Morphological and anatomical determinants of mesophyll conductance in wild relatives of tomato (Solanum sect. Lycopersicon,sect. Lycopersicoides; Solanaceae)

Natural selection on photosynthetic performance is a primary factor determining leaf phenotypes. The complex CO₂ diffusion path from substomatal cavities to the chloroplasts – the mesophyll conductance (g_m) – limits photosynthetic rate in many species and hence shapes variation in leaf morphology and anatomy. Among sclerophyllous and succulent taxa, structural investment in leaves, measured as the leaf dry mass per area (LMA), has been implicated in decreased g_m. However, in herbaceous taxa with high g_m, it is less certain how LMA impacts CO₂ diffusion and whether it significantly affects photosynthetic performance. We addressed these questions in the context of understanding the ecophysiological significance of leaf trait variation in wild tomatoes, a closely related group of herbaceous perennials. Although g_m was high in wild tomatoes, variation in g_m significantly affected photosynthesis. Even in these tender‐leaved herbaceous species, greater LMA led to reduced g_m. This relationship between g_m and LMA is partially mediated by cell packing and leaf thickness, although amphistomy (equal distribution of stomata on both sides of the leaf) mitigates the effect of leaf thickness. Understanding the costs of increased LMA will inform future work on the adaptive significance of leaf trait variation across ecological gradients in wild tomatoes and other systems.     

Adaptive evolution of reproductive and vegetative traits driven by breeding systems

The evolution of inflorescence size, a key trait in reproductive success, was studied in the genus Acer under a perspective of adaptive evolution. Breeding systems, hypothesized to indicate different levels of mating competition, were considered as the selective scenarios defining different optima of inflorescence size. Larger inflorescences, which increase male fitness by generating larger floral displays, were hypothesized to be selected under scenarios with higher competition with unisexuals. An identical approach was used to test if the same selective regimes could be driving the evolution of leaf size, a vegetative trait that was found to be correlated with inflorescence size. A Brownian motion model of inflorescence/leaf-size evolution (which cannot distinguish between changes caused by pure drift processes and changes caused by natural selection in rapidly and randomly changing environments) was compared with several adaptive Ornstein-Uhlenbeck (OU) models, which can quantify the effects of both stochasticity and natural selection. The best-fitting model for inflorescence/leaf-size evolution was an OU model with three optima that increased with the level of mating competition. Both traits evolved under the same selective regimes and in the same direction, confirming a pattern of correlated evolution. These results show that a selective regime hypothetically related to the evolution of a reproductive trait can also explain the evolution of a vegetative trait.     

Evidence of heterogeneous selection on quantitative traits of Prosopis flexuosa (Leguminosae) from multivariate Q ST –F ST test

Prosopis flexuosa is an arboreal Leguminosae that grows in arid and semiarid temperate zones of Argentina, in the Monte eco-region. It is a promising native forest species for recovering arid and semiarid regions because it plays an important role in erosion control as well as in soil fertility. Furthermore, it provides diverse economical resources. The main challenge to the forestry sector is finding a balance between production and forest protection. For this purpose, it is necessary to gather information about genetic parameters. In this study, we measured the distribution of the variation of 14 quantitative traits in an experimental half-sib stand, where families are representative of hierarchically structured populations. We applied a multivariate extension of the classical Q _ST –F _ST neutrality test to determine the relative importance of drift versus selection in the distribution of genetic variability. We found strong evidence that different selective regimes act on different traits and that selection favors different optima in each sampling site. The selection to different optima is much stronger among than within provenances. This result helps explain the possible causes for the regional variation observed in P. flexuosa and to define the management units and the evolutionarily significant units for this species.     

Selective regimes and functional anatomy in the mustelid forelimb: Diversification toward specializations for climbing,digging, and swimming

Anatomical traits associated with locomotion often exhibit specializations for ecological niche, suggesting that locomotor specializations may constitute selective regimes acting on limb skeletal traits. To test this, I sampled 42 species of Mustelidae, encompassing climbing, digging, and swimming specialists, and determined whether trait variation reflects locomotor specialization by performing a principal components analysis on 14 forelimb traits. In addition to Brownian motion models, three Ornstein–Uhlenbeck models of selective regimes were applied to PC scores describing trait variation among mustelids: one without a priori defined phenotypic optima, one with optima based upon locomotor habit, and one with a single phenotypic optimum. PC1, which explained 43.8% of trait variance, represented a trade‐off in long bone gracility and deltoid ridge length vs. long robustness and olecranon process length and distinguished between climbing specialists and remaining mustelids. PC2, which explained 17.4% of trait variance, primarily distinguished the sea otter from other mustelids. Best fitting trait diversification models are selective regimes differentiating between scansorial and nonscansorial mustelids (PC1) and selective regimes distinguishing the sea otter and steppe polecat from remaining mustelids (PC2). Phylogenetic half‐life values relative to branch lengths suggest that, in spite of a strong rate of adaptation, there is still the influence of past trait values. However, simulations of likelihood ratios suggest that the best fitting models are not fully adequate to explain morphological diversification within extant mustelids.     

The causes of variation in tree seedling traits: the roles of environmental selection versus chance

A key aspect of biodiversity is the great quantitative variation in functional traits observed among species. One perspective asserts that trait values should converge on a single optimum value in a particular selective environment, and consequently trait variation would reflect differences in selective environment, and evolutionary outcomes would be predictable. An alternative perspective asserts that there are likely multiple alternative optima within a particular selective environment, and consequently different lineages would evolve toward different optima due to chance. Because there is evidence for both of these perspectives, there is a long-standing controversy over the relative importance of convergence due to environmental selection versus divergence due to chance in shaping trait variation. Here, I use a model of tree seedling growth and survival to distinguish trait variation associated with multiple alternative optima from variation associated with environmental differences. I show that variation in whole plant traits is best explained by environmental differences, whereas in organ level traits variation is more affected by alternative optima. Consequently, I predict that in nature variation in organ level traits is most closely related to phylogeny, whereas variation in whole plant traits is most closely related to ecology.     

Physiological studies of subtidal red algae

The net photosynthesis of the subtidal red algae Euthora cristata (C. Agardh) J. Agardh, Phycodrys rubens (L. ) Batters, Phyllophora truncata (Pallas) Newroth et Taylor and Ptilota serrata Kützing were determined under a variety of different light and temperature regimes. The optimal light requirements for net photosynthesis of the species are relatively low, mostly ranging from 465 to 747 ft-c at 5 ° and 15 °C. Seasonal and spatial differences were found in the photosynthesis-light responses of Phyllophora truncata and Ptilota serrata; winter plants exhibited lower light optima for net photosynthesis than spring plants. Deep-water populations of Ptilota showed lower light optima and reduced net photosynthesis as compared with shallow subtidal populations. Summer plants of Euthora cristata, Phycodrys rubens and Phyllophora truncata showed a greater tolerance to high temperatures and higher temperature optima than winter plants. It is suggested that optimal temperature and light requirements of seaweeds are adjusted in an adaptive fashion to the environmental regimes of their habitats. The temperature requirements of the four species are discussed in relation to their local estuarine distributions in New England; eurythermal species have the widest estuarine distributions. Cystocarpic and tetrasporic plants of Euthora cristata and Ptilota serrata show differential physiological responses and vertical distributions. The significance of higher rates of net photosynthesis and lower light optima are discussed in relation to vertical stratification of different generations.     

Quantitative Genetic Analysis Indicates Natural Selection on Leaf Phenotypes Across Wild Tomato Species (Solanum sect. Lycopersicon; Solanaceae)

Adaptive evolution requires both raw genetic material and an accessible path of high fitness from one fitness peak to another. In this study, we used an introgression line (IL) population to map quantitative trait loci (QTL) for leaf traits thought to be associated with adaptation to precipitation in wild tomatoes (Solanum sect. Lycopersicon; Solanaceae). A QTL sign test showed that several traits likely evolved under directional natural selection. Leaf traits correlated across species do not share a common genetic basis, consistent with a scenario in which selection maintains trait covariation unconstrained by pleiotropy or linkage disequilibrium. Two large effect QTL for stomatal distribution colocalized with key genes in the stomatal development pathway, suggesting promising candidates for the molecular bases of adaptation in these species. Furthermore, macroevolutionary transitions between vastly different stomatal distributions may not be constrained when such large-effect mutations are available. Finally, genetic correlations between stomatal traits measured in this study and data on carbon isotope discrimination from the same ILs support a functional hypothesis that the distribution of stomata affects the resistance to CO₂ diffusion inside the leaf, a trait implicated in climatic adaptation in wild tomatoes. Along with evidence from previous comparative and experimental studies, this analysis indicates that leaf traits are an important component of climatic niche adaptation in wild tomatoes and demonstrates that some trait transitions between species could have involved few, large-effect genetic changes, allowing rapid responses to new environmental conditions.     

AMPHISTOMY AS AN ADAPTATION TO HIGH LIGHT INTENSITY IN AMBROSIA CORDIFOLIA (COMPOSITAE)

Adaptation to high light intensity in Ambrosia cordifolia (Compositae) involved an increase in leaf thickness, photosynthetic capacity, and maximum stomatal conductance. In addition, leaves produced at high light intensities were amphistomatous, but those produced at low light intensities were hypostomatous. Although stomatal density on the upper surface was increased with increasing light intensity, the total stomatal density (upper + lower surfaces) was not substantially affected by light intensity because the density of stomata on the lower surface was reduced at high light intensities. The possible value of amphistomy in reducing diffusional limitations to photosynthesis in thick, high photosynthetic-capacity leaves is discussed.     

Automatic measurement of stomatal density from microphotographs

Key message

An automated process using a cascade classifier allowed the rapid assessment of the density and distribution of stomata on microphotographs from leaves of two oak species.

Abstract

Stomatal density is the number of stomata per unit area, an intensively studied trait, involved in the control of CO₂ and H₂O exchange between leaf and atmosphere. This trait is usually estimated by counting manually each stoma on a given surface (e.g., a microphotograph), usually repeating the procedure with images from different parts of the leaf. To improve this procedure, we tested the performance of a cascade classifier to automatically detect stomata on microphotographs from two oak species: Quercus afares Pomel and Quercus suber L. The two species are phylogenetically close with similar stomatal morphology, which allowed testing the reuse of the cascade classifier on stomata with similar shape. The results showed that a cascade classifier trained on only 100 sample views of stomata from Q. afares was able to rapidly detect stomata in Q. afares as well as in Q. suber with a very low number of false positives (5 %/1.9 %) and a small number of undetected stomata (14.8 %/0.74 %), when partial stomata near the edge of the microphotographs were ignored. The remaining undetected stomata were due to obstacles such as trichomes. As an example of further applications, we used the positions detected by the cascade classifier to assess the spatial distribution of stomata and group them on the leaf surface. To our knowledge this is the first time that a cascade classifier has been applied to plant microphotographs, and we were able to show that it can dramatically decrease the time needed to estimate stomatal density and spatial distribution.     

Comparing environmental and genetic variance as adaptive response to fluctuating selection

Phenotypic variation within populations has two sources: genetic variation and environmental variation. Here, we investigate the coevolution of these two components under fluctuating selection. Our analysis is based on the lottery model in which genetic polymorphism can be maintained by negative frequency-dependent selection, whereas environmental variation can be favored due to bet-hedging. In our model, phenotypes are characterized by a quantitative trait under stabilizing selection with the optimal phenotype fluctuating in time. Genotypes are characterized by their phenotypic offspring distribution, which is assumed to be Gaussian with heritable variation for its mean and variance. Polymorphism in the mean corresponds to genetic variance while the width of the offspring distribution corresponds to environmental variance. We show that increased environmental variance is favored whenever fluctuations in the selective optima are sufficiently strong. Given the environmental variance has evolved to its optimum, genetic polymorphism can still emerge if the distribution of selective optima is sufficiently asymmetric or leptokurtic. Polymorphism evolves in a diagonal direction in trait space: one type becomes a canalized specialist for the more common ecological conditions and the other type a de-canalized bet-hedger thriving on the less-common conditions. All results are based on analytical approximations, complemented by individual-based simulations.     

Testing limits to adaptation along altitudinal gradients in rainforest Drosophila

Given that evolution can generate rapid and dramatic shifts in the ecological tolerance of a species, what prevents populations adapting to expand into new habitat at the edge of their distributions? Recent population genetic models have focused on the relative costs and benefits of migration between populations. On the one hand, migration may limit adaptive divergence by preventing local populations from matching their local selective optima. On the other hand, migration may also contribute to the genetic variance necessary to allow populations to track these changing optima. Empirical evidence for these contrasting effects of gene flow in natural situations are lacking, largely because it remains difficult to acquire. Here, we develop a way to explore theoretical models by estimating genetic divergence in traits that confer stress resistance along similar ecological gradients in rainforest Drosophila. This approach allows testing for the coupling of clinal divergence with local density, and the effects of genetic variance and the rate of change of the optimum on the response to selection. In support of a swamping effect of migration on phenotypic divergence, our data show no evidence for a cline in stress-related traits where the altitudinal gradient is steep, but significant clinal divergence where it is shallow. However, where clinal divergence is detected, sites showing trait means closer to the presumed local optimum have more genetic variation than sites with trait means distant from their local optimum. This pattern suggests that gene flow also aids a sustained response to selection.     

Leaf shape linked to photosynthetic rates and temperature optima in South African <Emphasis Type="Italic">Pelargonium</Emphasis> species

The thermal response of gas exchange varies among plant species and with growth conditions. Plants from hot dry climates generally reach maximal photosynthetic rates at higher temperatures than species from temperate climates. Likewise, species in these environments are predicted to have small leaves with more-dissected shapes. We compared eight species of Pelargonium (Geraniaceae) selected as phylogenetically independent contrasts on leaf shape to determine whether: (1) the species showed plasticity in thermal response of gas exchange when grown under different water and temperature regimes, (2) there were differences among more- and less-dissected leafed species in trait means or plasticity, and (3) whether climatic variables were correlated with the responses. We found that a higher growth temperature led to higher optimal photosynthetic temperatures, at a cost to photosynthetic capacity. Optimal temperatures for photosynthesis were greater than the highest growth temperature regime. Stomatal conductance responded to growth water regime but not growth temperature, whereas transpiration increased and water use efficiency (WUE) decreased at the higher growth temperature. Strikingly, species with more-dissected leaves had higher rates of carbon gain and water loss for a given growth condition than those with less-dissected leaves. Species from lower latitudes and lower rainfall tended to have higher photosynthetic maxima and conductance, but leaf dissection did not correlate with climatic variables. Our results suggest that the combination of dissected leaves, higher photosynthetic rates, and relatively low WUE may have evolved as a strategy to optimize water delivery and carbon gain during short-lived periods of high soil moisture. Higher thermal optima, in conjunction with leaf dissection, may reflect selection pressure to protect photosynthetic machinery against excessive leaf temperatures when stomata close in response to water stress.     

The genetic architecture of ecophysiological and circadian traits in Brassica rapa

Developmental mechanisms that enable perception of and response to the environment may enhance fitness. Ecophysiological traits typically vary depending on local conditions and contribute to resource acquisition and allocation, yet correlations may limit adaptive trait expression. Notably, photosynthesis and stomatal conductance vary diurnally, and the circadian clock, which is an internal estimate of time that anticipates diurnal light/dark cycles, may synchronize physiological behaviors with environmental conditions. Using recombinant inbred lines of Brassica rapa, we examined the quantitative-genetic architecture of ecophysiological and phenological traits and tested their association with the circadian clock. We also investigated how trait expression differed across treatments that simulated seasonal settings encountered by crops and naturalized populations. Many ecophysiological traits were correlated, and some correlations were consistent with expected biophysical constraints; for example, stomata jointly regulate photosynthesis and transpiration by affecting carbon dioxide and water vapor diffusion across leaf surfaces, and these traits were correlated. Interestingly, some genotypes had unusual combinations of ecophysiological traits, such as high photosynthesis in combination with low stomatal conductance or leaf nitrogen, and selection on these genotypes could provide a mechanism for crop improvement. At the genotypic and QTL level, circadian period was correlated with leaf nitrogen, instantaneous measures of photosynthesis, and stomatal conductance as well as with a long-term proxy (carbon isotope discrimination) for gas exchange, suggesting that gas exchange is partly regulated by the clock and thus synchronized with daily light cycles. The association between circadian rhythms and ecophysiological traits is relevant to crop improvement and adaptive evolution.     

The adaptive accuracy of flowers: measurement and microevolutionary patterns

Background and Aims

From Darwin''s time onward, biologists have thought about adaptation as evolution toward optimal trait values, but they have not usually assessed the relative importance of the distinct causes of deviations from optima. This problem is investigated here by measuring adaptive inaccuracy (phenotypic deviation from the optimum), using flower pollination as an adaptive system.

Methods

Adaptive accuracy is shown to have at least three distinct components, two of which are optimality (deviation of the mean from the optimum) and precision (trait variance). We then describe adaptive accuracy of both individuals and populations. Individual inaccuracy comprises the deviation of the genotypic target (the mean phenotype of a genotype grown in a range of environments) from the optimum and the phenotypic variation around that genotypic target (phenotypic imprecision). Population inaccuracy has three basic components: deviation of the population mean from the optimum, variance in the genotypic targets and phenotypic imprecision. In addition, a fourth component is proposed, namely within-population variation in the optimum. These components are directly estimable, have additive relationships, and allow exploration of the causes of adaptive inaccuracy of both individuals and populations. Adaptive accuracy of a sample of flowers is estimated, relating floral phenotypes controlling pollen deposition on pollinators to adaptive optima defined as the site most likely to get pollen onto stigmas (male inaccuracy). Female inaccuracy is defined as the deviation of the position of stigma contact from the expected location of pollen on pollinators.

Key Results

A surprising amount of variation in estimated accuracy within and among similar species is found. Some of this variation is generated by developmental changes in positions of stigmas or anthers during anthesis (the floral receptive period), which can cause dramatic change in accuracy estimates. There seem to be trends for higher precision and accuracy in flowers with higher levels of integration and dichogamy (temporal separation of sexual functions), and in those that have pollinators that are immobile (or immobilized) during pollen transfer. Large deviations from putative adaptive optima were observed, and these may be related to the effects of conflicting selective pressures on flowers, such as selection against self-pollination promoting herkogamy (spatial separation of pollen and stigmas).

Conclusions

Adaptive accuracy is a useful concept for understanding the adaptive significance of phenotypic means and variances of floral morphology within and among populations and species. Estimating and comparing the various components of adaptive accuracy can be particularly helpful for identifying the causes of inaccuracy, such as conflicting selective pressures, low environmental canalization and developmental instability.Key words: Adaptive accuracy, Collinsia, Dalechampia, fitness, floral precision, Linum, optimality, pollination, Stylidium     

STABILIZING SELECTION AND THE COMPARATIVE ANALYSIS OF ADAPTATION

Comparative studies tend to differ from optimality and functionality studies in how they treat adaptation. While the comparative approach focuses on the origin and change of traits, optimality studies assume that adaptations are maintained at an optimum by stabilizing selection. This paper presents a model of adaptive evolution on a macroevolutionary time scale that includes the maintenance of traits at adaptive optima by stabilizing selection as the dominant evolutionary force. Interspecific variation is treated as variation in the position of adaptive optima. The model illustrates how phylogenetic constraints not only lead to correlations between phylogenetically related species, but also to imperfect adaptations. From this model, a statistical comparative method is derived that can be used to estimate the effect of a selective factor on adaptive optima in a way that would be consistent with an optimality study of adaptation to this factor. The method is illustrated with an analysis of dental evolution in fossil horses. The use of comparative methods to study evolutionary trends is also discussed.     

Allometric escape from acoustic constraints is rare for frog calls

Allometric constraint is a product of natural selection and physical laws, particularly with respect to body size and traits constrained by properties thereof, such as metabolism, longevity, and vocal frequency. Allometric relationships are often conserved across lineages, indicating that physical constraints dictate scaling patterns in deep time, despite substantial genetic and ecological divergence among organisms. In particular, acoustic allometry (sound frequency ~ body size) is conserved across frogs, in defiance of massive variation in both body size and frequency. Here, we ask how many instances of allometric escape have occurred across the frog tree of life using a Bayesian framework that estimates the location, number, and magnitude of shifts in the adaptive landscape of acoustic allometry. Moreover, we test whether ecology in terms of calling site could affect these relationships. We find that calling site has a major influence on acoustic allometry. Despite this, we identify only four major instances of allometric escape, potentially deriving from ecomorphological adaptations to new signal modalities. In these instances of allometric escape, the optima and strength of the scaling relationship are different than expected for most other frog species, representing new adaptive regimes of body size ~ call frequency. Allometric constraints on frog calls are highly conserved and have rarely allowed escape, despite frequent invasions of new adaptive regimes and dramatic ecomorphological divergence. Our results highlight the rare instances in which natural and sexual selection combined can overcome physical constraints on sound production.     

Genomic signatures of experimental adaptive radiation in Drosophila

Abiotic environmental factors play a fundamental role in determining the distribution, abundance and adaptive diversification of species. Empowered by new technologies enabling rapid and increasingly accurate examination of genomic variation in populations, researchers may gain new insights into the genomic background of adaptive radiation and stress resistance. We investigated genomic variation across generations of large‐scale experimental selection regimes originating from a single founder population of Drosophila melanogaster, diverging in response to ecologically relevant environmental stressors: heat shock, heat knock down, cold shock, desiccation and starvation. When compared to the founder population, and to parallel unselected controls, there were more than 100,000 single nucleotide polymorphisms (SNPs) displaying consistent allelic changes in response to selective pressures across generations. These SNPs were found in both coding and noncoding sequences, with the highest density in promoter regions, and involved a broad range of functionalities, including molecular chaperoning by heat‐shock proteins. The SNP patterns were highly stressor‐specific despite considerable variation among line replicates within each selection regime, as reflected by a principal component analysis, and co‐occurred with selective sweep regions. Only ~15% of SNPs with putatively adaptive changes were shared by at least two selective regimes, while less than 1% of SNPs diverged in opposite directions. Divergent stressors driving evolution in the experimental system of adaptive radiation left distinct genomic signatures, most pronounced in starvation and heat‐shock selection regimes.     

Xeromorphic traits help to maintain photosynthesis in the perhumid climate of a Taiwanese cloud forest

Previous flux measurements in the perhumid cloud forest of northeastern Taiwan have shown efficient photosynthesis of the endemic tree species Chamaecyparis obtusa var. formosana even under foggy conditions in which leaf surface moisture would be expected. We hypothesized this to be the result of ‘xeromorphic’ traits of the Chamaecyparis leaves (hydrophobicity, stomatal crypts, stomatal clustering), which could prevent coverage of stomata by precipitation, fog, and condensation, thereby maintaining CO₂ uptake. Here we studied the amount, distribution, and composition of moisture accumulated on Chamaecyparis leaf surfaces in situ in the cloud forest. We studied the effect of surface tension on gas penetration to stomata using optical O₂ microelectrodes in the laboratory. We captured the dynamics of condensation to the leaf surfaces with an environmental scanning electron microscope (ESEM). In spite of substantial surface hydrophobicity, the mean water film thickness on branchlets under foggy conditions was 80 µm (upper surface) and 40 µm (lower surface). This amount of water could cover stomata and prevent CO₂ uptake. This is avoided by the clustered arrangement of stomata within narrow clefts and the presence of Florin rings. These features keep stomatal pores free from water due to surface tension and provide efficient separation of plant and atmosphere in this perhumid environment. Air pollutants, particularly hygroscopic aerosol, may disturb this functionality by enhancing condensation and reducing the surface tension of leaf surface water.     

MODELING STABILIZING SELECTION: EXPANDING THE ORNSTEIN-UHLENBECK MODEL OF ADAPTIVE EVOLUTION

Comparative methods used to study patterns of evolutionary change in a continuous trait on a phylogeny range from Brownian motion processes to models where the trait is assumed to evolve according to an Ornstein-Uhlenbeck (OU) process. Although these models have proved useful in a variety of contexts, they still do not cover all the scenarios biologists want to examine. For models based on the OU process, model complexity is restricted in current implementations by assuming that the rate of stochastic motion and the strength of selection do not vary among selective regimes. Here, we expand the OU model of adaptive evolution to include models that variously relax the assumption of a constant rate and strength of selection. In its most general form, the methods described here can assign each selective regime a separate trait optimum, a rate of stochastic motion parameter, and a parameter for the strength of selection. We use simulations to show that our models can detect meaningful differences in the evolutionary process, especially with larger sample sizes. We also illustrate our method using an empirical example of genome size evolution within a large flowering plant clade.     

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

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.