Niche separation between different functional types of mixoplankton: results from NPZ-style N-based model simulations

Protist plankton comprise phytoplankton (incapable of phagotrophy), protozooplankton (incapable of phototrophy) and mixoplankton (capable of phototrophy and phagotrophy). Of these, only phytoplankton and zooplankton are typically described in models. Over the last decade, however, the importance of mixoplankton across all marine biomes has risen to prominence. We thus need descriptions of mixoplankton within marine models. Here we present a simple yet flexible N-based model describing any one of the five basic patterns of protist plankton: phytoplankton, protozooplankton, and the three functional groups of mixoplankton: general non-constitutive mixoplankton (GNCM), specialist non-constitutive mixoplankton (SNCM), and constitutive mixoplankton (CM). By manipulation of a few input switch values, the same model can be used to describe any of these patterns, while adjustment of salient features, such as the percent of C-fixation required for mixotrophic growth, and the rate of phototrophic prey ingestion required to enable growth of GNCM and SNCM types, readily provides fine tuning. Example outputs are presented showing how the performance of these different protist configurations accords with expectations (set against empirical evidence). Simulations demonstrate clear niche separations between these protist functional groups according to nutrient, prey and light resource availabilities. This addition to classic NPZ plankton models provides for the exploration of the implications of mixoplankton activity in a simple yet robust fashion.

Plankton Models and Its Attractors in a Local Approximation

The previously accepted models of plankton consisting of two interacting populations—phytoplankton and zooplankton—are considered in a local approximation. The analysis of models is carried out with the help of a qualitative study of systems of differential equations as a whole (i.e., in the entire phase space of systems, not limited to a neighborhood of equilibrium positions). Analytical conditions for the occurrence of a Hopf bifurcation are obtained for each model using the Lyapunov stability theory. A comparison of various models is given, and their shortcomings associated with the incompleteness of research are indicated. It has been established that in some cases the loss of stability of the equilibrium position does not lead to the formation of a limit cycle (Hopf bifurcation) but to the formation of a limit continuum with a chaotic behavior of the trajectories in a large part of the phase space. It is shown that the parameters significantly influencing the dynamics of the development of plankton are the natural mortality of populations as an environmental characteristic of the environment.

Plankton food-webs: to what extent can they be simplified?

<p class="p1">Plankton is a hugely diverse community including both unicellular and multicellular organisms, whose individual dimensions span over seven orders of magnitude. Plankton is a fundamental part of biogeochemical cycles and food-webs in aquatic systems. While knowledge has progressively accumulated at the level of single species and single trophic processes, the overwhelming biological diversity of plankton interactions is insufficiently known and a coherent and unifying trophic framework is virtually lacking. We performed an extensive review of the plankton literature to provide a compilation of data suitable for implementing food-web models including plankton trophic processes at high taxonomic resolution. We identified the components of the plankton community at the Long Term Ecological Research Station MareChiara in the Gulf of Naples. These components represented the sixty-three nodes of a plankton food-web. To each node we attributed biomass and vital rates, <em><span class="s1">i.e. </span></em>production, consumption, assimilation rates and ratio between autotrophy and heterotrophy in mixotrophic protists. Biomasses and rates values were defined for two opposite system’s conditions; relatively eutrophic and oligotrophic states. We finally identified 817 possible trophic links within the web and provided each of them with a relative weight, in order to define a diet-matrix, valid for both trophic states, which included all consumers, fromn anoflagellates to carnivorous plankton. Vital rates for plankton resulted, as expected, very wide; this strongly contrasts with the narrow ranges considered in plankton system models implemented so far. Moreover, the amount and variety of trophic links highlighted by our review is largely excluded by state-of-the-art biogeochemical and food-web models for aquatic systems. Plankton models could potentially benefit from the integration of the trophic diversity outlined in this paper: first, by using more realistic rates; second, by better defining trophic roles of consumers in the planktonic web. We suggest that most trophic habits present in planktonic organisms must be contemplated in new generation plankton models.</p>

Addressing the impact of environmental uncertainty in plankton model calibration with a dedicated software system: the Marine Model Optimization Testbed (MarMOT 1.1 alpha)

A wide variety of different plankton system models have been coupled with ocean circulation models, with the aim of understanding and predicting aspects of environmental change. However, an ability to make reliable inferences about real-world processes from the model behaviour demands a quantitative understanding of model error that remains elusive. Assessment of coupled model output is inhibited by relatively limited observing system coverage of biogeochemical components. Any direct assessment of the plankton model is further inhibited by uncertainty in the physical state. Furthermore, comparative evaluation of plankton models on the basis of their design is inhibited by the sensitivity of their dynamics to many adjustable parameters. Parameter uncertainty has been widely addressed by calibrating models at data-rich ocean sites. However, relatively little attention has been given to quantifying uncertainty in the physical fields required by the plankton models at these sites, and tendencies in the biogeochemical properties due to the effects of horizontal processes are often neglected. Here we use model twin experiments, in which synthetic data are assimilated to estimate a system's known "true" parameters, to investigate the impact of error in a plankton model's environmental input data. The experiments are supported by a new software tool, the Marine Model Optimization Testbed, designed for rigorous analysis of plankton models in a multi-site 1-D framework. Simulated errors are derived from statistical characterizations of the mixed layer depth, the horizontal flux divergence tendencies of the biogeochemical tracers and the initial state. Plausible patterns of uncertainty in these data are shown to produce strong temporal and spatial variability in the expected simulation error variance over an annual cycle, indicating variation in the significance attributable to individual model-data differences. An inverse scheme using ensemble-based estimates of the simulation error variance to allow for this environment error performs well compared with weighting schemes used in previous calibration studies, giving improved estimates of the known parameters. The efficacy of the new scheme in real-world applications will depend on the quality of statistical characterizations of the input data. Practical approaches towards developing reliable characterizations are discussed.