Reproductive Ecology and Body Burden of Resident ... - The Love Lab

Statistical analysis of otolith and seawater microchemistry
We used univariate and multivariate statistics to test for differences in the concentration of particular
elements and multi-elemental signatures in otoliths and seawater among platforms and natural habitats
(SPSS, Inc. 2002). Before the statistical analysis, otolith and seawater element Ca -1 data were log 10
-transformed
to better fit assumptions of the models. Log (x+1) transformation was used on all otolith element
Ca -1 data to account for zero values. Prior to the analyses, we assessed the normality and homoscedacity of
the otolith data among water mass groups (SPSS, Inc. 2002).
We employed a two-way fixed analysis of variance (ANOVA) to simultaneously test for the effects of
habitat and geographic area on the abundance of an element (element Ca -1 ) in otoliths of a single species
and to test for interaction of these two factors. We also used a one-way ANOVA to test the effects of site (all
platforms and natural sites) on element abundance in otoliths. We employed the Tukey post hoc multiple
comparison test (or the Tamhane test when equal error variances could not be assumed) to examine differences
between all possible pairs of group (e.g., area, site) means (SPSS, Inc. 2002).
Canonical discriminant function analysis (DFA) was used to test whether the elemental signature of
otoliths identified the habitat types occupied by fish (SPSS Inc. 2002). We used the results from our univariate
analysis to determine the elements that were the best discriminators of either habitat types or geographic
areas, and included those elements in the DFA. The procedure generated a single discriminant function
(DF) for two groups (e.g., two habitat types, platforms and natural sites) or a set of DFs for more than two
groups based on linear combinations of the predictor variables (log (element Ca -1 +1) transformed) that
provide the best discrimination between the groups.
The classification accuracy of the DFA was evaluated by leave-one-out cross-validation, also called
jack-knife reclassification (SPSS Inc. 2002). The prior probabilities of group membership were assumed to
be uniform.
We used the Spearman’s rho correlation to determine whether the abundance of different elements in
otoliths co-varied and whether the abundance of an element in otoliths varied with the element concentration
in seawater (SPSS, Inc. 2002). We estimated the correlation between the average otolith element abundance
and average seawater concentration at sampling sites using the Pearson product-moment correlation
coefficient, r. If the correlation was significant, we used least squares regression to model the relationship
between seawater element concentration, the environmental predictor, and otolith element concentration,
the dependent variable, by fitting a linear equation to the observed data (Systat Software Inc. 2006).
Kelp rockfish otolith elemental signatures
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Results
The variability in the concentration of individual elements in kelp rockfish otoliths differed between
habitat types and geographic areas. The univariate two-way ANOVA model (habitat x geographic area)
showed that Mg Ca -1 , Sr Ca -1 , and Ba Ca -1 differed between platforms and natural sites, and Sr Ca -1 and Ba
Ca -1 differed among geographic areas (Table 2).
Mean otolith Mg Ca -1 of kelp rockfish was higher at platforms compared to natural reefs, except in the
ESB area (Fig. 3 A, B). Two-way ANOVA showed a significant difference in Mg Ca -1 between habitat types
(Fig. 3A) but not among areas (Table 2). There was a significant interaction (habitat x area) effect (Table 2)
as indicated by the inconsistency of otolith Mg Ca -1 being higher from the natural site in ESB rather than the
platform as in other areas. One-way ANOVA showed that otolith Mg Ca -1 differed among sites (Table 3), and
otolith Mg Ca -1 was significantly higher from Platform Gilda (OEC) than from natural sites in the same area
and the three sites in SCB (Fig. 3B; Tamhane tests, p