Patterns of variance and covariance for specific traits
Suspensorium length, palatine height, and ascending process length have strong positive correlation with PC axis 1 (0.75,0.75, 0.71 respectively) while pelvic girdle length, dentigerous arm depth and lower jaw length have strong negative correlations (-0.79, -0.74, -0.72 respectively; Appendix Table E5). PC2 is defined by positive correlations with ectopterygoid (0.45) and jaw opening in-lever (0.22) and strong negative correlations with head depth (-0.85), dentigerous arm width (-0.77), and cranial height (-0.76; Appendix Table E5). Most variation across both axes can be attributed to patterns in the Little Lake P matrix (93% of variance across PC1, and 63% variance across PC2), however, we can still identify clear differences in the relationship between traits for each population. For instance, there is a strong positive relationship between covariation patterns of lower jaw length and jaw opening in-lever in Little Lake, but this relationship is non-existent in Crescent Pond (Figure 8; Appendix Table E6). In fact, many relationships between traits captured by PC1 are strong in Little Lake but weak in Crescent Pond. Maxillary head height is the only trait in Crescent Pond to show a strong positive relationship with head depth, dentigerous arm width, and cranial height, while several traits in Little Lake share this relationship (Figure 8).
Finally, we found that overall variation within traits was similar between Crescent Pond and Little Lake (T test: t = -1.97, df = 27.45, p-value = 0.059) but variances in Little Lake were greater than variances in Crescent Pond for all traits. Although similar between populations, only the variation in Crescent Pond met null expectations associated with the laws of independent assortment and segregation (expected variation: 0.14, observed variation: 0.013; T test: t = -0.14, df = 33.72, p-value = 0.89). Variation in Little Lake was significantly higher than expected (expected variation: 0.007, observed variation: 0.029; T test: t = 3.05, df = 21.37, p-value = 0.006). We found that covariation estimates between traits were not significantly different from one another (LM: F=1.39, df=17, p-value=0.13), but that overall Little Lake had higher estimates of covariation than Crescent Pond (LM: F=30.1, df=17, p-value<0.01).
The interaction between population and trait significantly affected regression coefficient values (LM: F= 1.93, df=17, p-value=0.013). Within Crescent Pond, head depth, maxilla length, and palatine height had significantly higher regression coefficients than 50% of measured traits. Within Little Lake, head depth, lower jaw length, and dentigerous arm width had higher regression coefficients than 50% of measured traits. Comparing traits between populations regression coefficients for orbit diameter (Tukey’s HSD: t ratio=2.67, p-value=0.0078), palatine height (Tukey’s HSD: t ratio=3.45, p-value=0.0078), jaw closing in-lever (Tukey’s HSD: t ratio=2.22, p-value=0.027), and maxilla length (Tukey’s HSD: t ratio=2.18, p-value=0.003) were all higher in Crescent Pond than in Little Lake. Lastly, we found that squared correlation coefficients significantly varied between traits (LM: F=10.19, df=17, p-value<0.01) where dentigerous arm width, maxilla length, lower jaw length, and palatine height, had higher correlation coefficients than 50% of traits in the data set.