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The human-caused proliferation of cyanobacteria severely impacts consumers in freshwater ecosystems. Toxicity is often singled out as the sole trait to which consumers can adapt, even though cyanobacteria are not necessarily toxic and the lack of nutritionally critical sterols in cyanobacteria is known to impair consumers. We studied the relative significance of toxicity and dietary sterol deficiency in driving the evolution of grazer resistance to cyanobacteria in a large lake with a well-documented history of eutrophication and oligotrophication. Resurrecting decades-old Daphnia genotypes from the sediment allowed us to show that the evolution and subsequent loss of grazer resistance to cyanobacteria involved an adaptation to changes in both toxicity and dietary sterol availability. The adaptation of Daphnia to changes in cyanobacteria abundance revealed a sterol-mediated gleaner–opportunist trade-off. Genotypes from peak-eutrophic periods showed a higher affinity for dietary sterols at the cost of a lower maximum growth rate, whereas genotypes from more oligotrophic periods showed a lower affinity for dietary sterols in favour of a higher maximum growth rate. Our data corroborate the significance of sterols as limiting nutrients in aquatic food webs and highlight the applicability of the gleaner–opportunist trade-off for reconstructing eco-evolutionary processes.

Using sodium chloride (NaCl) for de-icing roads is known to have severe consequences on freshwater organisms when washed into water bodies. N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine, also known as 6PPD, is an antiozonant mainly found in automobile tire rubber to prevent ozone mediated cracking or wear-out. Especially the ozonated derivate, 6PPD-quinone, which is washed into streams after storm events, has been found to be toxic for coho salmon. Studies on other freshwater organisms could not confirm those findings, pointing towards distinct species-specific differences. Storm events result in greater run-offs from all water-soluble contaminants into freshwater bodies, potentially enhancing the concentrations of both chloride and 6PPD during winter. Here we show that these two contaminants have synergistic negative effects on the population growth of the rotifer Brachionus calyciflorus, a common freshwater herbivore. Hence, while only high concentrations of 6PPD and even higher concentrations of 6PPD-quinone, beyond environmentally relevant concentrations, had lethal effects on rotifers, the addition of NaCl enhanced the sensitivity of the rotifers towards the application of 6PPD so that their negative effects were more pronounced at lower concentrations. Similarly, 6PPD increased the lethal effect of NaCl. Our results support the species-specific toxicity of 6PPD and demonstrate a synergistic effect of the antiozonant on the toxicity of other environmentally relevant stressors, such as road salt contamination.

A large and growing body of theory has demonstrated how the presence of trait variation in prey or predator populations may affect the amplitude and phase of predator-prey cycles. Less attention has been given to so-called intermittent cycles, in which predator-prey oscillations recurrently disappear and re-appear, despite such dynamics being observed in empirical systems and modeling studies. A comprehensive understanding of the conditions under which trait changes may drive intermittent predator-prey dynamics, as well as their potential ecological implications, is therefore missing. Here we provide a first systematic analysis of the eco-evolutionary conditions that may give rise to intermittent predator-prey cycles, investigating 16 models that incorporate different types of trait variation within prey, predators, or both. Our results show that intermittent dynamics often arise through predator-prey coevolution, but only very rarely when only one trophic level can adapt. Additionally, the frequency of intermittent cycles depends on the source of trait variation (genetic variation or phenotypic plasticity) and the genetic architecture (Mendelian or quantitative traits), with intermittency occurring most commonly through Mendelian evolution, and very rarely through phenotypic plasticity. Further analysis identified three necessary conditions for when trait variation can drive intermittent cycles. First, the intrinsic stability of the predator-prey system must depend on the traits of prey, predators, or both. Second, there must be a mechanism causing the recurrent alternation between stable and unstable states, leading to a "trait" cycle superimposed on the population dynamics. Finally, these trait dynamics must be significantly slower than the predator-prey cycles. We show how these conditions explain all the abovementioned patterns. We further show an important unexpected consequence of these necessary conditions: they are most easily met when intraspecific trait variation is at high risk of being lost. As trait diversity is positively associated with ecosystem functioning, this can have potentially severe negative consequences. This novel result highlights the importance of identifying and understanding intermittent cycles in theoretical studies and natural systems. The new approach for detecting and quantifying intermittency we develop here will be instrumental in enabling future study.

Contemporary theory of predator coexistence through relative non-linearity in their functional responses strongly relies on the Rosenzweig and MacArthur (1963) equations in which the (autotrophic) prey exhibits logistic growth in the absence of the predators. This implies that the prey is limited by a resource such as light or space, which availability is independent of the predators. This assumption does not hold under nutrient limitation where both prey and predators bind resources such as nitrogen and phosphorus in their biomass. Furthermore, the prey’s resource uptake rate is assumed to be linear and the predator-prey system is considered to be closed. All these assumptions are unrealistic for many natural systems. Here, we show that nutrient retention in predator biomass strongly hampers the coexistence of two predators on one prey because it stabilizes the dynamics. In contrast, a non-linear resource uptake rate of the prey slightly promotes predator coexistence. Our study highlights that predator coexistence does depend not only on differences in the curvature of their functional responses but also on the type of resource constraining the growth of their prey. This has far-reaching consequences for the relative importance of fluctuation-dependent and fluctuation-independent mechanisms of species coexistence in natural systems where autotrophs experience light or nutrient limitation.

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.

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., Intraspecific variation in the traits “selectivity” and “maximum ingestion rate” for their prey significantly affected the competition between two freshwater ciliate species. Exclusion of either one of the ciliates or long‐term persistence depended on which of the competitors benefited more from feeding on a less abundant algal resource of high food quality, on severe nutrient limitation that affected the food quality of the dominant algal resource, and on the ability of one competitor to use bacteria as an alternative food source. Hence, trait variation at both trophic levels codetermined the population dynamics and the outcome of species competition.

Self-organized formation of spatial patterns is known from a variety of different ecosystems, yet little is known how these patterns affect functional diversity of local and regional 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 rate and defense against a heterotroph. On a single patch, stabilizing selection always promotes the dominance of a single autotroph species. Two alternative community states, with either defended or undefended species, are possible. In a metacommunity context, dispersal can destabilize these states, and complex spatio-temporal patterns emerge. This creates varying selection pressures on the local autotroph communities, which feed back on the trait dynamics. Local functional diversity increases ten-fold compared to a situation without self-organized pattern formation, thereby maintaining the adaptive potential of communities in an environment threatened by fragmentation and global change.

Ecological communities are complex adaptive systems that exhibit remarkable feedbacks between their biomass and trait dynamics. Trait-based aggregate models cope with this complexity by focusing on the temporal development of the community’s aggregate properties such as its total biomass, mean trait and trait variance. They are based on particular assumptions about the shape of the underlying trait distribution, which is commonly assumed to be normal. However, ecologically important traits are usually restricted to a finite range, and empirical trait distributions are often skewed or multimodal. As a result, normal distribution-based aggregate models may fail to adequately represent the biomass and trait dynamics of natural communities. We resolve this mismatch by developing a new moment closure approach assuming the trait values to be beta-distributed. We show that the beta distribution captures important shape properties of both observed and simulated trait distributions, which cannot be captured by a Gaussian. We further demonstrate that a beta distribution-based moment closure can strongly enhance the reliability of trait-based aggregate models. We compare the biomass, mean trait and variance dynamics of a full trait distribution (FD) model to the ones of beta (BA) and normal (NA) distribution-based aggregate models, under different selection regimes. This way, we demonstrate under which general conditions (stabilizing, fluctuating or disruptive selection) different aggregate models are reliable tools. All three models predicted very similar biomass and trait dynamics under stabilizing selection yielding unimodal trait distributions with small standing trait variation. We also obtained an almost perfect match between the results of the FD and BA models under fluctuating selection, promoting skewed trait distributions and ongoing oscillations in the biomass and trait dynamics. In contrast, the NA model showed unrealistic trait dynamics and exhibited different alternative stable states, and thus a high sensitivity to initial conditions under fluctuating selection. Under disruptive selection, both aggregate models failed to reproduce the results of the FD model with the mean trait values remaining within their ecologically feasible ranges in the BA model but not in the NA model. Overall, a beta distribution-based moment closure strongly improved the realism of trait-based aggregate models.

The shape of trait distributions may inform about the selective forces that structure ecological communities. Here, we present a new moment-based approach to classify the shape of observed biomass-weighted trait distributions into normal, peaked, skewed, or bimodal that facilitates spatio-temporal and cross-system comparisons. Our observed phytoplankton trait distributions exhibited substantial variance and were mostly skewed or bimodal rather than normal. Additionally, mean, variance, skewness und kurtosis were strongly correlated. This is in conflict with trait-based aggregate models that often assume normally distributed trait values and small variances. Given these discrepancies between our data and general model assumptions we used the observed trait distributions to test how well different aggregate models with first- or second-order approximations and different types of moment closure predict the biomass, mean trait, and trait variance dynamics using weakly or moderately nonlinear fitness functions. For weakly non-linear fitness functions aggregate models with a second-order approximation and a data-based moment closure that relied on the observed correlations between skewness and mean, and kurtosis and variance predicted biomass and often also mean trait changes fairly well and better than models with first-order approximations or a normal-based moment closure. In contrast, none of the models reflected the changes of the trait variances reliably. Aggregate model performance was often also poor for moderately nonlinear fitness functions. This questions a general applicability of the normal-based approach, in particular for predicting variance dynamics determining the speed of trait changes and maintenance of biodiversity. We evaluate in detail how and why better approximations can be obtained.

In their recent contribution, Wetzel et al. [Wetzel et al. (2016) Variability in plant nutrients reduces insect herbivore performance. Nature 539: 425-427] predict that variance in the plant nutrient level reduces herbivore performance via the nonlinear averaging effect (named Jensen’s effect by the authors) while variance in the defense level does not. We argue that the study likely underestimates the potential of plant defenses’ variance to cause Jensen’s effects for two reasons. First, this conclusion is based on the finding that the average Jensen’s effect of various defense traits on various herbivores is zero which does not imply that the Jensen’s effect of specific defense traits on specific herbivores is null, just that the effects balance each other globally. Second, the study neglects the nonlinearity effects that may arise from the synergy between nutritive and defense traits or between co-occurring defenses on herbivore performance. Covariance between interacting plant defense traits, or between plant nutritive and defense traits, can affect performance differently than would nutritive or single plant defense variance alone. Overlooking the interactive effects of plant traits and the traits’ covariance could impair the assessment of the true role of plant trait variability on herbivore populations in natural settings.

Contemporary theory of predator coexistence through relative non-linearity in their functional responses strongly relies on the Rosenzweig-MacArthur equations (1963) in which the (autotrophic) prey exhibits logistic growth in the absence of the predators. This implies that the prey is limited by a resource which availability is independent of the predators. This assumption does not hold under nutrient limitation where both prey and predators bind resources such as nitrogen or phosphorus in their biomass. Furthermore, the prey’s resource uptake-rate is assumed to be linear and the predator-prey system is considered to be closed. All these assumptions are unrealistic for many natural systems. Here, we show that predator coexistence on a single prey is strongly hampered when the prey and predators indirectly compete for the limiting resource in a flow-through system. In contrast, a non-linear resource uptake rate of the prey slightly promotes predator coexistence. Our study highlights that predator coexistence does not only depend on differences in the curvature of their functional responses but also on the type of resource constraining the growth of their prey. This has far-reaching consequences for the relative importance of fluctuation-dependent and -independent mechanisms of species coexistence in natural systems where autotrophs experience light or nutrient limitation.

Inducible defences against predation are widespread in the natural world, allowing prey to economise on the costs of defence when predation risk varies over time or is spatially structured. Through interspecific interactions, inducible defences have major impacts on ecological dynamics, particularly predator-prey stability and phase lag. Researchers have developed multiple distinct approaches, each reflecting assumptions appropriate for particular ecological communities. Yet, the impact of inducible defences on ecological dynamics can be highly sensitive to the modelling approach used, making the choice of model a critical decision that affects interpretation of the dynamical consequences of inducible defences. Here, we review three existing approaches to modelling inducible defences: Switching Function, Fitness Gradient and Optimal Trait. We assess when and how the dynamical outcomes of these approaches differ from each other, from classic predator-prey dynamics and from commonly observed eco-evolutionary dynamics with evolving, but non-inducible, prey defences. We point out that the Switching Function models tend to stabilise population dynamics, and the Fitness Gradient models should be carefully used, as the difference with evolutionary dynamics is important. We discuss advantages of each approach for applications to ecological systems with particular features, with the goal of providing guidelines for future researchers to build on.

Salinization of freshwater ecosystems is a growing hazard for organisms and ecosystem functioning worldwide. In northern latitudes, road salt that is being transported into water bodies can cause year-round increases in lake salinity levels. Exploring the environmental factors driving the susceptibility of freshwater zooplankton to road salt is crucial for assessing the impact of salinization on food web processes. We studied the role of essential lipids, i.e., sterols and long-chain polyunsaturated fatty acids (PUFAs), in mediating salt tolerance of the freshwater keystone herbivore Daphnia. Sterols and PUFAs are involved in regulating ion permeability of biological membranes and thus we hypothesized that the susceptibility to salt is affected by the dietary sterol and PUFA supply. Life history experiments revealed opposing effects of sterol and PUFA supplementation on salt tolerance, i.e., tolerance increased upon sterol supplementation but decreased upon PUFA supplementation, which is consistent with their proposed impact on membrane permeability. Our results suggest that the susceptibility of freshwater zooplankton to salinization strongly depends on the dietary lipid supply and thus the phytoplankton community composition. Hence, trophic state related differences in the phytoplankton community composition need to be considered when assessing the consequences of salinization for freshwater ecosystem functioning.

Made available in DSpace on 2018-11-26T17:12:14Z (GMT). No. of bitstreams: 0 Previous issue date: 2016-12-01 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) German Research Foundation (DFG) Functionally diverse communities can adjust their species composition to altered environmental conditions, which may influence food web dynamics. Trait-based aggregate models cope with this complexity by ignoring details about species identities and focusing on their functional characteristics (traits). They describe the temporal changes of the aggregate properties of entire communities, including their total biomasses, mean trait values, and trait variances. The applicability of aggregate models depends on the validity of their underlying assumptions that trait distributions are normal and exhibit small variances. We investigated to what extent this can be expected to work by comparing an innovative model that accounts for the full trait distributions of predator and prey communities to a corresponding aggregate model. We used a food web structure with well-established trade-offs among traits promoting mutual adjustments between prey edibility and predator selectivity in response to selection. We altered the shape of the trade-offs to compare the outcome of the two models under different selection regimes, leading to trait distributions increasingly deviating from normality. Their biomass and trait dynamics agreed very well for stabilizing selection and reasonably well for directional selection, under which different trait values are favored at different times. However, for disruptive selection, the results of the aggregate model strongly deviated from the full trait distribution model that showed bimodal trait distributions with large variances. Hence, the outcome of aggregate models is reliable under ideal conditions but has to be questioned when confronted with more complex selection regimes and trait distributions, which are commonly observed in nature. Univ Estadual Paulista, Inst Fis Teor, Sao Paulo, Brazil Univ Potsdam, Inst Biochem & Biol, Dept Ecol & Ecosyst Modeling, Potsdam, Germany Univ Estadual Paulista, Inst Fis Teor, Sao Paulo, Brazil FAPESP: 2012/05949-6 German Research Foundation (DFG): GA 401/19-1 German Research Foundation (DFG): 26-1

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 degree 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, variability, and resilience of entire food webs.

Introduction Although the ubiquitous biodiversity-related flexibility of ecological systems is qualitatively well established, most empirical and theoretical studies regard ecological systems so far as units with rigid, predefined properties. The reason for this static approach is that incorporating the tremendous diversity and flexibility of natural systems into empirical and theoretical studies has been extremely challenging in terms of developing consistent mathematical frameworks and designing appropriate experiments. This approach has also been necessary owing to the lack of empirical data on the ability of species to change properties over time. A recent approach to solve this problem is to move from a species- to a trait-based perspective. This is not just a change in terminology but in concept, providing a mechanistic basis for biodiversity–ecosystem function relationships and improving our potential to identify general rules in community ecology (McGill et al., 2006; Savage et al., 2007; Hillebrand and Matthiessen, 2009). Functional traits are used to link species to their function in the ecosystem. They are well defined, measurable properties of individuals (e.g., edibility or diet selectivity) affecting their performance and responses to environmental changes and hence population and community dynamics as well as trophic interactions. The frequency distribution of functional traits (Figure 10.1a) enables a quantification of functional diversity. Large variation in trait values (e.g., a full range from highly edible, fast growing to almost inedible, slow growing species) implies a high functional diversity and vice versa. This trait distribution may be described by its shape and central tendency (Figure 10.1b) and may change in response to altered abiotic (e.g., temperature) and biotic conditions (e.g., predator density) and thus characterize the milieu with which individual organisms interact (McGill et al., 2006) (Figure 10.1c). Scientific Background Maintaining the different kinds of ecosystem services in a way that optimizes human well-being and economy is one of the most urgent tasks of our century, which challenges policy-makers as well as scientists. The frequency and intensity of land use, climate change, and other anthropogenically induced environmental disturbances are accelerating biodiversity declines worldwide. The negative impact of these processes on ecological systems (e.g., individuals, populations, communities, and food webs) may amplify each other: environmental changes can accelerate biodiversity loss and a reduced biodiversity may increase the sensitivity of ecological systems to environmental changes. © Cambridge University Press 2018.

The concept that diversity promotes reliability of ecosystem function depends on the pattern that community-level biomass shows lower temporal variability than species-level biomasses. However, this pattern is not universal, as it relies on compensatory or independent species dynamics. When in contrast within--trophic level synchronization occurs, variability of community biomass will approach population-level variability. Current knowledge fails to integrate how species richness, functional distance between species, and the relative importance of predation and competition combine to drive synchronization at different trophic levels. Here we clarify these mechanisms. Intense competition promotes compensatory dynamics in prey, but predators may at the same time increasingly synchronize, under increasing species richness and functional similarity. In contrast, predators and prey both show perfect synchronization under strong top-down control, which is promoted by a combination of low functional distance and high net growth potential of predators. Under such conditions, community-level biomass variability peaks, with major negative consequences for reliability of ecosystem function.

Species can adjust their traits in response to selection which may strongly influence species coexistence. Nevertheless, current theory mainly assumes distinct and time‐invariant trait values. We examined the combined effects of the range and the speed of trait adaptation on species coexistence using an innovative multispecies predator–prey model. It allows for temporal trait changes of all predator and prey species and thus simultaneous coadaptation within and among trophic levels. We show that very small or slow trait adaptation did not facilitate coexistence because the stabilizing niche differences were not sufficient to offset the fitness differences. In contrast, sufficiently large and fast trait adaptation jointly promoted stable or neutrally stable species coexistence. Continuous trait adjustments in response to selection enabled a temporally variable convergence and divergence of species traits; that is, species became temporally more similar (neutral theory) or dissimilar (niche theory) depending on the selection pressure, resulting over time in a balance between niche differences stabilizing coexistence and fitness differences promoting competitive exclusion. Furthermore, coadaptation allowed prey and predator species to cluster into different functional groups. This equalized the fitness of similar species while maintaining sufficient niche differences among functionally different species delaying or preventing competitive exclusion. In contrast to previous studies, the emergent feedback between biomass and trait dynamics enabled supersaturated coexistence for a broad range of potential trait adaptation and parameters. We conclude that accounting for trait adaptation may explain stable and supersaturated species coexistence for a broad range of environmental conditions in natural systems when the absence of such adaptive changes would preclude it. Small trait changes, coincident with those that may occur within many natural populations, greatly enlarged the number of coexisting species.

We investigated the effects of warming on a natural phytoplankton community from the Baltic Sea, based on six mesocosm experiments conducted 2005–2009. We focused on differences in the dynamics of three phytoplankton size groups which are grazed to a variable extent by different zooplankton groups. While small-sized algae were mostly grazer-controlled, light and nutrient availability largely determined the growth of medium- and large-sized algae. Thus, the latter groups dominated at increased light levels. Warming increased mesozooplankton grazing on medium-sized algae, reducing their biomass. The biomass of small-sized algae was not affected by temperature, probably due to an interplay between indirect effects spreading through the food web. Thus, under the higher temperature and lower light levels anticipated for the next decades in the southern Baltic Sea, a higher share of smaller phytoplankton is expected. We conclude that considering the size structure of the phytoplankton community strongly improves the reliability of projections of climate change effects.