Change in vegetation structure alters habitat suitability for the threatened gopher tortoise (Gopherus polyphemus). An understanding of this dynamic is crucial to inform habitat and tortoise management strategies. However, it is not known how the choice of the sample grain (i.e., cell size) at which vegetation structure is measured impacts estimates of tortoise–habitat relationships. We used lidar remote sensing to estimate canopy cover around 1573 gopher tortoise burrows at incrementally larger sample grains (1–707 m2) in 450 ha of longleaf pine (Pinus palustris) savanna. Using an information theoretic approach, we demonstrate that the choice of grain size profoundly influences modeled relationships between canopy cover and burrow abandonment. At the most supported grain size (314 m2), the probability of burrow abandonment increased by 1.7% with each percent increase in canopy cover. Ultimately, detecting the appropriate sample grain can lead to more effective development of functional relationships and improve predictive models to manage gopher tortoise habitats.
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