DOI: 10.5061/dryad.q2bvq83hj
title: Greater Sage-grouse nest bowls buffer microclimate in a post-megafire landscape although effects on nest survival are marginal

description: Temperature at fine spatial scales is an important driver of nest site
 selection for many avian species during the breeding season and can
 influence nest success. Sagebrush (Artemisia spp.) communities have areas
 with high levels of vegetation heterogeneity and high thermal variation;
 however, fire removes vegetation that provides protection from predators
 and extreme environmental conditions. To examine  the influence
 of microclimates on Greater Sage-Grouse (Centrocercus urophasianus) nest
 site selection and nest success in a fire affected landscape, we measured
 black bulb temperature (Tbb) and vegetation attributes (e.g. visual
 obstruction) at 3 spatial scales (i.e. nest bowl, microsite, and
 landscape) in unburned and burned areas. Nest bowls exhibited greater
 buffering of Tbb than both nearby microsites and the broader landscape.
 Notably, nest bowls were warmer in cold temperatures, and cooler in hot
 temperatures, than nearby microsites and the broader landscape, regardless
 of burn stage. Nest survival (NS) was higher for nests in unburned areas
 compared to nests in burned areas (unburned NS = 0.43, 95% CI: 0.33 to
 0.54; burned NS = 0.24, 95% CI: 0.10 to 0.46). Amount of bare ground was
 negatively associated with nest survival, but effects diminished as the
 amount of bare ground reached very low levels. Shrub height and visual
 obstruction were positively associated with nest survival during the
 entire study period whereas, minimum Tbb had a weaker effect. Our findings
 demonstrate that thermoregulatory selection by Greater Sage-Grouse at nest
 sites had marginal effects on their nest survival. However, given that
 increases in vegetation structure (e.g. shrub height) provide thermal
 refuge and increase nest survival, vegetation remnants or regeneration in
 a post-fire landscape could be critical to Greater Sage-Grouse nesting
 ecology.
description: We attached 22-g or 30-g ARGOS/GPS Solar PTTs (Microwave
 Telemetry, Columbia, Maryland, USA) to adult and yearling female Greater
 Sage-grouse using a rump-mount technique (Rappole and Tipton 1991).
 GPS-PTT units were
 programmed to collect 4–6 locations per day for each individual during the
 nesting season (1 April to 31 May), and this location frequency allowed us
 to monitor nest status remotely after they were located. We considered a
 female to be nesting if GPS locations remained stationary for &gt;18
 hr during the nesting season. We used
 stainless steel spheres (15.24 cm-diameter, 20 gauge, 304 alloy) painted
 matte black (i.e. black bulb) with 1 temperature sensor (Onset
 Corporation, Bourn, Massachusetts, USA) suspended in the center, to
 measure black bulb temperature
 (<em>T<sub>bb</sub></em>). We measured
 <i>T<sub>bb</sub></i> at 3 spatial scales: nest
 bowl, nest microsite (6 m around nest), and the surrounding landscape
 within unburned and burned areas. An array consisting of 4 black bulbs
 attached to a HOBO 12U (Onset Corporation, Bourn, Massachusetts, USA) data
 logger was deployed at each nest bowl and associated microsite (i.e. nest
 array) and random landscape point (i.e. landscape array). At each nest
 site, we placed 1 black bulb in the nest bowl; and 3 black bulbs at 2 m, 4
 m, and 6 m in random cardinal directions from the nest bowl (i.e.
 microsite). We recorded <i>T<sub>bb</sub></i> at
 15-min intervals for a 24-hr period. We measured
 vegetation cover and height, and visual obstruction along two
 perpendicular 10-m transects centered on each nest bowl or landscape point
 (Connelly et al. 2003). We estimated percent cover of vegetation by
 dropping a pin flag at 0.5-m intervals along transects where we then
 recorded the number of shrubs, perennial grasses, forbs, cheatgrass, and
 bare ground that intersected the pin (i.e. line-point intercept method;
 Canfield 1941). The number of times a specific vegetation type was
 intersected by a pin divided by the total number of points along each
 transect was the estimate of percent cover. We measured the effective
 height (i.e. tallest vegetation that concealed 50% of a 2.5-cm-diameter
 pole) of the tallest shrub, perennial grass, and forb within a 30-cm
 cylinder centered on the transect at 1-m intervals (Musil 2011). We
 measured visual obstruction by placing a 150-cm pole that was taped in 10
 cm increments at 0 m, 5 m, and 10 m along each transect (i.e., Robel Pole
 Method; Robel et al. 1970).  
description: Thermal Nest
 Selection Analysis Requires R Project for
 Statistical Consulting (free software environment available at: https://www.r-project.org/). Figure 1, and data for Tables 2 and 3 in the manuscript can be attained by running lines 1 – 403 in the R script titled CRA_2020_Sagegrouse_Thermal_Nest.R. *User must set the working directory (setwd) to their own files (ex. Line 10) and have the csv file titled nest_temp_2016-2018_final.csv in their file. Figure 2 can be attained by running lines 407 – 548 403 in the R script titled CRA_2020_Sagegrouse_Thermal_Nest.R. *User must set the working directory (setwd) to their own files (ex. Line 10) and have the csv file titled nest_temp_2016-2018_final_naremoved.csv in their file. Thermal Nest Survival Analysis Requires Program MARK (free software available at: http://www.phidot.org/software/mark/). Requires DBF, FTP, and inp files. The user should be able to use the following path in Program Mark to open each of the files associated with each “Stage” of the analysis: File &gt; Open &gt; XXXX.DBF. Example: File &gt; Open &gt; TheCondor_Stage1.DBF