Fine-scale Movement Patterns of Coyotes (Canis latrans) on the
INEEL in Idaho.
Coyote depredation has been a persistent problem to the livestock
industry in the intermountain west for decades. As a pest species, they
can also pose problems to species other than domestic livestock, such as
game and sensitive species. While current depredation mitigation programs
are effective and clearly needed, a more complete understanding of how
coyotes move and use space provides a more solid framework for managers to
alter current techniques to increase efficiency and effectiveness.
Therefore, advancing our understanding of coyote space-use and movement
patterns is a crucial step in the management of this intractable predator.
Traditional methods for understanding space-use and movement patterns
of coyotes (and other medium to large sized carnivores) have relied on VHF
radio telemetry and quantitative techniques for home range estimation.
This approach has been criticized due to the fact that home range
estimation often does not examine meaningful hypotheses about an animal's
movements and behavior (Kernohan et al. 2001). Recent advancements in
technology now provide the means to record fine-scale location data on
coyotes at a rate (e.g. every 5 minutes) and volume (e.g. 12,000
locations/coyote/sampling period) that only a few years ago were
unattainable. This new approach provides a unique dataset that allows for
more meaningful investigations into coyote movement patterns and the
internal anatomy of their home ranges.
The overall goal of this project is to better understand how coyotes
actually move within their home ranges, paying special attention to the
temporal component of the dataset. The 2004 year represents the first
field season for this project, and specific goals for the year included
- Capture and radio-collar 30-40 coyotes that reside in several
contiguous territories in the study area on the INEEL.
- Test four4 new drop-off Global Positioning System (GPS) Lotek
collars and analyze the data from retrieved collars to determine the
appropriate sampling scheme necessary to gather meaningful fine-scale
- Using the information from objective # 2, recapture resident coyotes
and deploy 16 GPS collars to gather fine-scale data.
- Test the efficacy of new collaring scheme that increases the success
of recapturing specific animals via helicopter net gunning.
Accomplishments through 2004
- Thirty adult coyotes (16 females/14 males) were opportunistically
captured during late January 2004 via helicopter and net-gun. Each
coyote was processed and fitted with a 65 gram VHF radio collar. Two
pairs of coyotes from adjacent packs were also fitted with a GPS collars
set to record locations every 5 minutes. Figure 9-3 shows the
distribution of territories monitored during the 2004 season.
- The testing of the GPS collars showed exceptional accuracy (avg.
error < 25 meters) and performance with an average acquisition success
in the high 90th percent. Most missing locations were preceded and
followed by accurate locations very near den sites, suggesting that the
animals were underground and out of satellite view.
- Given the roughly inverse relationship between the absolute number
of locations and the sampling interval of the collars, the data were
sub-sampled to determine which interval provided the best data set for
future sampling periods. It was concluded that although collecting
locations every 5 minutes utilizes battery life rather-quickly, it also
provides the most accurate and useful data for the question of interest
(i.e. fine-scale space-use and movements). Even the most conservative
re-sample (i.e. every 10 minutes) frequently resulted in interactions
between coyotes and re-visitation to point locations being missed.
Figure 9-4 shows the difference in total straight-line distance traveled
for a single coyote at different sampling intervals during a single
sampling period. Figure 9-5 shows an example of how different sampling
intervals change the shape of an individual's movement path.
- The use of two separate collars (one VHF and GPS) is a rather new
approach to monitoring wildlife species. The idea is to keep radio
contact with animals after the GPS collars drop-off, and to increase the
probability and efficiency of recapturing specific coyotes multiple
times by homing in on the VHF frequencies with the helicopter during
capture. The second capture in early December 2004 showed the success of
such an approach. With 16 GPS collars available for deployment, 12
collared animals were able to be recaptured. GPS only had to be deployed
on four unknown animals (three of which proved to be pack associates of
previously collared animals).
The project is still in the data collection phase, although a few
preliminary results have been provided below for those interested.
- Home ranges for coyotes on the INEEL site appear to be relatively
large compared to previous studies. While this trend is true for most
territories monitored, one pair of elderly coyotes (approximately 10
years old) appear to be an exception with their comparatively small home
range (see Figure 9-3).
- Using serial locations to examine coyote movement patterns allows
one to visualize how coyotes actually travel within their home ranges.
Figure 9-6 shows the 5-minute GPS data (approximately 12,000 locations)
and travel paths superimposed on the home range for a single coyote. A
computer algorithm was used to divide locations into either "stationary"
or "moving." This allows us to group locations into unique continuous
"movement paths" and "resting spots" for further analyses (Figure 9-7).
Plans for Continuation
- Two additional captures are scheduled for 2005 (Spring and
Fall/Winter) with plans to deploy between 16 and 24 GPS collars during
each period. This should generate roughly 500,000 coyote locations.
Investigators and Affiliations
Mike Ebinger, graduate
student, Department of Forestry, Range, and Wildlife Science, Utah State
University, Logan, UT
Mike Jaeger, Research
Zoologist, USDA/APHIS/WS/National Wildlife Research Center, Predator
Ecology Field Station, Logan, UT.
Wildlife Research Center, Ft. Collins, Colorado.