Estimating habitat selection when GPS fix success is less than 100%.

Inferences about habitat selection by animals derived from sequences of relocations obtained with global positioning system (GPS) collars can be influenced by GPS fix success. Environmental factors such as dense canopy cover or rugged terrain can reduce GPS fix success, making subsequent modeling problematic if fix success depends on the selected habitat. Ignoring failed fix attempts may affect estimates of model coefficients and lead to incorrect conclusions about habitat selection. Here, we present a habitat selection model that accounts for missing locations due to habitat-induced data losses, called a resource selection function (RSF) for GPS fix success. The model's formulation is similar to adjusting estimates of probability of occupancy when detection is less than 100% in patch occupancy sampling. We demonstrate use of the model with GPS data collected from an adult female mule deer (Odocoileus hemionus) and discuss how to analyze data from multiple animals. In the simulations presented, our habitat selection model was generally unbiased for GPS data sets missing up to 50% of the locations.

[1]  Hannah W. McKenzie,et al.  Inferring linear feature use in the presence of GPS measurement error , 2009, Environmental and Ecological Statistics.

[2]  RYAN M. NIELSON,et al.  Winter Habitat Selection of Mule Deer Before and During Development of a Natural Gas Field , 2006 .

[3]  Robert A. Gitzen,et al.  Analysis of Resource Selection Using Utilization Distributions , 2006 .

[4]  Philip D. McLoughlin,et al.  Overcoming radiotelemetry bias in habitat- selection studies , 1999 .

[5]  Christopher S. Nations,et al.  Estimation of animal location from radio telemetry data with temporal dependencies , 2006 .

[6]  David R. Anderson,et al.  Model Selection and Multimodel Inference , 2003 .

[7]  M. Hebblewhite,et al.  Are All Global Positioning System Collars Created Equal? Correcting Habitat-Induced Bias Using Three Brands in the Central Canadian Rockies , 2007 .

[8]  K. Parker,et al.  Interpreting Resource Selection at Different Scales for Woodland Caribou in Winter , 2006 .

[9]  Arthur R. Rodgers,et al.  PERFORMANCE OF A GPS ANIMAL LOCATION SYSTEM UNDER BOREAL FOREST CANOPY , 1995 .

[10]  D. Seip,et al.  Grizzly Bear Behavior and Global Positioning System Collar Fix Rates , 2008 .

[11]  Hugh P. Possingham,et al.  A SPATIALLY EXPLICIT HABITAT SELECTION MODEL INCORPORATING HOME RANGE BEHAVIOR , 2005 .

[12]  Yosef Cohen,et al.  Effects of moose movement and habitat use on GPS collar performance , 1996 .

[13]  Christopher O. Kochanny,et al.  GPS radiotelemetry error and bias in mountainous terrain , 2002 .

[14]  Eon,et al.  Effects of a stationary GPS fix-rate BIAS on habitat-selection analyses , 2003 .

[15]  S. Creel,et al.  Elk alter habitat selection as an antipredator response to wolves , 2005 .

[16]  M. Boyce,et al.  WOLVES INFLUENCE ELK MOVEMENTS: BEHAVIOR SHAPES A TROPHIC CASCADE IN YELLOWSTONE NATIONAL PARK , 2005 .

[17]  Gordon B. Stenhouse,et al.  Removing GPS collar bias in habitat selection studies , 2004 .

[18]  J. Andrew Royle,et al.  ESTIMATING SITE OCCUPANCY RATES WHEN DETECTION PROBABILITIES ARE LESS THAN ONE , 2002, Ecology.

[19]  Fred L Ramsey,et al.  Persistence and heterogeneity in habitat selection studies using radio telemetry. , 2003, Biometrics.

[20]  B. Manly,et al.  Resource selection by animals: statistical design and analysis for field studies. , 1994 .

[21]  David W. Hosmer,et al.  Applied Logistic Regression , 1991 .