• Version
• Download 6
• File Size 259.23 KB
• Create Date 1 January 1998
• Download

Satellite radiotelemetry is a useful method of tracking movements of animals that travel long distances or inhabit remote areas. However, the logistical constraints that encourage the use of satellite telemetry also inhibit efforts to assess accuracy of the resulting data. To investigate effectiveness of methods that might be used to improve the reliability of these data, we compared 3 sets of criteria designed to select the most plausible locations of polar bears (Ursus maritimus) that were tracked using satellite radiotelemetry in the Bering, Chukchi, East Siberian, Laptev, and Kara seas during 1988-93. We also evaluated several indices of location accuracy. Our results suggested that, although indices could provide information useful in evaluating location accuracy, no index or set of criteria was sufficient to identify all the implausible locations. Thus, it was necessary to examine the data and make subjective decisions about which locations to accept or reject. However, by using a formal set of selection criteria, we simplified the task of evaluating locations and ensured that decisions were made consistently. This approach also enabled us to evaluate biases that may be introduced by the criteria used to identify location errors. For our study, the best set of selection criteria comprised: (1) rejecting locations for which the distance to the nearest other point from the same day was >50 km; (2) determining the highest accuracy code (NLOC) for a particular day and rejecting locations from that day with lesser values; and (3) from the remaining locations for each day, selecting the location closest to the location chosen for the previous transmission period. Although our selection criteria seemed unlikely to bias studies of habitat use or geographic distribution, basing selection decisions on distances between points might bias studies of movement rates or distances. It is unlikely that any set of criteria will be best for all situations; to make efficient use of data and minimize bias, these rules must be tailored to specific study objectives.