TY - JOUR A1 - Ehrlich, Elias A1 - Thygesen, Uffe Høgsbro A1 - Kiørboe, Thomas T1 - Evolution of toxins as a public good in phytoplankton JF - Proceedings of the Royal Society of London : B, Biological sciences N2 - Toxic phytoplankton blooms have increased in many waterbodies worldwide with well-known negative impacts on human health, fisheries and ecosystems. However, why and how phytoplankton evolved toxin production is still a puzzling question, given that the producer that pays the costs often shares the benefit with other competing algae and thus provides toxins as a 'public good' (e.g. damaging a common competitor or predator). Furthermore, blooming phytoplankton species often show a high intraspecific variation in toxicity and we lack an understanding of what drives the dynamics of coexisting toxic and non-toxic genotypes. Here, by using an individual-based two-dimensional model, we show that small-scale patchiness of phytoplankton strains caused by demography can explain toxin evolution in phytoplankton with low motility and the maintenance of genetic diversity within their blooms. This patchiness vanishes for phytoplankton with high diffusive motility, suggesting different evolutionary pathways for different phytoplankton groups. In conclusion, our study reveals that small-scale spatial heterogeneity, generated by cell division and counteracted by diffusive cell motility and turbulence, can crucially affect toxin evolution and eco-evolutionary dynamics in toxic phytoplankton species. This contributes to a better understanding of conditions favouring toxin production and the evolution of public goods in asexually reproducing organisms in general. KW - toxic algal blooms KW - evolution of cooperation KW - coexistence KW - patchiness in KW - phytoplankton KW - eco-evolutionary feedback KW - spatial pattern formation Y1 - 2022 U6 - https://doi.org/10.1098/rspb.2022.0393 SN - 0962-8452 SN - 1471-2954 VL - 289 IS - 1977 PB - Royal Society CY - London ER - TY - JOUR A1 - Wilhelms, Andre A1 - Börsig, Nicolas A1 - Yang, Jingwei A1 - Holbach, Andreas A1 - Norra, Stefan T1 - Insights into phytoplankton dynamics and water quality monitoring with the BIOFISH at the Elbe River, Germany JF - Water N2 - Understanding the key factors influencing the water quality of large river systems forms an important basis for the assessment and protection of cross-regional ecosystems and the implementation of adapted water management concepts. However, identifying these factors requires in-depth comprehension of the unique environmental systems, which can only be achieved by detailed water quality monitoring. Within the scope of the joint science and sports event "Elbschwimmstaffel" (swimming relay on the river Elbe) in June/July 2017 organized by the German Ministry of Education and Research, water quality data were acquired along a 550 km long stretch of the Elbe River in Germany. During the survey, eight physiochemical water quality parameters were recorded in high spatial and temporal resolution with the BIOFISH multisensor system. Multivariate statistical methods were applied to identify and delineate processes influencing the water quality. The BIOFISH dataset revealed that phytoplankton activity has a major impact on the water quality of the Elbe River in the summer months. The results suggest that phytoplankton biomass constitutes a substantial proportion of the suspended particles and that photosynthetic activity of phytoplankton is closely related to significant temporal changes in pH and oxygen saturation. An evaluation of the BIOFISH data based on the combination of statistical analysis with weather and discharge data shows that the hydrological and meteorological history of the sampled water body was the main driver of phytoplankton dynamics. This study demonstrates the capacity of longitudinal river surveys with the BIOFISH or similar systems for water quality assessment, the identification of pollution sources and their utilization for online in situ monitoring of rivers. KW - water quality KW - phytoplankton KW - river dynamics KW - multisensor system KW - online KW - monitoring KW - high spatial resolution KW - multivariate statistics Y1 - 2022 U6 - https://doi.org/10.3390/w14132078 SN - 2073-4441 VL - 14 IS - 13 PB - MDPI CY - Basel ER -