Model fitting and you may 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). n,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
Considering rear settings to have condition projects, we receive these types of bearded seals invested 70% of its implementation symptoms regarding the benthic foraging condition (B). They hauled on freeze (condition I) and you will rested from the ocean (condition S) into the around equivalent proportions, but you will find a clear regular part when you look at the hobby budgets certainly brand new hauled out on ice (I), benthic foraging (B), and you may transit (T) claims that coincided into the june haven and wintertime improve away from sea ice about Arctic (Table 2). Most of the seals exhibited intense benthic foraging over the continental shelves off the newest Chukchi otherwise Beaufort oceans just like the sea freeze receded northward inside summer time. We discovered almost no proof this type of freeze-related seals dragging on land, even if nearby the coastline when you look at the mostly freeze-free months in the summertime. Remarkably, an adult men briefly moved north of Beaufort seaside bookshelf in late and you can try predicted getting hauled from brand new receding ocean frost line between bouts of mid-h2o foraging regarding higher waters of one’s Canada Basin (Fig. 2). We offer a detailed cartoon off predict actions and you will state tasks for everyone seals prior to bathymetry and you can water ice safety from inside the Appendix S3.
- There are regular variations in activity finances ranging from “summer” (from marking when you look at the late June and you may very early July to help you 31 September), “autumn” (1 October so you can 29 December), and you may “winter” (step one January up until mark losings between February and you can April) that coincided to the southern area progress out-of winter water ice for the this new Snowy. Activity budget summaries was basically determined in accordance with the rear setting out of go out invested inside per county that have down (LCI) and you can top (UCI) legitimate times centered on 95% higher posterior density. Private seal activity costs are part of 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, 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 looking for a hookup San Francisco = ?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.
