Data from: Incubation recess behaviors influence nest survival of Wild Turkeys

We monitored live‒dead status daily during the reproductive season using handheld Yagi antennas and R4000 (Advanced Telemetry Systems, Inc., Isanti, MN) or Biotracker receivers (Biotrack Ltd., Wareham, Dorset, UK). Live-dead status was determined via GPS‒VHF transmitter mortality signals scheduled to activate if stationary for 24 hours. We downloaded GPS locations ≥ 1 per week via a VHF/UHF handheld command unit receiver (Biotrack Ltd., Wareham, Dorset, UK). We viewed GPS locations and determined incubation when female locations became concentrated around a single point for 1‒2 days (Collier and Chamberlain 2011, Conley et al. 2015, Yeldell et al. 2017, Wood et al. 2018). Nesting females were not disturbed or flushed from nest sites during monitoring, but instead were live‒dead checked daily via VHF from a distance of > 20 m.Our nest monitoring data produced a ragged telemetry dataset (Rotella et al. 2004), and we used the nest survival approach outlined by (Dinsmore et al. 2002) to evaluate influences of incubation recess movements on daily nest survival. The ragged telemetry approach serves as a general model for known fate data in program MARK (White and Burnham 1999) when loss date may not be known exactly and is flexible for integrating time‒dependent individual covariates (Rotella et al. 2004, Collier et al. 2009). For each nesting female, we created an encounter history for the entire incubation period and scaled each nesting event (k = 1) to the same start point, as evaluating temporal variation in nest survival was not our objective (Dinsmore et al. 2002). We recorded the last day each nest was known to be alive (l) and the final date that the female incubated (m) based on our VHF and GPS data (Conley et al. 2015, Conley et al. 2016, Yeldell et al. 2017) and assigned each nest a fate of 0 = survived or 1 = failed. We followed the approach of Collier et al. (2009), and developed time dependent covariates for both the daily frequency and distance of recess movements, and time‒dependent covariates for the cumulative values of daily frequency and distance of recess movements. We developed a set of candidate models which we used to evaluate time‒specific variation in wild turkey behaviors to better understand how variation in behavioral decisions during incubation drive nest survival. Underlying our work was the hypothesis that behavioral changes, manifested via the movement ecology of wild turkeys during nesting, would impact nest success. Our initial expectation was that, generally, increased movements would increase the level of attention on the landscape, which would thus increase nest failure. As such, we included models evaluating fully time‒dependent covariates for daily frequency of recess movements and daily distance of recess movements, as well as cumulative frequency and distance of recess movements (Franklin 2001, Collier et al. 2009). We also developed time-specific trend models for cumulative frequency of recesses and distance of recess movements, which assumed that the effect of each covariate did not vary by day and was thus constant over time (Franklin 2001). We used an information‒theoretic approach (Burnham and Burnham 2002) to rank candidate models and assess model strength (based on ΔAICc) using the standard from Burnham and Anderson (2002), and estimated daily nest survival for the best fitting candidate model given the data.