Book Reviews Syst. Biol. 64(2):363–365, 2015 © The Author(s) 2014. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email:
[email protected] DOI:10.1093/sysbio/syu092 Advance Access publication November 21, 2014
The Book of Trees: Visualizing Branches of Knowledge. By Manuel Lima. New York: Princeton Architectural Press, 2014. 208 pp. ISBN 978-1-61689-218-0 $29.95. £18.99 (hardback).
Trees can be many things: objects, art, symbols, or information. As objects, trees act as homes and shelter, they provide food and oxygen, and they bind soil to hold topography in place. You can read about this in any biology textbook. Trees have also had a long tradition in the visual arts. To me, perhaps the most interesting books about trees as art are those by Fowles and Horvat (1979) and by Shyam et al. (2006). The former is a disquisition by novelist John Fowles on the connection between the natural world and human creativity, accompanied by moody photographs of trees taken by Frank Horvat. The latter book is a series of hand-lithographed prints of tribal art images from three Gond people of central India (Bhajju Shyam, Durga Bai, and Ramsingh Urveti). (And yes, the land of the Gond is Gondwanaland, which was the source of our name for the southern land masses.) The most famous use of trees as symbols is the Tree of Life, which recurs in many cultures throughout the world, and which you can read about in Cook (1974). It often appears as a World Tree, which supports the heavens, thereby connecting the heavens, the human world, and (through its roots) the underworld. This motif has appeared in specific forms in many cultures, including Assyrian, Akkadian, Sumerian, Babylonian, Egyptian, Ancient Greek, Nordic (Norse), Celtic, Olmec, Aztec, Mayan, Buddhist, Tibetan, Hindu, and Siberian, among others. The Biblical Tree of Life, on the other hand, was actually the lignum vitae (Tree of Eternal Life) not the arbor vitae (Tree of Life). It was explicitly contrasted with the lignum scientiae boni et mali (Tree of Knowledge of Good and Evil), from which Adam and Eve ate the forbidden fruit, and were thereby ejected from Eden. This Biblical imagery was later co-opted as the arbor scientiae (Tree of Knowledge), starting with the Porphyrian tree in the third-century AD (although there are no extant copies from that time). That is, knowledge can often be arranged like the branches of a tree; and indeed, that metaphor has come down to us today
Downloaded from http://sysbio.oxfordjournals.org/ by David Morrison on February 19, 2015
Design for Information: An Introduction to the Histories, Theories, and Best Practices Behind Effective Information Visualizations. By Isabel Meirelles. Beverly MA: Rockport Publishers, 2013. 224 pp. ISBN 978-1-59253-806-5 $40.00 (paperback).
when referring to the different “branches” of human knowledge (e.g., branches of science). For example, Joachim of Fiore used the tree as a metaphor for historical relationships in his Liber Figurarum of 1202 (Hestmark 2000), a book whose exquisite prints could easily have been included above under “art.” In his book Arbor Scientiae Venerabilis et Cælitus of 1295, Ramón Llull used the tree to illustrate the growth and inter-relationships of knowledge more generally (Gontier 2011; Kutschera 2011). It is with this role of trees as illustrations of information that the two review books concern themselves. They thus represent the latest manifestations of a very long tradition involving visualizations of human knowledge. The tree is probably the most ubiquitous and longlasting of our visual metaphors, illustrating the relations between objects as well as the relations between concepts. In the modern world the Tree of Knowledge has been greatly generalized, so that trees are now both visual and mathematical representations of the relationships among pieces of information. There is thus much that is new for these two authors to discuss, because computers and new algorithmic models have produced an array of new methods and designs. The book by Manuel Lima (The Book of Trees) focuses on trees exclusively, although some of them you may not have recognized as trees. The book is arranged by type of tree: Figurative trees, Vertical trees, Horizontal trees, Multidirectional trees, Radial trees, Hyperbolic trees, Rectangular treemaps, Voronoi treemaps, Circular treemaps, Sunbursts, and Icicle trees. A tree is defined as representing hierarchically structured information, and therefore any such representation can be called a “tree,” including things that look more like maps and Venn diagrams than like traditional trees. Each chapter is arranged chronologically, which acknowledges the historical milieu noted above (covering more than 500 years). This means that the information being represented is not arranged by context, and thus conceptual themes recur throughout the book rather than being consolidated. For example, phylogenetic trees have historically been drawn as figurative, vertical, horizontal, multidirectional, radial, or hyperbolic (the latter being restricted to interactive trees), and so phylogenetic trees are illustrated throughout the book. Moreover, some trees could easily fit into more than one chapter, such as the horizontal trees on pp. 98–101, which could as easily be seen as multidirectional. This means that the book provides only a visual overview of trees, rather than providing some sort of
363
[17:56 3/2/2015 Sysbio-syu092.tex]
Page: 363
363–367
364
SYSTEMATIC BIOLOGY
[17:56 3/2/2015 Sysbio-syu092.tex]
(timelines and flows), Spatial structures (maps), Spatiotemporal structures, and Textual structures. Meirelles thus paints a much broader picture of data visualization and information design than does Lima, with trees as merely one possible iconography—in terms of coverage her book is broader but shallower. Meirelles also has a much stronger pedagogic philosophy than does Lima. Representing multidimensional information in two dimensions is not trivial, and Meirelles’ goal is to provide a combined discussion of the technical requirements and the design aspects of such visualizations. She insists that “understanding the constraints and capabilities of cognition and visual perception is essential” (p. 9), because her emphasis is on design rather than information. Her writing thus focuses much more on the theory, while still insisting that it is successful practice that is the ultimate goal. Phylogenetic diagrams are few in her book, and all of them are gathered in the chapter on trees. Surprisingly, none of the examples used appear in the book by Lima. As an aside, I am not sure that either author actually understands phylogenetic trees. For example, one of Lima’s labels starts with: “One of the first phenetic diagrams, also known as ‘cladograms,’ produced by numerical methods” (p. 103). (This figure was allegedly published in something called the “Oxford Journal of Systematic Biology”, which you and I know as Systematic Zoology; this is far from the only bibliographic error in his book.) Furthermore, neither author shows any interest in anthropology in either of its venerable guises as linguistics (language studies) or stemmatology (manuscript studies), both of which have long used trees to represent genealogies sensu lato. Interestingly, Meirelles shows that treemap methods were used in systematics long before the invention of computers (Lima notes only that they first appeared in cartography in 1845). Indeed, we can produce a treemap if we simply cut horizontal slices out of a vertical tree, as shown on p. 28 of Design for Information, which reproduces Maximilian Fürbringer’s (1888) tree of bird relationships. On the left is the side view of the tree, and on the right are three slices through the tree branches (as viewed from above). The latter produces a circular treemap, which is admittedly a less efficient use of the visualization space compared to a rectangular one. In spite of the chapter on relational structures, phylogenetic networks do not explicitly appear in Meirelles book, which I personally consider to be a major, if forgivable, oversight. The book’s networks are strictly of the type that connects observed nodes via observed links, rather than connecting observed (leaf) nodes via inferred (internal) nodes and inferred links. That is, none of them use the network to represent temporal relationships, let along evolutionary ones. Nevertheless, phylogenetic networks of a sort do appear in the book. A network is not a nested hierarchy, but instead involves a collection of overlapping sets. This can be represented as a Venn diagram, for example, but not as a treemap. This form of visualization has
Page: 364
Downloaded from http://sysbio.oxfordjournals.org/ by David Morrison on February 19, 2015
critical commentary and intellectual review. The book simply starts with one type of tree diagram and ends with another type. This is the book’s biggest weakness— it focuses on the visual characteristics and historical circumstances, rather than on the theoretical aspects. I strongly felt the lack of a critical overview of what trees can and cannot do in terms of representing information. A tree can be a clever way of displaying data, but that does not mean that it is necessarily a clear way of displaying it, and this distinction is insufficiently emphasized in the book. It is thus important to recognize that a beautifullooking tree does not necessarily represent information accurately. As but one recent example, D’Efilippo and Ball (2013) produce a classic Tree of Life drawn as a real tree (as inaugurated by Haeckel 1866). Unfortunately, quite a number of the taxonomic labels are misplaced, and we are therefore treated to some rather surprising pieces of alleged phylogenetic and systematic information. Nevertheless, Lima’s book does present us with a pictorial buffet of the sheer variety of Trees of Knowledge, both in terms of what they can look like and what information they can convey. The oldest images are the most beautiful, of course, as modern ones have become more stylized, adhering to Edward Tufte’s dictum that information is most clearly displayed by using the minimum amount of ink possible. I think that Tufte is right in general, but I do miss the old, more discursive, style. The treemaps are probably the tree images that are most unfamiliar to systematists and phylogeneticists, who have traditionally favored lines to display informational connections (i.e., the “node-link” tree layout), rather than using nested areas (i.e., space filling) to represent hierarchical information. Nevertheless, this is what treemaps do—each branch of the tree is given an area, which is then tiled with smaller areas representing sub-branches. The main advantage of using a map as a representation is that the size and color of the areas can be used to represent other information about each tree leaf. This idea has, on occasion, been adopted in biology. For example, taxonomic hierarchies are sometimes represented using a treemap, such as in the web database BioNames (which displays the taxonomic groups recognized by the Index to Organism Names database), and the Natural Science Museum of Barcelona (which allows interactive access to the database records via a taxonomic hierarchy). It has also been used to display the gene ontology associated with gene expression data from microarray studies (Baehrecke et al. 2004) as well as other ’omics data. It has even been suggested that treemaps could be used to represent phylogenetic trees (Arvelakis et al. 2005). Trees and treemaps also appear in the book by Isabel Meirelles (Design for Information), although this book covers much more than that. This time the book is arranged by subject: Hierarchical structures (trees), Relational structures (networks), Temporal structures
VOL. 64
363–367
2015
BOOK REVIEWS
REFERENCES Arvelakis A., Reczko M., Stamatakis A., Symeonidis A., Tollis I.G. 2005. Using treemaps to visualize phylogenetic trees. LNCS 3745:283–293.
Baehrecke E.H., Dang N., Babaria K., Shneiderman B. 2004. Visualization and analysis of microarray and gene ontology data with treemaps. BMC Bioinform. 5:84. Cook R. 1974. The Tree of Life: image for the cosmos. London: Thames & Hudson. D’Efilippo V., Ball J. 2013. The infographic history of the world. London: HarperCollins. Fowles J., Horvat F. 1979. The tree. London: Aurum Press. Fürbringer M. 1888. Untersuchungen zur Morphologie und Systematik der Vögel. T.J. Amsterdam: van Holkema. Goldfuss G.A. 1817. Über de Entwicklungsstufen des Thieres. Nürnberg: Leonhard Schrag. Gontier N. 2011. Depicting the Tree of Life: the philosophical and historical roots of evolutionary tree diagrams. Evol. Educ. Outreach 4:515–538. Haeckel E. 1866. Generelle Morphologie der Organismen. Berlin: G. Reimer. Hestmark G. 2000. Temptations of the tree. Nature 408:911. Kutschera U. 2011. From the scala naturae to the symbiogenetic and dynamic tree of life. Biol. Direct 6:33. Shyam B., Bai D., Urveti R. 2006. The night life of trees. Chennai, India: Tara Books. Swainson W. 1837. On the natural history and classification of birds. London: Longman et al.
David A. Morrison, Systematic Biology, Evolutionary Centre, Norbyvägen 18D, 752 36 Uppsala, Sweden;
[email protected]
Biology E-mail:
Syst. Biol. 64(2):365–367, 2015 © The Author(s) 2014. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email:
[email protected] DOI:10.1093/sysbio/syu127 Advance Access publication December 22, 2014
Homology, Genes, and Evolutionary Innovation. Günter P. Wagner. Princeton: Princeton University Press, 2014. xv+478 pp. ISBN: 978-0-691-15646-0 $60.00 £41.95 (hardback). Günter Wagner has produced a magisterial treatment of one of the truly fundamental concepts in evolutionary biology—homology. Homology is also one of the most controversial topics in biology, and tends to mean different things to different types of biologists. In molecular biology, homology is sometimes used as a synonym for “similarity,” for example stating that two genes in different organisms are “77% homologous” when their DNA sequences show 77% similarity. To evolutionary biologists, this is like stating that someone is “42% married,” because we tend to think of homology as either/or statements—two structures are either homologous or not. This is just one example of how different biologists use the term homology in very different ways because it is hard to identify how two parts can be homologous in spite of differences in form, function, and underlying genetic mechanisms. Günter Wagner has thought long and hard about homology in relation to character identity, and in his new book he goes into great detail about why we
[17:56 3/2/2015 Sysbio-syu092.tex]
should use character identity as the basis for the homology of morphological characters. For readers of Systematic Biology, the book is also a reminder that every morphological character used in a phylogenetic analysis is a hypothesis of homology, and that great care is needed when deciding whether morphological characters in different organisms are likely to be homologs. Wagner’s wide-ranging book is divided into two parts with 13 chapters (plus Preface and Introduction). Part I covers Concepts and Mechanisms and consists of: Chapter 1 The Intellectual Challenge of Morphological Evolution: A Case for Variational Structuralism, Chapter 2 A Conceptual Roadmap to Homology, Chapter 3 A Genetic Theory of Homology, Chapter 4 Evolutionary Novelties: The Origin of Homologs, Chapter 5 Developmental Mechanisms for Evolutionary Novelties, Chapter 6 The Genetics of Evolutionary Novelties, and Chapter 7 The Long Shadow of Metaphysics on Research Programs. Having laid the conceptual foundation, the author then, in Part II, surveys examples that serve to illustrate how the concepts developed in Part I can be used in empirical research programs. Part II thus covers Paradigms and Research Programs, including: Chapter 8 Cell Types and Their Origins, Chapter 9 Skin and a Few of Its
Page: 365
Downloaded from http://sysbio.oxfordjournals.org/ by David Morrison on February 19, 2015
also been a longstanding suggestion in phylogenetics. Two of these appear in the book. One is Goldfuss’ (1817) set of nested egg-shaped sets, expressing his ideas about affinity relationships, with one set overlapping several of the others, representing a nonnested series of relationships. The other is Swainson’s (1837) quinarian figure of nonoverlapping sets, expressing his ideas about multidimensional affinity relationships. Oddly, both figures are in the Hierarchy chapter not the Relational one, presumably reflecting the nested part of their information rather than the concomitant reticulate information. Both books, by Lima and Meirelles, are beautifully produced in full color, and the images dominate rather than the text. If you do not mind the limited range of iconography, then these books can be viewed as being about art just as much as information. That is, they show us infographics in the original sense, before people started putting cute cartoons all over them to distract attention from the actual information. I recommend both books as a feast for sore scientific eyes.
365
363–367
