Massimo Pigliucci

This paper outlines a critique of the use of the genetic variance–covariance matrix (G), one of the central concepts in the modern study of natural selection and evolution. Specifically, I argue that for both conceptual and empirical reasons, studies of G cannot be used to elucidate so-called constraints on natural selection, nor can they be employed to detect or to measure past selection in natural populations – contrary to what assumed by most practicing biologists. I suggest that the search for a general solution to the difficult problem of identifying causal structures given observed correlation’s has led evolutionary quantitative geneticists to substitute statistical modeling for the more difficult, but much more valuable, job of teasing apart the many possible causes underlying the action of natural selection. Hence, the entire evolutionary quantitative genetics research program may be in need of a fundamental reconsideration of its goals and how they correspond to the array of mathematical and experimental techniques normally employed by its practitioners

Research in ecology and evolutionary biology (evo-eco) often tries to emulate the “hard” sciences such as physics and chemistry, but to many of its practitioners feels more like the “soft” sciences of psychology and sociology. I argue that this schizophrenic attitude is the result of lack of appreciation of the full consequences of the peculiarity of the evo-eco sciences as lying in between a-historical disciplines such as physics and completely historical ones as like paleontology. Furthermore, evo-eco researchers have gotten stuck on mathematically appealing but philosophi- cally simplistic concepts such as null hypotheses and p-values defined according to the frequentist approach in statistics, with the consequence of having been unable to fully embrace the complexity and subtlety of the problems with which ecologists and evolutionary biologists deal with. I review and discuss some literature in ecology, philosophy of science and psychology to show that a more critical methodological attitude can be liberating for the evo-eco scientist and can lead to a more fecund and enjoyable practice of ecology and evolutionary biology. With this aim, I briefly cover concepts such as the method of multiple hypotheses, Bayesian analysis, and strong inference.

Philosophers of science have given up on the quest for a silver bullet to put an end to all pseudoscience, as such a neat formal criterion to separate good science from its contenders has proven elusive. In the literature on critical thinking and in some philosophical quarters, however, this search for silver bullets lives on in the taxonomies of fallacies. The attractive idea is to have a handy list of abstract definitions or argumentation schemes, on the basis of which one can identify bad or invalid types of reasoning, abstracting away from the specific content and dialectical context. Such shortcuts for debunking arguments are tempting, but alas, the promise is hardly if ever fulfilled. Different strands of research on the pragmatics of argumentation, probabilistic reasoning and ecological rationality have shown that almost every known type of fallacy is a close neighbor to sound inferences or acceptable moves in a debate. Nonetheless, the kernel idea of a fallacy as an erroneous type of argument is still retained by most authors. We outline a destructive dilemma we refer to as the Fallacy Fork: on the one hand, if fallacies are construed as demonstrably invalid form of reasoning, then they have very limited applicability in real life. On the other hand, if our definitions of fallacies are sophisticated enough to capture real-life complexities, they can no longer be held up as an effective tool for discriminating good and bad forms of reasoning. As we bring our schematic “fallacies” in touch with reality, we seem to lose grip on normative questions. Even approaches that do not rely on argumentation schemes to identify fallacies fail to escape the Fallacy Fork, and run up against their own version of it.

Mayr’s proximate–ultimate distinction has received renewed interest in recent years. Here we discuss its role in arguments about the relevance of developmental to evolutionary biology. We show that two recent critiques of the proximate–ultimate distinction fail to explain why developmental processes in particular should be of interest to evolutionary biologists. We trace these failures to a common problem: both critiques take the proximate–ultimate distinction to neglect specific causal interactions in nature. We argue that this is implausible, and that the distinction should instead be understood in the context of explanatory abstractions in complete causal models of evolutionary change. Once the debate is reframed in this way, the proximate–ultimate distinction’s role in arguments against the theoretical significance of evo-devo is seen to rely on a generally implicit premise: that the variation produced by development is abundant, small and undirected. We show that a “lean version” of the proximate–ultimate distinction can be maintained even when this isotropy assumption does not hold. Finally, we connect these considerations to biological practice. We show that the investigation of developmental constraints in evolutionary transitions has long relied on a methodology which foregrounds the explanatory role of developmental processes. It is, however, entirely compatible with the lean version of the proximate–ultimate distinction

The scientific status of evolutionary theory seems to be more or less perennially under question. I am not referring here (just) to the silliness of young Earth creation- ism (Pigliucci 2002; Boudry and Braeckman 2010), or even of the barely more intel- lectually sophisticated so-called Intelligent Design theory (Recker 2010; Brigandt this volume), but rather to discussions among scientists and philosophers of science concerning the epistemic status of evolutionary theory (Sober 2010). As we shall see in what follows, this debate has a long history, dating all the way back to Darwin, and it is in great part rooted in the fundamental dichotomy between what French biologist and Nobel laureate Jacques Monod (1971) called chance and necessity—i.e., the inevitable and inextricable interplay of deterministic and stochastic mechanisms operating during the course of evolution.

Ever since the publication of Richard Dawkins' The Selfish Gene, a book for the lay reader that popularized the ideas of influential evolutionary biologists like William Hamilton and George Williams, there has been much discussion of so-called "universal Darwinism". Dawkins' dual aim was to reduce evolutionary phenomena to the level of the gene, while at the same time abstracting the Darwinian process of natural selection of "replicators" and making it into something that would apply beyond the domain of biology.

The debate about the levels of selection has been one of the most controversial both in evolutionary biology and in philosophy of science. Okasha’s book makes the sort of contribution that simply will not be able to be ignored by anyone interested in this field for many years to come. However, my interest here is in highlighting some examples of how Okasha goes about discussing his material to suggest that his book is part of an increasingly interesting trend that sees scientists and philosophers coming together to build a broadened concept of “theory” through a combination of standard mathematical treatments and conceptual analyses. Given the often contentious history of the relationship between philosophy and science, such trend cannot but be welcome.

The theory of evolution, which provides the conceptual framework for all modern research in organismal biology and informs research in molecular bi- ology, has gone through several stages of expansion and refinement. Darwin and Wallace (1858) of course proposed the original idea, centering on the twin concepts of natural selection and common descent. Shortly thereafter, Wallace and August Weismann worked toward the complete elimination of any Lamarckian vestiges from the theory, leaning in particular on Weismann’s (1893) concept of the separation of soma and germ, resulting in what is some- times referred to as “neo-Darwinism”.

Ever since Socrates, philosophers have been in the business of asking ques- tions of the type “What is X?” The point has not always been to actually find out what X is, but rather to explore how we think about X, to bring up to the surface wrong ways of thinking about it, and hopefully in the process to achieve an increasingly better understanding of the matter at hand. In the early part of the twentieth century one of the most ambitious philosophers of sci- ence, Karl Popper, asked that very question in the specific case in which X = science. Popper termed this the “demarcation problem,” the quest for what distinguishes science from nonscience and pseudoscience (and, presumably, also the latter two from each other).

Twenty years have passed since Gould and Lewontin published their critique of ‘the adaptationist program’ – the tendency of some evolutionary biologists to assume, rather than demonstrate, the operation of natural selection. After the ‘Spandrels paper’, evolutionists were more careful about producing just-so stories based on selection, and paid more attention to a panoply of other processes. Then came reactions against the excesses of the anti-adaptationist movement, which ranged from a complete dismissal of Gould and Lewontin’s contribution to a positive call to overcome the problems. We now have an excellent opportunity for finally affirming a more balanced and pluralistic approach to the study of evolutionary biology.

Science and philosophy have a very long history, dating back at least to the 16th and 17th centuries, when the first scientist-philosophers, such as Bacon, Galilei, and Newton, were beginning the process of turning natural philosophy into science. Contemporary relationships between the two fields are still to some extent marked by the distrust that maintains the divide between the so-called “two cultures.” An increasing number of philosophers, however, are making conceptual contributions to sciences ranging from quantum mechanics to evolutionary biology, and a few scientists are conducting research relevant to classically philosophical fields of inquiry, such as consciousness and moral decision-making. This article will introduce readers to the borderlands between science and philosophy, beginning with a brief description of what philosophy of science is about, and including a discussion of how the two disciplines can fruitfully interact not only at the level of scholarship, but also when it comes to controversies surrounding public understanding of science.

Public discussions of science are often marred by two pernicious phenomena: a widespread rejection of scientific findings (e.g., the reality of anthropogenic climate change, the conclusion that vaccines do not cause autism, or the validity of evolutionary theory), coupled with an equally common acceptance of pseudoscientific notions (e.g., homeopathy, psychic readings, telepathy, tall tales about alien abductions, and so forth). The typical reaction by scientists and science educators is to decry the sorry state of science literacy among the general public, and to call for more science education as the answer to both problems. But the empirical evidence concerning the relationship between science literacy, rejection of science and acceptance of pseudoscience is mixed at best. In this chapter I argue that—while certainly important—efforts at increasing public knowledge of science (science education) need to be complemented by attention to common logical fallacies (philosophy), cognitive biases and dissonance (psychology), and the role of ideological commitments (sociology). Even this complex, multi-disciplinary approach to science education will likely only yield measurable results in the very long term. Meanwhile science remains, as Carl Sagan famously put it, a candle in the dark, delicate and in need of much nurturing.

What sets the practice of rigorously tested, sound science apart from pseudoscience? In this volume, the contributors seek to answer this question, known to philosophers of science as “the demarcation problem.” This issue has a long history in philosophy, stretching as far back as the early twentieth century and the work of Karl Popper. But by the late 1980s, scholars in the field began to treat the demarcation problem as impossible to solve and futile to ponder. However, the essays that Massimo Pigliucci and Maarten Boudry have assembled in this volume make a rousing case for the unequivocal importance of reflecting on the separation between pseudoscience and sound science.

The Modern Synthesis (MS) is the current paradigm in evolutionary biology. It was actually built by expanding on the conceptual foundations laid out by its predecessors, Darwinism and neo-Darwinism. For sometime now there has been talk of a new Extended Evolutionary Synthesis (EES), and this article begins to outline why we may need such an extension, and how it may come about. As philosopher Karl Popper has noticed, the current evolutionary theory is a theory of genes, and we still lack a theory of forms. The field began, in fact, as a theory of forms in Darwin’s days, and the major goal that an EES will aim for is a unification of our theories of genes and of forms. This may be achieved through an organic grafting of novel concepts onto the foundational structure of the MS, particularly evolvability, phenotypic plasticity, epigenetic inheritance, complexity theory, and the theory of evolution in highly dimensional adaptive landscapes.

Evolutionary theory is undergoing an intense period of discussion and reevaluation. This, contrary to the misleading claims of creationists and other pseudoscientists, is no harbinger of a crisis but rather the opposite: the field is expanding dramatically in terms of both empirical discoveries and new ideas. In this essay I briefly trace the conceptual history of evolutionary theory from Darwinism to neo-Darwinism, and from the Modern Synthesis to what I refer to as the Extended Synthesis, a more inclusive conceptual framework containing among others evo–devo, an expanded theory of heredity, elements of complexity theory, ideas about evolvability, and a reevaluation of levels of selection. I argue that evolutionary biology has never seen a paradigm shift, in the philosophical sense of the term, except when it moved from natural theology to empirical science in the middle of the 19th century. The Extended Synthesis, accordingly, is an expansion of the Modern Synthesis of the 1930s and 1940s, and one that—like its predecessor—will probably take decades to complete.

What makes beliefs thrive? In this paper, we model the dissemination of bona fide science versus pseudoscience, making use of Dan Sperber's epidemiological model of representations. Drawing on cognitive research on the roots of irrational beliefs and the institutional arrangement of science, we explain the dissemination of beliefs in terms of their salience to human cognition and their ability to adapt to specific cultural ecologies. By contrasting the cultural development of science and pseudoscience along a number of dimensions, we gain a better understanding of their underlying epistemic differences. Pseudoscience can achieve widespread acceptance by tapping into evolved cognitive mechanisms, thus sacrificing intellectual integrity for intuitive appeal. Science, by contrast, defies those deeply held intuitions precisely because it is institutionally arranged to track objective patterns in the world, and the world does not care much about our intuitions. In light of these differences, we discuss the degree of openness or resilience to conceptual change (evidence and reason), and the divergent ways in which science and pseudoscience can achieve cultural “success”.

Evolutionary biology is a field currently animated by much discussion concerning its conceptual foundations. On the one hand, we have supporters of a classical view of evolutionary theory, whose backbone is provided by population genetics and the so-called Modern Synthesis (MS). On the other hand, a number of researchers are calling for an Extended Synthe- sis (ES) that takes seriously both the limitations of the MS (such as its inability to incorporate developmental biology) and recent empirical and theoretical research on issues such as evolvability, modularity, and self-organization. In this article, I engage in an in-depth commentary of an influential paper by population geneticist Michael Lynch, which I take to be the best defense of the MS-population genetics position published so far. I show why I think that Lynch’s arguments are wanting and propose a modification of evolutionary theory that retains but greatly expands on population genetics.

Discussions about the biological bases (or lack thereof) of the concept of race in the human species seem to be never ending. One of the latest rounds is represented by a paper by Neven Sesardic, which attempts to build a strong scientific case for the existence of human races, based on genetic, morphometric and behavioral characteristics, as well as on a thorough critique of opposing positions. In this paper I show that Sesardic’s critique falls far short of the goal, and that his positive case is exceedingly thin. I do this through a combination of analysis of the actual scientific findings invoked by Sesardic and of some philo- sophical unpacking of his conceptual analysis, drawing on a dual professional background as an evolu- tionary biologist and a philosopher of science.

Phenotypic plasticity integrates the insights of ecological genetics, developmental biology, and evolutionary theory. Plasticity research asks foundational questions about how living organisms are capable of variation in their genetic makeup and in their responses to environmental factors. For instance, how do novel adaptive phenotypes originate? How do organisms detect and respond to stressful environments? What is the balance between genetic or natural constraints (such as gravity) and natural selection? The author begins by defining phenotypic plasticity and detailing its history, including important experiments and methods of statistical and graphical analysis. He then provides extended examples of the molecular basis of plasticity, the plasticity of development, the ecology of plastic responses, and the role of costs and constraints in the evolution of plasticity. A brief epilogue looks at how plasticity studies shed light on the nature/nurture debate in the popular media.

The term “scientism” is used in a variety of ways with both negative and positive connotations. I suggest that some of these uses are inappropriate, as they aim simply at dismissing without argument an approach that a particular author does not like. However, there are legitimate negative uses of the term, which I explore by way of an analogy with the term “pseudoscience.” I discuss these issues by way of a recent specific example provided by a controversy in the field of bioethics concerning the value, or lack thereof, of homeopathy. I then frame the debate about scientism within the broader context of C.P. Snow’s famous essay on the “two cultures.”

In a now classic paper published in 1991, Alberch introduced the concept of genotype–phenotype (G!P) mapping to provide a framework for a more sophisticated discussion of the integration between genetics and developmental biology that was then available. The advent of evo-devo first and of the genomic era later would seem to have superseded talk of transitions in phenotypic space and the like, central to Alberch’s approach. On the contrary, this paper shows that recent empirical and theoretical advances have only sharpened the need for a different conceptual treat- ment of how phenotypes are produced. Old-fashioned metaphors like genetic blueprint and genetic programme are not only woefully inadequate but positively misleading about the nature of G!P, and are being replaced by an algorithmic approach emerging from the study of a variety of actual G!P maps. These include RNA folding, protein function and the study of evolvable soft- ware. Some generalities are emerging from these disparate fields of analysis, and I suggest that the concept of ‘developmental encoding’ (as opposed to the classical one of genetic encoding) provides a promising computational–theoretical underpinning to coherently integrate ideas on evolvability, modularity and robustness and foster a fruitful framing of the G!P mapping problem.

During the last two decades the role of quantitative genetics in evolutionary theory has expanded considerably. Quantitative genetic-based models addressing long term phenotypic evolution, evolution in multiple environments (phenotypic plasticity) and evolution of ontogenies (developmental trajectories) have been proposed. Yet, the mathematical foundations of quantitative genetics were laid with a very different set of problems in mind (mostly the prediction of short term responses to artificial selection), and at a time in which any details of the genetic machinery were virtually unknown. In this paper we discuss what a model is in population biology, and what kind of model we need in order to address the complexities of phenotypic evolution. We review the assumptions of quantitative genetics and its most recent accomplishments, together with the limitations that such assumptions impose on the modelling of some aspects of phenotypic evolution. We also discuss three alternative appr oaches to the theoretical description of evolutionary trajectories (nonlinear dynamics, complexity theory and optimization theory), and their respective advantages and limitations. We conclude by calling for a new theoretical synthesis, including quantitative genetics and not necessarily limited to the other approaches here discussed.

Science is about conceptualizing the natural world in a way that can be understood by human beings while at the same time reflecting as much as possible what we can empirically infer about how the world actually is. Among the crucial tools that allow scientists to formulate hypotheses and to contribute to a progressive understanding of nature are the use of imagery and metaphors, on the one hand, and the ability to assume certain starting points on which to build new avenues of inquiry on the other hand. The premise of this work is that, in the words of philosopher of science Daniel Dennett, "There is no such thing as philosophy-free science; there is only science whose philosophical baggage is taken on board without examination." The purpose here is precisely to examine some of this philosophical baggage, and to see where such analysis may lead us. Obviously, it is not possible for a single project to take on science as a whole, or even an entire discipline such as physics, or ecology. Therefore, the core of this work is constituted by a series of eight case studies drawn from the field of evolutionary biology, with which I am particularly familiar as a practicing biologist. The hope is that combining expertise in both philosophy and science in one person, the resulting insights might be useful for the practicing scientist as well as because of their value as philosophical inquires. The dissertation is a combination of conceptual analysis and science criticism applied to specific questions in organismal biology, largely of an evolutionary nature, with the eight case studies grouped into three broad categories: Unexamined Baggage, Bad Habits, and Good and bad metaphors

What is a race? Ernst Mayr (1904–2005) distinguishes between species in which biological change is continuous in space, and species in which groups of populations with different character combinations are separated by borders. In the latter species, the entities separated by borders are geographic races or subspecies. Many anthropology textbooks describe human races as discrete (or nearly discrete) clusters of individuals, geographically localized, each of which shares a set of ancestors, and hence can be distinguished from other races by their common gene pool or by different alleles fixed in each.

Phenotypic Evolution explicitly recognizes organisms as complex genetic-epigenetic systems developing in response to changing internal and external environments. As a key to a better understanding of how phenotypes evolve, the authors have developed a framework that centers on the concept of the Developmental Reaction Norm. This encompasses their views: (1) that organisms are better considered as integrated units than as disconnected parts (allometry and phenotypic integration); (2) that an understanding of ontogeny is vital for evaluating evolution of adult forms (ontogenetic trajectories, epigenetics, and constraints); and (3) that environmental heterogeneity is ubiquitous and must be acknowledged for its pervasive role in phenotypic expression.