Plankton and its traits

Effects of grazing of mixotrophic dinoflagellates (MTD) on the phytoplankton size spectrum. (a) Changes in size spectra and potential grazing pressure of MTD when the fraction of MTD exceeded 10% of total biomass (value shown in the top left corner). (b) This fraction of MTD in the community (x) is a very good linear predictor for the feeding-loss index (FLI, overlapping of grazing pressure and biomass lost).

Some types of plankton, such as dinoflagellates, obtain energy and nutrients from both photosynthesis and the consumption of other organisms. This dual acquisition ability is called mixotrophy. Mixotrophs thrive in coastal waters where resources such as light and nutrients are highly variable and often limited. Our group develops trait-based models to unravel the role of mixotrophic organisms for ecosystem structure and biogeochemical cycling. Using a size-based predation model combined with observational and experimental data we have explored the ecological functions of mixotrophs in the Southern North Sea. For example, we revealed the critical role of mixotrophic dinoflagellates as main predators during late summer to winter (García-Oliva et al., 2022).

A key trait of dinoflagellates

Many dinoflagellates target prey in a confined size range. such as smaller phytoplankton or larger diatom chains, to enhance their growth and reproductive success (García-Oliva and Wirtz, 2022). In some cases, prey specialization and utilization allows dinoflagellates to grow so fast that they form Harmful Algal Blooms, which have detrimental effects on ecosystem functions, such as toxin production and oxygen depletion. Understanding prey specialization is thus crucial for assessing the health and stability of aquatic ecosystems.

A common trait across aquatic food-webs

Few eco-evolutionary rules for food-web assembly emerge from the universal feeding traits specialization and body size . These rules are based on repeated patterns in prey selection of aquatic predators across several orders of magnitude in body size and independent of taxa.

We discovered a small set of rules, which govern the assembly of aquatic food webs. The identification of these principles starts from the astounding prevalence of specialized predators in marine and freshwater food-webs (García-Oliva and Wirtz, 2025). Our new approach may allow the simplification of trophic relationships in end-to-end food web models and thus greatly improves the ability to predict the response of aquatic ecosystem to human pressures.

Effects of phytoplankton behaviour on the global carbon cycle

Increase in global oceanic NPP by >2 Pg-C yr-1 from 1985 to 2085 due to PVM
(Wirtz et al Nature Climate Change 2022)

The name plankton can be misleading because a majority of planktonic organisms are not just dumb drifters but regulate their vertical position in the water column and can thus access very different habitats. Our group has recently discovered -by modeling and compilation of indirect evidence- that bulk phytoplankton in the world oceans exhibits a migratory behavior. In the deep, phytoplankton cells take up nutrients, which are scarce in upper water layers. After ascending, these microscopic commuters fuel their carbon store by photosynthesis and then descend again to deeper waters. This migratory behavior has significant effects on the global carbon cycle. Publications

Vertical processes

Left: Phytoplankton Vertical Migration (PVM) as an adaptive behavior for resource acquisition in the widespread case of depleted nutrients at the surface. By descending to the chemocline at higher depth, autotrophic cells accumulate internal nutrient stores, while they gain energy and carbon after ascending to the sunlight upper ocean. Right: 1D Lagrangian model for the emergence of the subsurface chlorophyll (CHL) maximum due to PVM.

Phytoplankton Vertical Migration (PVM) as an adaptive behavior for resource acquisition in the widespread case of depleted nutrients at the surface. By descending to the chemocline at higher depth, autotrophic cells accumulate internal nutrient stores, while they gain energy and carbon after ascending to the sunlight upper ocean. Publications

Structure of the Model for Adaptive Ecosystems in Coastal Seas (MAECS) resolving plankton ecophysiological traits, biogeochemical cycling, also in the sediments, and pathogen dynamics (Wirtz 2019)

Our group develops innovative mechanistic trait-based models to describe the response of plankton and other ecosystem departments to multiple external drivers including Climate Change. We are also advancing the modular coupling of trait-based ecosystem models to physical models MOSSCO in order to describe the interaction between ocean physics and biological processes most efficiently. In many of our studies and projects (MuSSeL, ) we investigate the long-term ecosystem dynamics for identifying key drivers but also for evaluating mitigation strategies.
Using the first coupled, adaptive trait-based ecosystem model, the Model for Adaptive Ecosystems in Coastal Seas (MAECS), we could reconstruct long-term changes in ecosystem functioning but also plankton ecophysiology in the Southern North Sea (Wirtz 2019, data-set, Xu et al). For example, we revealed a critical importance of viral dynamics for the break-down of the phytoplankton spring bloom (Wirtz 2019, Krishna et al 2023), or the relevance of light conditions for a strong top-down regulation of coastal ecosystems.
Our numerical experiments always rely on extensive data integration and analysis and unravel how bottom-up and top-down controls are mediated by adaptive processes (trait variations) and system feed-backs.
Publications