Morphological Evolution: Bioinspired Methods for Analyzing Bioinspired Robots

To fully understand the evolution of complex morphologies, analyses cannot stop at selection: It is essential to investigate the roles and interactions of multiple processes that drive evolutionary outcomes. The challenges of undertaking such analyses have affected both evolutionary biologists and evolutionary roboticists, with their common interests in complex morphologies. In this paper, we present analytical techniques from evolutionary biology, selection gradient analysis and morphospace walks, and we demonstrate their applicability to robot morphologies in analyses of three evolutionary mechanisms: randomness (genetic mutation), development (an explicitly implemented genotype-to-phenotype map), and selection. In particular, we applied these analytical techniques to evolved populations of simulated biorobots—embodied robots designed specifically as models of biological systems, for the testing of biological hypotheses—and we present a variety of results, including analyses that do all of the following: illuminate different evolutionary dynamics for different classes of morphological traits; illustrate how the traits targeted by selection can vary based on the likelihood of random genetic mutation; demonstrate that selection on two selected sets of morphological traits only partially explains the variance in fitness in our biorobots; and suggest that biases in developmental processes could partially explain evolutionary dynamics of morphology. When combined, the complementary analytical approaches discussed in this paper can enable insight into evolutionary processes beyond selection and thereby deepen our understanding of the evolution of robotic morphologies.

Directional Selection on Tree Seedling Traits Driven by Experimental Drought Differs Between Mesic and Dry Populations

We evaluated population differences and drought-induced phenotypic selection on four seedling traits of the Australian forest tree Eucalyptus pauciflora using a glasshouse dry-down experiment. We compared dry and mesic populations and tested for directional selection on lamina length (reflecting leaf size), leaf shape, the node of ontogenetic transition to the petiolate leaf (reflecting the loss of vegetative juvenility), and lignotuber size (reflecting a recovery trait). On average, the dry population had smaller and broader leaves, greater retention of the juvenile leaf state and larger lignotubers than the mesic population, but the populations did not differ in seedling survival. While there was statistical support for directional selection acting on the focal traits in one or other population, and for differences between populations in selection gradient estimates for two traits, only one trait—lamina length—exhibited a pattern of directional selection consistent with the observed population differences being a result of past adaptation to reduce seedling susceptibility to acute drought. The observed directional selection for lamina length in the mesic population suggests that future increases in drought risk in the wild will shift the mean of the mesic population toward that of the dry population. Further, we provide evidence suggesting an early age trade-off between drought damage and recovery traits, with phenotypes which develop larger lignotubers early being more susceptible to drought death. Such trade-offs could have contributed to the absence of population mean differences in survival, despite marked differentiation in seedling traits.

Modeling host-associating microbes under selection

The concept of fitness is often reduced to a single component, such as the replication rate in a given habitat. For species with multi-step life cycles, this can be an unjustified oversimplification, as every step of the life cycle can contribute to the overall reproductive success in a specific way. In particular, this applies to microbes that spend part of their life cycles associated to a host. In this case, there is a selection pressure not only on the replication rates, but also on the phenotypic traits associated to migrating from the external environment to the host and vice-versa (i.e., the migration rates). Here, we investigate a simple model of a microbial lineage living, replicating, migrating and competing in and between two compartments: a host and an environment. We perform a sensitivity analysis on the overall growth rate to determine the selection gradient experienced by the microbial lineage. We focus on the direction of selection at each point of the phenotypic space, defining an optimal way for the microbial lineage to increase its fitness. We show that microbes can adapt to the two-compartment life cycle through either changes in replication or migration rates, depending on the initial values of the traits, the initial distribution across the two compartments, the intensity of competition, and the time scales involved in the life cycle versus the time scale of adaptation (which determines the adequate probing time to measure fitness). Overall, our model provides a conceptual framework to study the selection on microbes experiencing a host-associated life cycle.

Epidemiological and evolutionary consequences of periodicity in treatment coverage

Host heterogeneity is a key driver of host–pathogen dynamics. In particular, the use of treatments against infectious diseases creates variation in quality among hosts, which can have both epidemiological and evolutionary consequences. We present a general theoretical model to highlight the consequences of different imperfect treatments on pathogen prevalence and evolution. These treatments differ in their action on host and pathogen traits. In contrast with previous studies, we assume that treatment coverage can vary in time, as in seasonal or pulsed treatment strategies. We show that periodic treatment strategies can limit both disease spread and virulence evolution, depending on the type of treatment. We also introduce a new method to analytically calculate the selection gradient in periodic environments, which allows our predictions to be interpreted using the concept of reproductive value, and can be applied more generally to analyse eco-evolutionary dynamics in class-structured populations and fluctuating environments.

Modeling host-associating microbes under selection

The concept of fitness is often reduced to a single component, such as the replication rate in a given habitat. For species with complex life cycles, this can be an unjustified oversimplification, as every step of the life cycle can contribute to reproductive success in a specific way. In particular, this applies to microbes that spend part of their life cycles associated to a host, i.e. in a microbiota. In this case, there is a selection pressure not only on the replication rates, but also on the phenotypic traits associated to migrating from the external environment to the host and vice-versa. Here, we investigate a simple model of a microbial population living, replicating, migrating and competing in and between two compartments: a host and its environment. We perform a sensitivity analysis on the global growth rate to determine the selection gradient experienced by the microbial population. We focus on the direction of selection at each point of the phenotypic space, defining an optimal way for the microbial population to increase its fitness. We show that microbes can adapt to the two-compartment life cycle through either changes in replication or migration rates, depending on the initial values of the traits, the initial distribution of the population across the compartments, the intensity of competition, and the time scales involved in the life cycle versus the time scale of adaptation (which determines the adequate probing time to measure fitness). Overall, our model provides a conceptual framework to study the selection on microbes experiencing a host-associated life cycle.

Misalignment of selection, plasticity, and among-individual variation: A test of theoretical predictions with Peromyscus maniculatus.

Genetic variation and phenotypic plasticity are predicted to align with selection surfaces, a prediction that has rarely been empirically tested. Understanding the relationship between sources of phenotypic variation, i.e. genetic variation and plasticity, with selection surfaces improves our ability to predict a population's ability to adapt to a changing environment and our understanding of how selection has shaped phenotypes. Here, we estimated the (co)variances among three different behaviors (activity, aggression, and anti-predator response) in a natural population of deer mice (Peromyscus maniculatus). Using multi-response generalized mixed effects models, we divided the phenotypic covariance matrix into among- and within-individual matrices. The among-individual covariances includes genetic and permanent environmental covariances (e.g. developmental plasticity) and is predicted to align with selection. Simultaneously, we estimated the within-individual (co)variances, which include reversible phenotypic plasticity. To determine whether genetic variation, plasticity and selection align in multivariate space we calculated the dimensions containing the greatest among-individual variation and the dimension in which most plasticity was expressed (i.e. the dominant eigenvector for the among- and within-individual covariance matrices respectively). We estimated selection coefficients based on survival estimates from a mark-recapture model. Alignment between the dominant eigenvectors of behavioural variation and the selection gradient was estimated by calculating the angle between them, with an angle of 0 indicating perfect alignment. The angle between vectors ranged from 68 to 89, indicating that genetic variation, phenotypic plasticity, and selection are misaligned in this population. This misalignment could be due to the behaviors being close to their fitness optima, which is supported by low evolvabilities, or because of low selection pressure on these behaviors.

Individual variability and versatility in an eco-evolutionary model of avian migration

Seasonal migration is a complex and variable behaviour with the potential to promote reproductive isolation. In Eurasian blackcaps ( Sylvia atricapilla ), a migratory divide in central Europe separating populations with southwest (SW) and southeast (SE) autumn routes may facilitate isolation, and individuals using new wintering areas in Britain show divergence from Mediterranean winterers. We tracked 100 blackcaps in the wild to characterize these strategies. Blackcaps to the west and east of the divide used predominantly SW and SE directions, respectively, but close to the contact zone many individuals took intermediate (S) routes. At 14.0° E, we documented a sharp transition from SW to SE migratory directions across only 27 (10–86) km, implying a strong selection gradient across the divide. Blackcaps wintering in Britain took northwesterly migration routes from continental European breeding grounds. They originated from a surprisingly extensive area, spanning 2000 km of the breeding range. British winterers bred in sympatry with SW-bound migrants but arrived 9.8 days earlier on the breeding grounds, suggesting some potential for assortative mating by timing. Overall, our data reveal complex variation in songbird migration and suggest that selection can maintain variation in migration direction across short distances while enabling the spread of a novel strategy across a wide range.

No evidence of male-biased sexual selection in a snake with conventional Darwinian sex roles

Decades of research on sexual selection have demonstrated that ‘conventional’ Darwinian sex roles are common in species with anisogamous gametes, with those species often exhibiting male-biased sexual selection. Yet, mating system characteristics such as long-term sperm storage and polyandry have the capacity to disrupt this pattern. Here, these ideas were explored by quantifying sexual selection metrics for the western diamond-backed rattlesnake ( Crotalus atrox ). A significant standardized sexual selection gradient was not found for males ( β SS = 0.588, p = 0.199) or females ( β SS = 0.151, p = 0.664), and opportunities for sexual selection ( I s ) and selection ( I ) did not differ between males ( I s = 0.069, I = 0.360) and females ( I s = 0.284, I = 0.424; both p > 0.05). Furthermore, the sexes did not differ in the maximum intensity of precopulatory sexual selection (males: s′ max = 0.155, females: s′ max = 0.080; p > 0.05). Finally, there was no evidence that male snout–vent length, a trait associated with mating advantage, is a target of sexual selection ( p > 0.05). These results suggest a lack of male-biased sexual selection in this population. Mating system characteristics that could erode male-biased sexual selection, despite the presence of conventional Darwinian sex roles, are discussed.

Evolution of flowering time in a selfing annual plant: Roles of adaptation and genetic drift

Resurrection studies are a useful tool to measure how phenotypic traits have changed in populations and they allow testing whether these traits modifications are a response to selection caused by an environmental change. Selfing, through its reduction of effective size, could challenge the ability of a population to adapt to environmental changes. Here, we used a resurrection study to test for adaptation in a selfing population of Medicago truncatula, by comparing the genetic composition and flowering across 22 generations. We found evidence for evolution towards earlier flowering times by about two days and a peculiar genetic structure, typical for highly selfing population, where some multilocus genotypes (MLGs) are persistent through time. We used the change in frequency of the MLGs through time as a multilocus fitness measure and built a selection gradient that suggests evolution towards earlier flowering times. Yet, a simulation model revealed that the observed change in flowering time could be explained by drift alone, provided the effective size of the population is small enough (<150). These analyses suffer from the difficulty to estimate the effective size in a highly selfing population, where effective recombination is severely reduced.

Competitive state of actions during planning predicts sequence execution accuracy

SummaryHumans can learn and retrieve novel skilled movement sequences from memory, yet the content and structure of sequence planning are not well understood. Previous computational and neurophysiological work suggests that actions in a sequence are planned as parallel graded activations and selected for output through competition (competitive queuing; CQ). However, the relevance of CQ during planning to sequence fluency and accuracy, as opposed to sequence timing, is unclear. To resolve this question, we assessed the competitive state of constituent actions behaviourally during sequence preparation. In three separate multi-session experiments, 55 healthy participants were trained to retrieve and produce 4-finger sequences with particular timing from long-term memory. In addition to sequence production, we evaluated reaction time (RT) and error rate increase to constituent action probes at several points during the preparation period. Our results demonstrate that longer preparation time produces a steeper CQ activation and selection gradient between adjacent sequence elements, whilst no effect was found for sequence speed or temporal structure. Further, participants with a steeper CQ gradient tended to produce correct sequences faster and with a higher temporal accuracy. In a computational model, we hypothesize that the CQ gradient during planning is driven by the width of acquired positional tuning of each sequential item, independently of timing. Our results suggest that competitive activation during sequence planning is established gradually during sequence planning and predicts sequence fluency and accuracy, rather than the speed or temporal structure of the motor sequence.HighlightsPre-ordering of actions during sequence planning can be assessed behaviourallyCompetitive gradient reflects sequence preparedness and skill, but not speed or timingGradient is retrieved rapidly and revealed during automatic action selectionPositional tuning of actions boosts the competitive gradient during planning