DOI: 10.5061/dryad.xwdbrv1n5
title: Spatial behavior and diet data for discrete-choice analyses: data observed and classified from GPS video camera collars worn by female members of the Fortymile Caribou Herd across Alaska, USA, and Yukon, Canada

description: Competition for resources and space can drive forage selection of large
 herbivores from the bite through the landscape scale. Animal behavior and
 foraging patterns are also influenced by abiotic and biotic
 factors. Fine-scale mechanisms of density-dependent foraging at
 the bite scale are likely consistent with density-dependent behavioral
 patterns observed at broader scales, but few studies have directly tested
 this assertion. Here, we tested if space use intensity, a proxy of
 spatiotemporal density, affects foraging mechanisms at fine spatial scales
 similarly to density-dependent effects observed at broader scales in
 caribou. We specifically assessed how behavioral choices are affected by
 space use intensity and environmental processes using behavioral state and
 forage selection data from caribou (&lt;i&gt;Rangifer tarandus
 granti&lt;/i&gt;) observed from GPS video-camera collars using a
 multivariate discrete-choice modeling framework. We found that
 the probability of eating shrubs increased with increasing caribou space
 use intensity and cover of &lt;i&gt;Salix&lt;/i&gt; spp.
 shrubs, whereas the probability of eating lichen decreased. Insects also
 affected fine-scale foraging behavior by reducing the overall probability
 of eating. Strong eastward winds mitigated the negative effects of insects
 and resulted in higher probabilities of eating lichen. Lastly, caribou
 exhibited foraging functional responses wherein their probability of
 selecting each food type increased as the availability (% cover) of that
 food increased. Space use intensity signals of fine-scale foraging were
 consistent with density-dependent responses observed at larger scales and
 with recent evidence suggesting declining reproductive rates in the same
 caribou population. Our results highlight the potential risks of
 overgrazing on sensitive forage species such as lichen. Remote
 investigation of the functional responses of foraging behaviors provides
 exciting future applications where spatial models can identify
 high-quality habitats for conservation.
description: In the springs of 2018 and 2019, 30 adult female caribou were
 captured and fitted with a GPS-Iridium collar integrated with a camera
 (VERTEX Plus Iridium V 3.0, Vectronic Aerospace GmbH, Germany; see Ehlers
 et al., 2021). All animal captures were conducted by the Alaska Department
 of Fish and Game (ADFG) and approved in accordance with ADFG animal
 welfare standards (IACUC Permit numbers through ADFG: 0002-2018 and
 0002-2019). Video collars recorded a 9-second video every 20 minutes
 during daylight hours (14 – 18 hours/day) from 10 May – 10 September 2018
 and 2019. The internal GPS recorded spatial locations immediately
 following each 9-second video recording (see Ehlers <em>et
 al</em>. 2021). We used video collars to analyze the behavior and
 food choices of caribou during summer. We processed data from video
 collars using a two-phased approach that included both community science
 volunteers and botanists (see Ehlers <em>et al</em>. 2021 for
 details). In 18,134 processed videos, caribou behavior was classified into
 six categories for our spatial analysis of behavior: eating, ruminating,
 traveling, stationary awake, napping, or other (e.g., drinking, licking
 soil for minerals, and wading; Ehlers <em>et al.</em>, 2021).
 We removed 44 classified videos that were missing spatial locations due to
 GPS error, leaving a final sample size of 18,090 behavior-classified
 videos for our spatial behavior and diet analyses.
description: # Spatial behavior and diet data for discrete-choice analyses: data
 observed and classified from GPS video camera collars worn by female
 members of the Fortymile Caribou Herd across Alaska, USA, and Yukon,
 Canada [Access this dataset on
 Dryad](https://doi.org/10.5061/dryad.xwdbrv1n5) We have submitted our
 classified data set for the behavior choice of eating and the food choice
 of lichen. Data frames were set up like these for the other behaviors and
 food choices measured in this study. We have included these two datasets
 and have modified the animal locations to respect data-sharing agreements
 and protect animal locations. ## Description of the data and file
 structure In the springs of 2018 and 2019, 30 adult female caribou were
 captured and fitted with a GPS-Iridium collar integrated with a camera
 (VERTEX Plus Iridium V 3.0, Vectronic Aerospace GmbH, Germany; see Ehlers
 et al., 2021). All animal captures were conducted by the Alaska Department
 of Fish and Game (ADFG) and approved in accordance with ADFG animal
 welfare standards (IACUC Permit numbers through ADFG: 0002-2018 and
 0002-2019). Video collars recorded a 9-second video every 20 minutes
 during daylight hours (14 – 18 hours/day) from 10 May – 10 September 2018
 and 2019. The internal GPS recorded spatial locations immediately
 following each 9-second video recording (see Ehlers et al. 2021). We used
 video collars to analyze the behavior and food choices of caribou during
 summer. We processed data from video collars using a two-phased approach
 that included both community science volunteers and botanists (see Ehlers
 et al. 2021 for details). In 18,134 processed videos, caribou behavior was
 classified into six categories for our spatial analysis of behavior:
 eating, ruminating, traveling, stationary awake, napping, or other (e.g.,
 drinking, licking soil for minerals, and wading; Ehlers et al., 2021). We
 removed 44 classified videos that were missing spatial locations due to
 GPS error, leaving a final sample size of 18,090 behavior-classified
 videos for our spatial behavior and diet analyses. ## Files: Included are
 two datasets included: 1. DC for the behavior choice of eating (behavior
 choice data set) 2. DC for the food choice of lichen (food choice data
 set) These are the data associated with the discrete choice model specific
 to the behavior choice of eating and the food choice for eating lichen.
 Animals were observed eating, for example, at these locations through GPS
 video camera collars that recorded a spatial location at the time of the
 event. For each behavior or food choice set, the data frames are similar
 and vary only in the final variables included in the models that explained
 the data best. ## Variable Description: Included with each dataset on a
 separate worksheet tab is a description of the variables. ## Code/Software
 We conducted all analyses in R (R Core Team, 2020).