Why Averages Fail For Bacteria In Open Ocean

Sinking organic particles, often called "marine snow", transport carbon from the surface to the deep ocean, accounting for roughly half of the ocean's total organic carbon export. As these particles sink, bacteria colonize and degrade them, influencing how much carbon ultimately reaches the deep ocean.

For bacteria that rely on these organic particles, the open ocean presents a major challenge. After leaving one particle, they may spend long periods searching for the next one. Reasoning based on average encounter times has long suggested that this "particle hopping" strategy should rarely succeed, as most individual bacteria would exhaust their energy before reaching another particle.

When averages fall short

To probe this paradox more deeply, the research team combined environmental microbiology with stochastic modelling to derive a generalized branching-process model of bacterial foraging. Rather than relying on average encounter rates, the model represents the distribution of search times and particle interaction outcomes, including rare rapid encounters with large particles that generate many offspring. Although such encounters are infrequent, their outsized contribution can reverse what averages would predict for population growth. The authors describe this effect as "stochastic resilience".

The results indicate that variability allows motile, particle-foraging bacteria to persist across a much broader range of marine environments than average-based reasoning would suggest, including parts of the open ocean and deep (bathypelagic) waters. Crucially, this persistence does not require bacteria to endure years-long periods of starvation. While many individuals fail to find another particle, a small number succeed quickly and generate enough offspring to sustain the population.

Variability that shapes ocean-scale processes

It is still difficult for ocean scientists to connect tiny microbial behaviours, such as movement or attachment to particles, to the much larger ecological and chemical processes in the ocean. Large-scale models necessarily describe microbial dynamics in terms of aggregate or average rates. Yet variability and rare events can influence population-level outcomes in ways that mean behaviour alone does not capture. By combining mathematical theory with environmental microbiology, this study shows how probabilistic frameworks can make those effects explicit.

Sinking particles form the backbone of the ocean's biological carbon pump, transporting organic matter toward the deep sea. As bacteria colonize and degrade these particles, they influence how much carbon is respired back to CO₂ and how much continues downward. By highlighting encounter variability, the study suggests that models based solely on average rates may underestimate microbial contributions to carbon export.

Dr Natasha Blitvić, Reader in Mathematical Sciences at Queen Mary, said:

"It's counterintuitive that populations can persist when most individual searches fail. Rare rapid encounters make the difference, but you only see that when you step away from averages and think probabilistically. Bringing mathematics and marine microbiology together made that perspective possible."

Professor Roman Stocker, Head of the Environmental Microfluidics Lab at ETH Zurich, added:

"We have investigated the movement behaviour of marine bacteria quite extensively to date, but it was only thanks to the mathematical framework that Natasha and Vicente contributed that we were together finally able to scale up the effect of that behaviour from single cells to the ocean ecosystem and thereby demonstrate that the probabilistic nature of that behaviour is a key ingredient in understanding microbial foraging strategies and ultimately the important ecological and biogeochemical processes they underpin".