DOI: 10.5061/dryad.ncjsxksvx
title: Why did the chicken NOT cross the road? Anthropogenic development influences the movement of a grassland bird

description: Movement and selection are inherently linked behaviors that form the
 foundation of a species space-use patterns. Anthropogenic development in
 natural ecosystems can result in a variety of behavioral responses that
 can involve changes in either movement (speed or direction of travel) or
 selection (resources used) behaviors which in turn may cause differential
 population level consequences including loss of landscape level
 connectivity. Understanding how a species alters these different behaviors
 in response to human activity is essential for effective conservation. In
 this study, we investigated the effects of anthropogenic development such
 as roads, power lines and oil wells on the greater prairie-chicken
 (Typanuchus cupido) in the post-nesting and nonbreeding season. Our first
 objective was to assess if greater prairie-chickens alter their movement
 behaviors or their selection patterns when encountering oil wells, power
 lines, or roads using integrated step selection analysis (iSSA). Our
 second objective was to determine if prairie-chickens avoided crossing
 linear features such as roads or power lines by comparing the number of
 crossing events in greater prairie-chicken movement tracks to the number
 of movements that crossed these features in simulated movement tracks.
 Based on the iSSA analysis, we found that greater prairie-chickens avoided
 oil wells, power lines, and roads in both seasons, but found little
 evidence for changes in speed or direction of movement at the
 population-level. However, at the individual level we observed individuals
 using a number of strategies near development including avoidance and
 increased rates of movements. Furthermore, prairie-chickens traveled
 across roads and power lines at much lower rates than expected. Consistent
 avoidance of development resulted in indirect habitat loss for greater
 prairie-chickens. These behaviors also resulted in a potential loss of
 landscape connectivity for this species. By considering both movement and
 selection we were able to develop an ecological understanding of how
 increasing human activity may influence the space-use of this species of
 conservation concern. This research provides insight into the
 decision-making process by animals when they encounter anthropogenic
 development by considering multiple behavioral responses. --
description: We
 captured prairie-chickens in March and April of each year from 2014 – 2019
 using walk-in funnel traps at lek sites (communal courtship arenas). We
 aged and sexed all captured individuals based on plumage and the presence
 of secondary sex characteristics (enlarged air sacs and eye combs in
 males; Henderson et al. 1967), and we marked males and females with a
 uniquely numbered aluminum leg band to aid in identification. We attached
 rump-mounted, 22-gram ARGOS GPS transmitters (PTT-100, Microwave
 Telemetry, Columbia, Maryland, USA) to all captured female
 prairie-chickens. The GPS transmitters were programmed to record one GPS
 location every hour from 700 to 1900 from 1 March to 31 August and every
 two hours during the remainder of the year. All females were monitored
 remotely via data downloads from the ARGOS server as data became
 available. The GPS transmitters were estimated to have an average error of
 less than 20 meters (personal communication Microwave
 Telemetry). We focused on
 two seasons for our analysis, the post-nesting and the nonbreeding season.
 We defined the post-nesting season as the period after a female concluded
 nesting activity for the year (typically late May to early June) until 14
 September when the last broods are likely to have broken up prior to the
 fall/winter season. The start of the post-nesting period was determined
 separately for each individual based on when individual females were
 observed leaving the nest site (Londe et al. 2019). This period
 corresponds to the time when females are either raising newly hatched
 chicks or are recovering from previous reproductive efforts. Due to a lack
 of data about brood presence and survival in the early parts of our study,
 we combined data for all females during this period regardless of
 reproductive status. Previous studies suggest habitat selection patterns
 are likely similar between brooding and nonbrooding female
 prairie-chickens (Londe et al. 2019, Londe et al. 2021). The nonbreeding
 season was defined as the period from 15 September to 15 March of the
 subsequent year. This period corresponds to the fall and winter period
 when females are not engaged in any reproductive activity. We did not
 include telemetry locations from the period when females are attending
 leks (mid-March to late April) and nesting (early April to nest hatch or
 failure) as movements during these periods are limited and tend to be
 concentrated on leks or nest locations. For prairie-chickens that were
 monitored in multiple years in the study, we treated each year (hereafter,
 prairie-chicken year) as a separate individual to account for changing
 habitat conditions between years of the study (Hovick et al.
 2015). <i>Integrated step
 selection analysis</i>  Integrated step
 selection analysis (iSSA) allows for the simultaneous modelling of
 selection and movement processes by comparing environmental and habitat
 variables observed during a step (straight line connecting two GPS
 locations) and variables that describe an animal’s movement pattern, such
 as step length and turning angles (change in direction of travel between
 two steps), to those same variables recorded on random steps (Fortin et
 al. 2005, Thurfjell et al. 2014). For our analysis, we used observed
 prairie-chicken steps where the beginning and ending locations were at GPS
 telemetry locations that were recorded 2 hours apart, and were part of a
 series of steps that included ≥ 3 telemetry locations (this is the minimum
 number of consecutive relocations required to calculate valid turning
 angles; Avgar et al. 2016). For each observed step, we generated 10 random
 steps that shared a starting location with the observed step, but where
 step length and turning angles of the random step was randomly selected
 from a gamma and von Mises distribution, respectively (Avgar et al. 2016,
 Signer et al. 2019). We assigned habitat attributes to each step by
 extracting environmental variables from GIS rasters at the beginning and
 ending location for each step. Each set of observed and ten random steps
 was defined as a choice set and were compared using conditional logistic
 regression models in program R using the <i>survival</i>
 package (Therneau and Lumley 2015). Prior to analysis, we removed six
 individuals from the post-nesting season analysis and nine individuals
 from the nonbreeding season analysis that had established home ranges in
 areas where there was no oil and gas development, and the only roads were
 private ranch roads that received little traffic.
description: All data needed to perform the integrated step selection analysis
 in the two files titled as "summer_ssf.csv" (for the
 post-nesting analysis) and "winter_ssf.csv" (for the nonbreeding
 analysis). Columns within each file is the same.  ID contains a unique id
 number for each bird/year combination. Case_ indicates if a step was used
 (1) or unused (0). Step_id_2 is the step ID used in the random intercept
 for all models. time since fire is measured in years post fire (0=0-12
 months, 1=13-24 months, 2= &gt;24 months). Oil_start, oil end,
 road_start, road_end, powerline_start, power_line end indicate the
 log-transformed distance to each structure at the start and end of a step
 respectively. Ln_step and cos.turning.angle is the log-transformed step
 length, and cosine transformed turning angle.  Summary
 data needed to recreate the crossing analysis are contained in the two
 files titled "summer_crossing.csv" (post-nesting) and
 "winter_crossing.csv" (nonbreeding). Columns are the same in
 both files. ID is the bird/year ID. Case indicates if a movement track was
 used (1) or not (0). rd.cross.count and pl.cross.count indicate the number
 of crossing events that occurred in a movement track. Day.cnt is the
 number of days a bird was monitored. hr.dist.road and hr.dist.powerlines
 indicate the distance from the movement track centroid to the nearest road
 or powerline respectively.