In pursuit of formaldehyde: Causally explanatory models and falsification
Introduction
While for a long time the discussion of “theories” was dominant in the philosophy of science, in the last decades the literature on scientific models, as something in between theories and rules of the thumb, has proliferated enormously.1 In this paper, we focus on causal models. These models explain sequences of events by spelling out the relevant factors which produce the effects in question and define their relationships to each other. We take the appropriate visual representation of such models to be causal graphs consisting of a network of nodes (which indicate causal factors) and directed edges (which indicate causal relationships). Prime examples of this type of model are biochemical pathways, which perhaps not coincidentally are frequently depicted as graphs by the scientists themselves. Biochemical pathways describe the stepwise development of products out of a series of starting materials; they may take the form of a long chain of reactions or the form of a cycle; they are often very complex, while for many purposes simplified versions do well, since they can be expanded as occasion and knowledge demand (while the absence of a factor in the modelled pathway does not imply the factor’s irrelevance). How these pathways are established from experimental results, how they are modified and adapted is, therefore, of tremendous interest if one wants to learn more on the question how scientific models are construed—and under which circumstances they are abandoned.
The latter question is studied in this paper by the example of an episode taken from the long-winded search for the biochemical pathway of photosynthesis. This process in which solar energy is converted into energy that can be used biochemically is fundamental to life on earth, and the way organisms accomplish this task has intrigued scientists for more than two centuries. Yet still around 1900, photosynthesis was basically a black box, the internal mechanism of which was totally obscure. Scientists knew the starting materials and the products of the process, but they had only vague hypotheses of what happened in between.2 The model which most scientists favoured at the end of the nineteenth century was the formaldehyde model of photosynthesis. Originally suggested in 1870, it dominated the field until the 1930s, that is, for sixty years, although alternative models had always been debated.3 The puzzling fact is that the model remained dominant despite of the fact that none of the almost innumerable attempts to conclusively demonstrate the presence of the key intermediate—formaldehyde—in the green parts of plants, had ever been successful. From the point of view of traditional philosophy of science, these failures should have counted as an instance of fatal falsification, if ever there was one.
We shall argue that this way of thinking reveals a serious misconception of the nature of the underlying explanatory model. If models of biochemical pathways, such as the photosynthetic production of glucose, are understood as a framework of causal hypotheses (as opposed to simple conditionals), it becomes immediately clear why they cannot be falsified by negative empirical results. This impasse is closely related to Pierre Duhem’s well-known non-falsifiability thesis. Duhem drew attention to the fact that it is impossible to test (and reject) a specific hypothesis in isolation, since empirical predictions are always based on an entire system or group of hypotheses, and, on top of that, the derivation requires a number of auxiliary hypotheses concerning the experimental setup. Therefore, the well-targeted falsification of one specific hypothesis is rendered impossible.4 Despite this powerful criticism, philosophy of science for a long time favoured falsificationism as the best—in fact, the only—way to advance empirical science, in line with the influential suggestions by Karl Popper.5 This tradition, however, also thought of scientific hypotheses as universal conditionals, whereas we would like to suggest, in contrast, that they are causal hypotheses.
Falsifying a causal hypothesis requires to prove a factor’s irrelevance for an effect. However, from the point of view of causal reasoning, this is impossible to do. It would require a complete grasp of the causal structures underlying the effect in question and this clearly is something human beings cannot even hope to achieve In contrast to this difficulty, there are well-trodden ways to constructively establish causal hypotheses—which, incidentally, is also far more interesting and useful than the demonstration of what is wrong.
Section snippets
Accepted body of knowledge
We shall start by introducing some background to the example discussed in this paper. The well-known equation for oxygenic photosynthesis formulates the process as follows:
This equation, which was defined in the nineteenth century, contains the commonly held core assumptions on the processes of photosynthesis that were considered beyond dispute: that carbon dioxide and water (or the combination of these compounds in form of carbonic acid) are the starting materials of the
The model
The formaldehyde model was first put forward in 1870 by the German organic chemist Adolf von Baeyer (1835–1917).8 One of the most eminent figures of his time, Baeyer is particularly renowned for his research on the plant dye indigo: Baeyer successfully synthesised this important dye in the test tube in 1880, and by 1883 he had completely elucidated the molecule’s structure. (Baeyer was awarded the Nobel Prize in
Causal reasoning from experimental results
We mentioned in the introduction that we take explanatory models, such as the formaldehyde model, to be aptly represented by causal graphs: complex (but partial) networks of nodes (causal factors) and directed edges (causal relationships between nodes). The only way to reliably establish causal hypotheses is by conducting difference tests, which are frequently carried out in the form of experiments. A difference test realises two situations which comply with the homogeneity condition: they are
The meaning of negative results
In addition to the attempts to prove formaldehyde’s existence in plants, that is, the instantiation of this factor, scientists also tried hard to prove its causal effect on photosynthesis. One can derive from the formaldehyde model the following hypothesis: “Since formaldehyde is a key intermediate in photosynthetic assimilation, the presence of formaldehyde should lead to the photosynthetic formation of glucose (while no glucose should be produced if formaldehyde is absent).” This hypothesis
Why the model was dropped eventually
Although the hunting for formaldehyde went on for decades, it did not go on forever. Eventually, the model was dropped; but this was not due to any process of falsification. By the end of the 1930s, two decisive developments had taken place. First, the thermodynamic side of the process had become the subject of study; and it became increasingly difficult to reconcile the formaldehyde model—which was relatively costly, energetically speaking—with the amount of energy available for the process.
Concluding remarks
How explanatory models of causal processes are construed, modified and eventually abandoned, such as the model of the biochemical pathway of photosynthesis, is one of the central questions of the philosophy of science. Much can be learned about these issues from the reconstruction of actual case studies from the history of science; and one example was given in this paper. With hindsight, the formaldehyde model of photosynthesis was completely flawed. It was far too simplistic; furthermore,
Acknowledgements
We would like to thank Raphael Scholl (Bern) who provided helpful comments on an earlier draft and to Margareta Simons (Lucerne) who edited the manuscript.
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