Geometric morphometrics is the statistical analysis of form based on Cartesian landmark coordinates. After separating shape from overall size, position, and orientation of the landmark configurations, the resulting Procrustes shape coordinates can be used for statistical analysis. Kendall shape space, the mathematical space induced by the shape coordinates, is a metric space that can be approximated locally by a Euclidean tangent space. Thus, notions of distance (similarity) between shapes or of the length and direction of developmental and evolutionary trajectories can be meaningfully assessed in this space. Results of statistical techniques that preserve these convenient properties—such as principal component analysis, multivariate regression, or partial least squares analysis—can be visualized as actual shapes or shape deformations. The Procrustes distance between a shape and its relabeled reflection is a measure of bilateral asymmetry. Shape space can be extended to form space by augmenting the shape coordinates with the natural logarithm of Centroid Size, a measure of size in geometric morphometrics that is uncorrelated with shape for small isotropic landmark variation. The thin-plate spline interpolation function is the standard tool to compute deformation grids and 3D visualizations. It is also central to the estimation of missing landmarks and to the semilandmark algorithm, which permits to include outlines and surfaces in geometric morphometric analysis. The powerful visualization tools of geometric morphometrics and the typically large amount of shape variables give rise to a specific exploratory style of analysis, allowing the identification and quantification of previously unknown shape features.
Linear discriminant analysis (LDA) is a multivariate classification technique frequently applied to morphometric data in various biomedical disciplines. Canonical variate analysis (CVA), the generalization of LDA for multiple groups, is often used in the exploratory style of an ordination technique (a low-dimensional representation of the data). In the rare case when all groups have the same covariance matrix, maximum likelihood classification can be based on these linear functions. Both LDA and CVA require full-rank covariance matrices, which is usually not the case in modern morphometrics. When the number of variables is close to the number of individuals, groups appear separated in a CVA plot even if they are samples from the same population. Hence, reliable classification and assessment of group separation require many more organisms than variables. A simple alternative to CVA is the projection of the data onto the principal components of the group averages (between-group PCA). In contrast to CVA, these axes are orthogonal and can be computed even when the data are not of full rank, such as for Procrustes shape coordinates arising in samples of any size, and when covariance matrices are heterogeneous. In evolutionary quantitative genetics, the selection gradient is identical to the coefficient vector of a linear discriminant function between the populations before vs. after selection. When the measured variables are Procrustes shape coordinates, discriminant functions and selection gradients are vectors in shape space and can be visualized as shape deformations. Except for applications in quantitative genetics and in classification, however, discriminant functions typically offer no interpretation as biological factors.
Short-term evolutionary potential depends on the additive genetic variance in the population. The additive variance is often measured as heritability, the fraction of the total phenotypic variance that is additive. Heritability is thus a common measure of evolutionary potential. An alternative is to measure evolutionary potential as expected proportional change under a unit strength of selection. This yields the mean-scaled additive variance as a measure of evolvability. Houle in Genetics 130:195–204, (1992) showed that these two ways of scaling additive variance are often inconsistent and can lead to different conclusions as to what traits are more evolvable. Here, we explore this relation in more detail through a literature review, and through theoretical arguments. We show that the correlation between heritability and evolvability is essentially zero, and we argue that this is likely due to inherent positive correlations between the additive variance and other components of phenotypic variance. This means that heritabilities are unsuitable as measures of evolutionary potential in natural populations. More generally we argue that scaling always involves non-trivial assumptions, and that a lack of awareness of these assumptions constitutes a systemic error in the field of evolutionary biology.
Organisms represent a complex arrangement of anatomical structures and individuated parts that must maintain functional associations through development. This integration of variation between functionally related body parts and the modular organization of development are fundamental determinants of their evolvability. This is because integration results in the expression of coordinated variation that can create preferred directions for evolutionary change, while modularity enables variation in a group of traits or regions to accumulate without deleterious effects on other aspects of the organism. Using our own work on both model systems (e.g., lab mice, avians) and natural populations of rodents and primates, we explore in this paper the relationship between patterns of phenotypic covariation and the developmental determinants of integration that those patterns are assumed to reflect. We show that integration cannot be reliably studied through phenotypic covariance patterns alone and argue that the relationship between phenotypic covariation and integration is obscured in two ways. One is the superimposition of multiple determinants of covariance in complex systems and the other is the dependence of covariation structure on variances in covariance-generating processes. As a consequence, we argue that the direct study of the developmental determinants of integration in model systems is necessary to fully interpret patterns of covariation in natural populations, to link covariation patterns to the processes that generate them, and to understand their significance for evolutionary explanation.
Many bivalvian mollusks have a sperm-transmitted mitochondrial genome (M), along with the standard egg-transmitted one (F). The phenomenon, known as doubly uniparental inheritance (DUI) of mtDNA, is the only known case in which biparental inheritance of a cytoplasmic genome is the rule rather than the exception. In the mussel Mytilus sperm mitochondria disperse randomly among blastomeres in female embryos, but form an aggregate and stay in the same blastomere in male embryos. In adults, somatic tissues of both sexes are dominated by the F genome. Sperm contains only the M genome and eggs the F (and perhaps traces of M). A female produces mostly daughters, mostly sons, or both sexes in about equal numbers, irrespective of its mate. Thus maleness and M mtDNA fate are tightly linked and under maternal control. Hybridization and triploidization affect the former but not the latter, which suggests that the two are not causally linked. Gene content and arrangement are the same in conspecific F and M genomes, but primary sequence has diverged from 20 % to 40 %, depending on species. The two genomes differ at the control region (CR). Synonymous substitutions accumulate faster in the M than the F genome and non-synonymous even faster. Expression studies indicate that the M genome is active only at spermatogenesis. These observations suggest that the M genome is under a more relaxed selective constraint than the F. Some mytilid species carry, in low frequencies, sperm-transmitted mtDNAs whose primary sequence is of the F type and the CR is an F/M mosaic (“masculinized” genomes). In venerids sperm mitochondria behavior, M genome fate and sex determination are as in mytilids. In unionids the M genome also evolves faster than the F and F/M sequence divergence reaches 50 %. The identification of F-specific and M-specific open reading frames in non-coding regions of unionids and mytilids, in conjunction with the CR’s mosaic structure of masculinized genomes, suggest that the mitochondrial genomes of species with DUI carry sequences that affect their transmission route. A model that incorporates these findings is presented in this review.
The last two decades have seen an explosion in research analysing cultural change as a Darwinian evolutionary process. Here I provide an overview of the theory of cultural evolution, including its intellectual history, major theoretical tenets and methods, key findings, and prominent criticisms and controversies. ‘Culture’ is defined as socially transmitted information. Cultural evolution is the theory that this socially transmitted information evolves in the manner laid out by Darwin in The Origin of Species, i.e. it comprises a system of variation, differential fitness and inheritance. Cultural evolution is not, however, neo-Darwinian, in that many of the details of genetic evolution may not apply, such as particulate inheritance and random mutation. Following a brief history of this idea, I review theoretical and empirical studies of cultural microevolution, which entails both selection-like processes wherein some cultural variants are more likely to be acquired and transmitted than others, plus transformative processes that alter cultural information during transmission. I also review how phylogenetic methods have been used to reconstruct cultural macroevolution, including the evolution of languages, technology and social organisation. Finally, I discuss recent controversies and debates, including the extent to which culture is proximate or ultimate, the relative role of selective and transformative processes in cultural evolution, the basis of cumulative cultural evolution, the evolution of large-scale human cooperation, and whether social learning is learned or innate. I conclude by highlighting the value of using evolutionary methods to study culture for both the social and biological sciences.
Understanding the rate at which new species form is a key question in studying the evolution of life on earth. Here we review our current understanding of speciation rates, focusing on studies based on the fossil record, phylogenies, and mathematical models. We find that speciation rates estimated from these different studies can be dramatically different: some studies find that new species form quickly and often, while others find that new species form much less frequently. We suggest that instead of being contradictory, differences in speciation rates across different scales can be reconciled by a common model. Under the “ephemeral speciation model”, speciation is very common and very rapid but the new species produced almost never persist. Evolutionary studies should therefore focus on not only the formation but also the persistence of new species.
Morphological integration refers to the modular structuring of inter-trait relationships in an organism, which could bias the direction and rate of morphological change, either constraining or facilitating evolution along certain dimensions of the morphospace. Therefore, the description of patterns and magnitudes of morphological integration and the analysis of their evolutionary consequences are central to understand the evolution of complex traits. Here we analyze morphological integration in the skull of several mammalian orders, addressing the following questions: are there common patterns of inter-trait relationships? Are these patterns compatible with hypotheses based on shared development and function? Do morphological integration patterns and magnitudes vary in the same way across groups? We digitized more than 3,500 specimens spanning 15 mammalian orders, estimated the correspondent pooled within-group correlation and variance/covariance matrices for 35 skull traits and compared those matrices among the orders. We also compared observed patterns of integration to theoretical expectations based on common development and function. Our results point to a largely shared pattern of inter-trait correlations, implying that mammalian skull diversity has been produced upon a common covariance structure that remained similar for at least 65 million years. Comparisons with a rodent genetic variance/covariance matrix suggest that this broad similarity extends also to the genetic factors underlying phenotypic variation. In contrast to the relative constancy of inter-trait correlation/covariance patterns, magnitudes varied markedly across groups. Several morphological modules hypothesized from shared development and function were detected in the mammalian taxa studied. Our data provide evidence that mammalian skull evolution can be viewed as a history of inter-module parcellation, with the modules themselves being more clearly marked in those lineages with lower overall magnitude of integration. The implication of these findings is that the main evolutionary trend in the mammalian skull was one of decreasing the constraints to evolution by promoting a more modular architecture.
Approaches to macroevolution require integration of its two fundamental components, within a hierarchical framework. Following a companion paper on the origin of variation, I here discuss sorting within an evolutionary hierarchy. Species sorting—sometimes termed species selection in the broad sense, meaning differential origination and extinction owing to intrinsic biological properties—can be split into strict-sense species selection, in which rate differentials are governed by emergent, species-level traits such as geographic range size, and effect macroevolution, in which rates are governed by organism-level traits such as body size; both processes can create hitchhiking effects, indirectly causing the proliferation or decline of other traits. Several methods can operationalize the concept of emergence, so that rigorous separation of these processes is increasingly feasible. A macroevolutionary tradeoff, underlain by the intrinsic traits that influence evolutionary dynamics, causes speciation and extinction rates to covary in many clades, resulting in evolutionary volatility of some clades and more subdued behavior of others; the few clades that break the tradeoff can achieve especially prolific diversification. In addition to intrinsic biological traits at multiple levels, extrinsic events can drive the waxing and waning of clades, and the interaction of traits and events are difficult but important to disentangle. Evolutionary trends can arise in many ways, and at any hierarchical level; descriptive models can be fitted to clade trajectories in phenotypic or functional spaces, but they may not be diagnostic regarding processes, and close attention must be paid to both leading and trailing edges of apparent trends. Biotic interactions can have negative or positive effects on taxonomic diversity within a clade, but cannot be readily extrapolated from the nature of such interactions at the organismic level. The relationships among macroevolutionary currencies through time (taxonomic richness, morphologic disparity, functional variety) are crucial for understanding the nature of evolutionary diversification. A novel approach to diversity-disparity analysis shows that taxonomic diversifications can lag behind, occur in concert with, or precede, increases in disparity. Some overarching issues relating to both the origin and sorting of clades and phenotypes include the macroevolutionary role of mass extinctions, the potential differences between plant and animal macroevolution, whether macroevolutionary processes have changed through geologic time, and the growing human impact on present-day macroevolution. Many challenges remain, but progress is being made on two of the key ones: (a) the integration of variation-generating mechanisms and the multilevel sorting processes that act on that variation, and (b) the integration of paleontological and neontological approaches to historical biology.
Approaches to macroevolution require integration of its two fundamental components, i.e. the origin and the sorting of variation, in a hierarchical framework. Macroevolution occurs in multiple currencies that are only loosely correlated, notably taxonomic diversity, morphological disparity, and functional variety. The origin of variation within this conceptual framework is increasingly understood in developmental terms, with the semi-hierarchical structure of gene regulatory networks (GRNs, used here in a broad sense incorporating not just the genetic circuitry per se but the factors controlling the timing and location of gene expression and repression), the non-linear relation between magnitude of genetic change and the phenotypic results, the evolutionary potential of co-opting existing GRNs, and developmental responsiveness to nongenetic signals (i.e. epigenetics and plasticity), all requiring modification of standard microevolutionary models, and rendering difficult any simple definition of evolutionary novelty. The developmental factors underlying macroevolution create anisotropic probabilities—i.e., an uneven density distribution—of evolutionary change around any given phenotypic starting point, and the potential for coordinated changes among traits that can accommodate change via epigenetic mechanisms. From this standpoint, “punctuated equilibrium” and “phyletic gradualism” simply represent two cells in a matrix of evolutionary models of phenotypic change, and the origin of trends and evolutionary novelty are not simply functions of ecological opportunity. Over long timescales, contingency becomes especially important, and can be viewed in terms of macroevolutionary lags (the temporal separation between the origin of a trait or clade and subsequent diversification); such lags can arise by several mechanisms: as geological or phylogenetic artifacts, or when diversifications require synergistic interactions among traits, or between traits and external events. The temporal and spatial patterns of the origins of evolutionary novelties are a challenge to macroevolutionary theory; individual events can be described retrospectively, but a general model relating development, genetics, and ecology is needed. An accompanying paper (Jablonski in Evol Biol 2017) reviews diversity dynamics and the sorting of variation, with some general conclusions.
The origin of novelty is a critical subject for evolutionary biologists. Early geneticists speculated about the sudden appearance of new species via special macromutations, epitomized by Goldschmidt’s infamous “hopeful monster”. Although these ideas were easily dismissed by the insights of the Modern Synthesis, a lingering fascination with the possibility of sudden, dramatic change has persisted. Recent work on hybridization and gene exchange suggests an underappreciated mechanism for the sudden appearance of evolutionary novelty that is entirely consistent with the principles of modern population genetics. Genetic recombination in hybrids can produce transgressive phenotypes, “monstrous” phenotypes beyond the range of parental populations. Transgressive phenotypes can be products of epistatic interactions or additive effects of multiple recombined loci. We compare several epistatic and additive models of transgressive segregation in hybrids and find that they are special cases of a general, classic quantitative genetic model. The Dobzhansky-Muller model predicts “hopeless” monsters, sterile and inviable transgressive phenotypes. The Bateson model predicts “hopeful” monsters with fitness greater than either parental population. The complementation model predicts both. Transgressive segregation after hybridization can rapidly produce novel phenotypes by recombining multiple loci simultaneously. Admixed populations will also produce many similar recombinant phenotypes at the same time, increasing the probability that recombinant “hopeful monsters” will establish true-breeding evolutionary lineages. Recombination is not the only (or even most common) process generating evolutionary novelty, but might be the most credible mechanism for sudden appearance of new forms.
Insights into morphological diversification can be obtained from the ways the species of a clade occupy morphospace. Projecting a phylogeny into morphospace provides estimates of evolutionary trajectories as lineages diversified information that can be used to infer the dynamics of evolutionary processes that produced patterns of morphospace occupation. We present here a large-scale investigation into evolution of morphological variation in the skull of caecilian amphibians, a major clade of vertebrates. Because caecilians are limbless, predominantly fossorial animals, diversification of their skull has occurred within a framework imposed by the functional demands of head-first burrowing. We examined cranial shape in 141 species, over half of known species, using X-ray computed tomography and geometric morphometrics. Mapping an existing phylogeny into the cranial morphospace to estimate the history of morphological change (phylomorphospace), we find a striking pattern: most species occupy distinct clusters in cranial morphospace that closely correspond to the main caecilian clades, and each cluster is separated by unoccupied morphospace. The empty spaces in shape space are unlikely to be caused entirely by extinction or incomplete sampling. The main caecilian clades have different amounts of morphological disparity, but neither clade age nor number of species account for this variation. Cranial shape variation is clearly linked to phyletic divergence, but there is also homoplasy, which is attributed to extrinsic factors associated with head-first digging: features of caecilian crania that have been previously argued to correlate with differential microhabitat use and burrowing ability, such as subterminal and terminal mouths, degree of temporal fenestration (stegokrotaphy/zygokrotaphy), and eyes covered by bone, have evolved and many combinations occur in modern species. We find evidence of morphological convergence in cranial shape, among species that have eyes covered by bone, resulting in a narrow bullet-shaped head. These results reveal a complex history, including early expansion of morphospace and both divergent and convergent evolution resulting in the diversity we observe today.
Until 30 years ago, the emphasis on reproductive costs for males was mainly on costs related to mate searching, courtship and fighting with rival males. However, costs for males are substantial and varied and often resemble the more thoroughly studied female reproductive costs. Costs can be referred to as trade-off costs, where investment in reproductive activity comes at the expense of another important activity or fitness component. Investment in reproduction at the expense of longevity and future reproduction is the ultimate cost, because it affects fitness directly. In contrast, flawed performance (e.g., of the immune system) is perceived as a mechanistic trade-off, because it affects fitness indirectly through a mediator (i.e., parasites). Finally, direct costs refer to direct measurements of the energy expenditure during involvement in reproduction-related activities. Both direct and mechanistic trade-off costs often result in decreased longevity compared to unmated males (an ultimate cost). Males incur costs during different reproductive phases: before copulation, when producing sperm, while searching for, courting and copulating with females, and subsequently when guarding females or taking care of offspring. This synthesis follows previous pioneering reviews addressing specific aspects of male costs, but strives to summarize all known male reproductive cost types more comprehensively, including their classification. We suggest several directions for targeted future research. While costs for males have been fairly well described, it is now necessary to uncover the ecological and evolutionary factors responsible for differences between closely related species and systems and to better link between directly-measured costs, mechanistic trade-off costs and ultimate trade-off costs.
The diet of organisms generally provides a sufficient supply of energy and building materials for healthy growth and development, but should also contain essential nutrients. Species differ in their exogenous requirements, but it is not clear why some species are able to synthesize essential nutrients, while others are not. The unsaturated fatty acid, linoleic acid (LA; 18:2n-6) plays an important role in functions such as cell physiology, immunity, and reproduction, and is an essential nutrient in diverse organisms. LA is readily synthesized in bacteria, protozoa and plants, but it was long thought that all animals lacked the ability to synthesize LA de novo and thus required a dietary source of this fatty acid. Over the years, however, an increasing number of studies have shown active LA synthesis in animals, including insects, nematodes and pulmonates. Despite continued interest in LA metabolism, it has remained unclear why some organisms can synthesize LA while others cannot. Here, we review the mechanisms by which LA is synthesized and which biological functions LA supports in different organisms to answer the question why LA synthesis was lost and repeatedly gained during the evolution of distinct invertebrate groups. We propose several hypotheses and compile data from the available literature to identify which factors promote LA synthesis within a phylogenetic framework. We have not found a clear link between our proposed hypotheses and LA synthesis; therefore we suggest that LA synthesis may be facilitated through bifunctionality of desaturase enzymes or evolved through a combination of different selective pressures.
The biologist examining samples of multicellular organisms in anatomical detail must already have an intuitive concept of morphological integration. But quantifying that intuition has always been fraught with difficulties and paradoxes, especially for the anatomically labelled Cartesian coordinate data that drive today’s toolkits of geometric morphometrics. Covariance analyses of interpoint distances, such as the Olson–Miller factor approach of the 1950’s, cannot validly be extended to handle the spatial structure of complete morphometric descriptions; neither can analyses of shape coordinates that ignore the mean form. This paper introduces a formal parametric quantification of integration by analogy with how time series are approached in modern paleobiology. Over there, a finding of trend falls under one tail of a distribution for which stasis comprises the other tail. The null hypothesis separating these two classes of finding is the random walks, which are self-similar, meaning that they show no interpretable structure at any temporal scale. Trend and stasis are the two contrasting ways of deviating from this null. The present manuscript introduces an analogous maneuver for the spatial aspects of ontogenetic or phylogenetic organismal studies: a subspace within the space of shape covariance structures for which the standard isotropic (Procrustes) model lies at one extreme of a characteristic parameter and the strongest growth-gradient models at the other. In-between lies the suggested new construct, the spatially self-similar processes that can be generated within the standard morphometric toolkit by a startlingly simple algebraic manipulation of partial warp scores. In this view, integration and “disintegration” as in the Procrustes model are two modes of organismal variation according to which morphometric data can deviate from this common null, which, as in the temporal domain, is formally featureless, incapable of supporting any summary beyond a single parameter for amplitude. In practice the classification can proceed by examining the regression coefficient for log partial warp variance against log bending energy in the standard thin-plate spline setup. The self-similarity model, for which the regression slope is precisely $$-1,$$ - 1 , corresponds well to the background against which the evolutionist’s or systematist’s a-priori notion of “local shape features” can be delineated. Integration as detected by the regression slope can be visualized by the first relative intrinsic warp (first relative eigenvector of the nonaffine part of a shape coordinate configuration with respect to bending energy) and may be summarized by the corresponding quadratic growth gradient. The paper begins with a seemingly innocent toy example, uncovers an unexpected invariance as an example of the general manipulation proposed, then applies the new modeling tactic to three data sets from the existing morphometric literature. Conclusions follow regarding findings and methodology alike.
Recent calls for a revision of standard evolutionary theory (SET) are based partly on arguments about the reciprocal causation. Reciprocal causation means that cause–effect relationships are bi-directional, as a cause could later become an effect and vice versa. Such dynamic cause-effect relationships raise questions about the distinction between proximate and ultimate causes, as originally formulated by Ernst Mayr. They have also motivated some biologists and philosophers to argue for an Extended Evolutionary Synthesis (EES). The EES will supposedly expand the scope of the Modern Synthesis (MS) and SET, which has been characterized as gene-centred, relying primarily on natural selection and largely neglecting reciprocal causation. Here, I critically examine these claims, with a special focus on the last conjecture. I conclude that reciprocal causation has long been recognized as important by naturalists, ecologists and evolutionary biologists working in the in the MS tradition, although it it could be explored even further. Numerous empirical examples of reciprocal causation in the form of positive and negative feedback are now well known from both natural and laboratory systems. Reciprocal causation have also been explicitly incorporated in mathematical models of coevolutionary arms races, frequency-dependent selection, eco-evolutionary dynamics and sexual selection. Such dynamic feedback were already recognized by Richard Levins and Richard Lewontin in their bok The Dialectical Biologist. Reciprocal causation and dynamic feedback might also be one of the few contributions of dialectical thinking and Marxist philosophy in evolutionary theory. I discuss some promising empirical and analytical tools to study reciprocal causation and the implications for the EES. Finally, I briefly discuss how quantitative genetics can be adapated to studies of reciprocal causation, constructive inheritance and phenotypic plasticity and suggest that the flexibility of this approach might have been underestimated by critics of contemporary evolutionary biology.
Studies of morphological integration and modularity are a hot topic in evolutionary developmental biology. Geometric morphometrics using Procrustes methods offers powerful tools to quantitatively investigate morphological variation and, within this methodological framework, a number of different methods has been put forward to test if different regions within an anatomical structure behave like modules or, vice versa, are highly integrated and covary strongly. Although some exploratory techniques do not require a priori modules, commonly modules are specified in advance based on prior knowledge. Once this is done, most of the methods can be applied either by subdividing modules and performing separate Procrustes alignments or by splitting shape coordinates of anatomical landmarks into modules after a common superimposition. This second approach is particularly interesting because, contrary to completely separate blocks analyses, it preserves information on relative size and position of the putative modules. However, it also violates one of the fundamental assumptions on which Procrustes methods are based, which is that one should not analyse or interpret subsets of landmarks from a common superimposition, because the choice of that superimposition is purely based on statistical convenience (although with sound theoretical foundations) and not on a biological model of variance and covariance. In this study, I offer a first investigation of the effects of testing integration and modularity within a configuration of commonly superimposed landmarks using some of the most widely employed statistical methods available to this aim. When applied to simulated shapes with random non-modular isotropic variation, standard methods frequently recovered significant but arbitrary patterns of integration and modularity. Re-superimposing landmarks within each module, before testing integration or modularity, generally removes this artifact. The study, although preliminary and exploratory in nature, raises an important issue and indicates an avenue for future research. It also suggests that great caution should be exercised in the application and interpretation of findings from analyses of modularity and integration using Procrustes shape data, and that issues might be even more serious using some of the most common methods for handling the increasing popular semilandmark data used to analyse 2D outlines and 3D surfaces.
The mechanisms of variation, selection and inheritance, on which evolution by natural selection depends, are not fixed over evolutionary time. Current evolutionary biology is increasingly focussed on understanding how the evolution of developmental organisations modifies the distribution of phenotypic variation, the evolution of ecological relationships modifies the selective environment, and the evolution of reproductive relationships modifies the heritability of the evolutionary unit. The major transitions in evolution, in particular, involve radical changes in developmental, ecological and reproductive organisations that instantiate variation, selection and inheritance at a higher level of biological organisation. However, current evolutionary theory is poorly equipped to describe how these organisations change over evolutionary time and especially how that results in adaptive complexes at successive scales of organisation (the key problem is that evolution is self-referential, i.e. the products of evolution change the parameters of the evolutionary process). Here we first reinterpret the central open questions in these domains from a perspective that emphasises the common underlying themes. We then synthesise the findings from a developing body of work that is building a new theoretical approach to these questions by converting well-understood theory and results from models of cognitive learning. Specifically, connectionist models of memory and learning demonstrate how simple incremental mechanisms, adjusting the relationships between individually-simple components, can produce organisations that exhibit complex system-level behaviours and improve the adaptive capabilities of the system. We use the term “evolutionary connectionism” to recognise that, by functionally equivalent processes, natural selection acting on the relationships within and between evolutionary entities can result in organisations that produce complex system-level behaviours in evolutionary systems and modify the adaptive capabilities of natural selection over time. We review the evidence supporting the functional equivalences between the domains of learning and of evolution, and discuss the potential for this to resolve conceptual problems in our understanding of the evolution of developmental, ecological and reproductive organisations and, in particular, the major evolutionary transitions.
Changes in patterns and magnitudes of integration may influence the ability of a species to respond to selection. Consequently, modularity has often been linked to the concept of evolvability, but their relationship has rarely been tested empirically. One possible explanation is the lack of analytical tools to compare patterns and magnitudes of integration among diverse groups that explicitly relate these aspects to the quantitative genetics framework. We apply such framework here using the multivariate response to selection equation to simulate the evolutionary behavior of several mammalian orders in terms of their flexibility, evolvability and constraints in the skull. We interpreted these simulation results in light of the integration patterns and magnitudes of the same mammalian groups, described in a companion paper. We found that larger magnitudes of integration were associated with a blur of the modules in the skull and to larger portions of the total variation explained by size variation, which in turn can exert a strong evolutionary constraint, thus decreasing the evolutionary flexibility. Conversely, lower overall magnitudes of integration were associated with distinct modules in the skull, to smaller fraction of the total variation associated with size and, consequently, to weaker constraints and more evolutionary flexibility. Flexibility and constraints are, therefore, two sides of the same coin and we found them to be quite variable among mammals. Neither the overall magnitude of morphological integration, the modularity itself, nor its consequences in terms of constraints and flexibility, were associated with absolute size of the organisms, but were strongly associated with the proportion of the total variation in skull morphology captured by size. Therefore, the history of the mammalian skull is marked by a trade-off between modularity and evolvability. Our data provide evidence that, despite the stasis in integration patterns, the plasticity in the magnitude of integration in the skull had important consequences in terms of evolutionary flexibility of the mammalian lineages.
The evolution of senescence is often explained by arguing that, in nature, few individuals survive to be old and hence it is evolutionarily unimportant what happens to organisms when they are old. A corollary to this idea is that extrinsically imposed mortality, because it reduces the chance of surviving to be old, favors the evolution of senescence. We show that these ideas, although widespread, are incorrect. Selection leading to senescence does not depend directly on survival to old age, but on the shape of the stable age distribution, and we discuss the implications of this important distinction. We show that the selection gradient on mortality declines with age even in the hypothetical case of zero mortality, when survivorship does not decline. Changing the survivorship function by imposing age independent mortality has no affect on the selection gradients. A similar result exists for optimization models: age independent mortality does not change the optimal result. We propose an alternative, brief explanation for the decline of selection gradients, and hence the evolution of senescence.