DOI: 10.5061/dryad.gqnk98svz
title: Counts of winter ticks on live-captured moose in western US

description: Data include counts of winter ticks (ticks.hind) along transects of
 variable length (transect.cm.hind) on the rumps of live-captured moose in
 5 western US states (state).  Other attribute data include the
 moose ID, capture date, local moose density (density.category), migratory
 status (migratory), presence of other ungulates on shared winter range
 (shared.winter.range).  A suite of climate metrics are also
 included for each record specific to that capture location and year,
 labelled according to the biological season during which they were
 summarized (q=questing [fall]; d=dropoff [spring]; s=summer) as described
 in the manuscript.  Metrics include the proprortionate snow cover
 (SnowProp), amount of snow water equivalent during midpoint and endpoint
 of season (SWEmid, SWEend), mean temperature (TempMean), number of days
 below 0 and -20 degrees C (TempDays0, TempDaysm20), average relative
 humidity daily minimum and maximum (RHmin, RHmax), cumulative
 precipitation (Precip), and landcover category (landcover). 
 Lastly, also included are quadratic terms for some variables (_2) and
 10-year averages of each metric spanning the study period, 2013-2022,
 (_avg). 
description: Ticks were counted along transects through the hair of moose
 captured during winter.  Analyses were focused specifically on ticks
 counted on the rump area.  Transects varied in length so the length of
 transects was used as an offset term in models.  Please see associated
 manuscript for methodological details regarding tick load data collection
 and associated attribute data.
description: # Winter tick loads on moose in western US
 ## Description of the data
 and file structure Data include: **ticks.hind**: counts of individual
 winter ticks, Dermacentor albipictus, found along transects through the
 hair on the rumps of 750 live-captured moose, Alces alces, during winter
 (December 13%, January 52%, February 20%, March 16%) in 5 western US
 states (state). **transect.cm.hind**: length of the transects along which
 hair was parted and searches for ticks were conducted **moose ID**:
 individual moose that were captured **capture date**: date of the capture
 events **density.category**: We used expert opinion to characterize
 individual moose as being located within areas of low (&lt; 0.21), medium
 (between 0.21 and 0.41), or high (&gt; 0.41) adult females per km2,
 following quantitative delineation of moose densities with focus on adult
 females by Schmidt et al. (2007). We imagined overlaying a 5 x 5 km
 neighborhood surrounding each winter capture location and the biologist
 with field experience in each area estimated how many adult female moose
 would be found in that neighborhood; our low density category corresponded
 to ≤5 cows sharing that 25-km2 neighborhood, medium density to 6–10 cows
 sharing that neighborhood, and high density to &gt;10. **migratory**: We
 treated seasonal migration as a proxy for spatial overlap of individual
 moose during the tick drop-off and questing seasons, and assigned
 ‘resident’, ‘migratory’, or ‘unknown’ categorical depictions of migration
 behavior according to project-specific spatial analyses or subjective
 assessments of seasonal movements. We assumed that migration behavior
 subsequent to capture was an adequate proxy for behavior during the year
 prior to capture, when measured tick loads would have accumulated on each
 moose. **shared.winter.range**: presence of other ungulates on shared
 winter range; We included a binary categorical variable concerning whether
 moose shared their winter range with deer or elk populations of equal or
 greater abundance based on field experience in each study area **Climate
 metrics**: A suite of climate metrics are also included for each record
 specific to that capture location and to the specific year and season
 prior the capture event. These are labelled according to the biological
 season prior to moose captures during which they were summarized
 **(q=questing [fall, 15-Sep to 30-Nov]; d=dropoff [spring, 15-Mar to
 30-Apr]; s=summer [1-Aug to 14-Sep])** as described in the manuscript. 
 **qSnowProp & dSnowProp**: proportion of days with measurable snow
 across questing and drop-off periods according to daily gridded measures
 of normalized difference snow index (NDSI) detections of snow cover from
 MODIS version 6 MOD10A1 (Terra) and MYD10A1 (Aqua) data at a 500 m x 500 m
 resolution (Hall et al. 2006). We merged Terra and Aqua NDSI data
 according to the maximum snow cover value measured between each platform
 per day (Tran et al. 2019) and used a threshold NDSI value of 0.1 to
 distinguish snow from non-snow, following Hussainzada et al. (2021).
 **qSWEmid, qSWEend, dSWEmid, dSWEend:** the amount of snow using estimates
 of snow water equivalent (SWE) during the mid-point and end-point of the
 both the drop-off and questing periods using daily SWE data from Daymet
 V4R1 at 1 km x 1 km resolution. **qTempMean, dTempMean, sTempMean**: mean
 temperature; We quantified temperature as the mean of daily low
 temperatures across each of the late summer, questing, and drop-off
 periods using Daymet version 4 revision 1 data at a 1 x 1 km resolution
 (Thornton et al. 2022), accessed via the R package (Hufkens et al. 2018, R
 Core Team 2018). **qTempDays0, qTempDaysm20, dTempDays0, dTempDaysm20**:
 To capture potential threshold effects of cold temperatures during the
 questing and drop-off seasons, we also used the same Daymet data to
 measure the number of days with low temperatures below thresholds of 0˚
 (Powers and Pekins 2020) and -20C˚ (Holmes et al. 2018). **qRHmin, qRHmax,
 sRHmin, sRHmax**: We quantified daily minimum and maximum relative
 humidity during the late summer and questing seasons using daily minimum
 and maximum estimates of vapor pressure deficit and temperature produced
 by the PRISM (parameter-elevation regressions on independent slopes model)
 Climate Group at 4 km x 4 km resolution (PRISM Climate Group 2023) and
 following equations of Daly et al. (2015). **sPrecip**: cumulative
 precipitation; we used daily precipitation data from PRISM, also at 4 km x
 4 km resolution, to quantify the total precipitation during the late
 summer period. **landcover:** We characterized vegetation type at each
 capture site according to year-specific land cover data using the
 International Geosphere Biosphere Programme (IGBP) global vegetation
 classification of the moderate resolution imaging spectroradiometer
 (MODIS) land cover product (MCD12Q1) at a 500 m x 500 m resolution,
 following Liang et al. (2015). We simplified the 6 land cover types
 identified in the study areas (evergreen forest, woody savanna, savanna,
 grassland, cropland, and urban) into 2 land cover categories by
 aggregating together the first three (“forest”) and the latter three
 (“open”). \****_2**: Varibles with a "2" after the name are
 simply quadratic (squared) terms for some variables (_2) **qSnowPropavg,
 dSnowPropavg, qSWEmidavg, qSWEendavg, dSWEmidavg, dSWEendavg,
 qTempMeanavg, dTempMeanavg, sTempMeanavg, qTempDays0avg, dTempDays0avg,
 qRHmaxavg, qRHminavg, sRHmaxavg, sRHminavg, sPrecipavg**: These variables
 are 10-year averages of the same metrics described above, averaged across
 the entire study period, 2013-2022, as opposed to the variables above
 which were estimated specific to the year prior to data collection for
 each tick count measurement.