Spatial ecology and multilevel, multiscale habitat relationships of eastern copperheads (Agkistrodon contortrix)

Decrypting animal movements to identify the environmental resources most essential to population persistence is a central goal of conservation ecology. However, beneficial habitats, as well as the conditions under which they are used, can differ across physiological states or environmental contexts and may only become detectable when examined at appropriate ecological levels, spatial scales, or temporal periods. Wildlife-habitat models that account for multiple such dependencies can yield more accurate and actionable inferences relative to simpler approaches. Reptiles exemplify many habitat-related conservation challenges due to their multiple specific habitat needs, periodic reliance on highly communal sites, and extreme crypsis. In this dissertation, I investigated the movement and habitat interactions of eastern copperheads (Agkistrodon contortrix) in New Jersey, USA using a 10-year radiotelemetry dataset. In Chapter 1, I examined copperhead habitat selection at multiple ecological levels, spatial scales, behavioral states, and across two ecoregions. Selection criteria for home ranges differed from those for specific snake locations, with the latter driven by extremely fine-scale habitat variation (4 – 6 m). Comparisons among state- and region-specific responses revealed potential habitat management opportunities. In Chapter 2, I investigated whether episodic gregariousness at communal hibernacula generated distinct individual- and population-level core habitats. I found that core areas were level-dependent and occurred in spatially and environmentally distinct habitats, with both providing resources required by copperheads at different stages of their annual cycles. In Chapter 3, I evaluated whether models based on annual population-level movement patterns can predict the locations of communal hibernacula using snake observations from the surrounding landscape. Predictive precision depended on model formulation, date, sample size, and landscape factors, with model-generated search areas ranging from very small (< 1.0 ha) and successful (> 80%) to very large (> 20 ha) and unsuccessful (< 5%). Collectively, these chapters advance our understanding of copperhead spatial ecology and strengthen our ability to identify, protect, and manage their most limiting habitats. More broadly, they demonstrate how wildlife-habitat models that incorporate multi-level, multi-scale, and state-dependent inferences provide more reliable and conservation-relevant insights for reptiles and other taxa.