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Does my posterior look big in this? The effect of photographic distortion on morphometric analyses

  • Katie S. Collins (a1) and Michael F. Gazley (a2)
Abstract
Abstract

Most geometric morphometric studies are underpinned by sets of photographs of specimens. The camera lens distorts the images it takes, and the extent of the distortion will depend on factors such as the make and model of the lens and camera and user-controlled variation such as the zoom of the lens. Any study that uses populations of geometric data digitized from photographs will have shape variation introduced into the data set simply by the photographic process. We illustrate the nature and magnitude of this error using a 30-specimen data set of Recent New Zealand Mactridae (Mollusca: Bivalvia), using only a single camera and camera lens with four different photographic setups. We then illustrate the use of retrodeformation in Adobe Photoshop and test the magnitude of the variation in the data set using multivariate Procrustes analysis of variance. The effect of photographic method on the variance in the data set is significant, systematic, and predictable and, if not accounted for, could lead to misleading results, suggest clustering of specimens in ordinations that has no biological basis, or induce artificial oversplitting of taxa. Recommendations to minimize and quantify distortion include: (1) that studies avoid mixing data sets from different cameras, lenses, or photographic setups; (2) that studies avoid placing specimens or scale bars near the edges of the photographs; (3) that the same camera settings are maintained (as much as practical) for every image in a data set; (4) that care is taken when using full-frame cameras; and (5) that a reference grid is used to correct for or quantify distortion.

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Adams D. C., and Otárola-Castillo E.. 2013. geomorph: an R package for the collection and analysis of geometric morphometric shape data. Methods in Ecology and Evolution 4:393399.
Aguirre M. L., Perez S. I., and Sirch Y. N.. 2006. Morphological variability of Brachidontes Swainson (Bivalvia, Mytilidae) in the marine Quaternary of Argentina (SW Atlantic). Palaeogeography, Palaeoclimatology, Palaeoecology 239:100125.
Aguirre M. L., Richiano S., Alvarez A., and Farinati E. A.. 2016. Reading shell shape: implications for palaeoenvironmental reconstructions. A case study for bivalves from the marine Quaternary of Argentina (south-western Atlantic). Historical Biology 28:753773.
Anderson M. J. 2001. A new method for non-parametric multivariate analysis of variance. Austral Ecology 26:3246.
Anderson M. J., and Ter Braak C. J. F.. 2003. Permutation tests for multi-factorial analysis of variance. Journal of Statistical Computation and Simulation 73:85113.
Arnqvist G., and Martensson T.. 1998. Measurement error in geometric morphometrics: empirical strategies to assess and reduce its impact on measures of shape. Acta Zoologica Academiae Scientarium Hungaricae 44(1–2), 7396.
Bookstein F. L. 1991. Morphometric tools for landmark data: geometry and biology. Cambridge University Press, Cambridge.
Bookstein F. L. 1997. Landmark methods for forms without landmarks: morphometrics of group differences in outline shape. Medical Image Analysis 1:225243.
Clouse R. M., de Bivort B. L., and Giribet G.. 2009. A phylogenetic analysis for the South-east Asian mite harvestman family Stylocellidae (Opiliones: Cyphophthalmi)—a combined analysis using morphometric and molecular data. Invertebrate Systematics 23:515529.
Collins K. S., Crampton J. S., and Hannah M.. 2013. Identification and independence: morphometrics of Cenozoic New Zealand Spissatella and Eucrassatella (Bivalvia, Crassatellidae). Paleobiology 39:525537.
Collins K. S., Crampton J. S., and Hannah M.. 2014. Stratocladistic analysis and taxonomic revision of the character-poor New Zealand crassatellid bivalves Spissatella and Eucrassatella . Journal of Molluscan Studies 81:104123.
Cox G. C. 2007. Optical imaging techniques in cell biology. CRC/Taylor & Francis, Boca Raton, Fla.
Cromey D. W. 2010. Avoiding twisted pixels: ethical guidelines for the appropriate use and manipulation of scientific digital images. Science and Engineering Ethics 16:639667.
de Bivort B. L., Clouse R. M., and Giribet G.. 2010. A morphometrics-based phylogeny of the temperate Gondwanan mite harvestmen (Opiliones, Cyphophthalmi, Pettalidae). Journal of Zoological Systematics and Evolutionary Research 48:294309.
Fink W. L., and Zelditch M. L.. 1995. Phylogenetic analysis of ontogenetic shape transformations: a reassessment of the piranha genus Pygocentrus (Teleostei). Systematic Biology 44:343360.
Gómez G. F., Márquez E. J., Gutiérrez L. A., Conn J. E., and Correa M. M.. 2014. Geometric morphometric analysis of Colombian Anopheles albimanus (Diptera: Culicidae) reveals significant effect of environmental factors on wing traits and presence of a metapopulation. Acta Tropica 135:7585.
Goodall C. 1991. Procrustes methods in the statistical analysis of shape. Journal of the Royal Statistical Society B 53:285339.
Gray J. E. 1837. A synoptical catalogue of the species of certain tribes or genera of shells contained in the collection of the British Museum and the author’s cabinet; with descriptions of the new species. Magazine of Natural History and Journal of Zoology, Botany, Geology, and Mineralogy, new series 1:370376.
Kahle D., and Wickham H.. 2013. ggmap: spatial visualization with ggplot2. R Journal 5:144161. http://journal.r-project.org/archive/2013-1/kahle-wickham.pdf, accessed 30 October 2016.
Klingenberg C. P., and Gidaszewski N. A.. 2010. Testing and quantifying phylogenetic signals and homoplasy in morphometric data. Systematic Biology 59:245261.
Márquez F., Robledo J., Peñaloza G. E., and Van der Molen S.. 2010. Use of different geometric morphometrics tools for the discrimination of phenotypic stocks of the striped clam Ameghinomya antiqua (Veneridae) in north Patagonia, Argentina. Fisheries Research 101:127131.
Monteiro L. R., Di Benetto A. P. M., Guillermo L. H., and Rivera L. A.. 2005. Allometric changes and shape differentiation of sagitta otoliths in sciaenid fishes. Fisheries Research 74:288299.
Muir A. M., Vecsei P., and Krueger C. C.. 2012. A perspective on perspectives: methods to reduce variation in shape analysis of digital images. Transactions of the American Fisheries Society 141:11611170.
Perez S. I., Bernal V., and Gonzalez P. N.. 2006. Differences between sliding semi-landmark methods in geometric morphometrics, with an application to human craniofacial and dental variation. Journal of Anatomy 208:769784.
R Core Team 2016. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org, accessed 30 March 2016.
Reeve L. A. 1854. Monograph of the genus Mactra. Conchologia Iconica; or, illustrations of the shells of molluscous animals, Vol. 8. London, published by author.
Rohlf F. J. 2005. tpsDig: digitize landmarks and outlines, Version 2.05. Department of Ecology and Evolution, State University of New York at Stony Brook.
Tsai C.-H., and Fordyce R. E.. 2014. Disparate heterochronic processes in baleen whale evolution. Evolutionary Biology 41:299307.
Webster M., and Sheets H. D.. 2010. A practical introduction to landmark-based geometric morphometrics. In J. Alroy and G. Hunt, eds. Quantitative methods in paleobiology. Paleontological Society Papers 16:163–188.
Zelditch M. L., Bookstein F. L., and Lundrigan B. L.. 1992. Ontogeny of integrated skull growth in the cotton rat Sigmodon fulviventer . Evolution 46:11641180.
Zelditch M. L., Sheets H. D., and Fink W. L.. 2000. Spatiotemporal reorganization of growth rates in the evolution of ontogeny. Evolution 54:13631371.
Zelditch M. L., Swiderski D. L., Sheets H. D., and Fink W. L.. 2004. Geometric morphometrics for biologists. Elsevier Academic, London.
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Paleobiology
  • ISSN: 0094-8373
  • EISSN: 1938-5331
  • URL: /core/journals/paleobiology
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