Phytoplankton and particle size spectra indicate intense mixotrophic dinoflagellates grazing from summer to winter.

Mixotrophic dinoflagellates (MTD) are a diverse group of organisms often responsible for the formation of harmful algal blooms. However, the development of dinoflagellate blooms and their effects on the plankton community are still not well explored. Here we relate the species succession of MTD with parallel changes of phytoplankton size spectra during periods of MTD dominance. We used FlowCAM analysis to acquire size spectra in the range 2-200 µm every one or two weeks from July to December 2007 at Helgoland Roads (Southern North Sea). Most size spectra of dinoflagellates were bimodal, whereas for other groups, e.g. diatoms and autotrophic flagellates, the spectra were unimodal, which indicates different resource use strategies of autotrophs and mixotrophs. The biomass lost in the size spectrum correlates with the potential grazing pressure of MTD. Based on size-based analysis of trophic linkages, we suggest that mixotrophy, including detritivory, drives species succession and facilitates the formation of bimodal size spectra. Bimodality in particular indicates niche differentiation through grazing of large MTD on smaller MTD. Phagotrophy of larger MTD may exceed one of the smaller MTD since larger prey was more abundant than smaller prey. Under strong light limitation, a usually overlooked refuge strategy may derive from detritivory. The critical role of trophic links of MTD as a central component of the plankton community may guide future observational and theoretical research.

Changing readiness to mitigate SARS-CoV-2 steered long-term epidemic and social trajectories.

Societal responses crucially shape the course of a pandemic, but are difficult to predict. Mitigation measures such as social distancing are here assumed to minimize a utility function that consists of two conflicting sub-targets, the disease related mortality and the multifaceted consequences of mitigation. The relative weight of the two sub-targets defines the mitigation readiness H, which entails the political, social, and psychological aspects of decision making. The dynamics of social and behavioral mitigation thus follows an adaptive rule, which in turn is mediated by a non-adaptive dynamics of H. This framework for social dynamics is integrated into an epidemiological model and applied to the ongoing SARS-CoV-2 pandemic. Unperturbed simulations accurately reproduce diverse epidemic and mitigation trajectories from 2020 to 2021, reported from 11 European countries, Iran, and 8 US states. High regional variability in the severity and duration of the spring lockdown and in peak mortality rates of the first SARS-CoV-2 wave can be explained by differences in the reconstructed readiness H. A ubiquitous temporal decrease of H has greatly intensified second and third waves and slowed down their decay. The unprecedented skill of the model suggests that the combination of an adaptive and a non-adaptive rule may constitute a more fundamental mode in social dynamics. Its implementation in an epidemic context can produce realistic long-term scenarios relevant for strategic planning, such as on the feasibility of a zero-infection target or on the evolutionary arms race between mutations of SARS-CoV-2 and social responses.

Vertical migration by bulk phytoplankton sustains biodiversity and nutrient input to the surface ocean.

Phytoplankton subsumes the great variety of unicellular photoautotrophs that perform roughly half of Earth's primary production. They achieve this despite their challenging oceanic habitat, with opposing vertical gradients of nutrients (which often limit their growth near the surface) and light (which becomes limiting with increasing depth). Most phytoplankton species are commonly assumed to be incapable of moving actively between the zones of light and nutrient availability, which are separated vertically by from 30-120 m. Here we propose that a considerable fraction of phytoplankton vertically traverse these gradients over time scales from hours to weeks, employing variations of a common migration strategy to acquire multiple resources. We present a mechanistic Lagrangian model resolving phytoplankton growth linked to optimal migration behaviour and demonstrate unprecedented agreement of its calculated vertical CHL-a distributions with 773 profiles observed at five prominent marine time-series stations. Our simulations reveal that vertically cycling phytoplankton can pump up enough nutrient to sustain as much as half of oceanic Net Primary Production (NPP). Active locomotion is therefore a plausible mechanism enabling relatively high NPP in the oligotrophic surface ocean. Our simulations also predict similar fitness for a variety of very different migration strategies, which helps to explain the puzzling diversity of phytoplankton observed in the ocean.

Physics or biology? Persistent chlorophyll accumulation in a shallow coastal sea explained by pathogens and carnivorous grazing.

One of the most striking patterns at the land-ocean interface is the massive increase of chlorophyll-a (CHL) from continental shelves towards the coast, a phenomenon that is classically linked to physical features. Here I propose that the coastal-offshore CHL gradient in a shallow sea has biological origins related to phytoplankton mortality that are neglected in state-of-the-art biogeochemical models. I integrate a trait-based ecosystem model into a modular coupling framework that is applied to the southern North Sea (SNS). The coupled model very well reproduces daily, seasonal and inter-annual (2000-2014) dynamics and meso-scale patterns in macronutrients, zooplankton biomass, and CHL as observed in situ and by remote sensors. Numerical experiments reveal that coast-offshore CHL gradients may predominantly arise from a trophic effect as resolved by an increase in carnivorous grazing towards shallow waters. This carnivory gradient reflects higher near-coast abundance of juvenile fish and benthic filter feeders. Furthermore, the temporal evolution of CHL can be much affected by viral infection as a fast-responding loss process at intermediate to high phytoplankton concentrations. Viral control in the model also prevents excessive and unrealistic blooms during late spring. Herbivores as often only ecological factor considered for explaining the spatio-temporal phytoplankton distribution are in this study supplemented by pathogens as well as pelagic and benthic carnivores as powerful agents, which are barely represented in current modeling but can mediate physical drivers of coastal ecosystems.

Effect of phytoplankton size diversity on primary productivity in the North Pacific: trait distributions under environmental variability.

While most biodiversity and ecosystem functioning (BEF) studies have found positive effects of species richness on productivity, it remain unclear whether similar patterns hold for marine phytoplankton with high local richness. We use the continuous trait-based modelling approach, which assumes infinite richness and represents diversity in terms of the variance of the size distribution, to investigate the effects of phytoplankton size diversity on productivity in a three-dimensional ocean circulation model driven by realistic physics forcing. We find a slightly negative effect of size diversity on primary production, which we attribute to several factors including functional trait-environment interactions, flexible stoichiometry and the saturation of productivity at low diversity levels. The benefits of trait optimisation, whereby narrow size distributions enhance productivity under relatively stable conditions, tend to dominate over those of adaptive capacity, whereby greater diversity enhances the ability of the community to respond to environmental variability.

Rapid aggregation of biofilm-covered microplastics with marine biogenic particles.

Ocean plastic pollution has resulted in a substantial accumulation of microplastics in the marine environment. Today, this plastic litter is ubiquitous in the oceans, including even remote habitats such as deep-sea sediments and polar sea ice, and it is believed to pose a threat to ecosystem health. However, the concentration of microplastics in the surface layer of the oceans is considerably lower than expected, given the ongoing replenishment of microplastics and the tendency of many plastic types to float. It has been hypothesized that microplastics leave the upper ocean by aggregation and subsequent sedimentation. We tested this hypothesis by investigating the interactions of microplastics with marine biogenic particles collected in the southwestern Baltic Sea. Our laboratory experiments revealed a large potential of microplastics to rapidly coagulate with biogenic particles, which substantiates this hypothesis. Together with the biogenic particles, the microplastics efficiently formed pronounced aggregates within a few days. The aggregation of microplastics and biogenic particles was significantly accelerated by microbial biofilms that had formed on the plastic surfaces. We assume that the demonstrated aggregation behaviour facilitates the export of microplastics from the surface layer of the oceans and plays an important role in the redistribution of microplastics in the oceans.

Intermittency in processing explains the diversity and shape of functional grazing responses.

Central to theoretical studies of trophic interactions is the formulation of the consumer response to varying food availability. Response functions, however, are only rarely derived in mechanistic ways. As a consequence, the uncertainty in the functional representation of feeding remains large, as, e.g., evident from the ongoing debate on the usage of Ivlev, or Holling type I, II, and III functions in aquatic ecosystem models. Here, I refer to the work of Sjöberg in Ecol Model 10:215-225 (1980) who proposed to apply elements of the queuing theory developed in operational research to plankton-plankton interactions. Within this frame, food item processing is subdivided into two major stages which may operate with variable synchronicity. Asynchronous phasing of the two stages enhances the probability of long total processing times. This phenomenon is here termed feeding intermittency. Intermittency is assumed to determine the functional form of grazing kinetics, for which a novel grazing function containing a "shape" parameter is derived. Using this function, I evaluate the hypotheses that intermittency is influenced by (1) patchiness in the prey field (e.g., related to turbulence), and (2) the ratio of actual prey size to optimal prey size. Evidence for the first hypothesis arises from explaining reported variations in clearance rates of Acartia tonsa under different turbulence regimes. Further model applications to ingestion data for rotifers, copepods, and ciliates support the view that an increasing food size enhances intermittency and, this way, affects functional grazing responses. In the application to ciliate grazing, a possible prey density effect appears, possibly due to an intermittent activation of a feeding sub-stage. Queueing theory offers mechanistic explanations for transitions between Holling I-, II-, and Ivlev-type grazing. In doing so for variable prey size ratios, it may also refine size-based ecosystem models which are increasingly emerging in plankton ecology.

Predator-prey dynamics driven by feedback between functionally diverse trophic levels.

Neglecting the naturally existing functional diversity of communities and the resulting potential to respond to altered conditions may strongly reduce the realism and predictive power of ecological models. We therefore propose and study a predator-prey model that describes mutual feedback via species shifts in both predator and prey, using a dynamic trait approach. Species compositions of the two trophic levels were described by mean functional traits--prey edibility and predator food-selectivity--and functional diversities by the variances. Altered edibility triggered shifts in food-selectivity so that consumers continuously respond to the present prey composition, and vice versa. This trait-mediated feedback mechanism resulted in a complex dynamic behavior with ongoing oscillations in the mean trait values, reflecting continuous reorganization of the trophic levels. The feedback was only possible if sufficient functional diversity was present in both trophic levels. Functional diversity was internally maintained on the prey level as no niche existed in our system, which was ideal under any composition of the predator level due to the trade-offs between edibility, growth and carrying capacity. The predators were only subject to one trade-off between food-selectivity and grazing ability and in the absence of immigration, one predator type became abundant, i.e., functional diversity declined to zero. In the lack of functional diversity the system showed the same dynamics as conventional models of predator-prey interactions ignoring the potential for shifts in species composition. This way, our study identified the crucial role of trade-offs and their shape in physiological and ecological traits for preserving diversity.

The economy of oil spills: direct and indirect costs as a function of spill size.

As a rational basis for addressing both ecological and economic consequences of oil spills, a combination of simulating and estimating methods is proposed in this paper. An integration of the state-of-the-art oil spill contingency simulation system OSCAR with economic assessment method leads to realistic oil spill scenarios including their biological and economic impacts and the effort taken for combat as well as to an estimate for the total oil spill costs. In order to derive a simple function of total costs depending on few spill characteristics such as size, a number of hypothetical scenarios are simulated and evaluated for the German North Sea area. Results reveal that response costs of per unit oil spilled as well as integrated costs of oil released are simply characterized as two particular power-law functions of spill size. Such relationships can be straightforward transferred into decision making for efficient prevention and combat strategy in the study area.

Willingness to pay among households to prevent coastal resources from polluting by oil spills: a pilot survey.

In many coastal regions oil spills can be considered to be one of the most important risks for the coastal environment. Efficient contingency management in responding to oil spills is critically important. Strategic priorities in contingency management highly depend upon the importance attributed to different economic and ecological resources such as beaches or birds. Due to the lack of a market for natural resources in the real world, these resources cannot be directly measured in monetary terms. This increases the risk that natural resources and their services are neglected in contingency decision making. This paper evaluates these natural resources in a hypothetical market by using the methodology of stated choice experiments. Results from a pilot survey show that according to the perspective of individuals, an oil spill combat process should focus on the protection of coastal waters, beaches and eider ducks.

Consensus oriented fuzzified decision support for oil spill contingency management.

Studies on multi-group multi-criteria decision-making problems for oil spill contingency management are in their infancy. This paper presents a second-order fuzzy comprehensive evaluation (FCE) model to resolve decision-making problems in the area of contingency management after environmental disasters such as oil spills. To assess the performance of different oil combat strategies, second-order FCE allows for the utilization of lexical information, the consideration of ecological and socio-economic criteria and the involvement of a variety of stakeholders. On the other hand, the new approach can be validated by using internal and external checks, which refer to sensitivity tests regarding its internal setups and comparisons with other methods, respectively. Through a case study, the Pallas oil spill in the German Bight in 1998, it is demonstrated that this approach can help decision makers who search for an optimal strategy in multi-thread contingency problems and has a wider application potential in the field of integrated coastal zone management.

Adaptive significance of C partitioning and regulation of specific leaf area in Betula pendula.

Carbon allocation and regulation of specific leaf area (sigma) define key processes underlying the adaptation of plants to varying habitats. In this study, the general principles governing adaptation and a dynamic optimality model of plant adaptation are reviewed. The central new elements of this model are: (i) differential root carbon costs for maintaining a defined nutrient status; (ii) a simple formula for optimal sigma at steady-state as a function of nitrogen (N) status and irradiance; and (iii) generic rules for the time propagation of adapting traits. The model was applied to a large data set compiled by Ingestad et al. (1995) and McDonald et al. (1986a, 1986b) for birch seedlings (Betula pendula Roth) during stationary logarithmic growth and during transient changes in response to a range of irradiances and nutrient supply rates. In the stationary case, large variations in the fraction of leaf dry mass to total dry mass (f(L)), sigma and N concentration were simulated with high accuracy. The independently calibrated model described the temporal response of seedlings following a sharp decrease in N supply, which includes phenomena such as the temporary C accumulation in leaves and damped oscillations in N concentration. Dynamics in sigma were more sensitive to variation in light than in N supply. Nevertheless, adaptive adjustments in f(L), sigma and N concentration were strongly coupled, underlining the relevance of a whole-plant perspective when modeling plant growth and regulation. The high coincidence between model calculations and measured values supports the notion that plant acclimation can be both understood and predicted as a growth-optimizing mechanism.

Control of biogeochemical cycling by mobility and metabolic strategies of microbes in the sediments: an integrated model study.

An integrated modeling framework was developed to assess physical, biological and chemical processes in the sediment and at the sediment-water interface. Special focus is laid on the description of different functional groups of bacteria as defined according to their metabolic pathways, including fermentation, methanogenesis and oxidation of high and low molecular mass dissolved organic carbon, ammonium as well as other reduced compounds. The model is subjected to a new validation method which allows for an appropriate representation of remaining uncertainties. It is also able to reproduce two-dimensional gradients in all state variables induced by a pore-water velocity field typical for permeable sediments. Another improvement with respect to many classical models follows from the simulation of adaptive changes in dormancy and motility strategies. Within an extensive analysis stage, the evolutionary stability of these strategies is investigated under a variable hydrodynamical regime. The results show that optimal behavior in terms of adhesion and readiness to dormancy shifts differ between functional groups. This pattern is compared to recent empirical findings and discussed in relation to the confidence limits of the overall methodology. In the numerical experiments, also the effect of variable microbial strategies on the total carbon mineralization of the sediment is determined.

A generic model for changes in microbial kinetic coefficients.

Acclimation patterns in kinetic coefficients clearly demonstrate the limits of Monod's theory for the mathematical description of microbial growth. Focusing on E. coli grown under variable glucose levels, these patterns turn out to be highly diverse and sometimes even contradictory. Here, a new model based on an optimisation assumption is applied to a spectrum of adaptation phenomena, which are observed at steady-state as well as during transient situations. On the level of apparent kinetic coefficients, rates of adaptation are calculated depending on differential growth benefits. The resulting dynamics is bounded since maximum growth rate and substrate affinity are related by a non-linear trade-off. Long-term effects of phenotypic and genotypic changes under glucose limitation are robustly predicted by the model and explained in terms of their adaptive significance. Equivocal short-term recovery patterns occurring after sudden substrate excess are traced back to differences in the internal physiological state of the cells which in turn can be calculated in dependence on the inoculum history. Metabolic stress is a second determinant of short-term variations in kinetic coefficients which is here quantified in relation to external conditions as well as the internal state of cells. We demonstrate that lag phenomena and oscillations in anabolic activity exercised by E. coli under continuous growth acceleration can be reproduced without formulations being explicit in lag periods, metabolite concentrations or the timing of experimental changes. The overall predictive power of the simple approach indicates that slow as well as fast adjustments in apparent kinetic characteristics are strongly related to a dynamic optimisation strategy.