Phytoplankton adaptation in ecosystem models.

We compare two different approaches to model adaptation of phytoplankton through trait value changes. Both consider mutation and selection (MuSe) but differ with respect to the underlying conceptual framework. The first one (MuSe-IBM) explicitly considers a population of individuals that are subject to random mutation during cell division. The second is a deterministic multi-compartment model (MuSe-MCM) that considers numerous genotypes of the population and where mutations are treated as a transfer of biomass between neighboring genotypes (i.e., a diffusion of characteristics in trait space). Focusing on the adaptation of optimal temperature, we show model results for different scenarios: a sudden change in environmental temperature, a seasonal variation and high frequency fluctuations. In addition, we investigate the effect of different shapes of thermal reaction norms as well as the role of alternating growth and resting phases on the adaptation process. For all cases, the differences between MuSe-IBM and MuSe-MCM are found to be negligible. Both models produce a number of well-known and plausible features. While the IBM has the advantage of including more mechanistic (i.e., probabilistic) processes, the MCM is much less computationally demanding and therefore suitable for implementation in three-dimensional ecosystem models.

Evolution in temperature-dependent phytoplankton traits revealed from a sediment archive: do reaction norms tell the whole story?

The high evolutionary potential of phytoplankton species allows them to rapidly adapt to global warming. Adaptations may occur in temperature-dependent traits, such as growth rate, cell size and life cycle processes. Using resurrection experiments with resting stages from living sediment archives, it is possible to investigate whether adaptation occurred. For this study, we revived resting cysts of the spring bloom dinoflagellate Apocalathium malmogiense from recent and 100-year-old sediment layers from the Gulf of Finland, and compared temperature-dependent traits of recent and historic strains along a temperature gradient. We detected no changes in growth rates and cell sizes but a significant difference between recent and historic strains regarding resting cyst formation. The encystment rate of recent strains was significantly lower compared with historic strains which we interpret as an indication of adaptation to higher and more rapidly increasing spring temperatures. Low encystment rates may allow for bloom formation even if the threshold temperature inducing a loss of actively growing cells through resting cyst formation is exceeded. Our findings reveal that phenotypic responses of phytoplankton to changing temperature conditions may include hidden traits such as life cycle processes and their regulation mechanisms. This study emphasizes the potential of living sediment archives to investigate plankton responses and adaptation to global warming.

Modeling the Role of pH on Baltic Sea Cyanobacteria.

We simulate pH-dependent growth of cyanobacteria with an ecosystem model for the central Baltic Sea. Four model components-a life cycle model of cyanobacteria, a biogeochemical model, a carbonate chemistry model and a water column model-are coupled via the framework for aquatic biogeochemical models. The coupled model is forced by the output of a regional climate model, based on the A1B emission scenario. With this coupled model, we perform simulations for the period 1968-2098. Our simulation experiments suggest that in the future, cyanobacteria growth is hardly affected by the projected pH decrease. However, in the simulation phase prior to 1980, cyanobacteria growth and N2-fixation are limited by the relatively high pH. The observed absence of cyanobacteria before the 1960s may thus be explained not only by lower eutrophication levels, but also by a higher alkalinity.