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 - TY - JOUR A1 - Beisner, Beatrix E. A1 - Grossart, Hans-Peter A1 - Gasol, Josep M. T1 - A guide to methods for estimating phago-mixotrophy in nanophytoplankton JF - Journal of plankton research N2 - Growing attention to phytoplankton mixotrophy as a trophic strategy has led to significant revisions of traditional pelagic food web models and ecosystem functioning. Although some empirical estimates of mixotrophy do exist, a much broader set of in situ measurements are required to (i) identify which organisms are acting as mixotrophs in real time and to (ii) assess the contribution of their heterotrophy to biogeochemical cycling. Estimates are needed through time and across space to evaluate which environmental conditions or habitats favour mixotrophy: conditions still largely unknown. We review methodologies currently available to plankton ecologists to undertake estimates of plankton mixotrophy, in particular nanophytoplankton phago-mixotrophy. Methods are based largely on fluorescent or isotopic tracers, but also take advantage of genomics to identify phylotypes and function. We also suggest novel methods on the cusp of use for phago-mixotrophy assessment, including single-cell measurements improving our capacity to estimate mixotrophic activity and rates in wild plankton communities down to the single-cell level. Future methods will benefit from advances in nanotechnology, micromanipulation and microscopy combined with stable isotope and genomic methodologies. Improved estimates of mixotrophy will enable more reliable models to predict changes in food web structure and biogeochemical flows in a rapidly changing world. KW - flow cytometry KW - phagotrophy KW - phytoplankton KW - methods KW - fluorescence KW - microscopy KW - FISH KW - isotopic methods KW - phylotypes KW - carbon flows KW - gene sequencing Y1 - 2019 U6 - https://doi.org/10.1093/plankt/fbz008 SN - 0142-7873 SN - 1464-3774 VL - 41 IS - 2 SP - 77 EP - 89 PB - Oxford Univ. Press CY - Oxford ER -