Massing, J. C. | bioRxiv Science

bioRxiv2022

"Wissenschaft fürs Wohnzimmer" - two years of interactive, scientific livestreams weekly on YouTube

Science communication is becoming increasingly important to connect academia and society, and to counteract fake news among climate change deniers. Online video platforms, such as YouTube, offer great potential for low-threshold communication of scientific knowledge to the general public. In April 2020 a diverse group of researchers from the Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research launched the YouTube channel "Wissenschaft furs Wohnzimmer" (translated to "Sitting Room Science") to stream scientific talks about climate change and biodiversity every Thursday evening. Here we report on the numbers and diversity of content, viewers, and presenters from 2 years and 100 episodes of weekly livestreams. Presented topics encompass all areas of polar research, social issues related to climate change, and new technologies to deal with the changing world and climate ahead. We show that constant engagement by a group of co-hosts, and presenters from all topics, career stages, and genders enable a continuous growth of views and subscriptions, i.e. impact. After 783 days the channel gained 30,251 views and 828 subscribers and hosted well-known scientists while enabling especially early career researchers to improve their outreach and media skills. We show that interactive and science-related videos, both live and on-demand, within a pleasant atmosphere, can be produced voluntarily while maintaining high quality. We further discuss challenges and possible improvements for the future. Our experiences may help other researchers to conduct meaningful scientific outreach and to push borders of existing formats with the overall aim of developing a better understanding of climate change and our planet.

scientific communication and education↗

bioRxiv2022

Quantification of metabolic niche occupancy dynamics in a Baltic Sea bacterial community

Progress in molecular methods has enabled the monitoring of bacterial populations in time. Nevertheless, understanding community dynamics and its links with ecosystem functioning remains challenging due to the tremendous diversity of microorganisms. Conceptual frameworks that make sense of time-series of taxonomically-rich bacterial communities, regarding their potential ecological function, are needed. A key concept for organizing ecological functions is the niche, the set of strategies that enable a population to persist and define its impacts on the surroundings. Here we present a framework based on manifold learning, to organize genomic information into potentially occupied bacterial metabolic niches over time. We apply the method to re-construct the dynamics of putatively occupied metabolic niches using a long-term bacterial time-series from the Baltic Sea, the Linnaeus Microbial Observatory (LMO). The results reveal a relatively low-dimensional space of occupied metabolic niches comprising groups of taxa with similar functional capabilities. Time patterns of occupied niches were strongly driven by seasonality. Some metabolic niches were dominated by one bacterial taxon whereas others were occupied by multiple taxa, and this depended on season. These results illustrate the power of manifold learning approaches to advance our understanding of the links between community composition and functioning in microbial systems. ImportanceThe increase in data availability of bacterial communities highlights the need for conceptual frameworks to advance our understanding of these complex and diverse communities alongside the production of such data. To understand the dynamics of these tremendously diverse communities, we need tools to identify overarching strategies and describe their role and function in the ecosystem in a comprehensive way. Here, we show that a manifold learning approach can coarse grain bacterial communities in terms of their metabolic strategies and that we can thereby quantitatively organize genomic information in terms of potentially occupied niches over time. This approach therefore advances our understanding of how fluctuations in bacterial abundances and species composition can relate to ecosystem functions and it can facilitate the analysis, monitoring and future predictions of the development of microbial communities.

microbiology↗