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Abstract ContextIdeally, connectivity models would be developed using animal movement data because connectivity is fundamentally specific to species and movement processes. However, it can take years to collect sufficient data for all species of interest. Generalized multispecies connectivity models developed from expert opinion might help in the meantime. ObjectivesWe aimed to evaluate how well two common types of circuit theory-based generalized multispecies connectivity models (park-to-park and omnidirectional) predict areas important for animal movement for many species and movement processes. MethodsUsing GPS locations from 3525 individuals belonging to 17 species from 46 study areas across Canada and five tests, we assessed connectivity model prediction accuracy against movement processes measured at different scales, from within home range to presumed dispersal. ResultsAreas important for movement were accurately predicted for 52 to 78% of the datasets and movement processes. Prediction accuracy was lower for fast movements. The omnidirectional model was slightly better at predicting areas important for multiple movement processes. Both models were more accurate for species known to be more averse to human disturbance (72–78% of tests were accurate) compared to species less averse to human disturbance, steep slopes, and/or high elevations (38–41% of tests were accurate). ConclusionsOur study demonstrates that both park-to-park and omnidirectional multispecies connectivity models can predict areas important for various movements for many species and can be used for time-sensitive projects aimed at landscape-scale connectivity conservation. However, because the models were less accurate for some species and faster movements, species-specific connectivity models may be required for informing land management decisions. 

Abstract Integrating complex geospatial data into research and applications for wildlife ecology remains a challenge. For example, animations of wildlife tracking data can be useful for developing hypotheses, communicating with stakeholders and infrastructure planning. Conveying an effective message often requires visualizing movements in relation to custom background layers, such as dynamic weather conditions or local transportation features. However, animations are commonly made using software that is easy to use but offers few options for input layers, thus limiting their impact. Alternatively, bespoke solutions require advanced programming skills that are not readily available for many ecologists.We developed ECODATA, a suite of open‐source tools to support exploration, analysis and visualization of animal movements and dynamic geospatial data layers. The tools do not require programming skills and guide users through the process of manipulating vector, raster and tabular data files to prepare inputs to custom animations or further analyses. The software was developed by a team of remote sensing experts, quantitative ecologists, wildlife managers and conservation practitioners.We demonstrate the use of ECODATA through two examples. The first describes the use of the software to animate movements of elk (Cervus elaphus) and wolves (Canis lupus) in relation to roads, wildlife crossing structures and seasonal vegetation green‐up near Banff National Park in Canada. The second illustrates the impact of the software on wildlife management, with an animation of caribou (Rangifer tarandus) movements and parturitions during the calving season. Both examples include processed remote sensing data and feature layers that provide relevant local context.ECODATA offers a novel resource to explore and communicate animals' interactions with their environment, informing management decisions and conservation strategies. The flexible tools for geospatial data manipulation can be used for data visualization, as described here, or to create predictor variables for inclusion in habitat selection or other ecological models. 

Abstract Rapid climate warming has contributed to significant changes in Arctic and boreal vegetation over the past half century. Changes in vegetation can impact wildlife by altering habitat and forage availability, which can affect behavior and range use. However, animals can also influence vegetation through foraging and trampling and therefore play an important role in determining ecosystem responses to climate change. As wildlife populations grow, density‐dependent processes can prompt range expansion or shifts. One mechanism for this is density‐dependent forage reduction, which can contribute to nutritional stress and population declines, and can also alter vegetation change trajectories. We assessed the range characteristics of a migratory caribou (Rangifer tarandus) herd in east‐central Alaska and west‐central Yukon Territory as it grew (1992–2017) then declined (2017–2020). Furthermore, we analyzed the correlation between caribou relative spatial density and vegetation change over this period using remotely sensed models of plant functional type cover. Over this period, caribou population density increased in all seasonal ranges. This was most acute in the calving range where density increased 8‐fold, from 1.5 to 12.0 animals km⁻². Concurrent with increasing density, we documented range shifts and expansion across summer, post‐calving and winter ranges. In particular, summer range size doubled (12,000 km²increase) and overlap with core range (areas with repeated year‐round use) was halved. Meanwhile, lichen cover, a key forage item, declined more in areas with high caribou density (2.4% absolute, 22% relative decline in cover) compared to areas where caribou were mostly absent (0.3% absolute, 1.9% relative decline). Conversely, deciduous shrub cover increased more in high caribou density areas. However, increases were dominated by less palatable shrubs whereas more palatable shrubs (i.e., willow [Salixspp.]) were stable or declined slightly. These changes in vegetation cover were small relative to uncertainty in the map products used to calculate change. Nonetheless, correlations between vegetation change and caribou range characteristics, along with concerning demographic trends reported over this same period, suggest changing forage conditions may have played a role in the herd's subsequent population decline. Our research highlights the potential of remotely sensed metrics of vegetation change for assessing the impacts of herbivory and trampling and stresses the importance of in situ data such as exclosures for validating such findings. 

Abstract Plant biomass is a fundamental ecosystem attribute that is sensitive to rapid climatic changes occurring in the Arctic. Nevertheless, measuring plant biomass in the Arctic is logistically challenging and resource intensive. Lack of accessible field data hinders efforts to understand the amount, composition, distribution, and changes in plant biomass in these northern ecosystems. Here, we presentThe Arctic plant aboveground biomass synthesis dataset, which includes field measurements of lichen, bryophyte, herb, shrub, and/or tree aboveground biomass (g m⁻²) on 2,327 sample plots from 636 field sites in seven countries. We created the synthesis dataset by assembling and harmonizing 32 individual datasets. Aboveground biomass was primarily quantified by harvesting sample plots during mid- to late-summer, though tree and often tall shrub biomass were quantified using surveys and allometric models. Each biomass measurement is associated with metadata including sample date, location, method, data source, and other information. This unique dataset can be leveraged to monitor, map, and model plant biomass across the rapidly warming Arctic. 

ABSTRACT Long‐distance migrations are a striking, and strikingly successful, adaptation for highly mobile terrestrial animals in seasonal environments. However, it remains an open question whether migratory animals are more resilient or less resilient to rapidly changing environments. Furthermore, the mechanisms by which animals adapt or modify their migrations are poorly understood. We describe a dramatic shift of over 500 km in the wintering range of the Western Arctic Herd, a large caribou (Rangifer tarandus) herd in northwestern Alaska, an area that is undergoing some of the most rapid warming on Earth. Between 2012 and 2020, caribou switched from reliably wintering in maritime tundra in the southwesternmost portion of their range to more frequently wintering in mountainous areas to the east. Analysis of this range shift, in conjunction with nearly 200 documented mortality events, revealed that it was both broadly adaptive and likely driven by collective memory of poor winter conditions. Before the range shift, overwinter survival in the maritime tundra was high, routinely surpassing 95%, but falling to around 80% even as fewer animals wintered there. Meanwhile, in the increasingly used mountainous portion of the range, survival was intermediate and less variable across years compared to the extremes in the southern winter ranges. Thus, the shift only imperfectly mitigated overall increased mortality rates. The range shift has also been accompanied by changes in seasonal patterns of survival that are consistent with poorer nutritional intake in winter. Unexpectedly, the strongest single predictor of an individual's probability of migrating south was the overall survival of animals in the south in the preceding winter, suggesting that the range shift is in part driven by collective memory. Our results demonstrate the importance and use of collective decision making and memory for a highly mobile species for improving fitness outcomes in a dynamic, changing environment. 

Anthropogenic change is reshaping the regulation and stability of animal population dynamics across broad biogeographic gradients. For example, abiotic and biotic interactions can cause gradients in population cycle period and amplitude, but this research is mostly constrained to small mammals. Caribou and reindeer (Rangifer tarandus spp.) are threatened by human‐caused change and are known to fluctuate in population over multidecadal scales. But it is unclear how ecological mechanisms drive these cycles and whether these mechanisms are similar to those found in smaller mammals. Here, we carried out a global biogeographic study of Rangifer population cycles in response to top‐down and bottom‐up mechanisms. We hypothesized that predation and food resources would interact to affect the amplitude and period of population cycles across the species' range. To test this, we used a two‐pronged approach: (1) we conducted a range‐wide statistical analysis of population data from 43 Rangifer herds; and (2) we built tri‐trophic mechanistic population models of predator–Rangifer–food interactions. This approach allowed us to merge theoretical and empirical approaches to better understand the drivers of population cycling across space and time. We found statistical evidence for long‐term cyclicity in 19 Rangifer populations, and some evidence that decreasing food productivity and winter temperatures may have caused increased period length and amplitude across spatial gradients. Our mechanistic model largely agreed with our empirical results, showing that decreased food resources and increased predation can drive more intense cycles over time. These paired empirical and theoretical results suggest that gradients in Rangifer population cycles match ecological mechanisms found in smaller mammals. Moreover, human‐caused shifts in climate, food resources, and predators may shift Rangifer population dynamics towards more booms and busts, threatening population persistence. We recommend that dynamic management strategies, in tandem with theoretical and empirical approaches, could be used to better understand and manage population cycles across space and time. 

Competition for resources and space can drive forage selection of large herbivores from the bite through the landscape scale. Animal behaviour and foraging patterns are also influenced by abiotic and biotic factors. Fine‐scale mechanisms of density‐dependent foraging at the bite scale are likely consistent with density‐dependent behavioural patterns observed at broader scales, but few studies have directly tested this assertion. Here, we tested if space use intensity, a proxy of spatiotemporal density, affects foraging mechanisms at fine spatial scales similarly to density‐dependent effects observed at broader scales in caribou. We specifically assessed how behavioural choices are affected by space use intensity and environmental processes using behavioural state and forage selection data from caribou (Rangifer tarandus granti) observed from GPS video‐camera collars using a multivariate discrete‐choice modelling framework. We found that the probability of eating shrubs increased with increasing caribou space use intensity and cover of Salix spp. shrubs, whereas the probability of eating lichen decreased. Insects also affected fine‐scale foraging behaviour by reducing the overall probability of eating. Strong eastward winds mitigated negative effects of insects and resulted in higher probabilities of eating lichen. At last, caribou exhibited foraging functional responses wherein their probability of selecting each food type increased as the availability (% cover) of that food increased. Space use intensity signals of fine‐scale foraging were consistent with density‐dependent responses observed at larger scales and with recent evidence suggesting declining reproductive rates in the same caribou population. Our results highlight potential risks of overgrazing on sensitive forage species such as lichen. Remote investigation of the functional responses of foraging behaviours provides exciting future applications where spatial models can identify high‐quality habitats for conservation. 

Abstract Changes in vegetation distribution are underway in Arctic and boreal regions due to climate warming and associated fire disturbance. These changes have wide ranging downstream impacts—affecting wildlife habitat, nutrient cycling, climate feedbacks and fire regimes. It is thus critical to understand where these changes are occurring and what types of vegetation are affected, and to quantify the magnitude of the changes. In this study, we mapped live aboveground biomass for five common plant functional types (PFTs; deciduous shrubs, evergreen shrubs, forbs, graminoids and lichens) within Alaska and northwest Canada, every five years from 1985 to 2020. We employed a multi-scale approach, scaling from field harvest data and unmanned aerial vehicle-based biomass predictions to produce wall-to-wall maps based on climatological, topographic, phenological and Landsat spectral predictors. We found deciduous shrub and graminoid biomass were predicted best among PFTs. Our time-series analyses show increases in deciduous (37%) and evergreen shrub (7%) biomass, and decreases in graminoid (14%) and lichen (13%) biomass over a study area of approximately 500 000 km 2 . Fire was an important driver of recent changes in the study area, with the largest changes in biomass associated with historic fire perimeters. Decreases in lichen and graminoid biomass often corresponded with increasing shrub biomass. These findings illustrate the driving trends in vegetation change within the Arctic/boreal region. Understanding these changes and the impacts they in turn will have on Arctic and boreal ecosystems will be critical to understanding the trajectory of climate change in the region.