Bernd Blasius is a professor for Mathematical Modelling at the University of Oldenburg. He is also a founding member of the Helmholtz Institute for Functional Marine Biodiversity (HIFMB).
Bernd Blasius works at the theoretical description of complex living systems at the interface of theoretical ecology and applied mathematics. Using modern tools from statistical physics, complex networks, dynamical systems theory and data science, he aims to obtain fundamental insights into the organization of living systems, but he is also concerned with the application of such concepts to specific biological systems and tangible applications.
Major research activities include such diverse fields as population dynamics and species interactions in spatially extended environments, biodiversity, bioinvasion and epidemic spread, evolution and adaptation, animal navigation and search strategies, origins of life, microbiology, and marine biogeochemistry.
Most important scientific contributions (together with co-authors):
The rampant loss of biodiversity is starting to be recognized as a global crisis rivaling the climate emergency. To address this crisis, scientists need robust methods to measure the diversity in a system. Importantly, these methods should not only count species but capture the variety of different functions that the species in a system can perform. In this paper, we propose a machine learning method by which existing data from ecosystem monitoring can be reanalyzed to reveal changes of functional biodiversity over time.
Marine dissolved organic matter (DOM) contains more carbon than the combined stocks of Earth’s biota. Organisms in the ocean continuously release a myriad of molecules that become food for microheterotrophs, but, for unknown reasons, a residual fraction persists as DOM for millennia. In this Perspective, we discuss and compare two concepts that could explain this persistence. The long-standing ‘intrinsic recalcitrance’ paradigm attributes DOM stability to inherent molecular properties. In the ‘emergent recalcitrance’ concept, DOM is continuously transformed by marine microheterotrophs, with recalcitrance emerging on an ecosystems level. Both concepts are consistent with observations in the modern ocean, but they imply very different responses of the DOM pool to climate-related changes. To understand better DOM persistence, we propose a new overarching research strategy — the ecology of molecules — that integrates the concepts of intrinsic and emergent recalcitrance with the ecological and environmental context.
We analyse data on marine unicellular phytoplankton, exhibiting an astounding diversity of cell sizes and shapes. We quantify the variation in size and shape and explore their effects on taxonomic diversity. We find that cells of intermediate volume exhibit the greatest shape variation, with shapes ranging from oblate to extremely elongated forms, while very small and large cells are mostly compact. We show that cell shape has a strong effect on phytoplankton diversity, comparable in magnitude to the effect of cell volume, with both traits explaining up to 92% of the variance in phytoplankton diversity. Species richness decays exponentially with cell elongation and displays a log-normal dependence on cell volume, peaking for compact cells of intermediate volume.
COVID-19 is an emerging respiratory infectious disease caused by the coronavirus SARS-CoV-2. It was first reported on in early December 2019 in Wuhan, China and within three months spread as a pandemic around the whole globe. Here, we study macro-epidemiological patterns along the time course of the COVID-19 pandemic. We compute the distribution of confirmed COVID-19 cases and deaths for countries worldwide and for counties in the US and show that both distributions follow a truncated power-law over five orders of magnitude. We are able to explain the origin of this scaling behavior as a dual-scale process: the large-scale spread of the virus between countries and the small-scale accumulation of case numbers within each country. Assuming exponential growth on both scales, the critical exponent of the power-law is determined by the ratio of large-scale to small-scale growth rates. We confirm this theory in numerical simulations in a simple meta-population model, describing the epidemic spread in a network of interconnected countries. Our theory gives a mechanistic explanation why most COVID-19 cases occurred within a few epicenters, at least in the initial phase of the outbreak. By combining real world data, modeling, and numerical simulations, we make the case that the distribution of epidemic prevalence might follow universal rules.
Predator–prey cycles rank among the most fundamental concepts in ecology, are predicted by the simplest ecological models and enable, theoretically, the indefinite persistence of predator and prey. However, it remains an open question for how long cyclic dynamics can be self-sustained in real communities. Field observations have been restricted to a few cycle periods and experimental studies indicate that oscillations may be short-lived without external stabilizing factors. Here we performed microcosm experiments with a planktonic predator–prey system and repeatedly observed oscillatory time series of unprecedented length that persisted for up to around 50 cycles or approximately 300 predator generations.
The rate of biological invasions has strongly increased during the last decades, mostly due to the accelerated spread of species by increasing global trade and transport. Here, we combine the network of global cargo ship movements with port environmental conditions and biogeography to quantify the probability of new primary invasions through the release of ballast water…
Many real-world networks are characterized by adaptive changes in their topology depending on the state of their nodes. Here we study epidemic dynamics on an adaptive network, where the susceptibles are able to avoid contact with the infected by rewiring their network connections. This gives rise to assortative degree correlation, oscillations, hysteresis, and first order transitions. We propose a low-dimensional model to describe the system and present a full local bifurcation analysis. Our results indicate that the interplay between dynamics and topology can have important consequences for the spreading of infectious diseases and related applications.
Population cycles that persist in time and are synchronized over space pervade ecological systems, but their underlying causes remain a long-standing enigma. Here we examine the synchronization of complex population oscillations in networks of model communities and in natural systems. In the proposed spatial model, each local patch sustains a three-level trophic system composed of interacting predators, consumers and vegetation. Populations oscillate regularly and periodically in phase, but with irregular and chaotic peaks together in abundance—twin realistic features that are not found in standard ecological models…