Extending the integrated phenotype: covariance and correlation in plasticity of behavioural traits

Plasticity of the olfactory behaviors in Bactrocera dorsalis under various physiological states and environmental conditions

Insects rely heavily on their olfactory system for various behaviors, including foraging, mating, and oviposition. Numerous studies have demonstrated that insects can adjust their olfactory behaviors in response to different physiological states and environmental conditions. This flexibility allows them to perceive and process odorants according to different conditions. The Oriental fruit fly, Bactrocera dorsalis, is a highly destructive and invasive pest causing significant economic losses to fruit and vegetable crops worldwide. The olfactory behavior of B. dorsalis exhibits strong plasticity, resulting in its successful invasion. To enhance our understanding of B. dorsalis' olfactory behavior and explore potential strategies for behavior control, we have reviewed recent literature on its olfactory plasticity and potential molecular mechanisms.

Genetic regulators of a resource polyphenism interact to couple predatory morphology and behaviour

Phenotypic plasticity often requires the coordinated response of multiple traits observed individually as morphological, physiological or behavioural. The integration, and hence functionality, of this response may be influenced by whether and how these component traits share a genetic basis. In the case of polyphenism, or discrete plasticity, at least part of the environmental response is categorical, offering a simple readout for determining whether and to what degree individual components of a plastic response can be decoupled. Here, we use the nematode Pristionchus pacificus, which has a resource polyphenism allowing it to be a facultative predator of other nematodes, to understand the genetic integration of polyphenism. The behavioural and morphological consequences of perturbations to the polyphenism's genetic regulatory network show that both predatory activity and ability are strongly influenced by morphology, different axes of morphological variation are associated with different aspects of predatory behaviour, and rearing environment can decouple predatory morphology from behaviour. Further, we found that interactions between some polyphenism-modifying genes synergistically affect predatory behaviour. Our results show that the component traits of an integrated polyphenic response can be decoupled and, in principle, selected upon individually, and they suggest that multiple routes to functionally comparable phenotypes are possible.

Frank Beach Award Winner: The centrality of the hypothalamic-pituitary-adrenal axis in dealing with environmental change across temporal scales

Understanding if and how individuals and populations cope with environmental change is an enduring question in evolutionary ecology that has renewed importance given the pace of change in the Anthropocene. Two evolutionary strategies of coping with environmental change may be particularly important in rapidly changing environments: adaptive phenotypic plasticity and/or bet hedging. Adaptive plasticity could enable individuals to match their phenotypes to the expected environment if there is an accurate cue predicting the selective environment. Diversifying bet hedging involves the production of seemingly random phenotypes in an unpredictable environment, some of which may be adaptive. Here, I review the central role of the hypothalamic-pituitary-adrenal (HPA) axis and glucocorticoids (GCs) in enabling vertebrates to cope with environmental change through adaptive plasticity and bet hedging. I first describe how the HPA axis mediates three types of adaptive plasticity to cope with environmental change (evasion, tolerance, recovery) over short timescales (e.g., 1-3 generations) before discussing how the implications of GCs on phenotype integration may depend upon the timescale under consideration. GCs can promote adaptive phenotypic integration, but their effects on phenotypic co-variation could also limit the dimensions of phenotypic space explored by animals over longer timescales. Finally, I discuss how organismal responses to environmental stressors can act as a bet hedging mechanism and therefore enhance evolvability by increasing genetic or phenotypic variability or reducing patterns of genetic and phenotypic co-variance. Together, this emphasizes the crucial role of the HPA axis in understanding fundamental questions in evolutionary ecology.

Additive genetic variance for traits least related to fitness increases with environmental stress in the desert locust, Schistocerca gregaria

Under environmental stress, previously hidden additive genetic variation can be unmasked and exposed to selection. The amount of hidden variation is expected to be higher for life history traits, which strongly correlate to individual fitness, than for morphological traits, in which fitness effects are more ambiguous. However, no consensual pattern has been recovered yet, and this idea is still debated in the literature. Here, we hypothesize that the classical categorization of traits (i.e., life history and morphology) may fail to capture their proximity to fitness. In the desert locust, Schistocerca gregaria, a model organism for the study of insect polyphenism, we quantified changes in additive genetic variation elicited by lifetime thermal stress for ten traits, in which evolutionary significance is known. Irrespective of their category, traits under strong stabilizing selection showed genetic invariance with environmental stress, while traits more loosely associated with fitness showed a marked increase in additive genetic variation in the stressful environment. Furthermore, traits involved in adaptive phenotypic plasticity (growth compensation) showed either no change in additive genetic variance or a change of moderate magnitude across thermal environments. We interpret this mitigated response of plastic traits in the context of integrated evolution to adjust the entire phenotype in heterogeneous environments (i.e., adaptiveness of initial plasticity, compromise of phenotypic compensation with stress, and shared developmental pathway). Altogether, our results indicate, in agreement with theoretical expectations, that environmental stress can increase available additive genetic variance in some desert locust traits, but those closely linked to fitness are largely unaffected. Our study also highlights the importance of assessing the proximity to fitness of a trait on a case-by-case basis and in an ecologically relevant context, as well as considering the processes of canalization and plasticity, involved in the control of phenotypic variation.

Phenotypic integration does not constrain phenotypic plasticity: differential plasticity of traits is associated to their integration across environments

Understanding constraints to phenotypic plasticity is key given its role on the response of organisms to environmental change. It has been suggested that phenotypic integration, the structure of trait covariation, could limit trait plasticity. However, the relationship between plasticity and integration is far from resolved. Using a database of functional plasticity to drought of a Mediterranean shrub that included 20 ecophysiological traits, we assessed environmentally-induced changes in phenotypic integration and whether integration constrained the expression of plasticity, accounting for the within-environment phenotypic variation of traits. Furthermore, we provide the first test of the association between differential trait plasticity and trait integration across an optimum and a stressful environment. Phenotypic plasticity was positively associated with phenotypic integration in both environments, but this relationship was lost when phenotypic variation was considered. The similarity in the plastic response of two traits predicted their integration across environments, with integrated traits having more similar plasticity. Such variation in the plasticity of traits partly explained the lower phenotypic integration found in the stressful environment. We found no evidence that integration may constitute an internal constraint to plasticity. Rather, we present the first empirical demonstration that differences in plastic responses may involve a major reorganization of the relationships among traits, and challenge the notion that stress generally induces a tighter phenotype.

Does phenotypic plasticity initiate developmental bias?

The generation of variation is paramount for the action of natural selection. Although biologists are now moving beyond the idea that random mutation provides the sole source of variation for adaptive evolution, we still assume that variation occurs randomly. In this review, we discuss an alternative view for how phenotypic plasticity, which has become well accepted as a source of phenotypic variation within evolutionary biology, can generate nonrandom variation. Although phenotypic plasticity is often defined as a property of a genotype, we argue that it needs to be considered more explicitly as a property of developmental systems involving more than the genotype. We provide examples of where plasticity could be initiating developmental bias, either through direct active responses to similar stimuli across populations or as the result of programmed variation within developmental systems. Such biased variation can echo past adaptations that reflect the evolutionary history of a lineage but can also serve to initiate evolution when environments change. Such adaptive programs can remain latent for millions of years and allow development to harbor an array of complex adaptations that can initiate new bouts of evolution. Specifically, we address how ideas such as the flexible stem hypothesis and cryptic genetic variation overlap, how modularity among traits can direct the outcomes of plasticity, and how the structure of developmental signaling pathways is limited to a few outcomes. We highlight key questions throughout and conclude by providing suggestions for future research that can address how plasticity initiates and harbors developmental bias.

Developmental integration and evolution of labile plasticity in a complex quantitative character in a multiperiodic environment

Labile plasticity in a complex quantitative character is modeled, with multiple components contributing to net plasticity in the character. Each component has a specific development rate, norm of reaction, and cost of plasticity. For example, thermal adaptation in mammals includes seasonal fat deposition and fur growth, short-term shivering and sweating or panting, and movement between warm and cold sites. Norms of reaction do not reveal patterns of developmental integration, which must be investigated by studies of developmental dynamics in a changing environment. In a periodic environment, a labile character with a single component of plasticity is constrained by filtering environmental frequencies above the development rate and by the cost of plasticity. With multiple components of plasticity, some patterns of integration can alleviate these constraints to greatly improve fidelity of the mean phenotype tracking multiperiodic cycles in the optimum phenotype. This occurs by environmental signal amplification or inhibition through developmental integration among components and by an augmented development rate of net plasticity in the character that reduces environmental frequency filtering. When development of a component with high cost of plasticity is regulated partly by the norm of reaction of another component, evolution can diminish the reaction norm slope of the costly component without curtailing its development, thereby reducing the loss of fitness from its cost of plasticity. Apparent maladaptation in a component of plasticity may be an integral part of an adaptive pattern of developmental integration by mutual inhibition between components and compensatory evolution of a negative component reaction norm slope.

Selection for associative learning of color stimuli reveals correlated evolution of this learning ability across multiple stimuli and rewards

We are only starting to understand how variation in cognitive ability can result from local adaptations to environmental conditions. A major question in this regard is to what extent selection on cognitive ability in a specific context affects that ability in general through correlated evolution. To address this question, we performed artificial selection on visual associative learning in female Nasonia vitripennis wasps. Using appetitive conditioning in which a visual stimulus was offered in association with a host reward, the ability to learn visual associations was enhanced within 10 generations of selection. To test for correlated evolution affecting this form of learning, the ability to readily form learned associations in females was also tested using an olfactory instead of a visual stimulus in the appetitive conditioning. Additionally, we assessed whether the improved associative learning ability was expressed across sexes by color-conditioning males with a mating reward. Both females and males from the selected lines consistently demonstrated an increased associative learning ability compared to the control lines, independent of learning context or conditioned stimulus. No difference in relative volume of brain neuropils was detected between the selected and control lines.

Phenotypic integration and the evolution of signal repertoires: A case study of treefrog acoustic communication

Animal signals are inherently complex phenotypes with many interacting parts combining to elicit responses from receivers. The pattern of interrelationships between signal components reflects the extent to which each component is expressed, and responds to selection, either in concert with or independently of others. Furthermore, many species have complex repertoires consisting of multiple signal types used in different contexts, and common morphological and physiological constraints may result in interrelationships extending across the multiple signals in species' repertoires. The evolutionary significance of interrelationships between signal traits can be explored within the framework of phenotypic integration, which offers a suite of quantitative techniques to characterize complex phenotypes. In particular, these techniques allow for the assessment of modularity and integration, which describe, respectively, the extent to which sets of traits covary either independently or jointly. Although signal and repertoire complexity are thought to be major drivers of diversification and social evolution, few studies have explicitly measured the phenotypic integration of signals to investigate the evolution of diverse communication systems. We applied methods from phenotypic integration studies to quantify integration in the two primary vocalization types (advertisement and aggressive calls) in the treefrogs Hyla versicolor, Hyla cinerea, and Dendropsophus ebraccatus. We recorded male calls and calculated standardized phenotypic variance-covariance (P) matrices for characteristics within and across call types. We found significant integration across call types, but the strength of integration varied by species and corresponded with the acoustic similarity of the call types within each species. H. versicolor had the most modular advertisement and aggressive calls and the least acoustically similar call types. Additionally, P was robust to changing social competition levels in H. versicolor. Our findings suggest new directions in animal communication research in which the complex relationships among the traits of multiple signals are a key consideration for understanding signal evolution.

Comparative Analyses of Phenotypic Trait Covariation within and among Populations

Many morphological, behavioral, physiological, and life-history traits covary across the biological scales of individuals, populations, and species. However, the processes that cause traits to covary also change over these scales, challenging our ability to use patterns of trait covariance to infer process. Trait relationships are also widely assumed to have generic functional relationships with similar evolutionary potentials, and even though many different trait relationships are now identified, there is little appreciation that these may influence trait covariation and evolution in unique ways. We use a trait-performance-fitness framework to classify and organize trait relationships into three general classes, address which ones more likely generate trait covariation among individuals in a population, and review how selection shapes phenotypic covariation. We generate predictions about how trait covariance changes within and among populations as a result of trait relationships and in response to selection and consider how these can be tested with comparative data. Careful comparisons of covariation patterns can narrow the set of hypothesized processes that cause trait covariation when the form of the trait relationship and how it responds to selection yield clear predictions about patterns of trait covariation. We discuss the opportunities and limitations of comparative approaches to evaluate hypotheses about the evolutionary causes and consequences of trait covariation and highlight the importance of evaluating patterns within populations replicated in the same and in different selective environments. Explicit hypotheses about trait relationships are key to generating effective predictions about phenotype and its evolution using covariance data.

Using network analysis to study behavioural phenotypes: an example using domestic dogs

Phenotypic integration describes the complex interrelationships between organismal traits, traditionally focusing on morphology. Recently, research has sought to represent behavioural phenotypes as composed of quasi-independent latent traits. Concurrently, psychologists have opposed latent variable interpretations of human behaviour, proposing instead a network perspective envisaging interrelationships between behaviours as emerging from causal dependencies. Network analysis could also be applied to understand integrated behavioural phenotypes in animals. Here, we assimilate this cross-disciplinary progression of ideas by demonstrating the use of network analysis on survey data collected on behavioural and motivational characteristics of police patrol and detection dogs (Canis lupus familiaris). Networks of conditional independence relationships illustrated a number of functional connections between descriptors, which varied between dog types. The most central descriptors denoted desirable characteristics in both patrol and detection dog networks, with 'Playful' being widely correlated and possessing mediating relationships between descriptors. Bootstrap analyses revealed the stability of network results. We discuss the results in relation to previous research on dog personality, and benefits of using network analysis to study behavioural phenotypes. We conclude that a network perspective offers widespread opportunities for advancing the understanding of phenotypic integration in animal behaviour.

Using network analysis to study behavioural phenotypes: an example using domestic dogs

Phenotypic integration describes the complex interrelationships between organismal traits, traditionally focusing on morphology. Recently, research has sought to represent behavioural phenotypes as composed of quasi-independent latent traits. Concurrently, psychologists have opposed latent variable interpretations of human behaviour, proposing instead a network perspective envisaging interrelationships between behaviours as emerging from causal dependencies. Network analysis could also be applied to understand integrated behavioural phenotypes in animals. Here, we assimilate this cross-disciplinary progression of ideas by demonstrating the use of network analysis on survey data collected on behavioural and motivational characteristics of police patrol and detection dogs (Canis lupus familiaris). Networks of conditional independence relationships illustrated a number of functional connections between descriptors, which varied between dog types. The most central descriptors denoted desirable characteristics in both patrol and detection dog networks, with 'Playful' being widely correlated and possessing mediating relationships between descriptors. Bootstrap analyses revealed the stability of network results. We discuss the results in relation to previous research on dog personality, and benefits of using network analysis to study behavioural phenotypes. We conclude that a network perspective offers widespread opportunities for advancing the understanding of phenotypic integration in animal behaviour.