Some chelonians, such as the gopher tortoise (Gopherus polyphemus), spend much of their time underground in burrows. Often, they will retreat into these burrows when approached. This predator avoidance behavior may potentially influence the spatial use patterns that researchers directly observe via manual telemetry. In an effort to record the movements of gopher tortoises using affordable methods that reduce behavioral effects, we devised a novel application for Global Positioning System (GPS) loggers, specifically that of a low‐cost recreational unit that could be modified for extended deployment (~6 months) under gopher tortoise‐conditions. We conducted a stationary testing study of these GPS loggers whereby they were deployed at specific depths (0.5 m, 1.0 m, and 2.0 m) inside inactive burrows and on the surface at our study site in southeastern Georgia, USA, during summer 2017. This stationary trial allowed us to characterize the effect of burrow depth on GPS fix success rate (FSR), mean location error (µLE), and root mean square of the location error (LERMS). We found that µLE and LERMS increased with increasing depth underground; µLE ranged from 17.34 m on the surface to 69.98 m at the 2.0‐m depth. However, following exclusion of LE outliers >3 standard deviations from each treatment mean, LERMS decreased to 8.6 m at the surface to 40.46 m at the 2.0‐m depth. The FSR varied by burrow depth from 0.51 (2.0‐m depth) to 0.99 (surface). Additionally, we provide our attachment and deployment methods as used for studying the spatial ecology of the gopher tortoise with modified recreational GPS loggers. Overall, the modified GPS loggers performed well, obtaining 146,118 successful GPS fixes on 38 individual gopher tortoises during 84 unique deployments, each approximately 3.5–6 months in duration. © 2020 The Wildlife Society. Low‐cost recreational GPS loggers can be modified for application for wildlife and have been shown to produce reliable data useful for spatial ecology and behavior studies. Field‐based location and acquisition error rates can be assessed through short‐term validation studies that will yield a quantified understanding of how habitat and wildlife behavior affect data biases. [ABSTRACT FROM AUTHOR]