Mountain ranges, deserts, ice fields and oceans generally act as barriers to the movement of land-dependent animals, often profoundly shaping migration routes. We used satellite telemetry to track the southward flights of bar-tailed godwits (Limosa lapponica baueri), shorebirds whose breeding and non-breeding areas are separated by the vast central Pacific Ocean. Seven females with surgically implanted transmitters flew non-stop 8117–11 680 km (10 153±1043 s.d.) directly across the Pacific Ocean; two males with external transmitters flew non-stop along the same corridor for 7008–7390 km. Flight duration ranged from 6.0 to 9.4 days (7.8±1.3 s.d.) for birds with implants and 5.0 to 6.6 days for birds with externally attached transmitters. These extraordinary non-stop flights establish new extremes for avian flight performance, have profound implications for understanding the physiological capabilities of vertebrates and how birds navigate, and challenge current physiological paradigms on topics such as sleep, dehydration and phenotypic flexibility. Predicted changes in climatic systems may affect survival rates if weather conditions at their departure hub or along the migration corridor should change. We propose that this transoceanic route may function as an ecological corridor rather than a barrier, providing a wind-assisted passage relatively free of pathogens and predators.

Summary: The Argos System is used worldwide to satellite‐track free‐ranging animals, but location errors can range from tens of metres to hundreds of kilometres. Low‐quality locations (Argos classes A, 0, B and Z) dominate animal tracking data. Standard‐quality animal tracking locations (Argos classes 3, 2 and 1) have larger errors than those reported in Argos manuals. The Douglas Argos‐filter (DAF) algorithm flags implausible locations based on user‐defined thresholds that allow the algorithm's performance to be tuned to species' movement behaviours and study objectives. The algorithm is available in Movebank – a free online infrastructure for storing, managing, sharing and analysing animal movement data. We compared 21,044 temporally paired global positioning system (GPS) locations with Argos location estimates collected from Argos transmitters on free‐ranging waterfowl and condors (13 species, 314 individuals, 54,895 animal‐tracking days). The 95th error percentiles for unfiltered Argos locations 0, A, B and Z were within 35·8, 59·6, 163·2 and 220·2 km of the true location, respectively. After applying DAF with liberal thresholds, roughly 20% of the class 0 and A locations and 45% of the class B and Z locations were excluded, and the 95th error percentiles were reduced to 17·2, 15·0, 20·9 and 18·6 km for classes 0, A, B and Z, respectively. As thresholds were applied more conservatively, fewer locations were retained, but they possessed higher overall accuracy. Douglas Argos‐filter can improve data accuracy by 50–90% and is an effective and flexible tool for preparing Argos data for direct biological interpretation or subsequent modelling.

Projections of polar bear (Ursus maritimus) sea ice habitat distribution in the polar basin during the 21st century were developed to understand the consequences of anticipated sea ice reductions on polar bear populations. We used location data from satellite‐collared polar bears and environmental data (e.g., bathymetry, distance to coastlines, and sea ice) collected from 1985 to 1995 to build resource selection functions (RSFs). RSFs described habitats that polar bears preferred in summer, autumn, winter, and spring. When applied to independent data from 1996 to 2006, the RSFs consistently identified habitats most frequently used by polar bears. We applied the RSFs to monthly maps of 21st‐century sea ice concentration projected by 10 general circulation models (GCMs) used in the Intergovernmental Panel of Climate Change Fourth Assessment Report, under the A1B greenhouse gas forcing scenario. Despite variation in their projections, all GCMs indicated habitat losses in the polar basin during the 21st century. Losses in the highest‐valued RSF habitat (optimal habitat) were greatest in the southern seas of the polar basin, especially the Chukchi and Barents seas, and least along the Arctic Ocean shores of Banks Island to northern Greenland. Mean loss of optimal polar bear habitat was greatest during summer; from an observed 1.0 million km² in 1985–1995 (baseline) to a projected multi‐model mean of 0.32 million km² in 2090–2099 (−68% change). Projected winter losses of polar bear habitat were less: from 1.7 million km² in 1985–1995 to 1.4 million km² in 2090–2099 (−17% change). Habitat losses based on GCM multi‐model means may be conservative; simulated rates of habitat loss during 1985–2006 from many GCMs were less than the actual observed rates of loss. Although a reduction in the total amount of optimal habitat will likely reduce polar bear populations, exact relationships between habitat losses and population demographics remain unknown. Density and energetic effects may become important as polar bears make long‐distance annual migrations from traditional winter ranges to remnant high‐latitude summer sea ice. These impacts will likely affect specific sex and age groups differently and may ultimately preclude bears from seasonally returning to their traditional ranges.

The movement of animals is strongly influenced by external factors in their surrounding environment such as weather, habitat types, and human land use. With advances in positioning and sensor technologies, it is now possible to capture animal locations at high spatial and temporal granularities. Likewise, scientists have an increasing access to large volumes of environmental data. Environmental data are heterogeneous in source and format, and are usually obtained at different spatiotemporal scales than movement data. Indeed, there remain scientific and technical challenges in developing linkages between the growing collections of animal movement data and the large repositories of heterogeneous remote sensing observations, as well as in the developments of new statistical and computational methods for the analysis of movement in its environmental context. These challenges include retrieval, indexing, efficient storage, data integration, and analytical techniques. This paper contributes to movement ecology research by presenting a new publicly available system, Environmental-Data Automated Track Annotation (Env-DATA), that automates annotation of movement trajectories with ambient atmospheric observations and underlying landscape information. Env-DATA provides a free and easy-to-use platform that eliminates technical difficulties of the annotation processes and relieves end users of a ton of tedious and time-consuming tasks associated with annotation, including data acquisition, data transformation and integration, resampling, and interpolation. The system is illustrated with a case study of Galapagos Albatross (Phoebastria irrorata) tracks and their relationship to wind, ocean productivity and chlorophyll concentration. Our case study illustrates why adult albatrosses make long-range trips to preferred, productive areas and how wind assistance facilitates their return flights while their outbound flights are hampered by head winds. The new Env-DATA system enhances Movebank, an open portal of animal tracking data, by automating access to environmental variables from global remote sensing, weather, and ecosystem products from open web resources. The system provides several interpolation methods from the native grid resolution and structure to a global regular grid linked with the movement tracks in space and time. The aim is to facilitate new understanding and predictive capabilities of spatiotemporal patterns of animal movement in response to dynamic and changing environments from local to global scales.

The interannual variability and trend of above-ground photosynthetic activity of Arctic tundra vegetation in the 1990s is examined for the north slope region of Alaska, based on the seasonally integrated normalized difference vegetation index (SINDVI) derived from local area coverage (LAC) National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) data. Smaller SINDVI values occurred during the three years (1992-1994) following the volcanic eruption of Mt Pinatubo. Even after implementing corrections for this stratospheric aerosol effect and adjusting for changes in radiometric calibration coefficients, an apparent increasing trend of SINDVI in the 1990s is evident for the entire north slope. The most pronounced increase was observed for the foothills physiographical province.