Spatial overlap of gray wolves and ungulate prey changes seasonally corresponding to prey migration.

BACKGROUND: Prey are more vulnerable during migration due to decreased familiarity with their surroundings and spatially concentrated movements. Predators may respond to increased prey vulnerability by shifting their ranges to match prey. Moose (Alces alces) and white-tailed deer (Odocoileus virginianus) are primary gray wolf (Canis lupus) prey and important subsistence species for Indigenous communities. We hypothesized wolves would increase use of ungulate migration corridors during migrations and predicted wolf distributions would overlap primary available prey. METHODS: We examined seasonal gray wolf, moose, and white-tailed deer movements on and near the Grand Portage Indian Reservation, Minnesota, USA. We analyzed GPS collar data during 2012-2021 using Brownian bridge movement models (BBMM) in Migration Mapper and mechanistic range shift analysis (MRSA) to estimate individual- and population-level occurrence distributions and determine the status and timing of range shifts. We estimated proportional overlap of wolf distributions with moose and deer distributions and tested for differences among seasons, prey populations, and wolf sex and pack affiliations. RESULTS: We identified a single migration corridor through which white-tailed deer synchronously departed in April and returned in October-November. Gray wolf distributions overlapped the deer migration corridor similarly year-round, but wolves altered within-range distributions seasonally corresponding to prey distributions. Seasonal wolf distributions had the greatest overlap with deer during fall migration (10 October-28 November) and greatest overlap with moose during summer (3 May-9 October). CONCLUSIONS: Gray wolves did not increase their use of the white-tailed deer migration corridor but altered distributions within their territories in response to seasonal prey distributions. Greater overlap of wolves and white-tailed deer in fall may be due to greater predation success facilitated by asynchronous deer migration movements. Greater summer overlap between wolves and moose may be linked to moose calf vulnerability, American beaver (Castor canadensis) co-occurrence, and reduced deer abundance associated with migration. Our results suggest increases in predation pressure on deer in fall and moose in summer, which can inform Indigenous conservation efforts. We observed seasonal plasticity of wolf distributions suggestive of prey switching; that wolves did not exhibit migratory coupling was likely due to spatial constraints resulting from territoriality.

Diverse migration patterns and seasonal habitat use of Stone's sheep (Ovis dalli stonei).

We describe temporal and spatial patterns of seasonal space-use and migration by 16 GPS-collared Stone's sheep (Ovis dalli stonei) from nine bands in the Cassiar Mountains of northern British Columbia, Canada. Our objectives were to identify the timing of spring and fall migrations, characterize summer and winter ranges, map and describe migration routes and use of stopover sites, and document altitudinal change across seasons. Our last objective was to assess individual migration strategies based on patterns of geographic migration, altitudinal migration, or residency. Median start and end dates of the spring migration were 12 and 17 Jun (range: 20 May to 05 Aug), and of the fall migration were 30 Aug and 22 Sep (range: 21 Aug to 07 Jan). The median area of winter and summer ranges for geographic migrants were 630.8 ha and 2,829.0 ha, respectively, with a broad range from about 233.6 to 10,196.2 ha. Individuals showed high fidelity to winter ranges over the limited duration of the study. The winter and summer ranges of most individuals (n = 15) were at moderate to high elevations with a median summer elevation of 1,709 m (1,563-1,827 m) and 1,673 m (1,478-1,751 m) that varied <150 m between ranges. Almost all collared females (n = 14) exhibited changes in elevation use that coincide with abbreviated altitudinal migration. Specifically, these females descended to lower spring elevations from their winter range (Δ > 150 m), and then gradually moved up to higher-elevation summer ranges (Δ > 150 m). In the fall, they descended to lower elevations (Δ > 100 m) before returning to their higher winter ranges. The median distance travelled along geographic migration routes was 16.3 km (range: 7.6-47.4 km). During the spring migration, most geographic migrants (n = 8) used at least one stopover site (median = 1.5, range: 0-4), while almost all migrants (n = 11) used stopover sites more frequently in the fall (median = 2.5, range: 0-6). Of the 13 migratory individuals that had at least one other collared individual in their band, most migrated at about the same time, occupied the same summer and winter ranges, used similar migration routes and stopover sites, and exhibited the same migration strategy. We found collared females exhibited four different migration strategies which mostly varied across bands. Migration strategies included long-distance geographic migrants (n = 5), short-distance geographic migrants (n = 5), vacillating migrants (n = 2), and abbreviated altitudinal migrants (n = 4). Different migratory strategies occurred within one band where one collared individual migrated and two did not. We conclude that female Stone's sheep in the Cassiar Mountains displayed a diverse assemblage of seasonal habitat use and migratory behaviors. By delineating seasonal ranges, migration routes and stopover sites, we identify potential areas of priority that can help inform land-use planning and preserve the native migrations of Stone's sheep in the region.

African wild dog movements show contrasting responses to long and short term risk of encountering lions: analysis using dynamic Brownian bridge movement models.

BACKGROUND: Prey depletion is a threat to the world's large carnivores, and is likely to affect subordinate competitors within the large carnivore guild disproportionately. African lions limit African wild dog populations through interference competition and intraguild predation. When lion density is reduced as a result of prey depletion, wild dogs are not competitively released, and their population density remains low. Research examining distributions has demonstrated spatial avoidance of lions by wild dogs, but the effects of lions on patterns of movement have not been tested. Movement is one of the most energetically costly activities for many species and is particularly costly for cursorial hunters like wild dogs. Therefore, testing how top-down, bottom-up, and anthropogenic variables affect movement patterns can provide insight into mechanisms that limit wild dogs (and other subordinate competitors) in resource-depleted ecosystems. METHODS: We measured movement rates using the motion variance from dynamic Brownian Bridge Movement Models (dBBMMs) fit to data from GPS-collared wild dogs, then used a generalized linear model to test for effects on movement of predation risk from lions, predictors of prey density, and anthropogenic and seasonal variables. RESULTS: Wild dogs proactively reduced movement in areas with high lion density, but reactively increased movement when lions were immediately nearby. Predictors of prey density had consistently weaker effects on movement than lions did, but movements were reduced in the wet season and when dependent offspring were present. CONCLUSION: Wild dogs alter their patterns of movement in response to lions in ways that are likely to have important energetic consequences. Our results support the recent suggestion that competitive limitation of wild dogs by lions remains strong in ecosystems where lion and wild dog densities are both low as a result of anthropogenic prey depletion. Our results reinforce an emerging pattern that movements often show contrasting responses to long-term and short-term variation in predation risk.

Very Small Home Ranges of Two Gravid European Brown Bears during Hyperphagia.

In September 2019, two gravid female brown bears (Ursus arctos) were captured and equipped with GPS/GSM collars in Paklenica National Park (Croatia). Home ranges during hyperphagia were analyzed to describe the spatiotemporal requirements. Mean seasonal home ranges were very small with 9.2 km2 and 7.5 km2 (Brownian Bridge Movement Model 95%). During the tracking period, both bears used different territories and showed little to no use of overlapping area. The bears in our study spent a considerable time in proximity of artificial feeding sites, indicating a probable use of these structures as a food resource (mean 15.7% and 30.7%). Furthermore, the bears approached very close to human structures such as 8.9 m and 4.4 m. As most encounters between humans and bears occur during hyperphagia, it is important to offer refugia from human disturbance, especially as the National Park is not only used by residents, but also by tourists. To adapt management according to the animal's needs, further studies should include more individuals from different age and sex classes. Both females were gravid. It remains unclear whether gravidity has an effect on the home range and should be further investigated.

New insight into spatial ecology of Griffon Vulture (Gypsfulvus) on the Balkans provides opportunity for focusing conservation actions for a threatened social scavenger.

The knowledge in the behaviour and movement of endangered species is of key importance for the precise targeting and assessing the efficiency of nature conservation actions, especially considering vultures, which explore vast areas to locate ephemeral and unpredictable food resources. Therefore, a total of 51 Griffon Vultures (Gypsfulvus) from both the re-introduced population and the autochthonous Balkan Peninsula (Balkans) colonies have been tagged with GPS/GSM transmitters in recent years, in order to study their seasonal and spatial distribution. The current study presents the analysis of the high-resolution GPS location data, acquired between January 2016 and March 2021. A total of 1,138,383 locations (an average number of 23,716 ± 18,886 positions per bird, ranged between 2,515 and 76,431 of total fixes per bird; n=48) were used to estimate the home range size and identify the traditional foraging areas and roosting sites of the birds during the wintering, migration/roaming and summering periods. Our results reveal that Griffon Vultures movement activity and home range size varied considerably throughout the annual cycle, especially between their wintering and summering grounds, while exhibiting significant overlapping amongst the tracked individuals. Specifically, immature Griffon Vultures travel long distances across all Balkan Peninsula countries, but always gather with conspecifics, showing strong fidelity to active breeding/roosting sites. The total home range 95% area of the Griffon Vulture population on the Balkans was estimated at 39,986.4 km² and the 50% core area at 1,545.42 km² (n = 48). All tracked birds were found to either visit or frequently use (> 95% of the time) the same seven vulture key zones on the Balkan Peninsula - one in Serbia, one shared between North Macedonia and Bulgaria, one shared between Bulgaria and Greece, two entirely lying in Bulgaria, one in western Greece and one shared between Kvarner Archipelago islands in Croatia and the Julian Alps - Italy, Austria and Slovenia. Several smaller sub-zones were also defined within these general ones. The seven key zones form a coherent network and are used as stepping stones for Griffon Vultures during their migration movements and roaming, but also wintering and summering. The observed concentration tendency of Griffon Vultures on the Balkans and the predictability of their temporal and spatial presence should be used to precisely target, address and substantially increase the efficiency of the conservation measures in this marginal and, thus, still vulnerable meta-population.

Home Range Size and Seasonal Variation in Habitat Use of Aye-Ayes (Daubentonia madagascariensis) in Torotorofotsy, Madagascar.

Madagascar's dramatic climatic fluctuations mean most lemurs adjust behaviors seasonally as resource availability fluctuates. Many lemurs will adopt one of two strategies, a resource maximizer or an area minimizer, when adjusting to seasonal shifts in resource availability. However, it is unknown if and how aye-aye (Daubentonia madagascariensis) ranging behavior is influenced by seasonality. We explored whether habitat use changed seasonally. We followed two aye-ayes, an adult male and an adult female, in the undisturbed forest of Torotorofotsy, Madagascar, from April 2012 to December 2017. We used instantaneous focal-animal sampling to collect behavioral data every 5 min and GPS locations every 20 min. We used the minimum convex polygon (MCP) to determine overall home range, and the Brownian bridge movement model (BBMM) to estimate overall and seasonal home range of the female aye-aye from November 2014 to October 2017. We used Wilcoxon signed-rank tests to determine whether there were significant differences in home range sizes between seasons across years and to examine whether there were seasonal differences in height of invertebrate foraging, generalized linear models to assess seasonal differences in travel rates and nesting locations, and χ2 tests to determine whether there were differences in forest strata use when foraging on invertebrates. The male's MCP home range was 2,586 ha, and the female's MCP home range was 765 ha. The seasonal BBMM for the female varied between 443.6 and 1,010.0 ha, though infant rearing appears to have influenced these values. There were no significant differences in seasonal home range, travel rates, nesting locations, or height of invertebrate feeding. However, canopy level invertebrate foraging occurred more often than understory or ground levels. It appears aye-ayes in this undisturbed forest were not influenced by seasonal shifts and had larger home ranges than any previously reported. These findings may indicate that aye-ayes in an undisturbed forest are resource maximizers, closely linked to invertebrate assemblages.

Modelling animal movement as Brownian bridges with covariates.

BACKGROUND: The ability to observe animal movement and possible correlates has increased strongly over the past decades. Methods to analyze trajectories have developed in parallel, but many tools fail to make an immediate connection between a movement model, covariates of the movement, and animal space use. METHODS: Here I develop a novel method based on the Brownian Bridge Movement Model that facilitates investigating and testing covariates of movement. The model makes it possible to flexibly investigate different covariates including, for example, periodic movement patterns. RESULTS: I applied the Brownian Bridge Covariates Model (BBCM) to simulated trajectories demonstrating its ability to reproduce the parameters used for the simulation. I also applied the model to a GPS trajectory of a meerkat, showing its application to empirical data. The value of the model was shown by testing the interaction between maximal daily temperature and the daily movement pattern. CONCLUSION: This model produces accurate parameter estimates for covariates of the movements and location error in simulated trajectories. Application to the meerkat trajectory also produced plausible parameter estimates. This new method opens the possibility to directly test hypotheses about the influence of covariates on animal movement while linking these to space-use estimates.

Movement analysis of free-grazing domestic ducks in Poyang Lake, China: a disease connection.

Previous work suggests domestic poultry are important contributors to the emergence and transmission of highly pathogenic avian influenza throughout Asia. In Poyang Lake, China, domestic duck production cycles are synchronized with arrival and departure of thousands of migratory wild birds in the area. During these periods, high densities of juvenile domestic ducks are in close proximity to migratory wild ducks, increasing the potential for the virus to be transmitted and subsequently disseminated via migration. In this paper, we use GPS dataloggers and dynamic Brownian bridge models to describe movements and habitat use of free-grazing domestic ducks in the Poyang Lake basin and identify specific areas that may have the highest risk of H5N1 transmission between domestic and wild birds. Specifically, we determine relative use by free-grazing domestic ducks of natural wetlands, which are the most heavily used areas by migratory wild ducks, and of rice paddies, which provide habitat for resident wild ducks and lower densities of migratory wild ducks. To our knowledge, this is the first movement study on domestic ducks, and our data show potential for free-grazing domestic ducks from farms located near natural wetlands to come in contact with wild waterfowl, thereby increasing the risk for disease transmission. This study provides an example of the importance of movement ecology studies in understanding dynamics such as disease transmission on a complicated landscape.

Spatio-temporal hotspots of satellite-tracked arctic foxes reveal a large detection range in a mammalian predator.

BACKGROUND: The scale at which animals perceive their environment is a strong fitness determinant, yet few empirical estimates of animal detection ranges exist, especially in mammalian predators. Using daily Argos satellite tracking of 26 adult arctic foxes (Vulpes lagopus) during a single winter in the High Canadian Arctic, we investigated the detection range of arctic foxes by detecting hotspots of fox activity on the sea ice. RESULTS: While maintaining territories in the tundra, these solitary foragers occasionally used the sea ice where they sometimes formed spatio-temporal hotspots, likely scavenging on marine mammal carcasses. We detected 35 movements by 13 individuals forming five hotspots. Foxes often traveled more than 10 km, and up to 40 km, to reach hotspots, which lasted one-two weeks and could gather up to 12 individuals. The likelihood of a fox joining a hotspot was neither influenced by its distance from the hotspot nor by the distance of its home range to the coast. CONCLUSIONS: Observed traveling distances may indicate a high detection range in arctic foxes, and our results suggest their ability to detect food sources on the sea ice from their terrestrial home range. While revealing a wide knowledge gap regarding resource detection abilities in mammalian predators, our study provides estimates of detection range useful for interpreting and modeling animal movements. It also allows a better understanding of foraging behavior and navigation capacity in terrestrial predators.

Deriving movement properties and the effect of the environment from the Brownian bridge movement model in monkeys and birds.

BACKGROUND: The Brownian bridge movement model (BBMM) provides a biologically sound approximation of the movement path of an animal based on discrete location data, and is a powerful method to quantify utilization distributions. Computing the utilization distribution based on the BBMM while calculating movement parameters directly from the location data, may result in inconsistent and misleading results. We show how the BBMM can be extended to also calculate derived movement parameters. Furthermore we demonstrate how to integrate environmental context into a BBMM-based analysis. RESULTS: We develop a computational framework to analyze animal movement based on the BBMM. In particular, we demonstrate how a derived movement parameter (relative speed) and its spatial distribution can be calculated in the BBMM. We show how to integrate our framework with the conceptual framework of the movement ecology paradigm in two related but acutely different ways, focusing on the influence that the environment has on animal movement. First, we demonstrate an a posteriori approach, in which the spatial distribution of average relative movement speed as obtained from a "contextually naïve" model is related to the local vegetation structure within the monthly ranging area of a group of wild vervet monkeys. Without a model like the BBMM it would not be possible to estimate such a spatial distribution of a parameter in a sound way. Second, we introduce an a priori approach in which atmospheric information is used to calculate a crucial parameter of the BBMM to investigate flight properties of migrating bee-eaters. This analysis shows significant differences in the characteristics of flight modes, which would have not been detected without using the BBMM. CONCLUSIONS: Our algorithm is the first of its kind to allow BBMM-based computation of movement parameters beyond the utilization distribution, and we present two case studies that demonstrate two fundamentally different ways in which our algorithm can be applied to estimate the spatial distribution of average relative movement speed, while interpreting it in a biologically meaningful manner, across a wide range of environmental scenarios and ecological contexts. Therefore movement parameters derived from the BBMM can provide a powerful method for movement ecology research.

Mapping migratory flyways in Asia using dynamic Brownian bridge movement models.

BACKGROUND: Identifying movement routes and stopover sites is necessary for developing effective management and conservation strategies for migratory animals. In the case of migratory birds, a collection of migration routes, known as a flyway, is often hundreds to thousands of kilometers long and can extend across political boundaries. Flyways encompass the entire geographic range between the breeding and non-breeding areas of a population, species, or a group of species, and they provide spatial frameworks for management and conservation across international borders. Existing flyway maps are largely qualitative accounts based on band returns and survey data rather than observed movement routes. In this study, we use satellite and GPS telemetry data and dynamic Brownian bridge movement models to build upon existing maps and describe waterfowl space use probabilistically in the Central Asian and East Asian-Australasian Flyways. RESULTS: Our approach provided new information on migratory routes that was not easily attainable with existing methods to describe flyways. Utilization distributions from dynamic Brownian bridge movement models identified key staging and stopover sites, migration corridors and general flyway outlines in the Central Asian and East Asian-Australasian Flyways. A map of space use from ruddy shelducks depicted two separate movement corridors within the Central Asian Flyway, likely representing two distinct populations that show relatively strong connectivity between breeding and wintering areas. Bar-headed geese marked at seven locations in the Central Asian Flyway showed heaviest use at several stopover sites in the same general region of high-elevation lakes along the eastern Qinghai-Tibetan Plateau. Our analysis of data from multiple Anatidae species marked at sites throughout Asia highlighted major movement corridors across species and confirmed that the Central Asian and East Asian-Australasian Flyways were spatially distinct. CONCLUSIONS: The dynamic Brownian bridge movement model improves our understanding of flyways by estimating relative use of regions in the flyway while providing detailed, quantitative information on migration timing and population connectivity including uncertainty between locations. This model effectively quantifies the relative importance of different migration corridors and stopover sites and may help prioritize specific areas in flyways for conservation of waterbird populations.

Identifying impediments to long-distance mammal migrations.

In much of the world, the persistence of long-distance migrations by mammals is threatened by development. Even where human population density is relatively low, there are roads, fencing, and energy development that present barriers to animal movement. If we are to conserve species that rely on long-distance migration, then it is critical that we identify existing migration impediments. To delineate stopover sites associated with anthropogenic development, we applied Brownian bridge movement models to high-frequency locations of pronghorn (Antilocapra americana) in the Greater Yellowstone Ecosystem. We then used resource utilization functions to assess the threats to long-distance migration of pronghorn that were due to fences and highways. Migrating pronghorn avoided dense developments of natural gas fields. Highways with relatively high volumes of traffic and woven-wire sheep fence acted as complete barriers. At crossings with known migration bottlenecks, use of high-quality forage and shrub habitat by pronghorn as they approached the highway was lower than expected based on availability of those resources. In contrast, pronghorn consistently utilized high-quality forage close to the highway at crossings with no known migration bottlenecks. Our findings demonstrate the importance of minimizing development in migration corridors in the future and of mitigating existing pressure on migratory animals by removing barriers, reducing the development footprint, or installing crossing structures.

Using dynamic Brownian bridge movement modelling to measure temporal patterns of habitat selection.

Accurately describing animal space use is vital to understanding how wildlife use habitat. Improvements in GPS technology continue to facilitate collection of telemetry data at high spatial and temporal resolutions. Application of the recently introduced dynamic Brownian bridge movement model (dBBMM) to such data is promising as the method explicitly incorporates the behavioural heterogeneity of a movement path into the estimated utilization distribution (UD). Utilization distributions defining space use are normally estimated for time-scales ranging from weeks to months, obscuring much of the fine-scale information available from high-volume GPS data sets. By accounting for movement heterogeneity, the dBBMM provides a rigorous, behaviourally based estimate of space use between each set of relocations. Focusing on UDs generated between individual sets of locations allows us to quantify fine-scale circadian variation in habitat use. We used the dBBMM to estimate UDs bounding individual time steps for three terrestrial species with different life histories to illustrate how the method can be used to identify fine-scale variations in habitat use. We also demonstrate how dBBMMs can be used to characterize circadian patterns of habitat selection and link fine-scale patterns of habitat use to behaviour. We observed circadian patterns of habitat use that varied seasonally for a white-tailed deer (Odocoileus virginianus) and coyote (Canis latrans). We found seasonal patterns in selection by the white-tailed deer and were able to link use of conifer forests and agricultural fields to behavioural state of the coyote. Additionally, we were able to quantify the date in which a Rio Grande wild turkey (Meleagris gallopavo intermedia) initiated laying as well as when during the day, she was most likely to visit the nest site to deposit eggs. The ability to quantify circadian patterns of habitat use may have important implications for research and management of wildlife. Additionally, the ability to link such patterns to behaviour may aid in the development of mechanistic models of habitat selection.

Bivariate Gaussian bridges: directional factorization of diffusion in Brownian bridge models.

BACKGROUND: In recent years high resolution animal tracking data has become the standard in movement ecology. The Brownian Bridge Movement Model (BBMM) is a widely adopted approach to describe animal space use from such high resolution tracks. One of the underlying assumptions of the BBMM is isotropic diffusive motion between consecutive locations, i.e. invariant with respect to the direction. Here we propose to relax this often unrealistic assumption by separating the Brownian motion variance into two directional components, one parallel and one orthogonal to the direction of the motion. RESULTS: Our new model, the Bivariate Gaussian bridge (BGB), tracks movement heterogeneity across time. Using the BGB and identifying directed and non-directed movement within a trajectory resulted in more accurate utilisation distributions compared to dynamic Brownian bridges, especially for trajectories with a non-isotropic diffusion, such as directed movement or Lévy like movements. We evaluated our model with simulated trajectories and observed tracks, demonstrating that the improvement of our model scales with the directional correlation of a correlated random walk. CONCLUSION: We find that many of the animal trajectories do not adhere to the assumptions of the BBMM. The proposed model improves accuracy when describing the space use both in simulated correlated random walks as well as observed animal tracks. Our novel approach is implemented and available within the "move" package for R.