Inheritance and variation were a major focus of Charles Darwin’s studies. Small inherited variations were at the core of his theory of organic evolution by means of natural selection. He put forward a developmental theory of heredity (pangenesis) based on the assumption of the existence of material hereditary particles. However, unlike his proposition of natural selection as a new mechanism for evolutionary change, Darwin’s highly speculative and contradictory hypotheses on heredity were unfruitful for further research. They attempted to explain many (...) complex biological phenomena at the same time, disregarded the then modern developments in cell theory, and were, moreover, faithful to the widespread conceptions of blending and so-called Lamarckian inheritance. In contrast, Mendel’s approaches, despite the fact that features of his ideas were later not found to be tenable, proved successful as the basis for the development of modern genetics. Mendel took the study of the transmission of traits and its causes (genetics) out of natural history; by reducing complexity to simple particulate models, he transformed it into a scientific field of research. His scientific approach and concept of discrete elements (which later gave rise to the notion of discrete genes) also contributed crucially to the explanation of the existence of stable variations as the basis for natural selection. (shrink)

The most conspicuous form of agricultural experiment is the field trial, and within the history of such trials, the arrival of the randomised control trial is considered revolutionary. Originating with R.A. Fisher within British agricultural science in the 1920s and 30s, the RCT has since become one of the most prodigiously used experimental techniques throughout the natural and social sciences. Philosophers of science have already scrutinised the epistemological uniqueness of RCTs, undermining their status as the ‘gold standard’ in experimental design. (...) The present paper introduces a historical case study from the origins of the RCT, uncovering the initially cool reception given to this method by agricultural scientists at the University of Cambridge and the National Institute of Agricultural Botany. Rather than giving further attention to the RCT, the paper focuses instead on a competitor method – the half-drill strip – which both predated the RCT and remained in wide use for at least a decade beyond the latter’s arrival. In telling this history, John Pickstone’s Ways of Knowing is adopted, as the most flexible, and productive way to write the history of science, particularly when sciences and scientists have to work across a number of different kinds of place. It is shown that those who resisted the RCT did so in order to preserve epistemic and social goals that randomisation would have otherwise run a tractor through. (shrink)

In the early twentieth century, Wilhelm Johannsen proposed his pure line theory and the genotype/phenotype distinction, work that is prized as one of the most important founding contributions to genetics and Mendelian plant breeding. Most historians have already concluded that pure line theory did not change breeding practices directly. Instead, breeding became more orderly as a consequence of pure line theory, which structured breeding programmes and eliminated external heritable influences. This incremental change then explains how and why the large multi-national (...) seed companies that we know today were created; pure lines invited standardisation and economies of scale that the latter were designed to exploit. Rather than focus on breeding practice, this paper examines the plant varietal market itself. It focusses upon work conducted by the National Institute of Agricultural Botany during the interwar years, and in doing so demonstrates that, on the contrary, the pure line was actually only partially accepted by the industry. Moreover, claims that contradicted the logic of the pure line were not merely tolerated by the agricultural geneticists affiliated with NIAB, but were acknowledged and legitimised by them. The history of how and why the plant breeding industry was transformed remains to be written. (shrink)

Both clinical research and basic science rely on the epistemic practice of extrapolation from surrogate models, to the point that explanatory accounts presented in review papers and biology textbooks are in fact composite pictures reconstituted from data gathered in a variety of distinct experimental setups. This raises two new challenges to previously proposed mechanistic-similarity solutions to the problem of extrapolation: one pertaining to the absence of mechanistic knowledge in the early stages of research and the second to the large number (...) of extrapolations underpinning explanatory accounts. An analysis of the strategies deployed in experimental research supports the conclusion that while results from validated surrogate models are treated as a legitimate line of evidence supporting claims about target systems, the overall structure of research projects also demonstrates that extrapolative inferences are not considered definitive or sufficient evidence, but only partially justified hypotheses subjected to further testing. 1 Introduction2 Surrogate Models2.1 What exactly is a surrogate model?2.2 Why use surrogate models?3 Prior Validation of Surrogate Models3.1 The validation and ranking of surrogate models in the early stages of basic research3.2 The validation of surrogate models in later stages of basic research and in clinical research4 ‘Big Picture’ Accounts and the Extrapolations Underpinning Them4.1 The mosaic nature of mechanistic descriptions in basic science4.2 Challenges for mechanistic-similarity-based validation protocols5 Retrospective Testing of Extrapolated Knowledge5.1 Holistic confirmation5.2 Fallback strategies6 Conclusions. (shrink)

Multidisciplinary models aggregating ‘lower-level’ biological and ‘higher-level’ psychological and social determinants of a phenomenon raise a puzzle. How is the interaction between the physical, the psychological and the social conceptualized and explained? Using biopsychosocial models of pain as an illustration, I argue that these models are in fact level-neutral compilations of empirical findings about correlated and causally relevant factors, and as such they neither assume, nor entail a conceptual or ontological stratification into levels of description, explanation or reality. If inter-level (...) causation is deemed problematic or if debates about the superiority of a particular level of description or explanation arise, these issues are fueled by considerations other than empirical findings. (shrink)

A survey of models in immunology is conducted and distinct kinds of models are characterized based on whether models are material or conceptual, the distinctiveness of their epistemic purpose, and the criteria for evaluating the goodness of a model relative to its intended purpose. I argue that the diversity of models in interdisciplinary fields such as immunology reflects the fact that information about the phenomena of interest is gathered from different sources using multiple methods of investigation. To each model is (...) attached a description specifying how information about a phenomenon of interest has been acquired, highlighting points of commonality and difference between the methodological and epistemic histories of the information encapsulated in different models. These points of commonality and difference allow investigators to integrate findings from different models into more comprehensive explanatory accounts, as well as to troubleshoot anomalies and faulty accounts by going back to the original building blocks. (shrink)

Causal pluralism can be defended not only in respect to causal concepts and methodological guidelines, but also at the finer-grained level of causal inference from a particular source of evidence for causation. An argument for this last variety of pluralism is made based on an analysis of causal inference from randomized experiments (RCTs). Here, the causal interpretation of a statistically significant association can be established via multiple paths of reasoning, each relying on different assumptions and providing distinct elements of information (...) in favour of a causal interpretation. (shrink)

Current debates surrounding the virtues and shortcomings of randomization are symptomatic of a lack of appreciation of the fact that causation can be inferred by two distinct inference methods, each requiring its own, specific experimental design. There is a non-statistical type of inference associated with controlled experiments in basic biomedical research; and a statistical variety associated with randomized controlled trials in clinical research. I argue that the main difference between the two hinges on the satisfaction of the comparability requirement, which (...) is in turn dictated by the nature of the objects of study, namely homogeneous or heterogeneous populations of biological systems. Among other things, this entails that the objection according to which randomized experiments fail to provide better evidence for causation because randomization cannot guarantee comparability is mistaken. (shrink)

Examples from the sciences showing that mechanisms do not always succeed in producing the phenomena for which they are responsible have led some authors to conclude that the regularity requirement can be eliminated from characterizations of mechanisms. In this article, I challenge this conclusion and argue that a minimal form of regularity is inextricably embedded in examples of elucidated mechanisms that have been shown to be causally responsible for phenomena. Examples of mechanistic explanations from the sciences involve mechanisms that have (...) been shown to produce phenomena with a reproducible rate of success. By contrast, if phenomena are infrequent to the point that they amount to irreproducible observations and experimental results, they are indistinguishable from the background noise of accidental happenings. The inability to detect or measure the phenomenon of interest against the background noise of accidental correlations makes it impossible to elucidate a mechanism by experimental means, to demonstrate that a proposed mechanism actually produces the phenomenon, and ultimately to justify why a hypothetical scenario involving an irregular mechanism should be preferred over attributing irreproducible happenings to chance. (shrink)

This paper describes the historical background and early formation of Wilhelm Johannsen's distinction between genotype and phenotype. It is argued that contrary to a widely accepted interpretation his concepts referred primarily to properties of individual organisms and not to statistical averages. Johannsen's concept of genotype was derived from the idea of species in the tradition of biological systematics from Linnaeus to de Vries: An individual belonged to a group - species, subspecies, elementary species - by representing a certain underlying type. (...) Johannsen sharpened this idea theoretically in the light of recent biological discoveries, not least those of cytology. He tested and confirmed it experimentally combining the methods of biometry, as developed by Francis Galton, with the individual selection method and pedigree analysis, as developed for instance by Louis Vilmorin. The term "genotype" was introduced in W. Johannsen's 1909 treatise, but the idea of a stable underlying biological "type" distinct from observable properties was the core idea of his classical bean selection experiment published 6 years earlier. The individual ontological foundation of population analysis was a self-evident presupposition in Johannsen's studies of heredity in populations from their start in the early 1890s till his death in 1927. The claim that there was a "substantial but cautious modification of Johannsen's phenotype-genotype distinction" from a statistical to an individual ontological perspective derives from a misreading of the 1903 and 1909 texts. The immediate purpose of this paper is to correct this reading of the 1903 monograph by showing how its problems and results grow out of Johannsen's earlier work in heredity and plant breeding. Johannsen presented his famous selection experiment as the culmination of a line of criticism of orthodox Darwinism by William Bateson, Hugo de Vries, and others. They had argued that evolution is based on stepwise rather than continuous change in heredity. Johannsen's paradigmatic experiment showed how stepwise variation in heredity could be operationally distinguished from the observable, continuous morphological variation. To test Galton's law of partial regression, Johannsen deliberately chose pure lines of self-fertilizing plants, a pure line being the descendants in successive generations of one single individual. Such a population could be assumed to be highly homogeneous with respect to hereditary type, and Johannsen found that selection produced no change in this type. Galton, he explained, had experimented with populations composed of a number of stable hereditary types. The partial regression which Galton found was simply an effect of selection between types, increasing the proportion of some types at the expense of others. (shrink)

Agricultural experimentation is a world in constant evolution, spanning multiple scientific domains and affecting society at large. Even though the questions underpinning agricultural experiments remain largely the same, the instruments and practices for answering them have changed constantly during the twentieth century with the advent of new disciplines like molecular biology, genomics, statistics, and computing. Charting this evolving reality requires a mapping of the affinities and antinomies at work within the realm of agricultural research, and a consideration of the practices, (...) tools and social and political structures in which agricultural experiments are grounded. Three main questions will be addressed to provide an overview of the complex world of agricultural research investigated by the special issue: What is an agricultural experiment? Who is an experimenter in agriculture? Where do agricultural experiments take place? It will become apparent that agricultural experiments have a wide relevance for human development as they touch upon concerns related to human health and nutrition, contribute to policy discussions, and can affect the social and political structures in which farming is embedded. (shrink)

In addition to his experiments on selection in pure lines, Wilhelm Johannsen performed less well-known hybridisation experiments with beans. This article describes these experiments and discusses Johannsen’s motivations and interpretations, in the context of developments in early genetics. I will show that Johannsen first presented the hybridisation experiments as an additional control for his selection experiments. The latter were dedicated to investigating heredity with respect to debates concerning the significance of natural selection of continuous variation for evolution. In the course (...) of the establishment of a Mendelian research program after 1900, the study of heredity gained increasing independence from questions of evolution, and focused more on the modes and mechanisms of heredity. Further to their role as control experiments, Johannsen also saw his hybridisation experiments as contributing to the Mendelian program, by extending the scope of the principles of Mendelian inheritance to quantitative characters. Towards the end of the first decade of genetics, Johannsen revisited his experiments to illustrate the many–many relationship between genes and characters, at a time when that relationship appeared increasingly complex, and the unit-character concept, accordingly, became inadequate. For the philosophy of science, the example shows that experiments can have multiple roles in a research programme, and can be interpreted in the light of questions other than those that motivated the experiments in the first place. (shrink)

The history of twentieth-century life sciences is not exactly a new topic. However, in view of the increasingly rapid development of the life sciences themselves over the past decades, some of the well-established narratives are worth revisiting. Taking stock of where we stand on these issues was the aim of a conference in 2015, entitled “Perspectives for the History of Life Sciences”. The papers in this topical collection are based on work presented and discussed at and around this meeting. Just (...) as the conference, the collection aims at exploring fields in the history of life sciences that appear understudied, sources that have been overlooked, and novel ways of engaging with this material. The papers convened in this collection may not be representative of the field as a whole; but we feel that they do indicate some elements that have received emphasis in recent years, and may become more central in the years to come, such as the history of previously neglected contexts and domains of the life sciences, the question of continuity and change on the level of practices, the history of complexity and diversity in twentieth-century life sciences and the reconsideration of the relationship between history and philosophy of life sciences. (shrink)

Microbial diversity has become a leitmotiv of contemporary microbiology, as epitomized in the concept of the microbiome, with significant consequences for the classification of microbes. In this paper, I contrast microbiology’s current diversity ideal with its influential predecessor in the twentieth century, that of purity, as epitomized in Robert Koch’s bacteriological culture methods. Purity and diversity, the two polar opposites with regard to making sense of the microbial world, have been operationalized in microbiological practice by tools such as the “clean” (...) Petri dish versus the “dirty” Winogradsky column, the latter a container that mimics, in the laboratory, the natural environment that teems with diverse microbial life. By tracing the impact of the practices and concepts of purity and diversity on microbial classification through a history of techniques, tools, and manuals, I show the shifts in these concepts over the last century. Juxtaposing the dominant purity ideal with the more restricted, but continuously articulated, diversity ideal in microbial ecology not only provides a fresh perspective on microbial classification that goes beyond its intellectual history, but also contextualizes the present focus on diversity. By covering the period of a century, this paper outlines a revised longue durée historiography that takes its inspiration from artifacts, such as Petri dish and the Winogradsky column, and thereby simple, but influential technologies that often remain invisible. This enables the problem of historical continuity in modern science to be addressed and the accelerationist narratives of its development to be countered. (shrink)

Microbial diversity has become a leitmotiv of contemporary microbiology, as epitomized in the concept of the microbiome, with significant consequences for the classification of microbes. In this paper, I contrast microbiology’s current diversity ideal with its influential predecessor in the twentieth century, that of purity, as epitomized in Robert Koch’s bacteriological culture methods. Purity and diversity, the two polar opposites with regard to making sense of the microbial world, have been operationalized in microbiological practice by tools such as the “clean” (...) Petri dish versus the “dirty” Winogradsky column, the latter a container that mimics, in the laboratory, the natural environment that teems with diverse microbial life. By tracing the impact of the practices and concepts of purity and diversity on microbial classification through a history of techniques, tools, and manuals, I show the shifts in these concepts over the last century. Juxtaposing the dominant purity ideal with the more restricted, but continuously articulated, diversity ideal in microbial ecology not only provides a fresh perspective on microbial classification that goes beyond its intellectual history, but also contextualizes the present focus on diversity. By covering the period of a century, this paper outlines a revised longue durée historiography that takes its inspiration from artifacts, such as Petri dish and the Winogradsky column, and thereby simple, but influential technologies that often remain invisible. This enables the problem of historical continuity in modern science to be addressed and the accelerationist narratives of its development to be countered. (shrink)