Massimo Pigliucci

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.

Sewall Wright introduced the metaphor of evolution on “adaptive landscapes” in a pair of papers published in 1931 and 1932. The metaphor has been one of the most influential in modern evolutionary biology, although recent theoretical advancements show that it is deeply flawed and may have actually created research questions that are not, in fact, fecund. In this paper I examine in detail what Wright actually said in the 1932 paper, as well as what he thought of the matter at the very end of his career, in 1988. While the metaphor is flawed, some of the problems which Wright was attempting to address are still with us today, and are in the process of being reformulated as part of a forthcoming Extended Evolutionary Synthesis.

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.

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.

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.

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.

Is integrative biology a good idea, or even possible? There has been much interest lately in the unifica- tion of biology and the integration of traditionally separate disciplines such as molecular and develop- mental biology on one hand, and ecology and evolutionary biology on the other. In this paper I ask if and under what circumstances such integration of efforts actually makes sense. I develop by example an analogy with Aristotle’s famous four “causes” that one can investigate concerning any object or phenomenon: material (what something is made of), formal (what distinguishes that particular object from others), efficient (how was the object made) and final (why was the object made). The example is provided by ongoing research on different aspects of flowering time in the model system Arabidop- sis, a small weed belonging to the mustard family. I show that understanding how flowering time is controlled is an epistemologically different sort of question from why and how it evolved, and that the two research agendas can be pursued largely independently of each other. Toward the end, I propose that the real goal of integrative biology is to understand the boundary layers between levels of biologi- cal analysis, something to which modern philosophy of science can contribute significantly.

We attempt to improve the understanding of the notion of agene being `for a phenotypic trait or traits. Considering theimplicit functional ascription of one thing being `for another,we submit a more restrictive version of `gene for talk.Accordingly, genes are only to be thought of as being forphenotypic traits when good evidence is available that thepresence or prevalence of the gene in a population is the resultof natural selection on that particular trait, and that theassociation between that trait and the gene in question isdemonstrably causal. It is therefore necessary to gatherstatistical, biochemical, historical, as well as ecologicalinformation before properly claiming that a gene is for aphenotypic trait. Instead of hampering practical use of the `genefor talk, our approach aims at stimulating much needed researchinto the functional ecology and comparative evolutionary biologyof gene action.

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.

Philosophical inquiries into morality are as old as philosophy, but it may turn out that morality itself is much, much older than that. At least, that is the main thesis of prima- tologist Frans De Waal, who in this short book based on his Tanner Lectures at Princeton, elaborates on what biologists have been hinting at since Darwin’s (1871) book The Descent of Man and Hamilton’s (1963) studies on the evolution of altruism: morality is yet another allegedly human characteristic that turns out to be built over evolutionary time by natural

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.

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 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”.

In lieu of an abstract, here is a brief excerpt of the content:Why Gaia?Massimo Pigliucci (bio)The Gaia Hypothesis: Science on a Pagan Planet, Michael Ruse, Chicago: University of Chicago Press, 2013. 272 pages.“The Gaia Hypothesis: Science on a Pagan Planet tells a story that comes out of the 1960s, a story that reflects all of the beliefs and enthusiasms and tensions of that decade.” So begins Michael Ruse’s fascinating, if at times puzzling, exploration of James Lovelock’s famous idea that our planet is, in a serious scientific sense, a living organism with a tendency of taking care of (her)self. But why tell this particular story, especially considering that Gaia hardly makes an appearance in today’s scientific or philosophical publications, and doesn’t even seem quite that popular with the lay public as it used to be? Because, as Ruse tells us near the end of the book, at the onset of chapter seven: “the paradox that set us on our path [is] why the scientific community reacted so negatively to the Gaia hypothesis, whereas the public reaction was so positive.”As it turns out, there is a good answer to that conundrum, one that Ruse himself lays out clearly in the last chapter of the book, and which makes the reader wonder why this should count a paradox at all. But we will get there in due time. First, the basics: the so-called Gaia hypothesis is the brainchild of iconoclastic inventor-turned-independent-scientist James Lovelock, who later got significant help in elaborating (and promoting) his ideas from another iconoclast, biologist Lynn Margulis. By the time you get to the end of Ruse’s engaging book, however, you won’t have gained a particularly good understanding of what the hypothesis actually consists. But that’s not Ruse’s fault, it is Lovelock’s (and Margulis’). At times it sounds like the entirely uncontroversial claim that the Earth’s [End Page 117] biosphere is a somewhat homeostatic system—i.e., a biophysical system that is resistant to major changes, at the least within a certain range (the planet’s atmosphere, after all, did change dramatically early on, increasing its oxygen content as a result of the evolution of photosynthetic organisms—the anaerobic life forms that had up to that point been dominant did not appreciate the novelty). At other times the claim is downright preposterous: the Earth literally is a living organism (according to Lovelock) (Chapter 7),1 a finding that allegedly puts in question the whole Darwinian view of biological evolution (according to Margulis) (Chapter 7), a position that can only be characterized as nonsense on stilts. At yet other moments, Gaia is presented as just a metaphor to help us wrap our minds around the complexities (and homeostatic properties) of the world’s ecosystems (Chapter 8). It is this never-ending oscillation between the trivial and the bizarre that has led the majority of scientists to write off Gaia, to the chagrin of Lovelock, Margulis, and a large number of New Age tree huggers from the 1960s.Indeed, the scientific reaction to Gaia was swift and ranging from the condescending to the unforgiving. Evolutionary biologist John Maynard Smith—never one to mince words—called it “an evil religion” (Chapter 2). Another evolutionary biologist, Stephen Jay Gould (whose own disagreements with Maynard Smith became legendary) said that “Gaia strikes me as a metaphor, not a mechanism” (Chapter 2). Ecologist Robert May, who eventually became president of the Royal Society, called Lovelock “a holy fool” (Chapter 2). The highly respected theoretical biologist W.D. Hamilton said that in order for the hypothesis to work, it would require “treaties between Neptune and Zeus, a Gaian Interpol, conventions about bills of lading for chemical transport by air and water, and so on” (Chapter 7). Finally, Richard Dawkins accused Lovelock of committing the fallacy of “the BBC theorem,” assuming (or wishfully thinking) that the world is a harmonious place, just like in naive BBC nature documentaries (Chapter 2).You get the gist: pretty much from the beginning, and with very few exceptions, the scientific establishment rejected Gaia on the grounds that it is not a scientific hypothesis at all, and that its main tenets actually go against pretty...

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.

The scientific study of living organisms is permeated by machine and design metaphors. Genes are thought of as the ‘‘blueprint’’ of an organism, organisms are ‘‘reverse engineered’’ to discover their functionality, and living cells are compared to biochemical factories, complete with assembly lines, transport systems, messenger circuits, etc. Although the notion of design is indispensable to think about adaptations, and engineering analogies have considerable heuristic value (e.g., optimality assumptions), we argue they are limited in several important respects. In particular, the analogy with human-made machines falters when we move down to the level of molecular biology and genetics. Living organisms are far more messy and less transparent than human-made machines. Notoriously, evolution is an opportunistic tinkerer, blindly stumbling on ‘‘designs’’ that no sensible engineer would come up with. Despite impressive technological innovation, the prospect of artificially designing new life forms from scratch has proven more difficult than the superficial analogy with ‘‘programming’’ the right ‘‘software’’ would suggest. The idea of applying straightforward engineering approaches to living systems and their genomes— isolating functional components, designing new parts from scratch, recombining and assembling them into novel life forms—pushes the analogy with human artifacts beyond its limits. In the absence of a one-to-one correspondence between genotype and phenotype, there is no straightforward way to implement novel biological functions and design new life forms. Both the developmental complexity of gene expression and the multifarious interactions of genes and environments are serious obstacles for ‘‘engineering’’ a particular phenotype. The problem of reverse-engineering a desired phenotype to its genetic ‘‘instructions’’ is probably intractable for any but the most simple phenotypes. Recent developments in the field of bio-engineering and synthetic biology reflect these limitations. Instead of genetically engineering a desired trait from scratch, as the machine/engineering metaphor promises, researchers are making greater strides by co-opting natural selection to ‘‘search’’ for a suitable genotype, or by borrowing and recombining genetic material from extant life forms.

Recent debates between proponents of the modern evolutionary synthesis (the standard model in evolutionary biology) and those of a possible extended synthesis are a good example of the fascinating tangle among empirical, theoretical, and conceptual or philosophical matters that is the practice of evolutionary biology. In this essay, we briefly discuss two case studies from this debate, highlighting the relevance of philosophical thinking to evolutionary biologists in the hope of spurring further constructive cross-pollination between the two fields.

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.

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.

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.