Morphology
Morphological variation was quantified for the 79 lake trout and used to
compare fatty acid groupings (different feeding strategies) identified
within the piscivorous ecotype. Twenty-three landmarks and 20
semi-landmarks, based on Chavarie et al. (2015), and fourteen linear
measurements based on Muir et al. (2014), were used to characterize body
and head shape from digital images. The combination of traditional and
geometric ecotype metrics was used because relationships of phenotype
morphology with foraging (e.g., jaw size) and swimming (e.g., fin
lengths and caudal peduncle depth) (Kahilainen et al., 2004;
Kristjánsson et al., 2002; Webb, 1984). Landmarks and semi-landmarks
were digitized in x and y coordinates using TPSDig2 software
(http://life.bio.sunysb.edu/ecotype).
Subsequently, digitized landmarks and semi-landmarks were processed in a
series of Integrated Morphometrics Programs (IMP) version 8
(http://www2.canisius.edu/;sheets/ecotypesoft),
using partial warp scores, which are thin-plate spline coefficients.
Morphological methods and programs are described in Zelditch et al.
(2012) and specific procedures were described in further detail by
Chavarie et al. (2013). All morphological measurements were size-free,
using centroid sizes or residuals from regressions on standard length
(Zelditch et al., 2012).
Canonical Variate Analyses (CVA) were conducted on all morphological
data, including body shape, head shape, and linear measurements, to
determine relationships among fatty acid groups. Body and head shape
were analysed using CVAGen8 from the IMP software (Zelditch et al.,
2012) and for linear measurements, CVA was analyzed with SYSTAT (Systat
Software Inc., Chicago, IL, USA). Single Factor Permutation MANOVA with
10 000 permutations tested for differences among groups and determined
the percentage of variation explained for a grouping if a CVA was
significant. For linear measurements, a Bonferroni-corrected post-hoc
test followed MANOVA to identify measurements that differed among group.
Principal component analyses (PCA) were performed on body- and
head-shape data using PCAGen8 (IMP software) among groups to visualize
morphological variation within the dataset. PC-ORD version 6 software
(McCune et al., 2011) was used to perform a PCA on the linear
measurements.