‘Statisticalists’ argue that the individual interactions of organisms taken together constitute natural selection. On this view, natural selection is an aggregated effect of interactions rather than some added cause acting on populations. The statisticalists’ view entails that natural selection and drift are indistinguishable aggregated effects of interactions, so that it becomes impossible to make a difference between them. The present paper attempts to make sense of the difference between selection and drift, given the main insights of statisticalism; basically, (...) it will disentangle the various kinds of indistinguishability between selection and drift that happen within biology, by examining the epistemological and metaphysical nature of the distinction between selection and drift. It will be based on a ‘difference-making account’ of selection. The first section will explicate the inscrutability of selection and drift, its various types in the statisticalist writings, and its implications. The second section specifies concepts of natural selection and drift in the difference making account of selection I am using, and shows that one can derive from this the statistical signatures of selection and drift. On this basis I focus on one sort of indistinguishability issue about selection and drift, which I call epistemic opacity, and explain why it mostly affects small populations. The last section explains why epistemic opacity does not raise an genuine epistemic problem for evolutionary biology. (shrink)

Genetic drift (variously called “random drift”, “random genetic drift”, or sometimes just “drift”) has been a source of ongoing controversy within the philosophy of biology and evolutionary biology communities, to the extent that even the question of what drift is has become controversial. There seems to be agreement that drift is a chance (or probabilistic or statistical) element within population genetics and within evolutionary biology more generally, and that the term (...) “random” isn’t invoking indeterminism or any technical mathematical meaning, but that’s about where agreement ends. Yet genetic drift models are a staple topic in population genetics textbooks and research, with genetic drift described as one of the main factors of evolution alongside selection, mutation, and migration. Some claim that genetic drift has played a major role in evolution (particularly molecular evolution), while others claim it to be minor. This article examines these and other controversies. -/- In order to break through the logjam of competing definitions of drift, this entry begins with a brief history of the concept, before examining various philosophical claims about the proper characterization of drift and whether it can be distinguished from natural selection; the relation of drift to debates over statisticalism; whether drift can be detected empirically and if so, how; and the proper understanding of drift as a model and as a (purported) law. (shrink)

Contingency-theorists have gestured to a series of phenomena such as random mutations or rare Armageddon-like events as that which accounts for evolutionary contingency. These phenomena constitute a class, which may be aptly called the ‘sources of contingency’. In this paper, I offer a probabilistic conception of what it is to be a source of contingency and then examine two major candidates: chance variation and genetic drift, both of which have historically been taken to be ‘chancy’ in a (...) number of different senses. However,contrathe gesturing of contingency-theorists, chance variation and genetic drift are not always strong sources of contingency, as they can be non-chancy in at least one sense that opposes evolutionary contingency. The probabilistic conception offered herein allows for sources of contingency to appropriately vary in strength. To this end, I import Shannon’sinformation entropyas a statistical measure for systematically assessing the strength of a source of contingency, which is part and parcel of identifying sources of contingency. In brief, the higher the entropy, the greater the strength. This is also empirically significant because molecular, mutational, and replicative studies often contain sufficient frequency or probability data to allow for entropies to be calculated. In this way, contingency-theorists can evaluate the strength of a source of contingency in real-world cases. Moreover, the probabilistic conception also makes conceptual room for the converse of sources of contingency: ‘sources of directionality’, which ought to be recognised, as they can interact with genuine sources of contingency in undermining evolutionary contingency. (shrink)

The current mainstream in cancer research favours the idea that malignant tumour initiation is the result of a genetic mutation. Tumour development and progression is then explained as a sort of micro-evolutionary process, whereby an initial genetic alteration leads to abnormal proliferation of a single cell that leads to a population of clonally derived cells. It is widely claimed that tumour progression is driven by natural selection, based on the assumption that the initial tumour cells acquire some properties (...) that endow such cells with a selective advantage over the normal cells from which the tumour cells are derived. The standard view assumes that the transformed bodily cell somehow acquires "responsiveness" to natural selection independently of the whole organism to which the cell belongs. Yet, it is never explained where such an acquired capacity to respond to natural selection by the individual bodily cell comes from. This situation poses many difficult questions that so far have been left unanswered. For example, there is no explanation why some cells belonging to an organised whole and as such having no independent capacity for survival, apparently become 'independent' entities, able to respond to selective pressures in an autonomous fashion and then to be evaluated by natural selection. Hereunder it is argued that such a qualitative change cannot be the consequence of specific genetic mutations. Moreover, it is shown that natural selection is unlikely to be acting within the organism during tumour development and progression and that tumour evolution is a random, non-adaptive process, driven by no fundamental biological principle. Thus, mutations in the so-called oncogenes and tumour suppressor genes observed in epithelial cancers (that constitute more than 90% of all cancers) are not the result of selection for better cellular growth or survival under restrictive conditions. Instead, here it is suggested that they are the consequence of genetic drift acting upon gene functions that become non-relevant, either for the individual or the species fitness, once the organism is past its reproductive prime and as such, they also become superfluous for cell survival in the short term. It is proposed that the origin of cancer is epigenetic and it is a consequence of the need for a continued turnover of the individuals that constitute a species. (shrink)

One controversy about the existence of so called evolutionary forces such as natural selection and random genetic drift concerns the sense in which such “forces” can be said to interact. In this paper I explain how natural selection and random drift can interact. In particular, I show how population-level probabilities can be derived from individual-level probabilities, and explain the sense in which natural selection and drift are embodied in these population-level probabilities. I argue that (...) whatever causal character the individual-level probabilities have is then shared by the population-level probabilities, and that natural selection and random drift then have that same causal character. Moreover, natural selection and drift can then be viewed as two aspects of probability distributions over frequencies in populations of organisms. My characterization of population-level probabilities is largely neutral about what interpretation of probability is required, allowing my approach to support various positions on biological probabilities, including those which give biological probabilities one or another sort of causal character. ‡This paper has benefited from feedback on and discussions of this and earlier work. I want to thank André Ariew, Matt Barker, Lindley Darden, Patrick Forber, Nancy Hall, Mohan Matthen, Samir Okasha, Jeremy Pober, Robert Richardson, Alex Rosenberg, Eric Seidel, Denis Walsh, and Bill Wimsatt. †To contact the author, please write to: Department of Philosophy, University of Alabama at Birmingham, HB 414A, 900 13th Street South, Birmingham, AL 35294-1260; e-mail: [email protected]. (shrink)

Recently, several philosophers have challenged the view that evolutionary theory is usefully understood by way of an analogy with Newtonian mechanics. Instead, they argue that evolutionary theory is merely a statistical theory. According to this alternate approach, natural selection and random genetic drift are not even causes, much less forces. I argue that, properly understood, the Newtonian analogy is unproblematic and illuminating. I defend the view that selection and drift are causes in part by attending to (...) a pair of important distinctions—that between process and product and that between natural selection and fitness. (shrink)

Biologists and philosophers have been extremely pessimistic about the possibility of demonstrating random drift in nature, particularly when it comes to distinguishing random drift from natural selection. However, examination of a historical case-Maxime Lamotte's study of natural populations of the land snail, Cepaea nemoralis in the 1950s - shows that while some pessimism is warranted, it has been overstated. Indeed, by describing a unique signature for drift and showing that this signature obtained in the populations (...) under study, Lamotte was able to make a good case for a significant role for drift. It may be difficult to disentangle the causes of drift and selection acting in a population, but it is not impossible. (shrink)

There are several different ways in which chance affects evolutionary change. That all of these processes are called “random genetic drift” is in part a due to common elements across these different processes, but is also a product of historical borrowing of models and language across different levels of organization in the biological hierarchy. A history of the concept of drift will reveal the variety of contexts in which drift has played an explanatory role in (...) biology, and will shed light on some of the philosophical controversy surrounding whether drift is a cause of evolutionary change. (shrink)

Philosophers of biology have recently been debating about whether random genetic drift is a distinct process from that of natural selection. One camp argues that drift is a process of “indiscriminate sampling” that is logically and ontologically distinct from the “discriminate sampling” process that is natural selection. The other camp argues that, rather than being two autonomous processes, natural selection and drift are just two aspects or facets of a single process. I argue that the (...) two positions involved in this dispute are not mutually exclusive. Indeed, by explicitly taking into account its sources, I argue that two kinds of drift are theoretically possible. The first kind – that I call circumstantial-drift – involves a process of its own, separate from the process of natural selection, or, more specifically, it requires that differences in a circumstantial trait cause differences in reproductive output of biological entities. The second kind – that I label probabilistic-drift – requires no other process than a probabilistic causal relation between a heritable physical trait and reproductive output, i.e. requires only the causal relation on which the work of natural selection could also depend. If both of these kinds of drift are theoretically possible, then neither defining, nor empirically identifying drift need to be zero-sum games. (shrink)

A hitherto neglected form of explanation is explored, especially its role in population genetics. “Statistically abstractive explanation” (SA explanation) mandates the suppression of factors probabilistically relevant to an explanandum when these factors are extraneous to the theoretical project being pursued. When these factors are suppressed, the explanandum is rendered uncertain. But this uncertainty traces to the theoretically constrained character of SA explanation, not to any real indeterminacy. Random genetic drift is an artifact of such uncertainty, and it (...) is therefore wrong to reify it as a cause of evolution or as a process in its own right. *Received July 2009. †To contact the author, please write to: Department of Philosophy, University of Toronto, 170 St. George St., Toronto, ON M5R 2M8, Canada; e‐mail: [email protected]. (shrink)

Population genetics attempts to measure the influence of the causes of evolution, viz., mutation, migration, natural selection, and random genetic drift, by understanding the way those causes change the genetics of populations. But how does it accomplish this goal? After a short introduction, we begin in section (2) with a brief historical outline of the origins of population genetics. In section (3), we sketch the model theoretic structure of population genetics, providing the flavor of the ways in (...) which population genetics theory might be understood as incorporating causes. In sections (4) and (5) we discuss two specific problems concerning the relationship between population genetics and evolutionary causes, viz., the problem of conceptually distinguishing natural selection from random genetic drift, and the problem of interpreting fitness. In section (6), we briefly discuss the methodology and key epistemological problems faced by population geneticists in uncovering the causes of evolution. Section (7) of the essay contains concluding remarks. (shrink)

A widely accepted tenet of evolutionary biology is that spontaneous mutations occur randomly with regard to their fitness effect. However, since the mutation rate varies along a genome and this variation can be subject to selection, organisms might evolve lower mutation rates at loci where mutations are most deleterious or increased rates where mutations are most needed. In fact, mechanisms of targeted hypermutation are known in organisms ranging from bacteria to humans. Here we review the main forces driving the evolution (...) of local mutation rates and identify the main limiting factors. Both targeted hyper‐ and hypomutation can evolve, although the former is restricted to loci under very frequent positive selection and the latter is severely limited by genetic drift. Nevertheless, we show how an association of repair with transcription or chromatin‐associated proteins could overcome the drift limit and lead to non‐random hypomutation along the genome in most organisms.Editor's suggested further reading in BioEssays Stress‐induced mutation via DNA breaks in Escherichia coli: A molecular mechanism with implications for evolution and medicine Abstract. (shrink)

Common monogenic genetic diseases, ones that have unexpectedly high frequencies in certain populations, have attracted a great number of conflicting evolutionary explanations. This paper will attempt to explain the mystery of why two particularly extensively studied common genetic diseases, Tay Sachs disease and cystic fibrosis, remain evolutionary mysteries despite decades of research. I review the most commonly cited evolutionary processes used to explain common genetic diseases: reproductive compensation, random genetic drift (in the context of (...) founder effect), and especially heterozygote advantage. The latter process has drawn a particularly large amount of attention, having so successfully explained the elevated frequency of sickle cell anemia in malaria-endemic areas. However, the empirical evidence for heterozygote advantage in other common genetic diseases is quite weak. I introduce and illustrate the significance of a hierarchy of genetic disease phenomena found within the genetic disease explanations, which include the phenomena: single mutation variants of a common genetic disease, single genetic diseases, and classes of diseases with related phenotypic effects. I demonstrate that some of the confusion over the explanations of common genetic diseases can be traced back to confusions over which phenomena are being explained. I proceed to briefly evaluate the existing evidence for two common human genetic diseases: Tay Sachs disease and cystic fibrosis. The above considerations will ultimately shed light on why these diseases’ evolutionary explanations remain so deeply unresolved after so such a great volume of research. (shrink)

Population-level theories of evolution—the stock and trade of population genetics—are statistical theories par excellence. But what accounts for the statistical character of population-level phenomena? One view is that the population-level statistics are a product of, are generated by, probabilities that attach to the individuals in the population. On this conception, population-level phenomena are explained by individual-level probabilities and their population-level combinations. Another view, which arguably goes back to Fisher but has been defended recently, is that the population-level statistics are sui (...) generis, that they somehow emerge from the underlying deterministic behavior of the individuals composing the population. Walsh et al. label this the statistical interpretation. We are not willing to give them that term, since everyone will admit that the population-level theories of evolution are statistical, so we will call this the emergentist statistical interpretation. Our goals are to show that: This interpretation is based on gross factual errors concerning the practice of evolutionary biology, concerning both what is done and what can be done; its adoption would entail giving up on most of the explanatory and predictive projects of evolutionary biology; and finally a rival interpretation, which we will label the propensity statistical interpretation succeeds exactly where the emergentist interpretation fails. (shrink)

Population-level theories of evolution—the stock and trade of population genetics—are statistical theories par excellence. But what accounts for the statistical character of population-level phenomena? One view is that the population-level statistics are a product of, are generated by, probabilities that attach to the individuals in the population. On this conception, population-level phenomena are explained by individual-level probabilities and their population-level combinations. Another view, which arguably goes back to Fisher but has been defended recently, is that the population-level statistics are sui (...) generis, that they somehow emerge from the underlying deterministic behavior of the individuals composing the population. Walsh et al. label this the statistical interpretation. We are not willing to give them that term, since everyone will admit that the population-level theories of evolution are statistical, so we will call this the emergentist statistical interpretation. Our goals are to show that: This interpretation is based on gross factual errors concerning the practice of evolutionary biology, concerning both what is done and what can be done; its adoption would entail giving up on most of the explanatory and predictive projects of evolutionary biology; and finally a rival interpretation, which we will label the propensity statistical interpretation succeeds exactly where the emergentist interpretation fails. (shrink)

Among philosophers, controversy over the notion of drift in population genetics is ongoing. This is at least partly because the notion of drift has an ambiguous usage among population geneticists. My goal in this paper is to explicate the causal dimension of drift, to say what causal influences are responsible for the stochasticity in population genetics models. It is commonplace for population genetics to oppose the influence of selection to that of drift, and to consider how (...) the dynamics of populations are altered when each has greater or lesser influence. I define the causes that are referred to as drift when researchers speak this way. Introduction Populations and Variant Types The Cause–Effect Ambiguity of Drift Non-directional Factors in Population Genetics How N ev Is Used in Population Genetics Causal Conceptions of Drift 6.1 The Millstein/Beatty conception of drift 6.2 Rosenberg and Bouchard: Drift as initial conditions NINPICs 7.1 Why drift is instituted by NINPICs 7.2 How NINPICS work 7.3 NINPICs and random sampling 7.4 Independent sampling and effective population size 7.5 Variance in progeny number 7.6 Population effects of NINPICs NINPICs and the Stochastic Character of Selection Theory Conclusion Appendix CiteULike Connotea Del.icio.us What's this? (shrink)

This book explores important topics in Darwin’s theory of evolution and in the twentieth- and twenty-first-century theories that grew out of it. These topics include fitness, adaptation, altruism, intragenomic conflict, units of selection, genetic drift, the randomness of mutation, gradualism, common ancestry, taxonomy, race, phylogenetic inference, and optimality models. The book brings these and other biological topics into contact with numerous philosophical ideas − operationalism, reductionism, conventionalism, null hypotheses and default reasoning, instrumentalism versus realism, likelihoods versus probabilities, model (...) selection, essentialism, falsifiability, parsimony, the principle of the common cause, comparisons of causal power, interpretations of probaiblity, indeterminism, sensitivity to initial conditions, and the knowability of the past. (shrink)

Many environmental ethicists think evolutionary processes are good or, put differently, that they are morally valuable. Furthermore, many claim this value can be compromised when humans disrupt or cause a break in these processes. In this paper, I argue this account is mistaken. Evolution is not good. Furthermore, evolution cannot be “broken” by mere human involvement. There is no preordained trajectory in evolution; randomness, genetic drift, and historical contingency influence all evolutionary histories. Additionally, to think humans necessarily undermine (...) so-called “natural” processes and turn them artificial is to ignore Vogel (2011, 2015), and insist on pre-Darwinian dualism. There is no morally meaningful distinction between natural selection and artificial selection; they are both simply selection. Furthermore, animals shape their own evolutionary trajectories, their progenies’, and those of other organisms through their intentions and choices—as is illustrated in the theory of niche construction. Human involvement in evolutionary processes does not “break” them nor does it necessarily reduce the value of the end products of those processes. (shrink)

Recently, much philosophical discussion has centered on the best way to characterize the concepts of random drift and natural selection, and, in particular, whether selection and drift can be conceptually distinguished (Beatty, 1984; Brandon, 2005; Hodge, 1983, 1987; Millstein, 2002, 2005; Pfeifer, 2005; Shanahan, 1992; Stephens, 2004). These authors all contend, to a greater or lesser degree, that their concepts make sense of biological practice. So it should be instructive to see how the concepts of drift (...) and selection were distinguished by the disputants in a high-profile debate; debates such as these often force biologists to take a more philosophical turn, discussing the concepts at issue in greater detail than usual. Moreover, it is important to consider a debate where the disputants are actually trying to apply the models of population genetics to natural populations; only then can their proper interpretations become fully apparent. (Indeed, I contend that some of the philosophical confusion has arisen because authors have considered only the models themselves, and not the phenomena that the models are attempting to represent). A prime candidate for just such a case study is what Provine (1986) has termed “The Great Snail Debate,” that is, the debates over the highly polymorphic land snails Cepaea nemoralis and C. hortensis in the 1950s and early 1960s. These studies represent one of the best, if not the best, of the early attempts to demonstrate drift in natural populations. (shrink)

There has recently been a renewed interest in the “force” interpretation of evolutionary biology. In this article, I present the general structure of the arguments for the force interpretation and identify a problem in its overly permissive conditions for being a Newtonian force. I then attempt a solution that (1) helps to illuminate the difference between forces and other types of causes and (2) makes room for random genetic drift as a force. In particular, I argue that (...) forces are not different in kind from other types of causes but rather that forces are situated on a continuum of causes distinguished by their unifying power. †To contact the author, please write to: Department of Philosophy, University of Wisconsin–Madison, 5185 Helen C. White Hall, Madison, WI 53706; e‐mail: [email protected]. (shrink)

Two controversies exist regarding the appropriate characterization of hierarchical and adaptive evolution in natural populations. In biology, there is the Wright-Fisher controversy over the relative roles of random genetic drift, natural selection, population structure, and interdemic selection in adaptive evolution begun by Sewall Wright and Ronald Aylmer Fisher. There is also the Units of Selection debate, spanning both the biological and the philosophical literature and including the impassioned group-selection debate. Why do these two discourses exist separately, and (...) interact relatively little? We postulate that the reason for this schism can be found in the differing focus of each controversy, a deep difference itself determined by distinct general styles of scientific research guiding each discourse. That is, the Wright-Fisher debate focuses on adaptive process, and tends to be instructed by the mathematical modeling style, while the focus of the Units of Selection controversy is adaptive product, and is typically guided by the function style. The differences between the two discourses can be usefully tracked by examining their interpretations of two contested strategies for theorizing hierarchical selection: horizontal and vertical averaging. (shrink)

McShea and Brandon propose that in the absence of constraint, biological diversity increases spontaneously. While heuristically useful, the thesis is unclear and of dubious empirical validity. The authors have no natural way to distinguish entropic decrease of diversity from the kind of increase that they are interested in. They make unsupported claims about how to explain dramatic increases of diversity and increases of functional complexity.

Evolutionary investigations of human crania typically take a limited view of cranial diversity as they discount the possibility that human cranial variation could simply be due to the effects of random genetic drift, gene flow and mutation in favor of natural selection and developmental changes. Natural selection alone cannot explain similarities between patterns of cranial and molecular diversity observed in humans. It appears that the amount of phenotypic variance in the human cranium decreases at the population level (...) as a function of distance from Sub‐Saharan Africa much in the same way as observed for human molecular data.1 BioEssays 29:1185–1188, 2007. © 2007 Wiley Periodicals, Inc. (shrink)

I PSYCHOLOGY 5 The Probabilistic Revolution in Psychology--an Overview Gerd Gigerenzer 7 1 Probabilistic Thinking and the Fight against Subjectivity Gerd Gigerenzer 11 2 Statistical Method and the Historical Development of Research Practice in American Psychology Kurt Danziger 35 3 Survival of the Fittest Probabilist: Brunswik, Thurstone, and the Two Disciplines of Psychology Gerd Gigerenzer 49 4 A Perspective for Viewing the Integration of Probability Theory in Psychology David J. Murray 73 II SOCIOLOGY 101 5 The Two Empirical Roots of (...) Social Theory and the Probability Revolution Anthony Oberschall 103 III ECONOMICS 133 The Probabilistic Revolution in Economics--an Overview Mary S. Morgan 135 6 Why Was There No Probabilistic Revolution in Economic Thought? Claude Mènard 139 7 The Rise of Macroeconomic Calculations in Economic Statistics Robert A. Horváth 147 8 Statistics without Probability and Haavelmo’s Revolution in Econometrics Mary S. Morgan 171 IV PHYSIOLOGY 199 9 Experimental Physiology and Statistical Inference: The Therapeutic Trial in Nineteenth-Century Germany William Coleman 201 V EVOLUTIONARY BIOLOGY 227 The Probabilistic Revolution in Evolutionary Biology--an Overview John H. Beatty 229 10 Natural Selection as a Causal, Empirical, and Probabilistic Theory M. J. S. Hodge 233 11 Dobzhansky and Drift: Facts, Values, and Chance in Evolutionary Biology John H. Beatty 271 12 Random Genetic Drift, R. A. Fisher, and the Oxford School of Ecological Genetics John R. G. Turner 313 13 On the Prior Probability of the Existence of Life Bernd-Olaf Küppers 355 VI PHYSICS 371 The Probabilistic Revolution in Physics--an Overview Lorenz Krüger 373 14 Probabilistic Physics the Classical Way Jan von Plato 379 15 Max Born and the Reality of Quantum Probabilities Nancy Cartwright 409 16 Philosophical Problems of Quantum Theory: The Response of American Physicists Nancy Cartwright. (shrink)

Evolutionary biology since Darwin has seen a dramatic entrenchment and elaboration of the role of chance in evolution. It is nearly impossible to discuss contemporary evolutionary theory in any depth at all without making reference to at least some concept of “chance” or “randomness.” Many processes are described as chancy, outcomes are characterized as random, and many evolutionary phenomena are thought to be best described by stochastic or probabilistic models. Chance is taken by various authors to be central to (...) the understanding of fitness, genetic drift, macroevolution, mutation, foraging theory, and environmental variation, to take but a few examples. And for each of these notions, there are yet more stories to tell. Each weaves itself into the various branches of evolutionary theory in myriad different ways, with a wide variety of effects on the history and current state of life on Earth. Each is grounded in a particular trajectory in the history of philosophy and the history of biology, and has inspired a variety of responses throughout science and culture. This book endeavors to offer a cross-section of biological, historical, philosophical, and theological approaches to understanding chance in evolutionary theory. (shrink)

One hotly debated philosophical question in the analysis of evolutionary theory concerns whether or not evolution and the various factors which constitute it may profitably be considered as analogous to “forces” in the traditional, Newtonian sense. Several compelling arguments assert that the force picture is incoherent, due to the peculiar nature of genetic drift. I consider two of those arguments here – that drift lacks a predictable direction, and that drift is constitutive of evolutionary systems – (...) and show that they both fail to demonstrate that a view of genetic drift as a force is untenable. I go on to diagnose the reasons for the stubborn persistence of this problem, considering two open philosophical issues and offering some preliminary arguments in support of the force metaphor. (shrink)

Do evolutionary processes such as selection and random drift cause evolutionary change, or are they merely convenient ways of describing or summarizing it? Philosophers have lined up on both sides of this question. One recent defense (Reisman and Forber 2005) of the causal status of selection and drift appeals to a manipulability theory of causation. Yet, even if one accepts manipulability, there are still reasons to doubt that genetic drift, in particular, is genuinely causal. We (...) will address two challenges to treating drift as causal within a manipulation framework. We will argue that both challenges ultimately fail, but that they raise interesting and subtle issues about the nature of causation and the differences between selection and drift. ‡Thanks to audiences at the ‘PBDB1' Conference and the 2006 PSA Meeting for valuable feedback. †To contact the authors, please write to: Patrick Forber, Tufts University, Philosophy Department, Miner Hall, Medford, MA 02155; e-mail: [email protected]. (shrink)

While the notion of chance has been central in discussions over the probabilistic nature of natural selection and genetic drift, its role in the production of variants on which populational sampling takes place has received much less philosophical attention. This article discusses the concept of chance in evolution in the light of contemporary work in evo-devo. We distinguish different levels at which randomness and chance can be defined in this context, and argue that recent research on variability and (...) evolvability demands a causal understanding of variational probabilities under which development acquires a creative, rather than a constraining role in evolution. We then provide a propensity interpretation of variational probabilities that solves a conceptual confusion between causal properties, variational probabilities and extant variation present in the literature, and explore some metaphysical consequences that follow from our interpretation, specifically with regards to the nature of developmental types. (shrink)

Discussions of “chance” and related concepts are found throughout philosophical work on evolutionary theory. By drawing attention to three very commonly-recognized distinctions, I separate four independent concepts falling under the broad heading of “chance”: randomness, epistemic unpredictability, causal indeterminism, and probabilistic causal processes. Far from a merely semantic distinction, however, it is demonstrated that conflation of these obviously distinct notions has an important bearing on debates at the core of evolutionary theory, particularly the debate over the interpretation of fitness, natural (...) selection, and genetic drift. (shrink)

Chance comes into plays at many levels of the explanation of the evolutionary process; but the unity of sense of this category is problematic. The purpose of this talk is to clarify the meaning of chance at various levels in evolutionary theory: mutations, genetic drift, genetic revolutions, ecosystems, macroevolution. Three main concepts of chance are found at these various levels: luck (popular concept), randomness (probabilistic concept), and contingency relative to a given theoretical system (epistemological concept). After identifying (...) which concept(s) of chance fit(s) with these levels, the question is raised whether these concepts can be reduced to a smaller number, and whether chance in evolutionary theory has a subjective or an objective sense. (shrink)

Evolutionary biology teaches that all biological complexity is the result of material mechanisms. These include principally the Darwinian mechanism of natural selection and random variation, but also include other mechanisms (symbiosis, gene transfer, genetic drift, the action of regulatory genes in development, self-organizational processes, etc.). These mechanisms are just that: mindless material mechanisms that do what they do irrespective of intelligence. To be sure, mechanisms can be programmed by an intelligence. But any such intelligent programming of evolutionary (...) mechanisms is not properly part of evolutionary biology. (shrink)

Both language and genes evolve by transmission over generations with opportunity for differential replication of forms. The understanding that gene frequencies change at random by genetic drift, even in the absence of natural selection, was a seminal advance in evolutionary biology. Stochastic drift must also occur in language as a result of randomness in how linguistic forms are copied between speakers. Here we quantify the strength of selection relative to stochastic drift in language evolution. We (...) use time series derived from large corpora of annotated texts dating from the 12th to 21st centuries to analyse three well-known grammatical changes in English: the regularization of past-tense verbs, the introduction of the periphrastic ’do’, and variation in verbal negation. We reject stochastic drift in favour of selection in some cases but not in others. In particular, we infer selection towards the irregular forms of some past-tense verbs, which is likely driven by changing frequencies of rhyming patterns over time. We show that stochastic drift is stronger for rare words, which may explain why rare forms are more prone to replacement than common ones. This work provides a method for testing selective theories of language change against a null model and reveals an underappreciated role for stochasticity in language evolution. (shrink)

The adequacy of Elliott Sober’s analogy between classical mechanics and evolutionary theory—according to which both theories explain via a zero-force law and a set of forces that alter the zero-force state—has been criticized from various points of view. I focus here on McShea and Brandon’s claim that drift shouldn’t be considered a force because it is not directional. I argue that there are a number of different theses that could be meant by this, and show that one of those (...) theses—the idea that drift cannot bias populations to be taken somewhere in the evolutionary space from one generation to the next—is actually false. Not only has this thesis been implicitly assumed in the discussion of the force analogy thus far, but it is also commonly found in a wider range of philosophical and biological texts. I argue that correcting this view, and the usual images associated with it, will thereby bring heuristic benefits that impact the force analogy discussion, but that also go beyond it. (shrink)

Recent experimental data from proteomics and genomics are interpreted here in ways that challenge the predominant viewpoint in biology according to which the four evolutionary processes, including mutation, recombination, natural selection and genetic drift, are sufficient to explain the origination of species. The predominant viewpoint appears incompatible with the finding that the sequenced genome of each species contains hundreds, or even thousands, of unique genes - the genes that are not shared with any other species. These unique genes (...) and proteins, singletons, define the very character of every species. Moreover, the distribution of protein families from the sequenced genomes indicates that the complexity of genomes grows in a manner different from that of self-organizing networks: the dominance of singletons leads to the conclusion that in living organisms a most unlikely phenomenon can be the most common one. In order to provide proper rationale for these conclusions related to the singletons, the paper first treats the frequency of functional proteins among random sequences, followed by a discussion on the protein structure space, and it ends by questioning the idea that protein domains represent conserved units of evolution. (shrink)

November 4th-5th, 2012 at Kyoto University. Organizers: Hisashi Nakao & Pierre-Alain Braillard.

Population genetics is often taught in introductory biology classes, starting with the Hardy–Weinberg principle (HWP) and genetic drift. Here I argue that teaching these two topics first aligns neither with current expert knowledge, nor with good pedagogy. Student difficulties with mathematics in general, and probability in particular, make population genetics difficult to teach and learn. I recommend an alternative, historically inspired ordering of population genetics topics, based on progressively increasing mathematical difficulty. This progression can facilitate just‐in‐time math instruction. (...) This alternative ordering includes, but does not privilege, the HWP and genetic drift. Stochastic events whose consequences are felt within a single generation, and the deterministic accumulation of the effects of selection across multiple generations, are both taught before tackling the stochastic accumulation of the effects of accidents of sampling. (shrink)

Really statistical explanation is a hitherto neglected form of noncausal scientific explanation. Explanations in population biology that appeal to drift are RS explanations. An RS explanation supplies a kind of understanding that a causal explanation of the same result cannot supply. Roughly speaking, an RS explanation shows the result to be mere statistical fallout.

The origin of the genetic code has been attributed in part to an accidental assignment of codons to amino acids. Although several lines of evidence indicate the subsequent expansion and improvement of the genetic code, the hypothesis of Francis Crick concerning a frozen accident occurring at the early stage of genetic code evolution is still widely accepted. Considering Crick’s hypothesis, mathematical descriptions of hypothetical scenarios involving a huge number of possible coexisting random genetic codes could (...) be very important to explain the origin and evolution of a selected genetic code. This work aims to contribute in this regard, that is, it provides a theoretical framework in which statistical parameters of error functions are calculated. Given a genetic code and an amino acid property, the functional code robustness is estimated by means of a known error function. In this work, using analytical calculations, general expressions for the average and standard deviation of the error function distributions of completely random codes with standard stop codons were obtained. As a possible biological application of these results, any set of amino acids and any pure or mixed amino acid properties can be used in the calculations, such that, in case of having to select a set of amino acids to create a genetic code, possible advantages of natural selection of the genetic codes could be discussed. (shrink)

The latter half of the twentieth century has been marked by debates in evolutionary biology over the relative significance of natural selection and random drift: the so-called “neutralist/selectionist” debates. Yet John Beatty has argued that it is difficult, if not impossible, to distinguish the concept of random drift from the concept of natural selection, a claim that has been accepted by many philosophers of biology. If this claim is correct, then the neutralist/selectionist debates seem at best (...) futile, and at worst, meaningless. I reexamine the issues that Beatty raises, and argue that random drift and natural selection, conceived as processes, can be distinguished from one another. (shrink)

This article elaborates on McShea and Brandon’s idea that drift is unlike the rest of the evolutionary factors because it is constitutive rather than imposed on the evolutionary process. I show that the way they spelled out this idea renders it inadequate and is the reason why it received some objections. I propose a different way in which their point could be understood, that rests on two general distinctions. The first is a distinction between the underlying mathematical apparatus used (...) to formulate a theory and a concept proposed by that theory. With the aid of a formal reconstruction of a population genetic model, I show that drift belongs to the first category. That is, that drift is constitutive of population genetics in the same sense that multiplication is constitutive in classical mechanics, or that circle is constitutive in Ptolemaic astronomy. The second distinction is between eliminating a concept from a theory and setting its value to zero. I will show that even though drift can be set to zero just like the rest of the evolutionary factors, eliminating drift is much harder than eliminating those other factors, since it would require changing the entire mathematical apparatus of standard population genetic theory. I conclude by drawing some other implications from the proposed formal reconstruction. (shrink)

Alexander Rosenberg (1994) claims that the omniscient viewpoint of the evolutionary process would have no need for the concept of random drift. However, his argument fails to take into account all of the processes which are considered to be instances of random drift. A consideration of these processes shows that random drift is not eliminable even given a position of omniscience. Furthermore, Rosenberg must take these processes into account in order to support his claims (...) that evolution is deterministic and that evolutionary biology is an instrumental science. (shrink)

Several recent arguments by philosophers of biology have challenged the traditional view that evolutionary factors, such as drift and selection, are genuine causes of evolutionary outcomes. In the case of drift, advocates of the statistical theory argue that drift is merely the sampling error inherent in the other stochastic processes of evolution and thus denotes a mathematical, rather than causal, feature of populations. This debate has largely centered around one particular model of drift, the Wright–Fisher model, (...) and this has contributed to the plausibility of the statisticalists’ arguments. However, an examination of alternative, predictively inequivalent models shows that drift is a genuine cause that can be manipulated to change population outcomes. This case study illustrates the influence of methodological assumptions on ontological judgments, particularly the pernicious effect of focusing on a particular model at the expense of others and confusing its assumptions and idealizations for true claims about the phenomena being modeled. (shrink)

This article analyzes the view of evolutionary theory as a theory of forces. The analogy with Newtonian mechanics has been challenged due to the alleged mismatch between drift and the other evolutionary forces. Since genetic drift has no direction several authors tried to protect its status as a force: denying its lack of directionality, extending the notion of force and looking for a force in physics which also lacks of direction. I analyse these approaches, and although this (...) strategy finally succeeds, this discussion overlooks the crucial point on the debate between causalists and statisticalists: the causal status of evolutionary theory. (shrink)

We distinguish dynamical and statistical interpretations of evolutionary theory. We argue that only the statistical interpretation preserves the presumed relation between natural selection and drift. On these grounds we claim that the dynamical conception of evolutionary theory as a theory of forces is mistaken. Selection and drift are not forces. Nor do selection and drift explanations appeal to the (sub-population-level) causes of population level change. Instead they explain by appeal to the statistical structure of populations. We briefly (...) discuss the implications of the statistical interpretation of selection for various debates within the philosophy of biologythe `explananda of selection' debate and the `units of selection' debate. (shrink)

The statistical interpretation of the Theory of Natural Selection claims that natural selection and drift are statistical features of mathematical aggregates of individual-level events. Natural selection and drift are not themselves causes. The statistical interpretation is motivated by a metaphysical conception of individual priority. Recently, Millstein, Skipper, and Dietrich (2009) have argued (a) that natural selection and drift are physical processes, and (b) that the statistical interpretation rests on a misconception of the role of mathematics in biology. (...) Both theses are contested. (shrink)