Massimo Pigliucci

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.

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 The advent of evo-devo first and of the genomic era later would seem to have superseded talk of transitions in phenotypic space and the like, central to Alberch’s approach.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.

The idea of phenotypic novelty appears throughout the evolutionary literature. Novelties have been defined so broadly as to make the term meaningless and so narrowly as to apply only to a limited number of spectacular structures. Here I examine some of the available definitions of phenotypic novelty and argue that the modern synthesis is ill equipped at explaining novelties. I then discuss three frameworks that may help biologists get a better insight of how novelties arise during evolution but warn that these frameworks should be considered in addition to, and not as potential substitutes of, the modern synthesis. †To contact the author, please write to: Departments of Ecology and Evolution and Philosophy, Stony Brook University, Stony Brook, NY 11794; e‐mail: [email protected].

Stoicism is an ancient Greco-Roman practical philosophy focused on the ethics of everyday living. It is a eudaemonistic (i.e., emphasizing one’s flourishing) approach to life, as well as a type of virtue ethics (i.e., concerned with the practice of virtues as central to one’s existence). This paper summarizes the basic tenets of Stoicism and discusses how it tackles the issues of death and suicide. It presents a number of exercises that modern Stoics practice in order to prepare for death (one’s own, or those of relatives and friends). It argues that modern Stoicism is a viable personal philosophy.

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.

Are science and religion compatible when it comes to understanding cosmology (the origin of the universe), biology (the origin of life and of the human species), ethics, and the human mind (minds, brains, souls, and free will)? Do science and religion occupy non-overlapping magisteria? Is Intelligent Design a scientific theory? How do the various faith traditions view the relationship between science and religion? What, if any, are the limits of scientific explanation? What are the most important open questions, problems, or challenges confronting the relationship between science and religion, and what are the prospects for progress? These and other questions are explored in Science and Religion: 5 Questions--a collection of thirty-three interviews based on 5 questions presented to some of the world's most influential and prominent philosophers, scientists, theologians, apologists, and atheists. Contributions by Simon Blackburn, Susan Blackmore, Sean Carroll, William Lane Craig, William Dembski, Daniel C. Dennett, George F.R. Ellis, Owen Flanagan, Owen Gingerich, Rebecca Newberger Goldstein, John F. Haught, Muzaffar Iqbal, Lawrence Krauss, Colin McGinn, Alister McGrath, Mary Midgley, Seyyed Hossein Nasr, Timothy O'Connor, Massimo Pigliucci, John Polkinghorne, James Randi, Alex Rosenberg, Michael Ruse, Robert John Russell, John Searle, Michael Shermer, Victor J. Stenger, Robert Thurman, Michael Tooley, Charles Townes, Peter van Inwagen, Keith Ward, Rabbi David Wolpe.

The “demarcation problem,” the issue of how to separate science from pseu- doscience, has been around since fall 1919—at least according to Karl Pop- per’s (1957) recollection of when he first started thinking about it. In Popper’s mind, the demarcation problem was intimately linked with one of the most vexing issues in philosophy of science, David Hume’s problem of induction (Vickers 2010) and, in particular, Hume’s contention that induction cannot be logically justified by appealing to the fact that “it works,” as that in itself is an inductive argument, thereby potentially plunging the philosopher straight into the abyss of a viciously circular argument.

The concept of burden of proof is used in a wide range of discourses, from philosophy to law, science, skepticism, and even in everyday reasoning. This paper provides an analysis of the proper deployment of burden of proof, focusing in particular on skeptical discussions of pseudoscience and the paranormal, where burden of proof assignments are most poignant and relatively clear-cut. We argue that burden of proof is often misapplied or used as a mere rhetorical gambit, with little appreciation of the underlying principles. The paper elaborates on an important distinction between evidential and prudential varieties of burdens of proof, which is cashed out in terms of Bayesian probabilities and error management theory. Finally, we explore the relationship between burden of proof and several (alleged) informal logical fallacies. This allows us to get a firmer grip on the concept and its applications in different domains, and also to clear up some confusions with regard to when exactly some fallacies (ad hominem, ad ignorantiam, and petitio principii) may or may not occur

‘‘Theoretical biology’’ is a surprisingly heter- ogeneous field, partly because it encompasses ‘‘doing the- ory’’ across disciplines as diverse as molecular biology, systematics, ecology, and evolutionary biology. Moreover, it is done in a stunning variety of different ways, using anything from formal analytical models to computer sim- ulations, from graphic representations to verbal arguments. In this essay I survey a number of aspects of what it means to do theoretical biology, and how they compare with the allegedly much more restricted sense of theory in the physical sciences. I also tackle a recent trend toward the presentation of all-encompassing theories in the biological sciences, from general theories of ecology to a recent attempt to provide a conceptual framework for the entire set of biological disciplines. Finally, I discuss the roles played by philosophers of science in criticizing and shap- ing biological theorizing.

In the six decades since the publication of Julian Huxley's Evolution: The Modern Synthesis, spectacular empirical advances in the biological sciences have been accompanied by equally significant developments within the core theoretical framework of the discipline. As a result, evolutionary theory today includes concepts and even entire new fields that were not part of the foundational structure of the Modern Synthesis. In this volume, sixteen leading evolutionary biologists and philosophers of science survey the conceptual changes that have emerged since Huxley's landmark publication, not only in such traditional domains of evolutionary biology as quantitative genetics and paleontology but also in such new fields of research as genomics and EvoDevo. Most of the contributors to Evolution—The Extended Synthesis accept many of the tenets of the classical framework but want to relax some of its assumptions and introduce significant conceptual augmentations of the basic Modern Synthesis structure—just as the architects of the Modern Synthesis themselves expanded and modulated previous versions of Darwinism. This continuing revision of a theoretical edifice the foundations of which were laid in the middle of the nineteenth century—the reexamination of old ideas, proposals of new ones, and the synthesis of the most suitable—shows us how science works, and how scientists have painstakingly built a solid set of explanations for what Darwin called the "grandeur" of life.

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”.

Ever since Darwin a great deal of the conceptual history of biology may be read as a struggle between two philosophical positions: reductionism and holism. On the one hand, we have the reductionist claim that evolution has to be understood in terms of changes at the fundamental causal level of the gene. As Richard Dawkins famously put it, organisms are just ‘lumbering robots’ in the service of their genetic masters. On the other hand, there is a long holistic tradition that focuses on the complexity of developmental systems, on the non-linearity of gene– environment interactions, and on multi-level selective processes to argue that the full story of biology is a bit more complicated than that. Reductionism can marshal on its behalf the spectacular successes of genetics and molecular biology throughout the 20th and 21st centuries. Holism has built on the development of entirely new disciplines and conceptual frameworks over the past few decades, including evo-devo and phenotypic plasticity. Yet, a number of biologists are still actively looking for a way out of the reductionism–holism counterposition, often mentioning the word ‘emergence’ as a way to deal with the conundrum. This paper briefly examines the philosophical history of the concept of emergence, distinguishes between epistemic and ontological accounts of it, and comments on conceptions of emergence that can actually be useful for practising evolutionary biologists.

Genes are often described by biologists using metaphors derived from computa- tional science: they are thought of as carriers of information, as being the equivalent of ‘‘blueprints’’ for the construction of organisms. Likewise, cells are often characterized as ‘‘factories’’ and organisms themselves become analogous to machines. Accordingly, when the human genome project was initially announced, the promise was that we would soon know how a human being is made, just as we know how to make airplanes and buildings. Impor- tantly, modern proponents of Intelligent Design, the latest version of creationism, have exploited biologists’ use of the language of information and blueprints to make their spurious case, based on pseudoscientific concepts such as ‘‘irreducible complexity’’ and on flawed analogies between living cells and mechanical factories. However, the living organ- ism = machine analogy was criticized already by David Hume in his Dialogues Concerning Natural Religion. In line with Hume’s criticism, over the past several years a more nuanced and accurate understanding of what genes are and how they operate has emerged, ironically in part from the work of computational scientists who take biology, and in particular developmental biology, more seriously than some biologists seem to do. In this article we connect Hume’s original criticism of the living organism = machine analogy with the modern ID movement, and illustrate how the use of misleading and outdated metaphors in science can play into the hands of pseudoscientists. Thus, we argue that dropping the blueprint and similar metaphors will improve both the science of biology and its understanding by the general public.

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.

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.

Dorothy Rowe's book amounts to a spectacularly missed chance to make a significant contribution to the very important questions the author set out to address. The book promises to provide an answer to "why our beliefs about the nature of death and the purpose of life dominate our lives," but ends up being a bizarre hodgepodge of self-help psychology, uninformative case studies, and a large number of disconnected personal observations -- the whole thing peppered here and there with philosophical and even political considerations.

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.

In recent years, biologists have increasingly been asking whether the ability to evolve — the evolvability — of biological systems, itself evolves, and whether this phenomenon is the result of natural selection or a by-product of other evolutionary processes. The concept of evolvability, and the increasing theoretical and empirical literature that refers to it, may constitute one of several pillars on which an extended evolutionary synthesis will take shape during the next few years, although much work remains to be done on how evolvability comes about.

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

How micro- and macroevolutionary evolutionary processes produce phenotypic change is without question one of the most intriguing and perplexing issues facing evolutionary biologists. We believe that roadblocks to progress lie A) in the underestimation of the role of the environment, and in particular, that of the interaction of genotypes with environmental factors, and B) in the continuing lack of incorporation of development into the evolutionary synthesis. We propose the integration of genetic, environmental and developmental perspectives on the evolution of the phenotype in the form of the concept of the developmental reaction norm (DRN) The DRN represents the set of multivariate ontogenies that can be produced by a single genotype when it is exposed to environmental variation. It encompasses: 1) the processes that alter the phenotype throughout the ontogenetic trajectory, 2) the recognition that different aspects of the phenotype are (and must be) correlated and 3) the ability of a genotype to produce phenotypes in different environments. This perspective necessitates the explicit study of character expression during development, the evaluation of associations between pairs or groups of characters (e.g., multivariate allometries), and the exploration of reaction norms and phenotypic plasticity. We explicitly extend the concept of the DRN to encompass adjustments made in response to changes in the internal environment as well. Thus, ‘typical’ developmental sequences (e.g., cell fate determination) and plastic responses are simply manifestations of different scales of ‘environmental’ effects along a continuum. We present: (1) a brief conceptual review of three fundamental aspects of the generation and evolution of phenotypes: the changes in the trajectories describing growth and differentiation (ontogeny), the multivariate relationships among characters (allometry), and the effect of the environment (plasticity); (2) a discussion of how these components are merged in the concept of the developmental reaction norm; and (3) a reaction norm perspective of major determinants of phenotypes: epigenesis, selection and constraint.

Why do irrational beliefs adopt the trappings of science, to become what is known as “pseudoscience”? Here, we develop and extend an epidemiological framework to map the factors that explain the form and the popularity of irrational beliefs in scientific garb. These factors include the exploitation of epistemic vigilance, the misunderstanding of the authority of science, the use of the honorific title of “science” as an explicit argument for belief, and the phenomenon of epistemic negligence. We conclude by integrating the various factors in an epidemiological framework and thus provide a comprehensive cultural evolutionary account of science mimicry.

If evolutionary biologist Massimo Pigliucci didn't exist, it would be necessary to invent him. His Tales of the Rational defines an intellectual space as far removed as hardcore religious fundamentalism from mainstream thinking--but it may be coming closer as scientists and skeptics launch more aggressive attacks on pseudoscience and fuzzy thinking. Pigliucci, a rising star on the evolution-creationism debate circuit, pulls out all the stops in his work, not content merely to defend science against its detractors, but eagerly undermining belief in religion and the existence of any gods at all. Using writing that is strong if rarely eloquent, he defines his terms precisely, makes short work of creationists William Lane Craig and Duane Gish, challenges religious preconceptions, and even ventures to hose down the flames of pseudoscience spouting from chaos theory. Readers with any sympathy for spirituality will run face-first into statements like "I do not see what science has to gain from being reconciled with a system of superstitious beliefs that stands for the exact opposite of free inquiry."

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.