... Difficulty of distinguishing between Varieties and Species — Origin of Domestic ... and Origin— Principle of Selection anciently followed, its Effects— ...

Woodward's long awaited book is an attempt to construct a comprehensive account of causation explanation that applies to a wide variety of causal and explanatory claims in different areas of science and everyday life. The book engages some of the relevant literature from other disciplines, as Woodward weaves together examples, counterexamples, criticisms, defenses, objections, and replies into a convincing defense of the core of his theory, which is that we can analyze causation by appeal to the notion of manipulation.

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)

This paper is an interpretation and defense of Richard Levins’ “The Strategy of Model Building in Population Biology,” which has been extremely influential among biologists since its publication 40 years ago. In this article, Levins confronted some of the deepest philosophical issues surrounding modeling and theory construction. By way of interpretation, I discuss each of Levins’ major philosophical themes: the problem of complexity, the brute-force approach, the existence and consequence of tradeoffs, and robustness analysis. I argue that Levins’ article is (...) concerned, at its core, with justifying the use of multiple, idealized models in population biology. (shrink)

The most compelling extant accounts of explanation casts all explanations as causal. Yet there are sciences, theoretical population biology in particular, that explain their phenomena by appeal to statistical, non-causal properties of ensembles. I develop a generalised account of explanation. An explanation serves two functions: metaphysical and cognitive. The metaphysical function is discharged by identifying a counterfactually robust invariance relation between explanans event and explanandum. The cognitive function is discharged by providing an appropriate description of this relation. I offer examples (...) of explanations from portfolio theory and population genetics that meet this characterisation. In each case the invariance relation holds between a statistical property of an ensemble and a change in structure of the ensemble. In neither case, however, does the statistical property cause the outcome it explains. There are genuine statistical, non-causal scientific explanations. (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)

There are two competing interpretations of the modern synthesis theory of evolution: the dynamical (also know as ‘traditional’) and the statistical. The dynamical interpretation maintains that explanations offered under the auspices of the modern synthesis theory articulate the causes of evolution. It interprets selection and drift as causes of population change. The statistical interpretation holds that modern synthesis explanations merely cite the statistical structure of populations. This paper offers a defense of statisticalism. It argues that a change in trait frequencies (...) in a population can be attributed only to selection or drift against the background of a particular statistical description of the population. The traditionalist supposition that selection and drift are description‐independent causes of population change leads the dynamical interpretation into a dilemma: it must face a contradiction or accept the loss of explanatory power. (shrink)

In evolutionary biology changes in population structure are explained by citing trait fitness distribution. I distinguish three interpretations of fitness explanations—the Two‐Factor Model, the Single‐Factor Model, and the Statistical Interpretation—and argue for the last of these. These interpretations differ in their degrees of causal commitment. The first two hold that trait fitness distribution causes population change. Trait fitness explanations, according to these interpretations, are causal explanations. The last maintains that trait fitness distribution correlates with population change but does not cause (...) it. My defense of the Statistical Interpretation relies on a distinctive feature of causation. Causes conform to the Sure Thing Principle. Trait fitness distributions, I argue, do not. *Received July 2009; revised October 2009. †To contact the author, please write to: Department of Philosophy/Institute for the History, Philosophy of Science and Technology, University of Toronto, Victoria College, 91 Charles Street West, Toronto, ON M5S 1K7, Canada; e‐mail: [email protected]. (shrink)

The Units of Selection debate is a dispute about the causes of population change. I argue that it is generated by a particular `dynamical'' interpretation of natural selection theory, according to which natural selection causes differential survival and reproduction of individuals and natural selection explanations cite these causes. I argue that the dynamical interpretation is mistaken and offer in outline an alternative, `statistical'' interpretation, according to which natural selection theory is a fancy kind of `bookkeeping''. It explains by citing the (...) statistical structure of a population and not by citing the causes of survival and reproduction. From the perspective of the statistical interpretation there is no substantive Units of Selection issue. (shrink)

We present a logically detailed case-study of Darwinian evolutionary explanation. Special features of Darwin’s explanatory schema made it an unusual theoretical breakthrough, from the point of view of the philosophy of science. The schema employs no theoretical terms, and puts forward no theoretical hypotheses. Instead, it uses three observational generalizations—Variability, Heritability and Differential Reproduction—along with an innocuous assumption of Causal Efficacy, to derive Adaptive Evolution as a necessary consequence. Adaptive Evolution in turn, with one assumption of scale (‘Deep Time’), implies (...) the observational generalization of Adaptation. It is a fascinating methodological task to regiment the premises and make the reasoning both rigorous and clear. Doing so reveals how surprisingly small an amount of mathematics is needed in order to carry out the argument. The investigation also reveals the crucial role played by heritability, and how heritability itself admits of Darwinian explanation. (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)

I defend a radical interpretation of biological populations—what I call population pluralism—which holds that there are many ways that a particular grouping of individuals can be related such that the grouping satisfies the conditions necessary for those individuals to evolve together. More constraining accounts of biological populations face empirical counter-examples and conceptual difficulties. One of the most intuitive and frequently employed conditions, causal connectivity—itself beset with numerous difficulties—is best construed by considering the relevant causal relations as ‘thick’ causal concepts. I (...) argue that the fine-grained causal relations that could constitute membership in a biological population are huge in number and many are manifested by degree, and thus we can construe population membership as being defined by massively multidimensional constructs, the differences between which are largely arbitrary. I end by showing that positions in two recent debates in theoretical biology depend on a view of biological populations at odds with the pluralism defended here. (shrink)

I defend a radical interpretation of biological populations—what I call population pluralism—which holds that there are many ways that a particular grouping of individuals can be related such that the grouping satisfies the conditions necessary for those individuals to evolve together. More constraining accounts of biological populations face empirical counter-examples and conceptual difficulties. One of the most intuitive and frequently employed conditions, causal connectivity—itself beset with numerous difficulties—is best construed by considering the relevant causal relations as ‘thick’ causal concepts. I (...) argue that the fine-grained causal relations that could constitute membership in a biological population are huge in number and many are manifested by degree, and thus we can construe population membership as being defined by massively multidimensional constructs, the differences between which are largely arbitrary. I end by showing that positions in two recent debates in theoretical biology depend on a view of biological populations at odds with the pluralism defended here. 1 Introduction2 Biological Population, Broad and Narrow3 Difficulties with Narrow Biological Population Conditions3.1 Against the genealogical condition3.2 Against the conspecificity condition3.3 Against the proximity condition3.4 Against the typology condition4 Causal Connectivity5 Massively Multidimensional Population Constructs6 Population Uniqueness and Natural Selection6.1 Statisticalism and its discontents6.2 Price at what price?7 Conclusion. (shrink)

The Nature of Selection is a straightforward, self-contained introduction to philosophical and biological problems in evolutionary theory. It presents a powerful analysis of the evolutionary concepts of natural selection, fitness, and adaptation and clarifies controversial issues concerning altruism, group selection, and the idea that organisms are survival machines built for the good of the genes that inhabit them. "Sober's is the answering philosophical voice, the voice of a first-rate philosopher and a knowledgeable student of contemporary evolutionary theory. His book merits (...) broad attention among both communities. It should also inspire others to continue the conversation."-Philip Kitcher, Nature "Elliott Sober has made extraordinarily important contributions to our understanding of biological problems in evolutionary biology and causality. The Nature of Selection is a major contribution to understanding epistemological problems in evolutionary theory. I predict that it will have a long lasting place in the literature."-Richard C. Lewontin. (shrink)

The propensity interpretation of fitness draws on the propensity interpretation of probability, but advocates of the former have not attended sufficiently to problems with the latter. The causal power of C to bring about E is not well-represented by the conditional probability Pr. Since the viability fitness of trait T is the conditional probability Pr, the viability fitness of the trait does not represent the degree to which having the trait causally promotes surviving. The same point holds for fertility fitness. (...) This failure of trait fitness to capture causal role can also be seen in the fact that coextensive traits must have the same fitness values even if one of them promotes survival and the other is neutral or deleterious. Although the fitness of a trait does not represent the trait’s causal power to promote survival and reproduction, variation in fitness in a population causally promotes change in trait frequencies; in this sense, fitness variation is a population-level propensity. (shrink)

In several places we have argued that ‘fitness’ is a primitive term with respect to the theory of evolution properly understood. These arguments have relied heavily on the axiomatization of the theory provided by one of us. In contrast, both John Beatty and Robert Brandon have separately argued for a “propensity“ interpretation of “fitness” ; and in Brandon and Beatty they attack our view that “fitness“ is a primitive term in evolutionary theory, concluding that a definition by way of propensities (...) is possible and preferable. Here we reply to their criticisms, and argue that, at most, the view that fitness is a statistical propensity is a terminological variant on our thesis that it is a primitive in evolutionary theory. (shrink)

Denis Walsh has written a striking new defense in this journal of the statisticalist (i.e., noncausalist) position regarding the forces of evolution. I defend the causalist view against his new objections. I argue that the heart of the issue lies in the nature of nonadditive causation. Detailed consideration of that turns out to defuse Walsh’s ‘description‐dependence’ critique of causalism. Nevertheless, the critique does suggest a basis for reconciliation between the two competing views. *Received December 2009; revised December 2009. †To contact (...) the author, please write to: Department of Philosophy, 599 Lucas Hall, One University Boulevard, University of Missouri, St. Louis, MO 63121; e‐mail: [email protected]. (shrink)

The debate between the Mendelians and the (largely Darwinian) biometricians has been referred to by R. A. Fisher as ‘one of the most needless controversies in the history of science’ and by David Hull as ‘an explicable embarrassment’. The literature on this topic consists mainly of explaining why the controversy occurred and what factors prevented it from being resolved. Regrettably, little or no mention is made of the issues that figured in its resolution. This paper deals with the latter topic (...) and in doing so reorients the focus of the debate as one between Karl Pearson and R. A. Fisher rather than between the biometricians and the Mendelians. One reason for this reorientation is that Pearson's own work in 1904 and 1909 suggested that Mendelism and biometry could, to some extent, be made compatible, yet he remained steadfast in his rejection of Mendelism. The interesting question then is why Fisher, who was also a proponent of biometric methods, was able to synthesise the two traditions in a way that Pearson either could not or would not. My answer to this question involves an analysis of the ways in which different kinds of assumptions were used in modelling Mendelian populations. I argue that it is these assumptions, which lay behind the statistical techniques of Pearson and Fisher, that can be isolated as the source of Pearson's rejection of Mendelism and Fisher's success in the synthesis. (shrink)

Recent discussions in the philosophy of biology have brought into question some fundamental assumptions regarding evolutionary processes, natural selection in particular. Some authors argue that natural selection is nothing but a population-level, statistical consequence of lower-level events (Matthen and Ariew [2002]; Walsh et al. [2002]). On this view, natural selection itself does not involve forces. Other authors reject this purely statistical, population-level account for an individual-level, causal account of natural selection (Bouchard and Rosenberg [2004]). I argue that each of these (...) positions is right in one way, but wrong in another; natural selection indeed takes place at the level of populations, but it is a causal process nonetheless. (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)

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)

We have argued elsewhere that: (A) Natural selection is not a cause of evolution. (B) A resolution-of-forces (or vector addition) model does not provide us with a proper understanding of how natural selection combines with other evolutionary influences. These propositions have come in for criticism recently, and here we clarify and defend them. We do so within the broad framework of our own “hierarchical realization model” of how evolutionary influences combine.

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)

Throughout, this book questions our accepted definitions and biases, showing the self-reflective nature of scientific activity within society.

Some properties are causally relevant for a certain effect, others are not. In this paper we describe a problem for our understanding of this notion and then offer a solution in terms of the notion of a program explanation.

I criticize some arguments against the causal interpretability of population genetics put forward by Denis Walsh ([2007], [2010]). In particular, I seek to undermine the contention that population genetics exhibits frame of reference relativity or subjectivity with respect to its formal representations. I also show that classical population genetics does not fall foul of some criteria for causal representation put forward by James Woodward ([2003]), although those criteria do undermine some causalist stances. 1 Introduction2 Modularity3 The Crucially Important Point4 The (...) Gillespie Case: Density-Dependent Selection5 Conclusion. (shrink)

What is natural selection? I address this question by exploring the relation between two debates: Is natural selection a mechanism? Is natural selection a causal or a statistical theory? I argue that the first can be assessed only relative to a model and that, following the second, there are two fundamentally different and independent kinds of models, Modern-Synthesis and Darwinian models. MS-models, I argue, are not mechanistic even if they are causal. D-models, in contrast, are mechanistic. A causal-mechanistic interpretation of (...) D-models is thus compatible with a statistical interpretation of MS-models. Natural selection, I conclude, lacks a single, unifying nature. (shrink)

On the classical account of evolution by natural selection found in Lewontin and many subsequent authors, ENS is conceived as involving three key ingredients: phenotypic variation, fitness differences, and heredity. Through the analysis of three problem cases involving heredity, I argue that the classical conception is substantially flawed, showing that heredity is not required for selection. I consider further problems with the classical account of ENS arising from conflations between three distinct senses of the central concept of ‘fitness’ and offer (...) an alternative to the classical conception of ENS involving the interaction of distinct evolutionary mechanisms. (shrink)

Drift is to evolution as inertia is to Newtonian mechanics. Both are the "natural" or default states of the systems to which they apply. Both are governed by zero-force laws. The zero-force law in biology is stated here for the first time.

Recently advocates of the propensity interpretation of fitness have turned critics. To accommodate examples from the population genetics literature they conclude that fitness is better defined broadly as a family of propensities rather than the propensity to contribute descendants to some future generation. We argue that the propensity theorists have misunderstood the deeper ramifications of the examples they cite. These examples demonstrate why there are factors outside of propensities that determine fitness. We go on to argue for the more general (...) thesis that no account of fitness can satisfy the desiderata that have motivated the propensity account. (shrink)

The central point of this essay is to demonstrate the incommensurability of ‘Darwinian fitness’ with the numeric values associated with reproductive rates used in population genetics. While sometimes both are called ‘fitness’, they are distinct concepts coming from distinct explanatory schemes. Further, we try to outline a possible answer to the following question: from the natural properties of organisms and a knowledge of their environment, can we construct an algorithm for a particular kind of organismic life-history pattern that itself will (...) allow us to predict whether a type in the population will increase or decrease relative to other types? Introduction Darwinian fitness Reproductive fitness and genetical models of evolution The models of reproductive fitness 4.1 The Standard Viability Model 4.2 Frequency-dependent selection 4.3 Fertility models 4.4 Overlapping generations Fitness as outcome 5.1 Fitness as actual increase in type 5.2 Fitness as expected increase in type 5.2.1 Expected increase within a generation 5.2.2 Expected increase between generations 5.2.3 Postponed reproductive fitness effects The book-keeping problem Conclusion. (shrink)

The central point of this essay is to demonstrate the incommensurability of ‘Darwinian fitness’ with the numeric values associated with reproductive rates used in population genetics. While sometimes both are called ‘fitness’, they are distinct concepts coming from distinct explanatory schemes. Further, we try to outline a possible answer to the following question: from the natural properties of organisms and a knowledge of their environment, can we construct an algorithm for a particular kind of organismic life-history pattern that itself will (...) allow us to predict whether a type in the population will increase or decrease relative to other types? 1. Introduction2. Darwinian fitness3. Reproductive fitness and genetical models of evolution4. The models of reproductive fitness4.1 The Standard Viability Model4.2 Frequency-dependent selection4.3 Fertility models4.4 Overlapping generations5. Fitness as outcome5.1 Fitness as actual increase in type5.2 Fitness as expected increase in type5.2.1 Expected increase within a generation5.2.2 Expected increase between generations5.2.3 Postponed reproductive fitness effects6. The book-keeping problem7. Conclusion. (shrink)

In “Two Ways of Thinking About Fitness and Natural Selection” (Matthen and Ariew [2002]; henceforth “Two Ways”), we asked how one should think of the relationship between the various factors invoked to explain evolutionary change – selection, drift, genetic constraints, and so on. We suggested that these factors are not related to one another as “forces” are in classical mechanics. We think it incoherent, for instance, to think of natural selection and drift as separate and opposed “forces” in evolutionary change (...) – that it makes sense to say, for instance, that selection contributed 80% to the actual evolutionary history of the human eye, and drift only 20%. We proposed instead a statistical view of the Theory of Evolution, a view in which fitness is not a cause of evolution, but rather a measure of growth. We also argued for a “hierarchical realization model” for thinking about the relationship between evolutionary factors such as those mentioned above, and suggested that in a “fully specified model”, as we call it below, there is no distinction between natural selection and evolution. (shrink)

It's been 41 years since the publication of Ernst Mayr's Cause and Effect in Biology wherein Mayr most clearly develops his version of the influential distinction between ultimate and proximate causes in biology. In critically assessing Mayr's essay I uncover false statements and red-herrings about biological explanation. Nevertheless, I argue to uphold an analogue of the ultimate/proximate distinction as it refers to two different kinds of explanations, one dynamical the other statistical.

Several philosophers of science have advanced an instrumentalist thesis about the use of probabilities in evolutionary biology. I investigate the consequences of instrumentalism on evolutionary explanations. I take issue with Barbara Horan's (1994) argument that probabilities are unnecessary to explain evolutionary change given the underlying deterministic character of evolutionary processes. First, I question Horan's deterministic assumption. Then, I attempt to undermine her Laplacian argument by demonstrating that whether probabilities are necessary depends upon the sort of questions one is asking.

and was correct to conclude that the way a biological population is described should affect conclusions about whether natural selection occurs, but wrong to conclude that natural selection is therefore not a cause. After providing a new argument that ignored crucial biological details, I give a biological illustration that motivates a fairly extreme dependence on description. I argue that contrary to an implication of , biologists allow much flexibility in describing populations, as contemporary research on recent human evolution shows. Properly (...) understood, such description-dependence is consistent with descriptions capturing different causal relations involving the same population. I thus show that Walsh’s arguments fail for reasons that have not previously been understood; I argue that Walsh’s more recent “Sure Thing” argument fails for similar reasons. The resulting view provides a new perspective on causation in evolutionary processes. (shrink)

After the discovery of the structure of DNA in 1953, scientists working in molecular biology embraced reductionism—the theory that all complex systems can be understood in terms of their components. Reductionism, however, has been widely resisted by both nonmolecular biologists and scientists working outside the field of biology. Many of these antireductionists, nevertheless, embrace the notion of physicalism—the idea that all biological processes are physical in nature. How, Alexander Rosenberg asks, can these self-proclaimed physicalists also be antireductionists? With clarity and (...) wit, Darwinian Reductionism navigates this difficult and seemingly intractable dualism with convincing analysis and timely evidence. In the spirit of the few distinguished biologists who accept reductionism—E. O. Wilson, Francis Crick, Jacques Monod, James Watson, and Richard Dawkins—Rosenberg provides a philosophically sophisticated defense of reductionism and applies it to molecular developmental biology and the theory of natural selection, ultimately proving that the physicalist must also be a reductionist. (shrink)

One of our most brilliant evolutionary biologists, Richard Lewontin has also been a leading critic of those--scientists and non-scientists alike--who would misuse the science to which he has contributed so much. In The Triple Helix, Lewontin the scientist and Lewontin the critic come together to provide a concise, accessible account of what his work has taught him about biology and about its relevance to human affairs. In the process, he exposes some of the common and troubling misconceptions that misdirect and (...) stall our understanding of biology and evolution.The central message of this book is that we will never fully understand living things if we continue to think of genes, organisms, and environments as separate entities, each with its distinct role to play in the history and operation of organic processes. Here Lewontin shows that an organism is a unique consequence of both genes and environment, of both internal and external features. Rejecting the notion that genes determine the organism, which then adapts to the environment, he explains that organisms, influenced in their development by their circumstances, in turn create, modify, and choose the environment in which they live.The Triple Helix is vintage Lewontin: brilliant, eloquent, passionate, and deeply critical. But it is neither a manifesto for a radical new methodology nor a brief for a new theory. It is instead a primer on the complexity of biological processes, a reminder to all of us that living things are never as simple as they may seem. (shrink)