Fitness is a central but notoriously vexing concept in evolutionary biology. The propensity interpretation of fitness is often regarded as the least problematic account for fitness. It ties an individual's fitness to a probabilistic capacity to produce offspring. Fitness has a clear causal role in evolutionary dynamics under this account. Nevertheless, the propensity interpretation faces its share of problems. We discuss three of these. We first show that a single scalar value is an incomplete summary of a propensity. Second, we (...) argue that the widespread method of “abstracting away” environmental idiosyncrasies by averaging over reproductive output in different environments is not a valid approach when environmental changes are irreversible. Third, we point out that expanding the range of applicability for fitness measures by averaging over more environments or longer time scales (so as to ensure environmental reversibility) reduces one's ability to distinguish selectively relevant differences among individuals because of mutation and eco‐evolutionary feedbacks. This series of problems leads us to conclude that a general value of fitness that is both explanatory and predictive cannot be attained. We advocate for the use of propensity‐compatible methods, such as adaptive dynamics, which can accommodate these difficulties. (shrink)

In this dissertation, I present a novel account of the components that have a peculiar epistemic role in our scientific inquiries, since they contribute to establishing a form of coordination. The issue of coordination is a classic epistemic problem concerning how we justify our use of abstract conceptual tools to represent concrete phenomena. For instance, how could we get to represent universal gravitation as a mathematical formula or temperature by means of a numerical scale? This problem is particularly pressing when (...) justification for using these abstract tools comes, in part or entirely, from knowledge which is not independent from them, thus leading to threats of circularity. Achieving coordination between some abstract conceptual tools and the concrete phenomena that they are supposed to represent is usually a complex process, which involves several epistemic components. Some of these components eventually provide stable conditions for applying those abstract representations to concrete phenomena. It is in this sense of providing certain conditions of applicability that different philosophical traditions, as well as some contemporary reappraisals, view these components as constitutive or a priori. In this work, I present a new gradualist, contextualist, and relational approach to understand these constitutive components of scientific inquiry. It is gradualist inasmuch as the degree to which some component is constitutive depends on three quantifiable features: quasi-axiomaticity, generative potential, and empirical shielding. Since the quantification of these three features impinges on the history and practice of using these components in a scientific context, my approach is a contextualist one. Finally, my approach is relational in a double sense: first, it identifies ordinal relationships among epistemic components with respect to their constitutive character; second, these relationships are relative to a scientific framework of inquiry. After introducing my account and a classic example of constitutively a priori principles, i.e., Friedman’s (2001) analysis of Newtonian mechanics, I turn to my own case studies to demonstrate the advantages of my approach. Firstly, I discuss Okasha’s (2018) view of endogenization as a pervasive theoretical strategy in evolutionary biology and suggest that the constitutive character of the core Darwinian principles progressively increases with endogenization. Secondly, I apply a conceptual distinction between two varieties or scopes of coordination – general coordination and coordination in measurement – to Ohm’s work on electrical conductivity. This distinction allows me to pinpoint to what extent components along different dimensions (e.g., instrumentation, measurement, theorising, etc.) were constitutive of the forms of coordination which Ohm relied on. Thirdly, I discuss the epistemic function of the Hardy-Weinberg principle in the history and practice of population genetics. I assess this principle in terms of my account and identify approximation and stability as two components that are highly constitutive, in that they contribute to justifying its use in population genetics. Finally, applying my account to these case studies enables me to identify at least three qualitatively different types of constitutive components: domain-specific theoretical principles, material components, and domain-independent assumptions underlying reasoning abilities. In the light of my results, I draw some general conclusions on epistemic justification and scientific knowledge. (shrink)

This review essay reflects on recent discussions in evolutionary biology and philosophy of science on the central causes of evolution and the structure of causal explanations in evolutionary theory. In this debate, it has been argued that our view of evolutionary causation should be rethought by including more seriously developmental causes and causes of the individual acting organism. I use Tobias Uller’s and Kevin Laland’s volume Evolutionary Causation as well as recent reviews of it as a starting point to reflect (...) on the causal role of agency, individuality, and the environment in evolution. In addition, I critically discuss classical philosophical frameworks of theory change used in this debate to understand changing views of evolutionary causation. (shrink)

Michael Scriven’s (1959) example of identical twins (who are said to be equal in fitness but unequal in their reproductive success) has been used by many philosophers of biology to discuss how fitness should be defined, how selection should be distinguished from drift, and how the environment in which a selection process occurs should be conceptualized. Here it is argued that evolutionary theory has no commitment, one way or the other, as to whether the twins are equally fit. This is (...) because the theory of natural selection is fundamentally about the fitnesses of traits, not the fitnesses of token individuals. A plausible philosophical thesis about supervenience entails that the twins are equally fit if they live in identical environments, but evolutionary biology is not committed to the thesis that the twins live in identical environments. Evolutionary theory is right to focus on traits, rather than on token individuals, because the fitnesses of token organisms (as opposed to their actual survivorship and degree of reproductive success) are almost always unknowable. This point has ramifications for the question of how Darwin’s theory of evolution and R. A. Fisher’s are conceptually different. (shrink)

There are three related criteria that a concept of fitness should be able to meet: it should render the principle of natural selection non-tautologous and it should be explanatory and predictive. I argue that for fitness to be able to fulfill these criteria, it cannot be a property that changes over the course of an individual's life. Rather, I introduce a fitness concept--Block Fitness--and argue that an individual's genes and environment fix its fitness in such a way that each individual's (...) fitness has a fixed value over its lifetime. (shrink)

En un libro reciente McShea y Brandon defienden que la diversidad y la complejidad de la vida se explican, principalmente, por la acción de un principio que llaman “la ley evolutiva de fuerzas cero” o “ZFEL”. Tal principio actuaría de un modo implícito por detrás de muchas explicaciones de la biología, pero nunca habría sido explicitado. Asumiendo que esta idea es interesante, y que los autores en cuestión tienen razón, discutiremos el modo metateórico en que presentan dicho principio, como siendo (...) parte de la teoría de la probabilidad. Esto permite a los autores afirmar que la teoría de la probabilidad brindaría la base reductiva para toda la biología evolutiva (dado que consideran que otros principios, como el de selección natural, también serían parte de la teoría de la probabilidad). Defenderemos que, efectivamente, ZFEL no es propio de la biología únicamente, pero no por formar parte de la teoría de la probabilidad, sino por tratarse de una versión específica del principio de causa común. -/- In a recent book, McShea and Brandon argue that the observed diversity and complexity of life are explainable by a principle they call the “zero-force evolutionary law” or “ZFEL”. Although this principle would be implicit in many explanations given by biologists, it would have never been made explicit. Assuming that this idea is interesting, and that the authors are right, we will discuss the metatheoretical way in which they present said principle, as being a part of probability theory. This allows the authors to claim that probability theory provides the reductive basis for all evolutionary biology. We will defend, in accordance with them, that ZFEL is not a solely biological principle, but not because it is a part of probability theory, but rather because it is a specific version of the principle of common cause. (shrink)

The hologenome concept of evolution is a hypothesis about the evolution of animals and plants. It asserts that the evolution of animals and plants was partially triggered by their interactions with their symbiotic microbiomes. In that vein, the hologenome concept posits that the holobiont (animal host + symbionts of the microbiome) is a unit of selection. -/- The hologenome concept has been severely criticized on the basis that selection on holobionts would only be possible if there were a tight transgenerational (...) host-genotype-to-symbiont-genotype connection. As our current evidence suggests that this is not the case for most of the symbiont species that compose the microbiome of animals and plants, the opportunity for holobiont selection is very low in relation to the opportunity for selection on each of the species that compose the host microbiome. Therefore, holobiont selection will always be disrupted ‘from below’, by selection on each of the species that compose the microbiome. -/- This thesis constitutes a conceptual effort to defend philosophically the hologenome concept. I argue that the criticism according to which holobiont selection requires tight transgenerational host-genotype-to-symbiont-genotype connection is grounded on a metaphysical view of the world according to which the biological hierarchy needs to be nested, such that each new level of selection includes every entity from below. Applied to hologenomes, it entails that the hologenome is a collection of genomes, and selection of hologenomes is assumed to entail cospeciation of the host with the species that constitute its microbiome. -/- Against that interpretation, I propose the ‘stability of traits’ account, according to which hologenome evolution is the result of the action of natural selection in a non-nested hierarchical world. In that vein, hologenome evolution does not entail cospeciation, and thus it does not require tight transgenerational host-genotype-to-symbiont-genotype connection. By embracing a multilevel selection perspective, I argue that hologenome evolution results from the simultaneous action of natural selection on each of the lineages that compose the microbiome, and on the assemblage composed by the host genome plus the functional traits of its microbiome. Hologenome selection occurs when the evolution of the traits of the microbiome result from their effects on the fitness of the host, and it can take the form of multilevel selection 1, or multilevel selection 2. In both cases, hologenome selection entails the evolution of microbiome traits, as well as evolution of the host genome, rather than cospeciation of lineages. (shrink)

I distinguish two roles for a fitness concept in the context of explaining cumulative adaptive evolution: fitness as a predictor of gene frequency change, and fitness as a criterion for phenotypic improvement. Critics of inclusive fitness argue, correctly, that it is not an ideal fitness concept for the purpose of predicting gene-frequency change, since it relies on assumptions about the causal structure of social interaction that are unlikely to be exactly true in real populations, and that hold as approximations only (...) given a specific type of weak selection. However, Hamilton took this type of weak selection, on independent grounds, to be responsible for cumulative assembly of complex adaptations. In this special context, I argue that inclusive fitness is distinctively valuable as a criterion for improvement and a standard for optimality. Yet to call inclusive fitness a criterion for improvement and a standard for optimality is not to make any claim about the frequency with which inclusive fitness optimization actually occurs in nature. This is an empirical question that cannot be settled by theory alone. I close with some reflections on the place of inclusive fitness in the long running clash between ‘causalist’ and ‘statisticalist’ conceptions of fitness. (shrink)

The probability that the fitter of two alleles will increase in frequency in a population goes up as the product of N (the effective population size) and s (the selection coefficient) increases. Discovering the distribution of values for this product across different alleles in different populations is a very important biological task. However, biologists often use the product Ns to define a different concept; they say that drift “dominates” selection or that drift is “stronger than” selection when Ns is much (...) smaller than some threshold quantity (e.g., ½) and that the reverse is true when Ns is much larger than that threshold. We argue that the question of whether drift dominates selection for a single allele in a single population makes no sense. Selection and drift are causes of evolution, but there is no fact of the matter as to which cause is stronger in the evolution of any given allele. (shrink)

Philosophers of biology have worked extensively on how we ought best to interpret the probabilities which arise throughout evolutionary theory. In spite of this substantial work, however, much of the debate has remained persistently intractable. I offer the example of Bayesian models of divergence time estimation as a case study in how we might bring further resources from the biological literature to bear on these debates. These models offer us an example in which a number of different sources of uncertainty (...) are combined to produce an estimate for a complex, unobservable quantity. These models have been carefully analyzed in recent biological work, which has determined the relationship between these sources of uncertainty, both quantitatively and qualitatively. I suggest here that this case shows us the limitations of univocal analyses of probability in evolution, as well as the simple dichotomy between “subjective” and “objective” probabilities, and I conclude by gesturing toward ways in which we might introduce more sophisticated interpretive taxonomies of probability as a path toward advancing debates on probability in the life sciences. (shrink)

In this paper, I present a new framework supporting the claim that some elements in science play a constitutive function, with the aim of overcoming some limitations of Friedman's (2001) account. More precisely, I focus on what I consider to be the gradualism implicit in Friedman's interpretation of the constitutive a priori, that is, the fact that it seems to allow for degrees of 'constitutivity'. I tease out such gradualism by showing that the constitutive character Friedman aims to track can (...) be captured by three features - namely, quasi-axiomaticity (QA), generative potential (GP), and empirical shielding (ES) - which are exhibited to a maximal degree by the examples Friedman deploys, particularly in his analysis of Newtonian mechanics. I argue that not all varieties of 'constitutivity' can be captured by the kind of gradualism implicit in Friedman's view, although developing the gradualism itself might provide useful insights. To show this, I analyse the function of the Hardy-Weinberg principle (HWP) in population genetics in terms of its QA, GP, and ES. Whereas the HWP does not count as constitutive in classical philosophical interpretations (Sober 1984), nor does it within Friedman's framework, it does nonetheless perform a minimally constitutive function. By means of historical details and considerations on the prospects of replacing the HWP, I show that the HWP is minimally constitutive by being a counterfactual instantiation of a paradigmatically constitutive stability principle, where the latter might itself be regarded as an enabling condition for a variety of modelling practices across the sciences. (shrink)

A basic challenge to naturalistic moral realism is that, even if moral properties existed, there would be no way to naturalistically represent or track them. Here, the basic structure for a tracking account of moral epistemology is given in empirically respectable terms, based on a eudaimonist conception of morality. The goal is to show how this form of moral realism can be seen as consistent with the details of evolutionary biology as well as being amenable to the most current understanding (...) of representationalist or correspondence theories of truth. (shrink)

In this paper, we argue that rather than exclusively focusing on trying to determine if an idealized model fits a particular account of scientific explanation, philosophers of science should also work on directly analyzing various explanatory schemas that reveal the steps and justification involved in scientists’ use of highly idealized models to formulate explanations. We develop our alternative methodology by analyzing historically important cases of idealized statistical modeling that use a three-step explanatory schema involving idealization, mathematical operation, and explanatory interpretation.

This paper addresses the question of what organisms are and therefore what kinds of biological entities qualify as organisms. For some time now, the concept of organismality has been eclipsed by the notion of individuality. Biological individuals are those systems that are units of selection. I develop a conception of organismality that does not rely on evolutionary considerations, but instead draws on development and ecology. On this account, organismality and individuality can come apart. Organisms, in my view, are as Godfrey-Smith (...) puts it “essentially persisters.” I argue that persistence is underpinned by differentiation, integration, development, and the constitutive embeddedness of organisms in their worlds. I examine two marginal cases, the Portuguese Man O’ War and the honey bee colony, and show that both count as organisms in light of my analysis. Next, I examine the case of holobionts, hosts plus their microsymbionts, and argue that they can be counted as organisms even though they may not be biological individuals. Finally, I consider the question of whether other, less tightly integrated biological systems might also be treated as organisms. (shrink)

Karl Popper argued in 1974 that evolutionary theory contains no testable laws and is therefore a metaphysical research program. Four years later, he said that he had changed his mind. Here we seek to understand Popper’s initial position and his subsequent retraction. We argue, contrary to Popper’s own assessment, that he did not change his mind at all about the substance of his original claim. We also explore how Popper’s views have ramifications for contemporary discussion of the nature of laws (...) and the structure of evolutionary theory. (shrink)

Over the past fifteen years there has been a considerable amount of debate concerning what theoretical population dynamic models tell us about the nature of natural selection and drift. On the causal interpretation, these models describe the causes of population change. On the statistical interpretation, the models of population dynamics models specify statistical parameters that explain, predict, and quantify changes in population structure, without identifying the causes of those changes. Selection and drift are part of a statistical description of population (...) change; they are not discrete, apportionable causes. Our objective here is to provide a definitive statement of the statistical position, so as to allay some confusions in the current literature. We outline four commitments that are central to statisticalism. They are: 1. Natural Selection is a higher order effect; 2. Trait fitness is primitive; 3. Modern Synthesis (MS)-models are substrate neutral; 4. MS-selection and drift are model-relative. (shrink)

Using the evolution of the stickleback family of subarctic fish as a touchstone, we explore the effect of new discoveries about regulatory genetics, developmental plasticity, and epigenetic inheritance on the conceptual foundations of the Modern Evolutionary Synthesis. Identifying the creativity of natural selection as the hallmark of the Modern Synthesis, we show that since its inception its adherents have pursued a variety of research projects that at first seemed to conflict with its principles, but were accommodated. We situate challenges coming (...) from developmental biology in a dialectic between innovation and tradition, suggesting on the basis of past episodes that even if developmental plasticity and epigenetic inheritance are aligned with its principles the Modern Synthesis will be significantly affected. (shrink)

It is an ongoing controversy whether natural selection is a cause of population change, or a mere statistical description of how individual births and deaths accumulate. In this paper I restate the problem in terms of the reference class problem, and propose how the structure of stable equilibrium can provide a solution in continuity with biological practice. Insofar natural selection can be understood as a tendency towards equilibrium, key statisticalist criticisms are avoided. Further, in a modification of the Newtonian-force analogy, (...) it can be suggested that a better metaphor for natural selection is that of an emergent force, similar in nature to entropic forces: with magnitude and direction, but lacking a spatiotemporal origin or point of application. (shrink)

Shapiro and Sober claim that Walsh, Ariew, Lewens, and Matthen give a mistaken, a priori defense of natural selection and drift as epiphenomenal. Contrary to Shapiro and Sober’s claims, we first argue that WALM’s explanatory doctrine does not require a defense of epiphenomenalism. We then defend WALM’s explanatory doctrine by arguing that the explanations provided by the modern genetical theory of natural selection are ‘autonomous-statistical explanations’ analogous to Galton’s explanation of reversion to mediocrity and an explanation of the diffusion ofgases. (...) We then argue that whereas Sober’s theory of forces is an adequate description of Darwin’s theory, WALM’s explanatory doctrine is required to understand how themodern genetical theory of natural selection explains large-scale statistical regularities. 1 Introduction2 Shapiro and Sober’s ‘Epiphenomenalism Do’s and Don’ts’3 WALM’s Explanatory Doctrine4 Galton’s Autonomous-Statistical Explanation5 A Second Example: The Statistical Explanation of the Diffusion of Gases6 Distinguishing Two Theories of Evolution by Natural Selection7 A Possible Objection: Are Statistical Laws Sufficient for Explanation?8 Conclusion. (shrink)

This article analyzes the view of evolutionary theory as a theory of forces. The analogy with Newtonian mechanics has been challenged due to the alleged mismatch between drift and the other evolutionary forces. Since genetic drift has no direction several authors tried to protect its status as a force: denying its lack of directionality, extending the notion of force and looking for a force in physics which also lacks of direction. I analyse these approaches, and although this strategy finally succeeds, (...) this discussion overlooks the crucial point on the debate between causalists and statisticalists: the causal status of evolutionary theory. (shrink)

This paper provides a philosophical analysis of the Price equation and its role in evolutionary theory. Traditional models in population genetics postulate simplifying assumptions in order to make the models mathematically tractable. On the contrary, the Price equation implies a very specific way of theorizing, starting with assumptions that we think are true and then deriving from them the mathematical rules of the system. I argue that the Price equation is a generalization-sketch, whose main purpose is to provide a unifying (...) framework for researchers, helping them to develop specific models. The Price equation plays this role because, like other scientific principles, shows features as abstractness, unification and invariance. By underwriting this special role for the Price equation some recent disputes about it could be diverted. (shrink)

The explanatory role of natural selection is one of the long-term debates in evolutionary biology. Nevertheless, the consensus has been slippery because conceptual confusions and the absence of a unified, formal causal model that integrates different explanatory scopes of natural selection. In this study we attempt to examine two questions: (i) What can the theory of natural selection explain? and (ii) Is there a causal or explanatory model that integrates all natural selection explananda? For the first question, we argue that (...) five explananda have been assigned to the theory of natural selection and that four of them may be actually considered explananda of natural selection. For the second question, we claim that a probabilistic conception of causality and the statistical relevance concept of explanation are both good models for understanding the explanatory role of natural selection. We review the biological and philosophical disputes about the explanatory role of natural selection and formalize some explananda in probabilistic terms using classical results from population genetics. Most of these explananda have been discussed in philosophical terms but some of them have been mixed up and confused. We analyze and set the limits of these problems. (shrink)

Comparisons of causal efficacy are ubiquitous in the practice of science and indeed everyday life. I focus on just one aspect of this task – one to my knowledge nowhere yet addressed satisfactorily – namely, comparing the efficacies of two causes that work in apparently incommensurable ways. Contrary to common opinion I argue that, to be comparable, it is neither necessary nor sufficient that two causes also be commensurable.

Millstein argues against conceptual pluralism with respect to the definition of “population,” and proposes her own definition of the term. I challenge both Millstein’s negative arguments against conceptual pluralism and her positive proposal for a singular definition of population. The concept of population, I argue, does not refer to a natural kind; popula tions are constructs of biologists variably defined by contexts of inquiry.

According to one large family of views, scientific explanations explain a phenomenon (such as an event or a regularity) by subsuming it under a general representation, model, prototype, or schema (see Bechtel, W., & Abrahamsen, A. (2005). Explanation: A mechanist alternative. Studies in History and Philosophy of Biological and Biomedical Sciences, 36(2), 421–441; Churchland, P. M. (1989). A neurocomputational perspective: The nature of mind and the structure of science. Cambridge: MIT Press; Darden (2006); Hempel, C. G. (1965). Aspects of scientific (...) explanation. In C. G. Hempel (Ed.), Aspects of scientific explanation (pp. 331–496). New York: Free Press; Kitcher (1989); Machamer, P., Darden, L., & Craver, C. F. (2000). Thinking about mechanisms. Philosophy of Science, 67(1), 1–25). My concern is with the minimal suggestion that an adequate philosophical theory of scientific explanation can limit its attention to the format or structure with which theories are represented. The representational subsumption view is a plausible hypothesis about the psychology of understanding. It is also a plausible claim about how scientists present their knowledge to the world. However, one cannot address the central questions for a philosophical theory of scientific explanation without turning one’s attention from the structure of representations to the basic commitments about the worldly structures that plausibly count as explanatory. A philosophical theory of scientific explanation should achieve two goals. The first is explanatory demarcation. It should show how explanation relates with other scientific achievements, such as control, description, measurement, prediction, and taxonomy. The second is explanatory normativity. It should say when putative explanations succeed and fail. One cannot achieve these goals without undertaking commitments about the kinds of ontic structures that plausibly count as explanatory. Representations convey explanatory information about a phenomenon when and only when they describe the ontic explanations for those phenomena. (shrink)

I define a concept of causal probability and apply it to questions about the role of probability in evolutionary processes. Causal probability is defined in terms of manipulation of patterns in empirical outcomes by manipulating properties that realize objective probabilities. The concept of causal probability allows us see how probabilities characterized by different interpretations of probability can share a similar causal character, and does so in such way as to allow new inferences about relationships between probabilities realized in different chance (...) setups. I clarify relations between probabilities and properties defined in terms of them, and argue that certain widespread uses of computer simulations in evolutionary biology show that many probabilities relevant to evolutionary outcomes are causal probabilities. This supports the claim that higher-level properties such as biological fitness and processes such as natural selection are causal properties and processes, contrary to what some authors have argued. (shrink)

In what follows, I suggest that it makes good sense to think of the truth of the probabilistic generalizations made in the life sciences as metaphysically grounded in stochastic mechanisms in the world. To further understand these stochastic mechanisms, I take the general characterization of mechanism offered by MDC :1–25, 2000) and explore how it fits with several of the going philosophical accounts of chance: subjectivism, frequentism, Lewisian best-systems, and propensity. I argue that neither subjectivism, frequentism, nor a best-system-style interpretation (...) of chance will give us what we need from an account of stochastic mechanism, but some version of propensity theory can. I then draw a few important lessons from recent propensity interpretations of fitness in order to present a novel propensity interpretation of stochastic mechanism according to which stochastic mechanisms are thought to have probabilistic propensities to produce certain outcomes over others. This understanding of stochastic mechanism, once fully fleshed-out, provides the benefits of allowing the stochasticity of a particular mechanism to be an objective property in the world, a property investigable by science, a way of quantifying the stochasticity of a particular mechanism, and a way to avoid a problematic commitment to the causal efficacy of propensities. (shrink)

Scientists use models to understand the natural world, and it is important not to conflate model and nature. As an illustration, we distinguish three different kinds of populations in studies of ecology and evolution: theoretical, laboratory, and natural populations, exemplified by the work of R.A. Fisher, Thomas Park, and David Lack, respectively. Biologists are rightly concerned with all three types of populations. We examine the interplay between these different kinds of populations, and their pertinent models, in three examples: the notion (...) of “effective” population size, the work of Thomas Park on /Tribolium/ populations, and model-based clustering algorithms such as /Structure/. Finally, we discuss ways to move safely between three distinct population types while avoiding confusing models and reality. (shrink)

The causal nature of evolution is one of the central topics in the philosophy of biology. The issue concerns whether equations used in evolutionary genetics point to some causal processes or purely phenomenological patterns. To address this question the present article builds well-defined causal models that underlie standard equations in evolutionary genetics. These models are based on minimal and biologically plausible hypotheses about selection and reproduction, and generate statistics to predict evolutionary changes. The causal reconstruction of the evolutionary principles shows (...) adaptive evolution as a genuine causal process, where fitness and selection are both causes of evolution. 1 Introduction2 The Philosophical Puzzle3 Causal Models4 Causal Foundations of Evolutionary Genetics4.1 Univariate quantitative genetics model4.1.1 The causal graph4.1.2 Structural equations4.1.3 Deriving evolutionary transition functions4.2 One-locus population genetics model5 Evolution as a Causal Process5.1 Selection as a causal process5.2 Causes of evolutionary change6 Conclusion. (shrink)

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

The causal structure of Darwinian evolution by natural selection is investigated. Its basic scheme is reproduction resulting from a feedback loop driven by internal and external causes. Causation internal to the loop connects genotype, development, phenotype, and fitness, with environmental constraints on the latter preventing runaway reproduction. External causes driving the core loop are environmental change and genetic change. This basic causal structure is complicated by modern additions such as control of mutation rate, niche construction, interactions between evolution and development, (...) and epigenetic effects. In this article it is argued that at least one of these additions, control of mutation rate, produces an additional feedback loop incorporating a continual, targeted modulation of stochasticity, and thereby produces an unusual form of causation. This form of causation entangles deterministic and stochastic causation in such a way that it imposes, in effect, an active, goal-driven role on the organisms in a line of descent. The goal is defined by the factor driving the stochasticity, which must be regarded as an intrinsic estimate made implicitly by the organism of its own fitness. The estimator itself is an evolved property of the organism, and is aligned with the apparent goal-directedness of natural selection. (shrink)

There are two ways evolution by natural selection is conceptualized in the literature. One provides a ‘recipe’ for ENS incorporating three ingredients: variation, differences in fitness, and heritability. The other provides formal equations of evolutionary change and partitions out selection from other causes of evolutionary changes such as transmission biases or drift. When comparing the two approaches there seems to be a tension around the concept of heritability. A recent claim has been made that the recipe approach is flawed and (...) should be abandoned. In this article, I show that the tension is only a superficial one. If one uses a concept of heritability strictly in line with the formal equations of evolutionary change, the recipe approach keeps its validity and generality. To demonstrate that the intuitive concept of heritability is not a general one, I use one formulation of the Price equation formulated by Okasha, show that the concept of heritability in his formulation incorporates both the intuitive notion of heritability as a measure of similarity between parent and offspring characters, and a measure of persistence. I advocate for persistence to be incorporated in the concept of heritability used in recipes for ENS in the same way heredity is, show that this is readily attainable and thereby dissolve any point of tension concerning heritability between the recipe and the analytical approach to ENS. 1 Introduction2 Heritability in the Price Equation2.1 Different approaches to heredity and heritability2.2 Heritability: From recipes to the Price equation3 A Problem for the Recipes?4 Reinterpreting Heritability for Recipes5 Conclusion Appendix. (shrink)

Building upon a non-standard understanding of evolutionary process focusing on variation and persistence, I will argue that communities and ecosystems can evolve by natural selection as emergent individuals. Evolutionary biology has relied ever increasingly on the modeling of population dynamics. Most have taken for granted that we all agree on what is a population. Recent work has reexamined this perceived consensus. I will argue that there are good reasons to restrict the term “population” to collections of monophyletically related replicators and (...) interactors, which explains why many existing models in population biology exclude by definition many genuine evolving biological individuals such as communities and ecosystems. By studying a case of community evolution (a symbiotic termite–fungus community), we will see that it is variation that is important to evolutionary processes, not populations. Variation within a population is only one of many types of variation that can lead to evolution by natural selection. The upshot of focusing on variation is that cases of community and ecosystem adaptive change become tractable in evolutionary terms. I will show that complex emergent individuals such as communities and ecosystems cannot be fully accommodated by conventional population/reproduction models but can be accommodated by variation/persistence models. (shrink)

Although it may seem like a truism to assert that biology is the science that studies organisms, during the second half of the twentieth century the organism category disappeared from biological theory. Over the past decade, however, biology has begun to witness the return of the organism as a fundamental explanatory concept. There are three major causes: (a) the realization that the Modern Synthesis does not provide a fully satisfactory understanding of evolution; (b) the growing awareness of the limits of (...) reductionism in molecular biology; and (c) the renewed interest in the nature of life as a genuine scientific problem. This essay examines these recent developments and considers the new epistemological roles being played by the organism in each of them. It also reflects on what the present resurgence of the organism means for the philosophy of biology. (shrink)

Philosophers have long been interested in a series of interrelated questions about natural kinds. What are they? What role do they play in science and metaphysics? How do they contribute to our epistemic projects? What categories count as natural kinds? And so on. Owing, perhaps, to different starting points and emphases, we now have at hand a variety of conceptions of natural kinds—some apparently better suited than others to accommodate a particular sort of inquiry. Even if coherent, this situation isn’t (...) ideal. My goal in this article is to begin to articulate a more general account of ‘natural kind phenomena’. While I do not claim that this account should satisfy everyone—it is built around a certain conception of the epistemic role of kinds and has an obvious pragmatic flavour—I believe that it has the resources to go further than extant alternatives, in particular the homeostatic property cluster view of kinds. (shrink)

Nelson and Winter’s An Evolutionary Theory of Economic Change (1982) was the foundational work of what has become the thriving sub-discipline of evolutionary economics. In attempting to develop an alternative to neoclassical economics, the authors looked to borrow basic ideas from biology, in particular a concept of economic “natural selection.” However, the evolutionary models they construct in their seminal work are in many respects quite different from the models of evolutionary biology. There is no reproduction in any usual sense, “mutation” (...) is directed as opposed to blind, and there is no meaningful distinction between phenotype and genotype. Despite these substantial departures from the conceptions of evolutionary biology, I argue that the “evolutionary” economics of Nelson and Winter is indeed a legitimate extension of Darwinian evolutionary principles to a novel domain, and that the traditional conception of evolution by natural selection must be revised. The novel features of evolutionary economics models reflect the distinctive theoretical requirements faced by economists. I further contend that reproduction, heredity, blind variation, and the genotype/phenotype distinction are all inessential to evolutionary theory, and that their role in evolutionary biology is a domain-specific feature of biological theory. (shrink)

A prominent approach to scientific explanation and modeling claims that for a model to provide an explanation it must accurately represent at least some of the actual causes in the event's causal history. In this paper, I argue that many optimality explanations present a serious challenge to this causal approach. I contend that many optimality models provide highly idealized equilibrium explanations that do not accurately represent the causes of their target system. Furthermore, in many contexts, it is in virtue of (...) their independence of causes that optimality models are able to provide a better explanation than competing causal models. Consequently, our account of explanation and modeling must expand beyond the causal approach. (shrink)

Fitness plays many roles throughout evolutionary theory, from a measure of populations in the wild to a central element in abstract theoretical presentations of natural selection. It has thus been the subject of an extensive philosophical literature, which has primarily centered on the way to understand the relationship between fitness values and reproductive outcomes. If fitness is a probabilistic or statistical quantity, how is it to be defined in general theoretical contexts? How can it be measured? Can a single conceptual (...) model for fitness be offered that applies in all biological cases, or must fitness measures be case-specific? Philosophers have explored these questions over the last several decades, largely in the context of an influential definition of fitness proposed in the late 1970s: the propensity interpretation. This interpretation as first described undeniably suffers from significant difficulties, and debate regarding the tenability of amendments and alternatives to it remains unsettled. (shrink)

There is only one physically possible process that builds and operates purposive systems in nature: natural selection. What it does is build and operate systems that look to us purposive, goal directed, teleological. There really are not any purposes in nature and no purposive processes ether. It is just one vast network of linked causal chains. Darwinian natural selection is the only process that could produce the appearance of purpose. That is why natural selection must have built and must continually (...) shape the intentional causes of purposive behavior. Fodor’s argument against Darwinian theory involves a biologist’s modus tollens which is a cognitive scientist’s modus ponens. Assuming his argument is valid, the right conclusion is not that Darwin’s theory is mistaken but that Fodor’s and any other non-Darwinian approaches to the mind are wrong. It shows how getting things wrong in the philosophy of biology leads to mistaken conclusions with the potential to damage the acceptance of a theory with harmful consequences for human well-being. Fodor has shown that the real consequence of rejecting a Darwinian approach to the mind is to reject a Darwinian theory of phylogenetic evolution. This forces us to take seriously a notion that otherwise would not have much of a chance: that when it comes to the nature of mental states, indeterminacy rules. This is an insight that should have the most beneficial impact on freeing cognitive neuroscience from demands on the adequacy of its theories that it could never meet. (shrink)

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. (shrink)

I distinguish three theses associated with the new mechanistic philosophy – concerning causation, explanation and scientific methodology. Advocates of each thesis are identified and relationships among them are outlined. I then look at some recent work on natural selection and mechanisms. There, attention to different kinds of New Mechanism significantly affects of what is at stake.

I argue that the propensity interpretation of fitness, properly understood, not only solves the explanatory circularity problem and the mismatch problem, but can also withstand the Pandora’s box full of problems that have been thrown at it. Fitness is the propensity (i.e., probabilistic ability, based on heritable physical traits) for organisms or types of organisms to survive and reproduce in particular environments and in particular populations for a specified number of generations; if greater than one generation, “reproduction” includes descendants of (...) descendants. Fitness values can be described in terms of distributions of propensities to produce varying number of offspring and can be modeled for any number of generations using computer simulations, thus providing both predictive power and a means for comparing the fitness of different phenotypes. Fitness is a causal concept, most notably at the population level, where fitness differences are causally responsible for differences in reproductive success. Relative fitness is ultimately what matters for natural selection. (shrink)

The propensity interpretation of fitness (PIF) is commonly taken to be subject to a set of simple counterexamples. We argue that three of the most important of these are not counterexamples to the PIF itself, but only to the traditional mathematical model of this propensity: fitness as expected number of offspring. They fail to demonstrate that a new mathematical model of the PIF could not succeed where this older model fails. We then propose a new formalization of the PIF that (...) avoids these (and other) counterexamples. By producing a counterexample-free model of the PIF, we call into question one of the primary motivations for adopting the statisticalist interpretation of fitness. In addition, this new model has the benefit of being more closely allied with contemporary mathematical biology than the traditional model of the PIF. (shrink)

Following Wallace’s suggestion, Darwin framed his theory using Spencer’s expression “survival of the fittest”. Since then, fitness occupies a significant place in the conventional understanding of Darwinism, even though the explicit meaning of the term ‘fitness’ is rarely stated. In this paper I examine some of the different roles that fitness has played in the development of the theory. Whereas the meaning of fitness was originally understood in ecological terms, it took a statistical turn in terms of reproductive success throughout (...) the 20th Century. This has lead to the ever-increasing importance of sexually reproducing organisms and the populations they compose in evolutionary explanations. I will argue that, moving forward, evolutionary theory should look back at its ecological roots in order to be more inclusive in the type of systems it examines. Many biological systems can only be satisfactorily accounted for by offering a non-reproductive account of fitness. This argument will be made by examining biological systems with very small or transient population structures. I argue this has significant consequences for how we define Darwinism, increasing the significance of survival over that of reproduction. (shrink)

Essay review of Michael Ruse (ed.), The Oxford Handbook of the Philosophy of Biology (2008).

Evo-Devo exhibits a plurality of scientific “cultures” of practice and theory. When are the cultures acting—individually or collectively—in ways that actually move research forward, empirically, theoretically, and ethically? When do they become imperialistic, in the sense of excluding and subordinating other cultures? This chapter identifies six cultures – three /styles/ (mathematical modeling, mechanism, and history) and three /paradigms/ (adaptationism, structuralism, and cladism). The key assumptions standing behind, under, or within each of these cultures are explored. Characterizing the internal structure of (...) the cultures is necessary for understanding how they collaborate or compete, and how they are fragmented or integrated, in the rich interdisciplinary /trading zone/ (Galison 1997) of Evo-Devo. Evo-Devo is an important example of how science can progress through a radical plurality of perspectives and cultures. (shrink)