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ABSTRACT 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 tarandusspp.) 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 ofRangiferpopulation 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 43Rangiferherds; 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 19Rangiferpopulations, 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 inRangiferpopulation cycles match ecological mechanisms found in smaller mammals. Moreover, human‐caused shifts in climate, food resources, and predators may shiftRangiferpopulation 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. 

The reintroduction of extirpated species is a frequent tactic in rewilding projects because of the functional role species play in maintaining ecosystem health. Despite their potential to benefit both ecosystems and society, however, most well-known species reintroductions have adopted an eco-centric, “nature-in-people-out” approach. Rewilding theory and practitioners acknowledge that ignoring the role Indigenous people did and might once again play in shaping the distribution, abundance, movements, behavior, and health of wild species and ecosystems, is limiting. In this case study, we describe the technical steps we took and how Indigenous knowledge, ceremony, and cultural monitoring were woven into the recent reintroduction of plains bison to Canada’s Banff National Park. Six years later, the reintroduced bison herd has grown from 16 to >100 animals, ranges mostly within 30 km of the release site, and, if current growth continues, will likely be managed with Indigenous harvesting. Transboundary bison policy differences are shifting and may lead to bison being more sustainable. The ecocultural approach, therefore, has increased the resilience of our rewilding project. 

Abstract Background Global increases in human activity threaten connectivity of animal habitat and populations. Protection and restoration of wildlife habitat and movement corridors require robust models to forecast the effects of human activity on movement behaviour, resource selection, and connectivity. Recent research suggests that animal resource selection and responses to human activity depend on their behavioural movement state, with increased tolerance for human activity in fast states of movement. Yet, few studies have incorporated state-dependent movement behaviour into analyses of Merriam connectivity, that is individual-based metrics of connectivity that incorporate landscape structure and movement behaviour. Methods We assessed the cumulative effects of anthropogenic development on multiple movement processes including movement behaviour, resource selection, and Merriam connectivity. We simulated movement paths using hidden Markov movement models and step selection functions to estimate habitat use and connectivity for three landscape scenarios: reference conditions with no anthropogenic development, current conditions, and future conditions with a simulated expansion of towns and recreational trails. Our analysis used 20 years of grizzly bear ( Ursus arctos ) and gray wolf ( Canis lupus ) movement data collected in and around Banff National Park, Canada. Results Carnivores increased their speed of travel near towns and areas of high trail and road density, presumably to avoid encounters with people. They exhibited stronger avoidance of anthropogenic development when foraging and resting compared to travelling and during the day compared to night. Wolves exhibited stronger avoidance of anthropogenic development than grizzly bears. Current development reduced the amount of high-quality habitat between two mountain towns by more than 35%. Habitat degradation constrained movement routes around towns and was most pronounced for foraging and resting behaviour. Current anthropogenic development reduced connectivity from reference conditions an average of 85%. Habitat quality and connectivity further declined under a future development scenario. Conclusions Our results highlight the cumulative effects of anthropogenic development on carnivore movement behaviour, habitat use, and connectivity. Our strong behaviour-specific responses to human activity suggest that conservation initiatives should consider how proposed developments and restoration actions would affect where animals travel and how they use the landscape. 

Abstract Wildlife ecologists throughout the world strive to monitor trends in population abundance to help manage wildlife populations and conserve species at risk. Spatial capture–recapture studies are the gold standard for monitoring density, yet they can be difficult to apply because researchers must be able to distinguish all detected individuals. Spatial mark–resight (SMR) models only require a subset of the population to be marked and identifiable. Recent advances in SMR models with radio‐collared animals required a two‐staged analysis. We developed a one‐stage generalized SMR (gSMR) model that used detection histories of marked and unmarked animals in a single analysis. We used simulations to assess the performance of one‐ and two‐stage gSMR models. We then applied the one‐stage gSMR with telemetry and remote camera data to estimate grizzly bear (Ursus arctos) abundance from 2012 to 2023 within the Canadian Rocky Mountains. We estimated abundance trends for the population and reproductive females (females with cubs of the year). Simulations suggest that one‐ and two‐stage models performed equally well. One‐stage models are more dependable as they use exact likelihoods, whereas two‐stage models have shorter computation times for large data sets. Both methods had >95% credible interval coverage and minimal bias. Increasing the number of marked animals increased the accuracy and precision of abundance estimates, and ≥10 marked animals were required to obtain coefficients of variation <20% in most scenarios. The grizzly bear population increased slightly (growth rate λ_mean = 1.02) to a 2023 density of 10.4 grizzly bears/1000 km². Reproductive female abundance had high interannual variability and increased to 1.0 bears/1000 km². Population density was highest within protected areas, within high‐quality habitat and far from paved roads. The density of activity centers declined near paved roads over time. Mechanisms of decline may have included direct mortality and shifting activity centers to avoid human activity. Our study demonstrates the influence of human activity on localized density and the importance of protected areas for carnivore conservation. Finally, our study highlights the widespread utility of remote camera and telemetry‐based SMR models for monitoring spatiotemporal trends in abundance. 

Migration is a tactic used across taxa to access resources in temporally heterogenous landscapes. Populations that migrate can attain higher abundances because such movements allow access to higher quality resources, or reduction in predation risk resulting in increased fitness. However, most migratory species occur in partially migratory populations, a mix of migratory and non-migratory individuals. It is thought that the portion of migrants in a partial migration population is maintained either through (1) a population-level evolutionary stable state where counteracting density-dependent vital rates act on migrants and residents to balance fitness or (2) conditional migration, where the propensity to migrate is influenced by the individual's state. However, in many respects, migration is also a form of habitat selection and the proportion of migrants and residents may be the result of density-dependent habitat selection. Here, we test whether the theory of Ideal Free Distribution (IFD) can explain the coexistence of different migratory tactics in a partially migratory population. IFD predicts individuals exhibit density-dependent vital rates and select different migratory tactics to maximize individual fitness resulting in equal fitness (λ) between tactics. We tested the predictions of IFD in a partially migratory elk population that declined by 70% with 19 years of demographic data and migratory tactic switching rates from >300 individuals. We found evidence of density dependence for resident pregnancy and adult female survival providing a fitness incentive to switch tactics. Despite differences in vital rates between migratory tactics, mean λ (fitness) was equal. However, as predicted by the IFD, individuals switched tactics toward those of higher fitness. Our analysis reveals that partial migration may be driven by tactic selection that follows the ideal free distribution. These findings reinforce that migration across taxa may be a polymorphic behavior in large herbivores where migratory tactic selection is determined by differential costs and benefits, mediated by density dependence. 

Arctic vegetation communities are rapidly changing with climate warming, which impacts wildlife, carbon cycling and climate feedbacks. Accurately monitoring vegetation change is thus crucial, but scale mismatches between field and satellite-based monitoring cause challenges. Remote sensing from unmanned aerial vehicles (UAVs) has emerged as a bridge between field data and satellite-based mapping. We assess the viability of using high resolution UAV imagery and UAV-derived Structure from Motion (SfM) to predict cover, height and aboveground biomass (henceforth biomass) of Arctic plant functional types (PFTs) across a range of vegetation community types. We classified imagery by PFT, estimated cover and height, and modeled biomass from UAV-derived volume estimates. Predicted values were compared to field estimates to assess results. Cover was estimated with root-mean-square error (RMSE) 6.29-14.2% and height was estimated with RMSE 3.29-10.5 cm, depending on the PFT. Total aboveground biomass was predicted with RMSE 220.5 g m^-2, and per-PFT RMSE ranged from 17.14-164.3 g m^-2. Deciduous and evergreen shrub biomass was predicted most accurately, followed by lichen, graminoid, and forb biomass. Our results demonstrate the effectiveness of using UAVs to map PFT biomass, which provides a link towards improved mapping of PFTs across large areas using earth observation satellite imagery.