In the last two decades, invasive Burmese pythons have spread throughout the Greater Everglades and have severely affected native wildlife. Monitoring and managing their population has proven extremely challenging, and a better understanding of python spatial ecology in the Everglades would improve our ability to remove pythons and mitigate their effects on the ecosystem. Python spatial ecology has been studied in the last 10 years using VHF telemetry on 47 individuals, with weekly, daytime locations. GPS technology can provide a finer and more consistent temporal resolution of locations, allowing for more detailed analysis of habitat selection and spatial behavior, but the application of GPS telemetry in snakes is largely untested. We GPS-tagged 12 wild Burmese pythons in Everglades National Park between July and December 2015, with the tags programmed to attempt a GPS fix every 90-minutes. We assessed the accuracy of GPS locations by evaluating number of satellites and horizontal dilution of precision (HDOP). We described frequency of large movement bouts, and then tested overall, daytime, and nighttime preferences for different habitat types using selection ratios. Finally, we looked for potential biases in the GPS locations by comparing daytime habitat selection to previously published studies using VHF telemetry.
Results/Conclusions
Preliminary analysis of GPS data showed that 81% of attempted fixes failed (n=4394), and just 62% of successful fixes were 3D fixes (>3 visible satellites). HDOP values considered to be “good” (HDOP < 2.2) accounted for 25% of the successful fixes, and locations considered “poor” (HDOP > 5.5) comprised another 25%, with the remaining 50% lying in between. Exact timing of large movement bouts was not available because of the large percentage of failed fixes, but all pythons exhibited a movement bout every 3-5 weeks. Analysis of selection ratios suggested that pythons positively selected only dry prairie overall, and we found no difference in habitat selection between daytime and nighttime locations. In contrast, published analyses of VHF data showed that pythons tend to select habitats with dense vegetation, suggesting a potential bias in GPS fix success. In addition, the majority of GPS locations occurred in habitats without dense canopy cover, further indicating possible bias in the GPS data. Although GPS telemetry has the potential to reveal important patterns of python spatial behavior, such as movement patterns and rates, the potential for habitat-driven bias in GPS relocations must be considered.