Applications of step-selection functions in ecology and conservation

Climatically robust multiscale species distribution models to support pronghorn recovery in California

We combined two climate-based distribution models with three finer-scale suitability models to identify habitat for pronghorn recovery in California now and into the future. We used a consensus approach to identify areas of suitable climate now and future for pronghorn in California. We compared the results of climate models from two separate hypotheses about their historical ecology in the state. Under the migration hypothesis, pronghorn were expected to be limited climatically by extreme cold in winter and extreme heat in summer; under the niche reduction hypothesis, historical pronghorn of distribution would have better represented the climatic limitations of the species. We combined occurrences from GPS collars distributed across three populations of pronghorn in the state to create three distinct habitat suitability models: (1) an ensemble model using random forests, Maxent, classification and regression Trees, and a generalized linear model; (2) a step selection function; and (3) an expert-driven model. We evaluated consensus among both the climate models and the suitability models to prioritize areas for, and evaluate the prospects of, pronghorn recovery. Climate suitability for pronghorn in the future depends heavily on model assumptions. Under the migration hypothesis, our model predicted that there will be no suitable climate in California in the future. Under the niche reduction hypothesis, by contrast, suitable climate will expand. Habitat suitability also depended on the methods used, but areas of consensus among all three models exist in large patches throughout the state. Identifying habitat for a species which has undergone extreme range collapse, and which has very fine scale habitat needs, presents novel challenges for spatial ecologists. Our multimethod, multihypothesis approach can allow habitat modelers to identify areas of consensus and, perhaps more importantly, fill critical knowledge gaps that could resolve disagreements among the models. For pronghorn, a better understanding of their upper thermal tolerances and whether historical populations migrated will be crucial to their potential recovery in California and throughout the arid Southwest.

Methods for implementing integrated step-selection functions with incomplete data

Integrated step-selection analyses (iSSAs) are versatile and powerful frameworks for studying habitat and movement preferences of tracked animals. iSSAs utilize integrated step-selection functions (iSSFs) to model movements in discrete time, and thus, require animal location data that are regularly spaced in time. However, many real-world datasets are incomplete due to tracking devices failing to locate an individual at one or more scheduled times, leading to slight irregularities in the duration between consecutive animal locations. To address this issue, researchers typically only consider bursts of regular data (i.e., sequences of locations that are equally spaced in time), thereby reducing the number of observations used to model movement and habitat selection. We reassess this practice and explore four alternative approaches that account for temporal irregularity resulting from missing data. Using a simulation study, we compare these alternatives to a baseline approach where temporal irregularity is ignored and demonstrate the potential improvements in model performance that can be gained by leveraging these additional data. We also showcase these benefits using a case study on a spotted hyena (Crocuta crocuta).

Experience reduces route selection for conspecifics by the collectively migrating white stork

Migration can be an energetically costly behavior with strong fitness consequences in terms of mortality and reproduction.1,2,3,4,5,6,7,8,9,10,11 Migrants should select migratory routes to minimize their costs, but both costs and benefits may change with experience.12,13,14 This raises the question of whether experience changes how individuals select their migratory routes. Here, we investigate the effect of age on route selection criteria in a collectively migrating soaring bird, the white stork (Ciconia ciconia). We perform step-selection analysis on a longitudinal dataset tracking 158 white storks over up to 9 years to quantify how they select their routes based on the social and atmospheric environments and to examine how this selection changes with age. We find clear ontogenetic shifts in route selection criteria. Juveniles choose routes that have good atmospheric conditions and high conspecific densities. Yet, as they gain experience, storks' selection on the availability of social information reduces-after their fifth migration, experienced birds also choose routes with low conspecific densities. Thus, our results suggest that as individuals age, they gradually replace information gleaned from other individuals with information gained from experience, allowing them to shift their migration timing and increasing the timescale at which they select their routes.

What drives wild pig (Sus scrofa) movement in bottomland and upland forests?

BACKGROUND

The wild pig (Sus scrofa) is an exotic species that has been present in the southeastern United States for centuries yet continues to expand into new areas dominated by bottomland and upland forests, the latter of which are less commonly associated with wild pigs. Here, we aimed to investigate wild pig movement and space use attributes typically used to guide wild pig management among multiple spatiotemporal scales. Our investigation focused on a newly invaded landscape dominated by bottomland and upland forests.

METHODS

We examined (1) core and total space use using an autocorrelated kernel density estimator; (2) resource selection patterns and hot spots of space use in relation to various landscape features using step-selection analysis; and (3) daily and hourly differences in movement patterns between non-hunting and hunting seasons using generalized additive mixed models.

RESULTS

Estimates of total space use among wild pigs (n = 9) were smaller at calculated core (1.2 ± 0.3 km2) and 90% (5.2 ± 1.5 km2) isopleths than estimates reported in other landscapes in the southeastern United States, suggesting that wild pigs were able to meet foraging, cover, and thermoregulatory needs within smaller areas. Generally, wild pigs selected areas closer to herbaceous, woody wetlands, fields, and perennial streams, creating corridors of use along these features. However, selection strength varied among individuals, reinforcing the generalist, adaptive nature of wild pigs. Wild pigs also showed a tendency to increase movement from fall to winter, possibly paralleling increases in hard mast availability. During this time, there were also increases in anthropogenic pressures (e.g. hunting), causing movements to become less diurnal as pressure increased.

CONCLUSIONS

Our work demonstrates that movement patterns by exotic generalists must be understood across individuals, the breadth of landscapes they can invade, and multiple spatiotemporal scales. This improved understanding will better inform management strategies focused on curbing emerging invasions in novel landscapes, while also protecting native natural resources.

A test of the frost wave hypothesis in a temperate ungulate

Growing evidence supports the hypothesis that temperate herbivores surf the green wave of emerging plants during spring migration. Despite the importance of autumn migration, few studies have conceptualized resource tracking of temperate herbivores during this critical season. We adapted the frost wave hypothesis (FWH), which posits that animals pace their autumn migration to reduce exposure to snow but increase acquisition of forage. We tested the FWH in a population of mule deer in Wyoming, USA by tracking the autumn migrations of n = 163 mule deer that moved 15-288 km from summer to winter range. Migrating deer experienced similar amounts of snow but 1.4-2.1 times more residual forage than if they had naïve knowledge of when or how fast to migrate. Importantly, deer balanced exposure to snow and forage in a spatial manner. At the fine scale, deer avoided snow near their mountainous summer ranges and became more risk prone to snow near winter range. Aligning with their higher tolerance of snow and lingering behavior to acquire residual forage, deer increased stopover use by 1 ± 1 day (95% CI) day for every 10% of their migration completed. Our findings support the prediction that mule deer pace their autumn migration with the onset of snow and residual forage, but refine the FWH to include movement behavior en route that is spatially dynamic.

Cougars, wolves, and humans drive a dynamic landscape of fear for elk

To manage predation risk, prey navigate a dynamic landscape of fear, or spatiotemporal variation in risk perception, reflecting predator distributions, traits, and activity cycles. Prey may seek to reduce risk across this landscape using habitat at times and in places when predators are less active. In multipredator landscapes, avoiding one predator could increase vulnerability to another, making the landscape of fear difficult to predict and navigate. Additionally, humans may shape interactions between predators and prey, and induce new sources of risk. Humans can function as a shield, providing a refuge for prey from human-averse carnivores, and as a predator, causing mortality through hunting and vehicle collisions and eliciting a fear response that can exceed that of carnivores. We used telemetry data collected between 2017 and 2021 from 63 Global Positioning System-collared elk (Cervus canadensis), 42 cougars (Puma concolor), and 16 wolves (Canis lupus) to examine how elk habitat selection changed in relation to carnivores and humans in northeastern Washington, USA. Using step selection functions, we evaluated elk habitat use in relation to cougars, wolves, and humans, diel period (daytime vs. nighttime), season (summer calving season vs. fall hunting season), and habitat structure (open vs. closed habitat). The diel cycle was critical to understanding elk movement, allowing elk to reduce encounters with predators where and when they would be the largest threat. Elk strongly avoided cougars at night but had a near-neutral response to cougars during the day, whereas elk avoided wolves at all times of day. Elk generally used more open habitats where cougars and wolves were most active, rather than altering the use of habitat structure depending on the predator species. Elk avoided humans during the day and ~80% of adult female mortality was human caused, suggesting that humans functioned as a "super predator" in this system. Simultaneously, elk leveraged the human shield against wolves but not cougars at night, and no elk were confirmed to have been killed by wolves. Our results add to the mounting evidence that humans profoundly affect predator-prey interactions, highlighting the importance of studying these dynamics in anthropogenic areas.

The use of social information in vulture flight decisions

Animals rely on a balance of personal and social information to decide when and where to move next in order to access a desired resource. The benefits from cueing on conspecifics to reduce uncertainty about resource availability can be rapidly overcome by the risks of within-group competition, often exacerbated toward low-ranked individuals. Being obligate soarers, relying on thermal updraughts to search for carcasses around which competition can be fierce, vultures represent ideal models to investigate the balance between personal and social information during foraging movements. Linking dominance hierarchy, social affinities and meteorological conditions to movement decisions of eight captive vultures, Gyps spp., released for free flights in natural soaring conditions, we found that they relied on social information (i.e. other vultures using/having used the thermals) to find the next thermal updraught, especially in unfavourable flight conditions. Low-ranked individuals were more likely to disregard social cues when deciding where to go next, possibly to minimize the competitive risk of social aggregation. These results exemplify the architecture of decision-making during flight in social birds. It suggests that the environmental context, the context of risk and the social system as a whole calibrate the balance between personal and social information use.

Rayleigh step-selection functions and connections to continuous-time mechanistic movement models

BACKGROUND

The process known as ecological diffusion emerges from a first principles view of animal movement, but ecological diffusion and other partial differential equation models can be difficult to fit to data. Step-selection functions (SSFs), on the other hand, have emerged as powerful practical tools for ecologists studying the movement and habitat selection of animals.

METHODS

SSFs typically involve comparing resources between a set of used and available points at each step in a sequence of observed positions. We use change of variables to show that ecological diffusion implies certain distributions for available steps that are more flexible than others commonly used. We then demonstrate advantages of these distributions with SSF models fit to data collected for a mountain lion in Colorado, USA.

RESULTS

We show that connections between ecological diffusion and SSFs imply a Rayleigh step-length distribution and uniform turning angle distribution, which can accommodate data collected at irregular time intervals. The results of fitting an SSF model with these distributions compared to a set of commonly used distributions revealed how precision and inference can vary between the two approaches.

CONCLUSIONS

Our new continuous-time step-length distribution can be integrated into various forms of SSFs, making them applicable to data sets with irregular time intervals between successive animal locations.

Lesser prairie-chicken dispersal after translocation: Implications for restoration and population connectivity

Conservation translocations are frequently inhibited by extensive dispersal after release, which can expose animals to dispersal-related mortality or Allee effects due to a lack of nearby conspecifics. However, translocation-induced dispersals also provide opportunities to study how animals move across a novel landscape, and how their movements are influenced by landscape configuration and anthropogenic features. Translocation among populations is considered a potential conservation strategy for lesser prairie-chickens (Tympanuchus pallidicinctus). We determined the influence of release area on dispersal frequency by translocated lesser prairie-chickens and measured how lesser prairie-chickens move through grassland landscapes through avoidance of anthropogenic features during their dispersal movements. We translocated 411 lesser prairie-chickens from northwest Kansas to southeastern Colorado and southwestern Kansas in 2016-2019. We used satellite GPS transmitters to track 115 lesser prairie-chickens throughout their post-release dispersal movements. We found that almost all lesser prairie-chickens that survived from their spring release date until June undergo post-translocation dispersal, and there was little variation in dispersal frequency by release area (96% of all tracked birds, 100% in Baca County, Colorado, 94% in Morton County, Kansas, n = 55). Dispersal movements (male: 103 ± 73 km, female: 175 ± 108 km, n = 62) led to diffusion across landscapes, with 69% of birds settling >5 km from their release site. During dispersal movements, translocated lesser prairie-chickens usually travel by a single 3.75 ± 4.95 km dispersal flight per day, selecting for steps that end far from roads and in Conservation Reserve Program (CRP) grasslands. Due to this "stepping stone" method of transit, landscape connectivity is optimized when <5 km separates grassland patches on the landscape. Future persistence of lesser prairie-chicken populations can be aided through conservation of habitat and strategic placement of CRP to maximize habitat connectivity. Dispersal rates suggest that translocation is better suited to objectives for regional, rather than site-specific, population augmentation for this species.

Finding navigation cues near fishways

Many fish species depend on migration for various parts of their life cycle. Well-known examples include diadromous fish such as salmon and eels that need both fresh water and salt water to complete their life cycle. Migration also occurs within species that depend only on fresh water. In recent decades, anthropogenic pressures on freshwater systems have increased greatly, and have resulted, among other effects, in drastic habitat fragmentation. Fishways have been developed to mitigate the resulting habitat fragmentation, but these are not always effective. To improve fishway efficiency, the variety of navigation cues used by fish must be better understood: fish use a multitude of sensory inputs ranging from flow variables to olfactory cues. The reaction of a fish is highly dependent on the intensity of the cue, the fish species involved, and individual traits. Recently developed monitoring technologies allow us to gain insights into different combinations of environmental and physiological conditions. By combining fish behavioural models with environmental models, interactions among these components can be investigated. Several methods can be used to analyse fish migration, with state-space models, hidden Markov models, and individual-based models potentially being the most relevant since they can use individual data and can tie them to explicit spatial locations within the considered system. The aim of this review is to analyse the navigational cues used by fish and the models that can be applied to gather knowledge on these processes. Such knowledge could greatly improve the design and operation of fishways for a wider range of fish species and conditions.

Movement ecology of an endangered mesopredator in a mining landscape

BACKGROUND

Efficient movement and energy expenditure are vital for animal survival. Human disturbance can alter animal movement due to changes in resource availability and threats. Some animals can exploit anthropogenic disturbances for more efficient movement, while others face restricted or inefficient movement due to fragmentation of high-resource habitats, and risks associated with disturbed habitats. Mining, a major anthropogenic disturbance, removes natural habitats, introduces new landscape features, and alters resource distribution in the landscape. This study investigates the effect of mining on the movement of an endangered mesopredator, the northern quoll (Dasyurus hallucatus). Using GPS collars and accelerometers, we investigate their habitat selection and energy expenditure in an active mining landscape, to determine the effects of this disturbance on northern quolls.

METHODS

We fit northern quolls with GPS collars and accelerometers during breeding and non-breeding season at an active mine site in the Pilbara region of Western Australia. We investigated broad-scale movement by calculating the movement ranges of quolls using utilisation distributions at the 95% isopleth, and compared habitat types and environmental characteristics within observed movement ranges to the available landscape. We investigated fine-scale movement by quolls with integrated step selection functions, assessing the relative selection strength for each habitat covariate. Finally, we used piecewise structural equation modelling to analyse the influence of each habitat covariate on northern quoll energy expenditure.

RESULTS

At the broad scale, northern quolls predominantly used rugged, rocky habitats, and used mining habitats in proportion to their availability. However, at the fine scale, habitat use varied between breeding and non-breeding seasons. During the breeding season, quolls notably avoided mining habitats, whereas in the non-breeding season, they frequented mining habitats equally to rocky and riparian habitats, albeit at a higher energetic cost.

CONCLUSION

Mining impacts northern quolls by fragmenting favoured rocky habitats, increasing energy expenditure, and potentially impacting breeding dispersal. While mining habitats might offer limited resource opportunities in the non-breeding season, conservation efforts during active mining, including the creation of movement corridors and progressive habitat restoration would likely be useful. However, prioritising the preservation of natural rocky and riparian habitats in mining landscapes is vital for northern quoll conservation.

A multistate Langevin diffusion for inferring behavior-specific habitat selection and utilization distributions

The identification of important habitat and the behavior(s) associated with it is critical to conservation and place-based management decisions. Behavior also links life-history requirements and habitat use, which are key to understanding why animals use certain habitats. Animal population studies often use tracking data to quantify space use and habitat selection, but they typically either ignore movement behavior (e.g., foraging, migrating, nesting) or adopt a two-stage approach that can induce bias and fail to propagate uncertainty. We develop a habitat-driven Langevin diffusion for animals that exhibit distinct movement behavior states, thereby providing a novel single-stage statistical method for inferring behavior-specific habitat selection and utilization distributions in continuous time. Practitioners can customize, fit, assess, and simulate our integrated model using the provided R package. Simulation experiments demonstrated that the model worked well under a range of sampling scenarios as long as observations were of sufficient temporal resolution. Our simulations also demonstrated the importance of accounting for different behaviors and the misleading inferences that can result when these are ignored. We provide case studies using plains zebra (Equus quagga) and Steller sea lion (Eumetopias jubatus) telemetry data. In the zebra example, our model identified distinct "encamped" and "exploratory" states, where the encamped state was characterized by strong selection for grassland and avoidance of other vegetation types, which may represent selection for foraging resources. In the sea lion example, our model identified distinct movement behavior modes typically associated with this marine central-place forager and, unlike previous analyses, found foraging-type movements to be associated with steeper offshore slopes characteristic of the continental shelf, submarine canyons, and seamounts that are believed to enhance prey concentrations. This is the first single-stage approach for inferring behavior-specific habitat selection and utilization distributions from tracking data that can be readily implemented with user-friendly software. As certain behaviors are often more relevant to specific conservation or management objectives, practitioners can use our model to help inform the identification and prioritization of important habitats. Moreover, by linking individual-level movement behaviors to population-level spatial processes, the multistate Langevin diffusion can advance inferences at the intersection of population, movement, and landscape ecology.

Effects of vehicle traffic on space use and road crossings of caribou in the Arctic

Assessing the effects of industrial development on wildlife is a key objective of managers and conservation practitioners. However, wildlife responses are often only investigated with respect to the footprint of infrastructure, even though human activity can strongly mediate development impacts. In Arctic Alaska, there is substantial interest in expanding energy development, raising concerns about the potential effects on barren-ground caribou (Rangifer tarandus granti). While caribou generally avoid industrial infrastructure, little is known about the role of human activity in moderating their responses, and whether managing activity levels could minimize development effects. To address this uncertainty, we examined the influence of traffic volume on caribou summer space use and road crossings in the Central Arctic Herd within the Kuparuk and Milne Point oil fields on the North Slope of Alaska. We first modeled spatiotemporal variation in hourly traffic volumes across the road system from traffic counter data using gradient-boosted regression trees. We then used generalized additive models to estimate nonlinear step selection functions and road-crossing probabilities from collared female caribou during the post-calving and insect harassment seasons, when they primarily interact with roads. Step selection analyses revealed that caribou selected areas further from roads (~1-3 km) during the post-calving and mosquito seasons and selected areas with lower traffic volumes during all seasons, with selection probabilities peaking when traffic was <5 vehicles/h. Using road-crossing models, we found that caribou were less likely to cross roads during the insect seasons as traffic increased, but that response dissipated as insect harassment became more severe. Past studies suggested that caribou exhibit behavioral responses when traffic exceeds 15 vehicles/h, but our results demonstrate behavioral responses at much lower traffic levels. Our results illustrate that vehicle activity mediates caribou responses to road infrastructure, information that can be used in future land-use planning to minimize the behavioral responses of caribou to industrial development in sensitive Arctic landscapes.

Habitat selection of resident and non-resident gray wolves: implications for habitat connectivity

Habitat selection studies facilitate assessing and predicting species distributions and habitat connectivity, but habitat selection can vary temporally and among individuals, which is often ignored. We used GPS telemetry data from 96 Gray wolves (Canis lupus) in the western Great Lakes region of the USA to assess differences in habitat selection while wolves exhibited resident (territorial) or non-resident (dispersing or floating) movements and discuss implications for habitat connectivity. We used a step-selection function (SSF) to assess habitat selection by wolves exhibiting resident or non-resident movements, and modeled circuit connectivity throughout the western Great Lakes region. Wolves selected for natural land cover and against areas with high road densities, with no differences in selection among wolves when resident, dispersing, or floating. Similar habitat selection between resident and non-resident wolves may be due to similarity in environmental conditions, when non-resident movements occur largely within established wolf range rather than near the periphery or beyond the species range. Alternatively, non-resident wolves may travel through occupied territories because higher food availability or lower human disturbance outweighs risks posed by conspecifics. Finally, an absence of differences in habitat selection between resident and non-resident wolf movements may be due to other unknown reasons. We recommend considering context-dependency when evaluating differences in movements and habitat use between resident and non-resident individuals. Our results also provide independent validation of a previous species distribution model and connectivity analysis suggesting most potential wolf habitat in the western Great Lakes region is occupied, with limited connectivity to unoccupied habitat.

Multi-scale movement syndromes for comparative analyses of animal movement patterns

BACKGROUND

Animal movement is a behavioral trait shaped by the need to find food and suitable habitat, avoid predators, and reproduce. Using high-resolution tracking data, it is possible to describe movement in greater detail than ever before, which has led to many discoveries about the behavioral strategies of particular species. Recently, enough data been become available to enable a comparative approach, which has the potential to uncover general causes and consequences of variation in movement patterns, but which must be scale specific.

METHODS

Here we introduce a new multi-scale movement syndrome (MSMS) framework for describing and comparing animal movements and use it to explore the behavior of four sympatric mammals. MSMS incorporates four hierarchical scales of animal movement: (1) fine-scale movement steps which accumulate into (2) daily paths which then, over weeks or months, form a (3) life-history phase. Finally, (4) the lifetime track of an individual consists of multiple life-history phases connected by dispersal or migration events. We suggest a series of metrics to describe patterns of movement at each of these scales and use the first three scales of this framework to compare the movement of 46 animals from four frugivorous mammal species.

RESULTS

While subtle differences exist between the four species in their step-level movements, they cluster into three distinct movement syndromes in both path- and life-history phase level analyses. Differences in feeding ecology were a better predictor of movement patterns than a species' locomotory or sensory adaptations.

CONCLUSIONS

Given the role these species play as seed dispersers, these movement syndromes could have important ecosystem implications by affecting the pattern of seed deposition. This multiscale approach provides a hierarchical framework for comparing animal movement for addressing ecological and evolutionary questions. It parallels scales of analyses for resource selection functions, offering the potential to connect movement process with emergent patterns of space use.

Seasonal resource selection of free-ranging Zhongwei goats in the semi-arid grassland

Goats rarely move and forage randomly. They tend to move in ways generally influenced by biotic and abiotic factors, respectively. However, few studies have explored the foraging behaviour of goats in the absence of predation and human disturbance. Based on step selection function modelling framework, Normalised Difference Vegetation Index, vegetation surveys, and Global Positioning System tracking of 124 free-ranging domestic adult male Zhongwei goats over one year (2016-2017) were used to assess how biotic and abiotic environmental factors affected their spatiotemporal distribution, and developed a conceptual model to represent the goats' trade-off between forage quantity and preference at different seasons, in the semi-arid grassland of Loess Plateau of 1 178 hectare. The results showed that spatial distributions of goats responded to spatiotemporal variation of biotic factors rather than abiotic factors of elevation, slope and solar radiation, which indicated that biotic factors were of priority to abiotic factors in the foraging process for the goats. According to the season changing, the goats positively used areas with higher forage quantity in the spring and winter, areas of higher forage quantity and preferred species in summer, and areas of abundance of preferred species in autumn. We developed a model to describe the phenomenon that the goats selected areas with higher preferred species only when the forage quantity was plentiful, otherwise they selected areas with higher forage quantity. Better understanding of the patterns and drivers of spatiotemporal distribution of the goats can improve our ability to predict foraging behaviour of livestock in heterogeneous environment and lead to better management practices and policies for the sustainability of these semi-arid landscapes and associated ecosystem services.

Accounting for central place foraging constraints in habitat selection studies

Habitat selection studies contrast actual space use with the expected use under the null hypothesis of no selection (hereafter neutral use). Neutral use is most often equated to the relative frequencies with which environmental features occur. This generates a considerable bias when studying habitat selection by foragers that perform numerous trips back and forth to a central place (CP). Indeed, the increased space use close to the CP with respect to distant places reflects a mechanical effect, rather than a true selection for the closest habitats. Yet, correctly estimating habitat selection by CP foragers is of paramount importance for a better understanding of their ecology and to properly plan conservation actions. We show that including the distance to the CP as a covariate in unconditional Resource Selection Functions, as applied in several studies, is ineffective to correct for the bias. This bias can be eliminated only by contrasting the actual use to an appropriate neutral use that considers the CP forager behavior. We also show that the need to specify an appropriate neutral use overall distribution can be bypassed by relying on a conditional approach, where the neutral use is assessed locally regardless of the distance to the CP.

Bighorn sheep associations: understanding tradeoffs of sociality and implications for disease transmission

Sociality directly influences mating success, survival rates, and disease, but ultimately likely evolved for its fitness benefits in a challenging environment. The tradeoffs between the costs and benefits of sociality can operate at multiple scales, resulting in different interpretations of animal behavior. We investigated the influence of intrinsic (e.g., relatedness, age) and extrinsic factors (e.g., land cover type, season) on direct contact (simultaneous GPS locations ≤ 25 m) rates of bighorn sheep (Ovis canadensis) at multiple scales near the Waterton-Glacier International Peace Park. During 2002-2012, male and female bighorn were equipped with GPS collars. Indirect contact (GPS locations ≤ 25 m regardless of time) networks identified two major breaks whereas direct contact networks identified an additional barrier in the population, all of which corresponded with prior disease exposure metrics. More direct contacts occurred between same-sex dyads than female-male dyads and between bighorn groups with overlapping summer home ranges. Direct contacts occurred most often during the winter-spring season when bighorn traveled at low speeds and when an adequate number of bighorn were collared in the area. Direct contact probabilities for all dyad types were inversely related to habitat quality, and differences in contact probability were driven by variables related to survival such as terrain ruggedness, distance to escape terrain, and canopy cover. We provide evidence that probabilities of association are higher when there is greater predation risk and that contact analysis provides valuable information for understanding fitness tradeoffs of sociality and disease transmission potential.

Individual variation in the habitat selection of upstream migrating fish near a barrier

BACKGROUND

Migration is a vital element of the life cycle of many freshwater fish species but is increasingly hampered globally by riverine barriers. Fish passes are a common approach to enable migration past barriers but are often ineffective. More knowledge is required on fish behaviour as they approach barriers such as habitat preferences.

METHODS

We evaluate the habitat selection of two upstream migrating fish species, barbel Barbus barbus and grayling Thymallus thymallus, at a hydropower plant in southern Germany, considering individual variation and population trends. Fish were tracked via fine-scale 2D acoustic telemetry in 2018 during their spawning migration. Step selection functions were used to evaluate selection of hydraulic parameters by the fish for a time step of 20 s. Exploratory models were built via model selection for each individual fish, to evaluate the extent of individual variation in model structure. A population model was developed for each species by averaging coefficients from individual models to describe general trends. The extent of individual variation was determined and confidence intervals for the population model coefficients were calculated.

RESULTS

Fish varied greatly in individual model structure though common terms were apparent in both species, such as depth, flow velocity, the angular difference between fish and velocity, and the logarithm of the step length. Final population models for barbel included several parameters describing habitat selection and displacement. Barbel selected for faster flows, deeper water, and higher spatial velocity gradients. In addition, they selected to move more with the flow than against. Interactions were also present between habitat parameters, suggesting selection is context dependent. Barbel movement speed also changed with depth, flow velocity and spatial velocity gradient. With grayling, terms often had contrasting effects among individuals and thus general trends could not be distinguished for most terms.

CONCLUSION

Our findings demonstrate habitat selection by upstream migrating fish approaching a fish pass and differences in individual selection which may have an impact on barrier management. Step selection functions are a promising approach and can provide useful insight into habitat selection and movement by migrating freshwater fish in an altered river system.

Anthropogenic activities and age class mediate carnivore habitat selection in a human-dominated landscape

Human activities increasingly challenge wild animal populations by disrupting ecological connectivity and population persistence. Yet, human-modified habitats can provide resources, resulting in selection of disturbed areas by generalist species. To investigate spatial and temporal responses of a generalist carnivore to human disturbance, we investigated habitat selection and diel activity patterns in caracals (Caracal caracal). We GPS-collared 25 adults and subadults in urban and wildland-dominated subregions in Cape Town, South Africa. Selection responses for landscape variables were dependent on subregion, animal age class, and diel period. Contrary to expectations, caracals did not become more nocturnal in urban areas. Caracals increased their selection for proximity to urban areas as the proportion of urban area increased. Differences in habitat selection between urban and wildland caracals suggest that individuals of this generalist species exhibit high behavioral flexibility in response to anthropogenic disturbances that emerge as a function of habitat context.

Estimating the Directional Spread of Epidemics in Their Early Stages Using a Simple Regression Approach: A Study on African Swine Fever in Northern Italy

The early identification of the spreading patterns of an epidemic infectious disease is an important first step towards the adoption of effective interventions. We developed a simple regression-based method to estimate the directional speed of a disease's spread, which can be easily applied with a limited dataset. We tested the method using simulation tools, then applied it on a real case study of an African Swine Fever (ASF) outbreak identified in late 2021 in northwestern Italy. Simulations showed that, when carcass detection rates were <0.1, the model produced negatively biased estimates of the ASF-affected area, with the average bias being about -10%. When detection rates were >0.1, the model produced asymptotically unbiased and progressively more predictable estimates. The model produced rather different estimates of ASF's spreading speed in different directions of northern Italy, with the average speed ranging from 33 to 90 m/day. The resulting ASF-infected areas of the outbreak were estimated to be 2216 km², about 80% bigger than the ones identified only thorough field-collected carcasses. Additionally, we estimated that the actual initial date of the ASF outbreak was 145 days earlier than the day of first notification. We recommend the use of this or similar inferential tools as a quick, initial way to assess an epidemic's patterns in its early stages and inform quick and timely management actions.

Landscape of fear or landscape of food? Moose hunting triggers an antipredator response in brown bears

Hunters can affect the behavior of wildlife by inducing a landscape of fear, selecting individuals with specific traits, or altering resource availability across the landscape. Most research investigating the influence of hunting on wildlife resource selection has focused on target species and less attention has been devoted to nontarget species, such as scavengers that can be both attracted or repelled by hunting activities. We used resource selection functions to identify areas where hunters were most likely to kill moose (Alces alces) in south-central Sweden during the fall. Then, we used step-selection functions to determine whether female brown bears (Ursus arctos) selected or avoided these areas and specific resources during the moose hunting season. We found that, during both day and nighttime, female brown bears avoided areas where hunters were more likely to kill moose. We found evidence that resource selection by brown bears varied substantially during the fall and that some behavioral changes were consistent with disturbance associated with moose hunters. Brown bears were more likely to select concealed locations in young (i.e., regenerating) and coniferous forests and areas further away from roads during the moose hunting season. Our results suggest that brown bears react to both spatial and temporal variations in apparent risk during the fall: moose hunters create a landscape of fear and trigger an antipredator response in a large carnivore even if bears are not specifically targeted during the moose hunting season. Such antipredator responses might lead to indirect habitat loss and lower foraging efficiency and the resulting consequences should be considered when planning hunting seasons.

Individual based models for the simulation of fish movement near barriers: Current work and future directions

River fragmentation is an increasing issue for water managers and conservationists. Barriers such as dams interfere with freshwater fish migration, leading to drastic population declines. While there are a range of widely implemented mitigation approaches, e.g. fish passes, such measures are often inefficient due to suboptimal operation and design. There is increasing need to be able to assess mitigation options prior to implementation. Individual based models (IBMs) are a promising option. IBMs can simulate the fine-scale movement of individual fish within a population as they attempt to find a fish pass, incorporating movement processes themselves. Moreover, IBMs have high transferability to other sites or conditions (e.g. changing mitigation, change in flow conditions), making them potentially valuable for freshwater fish conservation yet their application to the fine-scale movement of fish past barriers is still novel. Here, we present an overview of existing IBMs for fine-scale freshwater fish movement, with emphasis on study species and the parameters driving movement in the models. In this review, we focus on IBMs suitable for the simulation of fish tracks as they approach or pass a single barrier. The selected IBMs for modelling fine-scale freshwater fish movement largely focus on salmonids and cyprinid species. IBMs have many applications in the context of fish passage, such as testing different mitigation options or understanding processes behind movement. Existing IBMs include movement processes such as attraction and rejection behaviours, as reported in literature. Yet some factors affecting fish movement e.g. biotic interactions are not covered by existing IBMs. As the technology available for fine scale data collection continues to advance, such as increasing data linking fish behaviour to hydraulics, IBMs could become a more common tool in the design and implementation of fish bypass structures.

Seabird morphology determines operational wind speeds, tolerable maxima, and responses to extremes

Storms can cause widespread seabird stranding and wrecking,1,2,3,4,5 yet little is known about the maximum wind speeds that birds are able to tolerate or the conditions they avoid. We analyzed >300,000 h of tracking data from 18 seabird species, including flapping and soaring fliers, to assess how flight morphology affects wind selectivity, both at fine scales (hourly movement steps) and across the breeding season. We found no general preference or avoidance of particular wind speeds within foraging tracks. This suggests seabird flight morphology is adapted to a "wind niche," with higher wing loading being selected in windier environments. In support of this, wing loading was positively related to the median wind speeds on the breeding grounds, as well as the maximum wind speeds in which birds flew. Yet globally, the highest wind speeds occur in the tropics (in association with tropical cyclones) where birds are morphologically adapted to low median wind speeds. Tropical species must therefore show behavioral responses to extreme winds, including long-range avoidance of wind speeds that can be twice their operable maxima. By contrast, Procellariiformes flew in almost all wind speeds they encountered at a seasonal scale. Despite this, we describe a small number of cases where albatrosses avoided strong winds at close range, including by flying into the eye of the storm. Extreme winds appear to pose context-dependent risks to seabirds, and more information is needed on the factors that determine the hierarchy of risk, given the impact of global change on storm intensity.6,7.

Navigating Storms: Examining Vultures’ Behavior in Response to Extreme Weather Events

Extreme weather events such as hurricanes and tornadoes have been found to change the spatial and temporal abundance of raptors by decreasing survival and forcing the emigration of individuals, or by increasing habitat heterogeneity and facilitating recolonization of disturbed areas. Nonetheless, little is known about how extreme weather events could affect raptors’ movements and their space use in areas disturbed by large-scale weather events. We studied how extreme weather affected the movements of black and turkey vultures (Coragyps atratus and Cathartes aura, respectively) in Mississippi, USA, facing Hurricane Zeta in November 2020, winter storm Viola in February 2021, and tornados MS-43 and MS-44 in May 2021. We GPS-tracked 28 vultures in the paths of these events. We compared movement rates, net-squared displacements, and use of forest cover, before, during, and after the events. Since storm avoidance behavior has been observed in other birds, we expected that vultures would shift their movements out of the path of these events before storms hit. Further, we forecasted that vultures would make greater use of forested areas as protection against harsh conditions such as strong winds and heavy rain. Vultures responded differently to each weather event; they shifted their movements out of the predicted path of the hurricane and tornadoes but not the snowstorm. These findings reveal that both species use avoidance behavior and adjust their navigation and hazard detection accordingly. Avoidance behavior was more pronounced in turkey vultures than in black vultures. In general, vultures did not make greater use of forest areas as we expected, but turkey vultures did select forest areas during the snowstorm. We propose that olfaction and audition may be key in vultures’ response to extreme weather events.

Joint use of location and acceleration data reveals influences on transitions among habitats in wintering birds

Quantifying relationships between animal behavior and habitat use is essential to understanding animal decision-making. High-resolution location and acceleration data allows unprecedented insights into animal movement and behavior. These data types allow researchers to study the complex linkages between behavioral plasticity and habitat distribution. We used a novel Markov model in a Bayesian framework to quantify the influence of behavioral state frequencies and environmental variables on transitions among landcover types through joint use of location and tri-axial accelerometer data. Data were collected from 56 greater white-fronted geese (Anser albifrons frontalis) across seven ecologically distinct winter regions over two years in midcontinent North America. We showed that goose decision-making varied across landcover types, ecoregions, and abiotic conditions, and was influenced by behavior. We found that time spent in specific behaviors explained variation in the probability of transitioning among habitats, revealing unique behavioral responses from geese among different habitats. Combining GPS and acceleration data allowed unique study of potential influences of an ongoing large-scale range shift in the wintering distribution of a migratory bird across midcontinent North America. We anticipate that behavioral adaptations among variable landscapes is a likely mechanism explaining goose use of highly variable ecosystems during winter in ways which optimize their persistence.

Coursing hyenas and stalking lions: The potential for inter- and intraspecific interactions

Resource partitioning promotes coexistence among guild members, and carnivores reduce interference competition through behavioral mechanisms that promote spatio-temporal separation. We analyzed sympatric lion and spotted hyena movements and activity patterns to ascertain the mechanisms facilitating their coexistence within semi-arid and wetland ecosystems. We identified recurrent high-use (revisitation) and extended stay (duration) areas within home ranges, as well as correlated movement-derived measures of inter- and intraspecific interactions with environmental variables. Spatial overlaps among lions and hyenas expanded during the wet season, and occurred at edges of home ranges, around water-points, along pathways between patches of high-use areas. Lions shared more of their home ranges with spotted hyenas in arid ecosystems, but shared more of their ranges with conspecifics in mesic environments. Despite shared space use, we found evidence for subtle temporal differences in the nocturnal movement and activity patterns between the two predators, suggesting a fine localized-scale avoidance strategy. Revisitation frequency and duration within home ranges were influenced by interspecific interactions, after land cover categories and diel cycles. Intraspecific interactions were also important for lions and, important for hyenas were moon illumination and ungulates attracted to former anthrax carcass sites in Etosha, with distance to water in Chobe/Linyanti. Recursion and duration according to locales of competitor probabilities were similar among female lions and both sexes of hyenas, but different for male lions. Our results suggest that lions and spotted hyenas mediate the potential for interference competition through subtle differences in temporal activity, fine-scale habitat use differentiation, and localized reactive-avoidance behaviors. These findings enhance our understanding of the potential effects of interspecific interactions among large carnivore space-use patterns within an apex predator system and show adaptability across heterogeneous and homogeneous environments. Future conservation plans should emphasize the importance of inter- and intraspecific competition within large carnivore communities, particularly moderating such effects within increasingly fragmented landscapes.

Land cover and NDVI are important predictors in habitat selection along migration for the Golden-crowned Sparrow, a temperate-zone migrating songbird

BACKGROUND

Migrating passerines in North America have shown sharp declines. Understanding habitat selection and threats along migration paths are critical research needs, but details about migrations have been limited due to the difficulty of tracking small birds. Recent technological advances of tiny GPS-tags provide new opportunities to delineate fine-scale movements in small passerines during a life stage that has previously been inherently difficult to study.

METHODS

We investigated habitat selection along migration routes for a temperate-zone migratory passerine, the Golden-crowned Sparrow (Zonotrichia atricapilla), given GPS tags on California wintering grounds. We used a resource selection function combined with conditional logistic regression to compare matched sets of known stopover locations and available but unused locations to determine how land cover class, vegetation greenness and climate variables influence habitat selection during migration. We also provide general migration descriptions for this understudied species including migration distance, duration, and elevation, and repeated use of stopover areas.

RESULTS

We acquired 22 tracks across 19 individuals, with a total of 541 valid spring and fall migration locations. Birds traveled to breeding grounds in Alaska and British Columbia along coastal routes, selecting for shrubland and higher vegetation greenness in both migration seasons as well as grasslands during fall migration. However, model interactions showed they selected sites with lower levels of greenness when in forest (both seasons) and shrubland (fall only), which may reflect their preference for more open habitats or represent a trade-off in selection between habitat type and productivity. Birds also selected for locations with higher daily maximum temperature during spring migration. Routes during spring migration were lower in elevation on average, shorter in duration, and had fewer long stopovers than in fall migration. For two birds, we found repeated use of the same stopover areas in spring and fall migration.

CONCLUSIONS

Using miniaturized GPS, this study provides new insight into habitat selection along migration routes for a common temperate-zone migrating songbird, contributing to a better understanding of full annual cycle models, and informing conservation efforts. Golden-crowned Sparrows selected for specific habitats along migration routes, and we found previously unknown behaviors such as repeated use of the same stopover areas by individuals across different migratory seasons.

How to scale up from animal movement decisions to spatiotemporal patterns: An approach via step selection

Uncovering the mechanisms behind animal space use patterns is of vital importance for predictive ecology, thus conservation and management of ecosystems. Movement is a core driver of those patterns so understanding how movement mechanisms give rise to space use patterns has become an increasingly active area of research. This study focuses on a particular strand of research in this area, based around step selection analysis (SSA). SSA is a popular way of inferring drivers of movement decisions, but, perhaps less well appreciated, it also parametrises a model of animal movement. Of key interest is that this model can be propagated forwards in time to predict the space use patterns over broader spatial and temporal scales than those that pertain to the proximate movement decisions of animals. Here, we provide a guide for understanding and using the various existing techniques for scaling up step selection models to predict broad-scale space use patterns. We give practical guidance on when to use which technique, as well as specific examples together with code in R and Python. By pulling together various disparate techniques into one place, and providing code and instructions in simple examples, we hope to highlight the importance of these techniques and make them accessible to a wider range of ecologists, ultimately helping expand the usefulness of SSA.

Dynamic winter weather moderates movement and resource selection of wild turkeys at high-latitude range limits

For wide-ranging species in temperate environments, populations at high-latitude range limits are subject to more extreme conditions, colder temperatures, and greater snow accumulation compared with their core range. As climate change progresses, these bounding pressures may become more moderate on average, while extreme weather occurs more frequently. Individuals can mitigate temporarily extreme conditions by changing daily activity budgets and exhibiting plasticity in resource selection, both of which facilitate existence at and expansion of high-latitude range boundaries. However, relatively little work has explored how animals moderate movement and vary resource selection with changing weather, and a general framework for such investigations is lacking. We applied hidden Markov models and step selection functions to GPS data from wintering wild turkeys (Meleagris gallopavo) near their northern range limit to identify how weather influenced transition among discrete movement states, as well as state-specific resource selection. We found that turkeys were more likely to spend time in a stationary state as wind chill temperatures decreased and snow depth increased. Both stationary and roosting turkeys selected conifer forests and avoided land covers associated with foraging, such as agriculture and residential areas, while shifting their strength of selection for these features during poor weather. In contrast, mobile turkeys showed relatively weak resource selection, with less response in selection coefficients during poor weather. Our findings illustrate that behavioral plasticity in response to weather was context dependent, but movement behaviors most associated with poor weather were also those in which resource selection was most plastic. Given our results, the potential for wild turkey range expansion will partly be determined by the availability of habitat that allows them to withstand periodic inclement weather. Combining hidden Markov models with step selection functions is broadly applicable for evaluating plasticity in animal behavior and dynamic resource selection in response to changing weather. We studied turkeys at northern range limits, but this approach is applicable for any system expected to experience significant changes in the coming decade, and may be particularly relevant to populations existing at range peripheries.

Using pseudo-absence models to test for environmental selection in marine movement ecology: the importance of sample size and selection strength

BACKGROUND

Understanding the selection of environmental conditions by animals requires knowledge of where they are, but also of where they could have been. Presence data can be accurately estimated by direct sampling, sightings, or through electronic tag deployments. However, absence data are harder to determine because absences are challenging to measure in an uncontrolled setting. To address this problem, ecologists have developed different methods for generating pseudo-absence data relying on theoretical movement models. These null models represent the movement of environmentally naive individuals, creating a set of locations that animals could have been if they were not exhibiting environmental selection.

METHODS

Here, we use four different kinds of null animal movement models-Brownian motion, Lévy walks, Correlated random walks, and Joint correlated random walks to test the ability and power of each of these null movement models to serve as appropriate animal absence models. We use Kolmogorov-Smirnov tests to detect environmental selection using two data sets, one of simulated animal tracks biased towards warmer sea surface temperatures, and one of 57 observed blue shark tracks of unknown sea surface temperature selection.

RESULTS

The four different types of movement models showed minimal difference in the ability to serve as appropriate null models for environmental selection studies. Selection strength and sample size were more important in detecting true environmental selection. We show that this method can suffer from high false positive rates, especially in the case where animals are not selecting for specific environments. We provide estimates of test accuracy at different sample sizes and selection strengths to avoid false positives when using this method.

CONCLUSION

We show how movement models can be used to generate pseudo-absences and test for habitat selection in marine organisms. While this approach efficiently detects environmental selection in marine organisms, it cannot detect the underlying mechanisms driving this selection.

Hide-and-Seek in a Highly Human-Dominated Landscape: Insights into Movement Patterns and Selection of Resting Sites of Rehabilitated Wolves (Canis lupus) in Northern Italy

Assessing the behavioural responses of floating wolves to human presence is crucial for investigating the chance of wolf populations expanding into urbanised landscapes. We studied the movement ecology of three rehabilitated wolves in a highly human-dominated landscape (Po Plain, Italy) to explore wolf's plasticity amid widespread human pressure. To reach this aim, we estimated individual 95% utilisation distributions (UD) after the release and inspected both 95% UDs and net squared displacements to identify individual movement patterns; tested for differences in movement patterns during day and night; and analysed the selection of resting sites during dispersal movement in a highly human-altered environment. Both the 95% UDs and step lengths were smaller for wolves settling in suitable areas than for those settling in more urbanised areas. All wolves exhibited strong temporal segregation with humans during all movement phases, particularly while dispersing across highly urbanised areas. Main roads and proximity to built-up areas were shown to limit wolves' dispersal, whereas small-wooded patches that provide shelter during rest facilitated long-distance movements. This study provides important insights into wolf movement and settling in urban and peri-urban areas, providing critical knowledge to promote human-carnivore coexistence.

Inferring spatially varying animal movement characteristics using a hierarchical continuous-time velocity model

Understanding the spatial dynamics of animal movement is an essential component of maintaining ecological connectivity, conserving key habitats, and mitigating the impacts of anthropogenic disturbance. Altered movement and migratory patterns are often an early warning sign of the effects of environmental disturbance, and a precursor to population declines. Here, we present a hierarchical Bayesian framework based on Gaussian processes for analysing the spatial characteristics of animal movement. At the heart of our approach is a novel covariance kernel that links the spatially varying parameters of a continuous-time velocity model with GPS locations from multiple individuals. We demonstrate the effectiveness of our framework by first applying it to a synthetic data set and then by analysing telemetry data from the Serengeti wildebeest migration. Through application of our approach, we are able to identify the key pathways of the wildebeest migration as well as revealing the impacts of environmental features on movement behaviour.

Movement and habitat selection of a large carnivore in response to human infrastructure differs by life stage

BACKGROUND

The movement extent of mammals is influenced by human-modified areas, which can affect population demographics. Understanding how human infrastructure influences movement at different life stages is important for wildlife management. This is true especially for large carnivores, due to their substantial space requirements and potential for conflict with humans.

METHODS

We investigated human impact on movement and habitat selection by GPS-collared male brown bears (Ursus arctos) in two life stages (residents and dispersers) in central Sweden. We identified dispersers visually based on their GPS locations and used hidden Markov models to delineate dispersal events. We used integrated step selection analysis (iSSA) to infer movement and habitat selection at a local scale (availability defined by hourly relocations), and resource selection functions (RSFs) to infer habitat selection at a landscape scale (availability defined by the study area extent).

RESULTS

Movement of residents on a local scale was facilitated by small forestry roads as they moved faster and selected areas closer to forestry roads, and they avoided areas closer to larger public roads and buildings on both scales. Dispersers were more ambivalent in their response to human infrastructure. Dispersers increased their speed closer to small forestry roads and larger public roads, did not exhibit selection for or against any road class, and avoided areas closer to buildings only at local scale. Dispersers did not select for any features on the landscape, which is likely explained by the novelty of the landscape or their naivety towards it.

CONCLUSION

Our results show that movement in male brown bears is life stage-dependent and indicate that connectivity maps derived from movement data of dispersing animals may provide more numerous and more realistic pathways than those derived from resident animal data alone. This suggests that data from dispersing animals provide more realistic models for reconnecting populations and maintaining connectivity than if data were derived from resident animals alone.

Agricultural land use shapes dispersal in white-tailed deer (Odocoileus virginianus)

BACKGROUND

Dispersal is a fundamental process to animal population dynamics and gene flow. In white-tailed deer (WTD; Odocoileus virginianus), dispersal also presents an increasingly relevant risk for the spread of infectious diseases. Across their wide range, WTD dispersal is believed to be driven by a suite of landscape and host behavioral factors, but these can vary by region, season, and sex. Our objectives were to (1) identify dispersal events in Wisconsin WTD and determine drivers of dispersal rates and distances, and (2) determine how landscape features (e.g., rivers, roads) structure deer dispersal paths.

METHODS

We developed an algorithmic approach to detect dispersal events from GPS collar data for 590 juvenile, yearling, and adult WTD. We used statistical models to identify host and landscape drivers of dispersal rates and distances, including the role of agricultural land use, the traversability of the landscape, and potential interactions between deer. We then performed a step selection analysis to determine how landscape features such as agricultural land use, elevation, rivers, and roads affected deer dispersal paths.

RESULTS

Dispersal predominantly occurred in juvenile males, of which 64.2% dispersed, with dispersal events uncommon in other sex and age classes. Juvenile male dispersal probability was positively associated with the proportion of the natal range that was classified as agricultural land use, but only during the spring. Dispersal distances were typically short (median 5.77 km, range: 1.3-68.3 km), especially in the fall. Further, dispersal distances were positively associated with agricultural land use in potential dispersal paths but negatively associated with the number of proximate deer in the natal range. Lastly, we found that, during dispersal, juvenile males typically avoided agricultural land use but selected for areas near rivers and streams.

CONCLUSION

Land use-particularly agricultural-was a key driver of dispersal rates, distances, and paths in Wisconsin WTD. In addition, our results support the importance of deer social environments in shaping dispersal behavior. Our findings reinforce knowledge of dispersal ecology in WTD and how landscape factors-including major rivers, roads, and land-use patterns-structure host gene flow and potential pathogen transmission.

Integrated animal movement and spatial capture-recapture models: Simulation, implementation, and inference

Over the last decade, spatial capture-recapture (SCR) models have become widespread for estimating demographic parameters in ecological studies. However, the underlying assumptions about animal movement and space use are often not realistic. This is a missed opportunity because interesting ecological questions related to animal space use, habitat selection, and behavior cannot be addressed with most SCR models, despite the fact that the data collected in SCR studies - individual animals observed at specific locations and times - can provide a rich source of information about these processes and how they relate to demographic rates. We developed SCR models that integrated more complex movement processes that are typically inferred from telemetry data, including a simple random walk, correlated random walk (i.e., short-term directional persistence), and habitat-driven Langevin diffusion. We demonstrated how to formulate, simulate from, and fit these models with standard SCR data using data-augmented Bayesian analysis methods. We evaluated their performance through a simulation study, in which we varied the detection, movement, and resource selection parameters. We also examined different numbers of sampling occasions and assessed performance gains when including auxiliary location data collected from telemetered individuals. Across all scenarios, the integrated SCR movement models performed well in terms of abundance, detection, and movement parameter estimation. We found little difference in bias for the simple random walk model when reducing the number of sampling occasions from T = 25 to T = 15. We found some bias in movement parameter estimates under several of the correlated random walk scenarios, but incorporating auxiliary location data improved parameter estimates and significantly improved mixing during model fitting. The Langevin movement model was able to recover resource selection parameters from standard SCR data, which is particularly appealing because it explicitly links the individual-level movement process with habitat selection and population density. We focused on closed population models, but the movement models developed here can be extended to open SCR models. The movement process models could also be easily extended to accommodate additional "building blocks" of random walks, such as central tendency (e.g., territoriality) or multiple movement behavior states, thereby providing a flexible and coherent framework for linking animal movement behavior to population dynamics, density, and distribution.

An integrated path for spatial capture-recapture and animal movement modeling

Ecologists and conservation biologists increasingly rely on spatial capture-recapture (SCR) and movement modeling to study animal populations. Historically, SCR has focused on population-level processes (e.g., vital rates, abundance, density, and distribution), whereas animal movement modeling has focused on the behavior of individuals (e.g., activity budgets, resource selection, migration). Even though animal movement is clearly a driver of population-level patterns and dynamics, technical and conceptual developments to date have not forged a firm link between the two fields. Instead, movement modeling has typically focused on the individual level without providing a coherent scaling from individual- to population-level processes, whereas SCR has typically focused on the population level while greatly simplifying the movement processes that give rise to the observations underlying these models. In our view, the integration of SCR and animal movement modeling has tremendous potential for allowing ecologists to scale up from individuals to populations and advancing the types of inferences that can be made at the intersection of population, movement, and landscape ecology. Properly accounting for complex animal movement processes can also potentially reduce bias in estimators of population-level parameters, thereby improving inferences that are critical for species conservation and management. This introductory article to the Special Feature reviews recent advances in SCR and animal movement modeling, establishes a common notation, highlights potential advantages of linking individual-level (Lagrangian) movements to population-level (Eulerian) processes, and outlines a general conceptual framework for the integration of movement and SCR models. We then identify important avenues for future research, including key challenges and potential pitfalls in the developments and applications that lie ahead.

On the move: spatial ecology and habitat use of red fox in the Trans-Himalayan cold desert

Red fox (Vulpes vulpes) is the most widespread wild carnivore globally, occupying diverse habitats. The species is known for its adaptability to survive in dynamic anthropogenic landscapes. Despite being one of the most extensively studied carnivores, there is a dearth of information on red fox from the Trans-Himalayan region. We studied the home range sizes of red fox using the different estimation methods: minimum convex polygon (MCP), kernel density estimator (KDE), local convex hull (LoCoH) and Brownian-bridge movement model (BBMM). We analysed the daily movement and assessed the habitat selection with respect to topographic factors (ruggedness, elevation and slope), environmental factor (distance to water) and anthropogenic factors (distance to road and human settlements). We captured and GPS-collared six red fox individuals (three males and three females) from Chiktan and one female from Hemis National Park, Ladakh, India. The collars were programmed to record GPS fixes every 15-min. The average BBMM home range estimate (95% contour) was 22.40 ± 12.12 SD km² (range 3.81-32.93 km²) and the average core area (50% contour) was 1.87 ± 0.86 SD km² (range 0.55-2.69 km²). The estimated average daily movement of red fox was 17.76 ± 8.45 SD km/d (range 10.91-34.22 km/d). Red fox significantly selected lower elevations with less rugged terrain and were positively associated with water. This is the first study in the Trans-Himalayan landscape which aims to understand the daily movement of red fox at a fine temporal scale. Studying the movement and home range sizes helps understand the daily energetics and nutritional requirements of red fox. Movement information of a species is important for the prioritisation of areas for conservation and can aid in understanding ecosystem functioning and landscape management.

Pathways for avian influenza virus spread: GPS reveals wild waterfowl in commercial livestock facilities and connectivity with the natural wetland landscape

Zoonotic diseases are of considerable concern to the human population and viruses such as avian influenza (AIV) threaten food security, wildlife conservation and human health. Wild waterfowl and the natural wetlands they use are known AIV reservoirs, with birds capable of virus transmission to domestic poultry populations. While infection risk models have linked migration routes and AIV outbreaks, there is a limited understanding of wild waterfowl presence on commercial livestock facilities, and movement patterns linked to natural wetlands. We documented 11 wild waterfowl (three Anatidae species) in or near eight commercial livestock facilities in Washington and California with GPS telemetry data. Wild ducks used dairy and beef cattle feed lots and facility retention ponds during both day and night suggesting use for roosting and foraging. Two individuals (single locations) were observed inside poultry facility boundaries while using nearby wetlands. Ducks demonstrated high site fidelity, returning to the same areas of habitats (at livestock facilities and nearby wetlands), across months or years, showed strong connectivity with surrounding wetlands, and arrived from wetlands up to 1251 km away in the week prior. Telemetry data provides substantial advantages over observational data, allowing assessment of individual movement behaviour and wetland connectivity that has significant implications for outbreak management. Telemetry improves our understanding of risk factors for waterfowl-livestock virus transmission and helps identify factors associated with coincident space use at the wild waterfowl-domestic livestock interface. Our research suggests that even relatively small or isolated natural and artificial water or food sources in/near facilities increases the likelihood of attracting waterfowl, which has important consequences for managers attempting to minimize or prevent AIV outbreaks. Use and interpretation of telemetry data, especially in near-real-time, could provide key information for reducing virus transmission risk between waterfowl and livestock, improving protective barriers between wild and domestic species, and abating outbreaks.

Precipitation, vegetation productivity, and human impacts control home range size of elephants in dryland systems in northern Namibia

Climatic variability, resource availability, and anthropogenic impacts heavily influence an animal's home range. This makes home range size an effective metric for understanding how variation in environmental factors alter the behavior and spatial distribution of animals. In this study, we estimated home range size of African elephants (Loxodonta africana) across four sites in Namibia, along a gradient of precipitation and human impact, and investigated how these gradients influence the home range size on regional and site scales. Additionally, we estimated the time individuals spent within protected area boundaries. The mean 50% autocorrelated kernel density estimate for home range was 2200 km² [95% CI:1500–3100 km²]. Regionally, precipitation and vegetation were the strongest predictors of home range size, accounting for a combined 53% of observed variation. However, different environmental covariates explained home range variation at each site. Precipitation predicted most variation (up to 74%) in home range sizes (n = 66) in the drier western sites, while human impacts explained 71% of the variation in home range sizes (n = 10) in Namibia's portion of the Kavango‐Zambezi Transfrontier Conservation Area. Elephants in all study areas maintained high fidelity to protected areas, spending an average of 85% of time tracked on protected lands. These results suggest that while most elephant space use in Namibia is driven by natural dynamics, some elephants are experiencing changes in space use due to human modification.

Is it the road or the fence? Influence of linear anthropogenic features on the movement and distribution of a partially migratory ungulate

BACKGROUND

Anthropogenic linear features change the behavior and selection patterns of species, which must adapt to these ever-increasing features on the landscape. Roads are a well-studied linear feature that alter the survival, movement, and distribution of animals. Less understood are the effects of fences on wildlife, though they tend to be more ubiquitous across the landscape than roads. Even less understood are potential indirect effects when fences are found in tandem with roads along transportation corridors.

METHODS

We assessed how the spatial configuration of fences and roads effect the movement (crossing effect) and distribution (proximity effect) of a partially migratory pronghorn population (Antilocapra americana) on the grasslands of southern Alberta, Canada. We used data from 55 collared pronghorn within a step-selection function framework to assess the influence of 4 linear features: (1) pasture fences, (2) roads not fenced, (3) roads fenced on one side, and (4) roads fenced on both sides on the selection pattern of migratory and resident animals. We examined whether steps along a movement pathway (i.e., crossing effect) were influenced by the type of linear feature animals attempted to cross and, whether these features affected the distribution of pronghorn (i.e., proximity effect) across the landscape.

RESULTS

The top model for crossing effect for both movement tactics contained all 4 linear features and land cover. Regression coefficients were negative for all linear features, indicating that individuals were less likely to chose steps that crossed linear features. For the proximity effect, migrant animals avoided all linear features except roads fenced on both sides, where they selected areas closer to this feature. Resident animals, on the other hand, were found closer to pasture fences but further from roads without fences.

CONCLUSIONS

Our results indicate that both fences and roads are indirectly affecting pronghorn resource use spatially and behaviorally, whether each linear feature is found separately or in tandem. Modifying existing fences and roads to account for responses to these distinct linear features could facilitate more successful crossing opportunities and/or shifts in distribution. Allowing pronghorn to freely move across the landscape will maintain functional connectivity to ensure population persistence of this endemic ungulate.