Quantifying the causal pathways contributing to natural selection

Personality traits differentially affect components of reproductive success in a Neotropical poison frog

Individual reproductive success has several components, including the acquisition of mating partners, offspring production, and offspring survival until adulthood. While the effects of certain personality traits-such as boldness or aggressiveness-on single components of reproductive success are well studied, we know little about the composite and multifaceted effects behavioural traits can have on all the aspects of reproductive success. Behavioural traits positively linked to one component of reproductive success might not be beneficial for other components, and these effects may differ between sexes. We investigated the influence of boldness, aggressiveness, and exploration on the number of mating partners, mating events, and offspring surviving until adulthood in males and females of the Neotropical poison frog Allobates femoralis. Behavioural traits had different-even opposite-effects on distinct components of reproductive success in both males and females. For example, males who displayed high levels of aggressiveness and exploration (or low levels of aggressiveness and exploration) managed to attract high number of mating partners, while males with low levels of boldness, low levels of aggressiveness, and high levels of exploration had the most offspring surviving until adulthood. Our results therefore suggest correlational selection favouring particular combinations of behavioural traits.

Evolutionary game theory of continuous traits from a causal perspective

Modern evolutionary game theory typically deals with the evolution of continuous, quantitative traits under weak selection, allowing the incorporation of rich biological detail and complicated nonlinear interactions. While these models are commonly used to find candidates for evolutionary endpoints and to approximate evolutionary trajectories, a less appreciated property is their potential to expose and clarify the causal structure of evolutionary processes. The mathematical step of differentiation breaks a nonlinear model into additive components which are more intuitive to interpret, and when combined with a proper causal hypothesis, partial derivatives in such models have a causal meaning. Such an approach has been used in the causal analysis of game-theoretical models in an informal manner. Here we formalize this approach by linking evolutionary game theory to concepts developed in causal modelling over the past century, from path coefficients to the recently proposed causal derivative. There is a direct correspondence between the causal derivative and the derivative used in evolutionary game theory. Some game theoretical models (e.g. kin selection) consist of multiple causal derivatives. Components of these derivatives correspond to components of the causal derivative, to path coefficients, and to edges on a causal graph, formally linking evolutionary game theory to causal modelling. This article is part of the theme issue 'Half a century of evolutionary games: a synthesis of theory, application and future directions'.

Can low-quality parents exploit their high-quality partners to gain higher fitness?

An individual's optimal investment in parental care potentially depends on many variables, including its future fitness prospects, the expected costs of providing care and its partner's expected or observed parental behaviour. Previous models suggested that low-quality parents could evolve to exploit their high-quality partners by reducing care, leading to the paradoxical prediction that low-quality parents could have higher fitness than their high-quality partners. However, these studies lacked a complete and consistent life-history model. Here, we challenge this result, developing a consistent analytical model of parental care strategies given individual variation in quality, and checking our results using agent-based simulations. In contrast to previous models, we predict that high-quality individuals always outcompete low-quality individuals in fitness terms. However, care effort may differ between high- and low-quality parents in either direction: low-quality individuals care more than high-quality individuals if their baseline mortality is higher, but less if their mortality increases more steeply with increasing care. We also highlight the ambiguity of the term 'quality' and stress the need for 'genealogical consistency' in evolutionary models.

A generalised approach to the study and understanding of adaptive evolution

Evolutionary theory has made large impacts on our understanding and management of the world, in part because it has been able to incorporate new data and new insights successfully. Nonetheless, there is currently a tension between certain biological phenomena and mainstream evolutionary theory. For example, how does the inheritance of molecular epigenetic changes fit into mainstream evolutionary theory? Is niche construction an evolutionary process? Is local adaptation via habitat choice also adaptive evolution? These examples suggest there is scope (and perhaps even a need) to broaden our views on evolution. We identify three aspects whose incorporation into a single framework would enable a more generalised approach to the understanding and study of adaptive evolution: (i) a broadened view of extended phenotypes; (ii) that traits can respond to each other; and (iii) that inheritance can be non-genetic. We use causal modelling to integrate these three aspects with established views on the variables and mechanisms that drive and allow for adaptive evolution. Our causal model identifies natural selection and non-genetic inheritance of adaptive parental responses as two complementary yet distinct and independent drivers of adaptive evolution. Both drivers are compatible with the Price equation; specifically, non-genetic inheritance of parental responses is captured by an often-neglected component of the Price equation. Our causal model is general and simplified, but can be adjusted flexibly in terms of variables and causal connections, depending on the research question and/or biological system. By revisiting the three examples given above, we show how to use it as a heuristic tool to clarify conceptual issues and to help design empirical research. In contrast to a gene-centric view defining evolution only in terms of genetic change, our generalised approach allows us to see evolution as a change in the whole causal structure, consisting not just of genetic but also of phenotypic and environmental variables.

Analysis of trait-performance-fitness relationships reveals pollinator-mediated selection on orchid pollination traits

PREMISE

The role of pollinators in evolutionary floral divergence has spurred substantial effort into measuring pollinator-mediated phenotypic selection and its variation in space and time. For such estimates, the fitness consequences of pollination processes must be separated from other factors affecting fitness.

METHODS

We built a fitness function linking phenotypic traits of food-deceptive orchids to female reproductive success by including pollinator visitation and pollen deposition as intermediate performance components and used the fitness function to estimate the strength of pollinator-mediated selection through female reproductive success. We also quantified male performance as pollinarium removal and assessed similarity in trait effects on male and female performance.

RESULTS

The proportion of plants visited at least once by an effective pollinator was moderate to high, ranging from 53.7% to 85.1%. Tall, many-flowered plants were often more likely to be visited and pollinated. Given effective pollination, pollen deposition onto stigmas tended to be more likely for taller plants. Pollen deposition further depended on traits affecting the physical fit of pollinators to flowers (flower size, spur length), though the exact relationships varied in time and space. Using the fitness function to assess pollinator-mediated selection through female reproductive success acting on multiple traits, we found that selection varied detectably among taxa after accounting for sampling uncertainty. Across taxa, selection on most traits was stronger on average and more variable when pollination was less reliable.

CONCLUSIONS

These results support pollination-related trait-performance-fitness relationships and thus pollinator-mediated selection on traits functionally involved in the pollination process.

The evolution of mating preferences for genetic attractiveness and quality in the presence of sensory bias

The aesthetic preferences of potential mates have driven the evolution of a baffling diversity of elaborate ornaments. Which fitness benefit-if any-choosers gain from expressing such preferences is controversial, however. Here, we simulate the evolution of preferences for multiple ornament types (e.g., "Fisherian," "handicap," and "indicator" ornaments) that differ in their associations with genes for attractiveness and other components of fitness. We model the costs of preference expression in a biologically plausible way, which decouples costly mate search from cost-free preferences. Ornaments of all types evolved in our model, but their occurrence was far from random. Females typically preferred ornaments that carried information about a male's quality, defined here as his ability to acquire and metabolize resources. Highly salient ornaments, which key into preexisting perceptual biases, were also more likely to evolve. When males expressed quality-dependent ornaments, females invested readily in costly mate search to locate preferred males. In contrast, the genetic benefits associated with purely arbitrary ornaments were insufficient to sustain highly costly mate search. Arbitrary ornaments could nonetheless "piggyback" on mate-search effort favored by other, quality-dependent ornaments. We further show that the potential to produce attractive male offspring ("sexy sons") can be as important as producing offspring of high general quality ("good genes") in shaping female preferences, even when preferred ornaments are quality dependent. Our model highlights the importance of mate-search effort as a driver of aesthetic coevolution.

On the evolution of trophic position

The trophic structure of food webs is primarily determined by the variation in trophic position among species and individuals. Temporal dynamics of food web structure are central to our understanding of energy and nutrient fluxes in changing environments, but little is known about how evolutionary processes shape trophic position variation in natural populations. We propose that trophic position, whose expression depends on both environmental and genetic determinants of the diet variation in individual consumers, is a quantitative trait that can evolve via natural selection. Such evolution can occur either when trophic position is correlated with other heritable morphological and behavioural traits under selection, or when trophic position is a target of selection, which is possible if the fitness effects of prey items are heterogeneously distributed along food chains. Recognising trophic position as an evolving trait, whose expression depends on the food web context, provides an important conceptual link between behavioural foraging theory and food web dynamics, and a useful starting point for the integration of ecological and evolutionary studies of trophic position.

Social competition as a driver of phenotype-environment correlations: implications for ecology and evolution

While it is universally recognised that environmental factors can cause phenotypic trait variation via phenotypic plasticity, the extent to which causal processes operate in the reverse direction has received less consideration. In fact individuals are often active agents in determining the environments, and hence the selective regimes, they experience. There are several important mechanisms by which this can occur, including habitat selection and niche construction, that are expected to result in phenotype–environment correlations (i.e. non‐random assortment of phenotypes across heterogeneous environments). Here we highlight an additional mechanism – intraspecific competition for preferred environments – that may be widespread, and has implications for phenotypic evolution that are currently underappreciated. Under this mechanism, variation among individuals in traits determining their competitive ability leads to phenotype–environment correlation; more competitive phenotypes are able to acquire better patches. Based on a concise review of the empirical evidence we argue that competition‐induced phenotype–environment correlations are likely to be common in natural populations before highlighting the major implications of this for studies of natural selection and microevolution. We focus particularly on two central issues. First, competition‐induced phenotype–environment correlation leads to the expectation that positive feedback loops will amplify phenotypic and fitness variation among competing individuals. As a result of being able to acquire a better environment, winners gain more resources and even better phenotypes – at the expense of losers. The distinction between individual quality and environmental quality that is commonly made by researchers in evolutionary ecology thus becomes untenable. Second, if differences among individuals in competitive ability are underpinned by heritable traits, competition results in both genotype–environment correlations and an expectation of indirect genetic effects (IGEs) on resource‐dependent life‐history traits. Theory tells us that these IGEs will act as (partial) constraints, reducing the amount of genetic variance available to facilitate evolutionary adaptation. Failure to recognise this will lead to systematic overestimation of the adaptive potential of populations. To understand the importance of these issues for ecological and evolutionary processes in natural populations we therefore need to identify and quantify competition‐induced phenotype–environment correlations in our study systems. We conclude that both fundamental and applied research will benefit from an improved understanding of when and how social competition causes non‐random distribution of phenotypes, and genotypes, across heterogeneous environments.

The evolutionary ecology of fatty-acid variation: Implications for consumer adaptation and diversification

The nutritional diversity of resources can affect the adaptive evolution of consumer metabolism and consumer diversification. The omega-3 long-chain polyunsaturated fatty acids eicosapentaenoic acid (EPA; 20:5n-3) and docosahexaenoic acid (DHA; 22:6n-3) have a high potential to affect consumer fitness, through their widespread effects on reproduction, growth and survival. However, few studies consider the evolution of fatty acid metabolism within an ecological context. In this review, we first document the extensive diversity in both primary producer and consumer fatty acid distributions amongst major ecosystems, between habitats and amongst species within habitats. We highlight some of the key nutritional contrasts that can shape behavioural and/or metabolic adaptation in consumers, discussing how consumers can evolve in response to the spatial, seasonal and community-level variation of resource quality. We propose a hierarchical trait-based approach for studying the evolution of consumers' metabolic networks and review the evolutionary genetic mechanisms underpinning consumer adaptation to EPA and DHA distributions. In doing so, we consider how the metabolic traits of consumers are hierarchically structured, from cell membrane function to maternal investment, and have strongly environment-dependent expression. Finally, we conclude with an outlook on how studying the metabolic adaptation of consumers within the context of nutritional landscapes can open up new opportunities for understanding evolutionary diversification.

Perspectives on Applications of Hierarchical Gene-To-Phenotype (G2P) Maps to Capture Non-stationary Effects of Alleles in Genomic Prediction

Genomic prediction of complex traits across environments, breeding cycles, and populations remains a challenge for plant breeding. A potential explanation for this is that underlying non-additive genetic (GxG) and genotype-by-environment (GxE) interactions generate allele substitution effects that are non-stationary across different contexts. Such non-stationary effects of alleles are either ignored or assumed to be implicitly captured by most gene-to-phenotype (G2P) maps used in genomic prediction. The implicit capture of non-stationary effects of alleles requires the G2P map to be re-estimated across different contexts. We discuss the development and application of hierarchical G2P maps that explicitly capture non-stationary effects of alleles and have successfully increased short-term prediction accuracy in plant breeding. These hierarchical G2P maps achieve increases in prediction accuracy by allowing intermediate processes such as other traits and environmental factors and their interactions to contribute to complex trait variation. However, long-term prediction remains a challenge. The plant breeding community should undertake complementary simulation and empirical experiments to interrogate various hierarchical G2P maps that connect GxG and GxE interactions simultaneously. The existing genetic correlation framework can be used to assess the magnitude of non-stationary effects of alleles and the predictive ability of these hierarchical G2P maps in long-term, multi-context genomic predictions of complex traits in plant breeding.