Hostname: page-component-7c8c6479df-fqc5m Total loading time: 0 Render date: 2024-03-18T19:59:02.102Z Has data issue: false hasContentIssue false

A case study of extant and extinct Xenarthra cranium covariance structure: implications and applications to paleontology

Published online by Cambridge University Press:  13 May 2016

Alex Hubbe
Affiliation:
Departamento de Oceanografia, Instituto de Geociências, Universidade Federal da Bahia, Salvador, BA, 40170-020, Brazil. E-mail: alexhubbe@yahoo.com
Diogo Melo
Affiliation:
Laboratório de Evolução de Mamíferos, Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, Rua do Matão 277, São Paulo, SP, 05508-090, Brazil. E-mail: diogro@usp.br, gmarroig@usp.br
Gabriel Marroig
Affiliation:
Laboratório de Evolução de Mamíferos, Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, Rua do Matão 277, São Paulo, SP, 05508-090, Brazil. E-mail: diogro@usp.br, gmarroig@usp.br

Abstract

Most of the mammalian diversity is known only from fossils, and only a few of these fossils are well preserved or abundant. This undersampling poses serious problems for understanding mammalian phenotypic evolution under a quantitative genetics framework, since this framework requires estimation of a group’s additive genetic variance–covariance matrix (G matrix), which is impossible, and estimating a phenotypic variance–covariance matrix (P matrix) requires larger sample sizes than what is often available for extinct species. One alternative is to use G or P matrices from extant taxa as surrogates for the extinct ones. Although there are reasons to believe this approach is usually safe, it has not been fully explored. By thoroughly determining the extant and some extinct Xenarthra (Mammalia) cranium P matrices, this study aims to explore the feasibility of using extant G or P matrices as surrogates for the extinct ones and to provide guidelines regarding the reliability of this strategy and the necessary sample sizes. Variance–covariance and correlation P matrices for 35 cranium traits from 16 xenarthran genera (12 extant and 4 extinct) were estimated and compared between genera. Results show xenarthran P-matrix structures are usually very similar if sample sizes are reasonable. This study and others developed with extant therian mammals suggest, in general, that using extant G or P matrices as an approximation to extinct ones is a valid approach. Nevertheless, the accuracy of this approach depends on sample size, selected traits, and the type of matrix being considered.

Type
Articles
Copyright
Copyright © 2016 The Paleontological Society. All rights reserved 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Literature Cited

Ackermann, R. R. 2002. Patterns of covariation in the hominoid craniofacial skeleton: implications for paleoanthropological models. Journal of Human Evolution 43:167187.Google Scholar
Ackermann, R. R. 2003. Using extant morphological variation to understand fossil relationships: a cautionary tale. South African Journal of Science 99:255258.Google Scholar
Ackermann, R. R. 2005. Variation in Neandertals: a response to Harvati (2003). Journal of Human Evolution 48:643646.CrossRefGoogle Scholar
Ackermann, R. R., and Cheverud, J. M.. 2004. Detecting genetic drift versus selection in human evolution. Proceedings of the National Academy of Sciences USA 101:1794617951.CrossRefGoogle ScholarPubMed
Aguirre, J. D., Hine, E., McGuigan, K., and Blows, M. W.. 2014. Comparing G: multivariate analysis of genetic variation in multiple populations. Heredity 112:2129.Google Scholar
Akesson, M., Bensch, S., and Hasselquist, D.. 2007. Genetic and phenotypic associations in morphological traits: a long term study of great reed warblers Acrocephalus arundinaceus. Journal of Avian Biology 38:5872.Google Scholar
Anderson, R. P., and Handley, C. O.. 2001. A new species of three-toed sloth (Mammalia: Xenarthra) from Panama, with a review of the genus Bradypus. Proceedings of the Biological Society of Washington 114:133.Google Scholar
Armbruster, W. S., Pélabon, C., Bolstad, G. H., and Hansen, T. F.. 2014. Integrated phenotypes: understanding trait covariation in plants and animals. Philosophical Transactions of the Royal Society B 369:20130245.Google Scholar
Arnold, S. J. 1981. Behavioral variation in natural populations. I. Phenotypic, genetic and environmental correlations between chemoreceptive responses to prey in the garter snake. Evolution 35:489509.CrossRefGoogle ScholarPubMed
Arnold, S. J. 1992. Constraints on phenotypic evolution. American Naturalist 140:S85S107.Google Scholar
Arnold, S., and Phillips, P.. 1999. Hierarchical comparison of genetic variance-covariance matrices. II. Coastal-inland divergence in the garter snake, Thamnophis elegans. Evolution 53:15161527.Google Scholar
Arnold, S. J., Buerger, R., Hohenlohe, P. A., Ajie, B. C., and Jones, A. G.. 2008. Understanding the evolution and stability of the G-matrix. Evolution 62:24512461.Google Scholar
Barton, N. H., and Turelli, M.. 1989. Evolutionary quantitative genetics: how little do we know? Annual Review of Genetics 23:337370.CrossRefGoogle ScholarPubMed
Bégin, M., and Roff, D. A.. 2003. The constancy of the G matrix through species divergence and the effects of quantitative genetic constraints on phenotypic evolution: a case study in crickets. Evolution 57:11071120.Google Scholar
Benton, M. J., and Harper, D. A. T.. 2009. Introduction to paleobiology and the fossil record. Wiley-Blackwell, Chichester, U.K.Google Scholar
Bergqvist, L. P., Abrantes, E. A. L., and Avilla, L. S.. 2004. The Xenarthra (Mammalia) of São José de Itaboraí Basin (upper Paleocene, Itaboraian), Rio de Janeiro, Brazil. Geodiversitas 26:323337.Google Scholar
Berner, D., Kaeuffer, R., Grandchamp, A. C., Raeymaekers, J. A. M., Räsänen, K., and Hendry, A. P.. 2011. Quantitative genetic inheritance of morphological divergence in a lake-stream stickleback ecotype pair: implications for reproductive isolation. Journal of Evolutionary Biology 24:19751983.CrossRefGoogle Scholar
Bininda-Emonds, O. R. P., Cardillo, M., Jones, K. E., MacPhee, R. D. E., Beck, R. M. D., Grenyer, R., Price, S. A., Vos, R. A., Gittleman, J. L., and Purvis, A.. 2007. The delayed rise of present-day mammals. Nature 446:507512.Google Scholar
Blows, M. W., Chenoweth, S. F., and Hine, E.. 2004. Orientation of the genetic variance-covariance matrix and the fitness surface for multiple male sexually selected traits. American Naturalist 163:329340.Google Scholar
Cardini, A., and Polly, P. D.. 2013. Larger mammals have longer faces because of size-related constraints on skull form. Nature Communications 4:2458.Google Scholar
Cartelle, C., De Iuliis, G., and Pujos, F.. 2008. A new species of Megalonychidae (Mammalia, Xenarthra) from the Quaternary of Poço Azul (Bahia, Brazil). Comptes Rendus Palevol 7:335346.Google Scholar
Chernick, M.R. 2008. Bootstrap methods: a guide for practitioners and researchers. Wiley, Hoboken, N.J.Google Scholar
Chernick, M. R., and LaBudde, L. A.. 2010. Revisiting qualms about bootstrap confidence intervals. American Journal of Mathematical and Management Sciences 29:437456.Google Scholar
Cheverud, J. M. 1982. Phenotypic, genetic, and environmental morphological integration in the cranium. Evolution 36:499516.CrossRefGoogle ScholarPubMed
Cheverud, J. M. 1984. Quantitative genetics and developmental constraints on evolution by selection. Journal of Theoretical Biology 110:155171.CrossRefGoogle ScholarPubMed
Cheverud, J. M. 1988. A comparison of genetic and phenotypic correlations. Evolution 42:958968.Google Scholar
Cheverud, J. M. 1995. Morphological integration in the saddle-back tamarin (Saguinus fuscicollis) cranium. American Naturalist 145:6389.Google Scholar
Cheverud, J. M. 1996. Quantitative genetic analysis of cranial morphology in the cotton-top (Saguinus oedipus) and saddle-back (S. fuscicollis) tamarins. Journal of Evolutionary Biology 9:542.Google Scholar
Cheverud, J. M., Wagner, G. P., and Dow, M. M.. 1989. Methods for the comparative-analysis of variation patterns. Systematic Zoology 38:201213.Google Scholar
Cheverud, J. M., and Marroig, G.. 2007. Comparing covariance matrices: random skewers method compared to the common principal components model. Genetics and Molecular Biology 30:461469.Google Scholar
Clark, A. A. 2010. Ancient DNA from the extinct folivorous xenarthrans, or sloths, with specific attention toward the Greater Antillean Megalonychids and the Patagonian Mylodontid, Mylodon darwinii. PhD Thesis. McMaster University, Ottawa.Google Scholar
Delsuc, F., Catzeflis, F. M., Stanhope, M. J., and Douzery, E. J. P.. 2001. The evolution of armadillos, anteaters and sloths depicted by nuclear and mitochondrial phylogenies: implications for the status of the enigmatic fossil Eurotamandua. Proceedings of the Royal Society of London B 268:16051615.Google Scholar
Delsuc, F., Superina, M., Tilak, M., Douzery, E. J. P., and Hassanin, A. 2012. Molecular phylogenetics unveils the ancient evolutionary origins of the enigmatic fairy armadillos. Molecular Phylogenetics and Evolution 62:673680.Google Scholar
Eisenberg, J. F. 1989. Mammals of the neotropics, Vol. 1. The northern neotropics: Panama, Colombia, Venezuela, Guyana, Suriname, French Guiana. University of Chicago Press, Chicago.Google Scholar
Eisenberg, J. F., and Redford, K. H.. 1999. Mammals of the neotropics, Vol. 3. The central neotropics: Ecuador, Peru, Bolivia, Brazil. University of Chicago Press, Chicago.Google Scholar
Elbroch, M. 2006. Animal skulls: a guide to North American species. Stackpole, Mechanicsburg, PA.Google Scholar
Engelmann, G. F. 1985. The phylogeny of the Xenarthra. Pp. 5164 in G. G. Montgomery, ed. The evolution and ecology of armadillos, sloths and vermilinguas. Smithsonian Institution Press, Washington, D.C.Google Scholar
Falconer, D. S., and MacKay, T. F. C.. 1996. Introduction to quantitative genetics. Longman, New York.Google Scholar
Fisher, R. A. 1930. The genetic theory of natural selection. Clarendon Press, Oxford.Google Scholar
Flury, B. 1988. Common principal components and related multivariate models. Wiley, New York.Google Scholar
Garcia, G. 2010. Análise comparativa dos padrões de covariação genética e fenotípica no crânio e mandíbula de Calomys expulsus (Rodentia: Muroidea). Master’s dissertation. Universidade de São Paulo, São Paulo.Google Scholar
Gardner, A. L. 2007. Mammals of South America, Vol. 1. Marsupials, xenarthrans, shrews, and bats. University of Chicago Press, Chicago.Google Scholar
Gaudin, T. J. 2004. Phylogenetic relationships among sloths (Mammalia, Xenarthra, Tardigrada): the craniodental evidence. Zoological Journal of the Linnean Society 140:255305.Google Scholar
Goloboff, P. A., Catalano, S. A., Mirande, J. M., Szumik, C. A., Arias, J. S., Kallersjo, M., and Farris, J. S.. 2009. Phylogenetic analysis of 73060 taxa corroborates major eukaryotic groups. Cladistics 25:211230.Google Scholar
Goswami, A. 2006. Morphological integration in the carnivoran skull. Evolution 60:169183.Google Scholar
Goswami, A. 2007. Phylogeny, diet, and cranial integration in Australodelphian marsupials. PLoS ONE 2:e995.Google Scholar
Goswami, A., and Polly, P. D.. 2010). Methods for studying morphological integration, modularity and covariance evolution. In J. Alroy, and G. Hunt, eds. Quantitative Methods in Paleobiology. Paleontological Society Short Course, October 30th, 2010. Paleontological Society Papers 16: 213–243.Google Scholar
Goswami, A., Smaers, J. B., Soligo, C., and Polly, P. D.. 2014. The macroevolutionary consequences of phenotypic integration: from development to deep time. Philosophical Transactions of the Royal Society of London B 369:20130254.Google Scholar
Haber, A. 2015. The evolution of morphological integration in the ruminant skull. Evolutionary Biology 42:99114.Google Scholar
Hallgrímsson, B., Jamniczky, H., Young, N. M., Rolian, C., Parsons, T. E., Boughner, J. C., and Marcucio, R. S. 2009. Deciphering the palimpsest: studying the relationship between morphological integration and phenotypic covariation. Evolutionary Biology 36:355376.Google Scholar
Hansen, T. F., and Houle, D.. 2008. Measuring and comparing evolvability and constraint in multivariate characters. Journal of Evolutionary Biology 21:12011219.CrossRefGoogle ScholarPubMed
Hansen, T. F., and Voje, K. L.. 2011. Deviation from the line of least resistance does not exclude genetic constraints: a comment on Berner et al. (2010). Evolution 65:18211822.Google Scholar
Hautier, L., Weisbecker, V., Goswami, A., Knight, F., Kardjilov, N., and Asher, R. J.. 2011. Skeletal ossification and sequence heterochrony in xenarthran evolution. Evolution and Development 13:460476.Google Scholar
Hoganson, J. W., and McDonald, H. G.. 2007. First report of Jefferson’s ground sloth (Megalonyx jeffersonii) in North Dakota: paleobiogeographical and paleoecological significance. Journal of Mammalogy 88:7380.Google Scholar
House, C. M., and Simmons, L. W.. 2005. The evolution of male genitalia: patterns of genetic variation and covariation in the genital sclerites of the dung beetle Onthophagus taurus. Journal of Evolutionary Biology 18:12811292.Google Scholar
Jones, A. G., Arnold, S. J., and Bürger, R.. 2003. Stability of the G-matrix in a population experiencing pleiotropic mutation, stabilizing selection, and genetic drift. Evolution 57:17471760.Google Scholar
Jones, A. G., Arnold, S. J., and Bürger, R.. 2004. Evolution and stability of the G-matrix on a landscape with a moving optimum. Evolution 58:16391654.Google Scholar
Klingenberg, C. P., and Monteiro, L. R.. 2005. Distances and directions in multidimensional shape spaces: implications for morphometric applications. Systematic Biology 54:678688.Google Scholar
Kohn, L. A., and Atchley, W. R.. 1988. How similar are genetic correlation structures? Data from mice and rats. Evolution 42:467481.Google Scholar
Krzanowski, W. J. 1979. Between-groups comparison of principal components. Journal of the American Statistical Association 74:703707.Google Scholar
Krzanowski, W. J. 2000. Principles of multivariate analysis: a user’s perspective, rev. ed. Clarendon, Oxford.Google Scholar
Lande, R. 1979. Quantitative genetic analysis of multivariate evolution, applied to brain: body size allometry. Evolution 33:402416.Google Scholar
Lande, R., and Arnold, S. J.. 1983. The measurement of selection on correlated characters. Evolution 37:12101226.Google Scholar
Lessells, C. M., and Boag, P. T.. 1987. Unrepeatable repeatabilities: a common mistake. Auk 104:116121.Google Scholar
Lofsvold, D. 1986. Quantitative genetics of morphological differentiation in Peromyscus. I. Tests of the homogeneity of genetic covariance structure among species and subspecies. Evolution 40:559573.Google Scholar
MacPhee, R. D. E., White, J. L., and Woods, C. A.. 2000. New megalonychid sloths (Phyllophaga, Xenarthra) from the Quaternary of Hispaniola. American Museum Novitates 3303:132.Google Scholar
Marquéz, E. J., Cabeen, R., Woods, R. P., and Houle, D. 2012. The measurement of local variation in shape. Evolutionary Biology 39:419439.Google Scholar
Marroig, G., and Cheverud, J. M.. 2001. A comparison of phenotypic variation and covariation patterns and the role of phylogeny. Ecology, and ontogeny during cranial evolution of New World monkeys. Evolution 55:25762600.Google Scholar
Marroig, G., and Cheverud, J. M. 2005. Size as a line of least evolutionary resistance: diet and adaptive morphological radiation in New World monkeys. Evolution 59:11281142.Google Scholar
Marroig, G., and Cheverud, J. M.. 2010. Size as a line of least resistance II: direct selection on size or correlated response due to constraints? Evolution 64:14701488.Google Scholar
Marroig, G., de Vivo, M., and Cheverud, J. M.. 2004. Cranial evolution in sakis (Pithecia, Platyrrhini) II: evolutionary processes and morphological integration. Journal of Evolutionary Biology 17:144155.Google Scholar
Marroig, G., Shirai, L. T., Porto, A., de Oliveira, F. B., and De Conto, V.. 2009. The evolution of modularity in the mammalian skull II: evolutionary consequences. Evolutionary Biology 36:136148.CrossRefGoogle Scholar
Marroig, G., Melo, D. A. R., and Garcia, G.. 2012. Modularity, noise, and natural selection. Evolution 66:15061524.Google Scholar
McAfee, R. K. 2009. Reassessment of the cranial characters of Glossotherium and Paramylodon (Mammalia: Xenarthra: Mylodontidae). Zoological Journal of the Linnean Society 155:885903.CrossRefGoogle Scholar
McDonald, H. G. 2005. Paleoecology of extinct xenarthrans and the Great American Biotic Interchange. Bulletin of the Florida Museum of Natural History 45:313333.Google Scholar
McDonald, H. G., Harington, C. R., and De Iuliis, G. 2000. The ground sloth, Megalonyx, from Pleistocene deposits of the Old Crow Basin, Yukon, Canada. Artic 53:213220.Google Scholar
McDonald, H. G., and Pelikan, S.. 2006. Mammoths and mylodonts: exotic species from two different continents in North American Pleistocene faunas. Quaternary International 142–143:229241.Google Scholar
McGuigan, M. C. 2006. Studying phenotypic evolution using multivariate quantitative genetics. Molecular Ecology 15:883896.Google Scholar
Melo, D., Garcia, G., Hubbe, A., Assis, A. P., and Marroig, G.. 2015. EvolQG—an an R package for evolutionary quantitative genetics, Version 1 [referees: 1 approved, 1 approved with reservations]. F1000Research 4:925.Google Scholar
Melo, D., and Marroig, G.. 2015. Directional selection can drive the evolution of modularity in complex traits. Proceedings of the National Academy of Sciences USA 112:470475.Google Scholar
Miño-Boilini, A. R., and Carlini, A. A.. 2009. The Scelidotheriinae Ameghino, 1904 (Phyllophaga, Xenarthra) from the Ensenadan–Lujanian Stage/Ages (Early Pleistocene to Early-Middle Pleistocene–Early Holocene) of Argentina. Quaternary International 210:93101.Google Scholar
Mitteroecker, P., and Bookstein, F. L.. 2009. The ontogenetic trajectory of the phenotypic covariance matrix, with examples from craniofacial shape in rats and humans. Evolution 63:727737.Google Scholar
Möller-Krull, M., Delsuc, F., Churakov, G., Marker, C., Superina, M., Brosius, J., Douzery, E. J. P., and Schmitz, J.. 2007. Retroposed elements and their flanking regions resolve the evolutionary history of xenarthran mammals (armadillos, anteaters, and sloths). Molecular Biology and Evolution 24:25732582.Google Scholar
Murphy, W. J., Eizirik, E., O’Brien, S. J., Madsen, O., Scally, M., Douady, C. J., Teeling, E., Ryder, O. A., Stanhope, M. J., de Jong, W. W., and Springer, M. S.. 2001. Resolution of the early placental mammal radiation using Bayesian phylogenetics. Science 294:23482351.Google Scholar
O’Leary, M. A., Bloch, J. I., Flynn, J. J., Gaudin, T. J., Giallombardo, A., Giannini, N. P., Goldberg, S. L., Kraatz, B. P., Luo, Z.-X., Meng, J., Ni, X., Novacek, M. J., Perini, F. A., Randall, Z. S., Rougier, G. W., Sargis, E. J., Silcox, M. T., Simmons, N. B., Spaulding, M., Velazco, P. M., Weksler, M., Wible, J. R., and Cirranello, A. L. 2013. The placental mammal ancestor and the post–K-Pg radiation of placentals. Science 339:662667.Google Scholar
Oliveira, F. B., Porto, A., and Marroig, G.. 2009. Covariance structure in the skull of Catarrhini: a case of pattern stasis and magnitude evolution. Journal of Human Evolution 56:417430.Google Scholar
Pavlicev, M., Cheverud, J. M., and Wagner, G. P.. 2009. Measuring morphological integration using eigenvalue variance. Evolutionary Biology 36:157170.Google Scholar
Porto, A., Oliveira, F. B. D., Shirai, L. T., Conto, V. D., and Marroig, G.. 2009. The evolution of modularity in the mammalian skull I: morphological integration patterns and magnitudes. Evolutionary Biology 36:118135.CrossRefGoogle Scholar
Porto, A., Shirai, L. T., de Oliveira, F. B., and Marroig, G.. 2013. Size variation, growth strategies, and the evolution of modularity in the mammalian skull. Evolution 67:33053322.Google Scholar
Prôa, M., O’Higgins, P., and Monteiro, L. R.. 2012. Type I error rates for testing genetic drift with phenotypic covariance matrices: a simulation study. Evolution 67:185195.Google Scholar
Puth, M., Neuhäuser, M., and Ruxton, G. D.. 2015. On the variety of methods for calculating confidence intervals by bootstrapping. Journal of Animal Ecology 84:892897.Google Scholar
R Development Core Team 2013. A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.Google Scholar
Rager, L., Hautier, L., Forasiepi, A., Goswami, A., and Sánchez-Villagra, M.. 2014. Timing of cranial suture closure in placental mammals: phylogenetic patterns, intraspecific variation, and comparison with marsupials. Journal of Morphology 275:125140.Google Scholar
Redford, K. H., and Eisenberg, J. F.. 1992. Mammals of the neotropics, Vol. 2. The Southern Cone: Chile, Argentina, Uruguay, Paraguay. University of Chicago Press, Chicago.Google Scholar
Reusch, T., and Blanckenhorn, W. U. 1998. Quantitative genetics of the dung fly Sepsis cynipsea: Cheverud’s conjecture revisited. Heredity 81:111119.Google Scholar
Roff, D. A. 1995. The estimation of genetic correlations from phenotypic correlations: a test of Cheverud’s conjecture. Heredity 74:481490.Google Scholar
Roff, D. A. 1996. The evolution of genetic correlations: an analysis of pattern. Evolution 50:13921403.CrossRefGoogle Scholar
Roff, D. A. 1997. Evolutionary quantitative genetics. Chapman and Hall, London.Google Scholar
Schluter, D. 1996. Adaptive radiation along genetic lines of least resistance. Evolution 50:17661774.Google Scholar
Shaw, F. H., Shaw, R. G., Wilkinson, G. S., and Turelli, M.. 1995. Changes in genetic variances and covariances: G whiz!. Evolution 49:12601267.Google Scholar
Shirai, L. T., and Marroig, G.. 2010. Skull modularity in neotropical marsupials and monkeys: size variation and evolutionary constraint and flexibility. Journal of Experimental Zoology B 314B:663683.Google Scholar
Simpson, G. G. 1980. Splendid isolation: the curious history of South American mammals. Yale University Press, New Haven, Conn.Google Scholar
Sokal, R. R., and Rolhf, F. J.. 1995. Biometry. Freeman, New York.Google Scholar
Steppan, S. J. 1997. Phylogenetic analysis of phenotypic covariance structure. I. Contrasting results from matrix correlation and common principal component analyses. Evolution 51:571586.Google Scholar
Steppan, S. J., Phillips, P. C., and Houle, D.. 2002. Comparative quantitative genetics: evolution of the G matrix. Trends in Ecology and Evolution 17:320327.Google Scholar
Stock, C. 1942. A ground sloth in Alaska. Science 95:552553.Google Scholar
Turelli, M. 1988. Phenotypic evolution, constant covariances and the maintenance of additive variance. Evolution 43:13421347.Google Scholar
Van der Linde, K., and Houle, D. 2009. Inferring the nature of allometry from geometric data. Evolutionary Biology 36:311322.Google Scholar
Vizcaino, S. F., Bargo, M. S., and Fariña, R. A.. 2008. Form, function, and paleobiology in xenarthrans. Pp. 8699 in S. F. Vizcaino, and W. J. Loughry, eds. The biology of the Xenarthra. University Press of Florida, Gainesville.Google Scholar
Wagner, G. P., and Altenberg, L.. 1996. Complex adaptations and the evolution of evolvability. Evolution 50:967976.Google Scholar
Walker, J.A. 2000. Ability of geometric morphometric methods to estimate a known covariance matrix. Systematic Biology 49:686696.Google Scholar
Webster, M., and Zelditch, M. L.. 2011. Evolutionary lability of integration in Cambrian ptychopariod trilobites. Evolutionary Biology 38:144162.Google Scholar
Wilkinson, G. S., Fowler, K., and Partridge, L.. 1990. Resistance of genetic correlation structure to directional selection in Drosophila melanogaster. Evolution 44:19902003.Google Scholar
Wright, S. 1931. Evolution in Mendelian populations. Genetics 16:97159.Google Scholar
Young, N. M., Wagner, G. P., and Hallgrímsson, B.. 2010. Development and the evolvability of human limbs. Proceedings of the National Academy of Sciences USA 107:34003405.Google Scholar