| Exploratory statistical modeling was conducted on associations between 18 habitat features and the occurrence of Anolis carolinensis, an arboreal lizard, in plots at its northern distributional limits in Tennessee. A genetic algorithm-informational modeling (GAIM) approach was developed to reduce certain limitations imposed by the commonly used stepwise algorithms and hypothesis-testing procedures and allow a wider exploration of multivariate data. The GAIM approach utilizes a genetic algorithm and an informational model-selection criterion to find a set of well-fitting models and a frequency distribution of variables in this set of models can help analysts find useful combinations of variables or factors.; Plots were surveyed for the presence of A. carolinensis in summer and winter and habitat variables were measured. Logistic regression modeling using GAIM methods was conducted separately on summer and winter data. Most frequent variables in the set of well-fitting summer models were: distance to overwintering rock, summer canopy categorization, distance to habitat edge, herb/shrub cover, summer sunlight index, ambient temperature, and standardized distance along the habitat edge from the habitat's western boundary.; Most frequent variables in the final set of winter models were: ambient temperature, presence of live overstory evergreen tree trunks, presence of overwintering rock, standardized distance along the habitat edge from the west boundary of habitat, distance to overwintering rock, and canopy cover categorization.; Summer models suggest that further research on A. carolinensis focus on sunlight and thermal factors and habitat features related to spatial scales beyond the summer home range scale. Winter results suggest future research might examine responses of this species to shelter and potential basking sites, sunlight availability and temperature, and spatial features beyond the typical winter home range size. Methods using experimental control, or at least partial control, over field variables are needed to determine the specific responses of this species to key habitat features and the causal mechanisms underlying those responses. In addition, more studies are needed which take approaches based on biophysical and physiological ecology, especially if they can be linked to reproductive output, population ecology, and habitat use on local and regional scales. |
