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.

This data release includes two summary geospatial rasters in GeoTIFF format indicating the seasonal Pacific walrus distribution apparent from location tracking obtained from the temporary attachment of Argos transmitter tags to 325 adult Pacific walruses (248 female, 67 male, 10 unknown) between 1987 and 2015. We deployed tags on walruses at locations in the eastern and northern Bering Sea, the eastern Chukchi Sea, and southern coast of the western Chukchi Sea. We estimated daily locations and characterized seasonal distributions (May-November and December-April) across the Pacific Arctic on a coarse grid (50km resolution).

This data release includes two summary geospatial rasters in GeoTIFF format indicating the seasonal Pacific walrus distribution apparent from from ARGOS location tracking obtained from the temporary attachment of ARGOS transmitter tags to Pacific walruses between 1987 and 2015. We deployed tags on walruses at locations in the eastern and northern Bering Sea, the eastern Chukchi Sea, and southern coast of the western Chukchi Sea. We estimated daily locations and characterized seasonal distributions (May-November and December-April) across the Pacific Arctic on a coarse grid (50km resolution).

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, and 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.

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.

This data release includes 2 child items with tracking data for Pacific walrus, a marine mammal that ranges between the Alaska Peninsula, up through the Bering and Chukchi seas, and over to Russia. Child Item 1: "Argos Satellite Tracking Data for Pacific Walrus (Odobenus rosmarus divergens) - Processed Data" -- Quality-controlled data collected from Argos satellite transmitters. Child Item 2: "Argos Satellite Tracking Data for Pacific Walrus (Odobenus rosmarus divergens) - Raw Data" -- All raw data collected from Argos satellite transmitters, provided for completeness of the archive. The quality-controlled, "Argos Processed Data" (Child Item 1) are better suited for most analytical purposes.

This data release includes 2 child items with tracking data for Pacific walrus, a marine mammal that ranges between the Alaska Peninsula, up through the Bering and Chukchi seas, and over to Russia. Child Item 1: "Argos Satellite Tracking Data for Pacific Walrus (Odobenus rosmarus divergens) - Processed Data" -- Quality-controlled data collected from Argos satellite transmitters. Child Item 2: "Argos Satellite Tracking Data for Pacific Walrus (Odobenus rosmarus divergens) - Raw Data" -- All raw data collected from Argos satellite transmitters, provided for completeness of the archive. The quality-controlled, "Argos Processed Data" (Child Item 1) are better suited for most analytical purposes.

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.

This dataset contains morphological measures of Pacific walruses sampled in the Chukchi and Bering Seas between 1972 and 1991. From 1972 through 1991 the Soviet Union employed industrial methods to harvest and process Pacific walruses to enhance the Russian Far East economy. Under the oversight of the Pacific branch of the Soviet All-Union Scientific Investigational Institute of Marine Fisheries and Oceanography (VNIRO), offshore harvesting crews worked from specialized marine mammal hunting ships (ZRS) throughout the spring, summer, and early autumn in the marginal sea ice habitats of the Bering and Chukchi Seas. They launched small (~7 m) wooden boats to approach walruses resting on ice pans, which were dispatched with standard hunting rifles. Harvested walruses were hauled back to the ZRS vessel for processing. Soviet cruises that contributed data to this dataset include ZRS Zagoriany (1976 spring), Surveyor (1978 spring), ZRS Zubarevo (1978), ZRS Zagorskii (1980 March 6 - April 23), ZRS Zvyagino (1981 February - March), KS Entuziast (1982 July 25 - August 23), ZRS Zakharova (1984 autumn, 1985 March 15 - April 26 and 1987 autumn), ZRS Zaslonovo (1991 March 28 - May 21). Beginning in 1981 harvesting extended into United States waters of the Pacific Arctic with permission of the National Oceanic and Atmospheric Administration (NOAA) under the auspices of the 1972 Area V bilateral agreement in the area of the environment. This bilateral agreement enabled direct liaison between Soviet and U.S. biologists who then arranged to collaborate collecting data from these offshore harvest efforts that may be used to understand basic walrus biology and monitor changes in their condition and reproductive success. Throughout the harvesting efforts, trained biologists inspected, measured, and weighed walrus specimens that had been landed onto the processing vessel. Harvest locations, observations, and measurements were recorded into numbered journals and standardized datasheets. This dataset contains these data. Originally these data were managed by VNIRO, however, to promote data curation during the post-Soviet period VNIRO formed an agreement with USGS Alaska Science Center (which at the time was the U.S. National Biological Survey) to maintain a copy of these data and provide access to them for studies vetted by representatives of the original data collection agency. This current database is published with permission of the original data curator, Dr. Yuri Bukhtiyarov.