Breakdown of brain–body allometry and the encephalization of birds and mammals

Thought for food: the endothermic brain hypothesis

The evolution of whole-body endothermy occurred independently in dinosaurs and mammals and was associated with some of the most significant neurocognitive shifts in life's history. These included a 20-fold increase in neurons and the evolution of new brain structures, supporting similar functions in both lineages. We propose the endothermic brain hypothesis, which holds that elaborations in endotherm brains were geared towards increasing caloric intake through efficient foraging. The hypothesis is grounded in the intrinsic coupling of cognition and organismic self-maintenance. We argue that coevolution of increased metabolism and new forms of cognition should be jointly investigated in comparative studies of behaviors and brain anatomy, along with studies of fossil species. We suggest avenues for such research and highlight critical open questions.

Multi-scaling allometry in human development, mammalian morphology, and tree growth

Various animal and plant species exhibit allometric relationships among their respective traits, wherein one trait undergoes expansion as a power-law function of another due to constraints acting on growth processes. For instance, the acknowledged consensus posits that tree height scales with the two-thirds power of stem diameter. In the context of human development, it is posited that body weight scales with the second power of height. This prevalent allometric relationship derives its nomenclature from fitting two variables linearly within a logarithmic framework, thus giving rise to the term "power-law relationship." Here, we challenge the conventional assumption that a singular power-law equation adequately encapsulates the allometric relationship between any two traits. We strategically leverage quantile regression analysis to demonstrate that the scaling exponent characterizing this power-law relationship is contingent upon the centile within these traits' distributions. This observation fundamentally underscores the proposition that individuals occupying disparate segments of the distribution may employ distinct growth strategies, as indicated by distinct power-law exponents. We introduce the innovative concept of "multi-scale allometry" to encapsulate this newfound insight. Through a comprehensive reevaluation of (i) the height-weight relationship within a cohort comprising 7, 863, 520 Japanese children aged 5-17 years for which the age, sex, height, and weight were recorded as part of a national study, (ii) the stem-diameter-height and crown-radius-height relationships within an expansive sample of 498, 838 georeferenced and taxonomically standardized records of individual trees spanning diverse geographical locations, and (iii) the brain-size-body-size relationship within an extensive dataset encompassing 1, 552 mammalian species, we resolutely substantiate the viability of multi-scale allometric analysis. This empirical substantiation advocates a paradigm shift from uni-scaling to multi-scaling allometric modeling, thereby affording greater prominence to the inherent growth processes that underlie the morphological diversity evident throughout the living world.

Endocranial shape variation and allometry in Euarchontoglires

While brain size in primates and their relatives within Euarchontoglires is well-studied, less research has examined brain shape, or the allometric trajectories that underlie the relationship between size and shape. Defining these patterns is key to understanding evolutionary trends. 3D geometric morphometric analyses of endocranial shape were performed on 140 species of extant euarchontoglirans using digital cranial endocasts. Principal component analyses on Procrustes shape variables show a clear phylogenetic pattern in endocranial shape, supported by an ANOVA which identified significant differences in shape among several groups (e.g., Platyrrhini, Strepsirrhini, Scandentia, Rodentia, and Lagomorpha). ANOVAs of shape and size also indicate that allometry has a small but significant impact on endocranial shape across Euarchontoglires, with homogeneity of slopes tests finding significant differences in the scaling relationship between shape and size among these same groups. While most of these clades possess a distinct endocranial morphotype, the highly derived platyrrhines display the strongest relationship between size and shape. Rodents show the most diversity in endocranial shape, potentially attributed to their comparatively weak relationship between shape and size. These results suggest fundamental differences in how shape and size covary among Euarchontoglires, which may have facilitated the adaptive radiations that characterize members of this group.

Co-evolutionary dynamics of mammalian brain and body size

Despite decades of comparative studies, puzzling aspects of the relationship between mammalian brain and body mass continue to defy satisfactory explanation. Here we show that several such aspects arise from routinely fitting log-linear models to the data: the correlated evolution of brain and body mass is in fact log-curvilinear. This simultaneously accounts for several phenomena for which diverse biological explanations have been proposed, notably variability in scaling coefficients across clades, low encephalization in larger species and the so-called taxon-level problem. Our model implies a need to revisit previous findings about relative brain mass. Accounting for the true scaling relationship, we document dramatically varying rates of relative brain mass evolution across the mammalian phylogeny, and we resolve the question of whether there is an overall trend for brain mass to increase through time. We find a trend in only three mammalian orders, which is by far the strongest in primates, setting the stage for the uniquely rapid directional increase ultimately producing the computational powers of the human brain.

The reduction in relative brain size in the domesticated dog is not an evolutionary singularity among the canids

Domestication has long been considered the most powerful evolutionary engine behind dramatic reductions in brain size in several taxa, and the dog (Canis familiaris) is considered as a typical example that shows a substantial decrease in brain size relative to its ancestor, the grey wolf (Canis lupus). However, to make the case for exceptional evolution of reduced brain size under domestication requires an interspecific approach in a phylogenetic context that can quantify the extent by which domestication reduces brain size in comparison to closely related non-domesticated species responding to different selection factors in the wild. Here, we used a phylogenetic method to identify evolutionary singularities to test if the domesticated dog stands out in terms of relative brain size from other species of canids. We found that the dog does not present unambiguous signature of evolutionary singularity with regard to its small brain size, as the results were sensitive to the considerations about the ancestral trait values upon domestication. However, we obtained strong evidence for the hibernating common raccoon dog (Nyctereutes procyonoides) being an evolutionary outlier for its brain size. Therefore, domestication is not necessarily an exceptional case concerning evolutionary reductions in brain size in an interspecific perspective.

Evolutionary-developmental (evo-devo) dynamics of hominin brain size

Brain size tripled in the human lineage over four million years, but why this occurred remains uncertain. Here, to study what caused this brain expansion, I mathematically model the evolutionary and developmental (evo-devo) dynamics of hominin brain size. The model recovers (1) the evolution of brain and body sizes of seven hominin species starting from brain and body sizes of the australopithecine scale, (2) the evolution of the hominin brain-body allometry and (3) major patterns of human development and evolution. I show that the brain expansion recovered is not caused by direct selection for brain size but by its genetic correlation with developmentally late preovulatory ovarian follicles. This correlation is generated over development if individuals experience a challenging ecology and seemingly cumulative culture, among other conditions. These findings show that the evolution of exceptionally adaptive traits may not be primarily caused by selection for them but by developmental constraints that divert selection.

Light conditions and the evolution of the visual system in birds

Despite vision being an essential sense for many animals, the intuitively appealing notion that the visual system has been shaped by environmental light conditions is backed by insufficient evidence. Based on a comprehensive phylogenetic comparative analysis of birds, we investigate if exposure to different light conditions might have triggered evolutionary divergence in the visual system through pressures on light sensitivity, visual acuity, and neural processing capacity. Our analyses suggest that birds that have adopted nocturnal habits evolved eyes with larger corneal diameters and, to a lesser extent, longer axial length than diurnal species. However, we found no evidence that sensing and processing organs were selected together, as observed in diurnal birds. Rather than enlarging the processing centers, we found a tendency among nocturnal species to either reduce or maintain the size of the two main brain centers involved in vision-the optic tectum and the wulst. These results suggest a mosaic pattern of evolution, wherein optimization of the eye optics for efficient light capture in nocturnal species may have compromised visual acuity and central processing capacity.

Smarter foragers do not forage smarter: a test of the diet hypothesis for brain expansion

A leading hypothesis for the evolution of large brains in humans and other species is that a feedback loop exists whereby intelligent animals forage more efficiently, which results in increased energy intake that fuels the growth and maintenance of large brains. We test this hypothesis for the first time with high-resolution tracking data from four sympatric, frugivorous rainforest mammal species (42 individuals) and drone-based maps of their predominant feeding trees. We found no evidence that larger-brained primates had more efficient foraging paths than smaller brained procyonids. This refutes a key assumption of the fruit-diet hypothesis for brain evolution, suggesting that other factors such as temporal cognition, extractive foraging or sociality have been more important for brain evolution.

The Role of (Co)variation in Shaping the Response to Selection in New World Leaf-Nosed Bats

AbstractUnderstanding and predicting the evolutionary responses of complex morphological traits to selection remains a major challenge in evolutionary biology. Because traits are genetically correlated, selection on a particular trait produces both direct effects on the distribution of that trait and indirect effects on other traits in the population. The correlations between traits can strongly impact evolutionary responses to selection and may thus impose constraints on adaptation. Here, we used museum specimens and comparative quantitative genetic approaches to investigate whether the covariation among cranial traits facilitated or constrained the response to selection during the major dietary transitions in one of the world's most ecologically diverse mammalian families-the phyllostomid bats. We reconstructed the set of net selection gradients that would have acted on each cranial trait during the major transitions to feeding specializations and decomposed the selection responses into their direct and indirect components. We found that for all transitions, most traits capturing craniofacial length evolved toward adaptive directions owing to direct selection. Additionally, we showed instances of dietary transitions in which the complex interaction between the patterns of covariation among traits and the strength and direction of selection either constrained or facilitated evolution. Our work highlights the importance of considering the within-species covariation estimates to quantify evolvability and to disentangle the relative contribution of variational constraints versus selective causes for observed patterns.

Different ways of evolving tool-using brains in teleosts and amniotes

In mammals and birds, tool-using species are characterized by their relatively large telencephalon containing a higher proportion of total brain neurons compared to other species. Some teleost species in the wrasse family have evolved tool-using abilities. In this study, we compared the brains of tool-using wrasses with various teleost species. We show that in the tool-using wrasses, the telencephalon and the ventral part of the forebrain and midbrain are significantly enlarged compared to other teleost species but do not contain a larger proportion of cells. Instead, this size difference is due to large fiber tracts connecting the dorsal part of the telencephalon (pallium) to the inferior lobe, a ventral mesencephalic structure absent in amniotes. The high degree of connectivity between these structures in tool-using wrasses suggests that the inferior lobe could contribute to higher-order cognitive functions. We conclude that the evolution of non-telencephalic structures might have been key in the emergence of these cognitive functions in teleosts.

Ontogenetic skull variation in a shovel-headed amphisbaenian species

Leposternon microcephalum is a species belonging to the Amphisbaenia, a group of burrowing reptiles. Amphisbaenia present various morphological and physiological adaptations that allow them to penetrate the ground and live underground, through a system of galleries and permanent chambers that they build themselves. Among the morphological adaptations in this group, those of the skull stand out as it serves as the main excavation tool. Four basic skull shapes are recognized: rounded, keeled, shovel-shaped, and spade-shaped. The skull of L. microcephalum belongs to this last type, which is considered the most specialized. The species inhabits soils that are highly compacted and difficult to penetrate. Among the species of Leposternon present in South America, L. microcephalum has the widest distribution, being found in all Brazilian biomes and neighboring countries such as Bolivia, Argentina, Paraguay, and Uruguay. The analysis of the skull of this species was carried out using three-dimensional geometric morphometrics (3D-GMM), a technique that allows comparative analysis, through robust statistical methods, of shape and its variations, using Cartesian coordinate data from a configuration of homologous landmarks. The technique allows the size and shape components of a structure to be analyzed separately. From an ontogenetic point of view, this methodology had also been used to investigate variations in Cynisca leucura, a member of the Amphisbaenidae with a rounded head. Our hypothesis is that the patterns of morphological differentiation in the skull, mainly in the intermediate and occipital regions, are similar in different Amphisbaenia species. Therefore, the objective of this study was to analyze cranial morphological variations in an ontogenetic series of L. microcephalum using 3D-GMM. Computed Tomographic scans of 13 specimens were analyzed: juveniles (N = 8) and adults (N = 5), based on 20 landmarks that characterize the skull. Principal components and regression analyses between shape (dependent variable) and size (independent variable) showed a clear difference between the cranial morphological pattern of juvenile individuals and that of adults. For instance, young specimens tend to have a dorsoventrally tall neurocranium, with the tip of the snout more anteriorly oriented and its dorsal border subtly curved. Dorsally, the parietal region is thicker and smoothly dome-shaped in juveniles. As in C. leucura, the variation was strongly correlated with the size change from juvenile to adult, indicating a dominant role for ontogenetic allometry in determining skull shape.

Innovation and elaboration on the avian tree of life

Widely documented, megaevolutionary jumps in phenotypic diversity continue to perplex researchers because it remains unclear whether these marked changes can emerge from microevolutionary processes. Here, we tackle this question using new approaches for modeling multivariate traits to evaluate the magnitude and distribution of elaboration and innovation in the evolution of bird beaks. We find that elaboration, evolution along the major axis of phenotypic change, is common at both macro- and megaevolutionary scales, whereas innovation, evolution away from the major axis of phenotypic change, is more prominent at megaevolutionary scales. The major axis of phenotypic change among species beak shapes at megaevolutionary scales is an emergent property of innovation across clades. Our analyses suggest that the reorientation of phenotypes via innovation is a ubiquitous route for divergence that can arise through gradual change alone, opening up further avenues for evolution to explore.

American crows that excel at tool use activate neural circuits distinct from less talented individuals

Tools enable animals to exploit and command new resources. However, the neural circuits underpinning tool use and how neural activity varies with an animal's tool proficiency, are only known for humans and some other primates. We use 18F-fluorodeoxyglucose positron emission tomography to image the brain activity of naïve vs trained American crows (Corvus brachyrhynchos) when presented with a task requiring the use of stone tools. As in humans, talent affects the neural circuits activated by crows as they prepare to execute the task. Naïve and less proficient crows use neural circuits associated with sensory- and higher-order processing centers (the mesopallium and nidopallium), while highly proficient individuals increase activity in circuits associated with motor learning and tactile control (hippocampus, tegmentum, nucleus basorostralis, and cerebellum). Greater proficiency is found primarily in adult female crows and may reflect their need to use more cognitively complex strategies, like tool use, to obtain food.

Body size and life history shape the historical biogeography of tetrapods

Dispersal across biogeographic barriers is a key process determining global patterns of biodiversity as it allows lineages to colonize and diversify in new realms. Here we demonstrate that past biogeographic dispersal events often depended on species' traits, by analysing 7,009 tetrapod species in 56 clades. Biogeographic models incorporating body size or life history accrued more statistical support than trait-independent models in 91% of clades. In these clades, dispersal rates increased by 28-32% for lineages with traits favouring successful biogeographic dispersal. Differences between clades in the effect magnitude of life history on dispersal rates are linked to the strength and type of biogeographic barriers and intra-clade trait variability. In many cases, large body sizes and fast life histories facilitate dispersal success. However, species with small bodies and/or slow life histories, or those with average traits, have an advantage in a minority of clades. Body size-dispersal relationships were related to a clade's average body size and life history strategy. These results provide important new insight into how traits have shaped the historical biogeography of tetrapod lineages and may impact present-day and future biogeographic dispersal.

Differential growth of the adductor muscles, eyeball, and brain in the chick Gallus gallus with comments on the fossil record of stem-group birds

The avian head is unique among living reptiles in its combination of relatively large brain and eyes, coupled with relatively small adductor jaw muscles. These derived proportions lend themselves to a trade-off hypothesis, wherein adductor size was reduced over evolutionary time as a means (or as a consequence) of neurosensory expansion. In this study, we examine this evolutionary hypothesis through the lens of development by describing the jaw-adductor anatomy of developing chickens, Gallus gallus, and comparing the volumetric expansion of these developing muscles with growth trajectories of the brain and eye. Under the trade-off hypothesis, we predicted that the jaw muscles would grow with negative allometry relative to brain and eyes, and that osteological signatures of a relatively large adductor system, as found in most nonavian dinosaurs, would be differentially expressed in younger chicks. Results did not meet these expectations, at least not generally, with muscle growth exhibiting positive allometry relative to that of brain and eye. We propose three, nonmutually exclusive explanations: (1) these systems do not compete for space, (2) these systems competed for space in the evolutionary past, and growth of the jaw muscles was truncated early in development (paedomorphosis), and (3) trade-offs in developmental investment in these systems are limited temporally to the perinatal period. These explanations are considered in light of the fossil record, and most notably the skull of the stem bird Ichthyornis, which exhibits an interesting combination of plesiomorphically large adductor chamber and apomorphically large brain.

Both Diet and Sociality Affect Primate Brain-Size Evolution

Increased brain size in humans and other primates is hypothesized to confer cognitive benefits but brings costs associated with growing and maintaining energetically expensive neural tissue. Previous studies have argued that changes in either diet or levels of sociality led to shifts in brain size, but results were equivocal. Here we test these hypotheses using phylogenetic comparative methods designed to jointly account for and estimate the effects of adaptation and phylogeny. Using the largest current sample of primate brain and body sizes with observation error, complemented by newly compiled diet and sociality data, we show that both diet and sociality have influenced the evolution of brain size. Shifting from simple to more complex levels of sociality resulted in relatively larger brains, while shifting to a more folivorous diet led to relatively smaller brains. While our results support the role of sociality, they modify a range of ecological hypotheses centered on the importance of frugivory, and instead indicate that digestive costs associated with increased folivory may have resulted in relatively smaller brains. [adaptation; allometry; bayou; evolutionary trend; energetic constraints; phylogenetic comparative methods; primate brain size; Slouch; social-brain hypothesis.].

From fossils to mind

Fossil endocasts record features of brains from the past: size, shape, vasculature, and gyrification. These data, alongside experimental and comparative evidence, are needed to resolve questions about brain energetics, cognitive specializations, and developmental plasticity. Through the application of interdisciplinary techniques to the fossil record, paleoneurology has been leading major innovations. Neuroimaging is shedding light on fossil brain organization and behaviors. Inferences about the development and physiology of the brains of extinct species can be experimentally investigated through brain organoids and transgenic models based on ancient DNA. Phylogenetic comparative methods integrate data across species and associate genotypes to phenotypes, and brains to behaviors. Meanwhile, fossil and archeological discoveries continuously contribute new knowledge. Through cooperation, the scientific community can accelerate knowledge acquisition. Sharing digitized museum collections improves the availability of rare fossils and artifacts. Comparative neuroanatomical data are available through online databases, along with tools for their measurement and analysis. In the context of these advances, the paleoneurological record provides ample opportunity for future research. Biomedical and ecological sciences can benefit from paleoneurology's approach to understanding the mind as well as its novel research pipelines that establish connections between neuroanatomy, genes and behavior.

Relating enhancer genetic variation across mammals to complex phenotypes using machine learning

Protein-coding differences between species often fail to explain phenotypic diversity, suggesting the involvement of genomic elements that regulate gene expression such as enhancers. Identifying associations between enhancers and phenotypes is challenging because enhancer activity can be tissue-dependent and functionally conserved despite low sequence conservation. We developed the Tissue-Aware Conservation Inference Toolkit (TACIT) to associate candidate enhancers with species' phenotypes using predictions from machine learning models trained on specific tissues. Applying TACIT to associate motor cortex and parvalbumin-positive interneuron enhancers with neurological phenotypes revealed dozens of enhancer-phenotype associations, including brain size-associated enhancers that interact with genes implicated in microcephaly or macrocephaly. TACIT provides a foundation for identifying enhancers associated with the evolution of any convergently evolved phenotype in any large group of species with aligned genomes.

Evolutionary history of hominin brain size and phylogenetic comparative methods

An absolutely and relatively large brain has traditionally been viewed as a distinctive characteristic of the Homo genus, with anatomically modern humans presented at the apex of a long line of progressive increases in encephalization. Many studies continue to focus attention on increasing brain size in the Homo genus, while excluding measures of absolute and relative brain size of more geologically recent, smaller brained, hominins such as Homo floresiensis, and Homo naledi and smaller brained Homo erectus specimens. This review discusses the benefits of using phylogenetic comparative methods to trace the diverse changes in hominin brain evolution and the drawbacks of not doing so.

Gradistics: An underappreciated dimension in evolutionary space

The growth of complexity is an unsolved and underappreciated problem. We consider possible causes of this growth, hypotheses testing, molecular mechanisms, complexity measures, cases of simplification, and significance for biomedicine. We focus on a general ability of regulation, which is based on the growing information storage and processing capacities, as the main proxy of complexity. Natural selection is indifferent to complexity. However, complexification can be inferred from the same first principle, on which natural selection is founded. Natural selection depends on potentially unlimited reproduction under limited environmental conditions. Because of the demographic pressure, the simple ecological niches become fulfilled and diversified (due to species splitting and divergence). Diversification increases complexity of biocenoses. After the filling and diversification of simple niches, the more complex niches can arise. This is the 'atomic orbitals' (AO) model. Complexity has many shortcomings but it has an advantage. This advantage is ability to regulatory adaptation, including behavioral, formed in the evolution by means of genetic adaptation. Regulatory adaptation is much faster than genetic one because it is based on the information previously accumulated via genetic adaptation and learning. Regulatory adaptation further increases complexity of biocenoses. This is the 'regulatory advantage' (RA) model. The comparison of both models allows testable predictions. We focus on the animal evolution because of the appearance of higher regulatory level (nervous system), which is absent in other lineages, and relevance to humans (including biomedical aspects).

Extended parental provisioning and variation in vertebrate brain sizes

Large brains provide adaptive cognitive benefits but require unusually high, near-constant energy inputs and become fully functional well after their growth is completed. Consequently, young of most larger-brained endotherms should not be able to independently support the growth and development of their own brains. This paradox is solved if the evolution of extended parental provisioning facilitated brain size evolution. Comparative studies indeed show that extended parental provisioning coevolved with brain size and that it may improve immature survival. The major role of extended parental provisioning supports the idea that the ability to sustain the costs of brains limited brain size evolution.

Evolution of Longevity as a Species-Specific Trait in Mammals

From the evolutionary point of view, the priority problem for an individual is not longevity, but adaptation to the environment associated with the need for survival, food supply, and reproduction. We see two main vectors in the evolution of mammals. One is a short lifespan and numerous offspring ensuring reproductive success (r-strategy). The other one is development of valuable skills in order compete successfully (K-strategy). Species with the K-strategy should develop and enhance specific systems (anti-aging programs) aimed at increasing the reliability and adaptability, including lifespan. These systems are signaling cascades that provide cell repair and antioxidant defense. Hence, any arbitrarily selected long-living species should be characterized by manifestation to a different extent of the longevity-favoring traits (e.g., body size, brain development, sociality, activity of body repair and antioxidant defense systems, resistance to xenobiotics and tumor formation, presence of neotenic traits). Hereafter, we will call a set of such traits as the gerontological success of a species. Longevity is not equivalent to the evolutionary or reproductive success. This difference between these phenomena reaches its peak in mammals due to the development of endothermy and cephalization associated with the cerebral cortex expansion, which leads to the upregulated production of oxidative radicals by the mitochondria (and, consequently, accelerated aging), increase in the number of non-dividing differentiated cells, accumulation of the age-related damage in these cells, and development of neurodegenerative diseases. The article presents mathematical indicators used to assess the predisposition to longevity in different species (including the standard mortality rate and basal metabolic rate, as well as their derivatives). The properties of the evolution of mammals (including the differences between modern mammals and their ancestral forms) are also discussed.

A Revision of the Traditional Analysis Method of Allometry to Allow Extension of the Normality-Borne Complexity of Error Structure: Examining the Adequacy of a Normal-Mixture Distribution-Driven Error Term

Huxley’s model of simple allometry provides a parsimonious scheme for examining scaling relationships in scientific research, resource management, and species conservation endeavors. Factors including biological error, analysis method, sample size, and overall data quality can undermine the reliability of a fit of Huxley’s model. Customary amendments enhance the complexity of the power function-conveyed systematic term while keeping the usual normality-borne error structure. The resulting protocols bear multiple-parameter complex allometry forms that could pose interpretative shortcomings and parameter estimation difficulties, and even being empirically pertinent, they could potentially bear overfitting. A subsequent heavy-tailed Q-Q normal spread often remains undetected since the adequacy of a normally distributed error term remains unexplored. Previously, we promoted the advantages of keeping Huxley’s model-driven systematic part while switching to a logistically distributed error term to improve fit quality. Here, we analyzed eelgrass leaf biomass and area data exhibiting a marked size-related heterogeneity, perhaps explaining a lack of systematization at data gathering. Overdispersion precluded adequacy of the logistically adapted protocol, thereby suggesting processing data through a median absolute deviation scheme aimed to remove unduly replicates. Nevertheless, achieving regularity to Huxley’s power function-like trend required the removal of many replicates, thereby questioning the integrity of a data cleaning approach. But, we managed to adapt the complexity of the error term to reliably identify Huxley’s model-like systematic part masked by variability in data. Achieving this relied on an error term conforming to a normal mixture distribution which successfully managed overdispersion in data. Compared to normal-complex allometry and data cleaning composites present arrangement delivered a coherent Q-Q normal mixture spread and a remarkable reproducibility strength of derived proxies. By keeping the analysis within Huxley’s original theory, the present approach enables substantiating nondestructive allometric proxies aimed at eelgrass conservation. The viewpoint endorsed here could also make data cleaning unnecessary.

Down a Rabbit Hole: Burrowing Behaviour and Larger Home Ranges are Related to Larger Brains in Leporids

Studies on the evolution of brain size variation usually focus on large clades encompassing broad phylogenetic groups. This risks introducing ‘noise’ in the results, often obscuring effects that might be detected in less inclusive clades. Here, we focus on a sample of endocranial volumes (endocasts) of 18 species of rabbits and hares (Lagomorpha: Leporidae), which are a discrete radiation of mammals with a suitably large range of body sizes. Using 60 individuals, we test five popular hypotheses on brain size and olfactory bulb evolution in mammals. We also address the pervasive issue of missing data, using multiple phylogenetic imputations as to conserve the full sample size for all analyses. Our analyses show that home range and burrowing behaviour are the only predictors of leporid brain size variation. Litter size, which is one of the most widely reported constraints on brain size, was unexpectedly not associated with brain size. However, a constraining effect may be masked by a strong association of litter size with temperature seasonality, warranting further study. Lastly, we show that unreasonable estimations of phylogenetic signal (Pagel’s lamba) warrant additional caution when using small sample sizes, such as ours, in comparative studies.

White Paper: An Integrated Perspective on the Causes of Hypometric Metabolic Scaling in Animals

Larger animals studied during ontogeny, across populations, or across species, usually have lower mass-specific metabolic rates than smaller animals (hypometric scaling). This pattern is usually observed regardless of physiological state (e.g. basal, resting, field, maximally-active). The scaling of metabolism is usually highly correlated with the scaling of many life history traits, behaviors, physiological variables, and cellular/molecular properties, making determination of the causation of this pattern challenging. For across-species comparisons of resting and locomoting animals (but less so for across populations or during ontogeny), the mechanisms at the physiological and cellular level are becoming clear. Lower mass-specific metabolic rates of larger species at rest are due to a) lower contents of expensive tissues (brains, liver, kidneys), and b) slower ion leak across membranes at least partially due to membrane composition, with lower ion pump ATPase activities. Lower mass-specific costs of larger species during locomotion are due to lower costs for lower-frequency muscle activity, with slower myosin and Ca++ ATPase activities, and likely more elastic energy storage. The evolutionary explanation(s) for hypometric scaling remain(s) highly controversial. One subset of evolutionary hypotheses relies on constraints on larger animals due to changes in geometry with size; for example, lower surface-to-volume ratios of exchange surfaces may constrain nutrient or heat exchange, or lower cross-sectional areas of muscles and tendons relative to body mass ratios would make larger animals more fragile without compensation. Another subset of hypotheses suggests that hypometric scaling arises from biotic interactions and correlated selection, with larger animals experiencing less selection for mass-specific growth or neurolocomotor performance. A additional third type of explanation comes from population genetics. Larger animals with their lower effective population sizes and subsequent less effective selection relative to drift may have more deleterious mutations, reducing maximal performance and metabolic rates. Resolving the evolutionary explanation for the hypometric scaling of metabolism and associated variables is a major challenge for organismal and evolutionary biology. To aid progress, we identify some variation in terminology use that has impeded cross-field conversations on scaling. We also suggest that promising directions for the field to move forward include: 1) studies examining the linkages between ontogenetic, population-level, and cross-species allometries, 2) studies linking scaling to ecological or phylogenetic context, 3) studies that consider multiple, possibly interacting hypotheses, and 4) obtaining better field data for metabolic rates and the life history correlates of metabolic rate such as lifespan, growth rate and reproduction.

Braitenberg Vehicles as Developmental Neurosimulation

Connecting brain and behavior is a longstanding issue in the areas of behavioral science, artificial intelligence, and neurobiology. As is standard among models of artificial and biological neural networks, an analogue of the fully mature brain is presented as a blank slate. However, this does not consider the realities of biological development and developmental learning. Our purpose is to model the development of an artificial organism that exhibits complex behaviors. We introduce three alternate approaches to demonstrate how developmental embodied agents can be implemented. The resulting developmental Braitenberg vehicles (dBVs) will generate behaviors ranging from stimulus responses to group behavior that resembles collective motion. We will situate this work in the domain of artificial brain networks along with broader themes such as embodied cognition, feedback, and emergence. Our perspective is exemplified by three software instantiations that demonstrate how a BV-genetic algorithm hybrid model, a multisensory Hebbian learning model, and multi-agent approaches can be used to approach BV development. We introduce use cases such as optimized spatial cognition (vehicle-genetic algorithm hybrid model), hinges connecting behavioral and neural models (multisensory Hebbian learning model), and cumulative classification (multi-agent approaches). In conclusion, we consider future applications of the developmental neurosimulation approach.

Allometric model of brain morphology of Hemiculter leucisculus and its variation along climatic gradients

Prior studies on Hemiculter leucisculus, which is a widespread native fish in China, mainly focused on its growth, feeding habits, and individual fecundity, but few have investigated the brain. In this research, we explored the developmental patterns of the Hemiculter leucisculus brain and found the brain showed allometry through sample time points and three age groups. At the same time, we found that the brain varied along climatic gradients. The volumes of the olfactory bulbs, telencephalic lobes, optic tectum, corpus cerebelli, and total brain in the south were larger than those in the north, while the volume of the hypothalamus in the north was larger than in the south. This study provides a view for the in-depth study of the acclimatized mechanism of the teleost brain, lays a foundation for the further study of evolutionary ecology, and provides a reference for the phenotypic plasticity of the teleost brain.

Evolvability and Macroevolution: Overview and Synthesis

Evolvability is best addressed from a multi-level, macroevolutionary perspective through a comparative approach that tests for among-clade differences in phenotypic diversification in response to an opportunity, such as encountered after a mass extinction, entering a new adaptive zone, or entering a new geographic area. Analyzing the dynamics of clades under similar environmental conditions can (partially) factor out shared external drivers to recognize intrinsic differences in evolvability, aiming for a macroevolutionary analog of a common-garden experiment. Analyses will be most powerful when integrating neontological and paleontological data: determining differences among extant populations that can be hypothesized to generate large-scale, long-term contrasts in evolvability among clades; or observing large-scale differences among clade histories that can by hypothesized to reflect contrasts in genetics and development observed directly in extant populations. However, many comparative analyses can be informative on their own, as explored in this overview. Differences in clade-level evolvability can be visualized in diversity-disparity plots, which can quantify positive and negative departures of phenotypic productivity from stochastic expectations scaled to taxonomic diversification. Factors that evidently can promote evolvability include modularity—when selection aligns with modular structure or with morphological integration patterns; pronounced ontogenetic changes in morphology, as in allometry or multiphase life cycles; genome size; and a variety of evolutionary novelties, which can also be evaluated using macroevolutionary lags between the acquisition of a trait and phenotypic diversification, and dead-clade-walking patterns that may signal a loss of evolvability when extrinsic factors can be excluded. High speciation rates may indirectly foster phenotypic evolvability, and vice versa. Mechanisms are controversial, but clade evolvability may be higher in the Cambrian, and possibly early in the history of clades at other times; in the tropics; and, for marine organisms, in shallow-water disturbed habitats.

Large and expensive brain comes with a short lifespan: The relationship between brain size and longevity among fish taxa

Vertebrates show substantial interspecific variation in brain size in relation to body mass. It has long been recognized that the evolution of large brains is associated with both costs and benefits, and it is their net benefit which should be favoured by natural selection. On one hand, the substantial energetic cost imposed by the maintenance of neural tissue is expected to compromise the energetic budget of organisms with large brains and their investment in other critical organs (expensive brain framework, EBF) or important physiological process, such as somatic maintenance and repair, thus accelerating ageing that shortens lifespan, as predicted by the disposable soma theory (DST). However, selection towards larger brain size can provide cognitive benefits (e.g., high behavioural flexibility) that may mitigate extrinsic mortality pressures, and thus may indirectly select for slower ageing that prolongs lifespan, as predicted by the cognitive buffer hypothesis (CBH). The relationship between longevity and brain size has been investigated to date only among terrestrial vertebrates, although the same selective forces acting on those species may also affect vertebrates living in aquatic habitats, such as fish. Thus, whether this evolutionary trade-off for brain size and longevity exists on a large scale among fish clades remains to be addressed. In this study, using a global dataset of 407 fish species, I undertook the first phylogenetic test of the brain size/longevity relationship in aquatic vertebrate species. The study revealed a negative relationship between brain size and longevity among cartilaginous fish confirming EBF and DST. However, no pattern emerged among bony fish species. Among sharks and rays, the high metabolic cost of producing neural tissue transcends the cognitive benefits of evolving a larger brain. Consequently, my findings suggest that the cost of maintaining brain tissue is relatively higher in ectothermic species than in endothermic ones.

Convergent mosaic brain evolution is associated with the evolution of novel electrosensory systems in teleost fishes

Brain region size generally scales allometrically with brain size, but mosaic shifts in brain region size independent of brain size have been found in several lineages and may be related to the evolution of behavioral novelty. African weakly electric fishes (Mormyroidea) evolved a mosaically enlarged cerebellum and hindbrain, yet the relationship to their behaviorally novel electrosensory system remains unclear. We addressed this by studying South American weakly electric fishes (Gymnotiformes) and weakly electric catfishes (Synodontis spp.), which evolved varying aspects of electrosensory systems, independent of mormyroids. If the mormyroid mosaic increases are related to evolving an electrosensory system, we should find similar mosaic shifts in gymnotiforms and Synodontis. Using micro-computed tomography scans, we quantified brain region scaling for multiple electrogenic, electroreceptive, and non-electrosensing species. We found mosaic increases in cerebellum in all three electrogenic lineages relative to non-electric lineages and mosaic increases in torus semicircularis and hindbrain associated with the evolution of electrogenesis and electroreceptor type. These results show that evolving novel electrosensory systems is repeatedly and independently associated with changes in the sizes of individual major brain regions independent of brain size, suggesting that selection can impact structural brain composition to favor specific regions involved in novel behaviors.

Larger animals tend to have larger brains and smaller animals tend to have smaller ones. However, some species do not fit the pattern that would be expected based on their body size. This variation between species can also apply to individual brain regions. This may be due to evolutionary forces shaping the brain when favouring particular behaviours. However, it is difficult to directly link changes in species behaviour and variations in brain structure.

One way to understand the impact of evolutionary adaptations is to study species that have developed new behaviours and compare them to related ones that lack such a behaviour. An opportunity to do this lies in the ability of several species of fish to produce and sense electric fields in water. While this system is not found in most fish, it has evolved multiple times independently in distantly-related lineages. Schumacher and Carlson examined whether differences in the size of brains and individual regions between species were associated with the evolution of electric field generation and sensing.

Micro-computed tomography, or μCT, scans of the brains of multiple fish species revealed that the species that can produce electricity – also known as ‘electrogenic’ species’ – have more similar brain structures to each other than to their close relatives that lack this ability. The brain regions involved in producing and detecting electrical charges were larger in these electrogenic fish. This similarity was apparent despite variations in how total brain size has evolved with body size across species.

These results demonstrate how evolutionary forces acting on particular behaviours can lead to predictable changes in brain structure. Understanding how and why brains evolve will allow researchers to better predict how species’ brains and behaviours may adapt as human activities alter their environments.

The costs and benefits of larger brains in fishes

The astonishing diversity of brain sizes observed across the animal kingdom is typically explained in the context of trade-offs: the benefits of a larger brain, such as enhanced cognitive ability, are balanced against potential costs, such as increased energetic demands. Several hypotheses have been formulated in this framework, placing different emphasis on ecological, behavioural, or physiological aspects of trade-offs in brain size evolution. Within this body of work, there exists considerable taxonomic bias towards studies of birds and mammals, leaving some uncertainty about the generality of the respective arguments. Here, we test three of the most prominent such hypotheses, the 'expensive tissue', 'social brain' and 'cognitive buffer' hypotheses, in a large dataset of fishes, derived from a publicly available resource (FishBase). In accordance with predictions from the 'expensive tissue' and the 'social brain' hypothesis, larger brains co-occur with reduced fecundity and increased sociality in at least some Classes of fish. Contrary to expectations, however, lifespan is reduced in large-brained fishes, and there is a tendency for species that perform parental care to have smaller brains. As such, it appears that some potential costs (reduced fecundity) and benefits (increased sociality) of large brains are near universal to vertebrates, whereas others have more lineage-specific effects. We discuss our findings in the context of fundamental differences between the classically studied birds and mammals and the fishes we analyse here, namely divergent patterns of growth, parenting and neurogenesis. As such, our work highlights the need for a taxonomically diverse approach to any fundamental question in evolutionary biology.

Growth and Mortality as Causes of Variation in Metabolic Scaling Among Taxa and Taxonomic Levels

Metabolic rate (MR) usually changes (scales) out of proportion to body mass (BM) as MR = aBMb, where a is a normalisation constant and b is the scaling exponent that reflects how steep this change is. This scaling relationship is fundamental to biology, but over a century of research has provided little consensus on the value of b, and why it appears to vary among taxa and taxonomic levels. By analysing published data on fish and taking an individual-based approach to metabolic scaling, I show that variation in growth of fish under naturally restricted food availability can explain variation in within-individual (ontogenetic) b for standard (maintenance) metabolic rate (SMR) of brown trout (Salmo trutta), with the fastest growers having the steepest metabolic scaling (b ≈ 1). Moreover, I show that within-individual b can vary much more widely than previously assumed from work on different individuals or different species, from -1 to 1 for SMR among individual brown trout. The negative scaling of SMR for some individuals was caused by reductions in metabolic rate in a food limited environment, likely to maintain positive growth. This resulted in a mean within-individual b for SMR that was significantly lower than the across-individual ("static") b, a difference that also existed for another species, cunner (Tautogolabrus adspersus). Interestingly, the wide variation in ontogenetic b for SMR among individual brown trout did not exist for maximum (active) metabolic rate (MMR) of the same fish, showing that these two key metabolic traits (SMR and MMR) can scale independently of one another. I also show that across-species ("evolutionary") b for SMR of 134 fishes is significantly steeper (b approaching 1) than the mean ontogenetic b for the brown trout and cunner. Based on these interesting findings, I hypothesise that evolutionary and static metabolic scaling can be systematically different from ontogenetic scaling, and that the steeper evolutionary than ontogenetic scaling for fishes arises as a by-product of natural selection for fast-growing individuals with steep metabolic scaling (b ≈ 1) early in life, where size-selective mortality is high for fishes. I support this by showing that b for SMR tends to increase with natural mortality rates of fish larvae within taxa.

Relative Brain Size and Cognitive Equivalence in Fishes

Scientists have long struggled to establish how larger brains translate into higher cognitive performance across species. While absolute brain size often yields high predictive power of performance, its positive correlation with body size warrants some level of correction. It is expected that larger brains are needed to control larger bodies without any changes in cognitive performance. Potentially, the mean value of intraspecific brain-body slopes provides the best available estimate for an interspecific correction factor. For example, in primates, including humans, an increase in body size translates into an increase in brain size without changes in cognitive performance. Here, we provide the first evaluation of this hypothesis for another clade, teleost fishes. First, we obtained a mean intraspecific brain-body regression slope of 0.46 (albeit with a relatively large range of 0.26-0.79) from a dataset of 51 species, with at least 10 wild adult specimens per species. This mean intraspecific slope value (0.46) is similar to that of the encephalisation quotient reported for teleosts (0.5), which can be used to predict mean cognitive performance in fishes. Importantly, such a mean value (0.46) is much higher than in endothermic vertebrate species (≤0.3). Second, we used wild-caught adult cleaner fish Labroides dimidiatus as a case study to test whether variation in individual cognitive performance can be explained by body size. We first obtained the brain-body regression slope for this species from two different datasets, which gave slope values of 0.58 (MRI scan data) and 0.47 (dissection data). Then, we used another dataset involving 69 adult cleaners different from those tested for their brain-body slope. We found that cognitive performance from four different tasks that estimated their learning, numerical, and inhibitory control abilities was not significantly associated with body size. These results suggest that the intraspecific brain-body slope captures cognitive equivalence for this species. That is, individuals that are on the brain-body regression line are cognitively equal. While rather preliminary, our results suggest that fish and mammalian brain organisations are fundamentally different, resulting in different intra- and interspecific slopes of cognitive equivalence.

Brain size, gut size and cognitive abilities: the energy trade-offs tested in artificial selection experiment

The enlarged brains of homeotherms bring behavioural advantages, but also incur high energy expenditures. The ‘expensive brain’ (EB) hypothesis posits that the energetic costs of the enlarged brain and the resulting increased cognitive abilities (CA) were met by either increased energy turnover or reduced allocation to other expensive organs, such as the gut. We tested the EB hypothesis by analysing correlated responses to selection in an experimental evolution model system, which comprises line types of laboratory mice selected for high or low basal metabolic rate (BMR), maximum (VO_2max) metabolic rates and random-bred (unselected) lines. The traits are implicated in the evolution of homeothermy, having been pre-requisites for the encephalization and exceptional CA of mammals, including humans. High-BMR mice had bigger guts, but not brains, than mice of other line types. Yet, they were superior in the cognitive tasks carried out in both reward and avoidance learning contexts and had higher neuronal plasticity (indexed as the long-term potentiation) than their counterparts. Our data indicate that the evolutionary increase of CA in mammals was initially associated with increased BMR and brain plasticity. It was also fuelled by an enlarged gut, which was not traded off for brain size.

Brawn before brains in placental mammals after the end-Cretaceous extinction

Mammals are the most encephalized vertebrates, with the largest brains relative to body size. Placental mammals have particularly enlarged brains, with expanded neocortices for sensory integration, the origins of which are unclear. We used computed tomography scans of newly discovered Paleocene fossils to show that contrary to the convention that mammal brains have steadily enlarged over time, early placentals initially decreased their relative brain sizes because body mass increased at a faster rate. Later in the Eocene, multiple crown lineages independently acquired highly encephalized brains through marked growth in sensory regions. We argue that the placental radiation initially emphasized increases in body size as extinction survivors filled vacant niches. Brains eventually became larger as ecosystems saturated and competition intensified.

The road to a larger brain

Ecological opportunities in the early Cenozoic favored larger, not smarter, mammals.

The evolution of brain neuron numbers in amniotes

The evolution of brain processing capacity has traditionally been inferred from data on brain size. However, similarly sized brains of distantly related species can differ in the number and distribution of neurons, their basic computational units. Therefore, a finer-grained approach is needed to reveal the evolutionary paths to increased cognitive capacity. Using a new, comprehensive dataset, we analyzed brain cellular composition across amniotes. Compared to reptiles, mammals and birds have dramatically increased neuron numbers in the telencephalon and cerebellum, which are brain parts associated with higher cognition. Astoundingly, a phylogenetic analysis suggests that as few as four major changes in neuron–brain scaling in over 300 million years of evolution pave the way to intelligence in endothermic land vertebrates.

Reconstructing the evolution of brain information-processing capacity is paramount for understanding the rise of complex cognition. Comparative studies of brain evolution typically use brain size as a proxy. However, to get a less biased picture of the evolutionary paths leading to high cognitive power, we need to compare brains not by mass but by numbers of neurons, which are their basic computational units. This study reconstructs the evolution of brains across amniotes by directly analyzing neuron numbers by using the largest dataset of its kind and including essential data on reptiles. We show that reptiles have not only small brains relative to body size but also low neuronal densities, resulting in average neuron numbers over 20 times lower than those in birds and mammals of similar body size. Amniote brain evolution is characterized by the following four major shifts in neuron–brain scaling. The most dramatic increases in brain neurons occurred independently with the appearance of birds and mammals, resulting in convergent neuron scaling in the two endotherm lineages. The other two major increases in the number of neurons happened in core land birds and anthropoid primates, which are two groups known for their cognitive prowess. Interestingly, relative brain size is associated with relative neuronal cell density in reptiles, birds, and primates but not in other mammals. This has important implications for studies using relative brain size as a proxy when looking for evolutionary drivers of animal cognition.

Primordial Germ Cell Development in the Poeciliid, Gambusia holbrooki, Reveals Shared Features Between Lecithotrophs and Matrotrophs

Metazoans exhibit two modes of primordial germ cell (PGC) specification that are interspersed across taxa. However, the evolutionary link between the two modes and the reproductive strategies of lecithotrophy and matrotrophy is poorly understood. As a first step to understand this, the spatio-temporal expression of teleostean germ plasm markers was investigated in Gambusia holbrooki, a poecilid with shared lecitho- and matrotrophy. A group of germ plasm components was detected in the ovum suggesting maternal inheritance mode of PGC specification. However, the strictly zygotic activation of dnd-β and nanos1 occurred relatively early, reminiscent of models with induction mode (e.g., mice). The PGC clustering, migration and colonisation patterns of G. holbrooki resembled those of zebrafish, medaka and mice at blastula, gastrula and somitogenesis, respectively-recapitulating features of advancing evolutionary nodes with progressive developmental stages. Moreover, the expression domains of PGC markers in G. holbrooki were either specific to teleost (vasa expression in developing PGCs), murine models (dnd spliced variants) or shared between the two taxa (germline and somatic expression of piwi and nanos1). Collectively, the results suggest that the reproductive developmental adaptations may reflect a transition from lecithotrophy to matrotrophy.

The Importance of Noise Colour in Simulations of Evolutionary Systems

Simulations of evolutionary dynamics often employ white noise as a model of stochastic environmental variation. Whilst white noise has the advantages of being simply generated and analytically tractable, empirical analyses demonstrate that most real environmental time series have power spectral densities consistent with pink or red noise, in which lower frequencies contribute proportionally greater amplitudes than higher frequencies. Simulated white noise environments may therefore fail to capture key components of real environmental time series, leading to erroneous results. To explore the effects of different noise colours on evolving populations, a simple evolutionary model of the interaction between life-history and the specialism-generalism axis was developed. Simulations were conducted using a range of noise colours as the environments to which agents adapted. Results demonstrate complex interactions between noise colour, reproductive rate, and the degree of evolved generalism; importantly, contradictory conclusions arise from simulations using white as opposed to red noise, suggesting that noise colour plays a fundamental role in generating adaptive responses. These results are discussed in the context of previous research on evolutionary responses to fluctuating environments, and it is suggested that Artificial Life as a field should embrace a wider spectrum of coloured noise models to ensure that results are truly representative of environmental and evolutionary dynamics.

Analyzing Disparity and Rates of Morphological Evolution with Model-Based Phylogenetic Comparative Methods

Understanding variation in rates of evolution and morphological disparity is a goal of macroevolutionary research. In a phylogenetic comparative methods framework, we present three explicit models for linking the rate of evolution of a trait to the state of another evolving trait. This allows testing hypotheses about causal influences on rates of phenotypic evolution with phylogenetic comparative data. We develop a statistical framework for fitting the models with generalized least-squares regression and use this to discuss issues and limitations in the study of rates of evolution more generally. We show that the power to detect effects on rates of evolution is low in that even strong causal effects are unlikely to explain more than a few percent of observed variance in disparity. We illustrate the models and issues by testing if rates of beak-shape evolution in birds are influenced by brain size, as may be predicted from a Baldwin effect in which presumptively more behaviorally flexible large-brained species generate more novel selection on themselves leading to higher rates of evolution. From an analysis of morphometric data for 645 species, we find evidence that both macro- and microevolution of the beak are faster in birds with larger brains, but with the caveat that there are no consistent effects of relative brain size.[Baldwin effect; beak shape; behavioral drive; bird; brain size; disparity; phylogenetic comparative method; rate of evolution.]

Scaling at different ontogenetic stages: Gastrointestinal tract contents of a marsupial foregut fermenter, the western grey kangaroo Macropus fuliginosus melanops

Prominent ontogenetic changes of the gastrointestinal tract (GIT) should occur in mammals whose neonatal diet of milk differs from that of adults, and especially in herbivores (as vegetation is particularly distinct from milk), and even more so in foregut fermenters, whose forestomach only becomes functionally relevant with vegetation intake. Due to the protracted lactation in marsupials, ontogenetic differences can be particularly well investigated in this group. Here, we report body mass (BM) scaling relationships of wet GIT content mass in 28 in-pouch young (50 g to 3 kg) and 15 adult (16-70 kg) western grey kangaroos Macropus fuliginosus melanops. Apart from the small intestinal contents, in-pouch young and adults did not differ in the scaling exponents ('slope' in log-log plots) but did differ in the scaling factor ('intercept'), with an implied substantial increase in wet GIT content mass during the out-of-pouch juvenile period. In contrast to forestomach contents, caecum contents were elevated in juveniles still in the pouch, suggestive of fermentative digestion of milk and intestinal secretion residues, particularly in the caecum. The substantial increase in GIT contents (from less than 1 to 10-20% of BM) was associated mainly with the increase in forestomach contents (from 25 to 80% of total GIT contents) and a concomitant decrease in small intestine contents (from 50 to 8%), emphasizing the shifting relevance of auto-enzymatic and allo-enzymatic (microbial) digestion. There was a concomitant increase in the contents-to-tissue ratio of the fermentation chambers (forestomach and caecum), but this ratio generally did not change for the small intestine. Our study not only documents significant ontogenetic changes in digestive morpho-physiology, but also exemplifies the usefulness of intraspecific allometric analyses for quantifying these changes.

Exceptionally Steep Brain-Body Evolutionary Allometry Underlies the Unique Encephalization of Osteoglossiformes

Brain-body static allometry, which is the relationship between brain size and body size within species, is thought to reflect developmental and genetic constraints. Existing evidence suggests that the evolution of large brain size without accompanying changes in body size (that is, encephalization) may occur when this constraint is relaxed. Teleost fish species are generally characterized by having close-fitting brain-body static allometries, leading to strong allometric constraints and small relative brain sizes. However, one order of teleost, Osteoglossiformes, underwent extreme encephalization, and its mechanistic bases are unknown. Here, I used a dataset and phylogeny encompassing 859 teleost species to demonstrate that the encephalization of Osteoglossiformes occurred through an increase in the slope of evolutionary (among-species) brain-body allometry. The slope is virtually isometric (1.03 ± 0.09 SE), making it one of the steepest evolutionary brain-body allometric slopes reported to date, and it deviates significantly from the evolutionary brain-body allometric slopes of other clades of teleost. Examination of the relationship between static allometric parameters (intercepts and slopes) and evolutionary allometry revealed that the dramatic steepening of the evolutionary allometric slope in Osteoglossiformes was a combined result of evolution in the slopes and intercepts of static allometry. These results suggest that the evolution of static allometry, which likely has been driven by evolutionary changes in the rate and timing of brain development, has facilitated the unique encephalization of Osteoglossiformes.