Population Genetics

The notion that natural selection is a process of fitness maximization gets a bad press in population genetics, yet in other areas of biology the view that organisms behave as if attempting to maximize their fitness remains widespread. Here I critically appraise the prospects for reconciliation. I first distinguish four varieties of fitness maximization. I then examine two recent developments that may appear to vindicate at least one of these varieties. The first is the ‘new’ interpretation of Fisher's fundamental theorem (...) of natural selection, on which the theorem is exactly true for any evolving population that satisfies some minimal assumptions. The second is the Formal Darwinism project, which forges links between gene frequency change and optimal strategy choice. In both cases, I argue that the results fail to establish a biologically significant maximization principle. I conclude that it may be a mistake to look for universal maximization principles justified by theory alone. A more promising approach may be to find maximization principles that apply conditionally and to show that the conditions were satisfied in the evolution of particular traits. (shrink)

Cooperation is rife in the microbial world, yet our best current theories of the evolution of cooperation were developed with multicellular animals in mind. Hamilton’s theory of inclusive fitness is an important case in point: applying the theory in a microbial setting is far from straightforward, as social evolution in microbes has a number of distinctive features that the theory was never intended to capture. In this article, I focus on the conceptual challenges posed by the project of extending Hamilton’s (...) theory to accommodate the effects of gene mobility. I begin by outlining the basics of the theory of inclusive fitness, emphasizing the role that the concept of relatedness is intended to play. I then provide a brief history of this concept, showing how, over the past fifty years, it has departed from the intuitive notion of genealogical kinship to encompass a range of generalized measures of genetic similarity. I proceed to argue that gene mobility forces a further revision of the concept. The reason in short is that, when the genes implicated in producing social behaviour are mobile, we cannot talk of an organism’s genotype simpliciter; we can talk only of an organism’s genotype at a particular stage in its life cycle. We must therefore ask: with respect to which stage(s) in the life cycle should relatedness be evaluated? For instance: is it genetic similarity at the time of social interaction that matters to the evolution of social behaviour, or is it genetic similarity at the time of reproduction? I argue that, strictly speaking, it is neither of these: what really matters to the evolution of social behaviour is diachronic genetic similarity between the producers of fitness benefits at the time they produce them and the recipients of those benefits at the end of their life-cycle. I close by discussing the implications of this result. The main payoff is that it makes room for a possible new mechanism for the evolution of altruism in microbes that does not require correlated interaction among bearers of the genes for altruism. The importance of this mechanism in nature remains an open empirical question. (shrink)

“ The Origins of Genome Architecture ” by Michael Lynch (2007) may not immediately sound like a book that someone interested in the philosophy of biology would grab off the shelf. But there are three important reasons why you should read this book. Firstly, if you want to understand biological evolution, you should have at least a passing familiarity with evolutionary change at the level of the genome. This is not to say that everyone interested in evolution should be a (...) geneticist or a bioinformatician, but that a working knowledge of genetic change is an essential part of the intellectual toolkit of modern evolutionary biology, even if your primary focus is the evolution of behaviour or the diversity of communities. Secondly, this book provides excellent examples of another important tool in the biologist’s intellectual toolkit, but one that is rarely explained or illustrated to such an extent: null (or neutral) models. The role null models play in testing hypotheses in evolution is a central focus of this book. Thirdly, as an accomplished work of advocacy for a strictly microevolutionary view of evolution, this book provides grist for the mill for the important debate about whether population genetic processes are the sine qua non of evolutionary explanations. (shrink)

The model of human intelligence that is most widely adopted derives from psychometrics and behavioral genetics. This standard approach conceives intelligence as a general cognitive ability that is genetically highly heritable and describable using quantitative traits analysis. The paper analyzes intelligence within the debate on natural kinds and contends that the general intelligence conceptualization does not carve psychological nature at its joints. Moreover, I argue that this model assumes an essentialist perspective. As an alternative, I consider an HPC theory of (...) intelligence and evaluate how it deals with essentialism and with intuitions coming from cognitive science. Finally, I highlight some concerns about the HPC model as well, and conclude by suggesting that it is unnecessary to treat intelligence as a kind in any sense. (shrink)

In this paper we present a new framework of idealization in biology. We characterize idealizations as a network of counterfactual and hypothetical conditionals that can exhibit different "degrees of contingency". We use this idea to say that, in departing more or less from the actual world, idealizations can serve numerous epistemic, methodological or heuristic purposes within scientific research. We defend that, in part, this structure explains why idealizations, despite being deformations of reality, are so successful in scientific practice. For illustrative (...) purposes, we provide an example from population genetics, the Wright-Fisher Model. (shrink)

In the 1960s molecular population geneticists used Monte Carlo experiments to evaluate particular diffusion equation models. In this paper I examine the nature of this comparative evaluation and argue for three claims: first, Monte Carlo experiments are genuine experiments: second, Monte Carlo experiments can provide an important meansfor evaluating the adequacy of highly idealized theoretical models; and, third, the evaluation of the computational adequacy of a diffusion model with Monte Carlo experiments is significantlydifferent from the evaluation of the emperical adequacy (...) of the same diffusion model. (shrink)

In popular articles that play down the genetical differences among human populations, it is often stated that about 85% of the total genetical variation is due to individual differences within populations and only 15% to differences between populations or ethnic groups. It has therefore been proposed that the division of Homo sapiens into these groups is not justified by the genetic data. This conclusion, due to R.C. Lewontin in 1972, is unwarranted because the argument ignores the fact that most of (...) the information that distinguishes populations is hidden in the correlation structure of the data and not simply in the variation of the individual factors. The underlying logic, which was discussed in the early years of the last century, is here discussed using a simple genetical example. (shrink)

Among philosophers, controversy over the notion of drift in population genetics is ongoing. This is at least partly because the notion of drift has an ambiguous usage among population geneticists. My goal in this paper is to explicate the causal dimension of drift, to say what causal influences are responsible for the stochasticity in population genetics models. It is commonplace for population genetics to oppose the influence of selection to that of drift, and to consider how the dynamics of populations (...) are altered when each has greater or lesser influence. I define the causes that are referred to as drift when researchers speak this way. Introduction Populations and Variant Types The Cause–Effect Ambiguity of Drift Non-directional Factors in Population Genetics How N ev Is Used in Population Genetics Causal Conceptions of Drift 6.1 The Millstein/Beatty conception of drift 6.2 Rosenberg and Bouchard: Drift as initial conditions NINPICs 7.1 Why drift is instituted by NINPICs 7.2 How NINPICS work 7.3 NINPICs and random sampling 7.4 Independent sampling and effective population size 7.5 Variance in progeny number 7.6 Population effects of NINPICs NINPICs and the Stochastic Character of Selection Theory Conclusion Appendix CiteULike Connotea Del.icio.us What's this? (shrink)

Para algunos la selección natural se identifica con las diferencias de éxito de distintos organismos en la reproducción diferencial. Si esto fuese así, el principio de Hardy-Weinberg, por permitir determinar con bastante precisión bajo ciertos supuestos que la frecuencia génica en una población no es la esperada, podría ser visto como una versión cuantitativa de la selección natural cualitativa propuesta por Darwin. Es mi intención mostrar, a través del análisis de explicaciones dadas por Darwin, que la selección natural es más (...) que la mera diferencia en el éxito en la reproducción diferencial e investigar algunas relaciones entre la teoría de la selección natural y la genética de poblaciones. (shrink)

Since the introduction of mathematical population genetics, its machinery has shaped our fundamental understanding of natural selection. Selection is taken to occur when differential fitnesses produce differential rates of reproductive success, where fitnesses are understood as parameters in a population genetics model. To understand selection is to understand what these parameter values measure and how differences in them lead to frequency changes. I argue that this traditional view is mistaken. The descriptions of natural selection rendered by population genetics models are (...) in general neither predictive nor explanatory and introduce avoidable conceptual confusions. I conclude that a correct understanding of natural selection requires explicitly causal models of reproductive success. *Received May 2006; revised December 2006. †To contact the author, please write to: Department of Philosophy, Kansas State University, 201 Dickens Hall, Manhattan, KS 66506; e‐mail: glymour@ksu.edu . (shrink)

Neven Sesardic has recently defended his arguments in favour of racial naturalism—the view that race is a valid biological category—in response to my criticism of his work. While Sesardic claims that a strong version of racial naturalism can survive critique, he has in fact weakened his position considerably. He concedes that conventional racial taxonomy is arbitrary and he no longer identifies ‘races’ as human subspecies. Sesardic now relies almost entirely on Theodosius Dobzhansky’s notion of race-as-population. This weak approach to ‘race’—according (...) to which all genetic difference between populations is ‘racial’ and ‘the races’ are simply the populations we choose to call races—survived its early critiques. As it is being mobilised to support racial naturalism once more, we need to continue the debate about whether we should weaken the concept of race to mean ‘population’, or abandon it as a failed biological category. I argue that Sesardic’s case for racial naturalism is only supported by his continued mischaracterisation of anti-realism about biological race and his appeal to Dobzhansky’s authority. Rather than deflating the meaning of ‘race’, it should be eliminated from our biological ontology. (shrink)

How can players reach a Nash equilibrium? I offer one possible explanation in terms of a low-rationality learning method called probe and adjust by proving that it converges to strict Nash equilibria in an important class of games. This demonstrates that decidedly limited learning methods can support Nash equilibrium play.

Lewis et al. (2011) attempted to restore the reputation of Samuel George Morton, a 19th century physician who reported on the skull sizes of different folk-races. Whereas Gould (1978) claimed that Morton’s conclusions were invalid because they reflected unconscious bias, Lewis et al. alleged that Morton’s findings were, in fact, supported, and Gould’s analysis biased. We take strong exception to Lewis et al.’s thesis that Morton was “right.” We maintain that Gould was right to reject Morton’s analysis as inappropriate and (...) misleading, but wrong to believe that a more appropriate analysis was available. Lewis et al. fail to recognize that there is, given the dataset available, no appropriate way to answer any of the plausibly interesting questions about the “populations” in question (which in many cases are not populations in any biologically meaningful sense). We challenge the premise shared by both Gould and Lewis et al. that Morton’s confused data can be used to draw any meaningful conclusions. This, we argue, reveals the importance of properly focusing on the questions asked, rather than more narrowly on the data gathered. (shrink)

Although there once was a general consensus among race scholars that applying race categories to humans is biologically illegitimate, this consensus has been erased over the past decade. This is largely due to advances in population genetics that allow biologists to pick out genetic population clusters that approximate some of our common sense racial categories. In this paper, I argue that this new ability really ought not undermine our confidence in the biological illegitimacy of the human races. Unfortunately, the claim (...) that races are biologically legitimate is ambiguous—the sense I will be concerned with here holds that the human species can be divided into biological subspecies. Sesardic and Andreasen have both argued that the cluster results are evidence for subspecies within the human population. I show the cluster results are in fact evidentially inert relative to each author’s preferred subspecies concept. I then sketch the kinds of biological facts that could be used to adjudicate whether human subspecies have existed in the past. (shrink)

Statistical reasoning is an integral part of modern scientific practice. In The Seven Pillars of Statistical Wisdom Stephen Stigler presents seven core ideas, or pillars, of statistical thinking and the historical developments of each of these pillars, many of which were concurrent with developments in biology. Here we focus on Stigler’s fifth pillar, regression, and his discussion of how regression to the mean came to be thought of as a solution to a challenge for the theory of natural selection. Stigler (...) argues that the purely mathematical phenomenon of regression to the mean provides a resolution to a problem for Darwin’s evolutionary theory. Thus, he argues that the resolution to the problem for Darwin’s theory is purely mathematical, rather than causal. We show why this argument is problematic. (shrink)

This article describes how empirical discoveries in the 1930s–1950s regarding population variation for chromosomal inversions affected Theodosius Dobzhansky and Richard Goldschmidt. A significant fraction of the empirical work I discuss was done by Dobzhansky and his coworkers; Goldschmidt was an astute interpreter, with strong and unusual commitments. I argue that both belong to a mechanistic tradition in genetics, concerned with the effects of chromosomal organization and systems on the inheritance patterns of species. Their different trajectories illustrate how scientists’ commitments affect (...) how they interpret new evidence and adjust to it. Dobzhansky was moved to revised views about selection, while Goldschmidt moved his attention to different genetic phenomena. However different, there are significant connections between the two that enrich our understanding of their views. I focus on two: the role of developmental considerations in Dobzhansky’s thought and the role of neutrality and drift in Goldschmidt’s evolutionary account. Dobzhansky’s struggle with chromosomal variation is not solely about competing schools of thought within the selectionist camp, as insightfully articulated by John Beatty, but also a story of competition between selectionist thinking and developmental perspectives. In contraposition, Goldschmidt emphasized the role of low penetrance mutations that spread neutrally and pointed out that drift could result from developmental canalization. This account adds to the dominant story about Goldschmidt’s resistance to the splitting of development from genetics, as told by Garland Allen and Michael Dietrich. The story I tell illustrates how developmental thinking and genetic thinking conflicted and influenced researchers with different convictions about the significance of chromosomal organization. (shrink)

A precise formulation of the structure of modern evolutionary theory has proved elusive. In this paper, I introduce and develop a formal approach to the structure of population genetics, evolutionary theory's most developed sub-theory. Under the semantic approach, used as a framework in this paper, presenting a theory consists in presenting a related family of models. I offer general guidelines and examples for the classification of population genetics models; the defining features of the models are taken to be their state (...) spaces, parameters, and laws. The suggestions regarding the various aspects of the characterization of population genetics models provide an outline for further detailed research. (shrink)

The aim of this paper is to further develop van Fraassen’s diagnosis, expanding a previous analysis of the fundamental law of classical genetics and the status of the so-called ‘Mendel’s laws’.6 According to this diagnosis the Hardy-Weinberg law: 1) cannot be considered as axiom (or fundamental law) for classical population genetics, since it is a law that describes an equilibrium that 2) holds only under certain special conditions, and 3) only determines a subclass of models, 4) whose generalized form (and (...) fundamental law) being shading off into logical vacuity, and 5) more complex variants of the fundamental law (and of the Hardy-Weinberg law) can be “deduced” for more realistic assumptions. In order to achieve this, I will use notions of the structuralist view of theories, a version that is related to but different from that of van Fraassen’s. These are the notions of fundamental law, specialization, and special law. Having as a background a structuralist reconstruction of classical population genetics, I will show why the Hardy-Weinberg law should not be in fact considered the fundamental law of such a theory, but a special law (and not even a “terminal” specialization, i.e. a “non-terminal” specialization). (shrink)

Biologists often define evolution as a change in allele frequencies. Consideration of the evolution of the pocket mouse will show that it is possible to have evolution without any change in the allele frequencies in a population (through change in the genotype frequencies). The implications of this for genic selectionism are then discussed. Sober and Lewontin (1982) have constructed an example to demonstrate the blindness of genic selectionism in certain cases. Sterelny and Kitcher (1988) offer a defense against these arguments (...) which assumes a conventionalist approach to populations. The example considered here will be shown to offer a more plausible and far-reaching argument against the view that alleles can always be seen as the units of selection. (shrink)

A hitherto neglected form of explanation is explored, especially its role in population genetics. “Statistically abstractive explanation” (SA explanation) mandates the suppression of factors probabilistically relevant to an explanandum when these factors are extraneous to the theoretical project being pursued. When these factors are suppressed, the explanandum is rendered uncertain. But this uncertainty traces to the theoretically constrained character of SA explanation, not to any real indeterminacy. Random genetic drift is an artifact of such uncertainty, and it is therefore wrong (...) to reify it as a cause of evolution or as a process in its own right. *Received July 2009. †To contact the author, please write to: Department of Philosophy, University of Toronto, 170 St. George St., Toronto, ON M5R 2M8, Canada; e‐mail: mohan.matthen@utoronto.ca. (shrink)

We have argued elsewhere that: (A) Natural selection is not a cause of evolution. (B) A resolution-of-forces (or vector addition) model does not provide us with a proper understanding of how natural selection combines with other evolutionary influences. These propositions have come in for criticism recently, and here we clarify and defend them. We do so within the broad framework of our own “hierarchical realization model” of how evolutionary influences combine.

How do fitness and natural selection relate to other evolutionary factors like architectural constraint, mode of reproduction, and drift? In one way of thinking, drawn from Newtonian dynamics, fitness is one force driving evolutionary change and added to other factors. In another, drawn from statistical thermodynamics, it is a statistical trend that manifests itself in natural selection histories. It is argued that the first model is incoherent, the second appropriate; a hierarchical realization model is proposed as a basis for a (...) statistical treatment. It emerges that natural selection does not cause evolution; it just is evolution. The theory incorporates relations of statistical correlation, but not the kind of causation found in fundamental physical processes. (shrink)

Population genetics attempts to measure the influence of the causes of evolution, viz., mutation, migration, natural selection, and random genetic drift, by understanding the way those causes change the genetics of populations. But how does it accomplish this goal? After a short introduction, we begin in section (2) with a brief historical outline of the origins of population genetics. In section (3), we sketch the model theoretic structure of population genetics, providing the flavor of the ways in which population genetics (...) theory might be understood as incorporating causes. In sections (4) and (5) we discuss two specific problems concerning the relationship between population genetics and evolutionary causes, viz., the problem of conceptually distinguishing natural selection from random genetic drift, and the problem of interpreting fitness. In section (6), we briefly discuss the methodology and key epistemological problems faced by population geneticists in uncovering the causes of evolution. Section (7) of the essay contains concluding remarks. (shrink)

Ernst Mayr has criticised the methodology of population genetics for being essentialist: interested only in “types” as opposed to individuals. In fact, he goes so far as to claim that “he who does not understand the uniqueness of individuals is unable to understand the working of natural selection” (1982, 47). This is a strong claim indeed especially since many responsible for the development of population genetics (especially Fisher, Haldane, and Wright) were avid Darwinians. In order to unravel this apparent incompatibility (...) I want to examine the possible sources and implications of essentialism in this context and show why the kind of mathematical analysis found in Fisher's work is better seen as responsible for extending the theory of natural selection to a broader context rather than inhibiting its applicability. (shrink)

The debate between the Mendelians and the (largely Darwinian) biometricians has been referred to by R. A. Fisher as ‘one of the most needless controversies in the history of science’ and by David Hull as ‘an explicable embarrassment’. The literature on this topic consists mainly of explaining why the controversy occurred and what factors prevented it from being resolved. Regrettably, little or no mention is made of the issues that figured in its resolution. This paper deals with the latter topic (...) and in doing so reorients the focus of the debate as one between Karl Pearson and R. A. Fisher rather than between the biometricians and the Mendelians. One reason for this reorientation is that Pearson's own work in 1904 and 1909 suggested that Mendelism and biometry could, to some extent, be made compatible, yet he remained steadfast in his rejection of Mendelism. The interesting question then is why Fisher, who was also a proponent of biometric methods, was able to synthesise the two traditions in a way that Pearson either could not or would not. My answer to this question involves an analysis of the ways in which different kinds of assumptions were used in modelling Mendelian populations. I argue that it is these assumptions, which lay behind the statistical techniques of Pearson and Fisher, that can be isolated as the source of Pearson's rejection of Mendelism and Fisher's success in the synthesis. (shrink)

Two new modes of thinking have spread through systematics in the twentieth century. Both have deep historical roots, but they have been widely accepted only during this century. Population thinking overtook the field in the early part of the century, culminating in the full development of population systematics in the 1930s and 1940s, and the subsequent growth of the entire field of population biology. Population thinking rejects the idea that each species has a natural type (as the earlier essentialist view (...) had assumed), and instead sees every species as a varying population of interbreeding individuals. Tree thinking has spread through the field since the 1960s with the development of phylogenetic systematics. Tree thinking recognizes that species are not independent replicates within a class (as earlier group thinkers had tended to see them), but are instead interconnected parts of an evolutionary tree. It lays emphasis on the explanation of evolutionary events in the context of a tree, rather than on the states exhibited by collections of species, and it sees evolutionary history as a story of divergence rather than a story of development. Just as population thinking gave rise to the new field of population biology, so tree thinking is giving rise to the new field of phylogenetic biology. (shrink)

In this essay, I argue for four related claims. First, Richard Levins’ classic “The Strategy of Model Building in Population Biology” was a statement and defense of theoretical population biology growing out of collaborations between Robert MacArthur, Richard Lewontin, E. O. Wilson, and others. Second, I argue that the essay served as a response to the rise of systems ecology especially as pioneered by Kenneth Watt. Third, the arguments offered by Levins against systems ecology and in favor of his own (...) methodological program are best construed as “pragmatic”. Fourth, I consider limitations of Levins’ arguments given contemporary population biology. (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)

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

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

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

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

This research was carried out in order to verify by simulation Mendel’s laws and seek for the clarification, from the author’s point of view, the Mendel-Fisher controversy. It was demonstrated from: the experimental procedure and the first two steps of the Hardy-Weinberg law, that the null hypothesis in such experiments is absolutely and undeniably true. Consequently, repeating hybridizing experiments as those showed by Mendel, it makes sense to expect a highly coincidence between the observed and the expected cell frequencies. By (...) simulation, 30 random samples were generated with size equal to the number of observations reported by Mendel for his single trait trial, in this case, seed shape; assuming complete dominance, with genes A and a; likewise, it was simulated the results for the experiment with two traits, segregating in separate chromosomes, in this case seed shape, as before, and albumen color, with genes B and b, both loci with complete dominance. In the case of a single trait, the data only showed evidence for rejecting the null hypothesis (Ho ) in 1/30 samples, with (P<0.05). In the case of the 30 samples of the two traits experiment, (Ho ) was rejected only on 3/30 times, when it was set a = 0.05. In both simulations there was a high correspondence between the observed and expected cell frequencies, which is simply due to the fact that (Ho ) is true, and under these conditions, that is what would to expect. It was concluded, that Mendel had no reason to manipulate his data in order to make them to coincide with his beliefs. Therefore, in experiment with a single trait, and in experiments with two traits assuming complete dominance, segregation ratios are 3:1; and 9:3:3:1, respectively. Consequently, Mendel’s laws, under the conditions as were described are absolutely valid and universal. (shrink)

H. B. D. Kettlewell's (1955, 1956) classic field experiments on industrial melanism in polluted and unpolluted settings using the peppered moth, Biston betularia, are routinely cited as establishing that the melanic (dark) form of the moth rose in frequency downwind of industrial centers because of the cryptic advantage dark coloration provides against visual predators in soot-darkened environments. This paper critiques three common myths surrounding these investigations: (1) that Kettlewell used a model that identified crypsis as the only selective force responsible (...) for the spread of the melanic gene, (2) that Kettlewell's field experiments alone established that selection for crypsis was the most important factor in the spread of melanic forms, and (3) that Kettlewell's investigations in an unpolluted wood near Dorset constituted a control for his earlier Birmingham studies (contra Hagen 1993, 1996). This analysis further identifies two features that distinguish manipulative experiments in evolutionary biology from experiments in other contexts. First, experiments in evolutionary biology rest on a wealth of information provided by strictly observational ecological studies; in the absence of such information experiments in evolutionary biology make no sense. Second, there is a trade-off between how much control investigators have over the conditions being studied and how informative the results of the experiment will be with regard to natural populations. (shrink)

: This paper explores the calibration of laboratory models in population genetics as an experimental strategy for justifying experimental results and claims based upon them following Franklin (1986, 1990) and Rudge (1996, 1998). The analysis provided undermines Coyne et al.'s (1997) critique of Wade and Goodnight's (1991) experimental study of Wright's (1931, 1932) Shifting Balance Theory. The essay concludes by further demonstrating how this analysis bears on Diamond's (1986) claims regarding the weakness of laboratory experiments as evidence, and further how (...) the calibration strategy fits within Lloyd's (1987, 1988) account of the confirmation of ecological and evolutionary models. (shrink)