The genetical theory of multilevel selection

A systematic framework for understanding the microbiome in human health and disease: from basic principles to clinical translation

The human microbiome is a complex and dynamic system that plays important roles in human health and disease. However, there remain limitations and theoretical gaps in our current understanding of the intricate relationship between microbes and humans. In this narrative review, we integrate the knowledge and insights from various fields, including anatomy, physiology, immunology, histology, genetics, and evolution, to propose a systematic framework. It introduces key concepts such as the 'innate and adaptive genomes', which enhance genetic and evolutionary comprehension of the human genome. The 'germ-free syndrome' challenges the traditional 'microbes as pathogens' view, advocating for the necessity of microbes for health. The 'slave tissue' concept underscores the symbiotic intricacies between human tissues and their microbial counterparts, highlighting the dynamic health implications of microbial interactions. 'Acquired microbial immunity' positions the microbiome as an adjunct to human immune systems, providing a rationale for probiotic therapies and prudent antibiotic use. The 'homeostatic reprogramming hypothesis' integrates the microbiome into the internal environment theory, potentially explaining the change in homeostatic indicators post-industrialization. The 'cell-microbe co-ecology model' elucidates the symbiotic regulation affecting cellular balance, while the 'meta-host model' broadens the host definition to include symbiotic microbes. The 'health-illness conversion model' encapsulates the innate and adaptive genomes' interplay and dysbiosis patterns. The aim here is to provide a more focused and coherent understanding of microbiome and highlight future research avenues that could lead to a more effective and efficient healthcare system.

Evolution of transmissible cancers: An adaptive, plastic strategy of selfish genetic elements?

A growing number of studies have applied evolutionary and ecological principles to understanding cancer. However, few such studies have examined whether phenotypic plasticity--the ability of a single individual or genome to respond differently to different environmental circumstances--can impact the origin and spread of cancer. Here, we propose the adaptive horizontal transmission hypothesis to explain how flexible decision-making by selfish genetic elements can cause them to spread from the genome of their original host into the genomes of other hosts through the evolution of transmissible cancers. Specifically, we hypothesize that such cancers appear when the likelihood of successful vertical transmission is sufficiently low relative to the likelihood of successful horizontal transmission. We develop an evolutionary optimization model of this hypothesis, highlight empirical findings that support it, and offer suggestions for future research. Generally, phenotypically plastic selfish genetic elements might play an important role in the evolution of transmissible cancers.

Behavioral selection in structured populations

The multilevel model of behavioral selection (MLBS) by Borgstede and Eggert (Behav Process 186:104370. 10.1016/j.beproc.2021.104370 , 2021) provides a formal framework that integrates reinforcement learning with natural selection using an extended Price equation. However, the MLBS is so far only formulated for homogeneous populations, thereby excluding all sources of variation between individuals. This limitation is of primary theoretical concern because any application of the MLBS to real data requires to account for variation between individuals. In this paper, I extend the MLBS to account for inter-individual variation by dividing the population into homogeneous sub-populations and including class-specific reproductive values as weighting factors for an individual's evolutionary fitness. The resulting formalism closes the gap between the theoretical underpinnings of behavioral selection and the application of the theory to empirical data, which naturally includes inter-individual variation. Furthermore, the extended MLBS is used to establish an explicit connection between the dynamics of learning and the maximization of individual fitness. These results expand the scope of the MLBS as a general theoretical framework for the quantitative analysis of learning and evolution.

On the Interpretation of the Operation of Natural Selection in Class-Structured Populations

AbstractBiological adaptation is the outcome of allele-frequency change by natural selection. At the same time, populations are usually class structured as individuals occupy different states, such as age, sex, or stage. This is known to result in the differential transmission of alleles through nonheritable fitness differences called class transmission, which also affects allele-frequency change even in the absence of selection. How does one then isolate allele-frequency change due to selection from that due to class transmission? We decompose one-generational allele-frequency change in terms of effects of selection and class transmission and show how reproductive values can be used to reach a decomposition between any two distant generations of the evolutionary process. This provides a missing relationship between multigenerational allele-frequency change and the operation of selection. It also allows a measure of fitness to be defined summarizing the effect of selection in a multigenerational evolutionary process, which connects asymptotically to invasion fitness.

Phenoptosis and the Various Types of Natural Selection

In the first description of evolution, the fundamental mechanism is the natural selection favoring the individuals best suited for survival and reproduction (selection at the individual level or classical Darwinian selection). However, this is a very reductive description of natural selection that does not consider or explain a long series of known phenomena, including those in which an individual sacrifices or jeopardizes his life on the basis of genetically determined mechanisms (i.e., phenoptosis). In fact, in addition to (i) selection at the individual level, it is essential to consider other types of natural selection such as those concerning: (ii) kin selection and some related forms of group selection; (iii) the interactions between the innumerable species that constitute a holobiont; (iv) the origin of the eukaryotic cell from prokaryotic organisms; (v) the origin of multicellular eukaryotic organisms from unicellular organisms; (vi) eusociality (e.g., in many species of ants, bees, termites); (vii) selection at the level of single genes, or groups of genes; (viii) the interactions between individuals (or more precisely their holobionts) of the innumerable species that make up an ecosystem. These forms of natural selection, which are all effects and not violations of the classical Darwinian selection, also show how concepts as life, species, individual, and phenoptosis are somewhat not entirely defined and somehow arbitrary. Furthermore, the idea of organisms selected on the basis of their survival and reproduction capabilities is intertwined with that of organisms also selected on the basis of their ability to cooperate and interact, even by losing their lives or their distinct identities.

Reuniting philosophy and science to advance cancer research

Cancers rely on multiple, heterogeneous processes at different scales, pertaining to many biomedical fields. Therefore, understanding cancer is necessarily an interdisciplinary task that requires placing specialised experimental and clinical research into a broader conceptual, theoretical, and methodological framework. Without such a framework, oncology will collect piecemeal results, with scant dialogue between the different scientific communities studying cancer. We argue that one important way forward in service of a more successful dialogue is through greater integration of applied sciences (experimental and clinical) with conceptual and theoretical approaches, informed by philosophical methods. By way of illustration, we explore six central themes: (i) the role of mutations in cancer; (ii) the clonal evolution of cancer cells; (iii) the relationship between cancer and multicellularity; (iv) the tumour microenvironment; (v) the immune system; and (vi) stem cells. In each case, we examine open questions in the scientific literature through a philosophical methodology and show the benefit of such a synergy for the scientific and medical understanding of cancer.

Spontaneous Emergence of Multicellular Heritability

The major transitions in evolution include events and processes that result in the emergence of new levels of biological individuality. For collectives to undergo Darwinian evolution, their traits must be heritable, but the emergence of higher-level heritability is poorly understood and has long been considered a stumbling block for nascent evolutionary transitions. Using analytical models, synthetic biology, and biologically-informed simulations, we explored the emergence of trait heritability during the evolution of multicellularity. Prior work on the evolution of multicellularity has asserted that substantial collective-level trait heritability either emerges only late in the transition or requires some evolutionary change subsequent to the formation of clonal multicellular groups. In a prior analytical model, we showed that collective-level heritability not only exists but is usually more heritable than the underlying cell-level trait upon which it is based, as soon as multicellular groups form. Here, we show that key assumptions and predictions of that model are borne out in a real engineered biological system, with important implications for the emergence of collective-level heritability.

The role of the ecological scaffold in the origin and maintenance of whole-group trait altruism in microbial populations

BACKGROUND

Kin and multilevel selection provide explanations for the existence of altruism based on traits or processes that enhance the inclusive fitness of an altruist individual. Kin selection is often based on individual-level traits, such as the ability to recognize other altruists, whereas multilevel selection requires a metapopulation structure and dispersal process. These theories are unified by the general principle that altruism can be fixed by positive selection provided the benefit of altruism is preferentially conferred to other altruists. Here we take a different explanatory approach based on the recently proposed concept of an "ecological scaffold". We demonstrate that ecological conditions consisting of a patchy nutrient supply that generates a metapopulation structure, episodic mixing of groups, and severe nutrient limitation, can support or "scaffold" the evolution of altruism in a population of microbes by amplifying drift. This contrasts with recent papers in which the ecological scaffold was shown to support selective processes and demonstrates the power of scaffolding even in the absence of selection.

RESULTS

Using computer simulations motivated by a simple theoretical model, we show that, although an altruistic mutant can be fixed within a single population of non-altruists by drift when nutrients are severely limited, the resulting altruistic population remains vulnerable to non-altruistic mutants. We then show how the imposition of the "ecological scaffold" onto a population of non-altruists alters the balance between selection and drift in a way that supports the fixation and subsequent persistence of altruism despite the possibility of invasion by non-altruists.

CONCLUSIONS

The fixation of an altruistic mutant by drift is possible when supported by ecological conditions that impose a metapopulation structure, episodic mixing of groups, and severe nutrient limitation. This is significant because it offers an alternative explanation for the evolution of altruism based on drift rather than selection. Given the ubiquity of low-nutrient "oligotrophic" environments in which microbes exist (e.g., the open ocean, deep subsurface soils, or under the polar ice caps) our results suggest that altruistic and cooperative behaviors may be highly prevalent among microbial populations.

Kin selection theory and the design of cooperative crops

In agriculture and plant breeding, plant traits may be favoured because they benefit neighbouring plants and ultimately increase total crop yield. This idea of promoting cooperation among crop plants has existed almost as long as W.D. Hamilton's inclusive fitness (kin selection) theory, the leading framework for explaining cooperation in biology. However, kin selection thinking has not been adequately applied to the idea of cooperative crops. Here, I give an overview of modern kin selection theory and consider how it explains three key strategies for designing cooperative crops: (1) selection for a less-competitive plant type (a 'communal ideotype'); (2) group-level selection for yield; and (3) exploiting naturally selected cooperation. The first two strategies, using artificial selection, have been successful in the past but suffer from limitations that could hinder future progress. Instead, I propose an alternative strategy and a new 'colonial ideotype' that exploits past natural selection for cooperation among the modules (e.g., branches or stems) of individual plants. More generally, I suggest that Hamiltonian agriculture-a kin selection view of agriculture and plant breeding-transforms our understanding of how to improve crops of the future.

Evolution of class-structured populations in periodic environments

What is the influence of periodic environmental fluctuations on life-history evolution? We present a general theoretical framework to understand and predict the long-term evolution of life-history traits under a broad range of ecological scenarios. Specifically, we investigate how periodic fluctuations affect selection when the population is also structured in distinct classes. This analysis yields time-varying selection gradients that clarify the influence of the fluctuations of the environment on the competitive ability of a specific life-history mutation. We use this framework to analyse the evolution of key life-history traits of pathogens. We examine three different epidemiological scenarios and we show how periodic fluctuations of the environment can affect the evolution of virulence and transmission as well as the preference for different hosts. These examples yield new and testable predictions on pathogen evolution, and illustrate how our approach can provide a better understanding of the evolutionary consequences of time-varying environmental fluctuations in a broad range of scenarios.

The emergence of group fitness

Whether and how selection can act on collectives rather than single entities has been a tumultuous issue in evolutionary biology for decades. Despite examples of multilevel selection, a simple framework is needed that makes explicit the constraints that lead to the emergence of a "group fitness function." We use evolutionary game theory to show that two constraints are sufficient for the emergence of a well-defined group fitness, which could even apply to multispecies groups. First, different parts of the group contribute to one another's growth via resources produced proportionally to the density of each resource producer (not the density of the population receiving benefits). Second, invading groups do not share these resources with resident groups. Jointly, these two constraints lead to the "entanglement" of invading individuals' outcomes such that individual fitness can no longer be defined and group fitness predicts evolutionary dynamics through the emergence of a higher level evolutionary individual. Group fitness is an emergent property, irreducible to the fitness of the group's parts and exhibiting downward causality on the parts. By formalizing group fitness as a model for evolutionary transitions in individuality, these results open up a broad class of models under the multilevel-selection framework.

Selection on age-specific survival: Constant versus fluctuating environment

According to a classic result in evolutionary biodemography, selection on age-specific survival invariably declines with reproductive age. The result assumes proportional changes in survival and a constant environment. Here, we look at selection on age-specific survival when changes are still proportional but the environment fluctuates. We find that selection may or may not decline with reproductive age depending on how exactly survival is proportionally altered by mutations. However, interpreted in neutral terms, the mathematics behind the classic result capture a general property that the genetics of populations with age structure possess both in a constant and in a fluctuating environment.

Toward a theory of evolution as multilevel learning

We apply the theory of learning to physically renormalizable systems in an attempt to outline a theory of biological evolution, including the origin of life, as multilevel learning. We formulate seven fundamental principles of evolution that appear to be necessary and sufficient to render a universe observable and show that they entail the major features of biological evolution, including replication and natural selection. It is shown that these cornerstone phenomena of biology emerge from the fundamental features of learning dynamics such as the existence of a loss function, which is minimized during learning. We then sketch the theory of evolution using the mathematical framework of neural networks, which provides for detailed analysis of evolutionary phenomena. To demonstrate the potential of the proposed theoretical framework, we derive a generalized version of the Central Dogma of molecular biology by analyzing the flow of information during learning (back propagation) and predicting (forward propagation) the environment by evolving organisms. The more complex evolutionary phenomena, such as major transitions in evolution (in particular, the origin of life), have to be analyzed in the thermodynamic limit, which is described in detail in the paper by Vanchurin et al. [V. Vanchurin, Y. I. Wolf, E. V. Koonin, M. I. Katsnelson, Proc. Natl. Acad. Sci. U.S.A. 119, 10.1073/pnas.2120042119 (2022)].

Identifying Causes of Social Evolution: Contextual Analysis, the Price Approach, and Multilevel Selection

Kin selection theory and multilevel selection theory are distinct approaches to explaining the evolution of social traits. The latter claims that it is useful to regard selection as a process that can occur on multiple levels of organisation such as the level of individuals and the level of groups. This is reflected in a decomposition of fitness into an individual component and a group component. This multilevel view is central to understanding and characterising evolutionary transitions in individuality, e.g., from unicellular life to multicellular organisms, but currently suffers from the lack of a consistent, quantifiable measure. Specifically, the two major statistical tools to determine the coefficients of such a decomposition, the multilevel Price equation and contextual analysis, are inconsistent and may disagree on whether group selection is present. Here we show that the reason for the discrepancies is that underlying the multilevel Price equation and contextual analysis are two non-equivalent causal models for the generation of individual fitness effects (thus leaving different “remainders” explained by group effects). While the multilevel Price equation assumes that the individual effect of a trait determines an individual's relative success within a group, contextual analysis posits that the individual effect is context-independent. Since these different assumptions reflect claims about the causal structure of the system, the correct approach cannot be determined on general theoretical or statistical grounds but must be identified by experimental intervention. We outline interventions that reveal the underlying causal structure and thus facilitate choosing the appropriate approach. We note that kin selection theory with its focus on the individual is immune to such inconsistency because it does not address causal structure with respect to levels of organisation. In contrast, our analysis of the two approaches to measuring group selection demonstrates that multilevel selection theory adds meaningful (falsifiable) causal structure to explain the sources of individual fitness and thereby constitutes a proper refinement of kin selection theory. Taking such refined causal structure into account seems indispensable for studying evolutionary transitions in individuality because these transitions are characterised by changes in the selection pressures that act on the respective levels.

Reproductive value and the evolution of altruism

Altruism is favored by natural selection provided that it delivers sufficient benefits to relatives. An altruist's valuation of her relatives depends upon the extent to which they carry copies of her genes - relatedness - and also on the extent to which they are able to transmit their own genes to future generations - reproductive value. However, although relatedness has received a great deal of attention with regard to altruism, reproductive value has been surprisingly neglected. We review how reproductive value modulates patterns of altruism in relation to individual differences in age, sex, and general condition, and discuss how social partners may manipulate each other's reproductive value to incentivize altruism. This topic presents opportunities for tight interplay between theoretical and empirical research.

Altruism and Phenoptosis as Programs Supported by Evolution

Phenoptosis is a programmed death that has emerged in the process of evolution, sometimes taking the form of an altruistic program. In particular, it is believed to be a weapon against the spread of pandemics in the past and an obstacle in fighting pandemics in the present (COVID). However, on the evolutionary scale, deterministic death is not associated with random relationships (for example, bacteria with a particular mutation), but is a product of higher nervous activity or a consequence of established hierarchy that reaches its maximal expression in eusocial communities of Hymenoptera and highly social communities of mammals. Unlike a simple association of individuals, eusociality is characterized by the appearance of non-reproductive individuals as the highest form of altruism. In contrast to primitive programs for unicellular organisms, higher multicellular organisms are characterized by the development of behavior-based phenoptotic programs, especially in the case of reproduction-associated limitation of lifespan. Therefore, we can say that the development of altruism in the course of evolution of sociality leads in its extreme manifestation to phenoptosis. Development of mathematical models for the emergence of altruism and programmed death contributes to our understanding of mechanisms underlying these paradoxical counterproductive (harmful) programs. In theory, this model can be applied not only to insects, but also to other social animals and even to the human society. Adaptive death is an extreme form of altruism. We consider altruism and programmed death as programmed processes in the mechanistic and adaptive sense, respectively. Mechanistically, this is a program existing as a predetermined chain of certain responses, regardless of its adaptive value. As to its adaptive value (regardless of the degree of "phenoptoticity"), this is a characteristic of organisms that demonstrate high levels of kinship, social organization, and physical association typical for higher-order individuals, e.g., unicellular organisms forming colonies with some characteristics of multicellular animals or colonies of multicellular animals displaying features of supraorganisms.

Sewall Wright's criticism of the gene's-eye view of evolution

The gene's-eye view of evolution has played a central but contentious role in evolutionary biology for the past half-century. By envisioning evolutionary history as a struggle between competing selfish genes, it accelerated the shift from organism-centric to gene-centric explanations that began with the emergence population genetics a century ago. At the forefront of this shift were George C. Williams and Richard Dawkins, who advocated an approach to thinking about evolution first introduced by R. A. Fisher. In this Perspective, I discuss the criticism of the gene's-eye view developed by another architect of population genetics, Sewall Wright, whose "On genic and organismic selection" was published in Evolution in 1980. I start by outlining the history of the gene's-eye view and then show how some long-standing differences in opinion over its value can be traced back to disagreements between Fisher and Wright, especially over Fisher's concept of genetic variance and the importance of epistasis. I end with some reflections on the role of genes and organisms in evolutionary explanations.

Experimentally measured group direct benefits according to worker density explain group living of the termite Reticulitermes chinensis

The evolution of cooperation requires more benefits of group living than solitary lifestyle. However, to some degree, our understanding about the benefits is hindered by abstract debates over theoretical and experimental evidences of individual selection or group selection because it is difficult to examine the actual benefits at the group level. Moreover, group density is a crucial ecological factor which deeply affects group reproduction and survival, few studies have been performed in social insects. Here, we study the effects of worker density on group direct benefits in the termite species Reticulitermes chinensis. The termite R. chinensis is an ideal model which lives with a high worker density in wood. We used the quantity of eggs and the total biomass (biomass of all group members) accumulation as two components of group benefits. We investigated the group benefits in the context of worker density according to eleven worker densities, and we measured the group benefits and the resource consumption with the same group members in two types of artificial nest areas. Moreover, we counted the stomodeal trophallaxis occurrences from any workers to queens under three worker densities to explore the degree of cooperation according to worker density. We found that both the number of eggs and the total biomass accumulation significantly increased with increasing worker density in groups. Furthermore, the consumption of resources was similar between groups with the same number of individuals gathered in small or large nest areas, but the production of eggs and the biomass accumulation were higher in groups of small nest areas than in large nest areas. Additionally, we found the stomodeal trophallaxis behavior significantly increased in higher worker density groups. Our results suggest that the group benefits influenced by the high worker density may at least partially explain the group living of eusocial insects in ecology.

Quasi-species evolution maximizes genotypic reproductive value (not fitness or flatness)

Growing efforts to measure fitness landscapes in molecular and microbial systems are motivated by a longstanding goal to predict future evolutionary trajectories. Sometimes under-appreciated, however, is that the fitness landscape and its topography do not by themselves determine the direction of evolution: under sufficiently high mutation rates, populations can climb the closest fitness peak (survival of the fittest), settle in lower regions with higher mutational robustness (survival of the flattest), or even fail to adapt altogether (error catastrophes). I show that another measure of reproductive success, Fisher's reproductive value, resolves the trade-off between fitness and robustness in the quasi-species regime of evolution: to forecast the motion of a population in genotype space, one should look for peaks in the (mutation-rate dependent) landscape of genotypic reproductive values-whether or not these peaks correspond to local fitness maxima or flat fitness plateaus. This new landscape picture turns quasi-species dynamics into an instance of non-equilibrium dynamics, in the physical sense of Markovian processes, potential landscapes, entropy production, etc.

Death happy: adaptive ageing and its evolution by kin selection in organisms with colonial ecology

Standard evolutionary theory, supported by mathematical modelling of outbred, dispersed populations predicts that ageing is not an adaptation. We recently argued that in clonal, viscous populations, programmed organismal death could promote fitness through social benefits and has, in some organisms (e.g. Caenorhabditis elegans), evolved to shorten lifespan. Here, we review previous adaptive death theory, including consumer sacrifice, biomass sacrifice and defensive sacrifice types of altruistic adaptive death. In addition, we discuss possible adaptive death in certain semelparous fish, coevolution of reproductive and adaptive death, and adaptive reproductive senescence in C. elegans. We also describe findings from recent tests for the existence of adaptive death in C. elegans using computer modelling. Such models have provided new insights into how trade-offs between fitness at the individual and colony levels mean that senescent changes can be selected traits. Exploring further the relationship between adaptive death and social interactions, we consider examples where adaptive death results more from action of kin than from self-destructive mechanisms and, to describe this, introduce the term adaptive killing of kin. This article is part of the theme issue 'Ageing and sociality: why, when and how does sociality change ageing patterns?'

Survival of the Systems

Since Darwin, individuals and more recently genes, have been the focus of evolutionary thinking. The idea that selection operates on nonreproducing, higher-level systems including ecosystems or societies, has met with scepticism. But research emphasising that natural selection can be based solely on differential persistence invites reconsideration of their evolution. Self-perpetuating feedback cycles involving biotic as well as abiotic components are critical to determining persistence. Evolution of autocatalytic networks of molecules is well studied, but the principles hold for any 'self-perpetuating' system. Ecosystem examples include coral reefs, rainforests, and savannahs. Societal examples include agricultural systems, dominant belief systems, and economies. Persistence-based selection of feedbacks can help us understand how ecological and societal systems survive or fail in a changing world.

Toward understanding of evolutionary constraints: experimental and theoretical approaches

Although organisms have diversified remarkably through evolution, they do not exhibit unlimited variability. During evolution, the phenotypic changes do not occur at random; instead, they are directional and restricted by the constraints imposed on them. Despite the perceived importance of characterizing the unevenness of these changes, studies on evolutionary constraints have been primarily qualitative in nature. In this review, we focus on the recent studies of evolutionary constraints, which are based on the quantification of high-dimensional phenotypic and genotypic data. Furthermore, we present a theoretical analysis that enables us to predict evolutionary constraints on the basis of phenotypic fluctuation, modeled on the fluctuation-response relationship in statistical physics. The review lays emphasis on the tight interactions between experimental and theoretical analyses in evolutionary biology that will contribute to a better understanding of evolutionary constraints.

Explanatory goals and explanatory means in multilevel selection theory

It has become customary in multilevel selection theory to use the same terms (namely "multilevel selection 1" and "multilevel selection 2") to denote both two explanatory goals (explaining why certain individual- and, respectively, group-level traits spread) and two explanatory means (namely, two kinds of group selection we may appeal to in such explanations). This paper spells out some of the benefits that derive from avoiding this terminological conflation. I argue that keeping explanatory means and goals well apart allows us to see that, contrary to a popular recent idea, Price's equation and contextual analysis-the statistical methods most extensively used for measuring the effects of certain evolutionary factors (like individual selection, group selection etc.) on the change in the focal individual trait in multilevel selection scenarios-do not come with built-in notions of group selection and, therefore, the efficacy of these methods at analyzing various kinds of cases does not constitute a basis for deciding how group selection should best be defined. Moreover, contrary to another widely accepted idea, I argue that more than one type of group selection may serve as explanatory means when one's goal is that of explaining the evolution of individual traits in multilevel selection scenarios and I spell out how this explanatory role should be understood.

Are kin and group selection rivals or friends?

Kin selection and group selection were once seen as competing explanatory hypotheses but now tend to be seen as equivalent ways of describing the same basic idea. Yet this 'equivalence thesis' seems not to have brought proponents of kin selection and group selection any closer together. This may be because the equivalence thesis merely shows the equivalence of two statistical formalisms without saying anything about causality. W.D. Hamilton was the first to derive an equivalence result of this type. Yet Hamilton was aware of its limitations, and saw that, while illuminating, it papered over some biologically important distinctions. Attending to these distinctions leads to the concept of 'K-G space', which helps us see where the biological disagreements between proponents of kin selection and group selection really lie.

Price's equation made clear

Price's equation provides a very simple-and very general-encapsulation of evolutionary change. It forms the mathematical foundations of several topics in evolutionary biology, and has also been applied outwith evolutionary biology to a wide range of other scientific disciplines. However, the equation's combination of simplicity and generality has led to a number of misapprehensions as to what it is saying and how it is supposed to be used. Here, I give a simple account of what Price's equation is, how it is derived, what it is saying and why this is useful. In particular, I suggest that Price's equation is useful not primarily as a predictor of evolutionary change but because it provides a general theory of selection. As an illustration, I discuss some of the insights Price's equation has brought to the study of social evolution. This article is part of the theme issue 'Fifty years of the Price equation'.

Opposite responses to selection and where to find them

We generally expect traits to evolve in the same direction as selection. However, many organisms possess traits that appear to be costly for individuals, while plant and animal breeding experiments reveal that selection may lead to no response or even negative responses to selection. We formalize both of these instances as cases of "opposite responses to selection." Using quantitative genetic models for the response to selection, we outline when opposite responses to selection should be expected. These typically occur when social selection opposes direct selection, when individuals interact with others less related to them than a random member of the population, and if the genetic covariance between direct and indirect effects is negative. We discuss the likelihood of each of these occurring in nature and therefore summarize how frequent opposite responses to selection are likely to be. This links several evolutionary phenomena within a single framework.

Mixed Model Analysis of Between-Subject Variability in Overnight Corneal Swelling and Deswelling With Silicone Hydrogel Lenses

Purpose

To model between subject variability of corneal swelling (CS) and deswelling after overnight wear of silicone hydrogel (SiHy) contact lenses.

Methods

A total of 29 neophyte subjects wore 12 SiHy lenses with central transmissibility range of 31 to 211 Dk/t units on separate nights, in random order, and on one eye only. The contralateral eye served as the control. Central corneal thickness was measured using digital optical pachymetry before lens insertion, immediately after lens removal on waking, then 20, 40 minutes, 1, 2, and 3 hours later. Mixed modelling was conducted for simultaneous analysis of group and between-subject effects of CS and deswelling.

Results

The best model for overnight CS versus Dk/t was linear with a random intercept showing constant between-subject differences in CS for different Dk/t values. The best fit for corneal deswelling versus time was a curvilinear random intercept and random slope model. About 90% of the total between-subject deswelling variance in either lens or control eyes was due to the intercept variability with much less (∼10%) being due to the variability of the individual deswelling rate (slope). Subject age, sex, and ametropia were not predictors of individual corneal swelling in the swelling versus Dk/t analysis. Age, however, was a significant (inverse) predictor of the rate of corneal deswelling, only in lens-wearing eyes.

Conclusions

A large proportion of variability in corneal swelling is because of subject-specific differences in corneal response to hypoxia. This shows that "low swellers" and "high swellers" actually do exist.

Shearing in flow environment promotes evolution of social behavior in microbial populations

How producers of public goods persist in microbial communities is a major question in evolutionary biology. Cooperation is evolutionarily unstable, since cheating strains can reproduce quicker and take over. Spatial structure has been shown to be a robust mechanism for the evolution of cooperation. Here we study how spatial assortment might emerge from native dynamics and show that fluid flow shear promotes cooperative behavior. Social structures arise naturally from our advection-diffusion-reaction model as self-reproducing Turing patterns. We computationally study the effects of fluid advection on these patterns as a mechanism to enable or enhance social behavior. Our central finding is that flow shear enables and promotes social behavior in microbes by increasing the group fragmentation rate and thereby limiting the spread of cheating strains. Regions of the flow domain with higher shear admit high cooperativity and large population density, whereas low shear regions are devoid of life due to opportunistic mutations.

According to the principle of the ‘survival of the fittest’, selfish individuals should be better off compared to peers that cooperate with each other. Indeed, even though a population of organisms benefits from working together, selfish members can exploit the cooperative behavior of others without doing their part. These ‘cheaters’ then use their advantage to reproduce faster and take over the population.

Yet, social cooperation is widespread in the natural world, and occurs in creatures as diverse as bacteria and whales. How can it arise and persist then? One idea is that when individuals form distinct groups, the ones with cheaters will perish. Even though a selfish individual will fare better than the rest of its team, overall, cooperating groups will survive more and reproduce faster; ultimately, they will be favored by evolution. This is called group selection.

Here, Uppal and Vural examine how the physical properties of the environment can influence the evolution of social interactions between bacteria. To this end, mathematical models are used to simulate how bacteria grow, evolve and drift in a flowing fluid. These are based on equations worked out from the behavior of real-life populations.

The results show that flow patterns in a fluid habitat govern the social behavior of bacteria. When different regions of the fluid are moving at different speeds, ‘shear forces’ are created that cause bacterial colonies to distort and occasionally break apart to form two groups. As such, cooperative groups will rapidly form new cooperating colonies, whereas groups with cheaters will reproduce slower or perish.

Furthermore, results show that when different areas of the fluid have different shear forces, social cooperation will only prevail in certain places. This makes it possible to use flow patterns to fine tune social evolution so that cooperating bacteria will be confined in a certain region. Outside of this area, these bacteria would be taken over by cheaters and go extinct.

Bacteria are both useful and dangerous to humans: for example, certain species can break down pollutants in the water, when others cause deadly infections. These results show it could be possible to control the activity of these microorganisms to our advantage by changing the flow of the fluids in which they live. More broadly, the simulations developed by Uppal and Vural can be applied to a variety of ecosystems where microscopic organisms inhabit fluids, such as plankton flowing in oceanic currents.

Psychopathy to Altruism: Neurobiology of the Selfish-Selfless Spectrum

The age-old philosophical, biological, and social debate over the basic nature of humans as being “universally selfish” or “universally good” continues today highlighting sharply divergent views of natural social order. Here we analyze advances in biology, genetics and neuroscience increasing our understanding of the evolution, features and neurocircuitry of the human brain underlying behavior in the selfish–selfless spectrum. First, we examine evolutionary pressures for selection of altruistic traits in species with protracted periods of dependence on parents and communities for subsistence and acquisition of learned behaviors. Evidence supporting the concept that altruistic potential is a common feature in human populations is developed. To go into greater depth in assessing critical features of the social brain, the two extremes of selfish–selfless behavior, callous unemotional psychopaths and zealous altruists who take extreme measures to help others, are compared on behavioral traits, structural/functional neural features, and the relative contributions of genetic inheritance versus acquired cognitive learning to their mindsets. Evidence from population groups ranging from newborns, adopted children, incarcerated juveniles, twins and mindfulness meditators point to the important role of neuroplasticity and the dopaminergic reward systems in forming and reforming neural circuitry in response to personal experience and cultural influences in determining behavior in the selfish–selfless spectrum. The underlying neural circuitry differs between psychopaths and altruists with emotional processing being profoundly muted in psychopaths and significantly enhanced in altruists. But both groups are characterized by the reward system of the brain shaping behavior. Instead of rigid assignment of human nature as being “universally selfish” or “universally good,” both characterizations are partial truths based on the segments of the selfish–selfless spectrum being examined. In addition, individuals and populations can shift in the behavioral spectrum in response to cognitive therapy and social and cultural experience, and approaches such as mindfulness training for introspection and reward-activating compassion are entering the mainstream of clinical care for managing pain, depression, and stress.

Class Structure, Demography, and Selection: Reproductive-Value Weighting in Nonequilibrium, Polymorphic Populations

In natural populations, individuals of a given genotype may belong to different classes. Such classes can represent different age groups, developmental stages, or habitats. Class structure has important evolutionary consequences because the fitness of individuals with the same genetic background may vary depending on their class. As a result, demographic transitions between classes can cause fluctuations in the trait mean that need to be removed when estimating selection on a trait. Intrinsic differences between classes are classically taken into account by weighting individuals by class-specific reproductive values, defined as the relative contribution of individuals in a given class to the future of the population. These reproductive values are generally constant weights calculated from a constant projection matrix. Here, I show for large populations and clonal reproduction that reproductive values can be defined as time-dependent weights satisfying dynamical demographic equations that depend only on the average between-class transition rates over all genotypes. Using these time-dependent demographic reproductive values yields a simple Price equation where the nonselective effects of between-class transitions are removed from the dynamics of the trait. This generalizes previous theory to a large class of ecological scenarios, taking into account density dependence, ecological feedbacks, arbitrary strength of selection, and arbitrary trait distributions. I discuss the role of reproductive values for prospective and retrospective analyses of the dynamics of phenotypic traits.

Evolutionary epistemology: Reviewing and reviving with new data the research programme for distributed biological intelligence

Numerous studies in microbiology, eukaryotic cell biology, plant biology, biomimetics, synthetic biology, and philosophy of science appear to support the principles of the epistemological theory inspired by evolution, also known as "Evolutionary Epistemology", or EE. However, that none of the studies acknowledged EE suggests that its principles have not been formulated with sufficient clarity and depth to resonate with the interests of the empirical research community. In this paper I review evidence in favor of EE, and also reformulate EE principles to better inform future research. The revamped programme may be tentatively called Research Programme for Distributed Biological Intelligence. Intelligence I define as the capacity of organisms to gain information about their environment, process that information internally, and translate it into phenotypic forms. This multistage progression may be expressed through the acronym IGPT (information-gain-process-translate). The key principles of the programme may be summarized as follows. (i) Intelligence, a universal biological phenomenon promoting individual fitness, is required for effective organism-environment interactions. Given that animals represent less than 0.01% of the planetary biomass, neural intelligence is not the evolutionary norm. (ii) The basic unit of intelligence is a single cell prokaryote. All other forms of intelligence are derived. (iii) Intelligence is hierarchical. It ranges from bacteria to the biosphere or Gaia. (iv) The concept of "information" acquires a new meaning because information processing is at the heart of biological intelligence. All biological systems, from bacteria to Gaia, are intelligent, open thermodynamic systems that exchange information, matter and energy with the environment. (v) The organism-environment interaction is cybernetic. As much as the organism changes due to the influence of the environment, the organism's responses to induced changes affect the environment and subsequent organism-environment interactions. Based on the above principles a new research agenda can be formulated to explore different forms of biological intelligence.

The meaning of intragenomic conflict

Recent years have seen an explosion of interest in genes that function for their own good and to the detriment of other genes that reside in the same genome. Such intragenomic conflicts are increasingly recognized to underpin maladaptation and disease. However, progress has been impeded by a lack of clear understanding regarding what intragenomic conflict actually means, and an associated obscurity concerning its fundamental drivers. Here we develop a general theory of intragenomic conflict in which genes are viewed as inclusive-fitness-maximizing agents that come into conflict when their inclusive-fitness interests disagree. This yields a classification of all intragenomic conflicts into three categories according to whether genes disagree about where they have come from, where they are going, or where they currently are. We illustrate each of these three basic categories, survey and classify all known forms of intragenomic conflict, and discuss the implications for organismal maladaptation and human disease.

The purpose of adaptation

A central feature of Darwin's theory of natural selection is that it explains the purpose of biological adaptation. Here, I: emphasize the scientific importance of understanding what adaptations are for, in terms of facilitating the derivation of empirically testable predictions; discuss the population genetical basis for Darwin's theory of the purpose of adaptation, with reference to Fisher's ‘fundamental theorem of natural selection'; and show that a deeper understanding of the purpose of adaptation is achieved in the context of social evolution, with reference to inclusive fitness and superorganisms.

Why an extended evolutionary synthesis is necessary

Since the last major theoretical integration in evolutionary biology—the modern synthesis (MS) of the 1940s—the biosciences have made significant advances. The rise of molecular biology and evolutionary developmental biology, the recognition of ecological development, niche construction and multiple inheritance systems, the ‘-omics’ revolution and the science of systems biology, among other developments, have provided a wealth of new knowledge about the factors responsible for evolutionary change. Some of these results are in agreement with the standard theory and others reveal different properties of the evolutionary process. A renewed and extended theoretical synthesis, advocated by several authors in this issue, aims to unite pertinent concepts that emerge from the novel fields with elements of the standard theory. The resulting theoretical framework differs from the latter in its core logic and predictive capacities. Whereas the MS theory and its various amendments concentrate on genetic and adaptive variation in populations, the extended framework emphasizes the role of constructive processes, ecological interactions and systems dynamics in the evolution of organismal complexity as well as its social and cultural conditions. Single-level and unilinear causation is replaced by multilevel and reciprocal causation. Among other consequences, the extended framework overcomes many of the limitations of traditional gene-centric explanation and entails a revised understanding of the role of natural selection in the evolutionary process. All these features stimulate research into new areas of evolutionary biology.

Multilevel and sex-specific selection on competitive traits in North American red squirrels

Individuals often interact more closely with some members of the population (e.g., offspring, siblings, or group members) than they do with other individuals. This structuring of interactions can lead to multilevel natural selection, where traits expressed at the group-level influence fitness alongside individual-level traits. Such multilevel selection can alter evolutionary trajectories, yet is rarely quantified in the wild, especially for species that do not interact in clearly demarcated groups. We quantified multilevel natural selection on two traits, postnatal growth rate and birth date, in a population of North American red squirrels (Tamiasciurus hudsonicus). The strongest level of selection was typically within-acoustic social neighborhoods (within 130 m of the nest), where growing faster and being born earlier than nearby litters was key, while selection on growth rate was also apparent both within-litters and within-study areas. Higher population densities increased the strength of selection for earlier breeding, but did not influence selection on growth rates. Females experienced especially strong selection on growth rate at the within-litter level, possibly linked to the biased bequeathal of the maternal territory to daughters. Our results demonstrate the importance of considering multilevel and sex-specific selection in wild species, including those that are territorial and sexually monomorphic.

Superorganismality and caste differentiation as points of no return: how the major evolutionary transitions were lost in translation

More than a century ago, William Morton Wheeler proposed that social insect colonies can be regarded as superorganisms when they have morphologically differentiated reproductive and nursing castes that are analogous to the metazoan germ-line and soma. Following the rise of sociobiology in the 1970s, Wheeler's insights were largely neglected, and we were left with multiple new superorganism concepts that are mutually inconsistent and uninformative on how superorganismality originated. These difficulties can be traced to the broadened sociobiological concept of eusociality, which denies that physical queen-worker caste differentiation is a universal hallmark of superorganismal colonies. Unlike early evolutionary naturalists and geneticists such as Weismann, Huxley, Fisher and Haldane, who set out to explain the acquisition of an unmated worker caste, the goal of sociobiology was to understand the evolution of eusociality, a broad-brush convenience category that covers most forms of cooperative breeding. By lumping a diverse spectrum of social systems into a single category, and drawing attention away from the evolution of distinct quantifiable traits, the sociobiological tradition has impeded straightforward connections between inclusive fitness theory and the major evolutionary transitions paradigm for understanding irreversible shifts to higher organizational complexity. We evaluate the history by which these inconsistencies accumulated, develop a common-cause approach for understanding the origins of all major transitions in eukaryote hierarchical complexity, and use Hamilton's rule to argue that they are directly comparable. We show that only Wheeler's original definition of superorganismality can be unambiguously linked to irreversible evolutionary transitions from context-dependent reproductive altruism to unconditional differentiation of permanently unmated castes in the ants, corbiculate bees, vespine wasps and higher termites. We argue that strictly monogamous parents were a necessary, albeit not sufficient condition for all transitions to superorganismality, analogous to single-zygote bottlenecking being a necessary but not sufficient condition for the convergent origins of complex soma across multicellular eukaryotes. We infer that conflict reduction was not a necessary condition for the origin of any of these major transitions, and conclude that controversies over the status of inclusive fitness theory primarily emanate from the arbitrarily defined sociobiological concepts of superorganismality and eusociality, not from the theory itself.

Contextual organismality: Beyond pattern to process in the emergence of organisms

Biologists have taken the concept of organism largely for granted. However, advances in the study of chimerism, symbiosis, bacterial‐eukaryote associations, and microbial behavior have prompted a redefinition of organisms as biological entities exhibiting low conflict and high cooperation among their parts. This expanded view identifies organisms in evolutionary time. However, the ecological processes, mechanisms, and traits that drive the formation of organisms remain poorly understood. Recognizing that organismality can be context dependent, we advocate elucidating the ecological contexts under which entities do or do not act as organisms. Here we develop a “contextual organismality” framework and provide examples of entities, such as honey bee colonies, tumors, and bacterial swarms, that can act as organisms under specific life history, resource, or other ecological circumstances. We suggest that context dependence may be a stepping stone to the development of increased organismal unification, as the most integrated biological entities generally show little context dependence. Recognizing that organismality is contextual can identify common patterns and testable hypotheses across different entities. The contextual organismality framework can illuminate timeless as well as pressing issues in biology, including topics as disparate as cancer emergence, genomic conflict, evolution of symbiosis, and the role of the microbiota in impacting host phenotype.

Multilevel Selection in Kin Selection Language

Few issues have raised more debate among evolutionary biologists than kin selection (KS) versus multilevel selection (MLS). They are formally equivalent, but use different-looking mathematical approaches, and are not causally equivalent: for a given problem KS can be a more suitable causal explanation than MLS, and vice versa. Methods for analyzing a given model from both viewpoints would therefore be valuable. I argue that there is often an easy way to achieve this: MLS can be written using the components of KS. This applies to the very general regression approach as well as to the practical evolutionarily stable strategy (ESS) maximization approach, and can hence be used to analyze many common ESS models from a multilevel perspective. I demonstrate this with example models of gamete competition and limitation.

Ecology and multilevel selection explain aggression in spider colonies

Progress in sociobiology continues to be hindered by abstract debates over methodology and the relative importance of within‐group vs. between‐group selection. We need concrete biological examples to ground discussions in empirical data. Recent work argued that the levels of aggression in social spider colonies are explained by group‐level adaptation. Here, we examine this conclusion using models that incorporate ecological detail while remaining consistent with kin‐ and multilevel selection frameworks. We show that although levels of aggression are driven, in part, by between‐group selection, incorporating universal within‐group competition provides a striking fit to the data that is inconsistent with pure group‐level adaptation. Instead, our analyses suggest that aggression is favoured primarily as a selfish strategy to compete for resources, despite causing lower group foraging efficiency or higher risk of group extinction. We argue that sociobiology will benefit from a pluralistic approach and stronger links between ecologically informed models and data.

Generalizing Contextual Analysis

Okasha, in Evolution and the Levels of Selection, convincingly argues that two rival statistical decompositions of covariance, namely contextual analysis and the neighbour approach, are better causal decompositions than the hierarchical Price approach. However, he claims that this result cannot be generalized in the special case of soft selection and argues that the Price approach represents in this case a better option. He provides several arguments to substantiate this claim. In this paper, I demonstrate that these arguments are flawed and argue that neither the Price equation nor the contextual and neighbour partitionings sensu Okasha are adequate causal decompositions in cases of soft selection. The Price partitioning is generally unable to detect cross-level by-products and this naturally also applies to soft selection. Both contextual and neighbour partitionings violate the fundamental principle of determinism that the same cause always produces the same effect. I argue that a fourth partitioning widely used in the contemporary social sciences, under the generic term of 'hierarchical linear model' and related to contextual analysis understood broadly, addresses the shortcomings of the three other partitionings and thus represents a better causal decomposition. I then defend this model against the argument that because it predicts that there is some organismal selection in some specific cases of segregation distortion then it should be rejected. I show that cases of segregation distortion that intuitively seem to contradict the conclusion drawn from the hierarchical linear model are in fact cases of multilevel selection 2 while the assessment of the different partitionings are restricted to multilevel selection 1.

Kin and multilevel selection in social evolution: a never-ending controversy?

Kin selection and multilevel selection are two major frameworks in evolutionary biology that aim at explaining the evolution of social behaviors. However, the relationship between these two theories has been plagued by controversy for almost half a century and debates about their relevance and usefulness in explaining social evolution seem to rekindle at regular intervals. Here, we first provide a concise introduction into the kin selection and multilevel selection theories and shed light onto the roots of the controversy surrounding them. We then review two major aspects of the current debate: the presumed formal equivalency of the two theories and the question whether group selection can lead to group adaptation. We conclude by arguing that the two theories can offer complementary approaches to the study of social evolution: kin selection approaches usually focus on the identification of optimal phenotypes and thus on the endresult of a selection process, whereas multilevel selection approaches focus on the ongoing selection process itself. The two theories thus provide different perspectives that might be fruitfully combined to promote our understanding of the evolution in group-structured populations.

The influence of space and time on the evolution of altruistic defence: the case of ant slave rebellion

How can antiparasite defence traits evolve even if they do not directly benefit their carriers? An example of such an indirect defence is rebellion of enslaved Temnothorax longispinosus ant workers against their social parasite Temnothorax americanus, a slavemaking ant. Ant slaves have been observed to kill their oppressors' offspring, a behaviour from which the sterile slaves cannot profit directly. Parasite brood killing could, however, reduce raiding pressure on related host colonies nearby. We analyse with extensive computer simulations for the Temnothorax slavemaker system under what conditions a hypothetical rebel allele could invade a host population, and in particular, how host-parasite dynamics and population structure influence the rebel allele's success. Exploring a wide range of model parameters, we only found a small number of parameter combinations for which kin selection or multilevel selection could allow a slave rebellion allele to spread in the host population. Furthermore, we did not detect any cases in which the reduction of raiding pressure in the close vicinity of the slavemaker nest would substantially contribute to the inclusive fitness of rebels. This suggests that slave rebellion is not costly and perhaps a side-effect of some other beneficial trait. In some of our simulations, however, even a costly rebellion allele could spread in the population. This was possible when host-parasite interactions led to a metapopulation dynamic with frequent local extinctions and recolonizations of demes by the offspring of few immigrants.

The Achilles' heel hypothesis: misinformed keystone individuals impair collective learning and reduce group success

Many animal societies rely on highly influential keystone individuals for proper functioning. When information quality is important for group success, such keystone individuals have the potential to diminish group performance if they possess inaccurate information. Here, we test whether information quality (accurate or inaccurate) influences collective outcomes when keystone individuals are the first to acquire it. We trained keystone or generic individuals to attack or avoid novel stimuli and implanted these trained individuals within groups of naive colony-mates. We subsequently tracked how quickly groups learned about their environment in situations that matched (accurate information) or mismatched (inaccurate information) the training of the trained individual. We found that colonies with just one accurately informed individual were quicker to learn to attack a novel prey stimulus than colonies with no informed individuals. However, this effect was no more pronounced when the informed individual was a keystone individual. In contrast, keystones with inaccurate information had larger effects than generic individuals with identical information: groups containing keystones with inaccurate information took longer to learn to attack/avoid prey/predator stimuli and gained less weight than groups harbouring generic individuals with identical information. Our results convey that misinformed keystone individuals can become points of vulnerability for their societies.

More on the genetical theory of multilevel selection

In my article The genetical theory of multilevel selection, I provided a synthesis of the theory of multilevel selection (MLS) and the theory of natural selection in class-structured populations. I framed this synthesis within Fisher's genetical paradigm, taking a strictly genetical approach to traits and fitness. I showed that this resolves a number of long-standing conceptual problems that have plagued the MLS literature, including the issues of 'aggregate' vs. 'emergent' group traits, 'collective fitness1 ' vs. 'collective fitness2 ' and 'MLS1' vs. 'MLS2 '. In his commentary, Goodnight suggests this theoretical and conceptual synthesis is flawed in several respects. Here, I show this is incorrect, by: reiterating the theoretical and conceptual goals of my synthesis; clarifying that my genetical approach to traits is necessary for a proper analysis of the action of MLS independently of non-Darwinian factors; emphasizing that the Price-Hamilton approach to MLS provides a consistent, useful and conceptually superior theoretical framework; and explaining the role of reproductive value in the study of natural selection in class-structured populations. I also show that Goodnight's contextual analysis treatment of MLS in a class-structured population is mathematically, biologically and conceptually inadequate.

Multilevel selection theory and evidence: a critique of Gardner, 2015

Gardner (2015) recently developed a model of a 'Genetical Theory of Multilevel Selection, which is a thoughtfully developed, but flawed model. The model's flaws appear to be symptomatic of common misunderstandings of the multi level selection (MLS) literature and the recent quantitative genetic literature. I use Gardner's model as a guide for highlighting how the MLS literature can address the misconceptions found in his model, and the kin selection literature in general. I discuss research on the efficacy of group selection, the roll of indirect genetic effects in affecting the response to selection and the heritability of group-level traits. I also discuss why the Price multilevel partition should not be used to partition MLS, and why contextual analysis and, by association, direct fitness are appropriate for partitioning MLS. Finally, I discuss conceptual issues around questions concerning the level at which fitness is measured, the units of selection, and I present a brief outline of a model of selection in class-structured populations. I argue that the results derived from the MLS research tradition can inform kin selection research and models, and provide insights that will allow researchers to avoid conceptual flaws such as those seen in the Gardner model.