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Dynamic homology and circularity in cladistic analysis

Abstract

In this article, I examine the issue of the alleged circularity in the determination of homologies within cladistic analysis. More specifically, I focus on the claims made by the proponents of the dynamic homology approach, regarding the distinction (sometimes made in the literature) between primary and secondary homology. This distinction is sometimes invoked to dissolve the circularity issue, by upholding that characters in a cladistic data matrix have to be only primarily homologous, and thus can be determined independently of phylogenetic hypotheses, by using the classical Owenian criteria (for morphological characters) or via multiple sequence alignment (for sequence data). However, since in the dynamic approach, sequence data can be analyzed without being pre-aligned, proponents have claimed that the distinction between primary and secondary homology has no place within cladistics. I will argue that this is not the case, since cladistic practice within the dynamic framework does presuppose primary homology statements at a higher level.

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Notes

  1. In this article, I focus on cladistic (i.e. maximum parsimony) approaches to phylogenetic reconstruction, leaving out other currently used methods such as maximum likelihood and Bayesian analysis. However, much of what I will say here will be applicable to those methods as well, since the dynamic homology approach has been applied to them as well (e.g. Wheeler 2006 for likelihood, Herman et al. 2014 for Bayesian inference). With the term ‘cladistics’ I am referring solely to the method of phylogenetic reconstruction, not to any views about classification (see Quinn 2017 for the various uses of the term).

  2. A similar point has been raised regarding the concept of adaptation, see e.g. Ginnobili (2018, pp. 26–31) and references therein.

  3. This corresponds to what Martin et al. (2010) call a node-based reading of phylogenetic trees; those authors show that there are other, equivalent, ways of interpreting trees. There has also been some discussion over whether cladograms and phylogenetic trees are equivalent, and what each represents (see e.g. Platnick 1977; Wiley 1979). I shall not go into these nuances, since they will not affect my points.

  4. If more than one tree has the same minimum length, then cladists will not typically choose one among them arbitrarily. Instead, they will present some consensus tree between all the optimal trees. For instance, the strict consensus tree will only contain the groups that are present in all the optimal trees (see Kitching et al. 1998, chapter 7).

  5. Again, there are many possible complications here, which do not always allow one to get a single optimal homology scheme. For instance, as mentioned above, cladistic analysis can yield more than one optimal tree, and those different trees can imply different homology schemes. Additionally, even a single tree can imply more than one possible scheme of homologies. For example, the tree in Fig. 2b can also be optimized by putting a 0 in all internal nodes, changing the homology scheme implied by it. I will not dig any deeper into these issues, since the general point made above will be enough for my purposes.

  6. This terminology is by de Pinna (1991), the article that has become an obligated reference on the subject. It can also be found (in some cases before de Pinna’s publication, as he himself acknowledges) as homology versus homogeny (Lankester 1870); hypotheses of homology versus homology (Patterson 1988); topographical correspondence versus homology (Rieppel 1988); etc. What I aim to show in this article is that dynamic analyses presuppose a data matrix that is built using the same (topological, compositional, etc.) criteria than those used in classical two-step analyses. Whether one calls the characters resulting from the application of these criteria homologies, primary homologies, hypotheses of homology or something that does not contain the term ‘homology’ at all (e.g. topographical correspondences) is irrelevant to my point. For simplicity’s sake, I will continue using de Pinna’s terminology.

  7. To clarify, in my view, secondary homologies are traits derived from a common ancestor, and cladistic analysis gives one way (but not the only way) of operationalizing this concept. Others might wish to directly define secondary homologies as the output of the method. Although interesting, this discussion has no impact on the conclusions drawn in this paper.

  8. In a static setting, characters can be revised after phylogenetic analysis has taken place, by recoding the data matrix that was used as its input and analyzing it again. This is a common characteristic of all science: one can revise the data after seeing how well they fare against the theoretical analysis of it (confirmation holism taught us this long ago). But what dynamic analyses do is different, they are effectively changing the theoretical analysis itself, and how it treats the data.

  9. The main (practical) disadvantage of the DO method is that it is computationally much more intensive than the traditional methodology.

  10. I am not claiming that individual sites are not characters, in the wider sense of characteristics that the study taxa possess, and that can therefore be compared and homologized (see above). I only state that, in a DO setting, the input matrix does not contain site-characters but rather loci-characters.

  11. The conceptual and mathematical apparatus used by Vogt is rather complex, and a fuller introduction and examination of it fall outside the scope of this article.

  12. All of this is not to deny that reciprocal illumination is a real phenomenon. As Hennig himself recognized (Hennig 1966, p. 21), it is not a phenomenon exclusive to phylogenetics. In all areas of science theories are tested through certain evidence, and at the same time the evidence can be modified to fit the theory. For example, if a theoretical prediction fails, one way to proceed is by revising the observations (either the initial conditions or the “observational” consequences), the measuring instruments, the auxiliary hypotheses, etc. In the philosophical literature this has long been known as confirmation holism. However, the occurrence of this phenomenon does not deny that the concepts in the explanandum of a theory have to be determinable independently of the theory for which they are explananda, on pain of circularity (as the structuralist school has long argued, and shown to be the case with multiple reconstructions of theories, see Balzer et al. 1987).

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Acknowledgements

I thank Martín Ramírez and three anonymous reviewers for commenting on an earlier version of the manuscript. This work has been funded by the research Projects PUNQ 1401/15 and SAI 827-223/19 (Universidad Nacional de Quilmes, Argentina), UNTREF 32/15 255 (Universidad Nacional Tres de Febrero, Argentina) and UBACyT 20020170200106BA (Universidad de Buenos Aires, Argentina).

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Correspondence to Ariel Jonathan Roffé.

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Roffé, A.J. Dynamic homology and circularity in cladistic analysis. Biol Philos 35, 21 (2020). https://doi.org/10.1007/s10539-020-9737-4

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Keywords

  • Homology
  • Circularity
  • Cladistics
  • Dynamic homology
  • Multiple sequence alignment
  • Direct optimization