Search

In a fast-changing world, understanding how organisms adapt to their environment is a pressing necessity. Research has focused on genetic adaptation, while our understanding of non-genetic modes is still in its infancy. The host-associated microbiome can be considered a non-genetic mode of adaptation, which can strongly influence an organism's ability to cope with its environment. However, the role of the microbiome in host ecological dynamics is largely unexplored, particularly in animal communities. Here, we discuss the following hypothesis: invasive species may rapidly adapt to local conditions by adopting beneficial microbes from similar co-occurring native species. This occurs when the invader's fitness is influenced by adaptation to local conditions that is facilitated by microbes acquired from native microbiomes. We present a minimal mathematical model to explore this hypothesis and show that a delayed acquisition of native microbes may explain the occurrence of an invasion lag. Overall, our results contribute to broadening the conceptualization of rapid adaptation via microbiome transfer and offer insights towards designing early intervention strategies for invasive species management.

Avoiding physical contact is regarded as one of the safest and most advisable strategies to follow to reduce pathogen spread. The flip side of this approach is that a lack of social interactions may negatively affect other dimensions of health, like induction of immunosuppressive anxiety and depression or preventing interactions of importance with a diversity of microbes, which may be necessary to train our immune system or to maintain its normal levels of activity. These may in turn negatively affect a population's susceptibility to infection and the incidence of severe disease. We suggest that future pandemic modelling may benefit from relying on 'SIR+ models': epidemiological models extended to account for the benefits of social interactions that affect immune resilience. We develop an SIR+ model and discuss which specific interventions may be more effective in balancing the trade-off between minimizing pathogen spread and maximizing other interaction-dependent health benefits. Our SIR+ model reflects the idea that health is not just the mere absence of disease, but rather a state of physical, mental and social well-being that can also be dependent on the same social connections that allow pathogen spread, and the modelling of public health interventions for future pandemics should account for this multidimensionality., (© 2024. The Author(s).)

The evolution of mutualism between host and symbiont communities plays an essential role in maintaining ecosystem function and should therefore have a profound effect on their range expansion dynamics. In particular, the presence of mutualistic symbionts at the leading edge of a host-symbiont community should enhance its propagation in space. We develop a theoretical framework that captures the eco-evolutionary dynamics of host-symbiont communities, to investigate how the evolution of resource exchange may shape community structure during range expansion. We consider a community with symbionts that are mutualistic or parasitic to various degrees, where parasitic symbionts receive the same amount of resource from the host as mutualistic symbionts, but at a lower cost. The selective advantage of parasitic symbionts over mutualistic ones is increased with resource availability (i.e. with host density), promoting mutualism at the range edges, where host density is low, and parasitism at the population core, where host density is higher. This spatial selection also influences the speed of spread. We find that the host growth rate (which depends on the average benefit provided by the symbionts) is maximal at the range edges, where symbionts are more mutualistic, and that host-symbiont communities with high symbiont density at their core (e.g. resulting from more mutualistic hosts) spread faster into new territories. These results indicate that the expansion of host-symbiont communities is pulled by the hosts but pushed by the symbionts, in a unique push-pull dynamic where both the host and symbionts are active and tightly-linked players., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Tethysbaena are small peracarid crustaceans inhabiting extreme environments such as subterranean lakes and thermal springs, represented by endemic species found around the ancient Tethys, including the Mediterranean, Arabian Sea, Mid-East Atlantic, and the Caribbean Sea. Two Tethysbaena species are known from the Levant: T. relicta , found along the Dead Sea-Jordan Rift Valley, and T. ophelicola , found in the Ayyalon cave complex in the Israeli coastal plain, both belonging to the same species-group based on morphological cladistics. Along the biospeleological research of the Levantine subterranean fauna, three biogeographic hypotheses determining their origins were proposed: (1) Pliocenic transgression, (2) Mid-late Miocenic transgression, and (3) The Ophel Paradigm, according to which these are inhabitants of a chemosynthetic biome as old as the Cambrian., Methods: Tethysbaena specimens of the two Levantine species were collected from subterranean groundwaters. We used the mitochondrial cytochrome c oxidase subunit I (COI) gene and the nuclear ribosomal 28S (28S rRNA) gene to establish the phylogeny of the Levantine Tethysbaena species, and applied a molecular clock approach for inferring their divergence times., Results: Contrary to the morphological cladistic-based classification, we found that T. relicta shares an ancestor with Tethysbaena species from Oman and the Dominican Republic, whereas the circum-Mediterranean species (including T. ophelicola ) share another ancestor. The mean age of the node linking T. relicta from the Dead Sea-Jordan Rift Valley and Tethysbaena from Oman was 20.13 MYA. The mean estimate for the divergence of T. ophelicola from the Mediterranean Tethysbaena clade dated to 9.46 MYA., Conclusions: Our results indicate a two-stage colonization of Tethysbaena in the Levant: a late Oligocene transgression, through a marine gulf extending from the Arabian Sea, leading to the colonization of T. relicta in the Dead Sea-Jordan Rift Valley, whereas T. ophelicola , originating from the Mesogean ancestor, inhabited anchialine caves in the coastal plain of Israel during the Mid-Miocene., Competing Interests: Tamar Guy-Haim is an Academic Editor for PeerJ., (©2023 Guy-Haim et al.)

Recent empirical studies offer conflicting findings regarding the relation between host fitness and the composition of its microbiome, a conflict which we term 'the microbial β- diversity conundrum'. The microbiome is crucial for host wellbeing and survival. Surprisingly, different healthy individuals' microbiome compositions, even in the same population, often differ dramatically, contrary to the notion that a vital trait should be highly conserved. Moreover, gnotobiotic individuals exhibit highly deleterious phenotypes, supporting the view that the microbiome is paramount to host fitness. However, the introduction of almost arbitrarily selected microbiota into the system often achieves a significant rescue effect of the deleterious phenotypes. This is true even for microbiota from soil or phylogenetically distant host species, highlighting an apparent paradox. We suggest several solutions to the paradox using a computational framework, simulating the population dynamics of hosts and their microbiomes over multiple generations. The answers invoke factors such as host population size, the specific mode of microbial contribution to host fitness, and typical microbiome richness, offering solutions to the conundrum by highlighting scenarios where even when a host's fitness is determined in full by its microbiome composition, this composition has little effect on the natural selection dynamics of the population., (© 2023. The Author(s).)

Human populations rely on cultural artefacts for their survival. Populations vary dramatically in the size of their tool repertoires, and the determinants of these cultural repertoire sizes have been the focus of extensive study. A prominent hypothesis, supported by computational models of cultural evolution, asserts that tool repertoire size increases with population size. However, not all empirical studies have found such a correlation, leading to a contentious and ongoing debate. As a possible resolution to this longstanding controversy, we suggest that accounting for even rare cultural migration events that allow sharing of knowledge between different-sized populations may help explain why a population's size might not always predict its cultural repertoire size. Using an agent-based model to test assumptions about the effects of population size and connectivity on tool repertoires, we find that cultural exchange between a focal population and others, particularly with large populations, may significantly boost its tool repertoire size. Thus, two populations of identical size may have drastically different tool repertoire sizes, hinging upon their access to other groups' knowledge. Intermittent contact between populations boosts cultural repertoire size and still allows for the development of unique tool repertoires that have limited overlap between populations.

Distributed adaptations are cases in which adaptation is dependent on the population as a whole: the adaptation is conferred by a structural or compositional aspect of the population; the adaptively relevant information cannot be reduced to information possessed by a single individual. Possible examples of human-distributed adaptations are song lines, traditions, trail systems, game drive lanes and systems of water collection and irrigation. Here we discuss the possible role of distributed adaptations in human cultural macro-evolution. Several kinds of human-distributed adaptations are presented, and their evolutionary implications are highlighted. In particular, we discuss the implications of population size, density and bottlenecks on the distributed adaptations that a population may possess and how they in turn would affect the population's resilience to ecological change. We discuss the implications that distributed adaptations may have for human collective action and the possibility that they played a role in colonization of new areas and niches, in seasonal migration, and in setting constraints for minimal inter-population connectivity. This article is part of the theme issue 'Human socio-cultural evolution in light of evolutionary transitions'.

The transition to specialization of knowledge within populations could have facilitated the accumulation of cultural complexity in humans. Specialization allows populations to increase their cultural repertoire without requiring that members of that population increase their individual capacity to accumulate knowledge. However, specialization also means that domain-specific knowledge can be concentrated in small subsets of the population, making it more susceptible to loss. Here, we use a model of cultural evolution to demonstrate that specialized populations can be more sensitive to stochastic loss of knowledge than populations without subdivision of knowledge, and that demographic and environmental changes have an amplified effect on populations with knowledge specialization. Finally, we suggest that specialization can be a double-edged sword; specialized populations may have an advantage in accumulating cultural traits but may also be less likely to expand and establish themselves successfully in new demes owing to the increased cultural loss that they experience during the population bottlenecks that often characterize such expansions. This article is part of the theme issue 'Human socio-cultural evolution in light of evolutionary transitions'.

The initial evolution of conspicuous aposematism is a longstanding evolutionary paradox: while the benefits of conspicuousness in aposematic signals have been demonstrated, they rely on predators being familiar with the conspicuous signals and avoiding them. In a system dominated by naïve predators, the appearance of conspicuousness would be expected to increase detection and attack rate by the predators. Hence, it is unclear how such signals could become established in a naïve community. We suggest that this problem may usefully be framed in the terms of fitness landscapes, an idea used for conceptualizing the mapping between genotype/phenotype and fitness. The evolution of conspicuousness can be thought of as a special case of valley crossing, which concerns the transition of populations between fitness peaks, when such a transition imposes an initial decrease in fitness. Crypsis may be regarded as a local fitness peak, hindering predators' ability to detect prey; for an unpalatable species, conspicuous aposematism may constitute a higher-still fitness peak, preventing predation attempts altogether and allowing access to niches unavailable to species encumbered by the necessity to remain concealed from predators. However, in order to reach this higher peak, the population must first cross the valley of non-intimidating conspicuousness, in which the prey is conspicuous but the predators are not yet deterred. Using terms borrowed from the concept of fitness landscapes, we categorize several solutions suggested previously in the literature as either concerning changes in the fitness landscape or as illuminating possible ridges connecting the two peaks, which emerge from unconsidered dimensions of the fitness landscape. We suggest that considering this question through the lens of fitness landscapes not only facilitates useful categorization of previously suggested solutions but may also prove useful for thinking about novel ones., (© The Author(s) 2022. Published by Oxford University Press on behalf of The Society for the Study of Evolution (SSE). All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Uchiyama et al. emphasize that culture evolves directionally and differentially as a function of selective pressures in different populations. Extending these principles to the level of families, lineages, and individuals exposes additional challenges to estimating heritability. Cultural traits expressed differentially as a function of the genetics whose influence they mask or unmask render inseparable the influences of culture and genetics.

Human milk oligosaccharides (HMOs) are a family of glycans found in breastmilk with over 200 identified structures. Despite being the third-largest component in breastmilk, HMOs are indigestible by infants, which raises an intriguing question: we would expect evolutionary dynamics to have shaped breastmilk to efficiently fulfill the baby's nutritional needs; what, then, could be the role of HMOs? Tracking their fate offers an answer: they are metabolized by certain gut bacteria, suggesting that breastmilk has been structured to shape the developing infant microbiome. We suggest that ecological paradigms, in particular, the notion of priority effects, can help contextualize the importance of HMOs as agents shaping the gut microbiome. The fitness consequences of this process provide insight regarding the evolutionary forces that have shaped the composition of breastmilk. In this review, we offer an eco-evolutionary perspective and present empirical data associating the compositions of mothers' milk and their infants' gut microbiomes., (Copyright © 2022. Published by Elsevier Ltd.)

An outstanding question regarding the human gut microbiota is whether and how microbiota-directed interventions influence host phenotypic traits. Here, we employed a dietary intervention to probe this question in the context of lactose intolerance. To assess the effects of dietary dairy product elimination and (re)introduction on the microbiota and host phenotype, we studied 12 self-reported mildly lactose-intolerant adults with triweekly collection of fecal samples over a 12-week study period: 2 weeks of baseline diet, 4 weeks of dairy product elimination, and 6 weeks of gradual whole cow milk (re)introduction. Of the 12 subjects, 6 reported either no dairy or only lactose-free dairy product consumption. A clinical assay for lactose intolerance, the hydrogen breath test, was performed before and after each of these three study phases, and 16S rRNA gene amplicon sequencing was performed on all fecal samples. We found that none of the subjects showed change in a clinically defined measure of lactose tolerance. Similarly, fecal microbiota structure resisted modification. Although the mean fraction of the genus Bifidobacterium, a group known to metabolize lactose, increased slightly with milk (re)introduction (from 0.0125 to 0.0206; Wilcoxon P =  0.068), the overall structure of each subject's gut microbiota remained highly individualized and largely stable in the face of diet manipulation. IMPORTANCE Lactose intolerance is a gastrointestinal disorder diagnosed with a lactose hydrogen breath test. Lifestyle changes such as diet interventions can impact the gut microbiome; however, the role of the microbiome in lactose intolerance is unclear. Our study assessed the effects of a 12-week dietary dairy product elimination and (re)introduction on the microbiome and clinical lactose intolerance status in 12 adult self-reported lactose-intolerant individuals. We found each subject's gut microbiome remained highly individualized and largely stable in the face of this diet manipulation. We also report that none of the subjects showed change in a clinically defined measure of lactose tolerance.

Animal vocal communication is a broad and multi-disciplinary field of research. Studying various aspects of communication can provide key elements for understanding animal behavior, evolution, and cognition. Given the large amount of acoustic data accumulated from automated recorders, for which manual annotation and analysis is impractical, there is a growing need to develop algorithms and automatic methods for analyzing and identifying animal sounds. In this study we developed an automatic detection and analysis system based on audio signal processing algorithms and deep learning that is capable of processing and analyzing large volumes of data without human bias. We selected the White Spectacled Bulbul ( Pycnonotus xanthopygos ) as our bird model because it has a complex vocal communication system with a large repertoire which is used by both sexes, year-round. It is a common, widespread passerine in Israel, which is relatively easy to locate and record in a broad range of habitats. Like many passerines, the Bulbul's vocal communication consists of two primary hierarchies of utterances, syllables and words . To extract each of these units' characteristics, the fundamental frequency contour was modeled using a low degree Legendre polynomial, enabling it to capture the different patterns of variation from different vocalizations, so that each pattern could be effectively expressed using very few coefficients. In addition, a mel-spectrogram was computed for each unit, and several features were extracted both in the time-domain (e.g., zero-crossing rate and energy) and frequency-domain (e.g., spectral centroid and spectral flatness). We applied both linear and non-linear dimensionality reduction algorithms on feature vectors and validated the findings that were obtained manually, namely by listening and examining the spectrograms visually. Using these algorithms, we show that the Bulbul has a complex vocabulary of more than 30 words, that there are multiple syllables that are combined in different words, and that a particular syllable can appear in several words. Using our system, researchers will be able to analyze hundreds of hours of audio recordings, to obtain objective evaluation of repertoires, and to identify different vocal units and distinguish between them, thus gaining a broad perspective on bird vocal communication., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Marck, Vortman, Kolodny and Lavner.)

Evolutionary accounts of feelings, and in particular of negative affect and of pain, assume that creatures that feel and care about the outcomes of their behavior outperform those that do not in terms of their evolutionary fitness. Such accounts, however, can only work if feelings can be shown to contribute to fitness-influencing outcomes. Simply assuming that a learner that feels and cares about outcomes is more strongly motivated than one that does is not enough, if only because motivation can be tied directly to outcomes by incorporating an appropriate reward function, without leaving any apparent role to feelings (as it is done in state-of-the-art engineered systems based on reinforcement learning). Here, we propose a possible mechanism whereby pain contributes to fitness: an actor-critic functional architecture for reinforcement learning, in which pain reflects the costs imposed on actors in their bidding for control, so as to promote honest signaling and ultimately help the system optimize learning and future behavior., (© The Author(s) 2021. Published by Oxford University Press.)

In the last decade, we have witnessed a major paradigm shift in the life sciences: the recognition that the microbiome, i.e. the set of microorganisms associated with healthy animals (including humans) and plants, plays a crucial role in the sustained health and fitness of its host. Enabled by rapid advances in sequencing technologies and analytical methods, substantial advances have been achieved in both identifying the microbial taxa and understanding the relationship between microbiome composition and host phenotype. These breakthroughs are leading to novel strategies for improved human and animal health, enhanced crop yield and nutritional quality, and the control of various pests and disease agents. This article is part of the theme issue 'The role of the microbiome in host evolution'.

Host-associated microbiomes influence their host's fitness in myriad ways and can be viewed as a source of phenotypic plasticity. This plasticity may allow the host to accommodate novel environmental challenges and thus influence the host's evolutionary adaptation. As with other modalities of phenotypic plasticity in phenomena such as the Baldwin effect and genetic assimilation, the microbiome-mediated plasticity may influence host genetic adaptation by facilitating and accelerating it, by slowing it down, or even by preventing it. The dynamics involved are likely more complex than those of previously studied phenomena related to phenotypic plasticity, and involve different processes on each time scale, such as acquired recognition of newly associated microbes by the host's immune system on single- and multiple-generation time scales, or selection on transmission dynamics of microbes between hosts, acting on longer time scales. To date, it is unclear if and how any of these processes shape host evolution. This opinion piece article provides a conceptual framework for considering the processes by which microbiome-mediated plasticity directs host evolution and concludes with suggestions for key experimental tests of the presented ideas. This article is part of the theme issue 'The role of the microbiome in host evolution'.

The course of infection by SARS-CoV-2 frequently includes a long asymptomatic period, followed in some individuals by an immune dysregulation period that may lead to complications and immunopathology-induced death. This course of disease suggests that the virus often evades detection by the innate immune system. We suggest a novel therapeutic approach to mitigate the infection's severity, probability of complications and duration. We propose that priming an individual's innate immune system for viral attack shortly before it is expected to occur may allow pre-activation of the preferable trajectory of immune response, leading to early detection of the virus. Priming can be carried out, for example, by administering a standard vaccine or another reagent that elicits a broad anti-viral innate immune response. By the time that the expected SARS-CoV-2 infection occurs, activation cascades will have been put in motion and levels of immune factors needed to combat the infection will have been elevated. The infection would thus be cleared faster and with less complication than otherwise, alleviating adverse clinical outcomes at the individual level. Moreover, priming may also mitigate population-level risk by reducing need for hospitalizations and decreasing the infectious period of individuals, thus slowing the spread and reducing the impact of the epidemic. In view of the latter consideration, our proposal may have a significant epidemiological impact even if applied primarily to low-risk individuals, such as young adults, who often show mild symptoms or none, by shortening the period during which they unknowingly infect others. The proposed view is, at this time, an unproven hypothesis. Although supported by robust bio-medical reasoning and multiple lines of evidence, carefully designed clinical trials are necessary.

Baumard's perspective asserts that "opportunity is the mother of innovation," in contrast to the adage ascribing this role to necessity. Drawing on behavioral ecology and cognition, we propose that both extremes - affluence and scarcity - can drive innovation. We suggest that the types of innovations at these two extremes differ and that both rely on mechanisms operating on different time scales.

Neanderthals and modern humans both occupied the Levant for tens of thousands of years prior to the spread of modern humans into the rest of Eurasia and their replacement of the Neanderthals. That the inter-species boundary remained geographically localized for so long is a puzzle, particularly in light of the rapidity of its subsequent movement. Here, we propose that infectious-disease dynamics can explain the localization and persistence of the inter-species boundary. We further propose, and support with dynamical-systems models, that introgression-based transmission of alleles related to the immune system would have gradually diminished this barrier to pervasive inter-species interaction, leading to the eventual release of the inter-species boundary from its geographic localization. Asymmetries between the species in the characteristics of their associated 'pathogen packages' could have generated feedback that allowed modern humans to overcome disease burden earlier than Neanderthals, giving them an advantage in their subsequent spread into Eurasia.

This article consists of commentaries on a selected group of papers of Marc Feldman published in Theoretical Population Biology from 1970 to the present. The papers describe a diverse set of population-genetic models, covering topics such as cultural evolution, social evolution, and the evolution of recombination. The commentaries highlight Marc Feldman's role in providing mathematically rigorous formulations to explore qualitative hypotheses, in many cases generating surprising conclusions., (Copyright © 2018 Elsevier Inc. All rights reserved.)

The host-associated microbiome affects individual health and behaviour, and may be influenced by local environmental conditions. However, little is known about microbiomes' temporal dynamics in free-living species compared with their dynamics in humans and model organisms, especially in body sites other than the gut. Here, we investigate longitudinal changes in the fur microbiome of captive and free-living Egyptian fruit bats. We find that, in contrast to patterns described in humans and other mammals, the prominent dynamics is of change over time at the level of the colony as a whole. On average, a pair of fur microbiome samples from different individuals in the same colony collected on the same date are more similar to one another than a pair of samples from the same individual collected at different time points. This pattern suggests that the whole colony may be the appropriate biological unit for understanding some of the roles of the host microbiome in social bats' ecology and evolution. This pattern of synchronized colony changes over time is also reflected in the profile of volatile compounds in the bats' fur, but differs from the more individualized pattern found in the bats' gut microbiome.

We propose that food-related uncertainty is but one of multiple cues that predicts harsh conditions and may activate "incentive hope." An evolutionarily adaptive response to these would have been to shift to a behavioral-metabolic phenotype geared toward facing hardship. In modernity, this phenotype may lead to pathologies such as obesity and hoarding. Our perspective suggests a novel therapeutic approach.

Culture evolves according to dynamics on multiple temporal scales, from individuals' minute-by-minute behaviour to millennia of cultural accumulation that give rise to population-level differences. These dynamics act on a range of entities-including behavioural sequences, ideas and artefacts as well as individuals, populations and whole species-and involve mechanisms at multiple levels, from neurons in brains to inter-population interactions. Studying such complex phenomena requires an integration of perspectives from a diverse array of fields, as well as bridging gaps between traditionally disparate areas of study. In this article, which also serves as an introduction to the current special issue, we highlight some specific respects in which the study of cultural evolution has benefited and should continue to benefit from an integrative approach. We showcase a number of pioneering studies of cultural evolution that bring together numerous disciplines. These studies illustrate the value of perspectives from different fields for understanding cultural evolution, such as cognitive science and neuroanatomy, behavioural ecology, population dynamics, and evolutionary genetics. They also underscore the importance of understanding cultural processes when interpreting research about human genetics, neuroscience, behaviour and evolution.This article is part of the theme issue 'Bridging cultural gaps: interdisciplinary studies in human cultural evolution'., (© 2018 The Author(s).)

Language plays a pivotal role in the evolution of human culture, yet the evolution of the capacity for language-uniquely within the hominin lineage-remains little understood. Bringing together insights from cognitive psychology, neuroscience, archaeology and behavioural ecology, we hypothesize that this singular occurrence was triggered by exaptation, or 'hijacking', of existing cognitive mechanisms related to sequential processing and motor execution. Observed coupling of the communication system with circuits related to complex action planning and control supports this proposition, but the prehistoric ecological contexts in which this coupling may have occurred and its adaptive value remain elusive. Evolutionary reasoning rules out most existing hypotheses regarding the ecological context of language evolution, which focus on ultimate explanations and ignore proximate mechanisms. Coupling of communication and motor systems, although possible in a short period on evolutionary timescales, required a multi-stepped adaptive process, involving multiple genes and gene networks. We suggest that the behavioural context that exerted the selective pressure to drive these sequential adaptations had to be one in which each of the systems undergoing coupling was independently necessary or highly beneficial, as well as frequent and recurring over evolutionary time. One such context could have been the teaching of tool production or tool use. In the present study, we propose the Cognitive Coupling hypothesis, which brings together these insights and outlines a unifying theory for the evolution of the capacity for language.This article is part of the theme issue 'Bridging cultural gaps: interdisciplinary studies in human cultural evolution'., (© 2018 The Authors.)

Most hypotheses in the heated debate about the Neanderthals' replacement by modern humans highlight the role of environmental pressures or attribute the Neanderthals' demise to competition with modern humans, who occupied the same ecological niche. The latter assume that modern humans benefited from some selective advantage over Neanderthals, which led to the their extinction. Here we show that a scenario of migration and selectively neutral species drift predicts the Neanderthals' replacement. Our model offers a parsimonious alternative to those that invoke external factors or selective advantage, and represents a null hypothesis for assessing such alternatives. For a wide range of parameters, this hypothesis cannot be rejected. Moreover, we suggest that although selection and environmental factors may or may not have played a role in the inter-species dynamics of Neanderthals and modern humans, the eventual replacement of the Neanderthals was determined by the repeated migration of modern humans from Africa into Eurasia.

Alternative behavioral strategies typically differ in their associated risks, meaning that a different variance in fitness-related outcomes characterizes each behavior. Understanding how selection acts on risk preference is crucial to interpreting and predicting behavior. Despite much research, most theoretical frameworks have been laid out as optimization problems from the individual's perspective, and the influence of population dynamics has been underappreciated. We use agent-based simulations that implement competition between two simple behavioral strategies to illuminate effects of population dynamics on risk-taking. We explore the effects of inter-generational reproduction dynamics, population size, the number of decisions throughout an individual's life, and simple alternate distributions of risk. We find that these factors, very often ignored in empirical and theoretical studies of behavior, can have significant and non-intuitive impacts on the selection of alternative behavioral strategies. Our results demonstrate that simple rules regarding predicted risk preference do not hold across the complete range of each of the factors we studied; we propose intuitive interpretations for the dynamics within each regime. We suggest that studies of behavioral strategies should explicitly take into account the species' life history and the ecological context in which selection acted on the risk-related behavior of the organism of interest.

When humans and other animals make cultural innovations, they also change their environment, thereby imposing new selective pressures that can modify their biological traits. For example, there is evidence that dairy farming by humans favored alleles for adult lactose tolerance. Similarly, the invention of cooking possibly affected the evolution of jaw and tooth morphology. However, when it comes to cognitive traits and learning mechanisms, it is much more difficult to determine whether and how their evolution was affected by culture or by their use in cultural transmission. Here we argue that, excluding very recent cultural innovations, the assumption that culture shaped the evolution of cognition is both more parsimonious and more productive than assuming the opposite. In considering how culture shapes cognition, we suggest that a process-level model of cognitive evolution is necessary and offer such a model. The model employs relatively simple coevolving mechanisms of learning and data acquisition that jointly construct a complex network of a type previously shown to be capable of supporting a range of cognitive abilities. The evolution of cognition, and thus the effect of culture on cognitive evolution, is captured through small modifications of these coevolving learning and data-acquisition mechanisms, whose coordinated action is critical for building an effective network. We use the model to show how these mechanisms are likely to evolve in response to cultural phenomena, such as language and tool-making, which are associated with major changes in data patterns and with new computational and statistical challenges., Competing Interests: The authors declare no conflict of interest.

Human cultural traits-behaviors, ideas, and technologies that can be learned from other individuals-can exhibit complex patterns of transmission and evolution, and researchers have developed theoretical models, both verbal and mathematical, to facilitate our understanding of these patterns. Many of the first quantitative models of cultural evolution were modified from existing concepts in theoretical population genetics because cultural evolution has many parallels with, as well as clear differences from, genetic evolution. Furthermore, cultural and genetic evolution can interact with one another and influence both transmission and selection. This interaction requires theoretical treatments of gene-culture coevolution and dual inheritance, in addition to purely cultural evolution. In addition, cultural evolutionary theory is a natural component of studies in demography, human ecology, and many other disciplines. Here, we review the core concepts in cultural evolutionary theory as they pertain to the extension of biology through culture, focusing on cultural evolutionary applications in population genetics, ecology, and demography. For each of these disciplines, we review the theoretical literature and highlight relevant empirical studies. We also discuss the societal implications of the study of cultural evolution and of the interactions of humans with one another and with their environment., Competing Interests: The authors declare no conflict of interest.

Evidence for interactions between populations plays a prominent role in the reconstruction of historical and prehistoric human dynamics; these interactions are usually interpreted to reflect cultural practices or demographic processes. The sharp increase in long-distance transportation of lithic material between the Middle and Upper Palaeolithic, for example, is seen as a manifestation of the cultural revolution that defined the transition between these epochs. Here, we propose that population interaction is not only a reflection of cultural change but also a potential driver of it. We explore the possible effects of inter-population migration on cultural evolution when migrating individuals possess core technological knowledge from their original population. Using a computational framework of cultural evolution that incorporates realistic aspects of human innovation processes, we show that migration can lead to a range of outcomes, including punctuated but transient increases in cultural complexity, an increase of cultural complexity to an elevated steady state and the emergence of a positive feedback loop that drives ongoing acceleration in cultural accumulation. Our findings suggest that population contact may have played a crucial role in the evolution of hominin cultures and propose explanations for observations of Palaeolithic cultural change whose interpretations have been hotly debated., (© 2017 The Authors.)

One of the most puzzling features of the prehistoric record of hominid stone tools is its apparent punctuation: it consists of abrupt bursts of dramatic change that separate long periods of largely unchanging technology. Within each such period, small punctuated cultural modifications take place. Punctuation on multiple timescales and magnitudes is also found in cultural trajectories from historical times. To explain these sharp cultural bursts, researchers invoke such external factors as sudden environmental change, rapid cognitive or morphological change in the hominids that created the tools, or replacement of one species or population by another. Here we propose a dynamic model of cultural evolution that accommodates empirical observations: without invoking external factors, it gives rise to a pattern of rare, dramatic cultural bursts, interspersed by more frequent, smaller, punctuated cultural modifications. Our model includes interdependent innovation processes that occur at different rates. It also incorporates a realistic aspect of cultural evolution: cultural innovations, such as those that increase food availability or that affect cultural transmission, can change the parameters that affect cultural evolution, thereby altering the population's cultural dynamics and steady state. This steady state can be regarded as a cultural carrying capacity. These parameter-changing cultural innovations occur very rarely, but whenever one occurs, it triggers a dramatic shift towards a new cultural steady state. The smaller and more frequent punctuated cultural changes, on the other hand, are brought about by innovations that spur the invention of further, related, technology, and which occur regardless of whether the population is near its cultural steady state. Our model suggests that common interpretations of cultural shifts as evidence of biological change, for example the appearance of behaviorally modern humans, may be unwarranted., Competing Interests: The authors have declared that no competing interests exist.

As a highly consequential biological trait, a memory "bottleneck" cannot escape selection pressures. It must therefore co-evolve with other cognitive mechanisms rather than act as an independent constraint. Recent theory and an implemented model of language acquisition suggest that a limit on working memory may evolve to help learning. Furthermore, it need not hamper the use of language for communication.

Archaeological accounts of cultural change reveal a fundamental conflict: Some suggest that change is gradual, accelerating over time, whereas others indicate that it is punctuated, with long periods of stasis interspersed by sudden gains or losses of multiple traits. Existing models of cultural evolution, inspired by models of genetic evolution, lend support to the former and do not generate trajectories that include large-scale punctuated change. We propose a simple model that can give rise to both exponential and punctuated patterns of gain and loss of cultural traits. In it, cultural innovation comprises several realistic interdependent processes that occur at different rates. The model also takes into account two properties intrinsic to cultural evolution: the differential distribution of traits among social groups and the impact of environmental change. In our model, a population may be subdivided into groups with different cultural repertoires leading to increased susceptibility to cultural loss, whereas environmental change may lead to rapid loss of traits that are not useful in a new environment. Taken together, our results suggest the usefulness of a concept of an effective cultural population size.

The "problem of serial order in behavior," as formulated and discussed by Lashley (1951), is arguably more pervasive and more profound both than originally stated and than currently appreciated. We spell out two complementary aspects of what we term the generalized problem of behavior: (i) multimodality, stemming from the disparate nature of the sensorimotor variables and processes that underlie behavior, and (ii) concurrency, which reflects the parallel unfolding in time of these processes and of their asynchronous interactions. We illustrate these on a number of examples, with a special focus on language, briefly survey the computational approaches to multimodal concurrency, offer some hypotheses regarding the manner in which brains address it, and discuss some of the broader implications of these as yet unresolved issues for cognitive science., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

The skills required for the learning and use of language are the focus of extensive research, and their evolutionary origins are widely debated. Using agent-based simulations in a range of virtual environments, we demonstrate that challenges of foraging for food can select for cognitive mechanisms supporting complex, hierarchical, sequential learning, the need for which arises in language acquisition. Building on previous work, where we explored the conditions under which reinforcement learning is out-competed by seldom-reinforced continuous learning that constructs a network model of the environment, we now show that realistic features of the foraging environment can select for two critical advances: (i) chunking of meaningful sequences found in the data, leading to representations composed of units that better fit the prevalent statistical patterns in the environment; and (ii) generalization across units based on their contextual similarity. Importantly, these learning processes, which in our framework evolved for making better foraging decisions, had been earlier shown to reproduce a range of findings in language learning in humans. Thus, our results suggest a possible evolutionary trajectory that may have led from basic learning mechanisms to complex hierarchical sequential learning that can support advanced cognitive abilities of the kind needed for language acquisition., (© 2015 The Author(s) Published by the Royal Society. All rights reserved.)

Natural behaviors, such as foraging, tool use, social interaction, birdsong, and language, exhibit branching sequential structure. Such structure should be learnable if it can be inferred from the statistics of early experience. We report that juvenile zebra finches learn such sequential structure in song. Song learning in finches has been extensively studied, and it is generally believed that young males acquire song by imitating tutors (Zann, 1996). Variability in the order of elements in an individual's mature song occurs, but the degree to which variation in a zebra finch's song follows statistical regularities has not been quantified, as it has typically been dismissed as production error (Sturdy et al., 1999). Allowing for the possibility that such variation in song is non-random and learnable, we applied a novel analytical approach, based on graph-structured finite-state grammars, to each individual's full corpus of renditions of songs. This method does not assume syllable-level correspondence between individuals. We find that song variation can be described by probabilistic finite-state graph grammars that are individually distinct, and that the graphs of juveniles are more similar to those of their fathers than to those of other adult males. This grammatical learning is a new parallel between birdsong and language. Our method can be applied across species and contexts to analyze complex variable learned behaviors, as distinct as foraging, tool use, and language.

We introduce a set of biologically and computationally motivated design choices for modeling the learning of language, or of other types of sequential, hierarchically structured experience and behavior, and describe an implemented system that conforms to these choices and is capable of unsupervised learning from raw natural-language corpora. Given a stream of linguistic input, our model incrementally learns a grammar that captures its statistical patterns, which can then be used to parse or generate new data. The grammar constructed in this manner takes the form of a directed weighted graph, whose nodes are recursively (hierarchically) defined patterns over the elements of the input stream. We evaluated the model in seventeen experiments, grouped into five studies, which examined, respectively, (a) the generative ability of grammar learned from a corpus of natural language, (b) the characteristics of the learned representation, (c) sequence segmentation and chunking, (d) artificial grammar learning, and (e) certain types of structure dependence. The model's performance largely vindicates our design choices, suggesting that progress in modeling language acquisition can be made on a broad front-ranging from issues of generativity to the replication of human experimental findings-by bringing biological and computational considerations, as well as lessons from prior efforts, to bear on the modeling approach., (Copyright © 2014 Cognitive Science Society, Inc.)

An associative learning account of mirror neurons should not preclude genetic evolution of its underlying mechanisms. On the contrary, an associative learning framework for cognitive development should seek heritable variation in the learning rules and in the data-acquisition mechanisms that construct associative networks, demonstrating how small genetic modifications of associative elements can give rise to the evolution of complex cognition.

Continuous, 'always on', learning of structure from a stream of data is studied mainly in the fields of machine learning or language acquisition, but its evolutionary roots may go back to the first organisms that were internally motivated to learn and represent their environment. Here, we study under what conditions such continuous learning (CL) may be more adaptive than simple reinforcement learning and examine how it could have evolved from the same basic associative elements. We use agent-based computer simulations to compare three learning strategies: simple reinforcement learning; reinforcement learning with chaining (RL-chain) and CL that applies the same associative mechanisms used by the other strategies, but also seeks statistical regularities in the relations among all items in the environment, regardless of the initial association with food. We show that a sufficiently structured environment favours the evolution of both RL-chain and CL and that CL outperforms the other strategies when food is relatively rare and the time for learning is limited. This advantage of internally motivated CL stems from its ability to capture statistical patterns in the environment even before they are associated with food, at which point they immediately become useful for planning.

In Drosophila, multiple lines of evidence converge in suggesting that beneficial substitutions to the genome may be common. All suffer from confounding factors, however, such that the interpretation of the evidence-in particular, conclusions about the rate and strength of beneficial substitutions-remains tentative. Here, we use genome-wide polymorphism data in D. simulans and sequenced genomes of its close relatives to construct a readily interpretable characterization of the effects of positive selection: the shape of average neutral diversity around amino acid substitutions. As expected under recurrent selective sweeps, we find a trough in diversity levels around amino acid but not around synonymous substitutions, a distinctive pattern that is not expected under alternative models. This characterization is richer than previous approaches, which relied on limited summaries of the data (e.g., the slope of a scatter plot), and relates to underlying selection parameters in a straightforward way, allowing us to make more reliable inferences about the prevalence and strength of adaptation. Specifically, we develop a coalescent-based model for the shape of the entire curve and use it to infer adaptive parameters by maximum likelihood. Our inference suggests that ∼13% of amino acid substitutions cause selective sweeps. Interestingly, it reveals two classes of beneficial fixations: a minority (approximately 3%) that appears to have had large selective effects and accounts for most of the reduction in diversity, and the remaining 10%, which seem to have had very weak selective effects. These estimates therefore help to reconcile the apparent conflict among previously published estimates of the strength of selection. More generally, our findings provide unequivocal evidence for strongly beneficial substitutions in Drosophila and illustrate how the rapidly accumulating genome-wide data can be leveraged to address enduring questions about the genetic basis of adaptation., Competing Interests: The authors have declared that no competing interests exist.