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The Arctic is entering a new ecological state, with alarming consequences for humanity. Animal-borne sensors offer a window into these changes. Although substantial animal tracking data from the Arctic and subarctic exist, most are difficult to discover and access. Here, we present the new Arctic Animal Movement Archive (AAMA), a growing collection of more than 200 standardized terrestrial and marine animal tracking studies from 1991 to the present. The AAMA supports public data discovery, preserves fundamental baseline data for the future, and facilitates efficient, collaborative data analysis. With AAMA-based case studies, we document climatic influences on the migration phenology of eagles, geographic differences in the adaptive response of caribou reproductive phenology to climate change, and species-specific changes in terrestrial mammal movement rates in response to increasing temperature.

Summary Predictive species distributional models are a cornerstone of wildlife conservation planning. Constructing such models requires robust underpinning science that integrates formerly disparate data types to achieve effective species management.Greater sage‐grouse Centrocercus urophasianus, hereafter ‘sage‐grouse’ populations are declining throughout sagebrush‐steppe ecosystems in North America, particularly within the Great Basin, which heightens the need for novel management tools that maximize the use of available information.Herein, we improve upon existing species distribution models by combining information about sage‐grouse habitat quality, distribution and abundance from multiple data sources. To measure habitat, we created spatially explicit maps depicting habitat selection indices (HSI) informed by >35 500 independent telemetry locations from >1600 sage‐grouse collected over 15 years across much of the Great Basin. These indices were derived from models that accounted for selection at different spatial scales and seasons. A region‐wide HSI was calculated using the HSI surfaces modelled for 12 independent subregions and then demarcated into distinct habitat quality classes.We also employed a novel index to describe landscape patterns of sage‐grouse abundance and space use (AUI). The AUI is a probabilistic composite of the following: (i) breeding density patterns based on the spatial configuration of breeding leks and associated trends in male attendance; and (ii) year‐round patterns of space use indexed by the decreasing probability of use with increasing distance to leks. The continuous AUI surface was then reclassified into two classes representing high and low/no use and abundance. Synthesis and applications. Using the example of sage‐grouse, we demonstrate how the joint application of indices of habitat selection, abundance and space use derived from multiple data sources yields a composite map that can guide effective allocation of management intensity across multiple spatial scales. As applied to sage‐grouse, the composite map identifies spatially explicit management categories within sagebrush steppe that are most critical to sustaining sage‐grouse populations as well as those areas where changes in land use would likely have minimal impact. Importantly, collaborative efforts among stakeholders guide which intersections of habitat selection indices and abundance and space use classes are used to define management categories. Because sage‐grouse are an umbrella species, our joint‐index modelling approach can help target effective conservation for other sagebrush obligate species and can be readily applied to species in other ecosystems with similar life histories, such as central‐placed breeding.

Background Spatio-temporal patterns of movement can characterize relationships between organisms and their surroundings, and address gaps in our understanding of species ecology, activity budgets, bioenergetics, and habitat resource management. Highly mobile waterfowl, which can exploit resources over large spatial extents, are excellent models to understand relationships between movements and resource usage, landscape interactions and specific habitat needs. Methods We tracked 3 species of dabbling ducks with GPS-GSM transmitters in 2015–17 to examine fine-scale movement patterns over 24 h periods (30 min interval), dividing movement pathways into temporally continuous segments and spatially contiguous patches. We quantified distances moved, area used and time allocated across the day, using linear and generalized linear mixed models. We investigated behavior through relationships between these variables. Results Movements and space-use were small, and varied by species, sex and season. Gadwall ( Mareca strepera ) generally moved least (FFDs: 0.5–0.7 km), but their larger foraging patches resulted from longer within-area movements. Pintails ( Anas acuta ) moved most, were more likely to conduct flights > 300 m, had FFDs of 0.8–1.1 km, used more segments and patches per day that they revisited more frequently, resulting in the longest daily total movements. Females and males differed only during the post-hunt season when females moved more. 23.6% of track segments were short duration (1–2 locations), approximately 1/3 more than would be expected if they occurred randomly, and were more dispersed in the landscape than longer segments. Distance moved in 30 min shortened as segment duration increased, likely reflecting phases of non-movement captured within segments. Conclusions Pacific Flyway ducks spend the majority of time using smaller foraging and resting areas than expected or previously reported, implying that foraging areas may be highly localized, and nutrients obtainable from smaller areas. Additionally, movement reductions over time demonstrates behavioral adjustments that represent divergent energetic demands, the detection of which is a key advantage of higher frequency data. Ducks likely use less energy for movement than currently predicted and management, including distribution and configuration of essential habitat, may require reconsideration. Our study illustrates how fine-scale movement data from tracking help understand and inform various other fields of research. Electronic supplementary material The online version of this article (10.1186/s40462-019-0146-8) contains supplementary material, which is available to authorized users.

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