A 'How to' guide for interpreting parameters in habitat-selection analyses

Habitat and movement selection processes of American lobster/jakej within a restricted bay in the Bras d'Or Lake/Pitu'paq, Nova Scotia, Canada

American lobster inhabit the unique, brackish Bras d'Or Lake system, although densities are low compared to areas with similar habitats in the Atlantic Ocean. Nevertheless, lobsters are an important part of local First Nation (Mi'kmaq) food and culture. We used acoustic telemetry and habitat mapping, combined with local Mi'kmaw knowledge, to document the movements and habitat use of adult lobsters within a section of the Lake. Movement patterns of acoustically tagged individual lobsters were analyzed with both resource selection functions and integrated step selection functions using data obtained from a high-resolution VEMCO Positioning System within a restricted bay in the Bras d'Or Lake. The resource selection function suggested stronger selections of substrates that contained a combination of soft and hard sediments. While the integrated step selection functions found substantial individual variability in habitat selections, there was a trend for lobsters to exhibit more resident behaviour on the combined soft/hard substrates despite the fact these sediments provided little in the way of obvious shelters for the animals. Adult lobsters at this site have very little risk of predation, which presumably allows them to freely exhibit exploratory behaviours and reduce their association with substrates that provide shelters.

Boundary Spanning Methodological Approaches for Collaborative Moose Governance in Eeyou Istchee

Natural resource governance challenges are often highly complex, particularly in Indigenous contexts. These challenges involve numerous landscape-level interactions, spanning jurisdictional, disciplinary, social, and ecological boundaries. In Eeyou Istchee, the James Bay Cree Territory of northern Quebec, Canada, traditional livelihoods depend on wild food species like moose. However, these species are increasingly being impacted by forestry and other resource development projects. The complex relationships between moose, resource development, and Cree livelihoods can limit shared understandings and the ability of diverse actors to respond to these pressures. Contributing to this complexity are the different knowledge systems held by governance actors who, while not always aligned, have broadly shared species conservation and sustainable development goals. This paper presents fuzzy cognitive mapping (FCM) as a methodological approach used to help elicit and interpret the knowledge of land-users concerning the impacts of forest management on moose habitat in Eeyou Istchee. We explore the difficulties of weaving this knowledge together with the results of moose GPS collar analysis and the knowledges of scientists and government agencies. The ways in which participatory, relational mapping approaches can be applied in practice, and what they offer to pluralistic natural resource governance research more widely, are then addressed.

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).

Associations between glucocorticoids and habitat selection reflect daily and seasonal energy requirements

BACKGROUND

Glucocorticoids are often associated with stressful environments, but they are also thought to drive the best strategies to improve fitness in stressful environments. Glucocorticoids improve fitness in part by regulating foraging behaviours in response to daily and seasonal energy requirements. However, many studies demonstrating relationships between foraging behaviour and glucocorticoids are experimental, and few observational studies conducted under natural conditions have tested whether changing glucocorticoid levels are related to daily and seasonal changes in energy requirements.

METHODS

We integrated glucocorticoids into habitat selection models to test for relationships between foraging behaviour and glucocorticoid levels in elk (Cervus canadensis) as their daily and seasonal energy requirements changed. Using integrated step selection analysis, we tested whether elevated glucocorticoid levels were related to foraging habitat selection on a daily scale and whether that relationship became stronger during lactation, one of the greatest seasonal periods of energy requirement for female mammals.

RESULTS

We found stronger selection of foraging habitat by female elk with elevated glucocorticoids (eß = 1.44 95% CI 1.01, 2.04). We found no difference in overall glucocorticoid levels after calving, nor a significant change in the relationship between glucocorticoids and foraging habitat selection at the time of calving. However, we found a gradual increase in the relationship between glucocorticoids and habitat selection by female elk as their calves grew over the next few months (eß = 1.01, 95% CI 1.00, 1.02), suggesting a potentially stronger physiological effect of glucocorticoids for elk with increasing energy requirements.

CONCLUSIONS

We suggest glucocorticoid-integrated habitat selection models demonstrate the role of glucocorticoids in regulating foraging responses to daily and seasonal energy requirements. Ultimately, this integration will help elucidate the implications of elevated glucocorticoids under natural conditions.

Hunting mode and habitat selection mediate the success of human hunters

BACKGROUND

As a globally widespread apex predator, humans have unprecedented lethal and non-lethal effects on prey populations and ecosystems. Yet compared to non-human predators, little is known about the movement ecology of human hunters, including how hunting behavior interacts with the environment.

METHODS

We characterized the hunting modes, habitat selection, and harvest success of 483 rifle hunters in California using high-resolution GPS data. We used Hidden Markov Models to characterize fine-scale movement behavior, and k-means clustering to group hunters by hunting mode, on the basis of their time spent in each behavioral state. Finally, we used Resource Selection Functions to quantify patterns of habitat selection for successful and unsuccessful hunters of each hunting mode.

RESULTS

Hunters exhibited three distinct and successful hunting modes ("coursing", "stalking", and "sit-and-wait"), with coursings as the most successful strategy. Across hunting modes, there was variation in patterns of selection for roads, topography, and habitat cover, with differences in habitat use of successful and unsuccessful hunters across modes.

CONCLUSIONS

Our study indicates that hunters can successfully employ a diversity of harvest strategies, and that hunting success is mediated by the interacting effects of hunting mode and landscape features. Such results highlight the breadth of human hunting modes, even within a single hunting technique, and lend insight into the varied ways that humans exert predation pressure on wildlife.

Effects of large-scale gold mining on habitat use and selection by American pronghorn

Anthropogenic disturbances, including extraction of natural resources and development of alternative energy, are reducing and fragmenting habitat for wildlife across the globe. Effects of those disturbances have been explored by studying populations that migrate through oil and gas fields or alternative energy facilities. Extraction of minerals, including precious metals and lithium, is increasing rapidly in remote areas, which results in dramatically altered landscapes in areas of resident populations of wildlife. Our goal was to examine how a resident population of American pronghorn (Antilocapra americana) in the Great Basin ecosystem selected resources near a large-scale disturbance year around. We investigated how individuals selected resources around a large, open-pit gold mine. We classified levels of disturbance associated with the mine, and used a random forest model to select ecological covariates associated with habitat selection by pronghorn. We used resource selection functions to examine how disturbances affected habitat selection by pronghorn both annually and seasonally. Pronghorn strongly avoided areas of high disturbance, which included open pits, heap leach fields, rock disposal areas, and a tram. Pronghorn selected areas near roads, although selection was strongest about 2 km away. We observed relatively broad variation among individuals in selection of resources, and how they responded to the mine. The Great Basin is a mineral-rich area that continues to be exploited for natural resources, especially minerals. Sagebrush-dependent species, including pronghorn, that rely on this critical habitat were directly affected by that transformation of the landscape, which is likely to increase with expansion of the mine. As extraction of minerals from remote landscapes around the world continues to fragment habitats for wildlife, increasing our understanding of impacts of those changes on behaviors of wildlife before populations decline, may assist in the mitigation and minimization of negative impacts on mineral-rich landscapes and on wildlife populations.

Spatial prey availability and pulsed reproductive tactics: Encounter risk in a canid-ungulate system

Predation risk is a function of spatiotemporal overlap between predator and prey, as well as behavioural responses during encounters. Dynamic factors (e.g. group size, prey availability and animal movement or state) affect risk, but rarely are integrated in risk assessments. Our work targets a system where predation risk is fundamentally linked to temporal patterns in prey abundance and behaviour. For neonatal ungulate prey, risk is defined within a short temporal window during which the pulse in parturition, increasing movement capacity with age and antipredation tactics have the potential to mediate risk. In our coyote-mule deer (Canis latrans-Odocoileus hemionus) system, leveraging GPS data collected from both predator and prey, we tested expectations of shared enemy and reproductive risk hypotheses. We asked two questions regarding risk: (A) How does primary and alternative prey habitat, predator and prey activity, and reproductive tactics (e.g. birth synchrony and maternal defence) influence the vulnerability of a neonate encountering a predator? (B) How do the same factors affect behaviour by predators relative to the time before and after an encounter? Despite increased selection for mule deer and intensified search behaviour by coyotes during the peak in mule deer parturition, mule deer were afforded protection from predation via predator swamping, experiencing reduced per-capita encounter risk when most neonates were born. Mule deer occupying rabbit habitat (Sylvilagus spp.; coyote's primary prey) experienced the greatest risk of encounter but the availability of rabbit habitat did not affect predator behaviour during encounters. Encounter risk increased in areas with greater availability of mule deer habitat: coyotes shifted their behaviour relative to deer habitat, and the pulse in mule deer parturition and movement of neonatal deer during encounters elicited increased speed and tortuosity by coyotes. In addition to the spatial distribution of prey, temporal patterns in prey availability and animal behavioural state were fundamental in defining risk. Our work reveals the nuanced consequences of pulsed availability on predation risk for alternative prey, whereby responses by predators to sudden resource availability, the lasting effects of diversionary prey and inherent antipredation tactics ultimately dictate risk.

Human access constrains optimal foraging and habitat availability in an avian generalist

Animals balance costs of antipredator behaviors with resource acquisition to minimize hunting and other mortality risks and maximize their physiological condition. This inherent trade-off between forage abundance, its quality, and mortality risk is intensified in human-dominated landscapes because fragmentation, habitat loss, and degradation of natural vegetation communities is often coupled with artificially enhanced vegetation (i.e., food plots), creating high-risk, high-reward resource selection decisions. Our goal was to evaluate autumn-winter resource selection trade-offs for an intensively hunted avian generalist. We hypothesized human access was a reliable cue for hunting predation risk. Therefore, we predicted resource selection patterns would be spatiotemporally dependent upon levels of access and associated perceived risk. Specifically, we evaluated resource selection of local-scale flights between diel periods for 426 mallards (Anas platyrhynchos) relative to wetland type, forage quality, and differing levels of human access across hunting and nonhunting seasons. Mallards selected areas that prohibited human access and generally avoided areas that allowed access diurnally, especially during the hunting season. Mallards compensated by selecting for high-energy and greater quality foraging patches on allowable human access areas nocturnally when they were devoid of hunters. Postseason selection across human access gradients did not return to prehunting levels immediately, perhaps suggesting a delayed response to reacclimate to nonhunted activities and thus agreeing with the assessment mismatch hypothesis. Last, wetland availability and human access constrained selection for optimal natural forage quality (i.e., seed biomass and forage productivity) diurnally during preseason and hunting season, respectively; however, mallards were freed from these constraints nocturnally during hunting season and postseason periods. Our results suggest risk-avoidance of human accessible (i.e., hunted) areas is a primary driver of resource selection behaviors by mallards and could be a local to landscape-level process influencing distributions, instead of forage abundance and quality, which has long-been assumed by waterfowl conservation planners in North America. Broadly, even an avian generalist, well adapted to anthropogenic landscapes, avoids areas where hunting and human access are allowed. Future conservation planning and implementation must consider management for recreational access (i.e., people) equally important as foraging habitat management for wintering waterfowl.

Home range size and habitat selection of owned outdoor domestic cats (Felis catus) in urban southwestern Ontario

Domestic cats (Felis catus) play a dual role in society as both companion animals and predators. When provided with unsupervised outdoor access, cats can negatively impact native wildlife and create public health and animal welfare challenges. The effective implementation of management strategies, such as buffer zones or curfews, requires an understanding of home range size, the factors that influence their movement, and the types of habitats they use. Here, we used a community/citizen scientist approach to collect movement and habitat use data using GPS collars on owned outdoor cats in the Kitchener-Waterloo-Cambridge-Guelph region, southwestern Ontario, Canada. Mean (± SD) 100% minimum convex polygon home range size was 8 ± 8 ha (range: 0.34-38 ha) and was positively associated with road density but not with intrinsic factors such as boldness, sex, or age. With regards to habitat selection, cats used greenspaces, roads, and agricultural land less often than predicted but strongly selected for impervious surfaces (urban areas other than greenspaces or roads). Our results suggest that wildlife near buildings and residential areas are likely at the greatest risk of cat predation and that a buffer size of 840 m would be needed to restrict cats from entering areas of conservation concern.

Agricultural habitat use and selection by a sedentary bird over its annual life cycle in a crop-depredation context

BACKGROUND

Modern agriculture has undoubtedly led to increasing wildlife-human conflicts, notably concerning bird damage in productive and attractive crops during some parts of the annual cycle. This issue requires utmost attention for sedentary birds that may impact agricultural crops at any stage of their annual life cycle. Reducing bird-human conflicts requires a better understanding of the relationship between bird foraging activity and the characteristics of agricultural areas, notably with respect to changes in food-resource availability and crop sensitivity across the year.

METHODS

We explored how GPS-tagged adult male western jackdaws- sedentary corvids- utilize agricultural areas throughout their annual cycle, in a context of crop depredation. More precisely, we described their daily occurrence distribution and the extent of habitat use and selection consistency with respect to landscape composition across time.

RESULTS

Jackdaws moved in the close agricultural surroundings of their urban nesting place over the year (< 2.5 km from the nest, on average). Daily occurrence distributions were restricted (< 2.2 km2), relatively centered on the nesting locality (distance between the daily occurrence centroid and the nest < 0.9 km), and rather spatially stable during each annual life-cycle period (overlap range: 63.4-76.1%). Their foraging patterns highlighted that they fed mainly in grasslands all year round, and foraged complementarily and opportunistically in maize (during sowing- coinciding with the first stages of the birds' breeding period) and cereal crops (during harvesting- their post-fledging period).

CONCLUSIONS

Our findings demonstrate the very limited space use by breeding male jackdaws which foraged preferentially in grasslands. We call for future investigations in other agricultural contexts and also considering non-breeders for extrapolation purposes.

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.

How to account for behavioral states in step-selection analysis: a model comparison

Step-selection models are widely used to study animals' fine-scale habitat selection based on movement data. Resource preferences and movement patterns, however, often depend on the animal's unobserved behavioral states, such as resting or foraging. As this is ignored in standard (integrated) step-selection analyses (SSA, iSSA), different approaches have emerged to account for such states in the analysis. The performance of these approaches and the consequences of ignoring the states in step-selection analysis, however, have rarely been quantified. We evaluate the recent idea of combining iSSAs with hidden Markov models (HMMs), which allows for a joint estimation of the unobserved behavioral states and the associated state-dependent habitat selection. Besides theoretical considerations, we use an extensive simulation study and a case study on fine-scale interactions of simultaneously tracked bank voles (Myodes glareolus) to compare this HMM-iSSA empirically to both the standard and a widely used classification-based iSSA (i.e., a two-step approach based on a separate prior state classification). Moreover, to facilitate its use, we implemented the basic HMM-iSSA approach in the R package HMMiSSA available on GitHub.

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.

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.

Habitat visibility affects the behavioral response of a large herbivore to human disturbance in forest landscapes

Wildlife can perceive humans as predators and human disturbance, whether lethal (e.g., hunting) or non-lethal (e.g., hiking, biking, and skiing), triggers antipredator behavior among prey. Visibility is the property that relates habitat structure to accessibility of visual information that allows animals to detect predators and evaluate predation risk. Thus, the visibility of a habitat (hereafter referred to as habitat visibility) for prey species alters the perceived risk of predation and therefore has a strong influence on their antipredator behavior. Yet, knowledge of how habitat visibility affects the response of animals to different types of human disturbance is limited, partly, because it is challenging to measure habitat visibility for animals at a fine spatial scale over a landscape, particularly in highly heterogeneous landscapes (e.g., forests). In this study, we employed a newly described approach that combines terrestrial and airborne LiDAR to contiguously measure fine-scale habitat visibility in a forested landscape. We applied the LiDAR-derived habitat visibility to examine how habitat visibility in forests affects the summer space use of 20 GPS-collared female red deer (Cervus elaphus) modeled with integrated step-selection functions in the Bavarian Forest National Park, Germany when exposed to various types of human disturbance including recreational activities, forest roads, hiking trails, and hunting. We found that red deer in our study area avoided areas with higher all types of human disturbance, especially during daylight hours. Furthermore, habitat visibility significantly modified the use of space by red deer in response to human recreational activities, forest roads, and hiking trails, but not to the hunting area. Red deer tended to tolerate a higher intensity of human recreational activities and to use areas closer to forest roads or hiking trails when they have lower habitat visibility (i.e., more cover). Our findings highlight the importance of considering visual perception when studying the response of wild animals to human disturbance. We emphasize the potential to mitigate negative consequences of human disturbance on wildlife, through measures such as maintaining vegetative buffers around recreational infrastructure (e.g., roads and skiing tracks) in order to reduce habitat visibility around areas frequented by humans.

The method matters. A comparative study of biologging and camera traps as data sources with which to describe wildlife habitat selection

Habitat use is a virtually universal activity among animals and is highly relevant as regards designing wildlife management and conservation actions. This has led to the development of a great variety of methods to study it, of which resource selection functions combined with biologging-derived data (RSF) is the most widely used for this purpose. However this approach has some constraints, such as its invasiveness and high costs. Analytical approaches taking into consideration imperfect detection coupled with camera trap data (IDM) have, therefore, emerged as a non-invasive cost-effective alternative. However, despite the fact that both approaches (RSF and IDM) have been used in habitat selection studies, they should also be comparatively assessed. The objective of this work is consequently to assess them from two perspectives: explanatory and predictive. This has been done by analyzing data obtained from camera traps (60 sampling sites) and biologging (17 animals monitored: 7 red deer Cervus elaphus, 6 fallow deer Dama dama and 4 wild boar Sus scrofa) in the same periods using IDM and RSF, respectively, in Doñana National Park (southern Spain) in order to explain and predict habitat use patterns for three studied species. Our results showed discrepancies between the two approaches, as they identified different predictors as being the most relevant to determine species intensity of use, and they predicted spatial patterns of habitat use with a contrasted level of concordance, depending on species and scale. Given these results and the characteristics of each approach, we suggested that although partly comparable interpretations can be obtained with both approaches, they are not equivalent but rather complementary. The combination of data from biologging and camera traps would, therefore, appear to be suitable for the development of an analytical framework with which to describe and characterise the habitat use processes of wildlife.

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.

Logging, linear features, and human infrastructure shape the spatial dynamics of wolf predation on an ungulate neonate

Humans are increasingly recognized as important players in predator-prey dynamics by modifying landscapes. This trend has been well-documented for large mammal communities in North American boreal forests: logging creates early seral forests that benefit ungulates such as white-tailed deer (Odocoileus virginianus), while the combination of infrastructure development and resource extraction practices generate linear features that allow predators such as wolves (Canis lupus) to travel and forage more efficiently throughout the landscape. Disturbances from recreational activities and residential development are other major sources of human activity in boreal ecosystems that may further alter wolf-ungulate dynamics. Here, we evaluate the influence that several major types of anthropogenic landscape modifications (timber harvest, linear features, and residential infrastructure) have on where and how wolves hunt ungulate neonates in a southern boreal forest ecosystem in Minnesota, USA. We demonstrate that each major anthropogenic disturbance significantly influences wolf predation of white-tailed deer fawns (n = 427 kill sites). In contrast with the "human shield hypothesis" that posits prey use human-modified areas as refuge, wolves killed fawns closer to residential buildings than expected based on spatial availability. Fawns were also killed within recently-logged areas more than expected. Concealment cover was higher at kill sites than random sites, suggesting wolves use senses other than vision, probably olfaction, to detect hidden fawns. Wolves showed strong selection for hunting along linear features, and kill sites were also closer to linear features than expected. We hypothesize that linear features facilitated wolf predation on fawns by allowing wolves to travel efficiently among high-quality prey patches (recently logged areas, near buildings), and also increase encounter rates with olfactory cues that allow them to detect hidden fawns. These findings provide novel insight into the strategies predators use to hunt ungulate neonates and the many ways human activity alters wolf-ungulate neonate predator-prey dynamics, which have remained elusive due to the challenges of locating sites where predators kill small prey. Our research has important management and conservation implications for wolf-ungulate systems subjected to anthropogenic pressures, particularly as the range of overlap between wolves and deer expands and appears to be altering food web dynamics in boreal ecosystems.

The Joint Evolution of Animal Movement and Competition Strategies

AbstractCompetition typically takes place in a spatial context, but eco-evolutionary models rarely address the joint evolution of movement and competition strategies. Here we investigate a spatially explicit forager-kleptoparasite model where consumers can either forage on a heterogeneous resource landscape or steal resource items from conspecifics (kleptoparasitism). We consider three scenarios: (1) foragers without kleptoparasites, (2) consumers specializing as foragers or as kleptoparasites, and (3) consumers that can switch between foraging and kleptoparasitism depending on local conditions. We model movement strategies as individual-specific combinations of preferences for environmental cues, similar to step-selection coefficients. Using mechanistic, individual-based simulations, we study the joint evolution of movement and competition strategies, and we investigate the implications for the distribution of consumers over this landscape. Movement and competition strategies evolve rapidly and consistently across scenarios, with marked differences among scenarios, leading to differences in resource exploitation patterns. In scenario 1, foragers evolve considerable individual variation in movement strategies, while in scenario 2, movement strategies show a swift divergence between foragers and kleptoparasites. In scenario 3, where individuals' competition strategies are conditional on local cues, movement strategies facilitate kleptoparasitism, and individual consistency in competition strategy also emerges. Even in the absence of kleptoparasitism (scenario 1), the distribution of consumers deviates considerably from predictions of ideal free distribution models because of the intrinsic difficulty of moving effectively on a depleted resource landscape with few reliable cues. Our study emphasizes the advantages of a mechanistic approach when studying competition in a spatial context and suggests how evolutionary modeling can be integrated with current work in animal movement ecology.

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.

Novel pathogen introduction triggers rapid evolution in animal social movement strategies

Animal sociality emerges from individual decisions on how to balance the costs and benefits of being sociable. Novel pathogens introduced into wildlife populations should increase the costs of sociality, selecting against gregariousness. Using an individual-based model that captures essential features of pathogen transmission among social hosts, we show how novel pathogen introduction provokes the rapid evolutionary emergence and coexistence of distinct social movement strategies. These strategies differ in how they trade the benefits of social information against the risk of infection. Overall, pathogen-risk-adapted populations move more and have fewer associations with other individuals than their pathogen-risk-naive ancestors, reducing disease spread. Host evolution to be less social can be sufficient to cause a pathogen to be eliminated from a population, which is followed by a rapid recovery in social tendency. Our conceptual model is broadly applicable to a wide range of potential host-pathogen introductions and offers initial predictions for the eco-evolutionary consequences of wildlife pathogen spillover scenarios and a template for the development of theory in the ecology and evolution of animals' movement decisions.

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.

Death comes for us all: relating movement-integrated habitat selection and social behavior to human-associated and disease-related mortality among gray wolves

Avoiding death affects biological processes, including behavior. Habitat selection, movement, and sociality are highly flexible behaviors that influence the mortality risks and subsequent fitness of individuals. In the Anthropocene, animals are experiencing increased risks from direct human causes and increased spread of infectious diseases. Using integrated step selection analysis, we tested how the habitat selection, movement, and social behaviors of gray wolves vary in the two months prior to death due to humans (being shot or trapped) or canine distemper virus (CDV). We further tested how those behaviors vary as a prelude to death. We studied populations of wolves that occurred under two different management schemes: a national park managed for conservation and a provincially managed multi-use area. Behaviors that changed prior to death were strongly related to how an animal eventually died. Wolves killed by humans moved slower than wolves that survived and selected to be nearer roads closer in time to their death. Wolves that died due to CDV moved progressively slower as they neared death and reduced their avoidance of wet habitats. All animals, regardless of dying or living, maintained selection to be near packmates across time, which seemingly contributed to disease dynamics in the packs infected with CDV. There were no noticeable differences in behavior between the two management areas. Overall, habitat selection, movement, and sociality interact to put individuals and groups at greater risks, influencing their cause-specific mortality.

Flexible hidden Markov models for behaviour-dependent habitat selection

BACKGROUND

There is strong incentive to model behaviour-dependent habitat selection, as this can help delineate critical habitats for important life processes and reduce bias in model parameters. For this purpose, a two-stage modelling approach is often taken: (i) classify behaviours with a hidden Markov model (HMM), and (ii) fit a step selection function (SSF) to each subset of data. However, this approach does not properly account for the uncertainty in behavioural classification, nor does it allow states to depend on habitat selection. An alternative approach is to estimate both state switching and habitat selection in a single, integrated model called an HMM-SSF.

METHODS

We build on this recent methodological work to make the HMM-SSF approach more efficient and general. We focus on writing the model as an HMM where the observation process is defined by an SSF, such that well-known inferential methods for HMMs can be used directly for parameter estimation and state classification. We extend the model to include covariates on the HMM transition probabilities, allowing for inferences into the temporal and individual-specific drivers of state switching. We demonstrate the method through an illustrative example of plains zebra (Equus quagga), including state estimation, and simulations to estimate a utilisation distribution.

RESULTS

In the zebra analysis, we identified two behavioural states, with clearly distinct patterns of movement and habitat selection ("encamped" and "exploratory"). In particular, although the zebra tended to prefer areas higher in grassland across both behavioural states, this selection was much stronger in the fast, directed exploratory state. We also found a clear diel cycle in behaviour, which indicated that zebras were more likely to be exploring in the morning and encamped in the evening.

CONCLUSIONS

This method can be used to analyse behaviour-specific habitat selection in a wide range of species and systems. A large suite of statistical extensions and tools developed for HMMs and SSFs can be applied directly to this integrated model, making it a very versatile framework to jointly learn about animal behaviour, habitat selection, and space use.

Lead exposure in brown bears is linked to environmental levels and the distribution of moose kills

Lead (Pb) is heterogeneously distributed in the environment and multiple sources like Pb ammunition and fossil fuel combustion can increase the risk of exposure in wildlife. Brown bears (Ursus arctos) in Sweden have higher blood Pb levels compared to bears from other populations, but the sources and routes of exposure are unknown. The objective of this study was to quantify the contribution of two potential sources of Pb exposure in female brown bears (n = 34 individuals; n = 61 samples). We used multiple linear regressions to determine the contribution of both environmental Pb levels estimated from plant roots and moose (Alces alces) kills to blood Pb concentrations in female brown bears. We found positive relationships between blood Pb concentrations in bears and both the distribution of moose kills by hunters and environmental Pb levels around capture locations. Our results suggest that the consumption of slaughter remains discarded by moose hunters is a likely significant pathway of Pb exposure and this exposure is additive to environmental Pb exposure in female brown bears in Sweden. We suggest that spatially explicit models, incorporating habitat selection analyses of harvest data, may prove useful in predicting Pb exposure in scavengers.

Habitat and climatic associations of climate-sensitive species along a southern range boundary

Climate change and habitat loss are recognized as important drivers of shifts in wildlife species' geographic distributions. While often considered independently, there is considerable overlap between these drivers, and understanding how they contribute to range shifts can predict future species assemblages and inform effective management. Our objective was to evaluate the impacts of habitat, climatic, and anthropogenic effects on the distributions of climate-sensitive vertebrates along a southern range boundary in Northern Michigan, USA. We combined multiple sources of occurrence data, including harvest and citizen-science data, then used hierarchical Bayesian spatial models to determine habitat and climatic associations for four climate-sensitive vertebrate species (American marten [Martes americana], snowshoe hare [Lepus americanus], ruffed grouse [Bonasa umbellus] and moose [Alces alces]). We used total basal area of at-risk forest types to represent habitat, and temperature and winter habitat indices to represent climate. Marten associated with upland spruce-fir and lowland riparian forest types, hares with lowland conifer and aspen-birch, grouse with lowland riparian hardwoods, and moose with upland spruce-fir. Species differed in climatic drivers with hares positively associated with cooler annual temperatures, moose with cooler summer temperatures and grouse with colder winter temperatures. Contrary to expectations, temperature variables outperformed winter habitat indices. Model performance varied greatly among species, as did predicted distributions along the southern edge of the Northwoods region. As multiple species were associated with lowland riparian and upland spruce-fir habitats, these results provide potential for efficient prioritization of habitat management. Both direct and indirect effects from climate change are likely to impact the distribution of climate-sensitive species in the future and the use of multiple data types and sources in the modelling of species distributions can result in more accurate predictions resulting in improved management at policy-relevant scales.

Open problems in PDE models for knowledge-based animal movement via nonlocal perception and cognitive mapping

The inclusion of cognitive processes, such as perception, learning and memory, are inevitable in mechanistic animal movement modelling. Cognition is the unique feature that distinguishes animal movement from mere particle movement in chemistry or physics. Hence, it is essential to incorporate such knowledge-based processes into animal movement models. Here, we summarize popular deterministic mathematical models derived from first principles that begin to incorporate such influences on movement behaviour mechanisms. Most generally, these models take the form of nonlocal reaction-diffusion-advection equations, where the nonlocality may appear in the spatial domain, the temporal domain, or both. Mathematical rules of thumb are provided to judge the model rationality, to aid in model development or interpretation, and to streamline an understanding of the range of difficulty in possible model conceptions. To emphasize the importance of biological conclusions drawn from these models, we briefly present available mathematical techniques and introduce some existing "measures of success" to compare and contrast the possible predictions and outcomes. Throughout the review, we propose a large number of open problems relevant to this relatively new area, ranging from precise technical mathematical challenges, to more broad conceptual challenges at the cross-section between mathematics and ecology. This review paper is expected to act as a synthesis of existing efforts while also pushing the boundaries of current modelling perspectives to better understand the influence of cognitive movement mechanisms on movement behaviours and space use outcomes.

Rapid behavioral responses of endangered tigers to major roads during COVID-19 lockdown

Roads pose a major, and growing, challenge for the conservation of endangered species. However, very little is known about how endangered species behaviorally respond to roads and what that means for road mitigation strategies. We used the nation-wide lockdown in Nepal during the COVID-19 pandemic as a natural experiment to investigate how dramatic reductions in traffic volume along the national highway affected movements of two GPS-collared tigers (Panthera tigris)-a globally endangered species. This work is the first systematic research on tigers in Nepal using radiotelemetry or GPS tracking data since the 1980s. We found that the highway more strongly constrained the space use and habitat selection of the male in Parsa National Park than the female in Bardia National Park. Over the entire study period, the female on average crossed 10 times more often per week than the male, and when he was near the highway, he was over 11 times more probable to not cross it than to cross during the day. However, we also found that the cessation of traffic during the pandemic lockdown relaxed tiger avoidance of roads and made the highway more permeable for both animals. They were 2-3 times more probable to cross the highway during the lockdown than before the lockdown. In the month following the lockdown, the space use area of the male tiger tripled in size (160-550 km²), whereas the female's shrunk to half its previous size (33-15 km²). These divergent patterns likely reflect differences between the two parks in their highway traffic volumes and regulations as well as ecological conditions. Our results provide clear evidence that vehicle traffic on major roads impede tiger movements, but also that tigers can respond quickly to reductions in human pressures. We conclude by identifying various actions to mitigate road impacts on tigers and other endangered species.

Influence of prey availability on habitat selection during the non-breeding period in a resident bird of prey

BACKGROUND

For resident birds of prey in the temperate zone, the cold non-breeding period can have strong impacts on survival and reproduction with implications for population dynamics. Therefore, the non-breeding period should receive the same attention as other parts of the annual life cycle. Birds of prey in intensively managed agricultural areas are repeatedly confronted with unpredictable, rapid changes in their habitat due to agricultural practices such as mowing, harvesting, and ploughing. Such a dynamic landscape likely affects prey distribution and availability and may even result in changes in habitat selection of the predator throughout the annual cycle.

METHODS

In the present study, we (1) quantified barn owl prey availability in different habitats across the annual cycle, (2) quantified the size and location of barn owl breeding and non-breeding home ranges using GPS-data, (3) assessed habitat selection in relation to prey availability during the non-breeding period, and (4) discussed differences in habitat selection during the non-breeding period to habitat selection during the breeding period.

RESULTS

The patchier prey distribution during the non-breeding period compared to the breeding period led to habitat selection towards grassland during the non-breeding period. The size of barn owl home ranges during breeding and non-breeding were similar, but there was a small shift in home range location which was more pronounced in females than males. The changes in prey availability led to a mainly grassland-oriented habitat selection during the non-breeding period. Further, our results showed the importance of biodiversity promotion areas and undisturbed field margins within the intensively managed agricultural landscape.

CONCLUSIONS

We showed that different prey availability in habitat categories can lead to changes in habitat preference between the breeding and the non-breeding period. Given these results we show how important it is to maintain and enhance structural diversity in intensive agricultural landscapes, to effectively protect birds of prey specialised on small mammals.

A three-step approach for assessing landscape connectivity via simulated dispersal: African wild dog case study

CONTEXT

Dispersal of individuals contributes to long-term population persistence, yet requires a sufficient degree of landscape connectivity. To date, connectivity has mainly been investigated using least-cost analysis and circuit theory, two methods that make assumptions that are hardly applicable to dispersal. While these assumptions can be relaxed by explicitly simulating dispersal trajectories across the landscape, a unified approach for such simulations is lacking.

OBJECTIVES

Here, we propose and apply a simple three-step approach to simulate dispersal and to assess connectivity using empirical GPS movement data and a set of habitat covariates.

METHODS

In step one of the proposed approach, we use integrated step-selection functions to fit a mechanistic movement model describing habitat and movement preferences of dispersing individuals. In step two, we apply the parameterized model to simulate dispersal across the study area. In step three, we derive three complementary connectivity maps; a heatmap highlighting frequently traversed areas, a betweenness map pinpointing dispersal corridors, and a map of inter-patch connectivity indicating the presence and intensity of functional links between habitat patches. We demonstrate the applicability of the proposed three-step approach in a case study in which we use GPS data collected on dispersing African wild dogs (Lycaon pictus) inhabiting northern Botswana.

RESULTS

Using step-selection functions we successfully parametrized a detailed dispersal model that described dispersing individuals' habitat and movement preferences, as well as potential interactions among the two. The model substantially outperformed a model that omitted such interactions and enabled us to simulate 80,000 dispersal trajectories across the study area.

CONCLUSION

By explicitly simulating dispersal trajectories, our approach not only requires fewer unrealistic assumptions about dispersal, but also permits the calculation of multiple connectivity metrics that together provide a comprehensive view of landscape connectivity. In our case study, the three derived connectivity maps revealed several wild dog dispersal hotspots and corridors across the extent of our study area. Each map highlighted a different aspect of landscape connectivity, thus emphasizing their complementary nature. Overall, our case study demonstrates that a simulation-based approach offers a simple yet powerful alternative to traditional connectivity modeling techniques. It is therefore useful for a variety of applications in ecological, evolutionary, and conservation research.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10980-023-01602-4.

Density-dependent habitat selection alters drivers of population distribution in northern Yellowstone elk

Although it is well established that density dependence drives changes in organismal abundance over time, relatively little is known about how density dependence affects variation in abundance over space. We tested the hypothesis that spatial trade-offs between food and safety can change the drivers of population distribution, caused by opposing patterns of density-dependent habitat selection (DDHS) that are predicted by the multidimensional ideal free distribution. We addressed this using winter aerial survey data of northern Yellowstone elk (Cervus canadensis) spanning four decades. Supporting our hypothesis, we found positive DDHS for food (herbaceous biomass) and negative DDHS for safety (openness and roughness), such that the primary driver of habitat selection switched from food to safety as elk density decreased from 9.3 to 2.0 elk/km² . Our results demonstrate how population density can drive landscape-level shifts in population distribution, confounding habitat selection inference and prediction and potentially affecting community-level interactions.

Are we telling the same story? Comparing inferences made from camera trap and telemetry data for wildlife monitoring

Estimating habitat and spatial associations for wildlife is common across ecological studies and it is well known that individual traits can drive population dynamics and vice versa. Thus, it is commonly assumed that individual- and population-level data should represent the same underlying processes, but few studies have directly compared contemporaneous data representing these different perspectives. We evaluated the circumstances under which data collected from Lagrangian (individual-level) and Eulerian (population-level) perspectives could yield comparable inference to understand how scalable information is from the individual to the population. We used Global Positioning System (GPS) collar (Lagrangian) and camera trap (Eulerian) data for seven species collected simultaneously in eastern Washington (2018-2020) to compare inferences made from different survey perspectives. We fit the respective data streams to resource selection functions (RSFs) and occupancy models and compared estimated habitat- and space-use patterns for each species. Although previous studies have considered whether individual- and population-level data generated comparable information, ours is the first to make this comparison for multiple species simultaneously and to specifically ask whether inferences from the two perspectives differed depending on the focal species. We found general agreement between the predicted spatial distributions for most paired analyses, although specific habitat relationships differed. We hypothesize the discrepancies arose due to differences in statistical power associated with camera and GPS-collar sampling, as well as spatial mismatches in the data. Our research suggests data collected from individual-based sampling methods can capture coarse population-wide patterns for a diversity of species, but results differ when interpreting specific wildlife-habitat relationships.

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.

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.

Habitat selection by free-roaming domestic dogs in rabies endemic countries in rural and urban settings

Domestic dogs can affect human health through bites and pathogen transmission, particularly in resource-poor countries where dogs, including owned ones, predominantly roam freely. Habitat and resource selection analysis methods are commonplace in wildlife studies but have not been used to investigate the environmental resource use of free-roaming domestic dogs (FRDD). The present study implements GPS devices to investigate habitat selection by FRDD from an urban site and a rural site in Indonesia, and one urban and two rural sites in Guatemala (N = 321 dogs). Spatial mixed effects logistic regression models, accounting for heterogeneous distribution of the resources, showed that patterns of habitat selection by FRDD were similar across study sites. The most preferred resources were anthropogenic, being buildings and roads, which implies selection for human proximity. Vegetation and open fields were less preferred and steep terrain was avoided, indicating that FRDD were synanthropic and that their space patterns likely optimised energy use. Results presented here provide novel data on FRDD habitat selection patterns, while improving our understanding of dog roaming behaviour. These findings provide insights into possible high-risk locations for pathogen transmission for diseases such as rabies, and can assist management authorities in the planning and deployment of efficient disease control campaigns, including oral vaccination.

Experience does not change the importance of wind support for migratory route selection by a soaring bird

Migration is a complex behaviour that is costly in terms of time, energy and risk of mortality. Thermal soaring birds rely on airflow, specifically wind support and uplift, to offset their energetic costs of flight. Their migratory routes are a record of movement decisions to negotiate the atmospheric environment and achieve efficiency. We expected that, regardless of age, birds use wind support to select their routes. Because thermal soaring is a complex flight behaviour that young birds need to learn, we expected that, as individuals gain more experience, their movement decisions will also increasingly favour the best thermal uplift conditions. We quantified how route choice during autumn migration of young European honey buzzards (Pernis apivorus) was adjusted to wind support and uplift over up to 4 years of migration and compared this with the choices of adult birds. We found that wind support was important in all migrations. However, we did not find an increase in the use of thermal uplifts. This could be due to the species-specific learning period and/or an artefact of the spatio-temporal scale of our uplift proxies.

Experience and social factors influence movement and habitat selection in scimitar-horned oryx (Oryx dammah) reintroduced into Chad

Reintroduced animals-especially those raised in captivity-are faced with the unique challenge of navigating a wholly unfamiliar environment, and often make erratic or extensive movements after release. Naïveté to the reintroduction landscape can be costly, e.g., through increased energy expenditure, greater exposure to predation, and reduced opportunities to forage. Integration with an extant population may provide opportunities for social information transfer. However, in the absence of interactions with residents, it is unclear how individual and social learning may affect an animal's ability to track resources in an unfamiliar landscape. We use integrated step selection functions (iSSFs) to address these knowledge gaps, by evaluating the extent to which environmental factors, individual experience (time since release), and social information-sharing (group size) influence movement decisions by scimitar-horned oryx (Oryx dammah) reintroduced into their native range for the first time in ca. 30 years. We found that both experience and social factors influenced the habitat selection and movement behavior of reintroduced oryx. Of four candidate iSSFs, the model that included environmental, experience, and group size variables performed best in both dry and wet periods. Statistically significant interaction terms between environmental variables and experience were generally larger than similar terms for group size, indicating that experience may affect habitat selection by reintroduced oryx more strongly than social factors. These findings may inform the management of recovering wildlife populations, update widely-held expectations about how released ungulates acclimate to novel landscapes, and demonstrate the utility of long-term monitoring of reintroduced populations.

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.

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.

Wolf spatial behavior promotes encounters and kills of abundant prey

Predators use different spatial tactics to track the prey on the landscape. Three hypotheses describe spatial tactics: prey abundance for prey that are aggregated in space; prey habitat for uniformly distributed prey; and prey catchability for prey that are difficult to catch and kill. The gray wolf (Canis lupus) is a generalist predator that likely employs more than one spatial hunting tactic to match their diverse prey with distinct distributions and behavior that are available. We conducted a study on 17 GPS collared wolves in 6 packs in Riding Mountain National Park, Manitoba, Canada where wolves prey on moose (Alces alces) and elk (Cervus canadensis). We evaluated wolf selection for prey density, habitat selection and catchability on the landscape through within-territory habitat selection analysis. We reveal support for both the prey habitat and prey catchability hypotheses. For moose, their primary prey, wolves employed a mixed habitat and catchability tactic. Wolves used spaces described by the intersection of moose habitat and moose catchability. Wolves selected for the catchability of elk, their secondary prey, but not elk habitat. Counter to our predictions, wolves avoided areas of moose and elk density, likely highlighting the ongoing space race between predator and prey. We illustrate that of the three hypotheses the primary driver was prey catchability, where the interplay of both prey habitat with catchability culminate in predator spatial behaviour in a multiprey system.

Targeting Sagebrush (Artemisia Spp.) Restoration Following Wildfire with Greater Sage-Grouse (Centrocercus Urophasianus) Nest Selection and Survival Models

Unprecedented conservation efforts for sagebrush (Artemisia spp.) ecosystems across the western United States have been catalyzed by risks from escalated wildfire activity that reduces habitat for sagebrush-obligate species such as Greater Sage-Grouse (Centrocercus urophasianus). However, post-fire restoration is challenged by spatial variation in ecosystem processes influencing resilience to disturbance and resistance to non-native invasive species, and spatial and temporal lags between slower sagebrush recovery processes and faster demographic responses of sage-grouse to loss of important habitat. Decision-support frameworks that account for these factors can help users strategically apply restoration efforts by predicting short and long-term ecological benefits of actions. Here, we developed a framework that strategically targets burned areas for restoration actions (e.g., seeding or planting sagebrush) that have the greatest potential to positively benefit sage-grouse populations through time. Specifically, we estimated sagebrush recovery following wildfire and risk of non-native annual grass invasion under four scenarios: passive recovery, grazing exclusion, active restoration with seeding, and active restoration with seedling transplants. We then applied spatial predictions of integrated nest site selection and survival models before wildfire, immediately following wildfire, and at 30 and 50 years post-wildfire based on each restoration scenario and measured changes in habitat. Application of this framework coupled with strategic planting designs aimed at developing patches of nesting habitat may help increase operational resilience for fire-impacted sagebrush ecosystems.