi, Woolway, R Iestyn, Yao, Huaxia, Hipsey, Matthew R, Bruce, Louise C, Frassl, Marieke A, Arhonditsis, George B, Gal, Gideon, Hamilton, David P, Hanson, Paul C, Hetherington, Amy L, Melack, John M, Read, Jordan S, Rinke, Karsten, Rigosi, Anna, Trolle, Dennis, Winslow, Luke, Adrian, Rita, Ayala, Ana I, Bocaniov, Serghei A, Boehrer, Bertram, Boon, Casper, Brookes, Justin D, Bueche, Thomas, Busch, Brendan D, Copetti, Diego, Cortés, Alicia, de Eyto, Elvira, Elliott, J Alex, Gallina, Nicole, Gilboa, Yael, Guyennon, Nicolas, Huang, Lei, Kerimoglu, Onur, Lenters, John D, MacIntyre, Sally, Makler-Pick, Vardit, McBride, Chris G, Moreira, Santiago, Özkundakci, Deniz, Pilotti, Marco, Rueda, Francisco J, Rusak, James A, Samal, Nihar R, Schmid, Martin, Shatwell, Tom, Snorthheim, Craig, Soulignac, Frédéric, Valerio, Giulia, van der Linden, Leon, Vetter, Mark, Vinçon-Leite, Brigitte, Wang, Junbo, Weber, Michael, Wickramaratne, Chaturangi, Woolway, R Iestyn, Yao, Huaxia, and Hipsey, Matthew R

Abstract

The modelling community has identified challenges for the integration and assessment of lake models due to the diversity of modelling approaches and lakes. In this study, we develop and assess a one-dimensional lake model and apply it to 32 lakes from a global observatory network. The data set included lakes over broad ranges in latitude, climatic zones, size, residence time, mixing regime and trophic level. Model performance was evaluated using several error assessment metrics, and a sensitivity analysis was conducted for nine parameters that governed the surface heat exchange and mixing efficiency. There was low correlation between input data uncertainty and model performance and predictions of temperature were less sensitive to model parameters than prediction of thermocline depth and Schmidt stability. The study provides guidance to where the general model approach and associated assumptions work, and cases where adjustments to model parameterisations and/or structure are required.

Published
2018
Full Text
View/download PDF

46. A multi-lake comparative analysis of the General Lake Model (GLM): stress-testing across a global observatory network

Author

Bruce, Louise C., Frassl, Marieke A., Arhonditsis, George B., Gal, Gideon, Hamilton, David P., Hanson, Paul C., Hetherington, Amy L., Melack, John M., Read, Jordan S., Rinke, Karsten, Rigosi, Anna, Trolle, Dennis, Winslow, Luke, Adrian, Rita, Ayala, Ana I., Bocaniov, Serghei A., Boehrer, Bertram, Boon, Casper, Brookes, Justin D., Bueche, Thomas, Busch, Brendan D., Copetti, Diego, Cortés, Alicia, de Eyto, Elvira, Elliott, J. Alex, Gallina, Nicole, Gilboa, Yael, Guyennon, Nicolas, Huang, Lei, Kerimoglu, Onur, Lenters, John D., MacIntyre, Sally, Makler-Pick, Vardit, McBride, Chris G., Moreira, Santiago, Özkundakci, Deniz, Pilotti, Marco, Rueda, Francisco J., Rusak, James A., Samal, Nihar R., Schmid, Martin, Shatwell, Tom, Snorthheim, Craig, Soulignac, Frédéric, Valerio, Giulia, van der Linden, Leon, Vetter, Mark, Vinçon-Leite, Brigitte, Wang, Junbo, Weber, Michael, Wickramaratne, Chaturangi, Woolway, R. Iestyn, Yao, Huaxia, Hipsey, Matthew R., Bruce, Louise C., Frassl, Marieke A., Arhonditsis, George B., Gal, Gideon, Hamilton, David P., Hanson, Paul C., Hetherington, Amy L., Melack, John M., Read, Jordan S., Rinke, Karsten, Rigosi, Anna, Trolle, Dennis, Winslow, Luke, Adrian, Rita, Ayala, Ana I., Bocaniov, Serghei A., Boehrer, Bertram, Boon, Casper, Brookes, Justin D., Bueche, Thomas, Busch, Brendan D., Copetti, Diego, Cortés, Alicia, de Eyto, Elvira, Elliott, J. Alex, Gallina, Nicole, Gilboa, Yael, Guyennon, Nicolas, Huang, Lei, Kerimoglu, Onur, Lenters, John D., MacIntyre, Sally, Makler-Pick, Vardit, McBride, Chris G., Moreira, Santiago, Özkundakci, Deniz, Pilotti, Marco, Rueda, Francisco J., Rusak, James A., Samal, Nihar R., Schmid, Martin, Shatwell, Tom, Snorthheim, Craig, Soulignac, Frédéric, Valerio, Giulia, van der Linden, Leon, Vetter, Mark, Vinçon-Leite, Brigitte, Wang, Junbo, Weber, Michael, Wickramaratne, Chaturangi, Woolway, R. Iestyn, Yao, Huaxia, and Hipsey, Matthew R.

Abstract

The modelling community has identified challenges for the integration and assessment of lake models due to the diversity of modelling approaches and lakes. In this study, we develop and assess a one-dimensional lake model and apply it to 32 lakes from a global observatory network. The data set included lakes over broad ranges in latitude, climatic zones, size, residence time, mixing regime and trophic level. Model performance was evaluated using several error assessment metrics, and a sensitivity analysis was conducted for nine parameters that governed the surface heat exchange and mixing efficiency. There was low correlation between input data uncertainty and model performance and predictions of temperature were less sensitive to model parameters than prediction of thermocline depth and Schmidt stability. The study provides guidance to where the general model approach and associated assumptions work, and cases where adjustments to model parameterisations and/or structure are required.

Published
2018

47. Patterns and drivers of spatio-temporal variability of suspended sediment in the Waikato lakes, New Zealand.

Author

Özkundakci, Deniz and Allan, Mathew Grant

Subjects
*SUSPENDED sediments, *LAKE sediments, *ECOSYSTEMS, *REMOTE sensing
Abstract

Quantifying and interpreting variability in ecological systems allows us to better understand the driving forces that determine ecosystems functioning. We utilised earth observation-based remote sensing to determine total suspended sediment (TSS) concentrations for 109 lakes over 16 years. The coefficient of variation (CV) was used to quantify variability of TSS at three temporal scales (monthly, annual and long-term) and at the horizontal spatial scale. CV values varied between 0.14 and 1.09. Drivers of observed variability patterns were explored using five lake morphological and catchment characteristics. Lake area was the most important variable to predict variability of TSS. De-vegetated lakes displayed significantly higher TSS concentrations than vegetated lakes; however, aquatic vegetation was found to moderate only spatial variability of TSS. As spatio-temporal variability can be assumed to drive key ecosystem functions, determining characteristic variability patterns for various attributes should be a prerequisite when setting management goals and developing monitoring regimes. [ABSTRACT FROM AUTHOR]

Published
2019
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48. Characteristics of consumer trophic resources for Waikato shallow lake food webs.

Author

Collier, Kevin J., Garrett-Walker, Jeremy, Özkundakci, Deniz, and Pingram, Michael A.

Subjects
LITTORAL zone, LAKES, PARTICULATE matter, FOOD quality, FOOD chains, SESTON, SUBGLACIAL lakes, LAKE management
Abstract

We characterised the quantity (mass per unit area or volume), quality (cabon:nitrogen ratio) and enrichment (δ15N) of basal food resources and benthic macroinvertebrates in six shallow lakes in the Waikato region, New Zealand, to elucidate patterns related to lake type (peat, riverine), habitat (littoral, mid-lake) and enrichment status (Trophic Level Index >6 or ≤5). Total seston dry mass was dominated by fine material that was correlated with chlorophyll a concentration. Seston was a higher quality food resource than benthic particulate organic matter which had higher biomass overall in littoral than in mid-lake habitats. Biomass of Chironomidae was highest in the less-enriched peat lakes, possibly due to clearer water supporting benthic algae in shallow littoral areas. Our results highlight the potential role of multiple bottom-up influences on shallow lake food webs. The more abundant and higher quality pelagic food resources in highly enriched lakes may have implications for resilience to non-indigenous fish invasion. [ABSTRACT FROM AUTHOR]

Published
2019
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