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Predictive equations for the estimation of body size in seals and sea lions ( C arnivora: P innipedia)
Author(s) -
Churchill Morgan,
Clementz Mark T.,
Kohno Naoki
Publication year - 2014
Publication title -
journal of anatomy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.932
H-Index - 118
eISSN - 1469-7580
pISSN - 0021-8782
DOI - 10.1111/joa.12199
Subject(s) - akaike information criterion , multivariate statistics , statistics , mathematics , principal component analysis , regression , stepwise regression , regression analysis , bayesian information criterion , feature selection , generalized estimating equation , multivariate analysis , biology , computer science , artificial intelligence
Body size plays an important role in pinniped ecology and life history. However, body size data is often absent for historical, archaeological, and fossil specimens. To estimate the body size of pinnipeds (seals, sea lions, and walruses) for today and the past, we used 14 commonly preserved cranial measurements to develop sets of single variable and multivariate predictive equations for pinniped body mass and total length. Principal components analysis ( PCA ) was used to test whether separate family specific regressions were more appropriate than single predictive equations for Pinnipedia. The influence of phylogeny was tested with phylogenetic independent contrasts ( PIC ). The accuracy of these regressions was then assessed using a combination of coefficient of determination, percent prediction error, and standard error of estimation. Three different methods of multivariate analysis were examined: bidirectional stepwise model selection using Akaike information criteria; all‐subsets model selection using Bayesian information criteria (BIC); and partial least squares regression. The PCA showed clear discrimination between Otariidae (fur seals and sea lions) and Phocidae (earless seals) for the 14 measurements, indicating the need for family‐specific regression equations. The PIC analysis found that phylogeny had a minor influence on relationship between morphological variables and body size. The regressions for total length were more accurate than those for body mass, and equations specific to Otariidae were more accurate than those for Phocidae. Of the three multivariate methods, the all‐subsets approach required the fewest number of variables to estimate body size accurately. We then used the single variable predictive equations and the all‐subsets approach to estimate the body size of two recently extinct pinniped taxa, the Caribbean monk seal ( M onachus tropicalis ) and the Japanese sea lion ( Z alophus japonicus ). Body size estimates using single variable regressions generally under or over‐estimated body size; however, the all‐subset regression produced body size estimates that were close to historically recorded body length for these two species. This indicates that the all‐subset regression equations developed in this study can estimate body size accurately.