Resource limitation determines realized thermal performance of consumers in trophodynamic models.

Recent work has demonstrated that changes in resource availability can alter a consumer's thermal performance curve (TPC). When resources decline, the optimal temperature and breadth of thermal performance also decline, leading to a greater risk of warming than predicted by static TPCs. We investigate the effect of temperature on coupled consumer-resource dynamics, focusing on the potential for changes in the consumer TPC to alter extinction risk. Coupling consumer and resource dynamics generally reduces the potential for resource decline to exacerbate the effects of warming via changes to the TPC due to a reduction in top-down control when consumers near the limits of their thermal performance curve. However, if resources are more sensitive to warming, consumer TPCs can be reshaped by declining resources, leading to increased extinction risk. Our work elucidates the role of top-down and bottom-up regulation in determining the extent to which changes in resource density alter consumer TPCs.

Variation cascades: resource pulses and top-down effects across time scales.

Top-down and bottom-up theories of trophic control have been fundamental to our understanding of community dynamics and structure. However, most ecological theories have focused on equilibrium dynamics and do not provide predictions for communities' responses in temporally fluctuating environments. By deriving the frequency response of populations in different trophic communities, we extend the top-down and bottom-up theories of ecology to include how temporal fluctuations in potential primary productivity percolate up the food chain and are re-expressed as population variability. Moreover, by switching from a time-based representation into the frequency domain, we provide a unified method to compare how the time scale of perturbations determines communities' responses. At low frequencies, primary producers and secondary consumers have the highest temporal variability, while the primary consumers are relatively stable. Similar to the Exploitation Ecosystem Hypothesis, top-down effects drive this alternating pattern of variability. We define the top-down effect of consumers on the variability of lower trophic levels as a variation cascade. However, at intermediate frequencies, variation cascades can amplify temporal variation up the food chain. At high frequencies, variation cascades weaken, and fluctuations are attenuated up the food chain. In summary, we provide a novel theory for how communities will respond to fluctuations in productivity, and we show that indirect species interactions play a crucial role in determining community dynamics across the frequency spectrum.

Opportunities for behavioral rescue under rapid environmental change.

Laboratory measurements of physiological and demographic tolerances are important in understanding the impact of climate change on species diversity; however, it has been recognized that forecasts based solely on these laboratory estimates overestimate risk by omitting the capacity for species to utilize microclimatic variation via behavioral adjustments in activity patterns or habitat choice. The complex, and often context-dependent nature, of microclimate utilization has been an impediment to the advancement of general predictive models. Here, we overcome this impediment and estimate the potential impact of warming on the fitness of ectotherms using a benefit/cost trade-off derived from the simple and broadly documented thermal performance curve and a generalized cost function. Our framework reveals that, for certain environments, the cost of behavioral thermoregulation can be reduced as warming occurs, enabling behavioral buffering (e.g., the capacity for behavior to ameliorate detrimental impacts) and "behavioral rescue" from extinction in extreme cases. By applying our framework to operative temperature and physiological data collected at an extremely fine spatial scale in an African lizard, we show that new behavioral opportunities may emerge. Finally, we explore large-scale geographic differences in the impact of behavior on climate-impact projections using a global dataset of 38 insect species. These multiple lines of inference indicate that understanding the existing relationship between thermal characteristics (e.g., spatial configuration, spatial heterogeneity, and modal temperature) is essential for improving estimates of extinction risk.

Managing the emergence of pathogen resistance via spatially targeted antimicrobial use.

From agriculture to public health to civil engineering, managing antimicrobial resistance presents a considerable challenge. The dynamics underlying resistance evolution reflect inherently spatial processes. Resistant pathogen strains increase in frequency when a strain that emerges in one locale can spread and replace pathogen subpopulations formerly sensitive to the antimicrobial agent. Moreover, the strength of selection for antimicrobial resistance is in part governed by the extent of antimicrobial use. Thus, altering how antimicrobials are used across a landscape can potentially shift the spatial context governing the dynamics of antimicrobial resistance and provide a potent management tool. Here, we model how the efficacy of adjusting antimicrobial use over space to manage antimicrobial resistance is mediated by competition among pathogen strains and the topology of pathogen metapopulations. For several pathogen migration scenarios, we derive critical thresholds for the spatial extent of antimicrobial use below which resistance cannot emerge, and relate these thresholds to (a) the ability to eradicate antimicrobial-sensitive pathogens locally and (b) the strength of the trade-off between resistance ability and competitive performance where antimicrobial use is absent. We find that in metapopulations where patches differ in connectedness, constraining antimicrobial use across space to mitigate resistance evolution only works if the migration of the resistant pathogen is modest; yet, this situation is reversed if the resistant strain has a high colonization rate, with variably connected metapopulations exhibiting less sensitivity to reducing antimicrobial use across space. Furthermore, when pathogens are alternately exposed to sites with and without the antimicrobial, bottlenecking resistant strains through sites without an antimicrobial is only likely to be effective under a strong competition-resistance trade-off. We therefore identify life-history constraints that are likely to suggest which pathogens can most effectively be controlled by a spatially targeted antimicrobial regime. We discuss implications of our results for managing and thinking about antimicrobial resistance evolution in spatially heterogeneous contexts.

Temporally Autocorrelated Environmental Fluctuations Inhibit the Evolution of Stress Tolerance.

As global environmental conditions continue to change at an unprecedented rate, many species will experience increases in natural and anthropogenic stress. Generally speaking, selection is expected to favor adaptations that reduce the negative impact of environmental stress (i.e., stress tolerance). However, natural environmental variables typically fluctuate, exhibiting various degrees of temporal autocorrelation, known as environmental colors, which may complicate evolutionary responses to stress. Here we combine experiments and theory to show that temporal environmental autocorrelation can determine long-term evolutionary responses to stress without affecting the total amount of stress experienced over time. Experimental evolution of RNA virus lineages in differing environmental autocorrelation treatments agreed closely with predictions from our theoretical models that stress tolerance is favored in less autocorrelated (whiter) environments but disfavored in more autocorrelated (redder) environments. This is explained by an interaction between environmental autocorrelation and a phenotypic trade-off between stress tolerance and reproductive ability. The degree to which environmental autocorrelation influences evolutionary trajectories depends on the shape of this trade-off as well as the relative level of tolerance exhibited by novel mutants. These results suggest that long-term evolutionary dynamics depend not only on the overall strength of selection but also on the way that selection is distributed over time.

Gradual plasticity alters population dynamics in variable environments: thermal acclimation in the green alga Chlamydomonas reinhartdii.

Environmental variability is ubiquitous, but its effects on populations are not fully understood or predictable. Recent attention has focused on how rapid evolution can impact ecological dynamics via adaptive trait change. However, the impact of trait change arising from plastic responses has received less attention, and is often assumed to optimize performance and unfold on a separate, faster timescale than ecological dynamics. Challenging these assumptions, we propose that gradual plasticity is important for ecological dynamics, and present a study of the plastic responses of the freshwater green algae Chlamydomonas reinhardtii as it acclimates to temperature changes. First, we show that C. reinhardtii's gradual acclimation responses can both enhance and suppress its performance after a perturbation, depending on its prior thermal history. Second, we demonstrate that where conventional approaches fail to predict the population dynamics of C. reinhardtii exposed to temperature fluctuations, a new model of gradual acclimation succeeds. Finally, using high-resolution data, we show that phytoplankton in lake ecosystems can experience thermal variation sufficient to make acclimation relevant. These results challenge prevailing assumptions about plasticity's interactions with ecological dynamics. Amidst the current emphasis on rapid evolution, it is critical that we also develop predictive methods accounting for plasticity.

Thermal variability alters the impact of climate warming on consumer-resource systems.

Thermal variation through space and time are prominent features of ecosystems that influence processes at multiple levels of biological organization. Yet, it remains unclear how populations embedded within biological communities will respond to climate warming in thermally variable environments, particularly as climate change alters existing patterns of thermal spatial and temporal variability. As environmental temperatures increase above historical ranges, organisms may increasingly rely on extreme habitats to effectively thermoregulate. Such locations desirable in their thermal attributes (e.g., thermal refugia) are often suboptimal for resource acquisition (e.g., underground tunnels). Thus, via the expected increase in both mean temperatures and diel thermal variation, climate warming may heighten the trade-off for consumers between behaviors maximizing thermal performance and those maximizing resource acquisition. Here, we integrate behavioral, physiological, and trophic ecology to provide a general framework for understanding how temporal thermal variation, mediated by access to a thermal refugium, alters the response of consumer-resource systems to warming. We use this framework to predict how temporal variation and access to thermal refugia affect the persistence of consumers and resources during climate warming, how the quality of thermal refugia impact consumer-resource systems, and how consumer-resource systems with fast vs. slow ecological dynamics respond to warming. Our results show that the spatial thermal variability provided by refugia can elevate consumer biomass at warmer temperatures despite reducing the fraction of time consumers spend foraging, that temporal variability detrimentally impacts consumers at high environmental temperatures, and that consumer-resource systems with fast ecological dynamics are most vulnerable to climate warming. Thus, incorporating both estimates of thermal variability and species interactions may be necessary to accurately predict how populations respond to warming.

Trait adaptation promotes species coexistence in diverse predator and prey communities.

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.

Life in the Frequency Domain: the Biological Impacts of Changes in Climate Variability at Multiple Time Scales.

Over the last few decades, biologists have made substantial progress in understanding relationships between changing climates and organism performance. Much of this work has focused on temperature because it is the best kept of climatic records, in many locations it is predicted to keep rising into the future, and it has profound effects on the physiology, performance, and ecology of organisms, especially ectothermic organisms which make up the vast majority of life on Earth. Nevertheless, much of the existing literature on temperature-organism interactions relies on mean temperatures. In reality, most organisms do not directly experience mean temperatures; rather, they experience variation in temperature over many time scales, from seconds to years. We propose to shift the focus more directly on patterns of temperature variation, rather than on means per se, and present a framework both for analyzing temporal patterns of temperature variation and for incorporating those patterns into predictions about organismal biology. In particular, we advocate using the Fourier transform to decompose temperature time series into their component sinusoids, thus allowing transformations between the time and frequency domains. This approach provides (1) standardized ways of visualizing the contributions that different frequencies make to total temporal variation; (2) the ability to assess how patterns of temperature variation have changed over the past half century and may change into the future; and (3) clear approaches to manipulating temporal time series to ask "what if" questions about the potential effects of future climates. We first summarize global patterns of change in temperature variation over the past 40 years; we find meaningful changes in variation at the half day to yearly times scales. We then demonstrate the utility of the Fourier framework by exploring how power added to different frequencies alters the overall incidence of long-term waves of high and low temperatures, and find that power added to the lowest frequencies greatly increases the probability of long-term heat and cold waves. Finally, we review what is known about the time scales over which organismal thermal performance curves change in response to variation in the thermal environment. We conclude that integrating information characterizing both the frequency spectra of temperature time series and the time scales of resulting physiological change offers a powerful new avenue for relating climate, and climate change, to the future performance of ectothermic organisms.

The body size dependence of trophic cascades.

Trophic cascades are indirect positive effects of predators on resources via control of intermediate consumers. Larger-bodied predators appear to induce stronger trophic cascades (a greater rebound of resource density toward carrying capacity), but how this happens is unknown because we lack a clear depiction of how the strength of trophic cascades is determined. Using consumer resource models, we first show that the strength of a trophic cascade has an upper limit set by the interaction strength between the basal trophic group and its consumer and that this limit is approached as the interaction strength between the consumer and its predator increases. We then express the strength of a trophic cascade explicitly in terms of predator body size and use two independent parameter sets to calculate how the strength of a trophic cascade depends on predator size. Both parameter sets predict a positive effect of predator size on the strength of a trophic cascade, driven mostly by the body size dependence of the interaction strength between the first two trophic levels. Our results support previous empirical findings and suggest that the loss of larger predators will have greater consequences on trophic control and biomass structure in food webs than the loss of smaller predators.

Synchronous dynamics of zooplankton competitors prevail in temperate lake ecosystems.

Although competing species are expected to exhibit compensatory dynamics (negative temporal covariation), empirical work has demonstrated that competitive communities often exhibit synchronous dynamics (positive temporal covariation). This has led to the suggestion that environmental forcing dominates species dynamics; however, synchronous and compensatory dynamics may appear at different length scales and/or at different times, making it challenging to identify their relative importance. We compiled 58 long-term datasets of zooplankton abundance in north-temperate and sub-tropical lakes and used wavelet analysis to quantify general patterns in the times and scales at which synchronous/compensatory dynamics dominated zooplankton communities in different regions and across the entire dataset. Synchronous dynamics were far more prevalent at all scales and times and were ubiquitous at the annual scale. Although we found compensatory dynamics in approximately 14% of all combinations of time period/scale/lake, there were no consistent scales or time periods during which compensatory dynamics were apparent across different regions. Our results suggest that the processes driving compensatory dynamics may be local in their extent, while those generating synchronous dynamics operate at much larger scales. This highlights an important gap in our understanding of the interaction between environmental and biotic forces that structure communities.

A bioenergetic framework for the temperature dependence of trophic interactions.

Changing temperature can substantially shift ecological communities by altering the strength and stability of trophic interactions. Because many ecological rates are constrained by temperature, new approaches are required to understand how simultaneous changes in multiple rates alter the relative performance of species and their trophic interactions. We develop an energetic approach to identify the relationship between biomass fluxes and standing biomass across trophic levels. Our approach links ecological rates and trophic dynamics to measure temperature-dependent changes to the strength of trophic interactions and determine how these changes alter food web stability. It accomplishes this by using biomass as a common energetic currency and isolating three temperature-dependent processes that are common to all consumer-resource interactions: biomass accumulation of the resource, resource consumption and consumer mortality. Using this framework, we clarify when and how temperature alters consumer to resource biomass ratios, equilibrium resilience, consumer variability, extinction risk and transient vs. equilibrium dynamics. Finally, we characterise key asymmetries in species responses to temperature that produce these distinct dynamic behaviours and identify when they are likely to emerge. Overall, our framework provides a mechanistic and more unified understanding of the temperature dependence of trophic dynamics in terms of ecological rates, biomass ratios and stability.

Increased temperature variation poses a greater risk to species than climate warming.

Increases in the frequency, severity and duration of temperature extremes are anticipated in the near future. Although recent work suggests that changes in temperature variation will have disproportionately greater effects on species than changes to the mean, much of climate change research in ecology has focused on the impacts of mean temperature change. Here, we couple fine-grained climate projections (2050-2059) to thermal performance data from 38 ectothermic invertebrate species and contrast projections with those of a simple model. We show that projections based on mean temperature change alone differ substantially from those incorporating changes to the variation, and to the mean and variation in concert. Although most species show increases in performance at greater mean temperatures, the effect of mean and variance change together yields a range of responses, with temperate species at greatest risk of performance declines. Our work highlights the importance of using fine-grained temporal data to incorporate the full extent of temperature variation when assessing and projecting performance.

Competition and the density dependence of metabolic rates.

Although mass and temperature are strong predictors of metabolic rates, there is considerable unexplained variation in metabolic rates both within and across species after body size and temperature are taken into account. Some of this variation may be due to changes in the rate of food intake with population density, as metabolism depends on the throughput of food to fuel biochemical reactions. Using data collected from the literature, we show that individual metabolic rates are negatively correlated with population density for a wide range of organisms including primary producers and consumers. Using new data for the zooplankter Daphnia ambigua, we also find genotypic variation in the relationship between metabolic rate and population density. The relationship between metabolic rate and population density generally follows a power law scaling, and within a population, density-correlated variation in metabolism can span two orders of magnitude. We suggest that density-dependent metabolic rates arise via competitive effects on foraging rates (both exploitation and interference competition), combined with an activity response to accommodate the resource constraint induced by competition. Standard ecological models predict the kind of density-dependent foraging patterns that could give rise to density-dependent metabolic rates, but this has generally not been investigated. Our results indicate that after body mass and temperature, population density represents an important third axis that may account for a large amount of unexplained variance in metabolic rates within and among species. The effect of population density on metabolism has implications for the scaling of metabolic rates from individuals to populations and the relative performance of species and genotypes and therefore also for community assembly and evolution.

Nonlinear effect of dispersal rate on spatial synchrony of predator-prey cycles.

Spatially-separated populations often exhibit positively correlated fluctuations in abundance and other population variables, a phenomenon known as spatial synchrony. Generation and maintenance of synchrony requires forces that rapidly restore synchrony in the face of desynchronizing forces such as demographic and environmental stochasticity. One such force is dispersal, which couples local populations together, thereby synchronizing them. Theory predicts that average spatial synchrony can be a nonlinear function of dispersal rate, but the form of the dispersal rate-synchrony relationship has never been quantified for any system. Theory also predicts that in the presence of demographic and environmental stochasticity, realized levels of synchrony can exhibit high variability around the average, so that ecologically-identical metapopulations might exhibit very different levels of synchrony. We quantified the dispersal rate-synchrony relationship using a model system of protist predator-prey cycles in pairs of laboratory microcosms linked by different rates of dispersal. Paired predator-prey cycles initially were anti-synchronous, and were subject to demographic stochasticity and spatially-uncorrelated temperature fluctuations, challenging the ability of dispersal to rapidly synchronize them. Mean synchrony of prey cycles was a nonlinear, saturating function of dispersal rate. Even extremely low rates of dispersal (<0.4% per prey generation) were capable of rapidly bringing initially anti-synchronous cycles into synchrony. Consistent with theory, ecologically-identical replicates exhibited very different levels of prey synchrony, especially at low to intermediate dispersal rates. Our results suggest that even the very low rates of dispersal observed in many natural systems are sufficient to generate and maintain synchrony of cyclic population dynamics, at least when environments are not too spatially heterogeneous.

Consistent scaling of persistence time in metapopulations.

Recent theory and experimental work in metapopulations and metacommunities demonstrates that long-term persistence is maximized when the rate at which individuals disperse among patches within the system is intermediate; if too low, local extinctions are more frequent than recolonizations, increasing the chance of regional-scale extinctions, and if too high, dynamics exhibit region-wide synchrony, and local extinctions occur in near unison across the region. Although common, little is known about how the size and topology of the metapopulation (metacommunity) affect this bell-shaped relationship between dispersal rate and regional persistence time. Using a suite of mathematical models, we examined the effects of dispersal, patch number, and topology on the regional persistence time when local populations are subject to demographic stochasticity. We found that the form of the relationship between regional persistence time and the number of patches is consistent across all models studied; however, the form of the relationship is distinctly different among low, intermediate, and high dispersal rates. Under low and intermediate dispersal rates, regional persistence times increase logarithmically and exponentially (respectively) with increasing numbers of patches, whereas under high dispersal, the form of the relationship depends on local dynamics. Furthermore, we demonstrate that the forms of these relationships, which give rise to the bell-shaped relationship between dispersal rate and persistence time, are a product of recolonization and the region-wide synchronization (or lack thereof) of population dynamics. Identifying such metapopulation attributes that impact extinction risk is of utmost importance for managing and conserving the earth's evermore fragmented populations.

Size-density scaling in protists and the links between consumer-resource interaction parameters.

Recent work indicates that the interaction between body-size-dependent demographic processes can generate macroecological patterns such as the scaling of population density with body size. In this study, we evaluate this possibility for grazing protists and also test whether demographic parameters in these models are correlated after controlling for body size. We compiled data on the body-size dependence of consumer-resource interactions and population density for heterotrophic protists grazing algae in laboratory studies. We then used nested dynamic models to predict both the height and slope of the scaling relationship between population density and body size for these protists. We also controlled for consumer size and assessed links between model parameters. Finally, we used the models and the parameter estimates to assess the individual- and population-level dependence of resource use on body-size and prey-size selection. The predicted size-density scaling for all models matched closely to the observed scaling, and the simplest model was sufficient to predict the pattern. Variation around the mean size-density scaling relationship may be generated by variation in prey productivity and area of capture, but residuals are relatively insensitive to variation in prey size selection. After controlling for body size, many consumer-resource interaction parameters were correlated, and a positive correlation between residual prey size selection and conversion efficiency neutralizes the apparent fitness advantage of taking large prey. Our results indicate that widespread community-level patterns can be explained with simple population models that apply consistently across a range of sizes. They also indicate that the parameter space governing the dynamics and the steady states in these systems is structured such that some parts of the parameter space are unlikely to represent real systems. Finally, predator-prey size ratios represent a kind of conundrum, because they are widely observed but apparently have little influence on population size and fitness, at least at this level of organization.

A dynamic explanation of size-density scaling in carnivores.

Population abundance is negatively related to body size for many types of organisms. Despite the ubiquity of size-density scaling relationships, we lack a general understanding of the underlying mechanisms. Although dynamic models suggest that it is possible to predict the intercept and slope of the scaling relationship from prior observations, this has never been empirically attempted. Here we fully parameterize a set of consumer-resource models for mammalian carnivores and successfully predict the size-density scaling relationship for this group without the use of free parameters. All models produced similar predictions, but comparison of nested models indicated that the primary factors generating size-density scaling in mammalian carnivores are prey productivity, predator-prey size ratios, and consumer area of capture.

Coexistence via resource partitioning fails to generate an increase in community function.

Classic ecological theory suggests that resource partitioning facilitates the coexistence of species by reducing inter-specific competition. A byproduct of this process is an increase in overall community function, because a greater spectrum of resources can be used. In contrast, coexistence facilitated by neutral mechanisms is not expected to increase function. We studied coexistence in laboratory microcosms of the bactivorous ciliates Paramecium aurelia and Colpidium striatum to understand the relationship between function and coexistence mechanism. We quantified population and community-level function (biomass and oxygen consumption), competitive interactions, and resource partitioning. The two ciliates partitioned their bacterial resource along a size axis, with the larger ciliate consuming larger bacteria than the smaller ciliate. Despite this, there was no gain in function at the community level for either biomass or oxygen consumption, and competitive effects were symmetrical within and between species. Because other potential coexistence mechanisms can be ruled out, it is likely that inter-specific interference competition diminished the expected gain in function generated by resource partitioning, leading to a system that appeared competitively neutral even when structured by niche partitioning. We also analyzed several previous studies where two species of protists coexisted and found that the two-species communities showed a broad range of biomass levels relative to the single-species states.

Seasonal variations alter the impact of functional traits on plankton dynamics.

Gaining understanding of food-web processes often requires a simplified representation of natural diversity. One such simplification can be based on functional traits, as functionally similar species may provide a similar contribution to ecosystem level-processes. However, understanding how similarity in functional traits actually translates into similar contributions to ecosystem-level properties remains a challenge due to the complex ways in which traits can influence species' dynamics. Moreover, in many communities, seasonality alters the abiotic and biotic forcing regime, causing ongoing changes to patterns of species' dominance; groups of species do not stay intact but are rather continuously subjected to changes throughout the year. Using long-term high frequency measurements of phytoplankton in Lake Constance, we investigated the effect of seasonal changes on the relationship between functional similarity and temporal dynamics similarity of 36 morphotypes, and the relative contribution of different functional traits during the different parts of the year. Our results revealed seasonal differences in the overall degree of synchronization of morphotypes' temporal dynamics and how combinations of functional traits influence the relationship between functional trait similarity and temporal dynamics similarity, showing that different forcing regimes change how species cope with their environment based on their functional traits. Moreover, we show that the individual functional traits matter at different periods of the year indicating that species which are dynamically similar at certain parts of the year may not be at others. The differential strength of the overall and individual impact of functional traits on species' temporal dynamics makes the cohesion of a pair of functionally similar species dependent on the different forcing. Hence, simplifying food webs based solely on functional traits may not provide consistent estimates of functional groups over all seasons.