Moderating <scp>A</scp>rgos location errors in animal tracking data

Summary The A rgos S ystem is used worldwide to satellite‐track free‐ranging animals, but location errors can range from tens of metres to hundreds of kilometres. Low‐quality locations ( A rgos classes A , 0, B and Z ) dominate animal tracking data. Standard‐quality animal tracking locations ( A rgos classes 3, 2 and 1) have larger errors than those reported in A rgos manuals. The D ouglas A rgos‐filter ( DAF ) algorithm flags implausible locations based on user‐defined thresholds that allow the algorithm's performance to be tuned to species' movement behaviours and study objectives. The algorithm is available in M ovebank – a free online infrastructure for storing, managing, sharing and analysing animal movement data. We compared 21,044 temporally paired global positioning system ( GPS ) locations with A rgos location estimates collected from A rgos transmitters on free‐ranging waterfowl and condors (13 species, 314 individuals, 54,895 animal‐tracking days). The 95th error percentiles for unfiltered A rgos locations 0, A , B and Z were within 35·8, 59·6, 163·2 and 220·2 km of the true location, respectively. After applying DAF with liberal thresholds, roughly 20% of the class 0 and A locations and 45% of the class B and Z locations were excluded, and the 95th error percentiles were reduced to 17·2, 15·0, 20·9 and 18·6 km for classes 0, A , B and Z , respectively. As thresholds were applied more conservatively, fewer locations were retained, but they possessed higher overall accuracy. Douglas A rgos‐filter can improve data accuracy by 50–90% and is an effective and flexible tool for preparing Argos data for direct biological interpretation or subsequent modelling.