3,241 research outputs found
Back to the Future for Lead Abatement? Drawing on lessons of the past to give condors and other wildlife a future
No full textProfessor Daniel J. Rohlf, of Lewis & Clark Law School, presented a working draft of his work Back to the Future for Lead Abatement? Drawing on lessons of the past to give condors and other wildlife a future. This work examines how advocates for eliminating lead are again using political, administrative, and judicial means to attack continued uses of lead in hunting and fishing.https://ecollections.law.fiu.edu/faculty-workshops/1009/thumbnail.jp
Proceedings of the Michigan Morphometrics Workshop
No full textProceedings of the Michigan Morphometrics Workshop held at the University of Michigan, Ann Arbor, Michigan from May 16 through May 28, 1988. Edited by F. James Rohlf and Fred L. Bookstein, with contributions by W. Fink, N. MacLeod, F.J. Rohlf, F.L. Bookstein, L. Marcus, R. Reyment, G.P. Lohmann, P.N. Schweitzer, D.O. Straney, T. Ray, R.E. Chapman, R. Tabachnick, J. Kitchell, D. Lindberg, S. Reilly, G.R. Smith, S.C. Ackerly, A. Sanfilippo, and W.R. Reidel.http://deepblue.lib.umich.edu/bitstream/2027.42/49535/1/michigan_morphometrics.pd
Figure 3 in Geometric morphometric analysis of shell shape variation in Conus (Gastropoda: Conidae)
No full textFigure 3. Plot of the results of the principal components analysis of the 32 coordinates of 16 landmarks on Conus specimens. +, Conus consors;, Conus miles; ¥, Conus stercusmuscarum; O, Conus striatus; °, Conus textile.Published as part of Cruz, Ronald Allan L., Pante, Ma. Josefa R. & Rohlf, F. James, 2012, Geometric morphometric analysis of shell shape variation in Conus (Gastropoda: Conidae), pp. 296-310 in Zoological Journal of the Linnean Society 165 (2) on page 300, DOI: 10.1111/j.1096-3642.2011.00806.x, http://zenodo.org/record/540770
Figure 4 in Geometric morphometric analysis of shell shape variation in Conus (Gastropoda: Conidae)
No full textFigure 4. Plot of the results of the principal components analysis of the 32 coordinates of 16 landmarks on Conus specimens grouped by dietary requirements. +, piscivores;, vermivores; °, molluscivores.Published as part of Cruz, Ronald Allan L., Pante, Ma. Josefa R. & Rohlf, F. James, 2012, Geometric morphometric analysis of shell shape variation in Conus (Gastropoda: Conidae), pp. 296-310 in Zoological Journal of the Linnean Society 165 (2) on page 302, DOI: 10.1111/j.1096-3642.2011.00806.x, http://zenodo.org/record/540770
Statistical tables /
No full textPrepared in conjunction with the textbook by R. R. Sokal and F. J. Rohlf: Biometry; the principles and practice of statistics in biological research
Figure 9 in Geometric morphometric analysis of shell shape variation in Conus (Gastropoda: Conidae)
No full textFigure 9. Plot of the results of the principal components analysis of relative warp 1 and relative warp 2. +, Conus consors;, Conus miles; ¥, Conus stercusmuscarum; O, Conus striatus; °, Conus textile.Published as part of Cruz, Ronald Allan L., Pante, Ma. Josefa R. & Rohlf, F. James, 2012, Geometric morphometric analysis of shell shape variation in Conus (Gastropoda: Conidae), pp. 296-310 in Zoological Journal of the Linnean Society 165 (2) on page 307, DOI: 10.1111/j.1096-3642.2011.00806.x, http://zenodo.org/record/540770
Figure 6 in Geometric morphometric analysis of shell shape variation in Conus (Gastropoda: Conidae)
No full textFigure 6. Plot of the results of the principal components analysis (PCA) with the identified Conus specimens and specimens unidentified a priori. Labels indicate identification of specimens after the PCA. +, Conus consors;, Conus miles; ¥, Conus stercusmuscarum; O, Conus striatus; °, Conus textile; •, unidentified.Published as part of Cruz, Ronald Allan L., Pante, Ma. Josefa R. & Rohlf, F. James, 2012, Geometric morphometric analysis of shell shape variation in Conus (Gastropoda: Conidae), pp. 296-310 in Zoological Journal of the Linnean Society 165 (2) on page 303, DOI: 10.1111/j.1096-3642.2011.00806.x, http://zenodo.org/record/540770
Figure 8 in Geometric morphometric analysis of shell shape variation in Conus (Gastropoda: Conidae)
No full textFigure 8. Thin-plate spline grids; warps in reference to mean shape. Numbers indicate area expansion or compression factors (i.e. degree of local growth). Green represents expansion, purple compression. A, Conus consors; B, Conus miles; C, Conus stercusmuscarum; D, Conus striatus; E, Conus textile.Published as part of Cruz, Ronald Allan L., Pante, Ma. Josefa R. & Rohlf, F. James, 2012, Geometric morphometric analysis of shell shape variation in Conus (Gastropoda: Conidae), pp. 296-310 in Zoological Journal of the Linnean Society 165 (2) on page 305, DOI: 10.1111/j.1096-3642.2011.00806.x, http://zenodo.org/record/540770
Figure 2 in Geometric morphometric analysis of shell shape variation in Conus (Gastropoda: Conidae)
No full textFigure 2. Landmarks (LM) on a Conus specimen. LM1 – apex of the shell; LM2–5 – sutures between major whorls on right profile; LM6 – junction between end of suture and apertural lip; LM7 – outermost curve of aperture; LM8 – lowest point of aperture at base; LM9 – lowest point of last whorl at base; LM10 – most external point on left profile of last whorl; LM11 – shoulder on left profile, where last whorl curves; LM12 – point opposite to LM5 on left profile; LM13 – point opposite LM4 on left profile; LM14 – point opposite LM3 on left profile; LM15 – point opposite LM2 on left profile; LM16 – most external point on right profile of last whorl.Published as part of Cruz, Ronald Allan L., Pante, Ma. Josefa R. & Rohlf, F. James, 2012, Geometric morphometric analysis of shell shape variation in Conus (Gastropoda: Conidae), pp. 296-310 in Zoological Journal of the Linnean Society 165 (2) on page 299, DOI: 10.1111/j.1096-3642.2011.00806.x, http://zenodo.org/record/540770
Seeing distinct groups where there are none:spurious patterns from between-group PCA
No full textUsing sampling experiments, we found that, when there are fewer groups than variables, between-groups PCA (bgPCA) may suggest surprisingly distinct differences among groups for data in which none exist. While apparently not noticed before, the reasons for this problem are easy to understand. A bgPCA captures the g-1 dimensions of variation among the g group means, but only a fraction of the∑ni-g dimensions of within-group variation ( are the sample sizes), when the number of variables, p, is greater than g-1. This introduces a distortion in the appearance of the bgPCA plots because the within-group variation will be underrepresented, unless the variables are sufficiently correlated so that the total variation can be accounted for with just g-1 dimensions. The effect is most obvious when sample sizes are small relative to the number of variables, because smaller samples spread out less, but the distortion is present even for large samples. Strong covariance among variables largely reduces the magnitude of the problem, because it effectively reduces the dimensionality of the data and thus enables a larger proportion of the within-group variation to be accounted for within the g-1-dimensional space of a bgPCA. The distortion will still be relevant though its strength will vary from case to case depending on the structure of the data (p, g, covariances etc.). These are important problems for a method mainly designed for the analysis of variation among groups when there are very large numbers of variables and relatively small samples. In such cases, users are likely to conclude that the groups they are comparing are much more distinct than they really are. Having many variables but just small sample sizes is a common problem in fields ranging from morphometrics (as in our examples) to molecular analyses
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