On growth and form in the "computer era": from geometric to biological morphometrics
Andrea Cardini 1  
,   Anna Loy 2
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Dipartimento di Scienze Chimiche e Geologiche, Università di Modena e Reggio Emilia, l.go S. Eufemia 19, 41121 Modena, Italy; Centre for Anatomical and Human Sciences, Hull York Medical School, University of Hull, Cottingham Road, Hull, HU6 7RX, UK and Centre for Forensic Science, The University of Western Australia, 35 Stirling Highway, Crawley WA 6009, Australia
Dipartimento Bioscienze e Territorio, Università del Molise, I-86090 Pesche
Publication date: 2013-06-13
Hystrix It. J. Mamm. 2013;24(1):1–5
Almost 100 years after the publication of Thompson's seminal book "On growth and form", the study of animal morphology is becoming again central to biology. This is also thanks to the development of powerful computerized quantitative methods for statistical shape analysis, collectively known as geometric morphometrics (GM). GM was announced as a revolution just two decades ago. The "revolution" is now a standard tool in numerical analyses of phenotypic variation in mammals and other organisms. Hundreds of studies are published every year that take advantage of GM (e.g., more than 800 entries in Google Scholar only for 2012). We celebrate the 20t anniversary of the "revolution in morphometrics" (Rohlf and Marcus, 1993, p. 129) with the publication of a "Yellow Book", a special issue of Hystrix dedicated to Evolutionary Morphometrics and Virtual Morphology. A series of 14 papers by leading morphometricians summarizes the main achievements in GM (surface methods, comparative shape analysis, phenotypic trajectories quantification, modularity/integration, the use of R in morphometrics), describes its most innovative developments (ecometrics, eigensound analysis, biomechanical GM), and discusses common misunderstandings of well extablished methods (visualization of shape differences). Besides celebrating the success of statistical shape analysis in biology, this issue aims at introducing to GM readers unfamiliar with or intimidated by its strong numerical background. This is why, as Editors, we asked all contributors to provide concise and accurate but also clear and simple descriptions of techniques and applications. We hope that we succeeded in this aim, and wish that this Yellow Book may help to tighten the connection between biologists and statisticians for a truly "biological" GM.