Book contents
- Cladistics
- The Systematics Association Special Volume Series
- Cladistics
- Copyright page
- Dedication
- Contents
- Preface
- Acknowledgements
- Introduction: Carving Nature at Its Joints, or Why Birds Are Not Dinosaurs and Men Are Not Apes
- Part I The Interrelationships of Organisms
- Part II Systematics: Exposing Myths
- Part III The Cladistic Programme
- Part IV How to Study Classification
- 8 Modern Artificial Methods and Raw Data
- 9 How to Study Classification: Consensus Techniques and General Classifications
- 10 How to Study Classification: ‘Total Evidence’ vs. ‘Consensus’, Character Congruence vs. Taxonomic Congruence, Simultaneous Analysis vs. Partitioned Data
- 11 How to Study Classification
- 12 How to Study Classification
- Part V Beyond Classification
- Afterword
- Index
- Systematics Association Special Volumes
- References
8 - Modern Artificial Methods and Raw Data
from Part IV - How to Study Classification
Published online by Cambridge University Press: 20 July 2020
- Cladistics
- The Systematics Association Special Volume Series
- Cladistics
- Copyright page
- Dedication
- Contents
- Preface
- Acknowledgements
- Introduction: Carving Nature at Its Joints, or Why Birds Are Not Dinosaurs and Men Are Not Apes
- Part I The Interrelationships of Organisms
- Part II Systematics: Exposing Myths
- Part III The Cladistic Programme
- Part IV How to Study Classification
- 8 Modern Artificial Methods and Raw Data
- 9 How to Study Classification: Consensus Techniques and General Classifications
- 10 How to Study Classification: ‘Total Evidence’ vs. ‘Consensus’, Character Congruence vs. Taxonomic Congruence, Simultaneous Analysis vs. Partitioned Data
- 11 How to Study Classification
- 12 How to Study Classification
- Part V Beyond Classification
- Afterword
- Index
- Systematics Association Special Volumes
- References
Summary
In Chapter 2 we noted some differences between natural and artificial classifications. To recap: artificial classifications are created or imposed and often constructed so that those who do not know a particular organism are able to identify it. Natural classification is about discovery; discovering something about the natural world (of which more later). The usual kinds of artificial classifications are keys and field guides (see Chapter 2), but here we extend the term to include classifications found by using any specific method, or any specific algorithm, or any specific kind of data, even a combination of the above. This may seem an extreme position to take, one that would eliminate all methods of analysis as having any merit. This is not what we are stating and we will expand on this below, but first we begin by considering ‘sets’ of numerical methods and discussing what we understand to be their underlying philosophy. We do not intend to discuss in detail the technical workings of all those methods. As we have already noted, we are not writing a cookbook.
- Type
- Chapter
- Information
- CladisticsA Guide to Biological Classification, pp. 215 - 236Publisher: Cambridge University PressPrint publication year: 2020
References
References
References
Further Reading
Readers who are interested in ‘point-and-click’ guidance should seek other sources in addition to this book. In all honesty, we cannot recommend any of the methods discussed by these authors as they are all approaches to artificial classification rather than natural classification, the latter being the subject we are interested in. We are, therefore, a little reluctant to suggest any single book (and there are very many), but perhaps those below are at least representative of what to expect. In any case, we suggest reading them with a critical eye – if so, it should not take too long to come to the conclusion the subject, as conceived via these contributions, is ‘drowning in number’ (Williams & Ebach 2005).
Although comprehensive, now a remarkable 15 years old, it lacks some of the developments of the past decade. As far as we are aware, Felsenstein is not planning any revised version.
Each edition was reviewed extensively with mixed reception. We suggest reading a few reviews then proceed with caution.
As a further note of caution, neither of these two books discuss classification (or taxonomy) in the sense we explore in this book.
Phenetics
The best we can offer on this subject is Sokal and Sneath’s two books. These are now quite old but both worth dipping into for a comprehensive view of how phenetics began, why it began, what it hoped to achieve, how it developed and flourished under the ‘numerical taxonomy’ umbrella, and – in part – its apparent slide into ‘phylogenetics’. Above we suggested that Felsenstein’s Inferring Phylogenies should be considered the third in this series of books, a view we still hold (Williams et al. 2010). None of these books is without value, if read critically – even if that value is to understand how the first wave of numerical taxonomy lost its way, and, more crucially, how the second wave persists in misleading others.
Steussy’s book has a more up-to-date summary of phenetics.
Weighted Phenetics (Parsimony)
There are several books that focus on parsimony, as understood and implemented by the Wagner Parsimony algorithm (e.g., Farris 1983), such as Biological Systematics: Principles and Applications, which is the best available (Schuh and Brower 2009). We have listed all editions below – the 3rd edition is due in 2021 (Brower and Schuh 2021). Another recent contribution is Caetano-Anollés et al. (2018).
There are a few books that follow Willi Hennig’s original version of Phylogenetic Systematics more closely, and differ considerably from what has been called ‘modern cladistics’ (by Nixon and Carpenter, 2012a, for example). It is perhaps incorrect (and maybe inaccurate) to include them here, but we do not want these books to disappear from sight. These authors are critical of ‘modern cladistics’ as discussed above under ‘weighted phenetics’ (parsimony). It is worth noting, somewhat inexplicably, that neither Mikoleit nor Wiesemüller et al. have been translated into English. They both deserve an English translation.
Wagner Parsimony
Hennig
Weighted Phenetics (Compatibility)
Sadly, the development of compatibility methods was truncated after it was ferociously (and somewhat unfairly) attacked in the mid-1980s, mostly in the pages of Taxon (primarily between 1984 and 1986). Many empirical studies were published in Systematic Botany, and it is worth perusing back issues of that journal for examples. From the vast literature on the subject, we recommend the papers by Le Quesne (1979), Meacham (1980) and the summary in Felsenstein (1982, pp. 389–393), as they are all, if a little dated, clearly written. The Meacham & Estabrook review (1985) is also a bit dated but still worth a glance, as is Scotland & Steel (2015), for its recent discussion, and Williams & Ebach (2017), who generalise the issue. Patterson explored compatibility in terms of homology testing (1982, 1988).
It is worth noting that when reading papers on compatibility one must distinguish between the method of analysis and some of the ideas its proponents expressed about how to and what to classify. For example, their discussions concerning the necessity of ‘convex groups’ in classification is really a defence of paraphyly and promoted as support for what was referred to as ‘traditional evolutionary classification’ (Meacham & Duncan 1987, for commentary see Wiley 1981 and 2009). In this they were mistaken (see Chapters 3–5) but it should not detract from the general usefulness of the method.
Weighted Phenetics (Phylogeny – ‘Model’ Methods)
We have already mentioned the books by Felsenstein and Hall. We could add Baum and Smiths’s Tree Thinking: An Introduction to Phylogenetic Biology (Baum & Smith 2012) and Ward Wheeler’s Systematics: A Course of Lectures (Wheeler 2012). All four of these books are quite different from one another but each has extended discussions on the modelling approach and some delve into theory here and there – but caveat lector: these books primarily focus on phylogeny to the exclusion of classification. There are some philosophical contributions such as Sober (1988 and 2015, but see Brower 2017).
There are many highly technical (that is mathematical) books available, and it is beyond our ability (and stamina!) to make recommendations from this veritable mountain of literature. These are just a selection (we have resisted noting any of the numerous books on phylogenomics, see Box 10.3 for our brief comments on that topic). Interested readers who feel the urge to explore phylogenetic modelling might dip into any of the following:
Books of this kind are numerous, reading them is exhausted only by your purse, your enthusiasm or your patience – whichever is the greater. We are compelled to note that, from our perspective, there is not much to recommend here for the taxonomist. Our advice: spend your money on a field trip!