Anya Plutynski

Speciation is the process by which one or more species arises from a common ancestor, and “macroevolution” refers to patterns and processes at and above the species level – or, transitions in higher taxa, such as new families, phyla or genera. “Macroevolution” is contrasted with “microevolution,” evolutionary change within populations, due to migration, assortative mating, selection, mutation and drift. In the evolutionary synthesis of the 1930’s and 40’s, Haldane , Dobzhansky , Mayr , and Simpson argued that the origin of species and higher taxa were, given the right environmental conditions and sufficient time, the product of the same microevolutionary factors yielding change within populations. Dobzhansky reviewed the evidence from genetics, and argued, “nothing in the known macroevolutionary phenomena would require other than the known genetic principles for causal explanation” . In sum, genetic variation between species was not different in kind from the genetic variation within species. Dobzhansky concluded that one may “reluctantly put an equal sign” between micro- and macroevolution. In this chapter, I review arguments for and against this "neo-Darwinian" consensus on speciation, as well as debates concerning macroevolution and punctuated equilibrium

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.

In the past five years, there have been a series of papers in the journal Evolution debating the relative significance of two theories of evolution, a neo-Fisherian and a neo-Wrightian theory, where the neo-Fisherians make explicit appeal to parsimony. My aim in this paper is to determine how we can make sense of such an appeal. One interpretation of parsimony takes it that a theory that contains fewer entities or processes, (however we demarcate these) is more parsimonious. On the account that I defend here, parsimony is a ‘local’ virtue. Scientists’ appeals to parsimony are not necessarily an appeal to a theory’s simplicity in the sense of it’s positing fewer mechanisms. Rather, parsimony may be proxy for greater probability or likelihood. I argue that the neo-Fisherians appeal is best understood on this interpretation. And indeed, if we interpret parsimony as either prior probability or likelihood, then we can make better sense of Coyne et al. argument that Wright’s three phase process operates relatively infrequently.

In 1968, Motoo Kimura submitted a note to Nature entitled “Evolutionary Rate at the Molecular Level,” in which he proposed what has since become known as the neutral theory of molecular evolution. This is the view that the majority of evolutionary changes at the molecular level are caused by random drift of selectively neutral or nearly neutral alleles. Kimura was not proposing that random drift explains all evolutionary change. He does not challenge the view that natural selection explains adaptive evolution, or, that the vertebrate eye or the tetrapod limb are products of natural selection. Rather, his objection is to “panselectionism’s intrusion into the realm of molecular evolutionary studies”. According to Kimura, most changes at the molecular level from one generation to the next do not affect the fitness of organisms possessing them. King and Jukes (1969) published an article defending the same view in Science, with the radical title, “Non- Darwinian Evolution,” at which point, “the fat was in the fire” (Crow, 1985b). The neutral theory was one of the most controversial theories in biology in the late twentieth century. This chapter will review the debate over the netural theory subsequent to Kimura.

Roderic Page’s new book, Tangled Trees: Phylogeny, Cospeciation and Coevolution (2003), is a worthwhile read for anyone interested in either methodological issues in systematics, or how organisms shape one another’s selective environments. “Cospeciation,” for the uninitiated, is the concurrent speciation of two or more lineages that are ecologically associated (e.g. host-parasite associations, as well as mutualistic or symbiotic associations). “Coevolution,” in contrast, is the reciprocal adaptation of hosts and parasite taxa. The main focus of Page’s book is thus when, how and why the branching process of host taxa mirrors that of parasite taxa. “Parasite” here is broadly conceived to be anything from a louse to a virus to a retrotransposon, and “host” may be anything from a genome to a whale.

The modern synthesis in evolutionary biology is taken to be that period in which a consensus developed among biologists about the major causes of evolution, a consensus that informed research in evolutionary biology for at least a half century. As such, it is a particularly fruitful period to consider when reflecting on the meaning and role of chance in evolutionary explanation. Biologists of this period make reference to “chance” and loose cognates of “chance,” such as: “random,” “contingent,” “accidental,” “haphazard,” or “stochastic.” Of course, what an author might mean by “chance” in any specific context varies. In the following, we first offer a historiographical note on the synthesis. Second, we introduce five ways in which synthesis authors spoke about chance. We do not take these to be an exhaustive taxonomy of all possible ways in which chance meaningfully figures in explanations in evolutionary biology. These are simply five common uses of the term by biologists at this period. They will serve to organize our summary of the collected references to chance and the analysis and discussion of the following questions: • What did synthesis authors understand by chance? • How did these authors see chance operating in evolution? • Did their appeals to chance increase or decrease over time during the synthesis? That is, was there a “hardening” of the synthesis, as Gould claimed (1983)?

This paper uses a number of examples of diverse types and functions of models in evolutionary biology to argue that the demarcation between theory and practice, or "theory model" and "data model," is often difficult to make. It is shown how both mathematical and laboratory models function as plausibility arguments, existence proofs, and refutations in the investigation of questions about the pattern and process of evolutionary history. I consider the consequences of this for the semantic approach to theories and theory confirmation. The paper attempts to reconcile the insights of both critics and advocates of the semantic approach to theories

Abstract:In this paper, I distinguish four ways in which aspects or features of mental illness may be said to be functional. I contend that discussion of teleological perspectives on mental illness has unfortunately tended to conflate these senses. The latter two senses have played important practical roles both in predicting and explaining patterns of behavior, cognition, and affective response, atnd relatedly, in developing successful interventions. I further argue that functional talk in this context is neither inconsistent with viewing some disorders as dysfunctional in one of several senses, nor inappropriately adaptationist, provided we keep these senses of function distinct, and are precise about which is in play in a given context.

Debates concerning the character, scope, and warrant of abductive inference have been active since Peirce first proposed that there was a third form of inference, distinct from induction and deduction. Abductive reasoning has been dubbed weak, incoherent, and even nonexistent. Part, at least, of the problem of articulating a clear sense of abductive inference is due to difficulty in interpreting Peirce. Part of the fault must lie with his critics, however. While this article will argue that Peirce indeed left a number of puzzles for interpreters, it will also contend that interpreters should be careful to distinguish discussion of the formal and strictly epistemic question of whether and how abduction is a sound form of inference from discussions of the practical goals of abduction, as Peirce understood them. This article will trace a history of critics and defenders of Peirce’s notion of abduction and discuss how Peirce both fueled the confusion and in fact anticipated and responded to several recurring objections.

The object of this paper is to reply to Morrison's ([2000]) claim that while ‘structural unity’ was achieved at the level of the mathematical models of population genetics in the early synthesis, there was explanatory disunity. I argue to the contrary, that the early synthesis effected by the founders of theoretical population genetics was unifying and explanatory both. Defending this requires a reconsideration of Morrison's notion of explanation. In Morrison's view, all and only answers to ‘why’ questions which include the ‘cause or mechanism’ for some phenomenon count as explanatory. In my view, mathematical demonstrations that answer ‘how possibly’ and ‘why necessarily’ questions may also count as explanatory. The authors of the synthesis explained how evolution was possible on a Mendelian system of inheritance, answered skepticism about the sufficiency of selection, and thus explained why and how a Darwinian research program was warranted. While today we take many of these claims as obvious, they required argument, and part of the explanatory work of the formal sciences is providing such arguments. Surely, Fisher and Wright had competing views as to the optimal means of generating adaptation. Nevertheless, they had common opponents and a common unifying and explanatory goal that their mathematical demonstrations served. Introduction: Morrison's challenge Fisher v. Wright revisited The early synthesis Conclusion: unification and explanation reconciled.

In 1966, Richard Levins argued that there are different strategies in model building in population biology. In this paper, I reply to Orzack and Sober’s (1993) critiques of Levins, and argue that his views on modeling strategies apply also in the context of evolutionary genetics. In particular, I argue that there are different ways in which models are used to ask and answer questions about the dynamics of evolutionary change, prospectively and retrospectively, in classical versus molecular evolutionary genetics. Further, I argue that robustness analysis is a tool for, if not confirmation, then something near enough, in this discipline.

November 2009’s announcement of the USPSTF’s recommendations for screening for breast cancer raised a firestorm of objections. Chief among them were that the panel had insufficiently valued patients’ lives or allowed cost considerations to influence recommendations. The publicity about the recommendations, however, often either simplified the actual content of the recommendations or bypassed significant methodological issues, which a philosophical examination of both the science behind screening recommendations and their import reveals. In this article, I discuss two of the leading ethical considerations at issue in screening recommendations: respect for patient autonomy and beneficence and then turn to the most significant methodological issues raised by cancer screening: the potential biases that may infect a trial of screening effectiveness, the problem of base rates in communicating risk, and the trade-offs involved in a judgment of screening effectiveness. These issues reach more broadly, into the use of “evidence-based” medicine generally, and have important implications for informed consent.

Cancer is not one, but many diseases, and each is a product of a variety of causes acting (and interacting) at distinct temporal and spatial scales, or “levels” in the biological hierarchy. In part because of this diversity of cancer types and causes, there has been a diversity of models, hypotheses, and explanations of carcinogenesis. However, there is one model of carcinogenesis that seems to have survived the diversification of cancer types: the multi-stage model of carcinogenesis. This paper examines the history of the multistage theory, and uses the theory as a case study in the limits and goals of unification as a theoretical virtue, comparing and contrasting it with “integrative” research.

One of the major developments in cancer research in recent years has been the construction of models that treat cancer as a cellular population subject to natural selection. We expand on this idea, drawing upon multilevel selection theory. Cancer is best understood in our view from a multilevel perspective, as both a by-product of selection at other levels of organization, and as subject to selection at several levels of organization. Cancer is a by-product in two senses. First, cancer cells co-opt signaling pathways that are otherwise adaptive at the organismic level. Second, cancer is also a by-product of features distinctive to the metazoan lineage: cellular plasticity and modularity. Applying the multilevel perspective in this way permits one to explain transitions in complexity and individuality in cancer progression. Our argument is a reply to Germain’s scepticism towards the explanatory relevance of natural selection for cancer. The extent to which cancer fulfills the conditions for being a paradigmatic Darwinian population depends on the scale of analysis, and the details of the purported selective scenario. Taking a multilevel perspective clarifies some of the complexities surrounding how to best understand the relevance of evolutionary thinking in cancer progression

Natural selection is an extremely powerful process – so powerful, in fact, that it is often tempting to deploy it in explaining phenomena as wide-ranging as the persistence of blue eyes, the origins or persistence of religious belief, or, the history of science. One long-standing debate among both critics and advocates of Darwin’s concerns the scope of Darwinian explanations, and how we are to draw the line. Peter Godfrey-Smith’s Darwinian Populations and Natural Selection is a detailed examination of this question. The book explores the criteria for what may count as a “Darwinian population,” by which Godfrey-Smith means, which collections of entities have the capacity to undergo evolution via natural selection (p. 6). Drawing upon his answer to this question, Godfrey-Smith examines and provides his own solution to the following long-standing debates in philosophy of biology: (a) the twin problems of reproduction and individuation of biological entities, (b) the persistent “gene’s eye view,” (c) the levels and units of selection problem, and (d) the evolution of cultural artifacts and behaviors.

The recent literature in philosophy of biology has drawn attention to the different sorts of explanations proffered in the biological sciences—we have molecular, biomedical, and evolutionary explanations. Do these explanations all have a common structure or relation that they seek to capture? This paper will answer in the negative. I defend a pluralistic and pragmatic approach to explanation. Using examples from classical population genetics, I argue that formal demonstrations, and even strictly “mathematical truths,” may serve as explanatory in different historical contexts.

Mainstream philosophy of science has embraced an “empiricist” approach to scientific method. To be slightly more precise, I venture that most philosophers of science today would endorse the view that experience is the source of most scientific knowledge. The aim of this essay will be to challenge the consensus, by showing how we cannot and should not abandon all elements of the “rationalist” tradition, a tradition often identified with philosophers such as Descartes. There are several elements frequently identified with “rationalist” science (Stump, 2005): questioning of sense experience, the attempt to rethink the “metaphysical” foundations of one’s science, using either thought experiment, or appealing to demonstrative arguments purporting to establish ‘necessary’ truths, often using either mathematics or geometry, and appeal to “virtues” not usually considered “strictly empirical,” such as simplicity. This essay explores the effective deployment of such considerations in the history and current practice of science.

The focus of this chapter will be on the epistemic and normative questions at issue in debates about cancer screening, with a special focus on mammography as a case study. Such questions include: How do we know who needs to be screened? What are the benefits and harms of cancer screening, and what is the quality of evidence for each? How ought we to measure and compare these benefits and harms? What are the sources of uncertainty about our estimates of benefit and harm? Why are such issues so contested? What are the major drivers of dissent and consensus on the data and their interpretation? How, if at all, do values play a role in debates surrounding mammography screening? In sum: In what ways does inductive risk, broadly conceived, 1 come into play in the science behind cancer screening, and mammography screening in particular?

Biological diversity - or ‘biodiversity’ - is the degree of variation of life within an ecosystem. It is a relatively new topic of study but has grown enormously in recent years. Because of its interdisciplinary nature the very concept of biodiversity is the subject of debate amongst philosophers, biologists, geographers and environmentalists. The Routledge Handbook of Philosophy of Biodiversity is an outstanding reference source to the key topics and debates in this exciting subject. Comprising twenty-three chapters by a team of international contributors the _Handbook_ is divided into six parts: Historical and sociological contexts, focusing on the emergence of the term and early attempts to measure biodiversity _What is biodiversity? _How should biodiversity be defined? How can biodiversity include entities at the edge of its boundaries, including microbial diversity and genetically engineered organisms? _Why protect biodiversity? _What can traditional environmental ethics_ _contribute to biodiversity?_ _Topics covered include anthropocentrism, intrinsic value, and ethical controversies surrounding the economics of biodiversity _Measurement and methodology: _including decision-theory and conservation, the use of indicators for biodiversity, and the changing use of genetics in biodiversity conservation _Social contexts and global justice: _including conservation and community conflicts and biodiversity and cultural values _Biodiversity and other environmental values_: How does biodiversity relate to other values like ecological restoration or ecological sustainability? Essential reading for students and researchers in philosophy, environmental science and environmental studies, and conservation management, it will also be extremely useful to those studying biodiversity in subjects such as biology and geography.

Fisher’s ‘fundamental theorem of natural selection’ is notoriously abstract, and, no less notoriously, many take it to be false. In this paper, I explicate the theorem, examine the role that it played in Fisher’s general project for biology, and analyze why it was so very fundamental for Fisher. I defend Ewens (1989) and Lessard (1997) in the view that the theorem is in fact a true theorem if, as Fisher claimed, ‘the terms employed’ are ‘used strictly as defined’ (1930, p. 38). Finally, I explain the role that projects such as Fisher’s play in the progress of scientific inquiry.

In 2015, Tomasetti and Vogelstein published a paper in Science containing the following provocative statement: “… only a third of the variation in cancer risk among tissues is attributable to environmental factors or inherited predispositions. The majority is due to “bad luck,” that is, random mutations arising during DNA replication in normal, noncancerous stem cells.” The paper—and perhaps especially this rather coy reference to “bad luck”—became a flash point for a series of letters and reviews, followed by replies and yet further counterpoints. In this paper, I critically assess Tomasetti and Vogelstein's argument, discuss the meaning of “luck” (or, better: “chance”) in the context of the debate, and use this case study to address larger questions about methodological criteria for causal explanations of population level patterns in biomedicine.

Comprised of essays by top scholars in the field, this volume offers concise overviews of philosophical issues raised by biology. Brings together a team of eminent scholars to explore the philosophical issues raised by biology Addresses traditional and emerging topics, spanning molecular biology and genetics, evolution, developmental biology, immunology, ecology, mind and behaviour, neuroscience, and experimentation Begins with a thorough introduction to the field Goes beyond previous treatments that focused only on evolution to give equal attention to other areas, such as molecular and developmental biology Represents both an authoritative guide to philosophy of biology, and an accessible reference work for anyone seeking to learn about this rapidly-changing field

In this article, we argue, first, that there are very different research projects that fall under the heading of “systems biology of cancer.” While they share some general features, they differ in their aims and theoretical commitments. Second, we argue that some explanations in systems biology of cancer are concerned with properties of signaling networks and how they may play an important causal role in patterns of vulnerability to cancer. Further, some systems biological explanations are compelling illustrations of how “top-down” and “bottom-up” approaches to the same phenomena may be integrated.

There have been two different schools of thought on the evolution of dominance. On the one hand, followers of Wright [Wright S. 1929. Am. Nat. 63: 274–279, Evolution: Selected Papers by Sewall Wright, University of Chicago Press, Chicago; 1934. Am. Nat. 68: 25–53, Evolution: Selected Papers by Sewall Wright, University of Chicago Press, Chicago; Haldane J.B.S. 1930. Am. Nat. 64: 87–90; 1939. J. Genet. 37: 365–374; Kacser H. and Burns J.A. 1981. Genetics 97: 639–666] have defended the view that dominance is a product of non-linearities in gene expression. On the other hand, followers of Fisher [Fisher R.A. 1928a. Am. Nat. 62: 15–126; 1928b. Am. Nat. 62: 571–574; Bürger R. 1983a. Math. Biosci. 67: 125–143; 1983b. J. Math. Biol. 16: 269–280; Wagner G. and Burger R. 1985. J. Theor. Biol. 113: 475–500; Mayo O. and Reinhard B. 1997. Biol. Rev. 72: 97–110] have argued that dominance evolved via selection on modifier genes. Some have called these “physiological” versus “selectionist,” or more recently [Falk R. 2001. Biol. Philos. 16: 285–323], “functional,” versus “structural” explanations of dominance. This paper argues, however, that one need not treat these explanations as exclusive. While one can disagree about the most likely evolutionary explanation of dominance, as Wright and Fisher did, offering a “physiological” or developmental explanation of dominance does not render dominance “epiphenomenal,” nor show that evolutionary considerations are irrelevant to the maintenance of dominance, as some [Kacser H. and Burns J.A. 1981. Genetics 97: 639–666] have argued. Recent work [Gilchrist M.A. and Nijhout H.F. 2001. Genetics 159: 423–432] illustrates how biological explanation is a multi-level task, requiring both a “top-down” approach to understanding how a pattern of inheritance or trait might be maintained in populations, as well as “bottom-up” modeling of the dynamics of gene expression.

Cancer is not one, but many diseases, and each is a product of a variety of causes acting at distinct temporal and spatial scales, or ‘‘levels’’ in the biological hierarchy. In part because of this diversity of cancer types and causes, there has been a diversity of models, hypotheses, and explanations of carcinogenesis. However, there is one model of carcinogenesis that seems to have survived the diversification of cancer types: the multi-stage model of carcinogenesis. This paper examines the history of the multistage theory, and uses the theory as a case study in the limits and goals of unification as a theoretical virtue, comparing and contrasting it with ‘‘integrative’’ research.