Is there any way to reconcile the adaptationist’s image of natural selection as an engine of optimality with the more complex image of its dynamics we get from population genetics? This has long been an important strand in the controversy surrounding adaptationism, yet debate has been hampered by a tendency to conflate various different ways of thinking about maximization. Here I distinguish four varieties of maximization principle. I then discuss the logical relations between these varieties, arguing that, although they may (...) seem similar at face value, none entails any of the others. I then turn briefly to the status of each variety, arguing that, while each type of maximization principle faces serious problems, the problems are subtly different for each type. In the last section, I reflect on what is at stake in the debate. (shrink)

The notion that natural selection is a process of fitness maximization gets a bad press in population genetics, yet in other areas of biology the view that organisms behave as if attempting to maximize their fitness remains widespread. Here I critically appraise the prospects for reconciliation. I first distinguish four varieties of fitness maximization. I then examine two recent developments that may appear to vindicate at least one of these varieties. The first is the ‘new’ interpretation of Fisher's fundamental theorem (...) of natural selection, on which the theorem is exactly true for any evolving population that satisfies some minimal assumptions. The second is the Formal Darwinism project, which forges links between gene frequency change and optimal strategy choice. In both cases, I argue that the results fail to establish a biologically significant maximization principle. I conclude that it may be a mistake to look for universal maximization principles justified by theory alone. A more promising approach may be to find maximization principles that apply conditionally and to show that the conditions were satisfied in the evolution of particular traits. (shrink)

Scientists use models to understand the natural world, and it is important not to conflate model and nature. As an illustration, we distinguish three different kinds of populations in studies of ecology and evolution: theoretical, laboratory, and natural populations, exemplified by the work of R.A. Fisher, Thomas Park, and David Lack, respectively. Biologists are rightly concerned with all three types of populations. We examine the interplay between these different kinds of populations, and their pertinent models, in three examples: the notion (...) of “effective” population size, the work of Thomas Park on /Tribolium/ populations, and model-based clustering algorithms such as /Structure/. Finally, we discuss ways to move safely between three distinct population types while avoiding confusing models and reality. (shrink)

Individual-as-maximizing agent analogies result in a simple understanding of the functioning of the biological world. Identifying the conditions under which individuals can be regarded as fitness maximizing agents is thus of considerable interest to biologists. Here, we compare different concepts of fitness maximization, and discuss within a single framework the relationship between Hamilton’s (J Theor Biol 7:1–16, 1964) model of social interactions, Grafen’s (J Evol Biol 20:1243–1254, 2007a) formal Darwinism project, and the idea of evolutionary stable strategies. We distinguish cases (...) where phenotypic effects are additive separable or not, the latter not being covered by Grafen’s analysis. In both cases it is possible to define a maximand, in the form of an objective function ϕ(z), whose argument is the phenotype of an individual and whose derivative is proportional to Hamilton’s inclusive fitness effect. However, this maximand can be identified with the expression for fecundity or fitness only in the case of additive separable phenotypic effects, making individual-as-maximizing agent analogies unattractive (although formally correct) under general situations of social interactions. We also feel that there is an inconsistency in Grafen’s characterization of the solution of his maximization program by use of inclusive fitness arguments. His results are in conflict with those on evolutionary stable strategies obtained by applying inclusive fitness theory, and can be repaired only by changing the definition of the problem. (shrink)

Selectionist evolutionary theory has often been faulted for not making novel predictions that are surprising, risky, and correct. I argue that it in fact exhibits the theoretical virtue of predictive capacity in addition to two other virtues: explanatory unification and model fitting. Two case studies show the predictive capacity of selectionist evolutionary theory: parallel evolutionary change in E. coli, and the origin of eukaryotic cells through endosymbiosis.

Hamilton’s Rule, named after the evolutionary biologist Bill Hamilton, and the related concepts of inclusive fitness and kin selection, have been the bedrock of the study of social evolution for the past half century. In ’The Philosophy of Social Evolution’, Jonathan Birch provides a comprehensive introduction to the conceptual foundations of the Hamiltonian view of social evolution, and a passionate defence of its enduring value in face of the recent high profile criticism. In this review essay, I first outline the (...) version of Hamilton’s Rule defended by Birch, dubbed Hamilton’s Rule General, and its derivation. With this in place, I then navigate through the fierce disagreements that Hamilton’s Rule generates among social evolution researchers and evaluate Birch’s central argument of the book that HRG serves as an organizing framework for social evolution research under which we can compare and interpret more detailed causal models. I then spend the remainder of the review discussing what I take to be three of the most exciting implications of Hamilton’s thinking raised by Birch: the extension of Hamilton’s Rule to mobile genetic elements, maximization of inclusive fitness models and the idea of adaptation as organism design, and the relationship between Hamilton’s approaches to social behaviour and the gene’s-eye view of evolution. (shrink)

This paper is a commentary on the focal article by Grafen and on earlier papers of his on which many of the results of this focal paper depend. Thus it is in effect a commentary on the “formal Darwinian project”, the focus of this sequence of papers. Several problems with this sequence are raised and discussed. The first of these concerns fitness maximization. It is often claimed in these papers that natural selection leads to a maximization of fitness and that (...) this view is claimed in Fisher’s “fundamental theorem of natural selection”. These claims are refuted, and various incorrect statements about the meaning and interpretation of the fundamental theorem of natural selection, in this sequence and in other papers by other authors, are discussed. Next, much of the work in this sequence rests on the first Price equation. In the deterministic (infinite population) case this equation is no more than the standard classical equation relating to changes in gene frequencies. In the stochastic case the equation gives the change in gene frequencies as the sum of two terms (the second of which vanishes in the deterministic case). These two terms are of essentially equal importance in the situation considered in the focal article, yet one of Grafen’s results ignores the second term in the stochastic analysis. This is associated with a wavering between deterministic and stochastic analyses and the use of the Price fitness concept and the classical fitness concept. These comments cast doubts on Grafen’s optimization theory. (shrink)

Abstract Gene-selectionists define fundamental terms in non-standard ways. Genes are determinants of difference. Phenotypes are defined as a gene’s effects relative to some alternative whereas the environment is defined as all parts of the world that are shared by the alternatives being compared. Environments choose among phenotypes and thereby choose among genes. By this process, successful gene sequences become stores of information about what works in the environment. The strategic gene is defined as a set of gene tokens that combines (...) ‘actor’ tokens responsible for an effect with ‘recipient’ tokens whose replication is thereby enhanced. This set of tokens can extend across the boundaries of individual organisms, or other levels of selection, as these are traditionally defined. Content Type Journal Article Pages 1-19 DOI 10.1007/s10539-012-9315-5 Authors David Haig, Department of Organismic and Evolutionary Biology, Harvard University, 26 Oxford Street, Cambridge, MA 02138, USA Journal Biology and Philosophy Online ISSN 1572-8404 Print ISSN 0169-3867. (shrink)

Wright’s “adaptive landscape” has been influential in evolutionary thinking but controversial, especially because the landscape that organisms encounter is altered by the evolutionary process itsel...