Abstract
A bstract Several methods have been used to identify erroneous animal locations based on Argos satellite data. Using 15,987 satellite locations for 37 gray seals ( Haliockoerus grypus ), we tested a three‐stage filtering algorithm designed to address shortcomings of other filters. In stage 1, for each location, four rates of travel were calculated—the rate to each of the two previous locations and the two subsequent locations. If all four rates exceeded 2 m/sec (95th percentile of our data), the location was removed (7.25% of total locations). Stage 2 incorporated the filtering algorithm developed by McConnell et al. (1992) resulting in the rejection of 22.75% of total locations based on reasonable assumptions of straight‐line travel. At stage 3, the remaining data were evaluated against a distance threshold, defined as the 99th percentile of realized distance traveled over a period of seven days. Locations exceeding this threshold‐were rejected (0.69% of total locations). Overall, the three‐stage filter eliminated fewer locations (30.7 ± 1.62%), than the stage 2 filter alone. Most standard locations were retained, but 85.7% of location class 0, 76.6% of A, and 41.9% of B were also retained. These location classes account for most of data routinely collected but not used.