DOI: 10.5061/dryad.44j0zpcf5
title: Data for Integrated Step Selection Analysis of translocated female greater sage-grouse in the 60 days post-release, North Dakota 2018-2020

description: The data include used and random available steps at 11-hour resolution
 generated for 26 female greater sage-grouse in the 60 days
 post-translocation to North Dakota, with associated environmental
 predictors and individual information. The code fits individual habitat
 selection models in an Integrated Step Selection Analysis framework. Data
 used to fit the models described in: Picardi, S., Ranc, N., Smith, B.J.,
 Coates, P.S., Mathews, S.R., Dahlgren, D.K. Individual variation in
 temporal dynamics of post-release habitat selection. Frontiers in
 Conservation Science (in review) Code used to implement the analysis is
 available on
 GitHub: https://github.com/picardis/picardi-et-al_2021_sage-grouse_frontiers-in-conservation
description: We equipped sage-grouse
 with rump-mounted Global Positioning System (GPS) Platform Transmitter
 Terminal (PTT) ARGOS-enabled tracking devices (23 g, GeoTrak, Inc.)
 scheduled to acquire 6 locations a day at irregular intervals. We only
 retained 11-hour steps within the first 60 days post-release for further
 analysis. For each used step, we generated a set of 100 random steps drawn
 from the empirical population-level distribution of steps lengths and
 turning angles (gamma with shape = 0.72 and scale = 725.04; von Mises with
 mean = 0.00 and concentration = 0.10). We intersected each step with
 environmental covariates including percent sagebrush cover, percent
 herbaceous cover, slope, and distance to roads. We obtained percent
 sagebrush and herbaceous cover data at a 30-m resolution from the National
 Land Cover Database (NLCD 2016;
 https://www.mrlc.gov/national-land-cover-database-nlcd-2016). We obtained
 data on slope at a 30-m resolution from Landfire (https://landfire.gov/).
 We obtained data on roads from the USGS National Transportation Dataset
 (USGS 2014), including paved roads, highways, and interstates as well as
 gravel or dirt roads. We rasterized the roads vector layer to a 30-m
 resolution and calculated distance of each pixel to the nearest road. We
 log-transformed distance values to allow for a spatial decay in the
 behavioral response to roads. All habitat variables are scaled and
 centered. Data processing was conducted in R (R Core Team, 2020) using the
 packages ‘amt’, ‘tidyverse’, ‘sf’, ‘raster’, and ‘lubridate’.
description: Fields: "hen_name": individual
 identifier "status": individual
 reproductive status; brood-rearing (TBH) or non-brood-rearing
 (NBH) "step_id_": serial
 number to uniquely identify steps                 "case_": Boolean
 indicating whether the step is used (TRUE) or available (i.e., random;
 FALSE)                    "t1_": timestamp at the
 beginning of the step                     "t2_": timestamp at the
 end of the step                      "dt_": duration of the
 step (h)                      "sl_": step length
 (m)                     "ta_": turning angle
 (degrees)                      "cos_ta_": cosine of
 the turning angle                  "log_sl_": logarithm of
 the step length                 "slope_scaled": value
 of slope (degrees; scaled and centered)             "dist_to_roads_log_scaled": value of distance to nearest road (m; scaled and centered) "sagebrush_scaled": value of sagebrush cover (percent; scaled and centered)        "perennial_herb_scaled": value of perennial herbaceous cover (percent; scaled and centered)    "dst": days since translocation                      "log_dst": logarithm of days since translocation