A map made from wildlife tracking data can look wonderfully precise. Each dot seems to say, with confidence, that an animal was right here at a particular moment. Yet when researchers from the Urban Sloth Project plotted raw GPS locations from a sloth named Lee, some dots appeared in the ocean.
Lee had not suddenly taken up deep-sea swimming. The impossible points were a reminder that GPS data is measured, not magical. Signals can be weak, obstructed or poorly arranged, especially beneath dense rainforest canopy. For an animal that moves slowly and over short distances, even a modest location error can completely change the story a map appears to tell.
Why tracking a slow animal is surprisingly difficult
GPS is often associated with animals that travel across huge landscapes. If a whale, bird or big cat moves many kilometres, an error of several metres may not hide the broad route. Sloths create a different problem. Their movements can be subtle, and researchers may want to know which trees they use, whether they cross a road, or how they respond to fragmented urban habitat.
A misplaced point can make a sloth look as though it visited the wrong tree, crossed open ground or travelled farther than it really did. The Sloth Conservation Foundation therefore says accuracy is especially important when studying an animal that does not move much.
How a GPS collar creates a dot
A GPS device calculates a position from satellite signals available at the time of a reading. In the Urban Sloth Project example, collars recorded a point every three hours. Some fixes were built from signals received from several satellites and were more trustworthy. Others were only rough estimates because fewer useful signals were available.
Rainforest is a difficult workplace for satellite tracking. Leaves, branches, tree trunks, terrain and even the position of the device can obstruct or distort signals. A broader study of lightweight GPS loggers found that completely or partly obstructed habitats could reduce the proportion of successful fixes and increase location error. Forest habitat also affected accuracy. That research was not conducted specifically on sloths, but it helps explain why field biologists treat raw wildlife GPS locations with caution.
What HDOP tells researchers
One clue is Horizontal Dilution of Precision, usually shortened to HDOP. It describes how the arrangement of available satellites affects confidence in a horizontal position. A lower HDOP generally indicates a stronger geometry and a potentially more accurate fix. A higher value warns that the dot may be less reliable.
Satellite count matters too. The Sloth Conservation Foundation reports that its team filters Urban Sloth Project data using both HDOP and the number of available satellites. For its work, a reliable point requires signals from at least five satellites. That is a project-specific quality rule, not a guarantee that every accepted dot is perfect.
Researchers also compare GPS fixes with locations collected manually while following sloths in the field. The map and the people beneath the trees act as checks on one another. A dot with poor satellite information that conflicts with a field observation can be discarded rather than allowed to distort the analysis.
One dot is not a journey
This filtering matters because an isolated point can be tempting to overinterpret. A single strange dot does not prove that a sloth crossed a road, entered a garden or visited the shoreline. Scientists look for consistent patterns, examine the quality information attached to each fix and combine positions with other observations.
The GPS location is only one layer. The Urban Sloth Project also collects information such as temperature, humidity, noise, height and activity. Separate backpack-mounted data loggers can record body movement and orientation many times each second. VHF radio collars help researchers find an individual directly in the field. Together, these tools can reveal much more than a line of dots alone.
Why messy data can still help sloths
Imperfect data is not useless data. Once unreliable fixes are identified, the remaining patterns can help researchers study home ranges, tree use and movement through altered landscapes. That evidence can support practical decisions, including where connected canopy is most important or where a wildlife crossing may reduce risk.
The most valuable lesson may be methodological. Good conservation science does not hide the messy points. It records uncertainty, tests different sources of evidence and keeps only the conclusions the data can support.
So if a tracking map appears to put a sloth in the ocean, the researchers have not discovered a new marine species. They have found a noisy GPS fix, and a useful opportunity to show how careful science turns imperfect measurements into better knowledge of life in the trees.
Sources
- The Sloth Conservation Foundation: GPS Collars and Accuracy to Study Sloths
- The Sloth Conservation Foundation: Collars, Backpacks, and Data Loggers
- PLOS ONE: Performance and Accuracy of Lightweight and Low-Cost GPS Data Loggers
Featured image: Rona Neri, via The Sloth Conservation Foundation.