A trait-based approach for downscaling complexity in plankton ecosystem models

We need to talk about the role of zooplankton in marine food webs

Zooplankton are the key intermediary between primary production and the fish community and a cornerstone of marine food webs, but they are often poorly represented in models that tend to focus on fish, charismatic top predators, or ocean biogeochemistry. In this study, we use an intermediate complexity end-to-end food web model of the North Sea with explicit two-way coupling of zooplankton to phytoplankton and higher trophic levels to ask whether this matters. We vary the metabolic rate of omnivorous zooplankton (OZ) as a proxy for uncertainties in our understanding and modeling of zooplankton form and function, and moving beyond previous studies we look at the impacts on the food web in concert with climate warming and fishing. We consider impacts on food web state and time to recover the relevant unfished state after fishing ceases. We also consider potential impacts on pelagic and demersal fishing fleets if we assume that they are constrained by the requirement to allow recovery to an unfished state within a certain period of time as a way of ensuring consistency with Good Environmental Status as required by EU and UK legislation. We find that all three aspects considered are highly sensitive to changes in the treatment of zooplankton, with impacts being larger than for warming of 2 or 4°C across most food web functional groups, particularly for apex predators. We call for a programme of research aimed at improving our understanding of zooplankton ecology and its relationship to the wider food web, and we recommend that improved representations of zooplankton are incorporated in future modeling studies as a priority.

Predator-Prey Evolution from an Eco-evolutionary Trade-off Model: The Role of Trait Differentiation

We develop a novel eco-evolutionary modelling framework and demonstrate its efficacy by simulating the evolution of trait distributions in predator and prey populations. The eco-evolutionary modelling framework assumes that population traits have beta distributions and defines canonical equations for the dynamics of each total population size, the population's average trait value, and a measure of the population's trait differentiation. The trait differentiation is included in the modelling framework as a phenotype analogue, Q, of Wright's fixation index [Formula: see text], which is inversely related to the sum of the beta distribution shape parameters. The canonical equations may be used as templates to describe the evolution of population trait distributions in many ecosystems that are subject to stabilising selection. The solutions of the "population model" are compared with those of a "phenotype model" that simulates the growth of each phenotype as it interacts with every other phenotype under the same trade-offs. The models assume no sources of new phenotypic variance, such as mutation or gene flow. We examine a predator-prey system in which each population trades off growth against mortality: the prey optimises devoting resources to growth or defence against predation; and the predator trades off increasing its attack rate against increased mortality. Computer solutions with stabilising selection reveal very close agreement between the phenotype and population model results, which both predict that evolution operates to stabilise an initially oscillatory system. The population model reduces the number of equations required to simulate the eco-evolutionary system by several orders of magnitude, without losing verisimilitude for the overarching population properties. The population model also allows insights into the properties of the system that are not available from the equivalent phenotype model.

Biogeochemical extremes and compound events in the ocean

The ocean is warming, losing oxygen and being acidified, primarily as a result of anthropogenic carbon emissions. With ocean warming, acidification and deoxygenation projected to increase for decades, extreme events, such as marine heatwaves, will intensify, occur more often, persist for longer periods of time and extend over larger regions. Nevertheless, our understanding of oceanic extreme events that are associated with warming, low oxygen concentrations or high acidity, as well as their impacts on marine ecosystems, remains limited. Compound events-that is, multiple extreme events that occur simultaneously or in close sequence-are of particular concern, as their individual effects may interact synergistically. Here we assess patterns and trends in open ocean extremes based on the existing literature as well as global and regional model simulations. Furthermore, we discuss the potential impacts of individual and compound extremes on marine organisms and ecosystems. We propose a pathway to improve the understanding of extreme events and the capacity of marine life to respond to them. The conditions exhibited by present extreme events may be a harbinger of what may become normal in the future. As a consequence, pursuing this research effort may also help us to better understand the responses of marine organisms and ecosystems to future climate change.

Intraspecific trait variation alters the outcome of competition in freshwater ciliates

Trait variation among heterospecific and conspecific organisms may substantially affect community and food web dynamics. While the relevance of competition and feeding traits have been widely studied for different consumer species, studies on intraspecific differences are more scarce, partly owing to difficulties in distinguishing different clones of the same species. Here, we investigate how intraspecific trait variation affects the competition between the freshwater ciliates Euplotes octocarinatus and Coleps hirtus in a nitrogen-limited chemostat system. The ciliates competed for the microalgae Cryptomonas sp. (Cry) and Navicula pelliculosa (Nav), and the bacteria present in the cultures over a period of 33 days. We used monoclonal Euplotes and three different Coleps clones (Col 1, Col 2, and Col 3) in the experiment that could be distinguished by a newly developed rDNA-based molecular assay based on the internal transcribed spacer (ITS) regions. While Euplotes feeds on Cry and on bacteria, the Coleps clones cannot survive on bacteria alone but feed on both Cry and Nav with clone-specific rates. Experimental treatments comprised two-species mixtures of Euplotes and one or all of the three different Coleps clones, respectively. We found intraspecific variation in the traits "selectivity" and "maximum ingestion rate" for the different algae to significantly affect the competitive outcome between the two ciliate species. As Nav quickly escaped top-down control and likely reached a state of low food quality, ciliate competition was strongly determined by the preference of different Coleps clones for Cry as opposed to feeding on Nav. In addition, the ability of Euplotes to use bacteria as an alternative food source strengthened its persistence once Cry was depleted. Hence, trait variation at both trophic levels codetermined the population dynamics and the outcome of species competition.

The emergence of new trophic levels in eco-evolutionary models with naturally-bounded traits

Ecosystems and food webs are structured into trophic levels of who eats whom. Species that occupy higher trophic levels have less available energy and higher energetic costs than species at lower trophic levels. So why do higher trophic levels exist? What processes generate new trophic levels? We consider a heuristic eco-evolutionary model based on simple Lotka-Volterra equations, where the evolution of traits is described by a generalisation of Lande's equation. The transition from competition to predation in this simplest of models is a successful, safe strategy for a population, and suggests a propensity to develop new trophic levels may be an inherent property of ecosystems. Numerical simulations with a more complex eco-evolutionary model of interacting plant and herbivore populations display the emergence of a new trophic level as an alternative to continued competition. These simulations reveal that new trophic levels may arise naturally from ecosystems because a robust strategy for a population in the presence of a strong competitor that could dominate or potentially extinguish them, is to predate upon the competitor. The same properties that make the competitor strong make it an ideal prey, suggesting the rubric that it is better to eat a strong competitor than to continue competing.

Second-order phase transition in phytoplankton trait dynamics

Key traits of unicellular species, such as cell size, often follow scale-free or self-similar distributions, hinting at the possibility of an underlying critical process. However, linking such empirical scaling laws to the critical regime of realistic individual-based model classes is difficult. Here, we reveal new empirical scaling evidence associated with a transition in the population and the chlorophyll dynamics of phytoplankton. We offer a possible explanation for these observations by deriving scaling laws in the vicinity of the critical point of a new universality class of non-local cell growth and division models. This "criticality hypothesis" can be tested through new scaling predictions derived for our model class, for the response of chlorophyll distributions to perturbations. The derived scaling laws may also be generalized to other cellular traits and environmental drivers relevant to phytoplankton ecology.

Storm impacts on phytoplankton community dynamics in lakes

In many regions across the globe, extreme weather events such as storms have increased in frequency, intensity, and duration due to climate change. Ecological theory predicts that such extreme events should have large impacts on ecosystem structure and function. High winds and precipitation associated with storms can affect lakes via short-term runoff events from watersheds and physical mixing of the water column. In addition, lakes connected to rivers and streams will also experience flushing due to high flow rates. Although we have a well-developed understanding of how wind and precipitation events can alter lake physical processes and some aspects of biogeochemical cycling, our mechanistic understanding of the emergent responses of phytoplankton communities is poor. Here we provide a comprehensive synthesis that identifies how storms interact with lake and watershed attributes and their antecedent conditions to generate changes in lake physical and chemical environments. Such changes can restructure phytoplankton communities and their dynamics, as well as result in altered ecological function (e.g., carbon, nutrient and energy cycling) in the short- and long-term. We summarize the current understanding of storm-induced phytoplankton dynamics, identify knowledge gaps with a systematic review of the literature, and suggest future research directions across a gradient of lake types and environmental conditions.

Changes in water color shift competition between phytoplankton species with contrasting light-harvesting strategies

The color of many lakes and seas is changing, which is likely to affect the species composition of freshwater and marine phytoplankton communities. For example, cyanobacteria with phycobilisomes as light-harvesting antennae can effectively utilize green or orange-red light. However, recent studies show that they use blue light much less efficiently than phytoplankton species with chlorophyll-based light-harvesting complexes, even though both phytoplankton groups may absorb blue light to a similar extent. Can we advance ecological theory to predict how these differences in light-harvesting strategy affect competition between phytoplankton species? Here, we develop a new resource competition model in which the absorption and utilization efficiency of different colors of light are varied independently. The model was parameterized using monoculture experiments with a freshwater cyanobacterium and green alga, as representatives of phytoplankton with phycobilisome-based vs. chlorophyll-based light-harvesting antennae. The parameterized model was subsequently tested in a series of competition experiments. In agreement with the model predictions, the green alga won the competition in blue light whereas the cyanobacterium won in red light, irrespective of the initial relative abundances of the species. These results are in line with observed changes in phytoplankton community structure in response to lake brownification. Similarly, in marine waters, the model predicts dominance of Prochlorococcus with chlorophyll-based light-harvesting complexes in blue light but dominance of Synechococcus with phycobilisomes in green light, with a broad range of coexistence in between. These predictions agree well with the known biogeographical distributions of these two highly abundant marine taxa. Our results offer a novel trait-based approach to understand and predict competition between phytoplankton species with different photosynthetic pigments and light-harvesting strategies.

Considering the Role of Adaptive Evolution in Models of the Ocean and Climate System

Numerical models have been highly successful in simulating global carbon and nutrient cycles in today's ocean, together with observed spatial and temporal patterns of chlorophyll and plankton biomass at the surface. With this success has come some confidence in projecting the century-scale response to continuing anthropogenic warming. There is also increasing interest in using such models to understand the role of plankton ecosystems in past oceans. However, today's marine environment is the product of billions of years of continual evolution-a process that continues today. In this paper, we address the questions of whether an assumption of species invariance is sufficient, and if not, under what circumstances current model projections might break down. To do this, we first identify the key timescales and questions asked of models. We then review how current marine ecosystem models work and what alternative approaches are available to account for evolution. We argue that for timescales of climate change overlapping with evolutionary timescales, accounting for evolution may to lead to very different projected outcomes regarding the timescales of ecosystem response and associated global biogeochemical cycling. This is particularly the case for past extinction events but may also be true in the future, depending on the eventual degree of anthropogenic disruption. The discipline of building new numerical models that incorporate evolution is also hugely beneficial in itself, as it forces us to question what we know about adaptive evolution, irrespective of its quantitative role in any specific event or environmental changes.

Phytoplankton size diversity and ecosystem function relationships across oceanic regions

Trait diversity, a key component of biodiversity, mediates many essential ecosystem functions and services. However, the mechanisms behind such relationships at large spatial scales are not fully understood. Here we adopt the functional biogeography approach to investigate how the size composition of phytoplankton communities relates to primary production and export production along a broad latitudinal gradient. Using in situ phytoplankton size distribution data and a trait-based model, we find an increase in the average phytoplankton size, size diversity, primary production and export when moving from low to high latitudes. Our analysis indicates that the interplay between spatio-temporal heterogeneities in environmental conditions and a trade-off between the high affinity for nutrients of smaller cells and the ability to avoid predation by larger cells are the main mechanisms driving the observed patterns. Our results also suggest that variations in size diversity alone do not directly lead to changes in primary production and export. The trade-off thus introduces a feedback that influences the relationship between size diversity and ecosystem functions. These findings support the importance of environmentally mediated trade-offs as crucial mechanisms shaping biodiversity and ecosystem function relationships at large spatial scales.

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.

Trait selection and co-existence of phytoplankton in partially mixed systems: Trait based modelling and potential of an aggregated approach

Trait selection and co-existence in phytoplankton communities in partially mixed water columns is investigated using trait based modelling. In the models employed, trait selection results from phytoplankton competition for two limiting resources, light and nutrients. The study employs spatially resolved models, in which the phytoplankton community is represented as a large number of trait-groups characterized by fixed trait combinations (trade-offs). Results from the trait-group resolving model (RM) are compared to results from an aggregated trait based model with adaptive traits (AM). Differences in specific production resulting from a trade-off between the half saturation constants of light and nutrients are sufficient to support evolutionary stable co-existence confirming that co-existence does not require differences in resource consumption. If abiotic conditions lead to the selection of a single trait group in RM, AM provides excellent approximations of the development of total biomass, average community trait and trait variance in the phytoplankton community. However, if selection leads to bimodal trait distributions, e.g. to co-existence of two trait groups (or species), functionally important properties of the phytoplankton community cannot be adequately represented by the aggregated information provided by AM. Because the increase in variance due to the development of bimodal trait distributions cannot be distinguished from an increase in variance due to an increase in trait diversity, the development of trait variance in AM models is not a reliable measure of trait diversity. Furthermore, AM may not provide reliable simulations of trophic interactions if the performance of the consumers depends on the traits of their resources. However, AM may support exploration of the consequences of environmental conditions and of the parameterization of species for co-existence within communities.

Evaluation of the complexity and performance of marine planktonic trophic models

Planktonic models represent a powerful tool for creating hypotheses and making predictions about the functioning of marine ecosystems. Their complexity varies according to the number of state variables and the choice of functional forms. We evaluated plankton models during the last 15 years (n =145) with the aims of understanding why they differ in complexity, evaluating model robustness, and describing studies of plankton modelling around the globe. We classified models into four groups: Nutrient-Phytoplankton-Zooplankton (NPZ), Nutrient-Phytoplankton-Zooplankton-Detritus (NPZD), Size-Structured (SS) and Plankton-Functional-Type (PFT). Our results revealed that the number of state variables varied according to the question being addressed: NPZ models were more frequently applied in physical-biological studies, while PFT models were more applied for investigating biogeochemical cycles. Most models were based on simple functional forms which neglect important feedback related to control of plankton dynamics. Modelling studies sometimes failed to describe sensitivity analysis, calibration and validation. The importance of testing different functional forms was commonly overlooked, and the lack of empirical data affected the verification of model robustness. Lastly, we highlight the need to develop modelling studies in the Southern Hemisphere, including Brazil, in order to provide predictions that assist the management of marine ecosystems.

Phytoplankton size-diversity mediates an emergent trade-off in ecosystem functioning for rare versus frequent disturbances

Biodiversity is known to be an important determinant of ecosystem-level functions and processes. Although theories have been proposed to explain the generally positive relationship between, for example, biodiversity and productivity, it remains unclear which mechanisms underlie the observed variations in Biodiversity-Ecosystem Function (BEF) relationships. Using a continuous trait-distribution model for a phytoplankton community of gleaners competing with opportunists, and subjecting it to differing frequencies of disturbance, we find that species selection tends to enhance temporal species complementarity, which is maximised at high disturbance frequency and intermediate functional diversity. This leads to the emergence of a trade-off whereby increasing diversity tends to enhance short-term adaptive capacity under frequent disturbance while diminishing long-term productivity under infrequent disturbance. BEF relationships therefore depend on both disturbance frequency and the timescale of observation.

Variable but persistent coexistence of Prochlorococcus ecotypes along temperature gradients in the ocean's surface mixed layer

The vast majority of the phytoplankton communities in surface mixed layer of the oligotrophic ocean are numerically dominated by one of two ecotypes of Prochlorococcus, eMIT9312 or eMED4. In this study, we surveyed large latitudinal transects in the Atlantic and Pacific Ocean to determine if these ecotypes discretely partition the surface mixed layer niche, or if populations exist as a continuum along key environmental gradients, particularly temperature. Transitions of dominance occurred at approximately 19-21°C, with the eMED4 ecotype dominating the colder, and eMIT9312 ecotype dominating the warmer regions. Within these zones of regional dominance, however, the minority ecotype was not competed to extinction. Rather, a robust log-linear relationship between ecotype ratio and temperature characterized this stabilized coexistence: for every 2.5°C increase in temperature, the eMIT9312:eMED4 ratio increased by an order of magnitude. This relationship was observed in both quantitative polymerase chain reaction and in pyrosequencing assays. Water column stratification also contributed to the ecotype ratio along the basin-scale transects, but to a lesser extent. Finally, instances where the ratio of the eMED4 and eMIT9312 abundances did not correlate well with temperature were identified. Such occurrences are likely due to changes in water temperatures outpacing changes in community structure.

Microbial resource utilization traits and trade-offs: implications for community structure, functioning, and biogeochemical impacts at present and in the future

Trait-based approaches provide a mechanistic framework to understand and predict the structure and functioning of microbial communities. Resource utilization traits and trade-offs are among key microbial traits that describe population dynamics and competition among microbes. Several important trade-offs have been identified for prokaryotic and eukaryotic microbial taxa that define contrasting ecological strategies and contribute to species coexistence and diversity. The shape, dimensionality, and hierarchy of trade-offs may determine coexistence patterns and need to be better characterized. Laboratory measured resource utilization traits can be used to explain temporal and spatial structure and dynamics of natural microbial communities and predict biogeochemical impacts. Global environmental change can alter microbial community composition through altering resource utilization by different microbes and, consequently, may modify biogeochemical impacts of microbes.

Mechanisms shaping size structure and functional diversity of phytoplankton communities in the ocean

The factors regulating phytoplankton community composition play a crucial role in structuring aquatic food webs. However, consensus is still lacking about the mechanisms underlying the observed biogeographical differences in cell size composition of phytoplankton communities. Here we use a trait-based model to disentangle these mechanisms in two contrasting regions of the Atlantic Ocean. In our model, the phytoplankton community can self-assemble based on a trade-off emerging from relationships between cell size and (1) nutrient uptake, (2) zooplankton grazing, and (3) phytoplankton sinking. Grazing 'pushes' the community towards larger cell sizes, whereas nutrient uptake and sinking 'pull' the community towards smaller cell sizes. We find that the stable environmental conditions of the tropics strongly balance these forces leading to persistently small cell sizes and reduced size diversity. In contrast, the seasonality of the temperate region causes the community to regularly reorganize via shifts in species composition and to exhibit, on average, bigger cell sizes and higher size diversity than in the tropics. Our results raise the importance of environmental variability as a key structuring mechanism of plankton communities in the ocean and call for a reassessment of the current understanding of phytoplankton diversity patterns across latitudinal gradients.

Individual cell based traits obtained by scanning flow-cytometry show selection by biotic and abiotic environmental factors during a phytoplankton spring bloom

In ecology and evolution, the primary challenge in understanding the processes that shape biodiversity is to assess the relationship between the phenotypic traits of organisms and the environment. Here we tested for selection on physio-morphological traits measured by scanning flow-cytometry at the individual level in phytoplankton communities under a temporally changing biotic and abiotic environment. Our aim was to study how high-frequency temporal changes in the environment influence biodiversity dynamics in a natural community. We focused on a spring bloom in Lake Zurich (Switzerland), characterized by rapid changes in phytoplankton, water conditions, nutrients and grazing (mainly mediated by herbivore ciliates). We described bloom dynamics in terms of taxonomic and trait-based diversity and found that diversity dynamics of trait-based groups were more pronounced than those of identified phytoplankton taxa. We characterized the linkage between measured phytoplankton traits, abiotic environmental factors and abundance of the main grazers and observed weak but significant correlations between changing abiotic and biotic conditions and measured size-related and fluorescence-related traits. We tested for deviations in observed community-wide distributions of focal traits from random patterns and found evidence for both clustering and even spacing of traits, occurring sporadically over the time series. Patterns were consistent with environmental filtering and phenotypic divergence under herbivore pressure, respectively. Size-related traits showed significant even spacing during the peak of herbivore abundance, suggesting that morphology-related traits were under selection from grazing. Pigment distribution within cells and colonies appeared instead to be associated with acclimation to temperature and water chemistry. We found support for trade-offs among grazing resistance and environmental tolerance traits, as well as for substantial periods of dynamics in which our measured traits were not under selection.

Human adaptive behavior in common pool resource systems

Overexploitation of common-pool resources, resulting from uncooperative harvest behavior, is a major problem in many social-ecological systems. Feedbacks between user behavior and resource productivity induce non-linear dynamics in the harvest and the resource stock that complicate the understanding and the prediction of the co-evolutionary system. With an adaptive model constrained by data from a behavioral economic experiment, we show that users’ expectations of future pay-offs vary as a result of the previous harvest experience, the time-horizon, and the ability to communicate. In our model, harvest behavior is a trait that adjusts to continuously changing potential returns according to a trade-off between the users’ current harvest and the discounted future productivity of the resource. Given a maximum discount factor, which quantifies the users’ perception of future pay-offs, the temporal dynamics of harvest behavior and ecological resource can be predicted. Our results reveal a non-linear relation between the previous harvest and current discount rates, which is most sensitive around a reference harvest level. While higher than expected returns resulting from cooperative harvesting in the past increase the importance of future resource productivity and foster sustainability, harvests below the reference level lead to a downward spiral of increasing overexploitation and disappointing returns.

Modeling microbial community structure and functional diversity across time and space

Microbial communities exhibit exquisitely complex structure. Many aspects of this complexity, from the number of species to the total number of interactions, are currently very difficult to examine directly. However, extraordinary efforts are being made to make these systems accessible to scientific investigation. While recent advances in high-throughput sequencing technologies have improved accessibility to the taxonomic and functional diversity of complex communities, monitoring the dynamics of these systems over time and space - using appropriate experimental design - is still expensive. Fortunately, modeling can be used as a lens to focus low-resolution observations of community dynamics to enable mathematical abstractions of functional and taxonomic dynamics across space and time. Here, we review the approaches for modeling bacterial diversity at both the very large and the very small scales at which microbial systems interact with their environments. We show that modeling can help to connect biogeochemical processes to specific microbial metabolic pathways.

Modeling microbial communities: current, developing, and future technologies for predicting microbial community interaction

Never has there been a greater opportunity for investigating microbial communities. Not only are the profound effects of microbial ecology on every aspect of Earth's geochemical cycles beginning to be understood, but also the analytical and computational tools for investigating microbial Earth are undergoing a rapid revolution. This environmental microbial interactome, the system of interactions between the microbiome and the environment, has shaped the planet's past and will undoubtedly continue to do so in the future. We review recent approaches for modeling microbial community structures and the interactions of microbial populations with their environments. Different modeling approaches consider the environmental microbial interactome from different aspects, and each provides insights to different facets of microbial ecology. We discuss the challenges and opportunities for the future of microbial modeling and describe recent advances in microbial community modeling that are extending current descriptive technologies into a predictive science.

Modeling diverse communities of marine microbes

Biogeochemical cycles in the ocean are mediated by complex and diverse microbial communities. Over the past decade, marine ecosystem and biogeochemistry models have begun to address some of this diversity by resolving several groups of (mostly autotrophic) plankton, differentiated by biogeochemical function. Here, we review recent model approaches that are rooted in the notion that an even richer diversity is fundamental to the organization of marine microbial communities. These models begin to resolve, and address the significance of, diversity within functional groups. Seeded with diverse populations spanning prescribed regions of trait space, these simulations self-select community structure according to relative fitness in the virtual environment. Such models are suited to considering ecological questions, such as the regulation of patterns of biodiversity, and to simulating the response to changing environments. A key issue for all such models is the constraint of viable trait space and trade-offs. Size-structuring and mechanistic descriptions of energy and resource allocation at the individual level can rationalize these constraints.