DOI: 10.5061/dryad.f9p3dq4
title: Data from: Continuous time resource selection analysis for moving animals

description: 1. Resource selection analysis (RSA) seeks to understand how spatial
 abundance covaries with environmental features. By combining RSA with
 movement, step selection analysis (SSA) has helped uncover the mechanisms
 behind animal relocations, thereby giving insight into the movement
 decisions underlying spatial patterns. However, SSA typically assumes that
 at each observed location, an animal makes a `selection' of the next
 observed location. This conflates observation with behavioural mechanism
 and does not account for decisions occurring at any other time along the
 animal's path. 2. To address this, we introduce a continuous time
 framework for resource selection. It is based on a switching
 Ornstein-Uhlenbeck (OU) model, parameterised by Bayesian Monte Carlo
 techniques. Such OU models have been used successfully to identify
 switches in movement behaviour, but hitherto not combined with resource
 selection. We test our inference procedure on simulated paths,
 representing both migratory movement (where landscape quality varies
 according to season) and foraging with depletion and renewal of resources
 (where the variation is due to past locations of the animals). We apply
 our framework to location data of migrating mule deer (Odocoileus
 hemionus) to shed light on the drivers of migratory decisions. 3. In a
 wide variety of simulated situations, our inference procedure returns
 reliable estimations of the parameter values, including the extent to
 which animals trade-off resource quality and travel distance (within 95%
 posterior intervals for the vast majority of cases). When applied to the
 mule deer data, our model reveals some individual variation in parameter
 values. Nevertheless, the migratory decisions of most individuals are
 well-described by a model that accounts for the cost of moving and the
 difference between instantaneous change of vegetation quality at source
 and target patches. 4.We have introduced a technique for inferring the
 resource-driven decisions behind animal movement that accounts for the
 fact that these decisions may take place at any point along a path, not
 just when the animal's location is known. This removes an
 oft-acknowledged but hitherto little-addressed shortcoming of stepwise
 movement models. Our work is of key importance in understanding how
 environmental features drive movement decisions and, as a consequence,
 space use patterns.
description: Mule deer movements
 spring 2016 WyomingThe data file represents
 GPS relocations from 28 adult (&gt; 1:5 years of age) female mule between
 March and August 2016. Deer were captured in March 2016 using a netgun
 fired from a helicopter near Cody, Wyoming (USA). Collars (Advanced
 Telemetry Systems, Iridium, Isanti, Minnesota, USA) were programmed to
 take a location every 2 hours. All deer were captured following protocols
 consistent with the University of Wyoming standards. Note, this database
 is a small subset of data from a larger collaring project. Program R was
 used to create the datafile in April 2017. Each row in the database
 represents a single GPS relocation. Description of the column headings are
 as follows: AID - unique identifier for each animal; hour - hour as
 decimal number, 0 to 23; min - minute as decimal number, 0 to 59; year -
 year with century; month - month as decimal number, 1 to 12; day - day as
 decimal number 1 to 31; jul - julian date as decimal number, 0 to 365;
 date - date in POSIX format (local time; Mountain Standard Time) for
 program R; Long - longitude; Lat - latitude. There are 54,528 rows in the
 database, with an average of 1,947 relocations per individual. Please
 contact Jerod Merkle (jmerkle@uwyo.edu) or Matt Kauffman
 (mkauffm1@uwyo.edu) at University of Wyoming prior to using these data. If
 neither of these people can be reached, please contact the Wyoming
 Cooperative Fish and Wildlife Research Unit at University of
 Wyoming.MuleDeer_Cody_ForPotts.csv