TRACKING WILDLIFE BY SATELLITE 



21 



0.8 



Fig. 16. Relation between the elevation of nine 

 study sites and the strength of the correlation 

 (Batschelet 1981:187) between satellite 

 azimuth at closest approach and the azimuth 

 of error. Locations, in order of increasing 

 elevation, are Inuvik, Northwest Terri- 

 torities; Nome, Alaska; Fairbanks, Alaska 

 (three locations); Chatham Dome, AK; Mur- 

 phy Dome, Alaska; Galbraith Lake, Alaska; 

 Gardiner-Mammoth area of Yellowstone 

 National Park. Argos's calculations assumed 

 that all PTT's were at sea level. 



C 



o 



5 0.6 





 o 

 O 



O 



O 



0.4 1 



0.2 



500 1POO 100 2,000 



Location Elevation (m) 



Long-term Activity Index 



We did not calibrate 24-h sensors to specific behavior 

 patterns because it was difficult to keep animals under 

 constant surveillance. However, from extensive experi- 

 ence in the caribou project, we found that successive 

 counts of zero meant that the animal had died or the collar 

 had been shed. In some cases, this indicator quickly re- 

 sulted in aerial searches to find the animal, which allowed 

 a better chance to determine the cause of death and retrieve 

 the collar. 



Results from caribou studies supported the concept that 

 the 24-h index was related to the amount of activity. Stud- 

 ies of the Porcupine and Central Arctic caribou herds 

 revealed a strong (P < 0.0001) correlation between the 

 mean monthly 24-h activity index and monthly movement 

 rates (Fancy et al. 1989). Both indices peaked in July and 

 had their lowest values in midwinter. It also seemed that 

 the 24-h index was useful in identifying when the caribou 

 cows bore young: for a caribou known to be pregnant, a 

 notable drop in the index indicated calving (Fig. 19). 



Short-term Activity Index 



Calibration of the Short-term Activity Index 



Calibration studies were conducted with captive car- 

 ibou, elk, mule deer, and moose. The purpose was to 

 associate counts or series of counts with gross activity 

 categories (e.g., inactive, walking, feeding) and apply the 

 interpretation to free-ranging animals. Calibration in the 

 wild was performed only for elk. For each species, pre- 

 liminary experiments were conducted to determine the 

 inclination of the mercury switch that resulted in the 

 best discrimination between activity types. Some switch 



angles were so extreme that motion was never detected 

 because the mercury never moved back and forth, while 

 other angles produced high counts from subtle move- 

 ments, such as those from respiration. 



Methods. All experiments were conducted with a spe- 

 cially designed collar that allowed the investigator to ad- 

 just the inclination of the mercury tip-switch for recording 

 activity data (Pank et al. 1985, 1987; Fancy et al. 1988). 

 The collar was otherwise identical to other second-genera- 

 tion collars we used. 



Data were obtained at 60-s intervals by using a Telonics 

 uplink receiver (Beaty et al. 1987) that received transmis- 

 sions from active PTT's within a 2-km radius. Captive 

 animals were fitted with the experimental collar and ob- 



_ 6i 



5- 



O A 



LU 



15 3 



10 20 30 40 50 60 

 Maximum Satellite Elevation () 



70 



Fig. 17. Relation between longitudinal errors of location esti- 

 mates and maximum elevation of the satellite for 20 known 

 positions of Dall sheep in Alaska. Argos's calculations as- 

 sumed that the PTT was at sea level. Data courtesy of M. 

 Hansen, University of Alaska. 



