To, Sze-Wing ORCID: https://orcid.org/0000-0003-3410-3385, Chakraborty, Subhendu ORCID: https://orcid.org/0000-0002-2904-9313, Acevedo‐Trejos, Esteban ORCID: https://orcid.org/0000-0003-4222-7062, Pomati, Francesco and Merico, Agostino ORCID: https://orcid.org/0000-0001-8095-8056 (2026) Future warming reshapes inorganic nutrient and plankton dynamics in a temperate lake. Limnology and Oceanography, 71 (7). e70447. DOI https://doi.org/10.1002/lno.70447.

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Abstract

Lakes are experiencing high temperatures and frequent phytoplankton blooms. These events threaten the health of lake ecosystems. Phytoplankton respond to lake warming in various ways, making it challenging to predict changes in community composition. Although understanding the effects of lake warming on phytoplankton communities is crucial for lake management, these effects are not clear and have been a matter of debate due to contrasting observations. Here we use a data-informed, trait-based model to disentangle and project, based on future warming scenarios, the effects of temperature on the dynamics of inorganic nutrient (phosphate) and plankton at Greifensee, a medium-size eutrophic lake near Zurich, Switzerland. Assuming identical thermal characteristics among phytoplankton size classes, we find that phosphate concentrations and phytoplankton mean cell size increase with rising lake temperature. This is driven by the interplay between reduced growth and nutrient uptake by all phytoplankton under sub-optimal temperatures, resulting in higher summer nutrients and intensified zooplankton grazing on smaller phytoplankton cells. The small phytoplankton cells typically occurring during winter and spring are replaced by large phytoplankton cells. In addition, peaks of phytoplankton biomass, typically occurring in early summer, emerge earlier, in early spring. The earlier occurrence of these peaks is caused by a shift in the optimal temperature for phytoplankton growth. Although our results are based on various modeling approximations, they highlight the importance of combining observations and trait-based modeling for gaining insights into the future compositions of lake phytoplankton and establish a foundation for examining lake ecosystems in a warming world.

Document Type:	Article
Programme Area:	PA2
Research affiliation:	Systems Ecology
Refereed:	Yes
Document Access:	Open access
DOI:	https://doi.org/10.1002/lno.70447
ISSN:	0024-3590
Date Deposited:	17 Aug 2026 09:30
Last Modified:	17 Aug 2026 09:30
URI:	https://cris.leibniz-zmt.de/id/eprint/6255

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