Selected publications

Scientific highlights of IGB
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31 - 40 of 624 items
March 2025
Molecular Ecology Resources. - XX(202X)X, Art. e14099

ParAquaSeq, a Database of Ecologically Annotated rRNA Sequences Covering Zoosporic Parasites Infecting Aquatic Primary Producers in Natural and Industrial Systems

Silke Van den Wyngaert ; Slawek Cerbin ; Laura Garzoli ; Hans-Peter Grossart ; Alena S. Gsell ; Alexandra Kraberg ; Cécile Lepère ; Sigrid Neuhauser ; Miloš Stupar ; Andrea Tarallo ; Michael Cunliffe ; Claire Gachon ; Ana Gavrilović ; Hossein Masigol ; Serena Rasconi ; Géza B. Selmeczy ; Dirk S. Schmeller ; Bettina Scholz ; Natàlia Timoneda ; Ivana Trbojević ; Elżbieta Wilk-Woźniak ; Albert Reñé
March 2025
WIREs Water. - 12(2025)2, Art. e70015

Recent Developments and Emerging Challenges in Tracer-Aided Modeling

Hyekyeng Jung; Dörthe Tetzlaff; Christian Birkel; Chris Soulsby

The authors reviewed recent advances and remaining challenges of tracer-aided modelling which offers insights into internal storages, water sources, flow pathways, mixing processes, and water ages, which cannot be derived from hydrometric data alone. Tracer data have the capability to falsify hydrological models and test hypotheses, and thus increase understanding of hydrological processes.

March 2025
Ecological Indicators. - 172(2025), Art. 113331

Diversification of macrophytes within aquatic nature-based solutions (NBS) developing under urban environmental conditions across European cities

Krzysztof Szoszkiewicz; Krzysztof Achtenberg; Robrecht Debbaut; Vladimíra Dekan Carreira; Daniel Gebler; Szymon Jusik; Tomasz Kałuża; Krister Karttunen; Niko Lehti; Silvia Martin Muñoz; Mariusz Sojka; Ana Júlia Pereira; Pedro Pinho; Jonas Schoelynck; Jan Staes; Doerthe Tetzlaff; Maria Magdalena Warter; Kati Vierikko
March 2025
Water Resources Research. - 61(2025)3, Art. e2024WR038779

DREAM(LoAX): Simultaneous Calibration and Diagnosis for Tracer-Aided Ecohydrological Models Under the Equifinality Thesis

Songjun Wu; Doerthe Tetzlaff; Keith Beven; Chris Soulsby

The authors developed a new algorithm DREAM(LoAX) as an effective conditioning tool to consider epistemic uncertainty in process-based models. It provides real-time diagnostic information of model failures for identification of uncertainty in data or flaws in model structure, and hence is a learning tool for limitations in current monitoring networks and development of future models.