These data were used to evaluate effects of vessel exposure on Pacific walrus (Odobenus rosmarus divergens) behaviors. We obtained >120,000 hours of location and behavior (foraging, in-water not foraging, hauled out) data from 218 satellite-tagged walruses and linked them to vessel locations from the marine Automated Information System. This yielded 206 vessel-exposed walrus telemetry hours for comparison to unexposed hours which we used to assess if vessel exposure altered walrus behavior.

An animal's energetic costs are dependent on the amount of time it allocates to various behavioral activities. For Arctic pinnipeds, the time allocated to active and resting behaviors could change with future reductions in sea ice cover and longer periods of open water. The Pacific walrus (Odobenus rosmarus divergens) is a large Arctic pinniped that rests on sea ice or land between foraging trips to feed on the seafloor. This dataset contains behavioral data collected from 216 radio-tagged adult female walruses instrumented in the Chukchi Sea (2008–2014) that formed the basis of a Bayesian generalized linear mixed effects model that investigated probability that a walrus was in water foraging, in water not foraging, or hauled out, as a function of environmental covariates. The data are structured such that each line represents an hour of behavior collected during every third hour of the UTC day (hours 0 through 21), which was associated with temperature and wind metrics derived from the North American Regional Reanalysis dataset, as well as an index of the daily availability of sea ice based on the daily National Ice Center's Marginal Ice Zone product and an index of the availability of land. Each record presents the walrus behavior recorded during the record's hour, the previous hour, and the subsequent hour.

An animal's energetic costs are dependent on the amount of time it allocates to various behavioral activities. For Arctic pinnipeds, the time allocated to active and resting behaviors could change with future reductions in sea ice cover and longer periods of open water. The Pacific walrus (Odobenus rosmarus divergens) is a large Arctic pinniped that rests on sea ice or land between foraging trips to feed on the seafloor. This dataset contains behavioral data collected from 216 radio-tagged adult female walruses instrumented in the Chukchi Sea (2008–2014) that formed the basis of a Bayesian generalized linear mixed effects model that investigated probability that a walrus was in water foraging, in water not foraging, or hauled out, as a function of environmental covariates. The data are structured such that each line represents an hour of behavior collected during every third hour of the UTC day (hours 0 through 21), which was associated with temperature and wind metrics derived from the North American Regional Reanalysis dataset, as well as an index of the daily availability of sea ice based on the daily National Ice Center's Marginal Ice Zone product and an index of the availability of land. Each record presents the walrus behavior recorded during the record's hour, the previous hour, and the subsequent hour.

This data release includes three datasets used to develop forecasts of autumn body condition for adult female Pacific walruses in the Chukchi Sea during mid and late century time periods. (1) The activity dataset contains daily telemetry records for 218 adult female walruses tracked for periods of 7 to 104 days during 2008-2014, in the Chukchi Sea. Records include the number of hours the walrus was in the water, number of hours the walrus was foraging, study area region where the walrus was located, depths of the foraging locations, and the proportion of the region covered by sea ice. (2) The movement dataset contains telemetry records for 94 of these walruses, giving the dates they moved from one region to another, and the date of the beginning of minimum ice period for that year. (3) The projected-ice dataset contains daily projections of ice conditions in the study area regions derived from 7 general circulation models of future ice availability for mid-century (2045-2054) and late-century (2090-2099) time periods. The movement and activity datasets were developed to model walrus activity and movement as functions of sea ice conditions. The projected-ice dataset was developed to provide input for those models to forecast future walrus activity and movement. Forecasting autumn body condition requires linkage to bioenergetics models.

This data release includes three datasets used to develop forecasts of autumn body condition for adult female Pacific walruses in the Chukchi Sea during mid and late century time periods. (1) The activity dataset contains daily telemetry records for 218 adult female walruses tracked for periods of 7 to 104 days during 2008-2014, in the Chukchi Sea. Records include the number of hours the walrus was in the water, number of hours the walrus was foraging, study area region where the walrus was located, depths of the foraging locations, and the proportion of the region covered by sea ice. (2) The movement dataset contains telemetry records for 94 of these walruses, giving the dates they moved from one region to another, and the date of the beginning of minimum ice period for that year. (3) The projected-ice dataset contains daily projections of ice conditions in the study area regions derived from 7 general circulation models of future ice availability for mid-century (2045-2054) and late-century (2090-2099) time periods. The movement and activity datasets were developed to model walrus activity and movement as functions of sea ice conditions. The projected-ice dataset was developed to provide input for those models to forecast future walrus activity and movement. Forecasting autumn body condition requires linkage to bioenergetics models.

Sea ice loss represents a stressor to the Pacific walrus (Odobenus rosmarus divergens), which feeds on benthic macroinvertebrates in the Bering and Chukchi seas. However, no studies have examined the effects of sea ice on foraging walrus space use patterns. Thus, we examined walrus foraging resource selection as a function of proximity to resting substrates and prey biomass with a matched use-availability design. We quantified biomass of 17 benthic taxa, which included amphipods, bivalves, polychaete, sand dollars, tunicates, and sipunculids. We included covariates for distance to sea ice and distance to land, and systematically developed a series of candidate models to examine interactions among benthic prey biomass and resting substrates. We ranked candidate models with Bayesian Information Criterion and made inferences on walrus resource selection based on the top-ranked model. Biomass of the bivalve family Tellinidae, distance to ice, distance to land, and the interaction of distances to ice and land were in the top-ranked model. Standardized model coefficients indicated that distance to ice explained the most variation in walrus foraging resource selection patterns followed by Tellinidae biomass. Distance to land and the interaction of distances to ice and land accounted for similar levels of variation in foraging walrus resource selection. These data represent the used and available resource units with the covariates of distance to land and distance to ice.

Sea ice loss represents a stressor to the Pacific walrus (Odobenus rosmarus divergens), which feeds on benthic macroinvertebrates in the Bering and Chukchi seas. However, no studies have examined the effects of sea ice on foraging walrus space use patterns. Thus, we examined walrus foraging resource selection as a function of proximity to resting substrates and prey biomass with a matched use-availability design. We quantified biomass of 17 benthic taxa, which included amphipods, bivalves, polychaete, sand dollars, tunicates, and sipunculids. We included covariates for distance to sea ice and distance to land, and systematically developed a series of candidate models to examine interactions among benthic prey biomass and resting substrates. We ranked candidate models with Bayesian Information Criterion and made inferences on walrus resource selection based on the top-ranked model. Biomass of the bivalve family Tellinidae, distance to ice, distance to land, and the interaction of distances to ice and land were in the top-ranked model. Standardized model coefficients indicated that distance to ice explained the most variation in walrus foraging resource selection patterns followed by Tellinidae biomass. Distance to land and the interaction of distances to ice and land accounted for similar levels of variation in foraging walrus resource selection. These data represent the used and available resource units with the covariates of distance to land and distance to ice.

This dataset is comprised of three tables showing the reaction of walruses hauled out on sea ice of the Chukchi Sea to overflights by rotary wing Unoccupied Aircraft Systems (UAS). Data include behavior of walruses before, during, and after overflights, and environmental conditions during flights.

This dataset is comprised of three tables showing the reaction of walruses hauled out on sea ice of the Chukchi Sea to overflights by rotary wing Unoccupied Aircraft Systems (UAS). Data include behavior of walruses before, during, and after overflights, and environmental conditions during flights.

State-space models offer researchers an objective approach to modeling complex animal location datasets, and state-space model behavior classifications are often assumed to have a link to animal behavior. We evaluated the behavioral classification accuracy of a Bayesian state-space model in Pacific walruses using Argos satellite tags outfitted with sensors to detect animal behavior in real time. Specifically, tags were targeted to attach midway between the shoulders and each tag had a conductivity sensor and pressure transducer sensor integrated with an Argos satellite telemetry tag. At 1 s intervals, the pressure transducer recorded the depth of the tag and the conductivity sensor indicated whether the tag was in salt water. Two simple algorithms that ran onboard the tag summarized behavior information within 1-hr intervals to facilitate behavior data transmission through the Argos system using two indicator variables. One algorithm set the forage indicator variable to 1 if >50% of depth measurements exceeded 10 m during a 1-hr interval and to 0 if otherwise. A second algorithm set the wet indicator variable to 1 if >10% of conductivity measurements indicated the tag was in salt water during that 1-hr interval and to 0 if otherwise. Based on the values of these two indicator variables, we categorized each 1-hr interval into one of three behavior states. A combination of wet = 0 and forage = 0 for a 1-hr interval indicated the animal was primarily hauled-out during that period. Variable indicators of wet = 1 and forage = 0 indicated a walrus was primarily in water and not foraging (swimming) during the associated 1-hr interval. Finally, combinations of wet = 1 and foraging = 1 represented an individual foraging at depth for the corresponding 1-hr interval. To compare these real behaviors to modeled behaviors, we fit a two-state discrete-time continuous-space Bayesian state-space model to data from 306 Pacific walruses tagged in the Chukchi Sea. We matched predicted locations and behaviors from the state-space model (resident, transient behavior) to true animal behavior (foraging, swimming, hauled-out) and evaluated classification accuracy with kappa statistics and root mean square error. These data represent Bayesian state-space model output for 8 hr and 12 hr time steps.