Model suitable and you can diagnostics
We fit our Bayesian state-space model, consisting of both movement and observation process components, using Markov chain Monte Carlo (MCMC) methods. We assigned uninformative priors whenever there were no a priori expectations about the relationships of the model parameters and the movement behavior states (see Appendix S1). letter,t) within each iteration of the MCMC algorithm (see Appendix S2). We initialized six chains from random starting values drawn from the prior distributions. After initial pilot tuning and burn-in, we ran the chains until the univariate Gelman–Rubin potential scale reduction factor (PSRF) for monitored parameters was <1.2 and effective sample sizes exceeded 4000. This required about 6 million iterations per chain, where 1 million iterations for each parallel chain required about 100 h using six cores of a 3.7-GHz processor. Data and code can be found in Data S1.
Efficiency
Based on rear modes to own condition assignments, i located such bearded seals spent 70% of their implementation episodes about benthic foraging state (B). It hauled from frost (condition We) and you can rested during the water (state S) from inside the around equal proportions, however, there’s a clear seasonal part inside craft budgets one of the fresh new hauled on frost (I), benthic foraging (B), and transit (T) says that coincided to your june haven and you will winter months advance of sea freeze about Snowy (Desk 2). All of the seals presented rigorous benthic foraging along side continental cabinets off brand new Chukchi or Beaufort waters as water frost receded northward when you look at the the summer. I located little proof such frost-related seals hauling on residential property, in the event close to the coastline into the mainly freeze-free several months in the summer. Surprisingly, a grown-up men temporarily went north of one’s Beaufort coastal shelf in the later and is actually predict having hauled out on this new receding ocean ice edge ranging from bouts away from mid-water foraging on the deeper waters of one’s Canada Basin (Fig. 2). We provide an in depth cartoon away from predicted moves and you can condition projects for everyone seals in accordance with bathymetry and water freeze coverage for the Appendix S3.
- There were seasonal variations in interest costs anywhere between “summer” (away from marking for the later June and you may early July to help you 30 Sep), “autumn” (step 1 October so you can 29 December), and you can “winter” (step one January up to level loss between February and you can April) you to definitely coincided on southern area get better off cold weather water ice from inside the the latest Arctic. Interest funds summaries was indeed calculated based on the posterior mode out-of date spent into the per condition which have lower (LCI) and you may higher (UCI) credible times predicated on 95% large posterior thickness. Private seal pastime spending plans are included in Appendix S4.
As expected, the resting states (I, S, and L) exhibited shorter step lengths, no directional persistence, and lower proportions of each time step diving >4 m below the surface based on state-specific parameter estimates (Fig. 3; see Appendix S4 for posterior sumeters). Both the mid-water foraging (M) and transit (T) states exhibited longer step lengths, lower proportions of dry time, and higher proportions of diving >4 m below the surface. Only the transit state exhibited strong directional persistence local hookup app Las Vegas, but state M exhibited moderate directional persistence for some individuals (Fig. 3). The benthic foraging (B) state generally exhibited moderate step lengths, no directional persistence, lower proportions of dry time, higher proportions of diving >4 m below the surface, and considerably higher benthic dive counts (posterior median for ?B = 41.4; 95% highest posterior density interval: 41.2–41.7). The resting (?I = ?S = ?L = 9.7; 95% HPDI: 9.4–10.0) and transit (?T = 15.0; 95% HPDI: 14.5–15.5) states exhibited moderate benthic dive counts, while the mid-water foraging state generally had the lowest benthic dive counts (?M = 1.5; 95% HPDI: 1.3–1.7; Fig. 3). The moderate benthic dive counts for the resting and transit states could be attributable to mid-interval state switches, but there certainly could have been opportunistic benthic foraging during transit. There also could have been high-speed, directionally persistent benthic dives while transiting in relatively shallow shelf waters.