Bimodal trait distributions with large variances question the reliability of trait-based aggregate models

Dynamic Trait Distribution as a Source for Shifts in Interaction Strength and Population Density

AbstractIntraspecific trait variation has been increasingly recognized as an important factor in determining species interactions and diversity. Eco-evolutionary models have studied the distribution of trait values within a population that changes over the generations as a result of selection and heritability. Nonheritable traits that can change within the lifetime, such as behavior, can cause trait-mediated indirect effects, often studied by modeling the dynamics of a homogeneous trait. Complementary to these approaches, we study the distribution of traits within a population and its dynamics on short timescales due to ecological processes. We consider several mechanisms by which the trait distribution can shift dynamically: phenotypic plasticity within each individual, differential growth among individuals, and preferential consumption by the predator. Through a simple predator-prey model that explicitly tracks the trait distribution within the prey, we identify the density and trait effects from the predator. We show that the dynamic shift of the trait distribution can lead to the modification of interaction strength between species and result in otherwise unexpected consequences. A particular example is the emergent promotion of the prey by the predator, where the introduction of the predator causes the prey population to increase rather than decrease.

Range of trait variation in prey determines evolutionary contributions to predator growth rates

Evolutionary and ecological dynamics can occur on similar timescales and thus influence each other. While it has been shown that the relative contribution of ecological and evolutionary change to population dynamics can vary, it still remains unknown what influences these differences. Here, we test whether prey populations with increased variation in their defence and competitiveness traits will have a stronger impact on evolution for predator growth rates. We controlled trait variation by pairing distinct clonal lineages of the green alga Chlamydomonas reinhardtii with known traits as prey with the rotifer Brachionus calyciforus as predator and compared those results with a mechanistic model matching the empirical system. We measured the impact of evolution (shift in prey clonal frequency) and ecology (shift in prey population density) for predator growth rate and its dependency on trait variation using an approach based on a 2-way ANOVA. Our experimental results indicated that higher trait variation, i.e., a greater distance in trait space, increased the relative contribution of prey evolution to predator growth rate over 3-4 predator generations, which was also observed in model simulations spanning longer time periods. In our model, we also observed clone-specific results, where a more competitive undefended prey resulted in a higher evolutionary contribution, independent of the trait distance. Our results suggest that trait combinations and total prey trait variation combine to influence the contribution of evolution to predator population dynamics, and that trait variation can be used to identify and better predict the role of eco-evolutionary dynamics in predator-prey systems.

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.

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.

Construction of Environmental Synthetic Microbial Consortia: Based on Engineering and Ecological Principles

In synthetic biology, engineering principles are applied to system design. The development of synthetic microbial consortia represents the intersection of synthetic biology and microbiology. Synthetic community systems are constructed by co-cultivating two or more microorganisms under certain environmental conditions, with broad applications in many fields including ecological restoration and ecological theory. Synthetic microbial consortia tend to have high biological processing efficiencies, because the division of labor reduces the metabolic burden of individual members. In this review, we focus on the environmental applications of synthetic microbial consortia. Although there are many strategies for the construction of synthetic microbial consortia, we mainly introduce the most widely used construction principles based on cross-feeding. Additionally, we propose methods for constructing synthetic microbial consortia based on traits and spatial structure from the perspective of ecology to provide a basis for future work.

The eco-evolutionary modelling of populations and their traits using a measure of trait differentiation

We develop new equations for the eco-evolutionary dynamics of populations and their traits. These equations resolve the change in the phenotypic differentiation within a population, which better estimates how the variance of the trait distribution changes. We note that traits may be bounded, assume they may be described by beta distributions with small variances, and develop a coupled ordinary differential equation system to describe the dynamics of the total population, the mean trait value, and a measure of phenotype differentiation. The variance of the trait in the population is calculated from its mean and the population's phenotype differentiation. We consider an example of two competing plant populations to demonstrate the efficacy of the new approach. Each population may trade-off its growth rate against its susceptibility to direct competition from the other population. We create two models of this system: a population model based on our new eco-evolutionary equations; and a phenotype model, in which the growth or demise of each fraction of each population with a defined phenotype is simulated as it interacts with a shared limiting resource and its competing phenotypes and populations. Comparison of four simulation scenarios reveals excellent agreement between the predicted quantities from both models: total populations, the average trait values, the trait variances, and the degree of phenotypic differentiation within each population. In each of the four scenarios simulated, three of which are initially subject to competitive exclusion in the absence of evolution, the populations adapt to coexist. One population maximises growth and dominates, while the other minimises competitive losses. These simulations suggest that our new eco-evolutionary equations may provide an excellent approximation to phenotype changes in populations.

Self-organised pattern formation increases local diversity in metacommunities

Self-organised formation of spatial patterns is known from a variety of different ecosystems, yet little is known about how these patterns affect the diversity of communities. Here, we use a food chain model in which autotroph diversity is described by a continuous distribution of a trait that affects both growth and defence against heterotrophs. On isolated patches, diversity is always lost over time due to stabilising selection, and the local communities settle on one of two alternative stable community states that are characterised by a dominance of either defended or undefended species. In a metacommunity context, dispersal can destabilise these states and complex spatio-temporal patterns in the species' abundances emerge. The resulting biomass-trait feedback increases local diversity by an order of magnitude compared to scenarios without self-organised pattern formation, thereby maintaining the ability of communities to adapt to potential future changes in biotic or abiotic environmental conditions.

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.

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.

How (co)evolution alters predator responses to increased mortality: extinction thresholds and hydra effects

Population responses to environmental change depend on both the ecological interactions between species and the evolutionary responses of all species. In this study, we explore how evolution in prey, predators, or both species affect the responses of predator populations to a sustained increase in mortality. We use an eco-evolutionary predator-prey model to explore how evolution alters the predator extinction threshold (defined as the minimum mortality rate that prevents population growth at low predator densities) and predator hydra effects (increased predator abundance in response to increased mortality). Our analysis identifies how evolutionary responses of prey and predators individually affect the predator extinction threshold and hydra effects, and how those effects are altered by interactions between the evolutionary responses. Based on our theoretical results, we predict that it is common in natural systems for evolutionary responses in one or both species to allow predators to persist at higher mortality rates than would be possible in the absence of evolution (i.e., evolution increases the predator mortality extinction threshold). We also predict that evolution-driven hydra effects occur in a minority of natural systems, but are not rare. We revisited published eco-evolutionary models and found that evolution causes hydra effects and increases the predator extinction threshold in many studies, but those effects have been overlooked. We discuss the implications of these results for species conservation, predicting population responses to environmental change, and the possibility of evolutionary rescue.

The effects of functional diversity on biomass production, variability, and resilience of ecosystem functions in a tritrophic system

Diverse communities can adjust their trait composition to altered environmental conditions, which may strongly influence their dynamics. Previous studies of trait-based models mainly considered only one or two trophic levels, whereas most natural system are at least tritrophic. Therefore, we investigated how the addition of trait variation to each trophic level influences population and community dynamics in a tritrophic model. Examining the phase relationships between species of adjacent trophic levels informs about the strength of top-down or bottom-up control in non-steady-state situations. Phase relationships within a trophic level highlight compensatory dynamical patterns between functionally different species, which are responsible for dampening the community temporal variability. Furthermore, even without trait variation, our tritrophic model always exhibits regions with two alternative states with either weak or strong nutrient exploitation, and correspondingly low or high biomass production at the top level. However, adding trait variation increased the basin of attraction of the high-production state, and decreased the likelihood of a critical transition from the high- to the low-production state with no apparent early warning signals. Hence, our study shows that trait variation enhances resource use efficiency, production, stability, and resilience of entire food webs.

Environmental status assessment using biological traits analyses and functional diversity indices of benthic ciliate communities

In this study, we tested the hypothesis that the functional diversity of benthic ciliates has high potential to monitor marine ecological status. Therefore, we investigated the spatial and temporal variation of functional diversity of benthic ciliates in the Yangtze Estuary during one year using biological traits analyses and functional diversity indices. Traits and community compositions showed clear spatial and temporal variations. Among a variety of biological traits, feeding type and body size emerged as strongest predictable variables. Functional divergence (FDiv) had an advantage over two other functional diversity indices, as well as over classical diversity measures (i.e. richness, evenness, Shannon-Wiener) to infer environmental status. Significant correlations between biological traits, FDiv and environmental variables (i.e. nutrients, temperature, salinity) suggested that functional diversity of benthic ciliates might be used as a bio-indicator in environmental status assessments. Further mandatory researches need to implement functional diversity of ciliates in routine monitoring programs were discussed.

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.