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Data for Integrated Step Selection Analysis of translocated female greater sage-grouse in the 60 days post-release, North Dakota 2018-2020

Citation

Picardi, Simona (2021), Data for Integrated Step Selection Analysis of translocated female greater sage-grouse in the 60 days post-release, North Dakota 2018-2020, Dryad, Dataset, https://doi.org/10.5061/dryad.44j0zpcf5

Abstract

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

Methods

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’.

Usage Notes

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      

Funding

North Dakota Game and Fish Department

Wyoming Game and Fish Department

North Dakota Game and Fish Department

Wyoming Game and Fish Department