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An Introduction to Sociobiology: Inclusive Fitness and the Core Genome Herbert Gintis

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An Introduction to Sociobiology: Inclusive Fitness and the Core Genome Herbert Gintis An Introduction to Sociobiology: Inclusive Fitness and the Core Genome Herbert Gintis June 29, 2013 The besetting danger is ...mistaking part of the truth for the whole...in every one of the leading controversies...both sides were in the right in what they affirmed, though wrong in what they denied John Stuart Mill, On Coleridge, 1867 A Mendelian populationhas a common gene pool, whichis itscollective or corporate genotype. Theodosius Dobzhansky, Cold Springs Harbor Symposium, 1953. The interaction between regulator and structural genes... [reinforces] the concept that the genotype of the individual is a whole. Ernst Mayr, Populations, Species and Evolution, 1970 Abstract This paper develops inclusive fitness theory with the aim of clarifying its appropriate place in sociobiological theory and specifying the associated principles that render it powerful. The paper introduces one new concept, that of the core genome. Treating the core genome as a unit of selection solves problems concerning levels of selection in evolution. 1 Summary Sociobiology is the study of biological interaction, both intragenomic, among loci in the genome, and intergenomic, among individuals in a reproductive popula- tion (Gardner et al. 2007). William Hamilton (1964) extended the theory of gene frequencies developed in the first half of the Twentieth century (Crow and I would like to thank Samuel Bowles, Eric Charnov, Steven Frank, Michael Ghiselin, Peter Godfrey-Smith, David Haig, David Queller, Laurent Lehmann, Samir Okasha, Peter Richerson, Joan Roughgarden, Elliot Sober, David Van Dyken, Mattijs van Veelen and Edward O. Wilson for advice in preparing this paper. 1 Kimura 1970, B¨urger 2000, Provine 2001) to deal with such behavior. Hamil- ton’s rule has a simplicity that belies its considerable analytical power. But it is virtually powerless unless supplemented by other principles that are far less well understood. My purpose here is to delineate the proper place of Hamilton’s rule in sociobiological theory, and articulate these additional principles. I have kept the mathematical arguments self-contained and rather transparent, relegating equation-heavy arguments to Section 4 and Appendices A and B, all of which may be skipped without loss of continuity. There is only one new concept offered in this paper, that of the core genome. Treating the core genome as a replicator reconceptualizes the role of groups in evolution, and resolves chronic divisive issues concerning levels of selection. Using Hamilton’s rule, Alan Grafen has shown that under extremely general conditions, genes can be modeled as maximizers of inclusive fitness (Grafen 2000, 2006ab), which supports the concept of the selfish gene developed by George Williams (1966) and Richard Dawkins (1976). The simplicity of inclusivefitness theory is purchased at a price: it applies only to the behavior of alleles at a single locus, without the slightest influence from or upon, alleles at otherloci of thegenome. In essence, inclusive fitness theory models a direct relationship between a single genetic locus and the behavior of individual who carry the genome of which this locus is a tiny part. Because the various loci in the genome are highly interdependent, and social behavior generally involves the interaction of gene networks comprising many loci, inclusive fitness theory is not a full theory of gene frequency dynamics. Inclusive fitness theory would be dramatically strengthened if individualfitness were a weighted average of allele frequencies in the genome, for then maximiza- tion of inclusive fitness at the level of the single locus would extend directly to individual fitness maximization (Frank 1997, Grafen 2006a). However, it is well known that reproductive populations do not maximize fitness (Moran 1964, Akin 1982, 1987), and if individualfitness were a weightedaverage of allele frequencies, then Price’s equation could be used to show that populations do maximize fitness (Appendix B). Thus individual fitness cannot generally be treated as a weighted average of allele frequencies. It follows that the notion that inclusive fitness theory implies that individuals maximize inclusive fitness is incorrect. Inclusive fitness theory can be extended to complex social processes governed by networksof genes by employingthe so-called phenotypic gambit (Grafen 1984). The phenotypic gambit assumes that the behavior under study is governed by a single locus in the genome. With this assumption, Hamilton’s rule directly implies that behavior is the product of inclusive fitness maximization. More generally, total organismal fitness might be partitioned into several parts, each governed by distinct genetic networks,so that the phenotypicgambit could be applied separately in each 2 part, each covering a single behavioral complex, such as beak and wing shape, mating rituals, patterns of brood care, foraging strategies, predator avoidance, and territorial signaling. While the phenotypic gambit is extremely useful, it is, in our present state of knowledge, merely a heuristic device for generating plausible hypotheses. This ex- plains why the notion that individualsmaximize inclusive fitness is false in general but often offers powerful insight into social behavior. Yet it fails, for instance, in species that exhibit a social division of labor in which tasks are distributed across multiple participants (castes) with different inclusive fitness maximands.1 Without the phenotypic gambit, inclusive fitness theory has not the slightest power to account for the fact that complex metazoan species appear to be the prod- uct of design (Dawkins 1996); i.e., that the various loci in a successful organism generally cooperate harmoniously in enhancing the fitness of their carriers. Indeed the assumption of additivity across loci (frequency independence) that permits in- clusive fitness theory to extend beyond a single locus is precisely equivalent to the assumption that genes at distinct loci neither cooperate nor conflict. As we show below, the inclusive fitness conditions for success at a locus are distinct from the conditions for the success of its carriers and because genes are utterly selfish, each maximizes its inclusive fitness without regard for the fitness of its carriers. Although at times this leads to the fixation of deleterious mutations (Burt and Trivers 2006) and dysfunctional social norms (Edgerton 1992), for the most part such antisocial alleles are suppressed through the actions of regulatory networks of genes at other loci—phenomena that cannot be modeled within inclu- sive fitness theory (Burt and Trivers 2006, Ratnieks et al. 2006). If we add a Harmony Principle that asserts that organisms are evolutionarily successful to the extent that they suppress antisocial alleles, inclusive fitness theory becomes very strong. Much of the intuitive appeal of inclusive fitness theory lies in the tacit acceptance of the Harmony Principle. However, the mechanisms un- derlying the Harmony Principle are still largely unknown, and are likely be under- stood through bioengineering and social theory in addition to population biology (Maynard Smith and Szathm´ary 1997, Crespi 2001, Strassmann and Queller 2004, Queller and Strassmann 2009, Bowles and Gintis 2011, Wilson 2012). Recognizing that the genome as a whole is responsible for ensuring the co- operative interaction of genes in the genome as well as individuals in a social group leads us to reassess the role of the genome as a unit of selection. Richard 1The general equilibrium model of economic theory (Arrow and Hahn 1971) shows that indi- vidual utility maximization of all economic actors can be achieved when all actors face a common set of equilibrium prices, and with minimal assumptions, these common prices are dynamically sta- ble (Gintis and Mandel 2012). There is no known equivalent of a price system in other biological systems. 3 Dawkins’ (1976) replicator/vehicle distinction suggests that individuals, and a for- tiori groups, have no evolutionary permanence, but are merely carriers for the re- productive population’s genetic material. Individuals cannot adapt genetically be- cause they are destroyed by death and groups are destroyed by dissolution. Genetic material, however, can be faithfully reproduced across generations. Hence genetic material is subject to the evolutionary forces of reproduction, mutation, and se- lection (Lewontin 1974). Dawkins argues that the gene is the only replicator in diploid organisms, because larger units, such as chromosomes, are “torn apart” in each generation through meiosis and crossover. We suggest in Section 8, however, that a large fraction of the genome, which we call the core genome, has precisely such an identity across generations. The core genome is thus a replicator. The core genome codes for biochemical interactions among loci, as well as the characteristic environment of a social species and the characteristic social relations and signaling patterns among its individual members. For instance, in a territorial species, the behaviors signaling territorial boundaries and those underlying respect for such boundaries are coded in the species’ core genome (Gintis 2007). The is- sue of individual vs. group selection vanishesaccording to this conception, because both individuals and groups are phenotypic effects of the core genome. When the core genome codes for a subdivided population, and the result is evolutionarily successful, we can speak of group selection, with the understanding that selection is for a pattern of population subdivision, not
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