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Abstract
Spatial variation in skull form was analyzed for white-tailed deer (Odocoileus virginianus) from eight sites within three physiographic regions [upper (UCP) and lower coastal plain (LCP) and barrier islands (BI)] of the Southeast. Components of skull form vary among the physiographic regions. Deer from BI were smaller than mainland deer, and together with LCP deer, exhibited increased fluctuating asymmetry (FA) compared to UCP deer. LCP deer exhibited decreased shape variation compared to animals from either the UCP or BI. Form components for sites within regions appeared to be influenced more by recent processes such as hunting regime, restocking effort and habitat change. Evidence for maintaining the subspecific status of O. v. hiltonensis appeared weak. Fluctuating asymmetry occurs on a smaller scale than the original character and measurement error represents a significant proportion of FA. Mixed-model ANOVA allows group-level FA to be corrected for measurement. Currently, individual-level FA estimates include measurement error. Best linear unbiased predictors (BLUP) can provide error-corrected estimates of individual FA. A simulated data set showed BLUP estimates were more efficient than arithmetic means at error reduction. An analysis of a Gambusia hybridization study showed the usefulness of individual-level FA analysis. Form is a composite character and cannot be measured. Path analysis was utilized to develop individual-level models of skull form evolution for the hispid cotton rat (Sigmodon hispidus). Path coefficients are essentially selection coefficients and translate into relative time scales. Structural size operated over the shortest time scale in six models and an intermediate scale in two models. Mass operated over the shortest time scale in four models and an intermediate scale in four models. Age operated over the shortest time scale in four models but sex operated over the shortest time scale in one model and an intermediate scale in the remaining three. Density class operated on an intermediate time scale in all models. Heterozygosity class acted over intermediate (2 models) or long (6 models) time scales. Path models allowed the identification of covariates when utilizing form as a biomarker. Structural size, mass and age together accounted for 89.8% to 95.7% of explained variation.