Step Selection Analysis Research Articles

Imprinted habitat selection varies across dispersal phases in a raptor species

Natal Habitat Preference Induction (NHPI) plays a significant role in shaping settlement decisions in dispersive animals. Despite its importance, limited research has explored how NHPI varies during natal dispersal phases and across different types of natal habitats. In this study, we examined NHPI in 77 GPS-tagged juvenile red kites (Milvus milvus) originating from different natal habitats along an elevational gradient in Switzerland. We applied individual-based step selection analysis to investigate habitat selection from independence to settlement. We found that during the prospecting phase, individuals predominantly selected habitats similar to their natal environments. However, this pattern changed in the settlement phase: individuals fledged from habitats at higher elevations or closer to urban areas mostly avoided similar habitats (negative NHPI), while those from areas with more farmlands or pastures (combined with forests) showed a preference for similar habitats (positive NHPI). Moreover, the magnitude and individual variation in NHPI differed depending on the natal habitat types from which individuals originated. These findings highlight that strength, direction, and individual variation in NHPI differ between natal habitat types and dispersal phases. Natal habitats therefore can have pervasive legacy effects on subsequent habitat selection, likely affecting population and range dynamics.

Naivety dies with the calf: calf loss to human hunters imposes behavioral change in a long-lived but heavily harvested ungulate

BackgroundIn prey, patterns of individual habitat selection and movement can be a consequence of an individuals’ anti-predator behavior. Adjustments of anti-predator behavior are important for prey to increase their survival. Hunters may alter the anti-predator behavior of prey. In long-lived animals, experience may cause behavioral changes during individuals’ lifetime, which may result in altered habitat selection and movement. Our knowledge of which specific events related to hunting activity induce behavioral changes in solitary living species is still limited.MethodsWe used offspring loss in a solitary and long-lived ungulate species, moose (Alces alces), as our model system. We investigated whether offspring loss to hunters induces behavioral changes in a species subjected to heavy human harvest but free from natural predation. To test for behavioral change in relation to two proxies for experience (calf fate and age), we combined movement data from 51 adult female moose with data on their offspring survival and female age. We tested for adjustments in females’ habitat selection and movement following calf harvest using Hidden Markov Models and integrated Step Selection Analysis to obtain behavioral state specific habitat selection coefficients.ResultsWe found that females with a harvested calf modified habitat selection and movement during the following hunting season. Female moose selected for shorter distance to roads during the night, selected for shorter distance to forests and greater distance to human settlements following calf harvest than females who had not lost a calf. The survival of twins in a given hunting season was related to female age. Older females we more likely to have twins survive the hunting season.ConclusionsOur findings suggest that losing offspring to human harvest imposes behavioral changes in a long-lived ungulate species, leading to adjustments in females' habitat selection and movement behavior, which may lower the risk of encountering hunters. In our study, female moose that experienced calf loss selected for lower distance to forest and selected for greater distance to human settlements during periods of high hunting pressure compared to females without the experience of calf loss during the previous hunting season. We interpret this as potential learning effects.

Impacts of management practices on habitat selection during juvenile mountain lion dispersal.

Dispersal is a complex series of movements before an individual establishes a home range. Animals must travel and forage in unfamiliar landscapes that include anthropogenic risks such as road crossings, harvest, and urban landscapes. We compare dispersal behavior of juvenile mountain lions (Puma concolor) from two geographically distinct populations in California and Nevada, USA. These two sites are ecologically similar but have different management practices; hunting is permitted in Nevada, whereas mountain lions are protected in California. We used GPS-collar data and net-squared displacement analysis to identify three dispersal states: exploratory, departure, and transient home range. We then compared each dispersal state of the two mountain lion populations using an integrated step selection analysis (iSSA). The model included explanatory variables hypothesized to influence one or more dispersal states, including distance to forest, shrub, water, hay and crop, developed lands, and four-wheel drive roads, as well as elevation and terrain ruggedness. Results revealed consistent habitat selection between sites across most landscape variables, with one notable exception: anthropogenic covariates, including distance to developed land, distance to hay and crop, and distance to four-wheeled drive roads, were only statistically significant on modeled habitat selection during dispersal in the population subject to hunting (i.e., Nevada). Results suggest that hunting (pursuit with hounds resulting in harvest) and non-lethal pursuit (pursuit with hounds but no harvest allowed) increase avoidance of anthropogenic landscapes during dispersal for juvenile mountain lions. By comparing populations, we provided valuable insights into the role of management in shaping dispersal behavior.

Pursuit and escape drive fine-scale movement variation during migration in a temperate alpine ungulate

Climate change reduces snowpack, advances snowmelt phenology, drives summer warming, alters growing season precipitation regimes, and consequently modifies vegetation phenology in mountain systems. Elevational migrants track spatial variation in seasonal plant growth by moving between ranges at different elevations during spring, so climate-driven vegetation change may disrupt historic benefits of migration. Elevational migrants can furthermore cope with short-term environmental variability by undertaking brief vertical movements to refugia when sudden adverse conditions arise. We uncover drivers of fine-scale vertical movement variation during upland migration in an endangered alpine specialist, Sierra Nevada bighorn sheep (Ovis canadensis sierrae) using a 20-year study of GPS collar data collected from 311 unique individuals. We used integrated step-selection analysis to determine factors that promote vertical movements and drive selection of destinations following vertical movements. Our results reveal that relatively high temperatures consistently drive uphill movements, while precipitation likely drives downhill movements. Furthermore, bighorn select destinations at their peak annual biomass and maximal time since snowmelt. These results indicate that although Sierra Nevada bighorn sheep seek out foraging opportunities related to landscape phenology, they compensate for short-term environmental stressors by undertaking brief up- and downslope vertical movements. Migrants may therefore be impacted by future warming and increased storm frequency or intensity, with shifts in annual migration timing, and fine-scale vertical movement responses to environmental variability.

Using integrated step selection to determine effects of predation risk on bison habitat selection and movement

AbstractAnimal movement is a fundamental mechanism that shapes communities and ecosystems. Ungulates alter the ecosystems they inhabit and understanding their movements and distribution is critical for linking habitat with population dynamics. Predation risk has been shown to strongly influence ungulate movement patterns, such that ungulates may select habitat where predation risk is lower (refugia), adjust movement rates, temporal patterns, or selection of cover variables in areas with greater predation risk. We evaluated potential predation avoidance behavior in a population of plains bison inhabiting the north rim of Grand Canyon National Park (GRCA) and adjacent Kaibab National Forest (KNF). The KNF has year‐round hunting managed by Arizona Game and Fish Department, whereas hunting is not allowed in GRCA. Human‐maintained water sources on the KNF are particularly important resources for bison wherein they may be exposed to higher predation risk to access these resources. We used 2‐h GPS locations for three years from 31 bison (n = 9 males; n = 22 females), and integrative step selection analysis to test four hypotheses about the potential for bison to reduce their risk from human predation by avoiding areas of high predation risk; moving faster in areas with high predation risk; entering high‐risk areas at night when risk is reduced; and entering high‐risk areas in habitats that provide cover (coniferous forest). The highest performing model indicated bison movement was 1.3 times faster per 2‐h step interval than in areas with no hunting across all vegetation classes (coniferous forest, shrub, quaking aspen, grass‐forb meadow) and across all topography classes (valley, slope, ridge). Bison moved more slowly in grass‐forb meadows than all other vegetation types, and in valleys relative to slopes and ridges. Several radio‐collared individuals had no GPS locations in KNF for the duration of the study. Bison avoided predation risk using two strategies: moving faster while in the KNF, and fully avoiding high‐risk areas by remaining within GRCA. Management that manipulates or reduces timing of hunting seasons may reduce perceived predation risk and encourage bison to distribute into the KNF and across a broader range of available habitat.

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

BackgroundGlucocorticoids 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.MethodsWe 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.ResultsWe 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.ConclusionsWe 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.

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.

Risk response towards roads is consistent across multiple species in a temperate forest ecosystem

Roads can have diverse impacts on wildlife species, and while some species may adapt effectively, others may not. Studying multiple species' responses to the same infrastructure in a given area can help understand this variation and reveal the effects of disturbance on the ecology of wildlife communities. This study investigates the behavioural responses of four species with distinctive ecological and behavioural traits to roads in the protected Bohemian Forest Ecosystem in central Europe: European roe deer Capreolus capreolus, a solitary herbivore; red deer Cervus elaphus a gregarious herbivore; wild boar Sus scrofa, a gregarious omnivore and Eurasian lynx Lynx lynx, a solitary large carnivore. We used GPS data gathered from each species to study movement behaviour and habitat selection in relation to roads using an integrated step selection analysis. For all species and sexes, we predicted increased movement rates in response to roads, selection of vegetation cover near roads and open areas after road crossings, and increased road avoidance during the day. We found remarkably similar behavioural responses towards roads across species. The behavioural adaptations to road exposure, such as increased movement rates and selection for vegetation cover, were analogous to responses to natural predation risk. Roads were more strongly avoided during daytime, when traffic volume was high. Road crossings were more frequent at twilight and at night within open areas offering food resources. Gregarious animals exposed to roads favoured stronger road avoidance over faster movements. Ungulates crossed roads more at twilight, coinciding with commuter traffic during winter. Despite differences in the ecology and behaviour of the four species, our results showed similar adaptations towards a common threat. The continuous expansion of the global transportation network should be accompanied by efforts to understand and minimise the impact of roads on wildlife to assist wildlife management and ensure conservation.

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.

Not all sanctuaries are created equal: variation in protected area selection by wintering mallards

AbstractPublic lands managed for wildlife frequently provide various forms of sanctuary to increase residency times and allow access to energetic and other habitat resources for waterfowl. The influence of sanctuary type and disturbance regime on resource use and fine‐scale movements of waterfowl has not been investigated extensively using currently available transmitter technologies. We examined mallard (Anas platyrhynchos) use of various types of waterfowl sanctuary and non‐sanctuary areas in the Mississippi Alluvial Valley region of eastern Arkansas, USA, during winters of 2019–2021. We deployed 105 global positioning system transmitters on mallards at 4 closed‐access spatial sanctuaries on or adjacent to Dale Bumpers White River National Wildlife Refuge. We used hourly transmitter locations to examine mallard use of public sanctuary areas, public hunt areas, and private lands using integrated step selection analysis. Public sanctuary areas provided varying levels of protected status, public hunt areas allowed for varying levels of hunting intensity by duck hunters, and private lands were open to waterfowl hunting and other forms of private uses but may or may not have been hunted at any specific frequency. Mallards selected spatial sanctuary and avoided public hunt areas, other sanctuary types, and private lands during the day. In contrast, mallards selected for private lands over spatial sanctuary at night. Mallards tended to avoid areas that allowed duck hunting or used them during the night when risk of harvest mortality was removed. After the hunting season closed, mallards began using areas that previously allowed duck hunting during the day, suggesting that risk was the primary factor influencing site use. Moreover, mallards were 1.6 times more likely to use public daily hunt areas and 2.1 times more likely to use private lands potentially open to hunting during the day than spatial sanctuary 2 weeks after the close of duck hunting season in February. Spatial sanctuaries appear more effective in influencing mallard use than temporal sanctuaries or inviolate sanctuaries, which are commonly used by state and federal agencies. Partial daily, daily, or activity‐specific (e.g., no hunting past noon, no hunting 3 days/week, no waterfowl hunting) closures to encourage mallard use of temporal sanctuaries do not appear to reduce the perceived harvest‐related risk to mallards enough for them to view these areas as accessible or significantly increase their use.

Movement behaviour of the common frog (Rana temporaria) in an anthropized mountain landscape: integrated step selection analysis of GPS tracking data

Abstract Movement is a key aspect of amphibian ecology as the life cycle of many species involves seasonal dispersal and migration. However, there is still a lack of knowledge about how amphibians move across landscapes in relation to landscape structure and resource availability. Modern lightweight GPS loggers and associated statistical tools offer new perspectives to fill this gap. We tracked the movements of 20 adult European common frogs (Rana temporaria) in a human-transformed mountain landscape during summer using GPS tags programmed with a constant 4-hour time interval between fixes. Using integrated step-selection analysis, we demonstrate firstly that frogs strongly selected aquatic habitats over open grassland. Second, ski runs have a negative effect on frogs, indicated by longer movement steps. Weather (air temperature and rain) had no effect on frog movements. These results constitute a promising first step towards studying anuran movement in relation to landscape structure at fine spatial and temporal scales.

Understanding step selection analysis through numerical integration

Abstract Step selection functions (SSFs) are flexible statistical models used to jointly describe animals' movement and habitat preferences. The popularity of SSFs has grown rapidly, and various extensions have been developed to increase their utility, including the ability to use multiple statistical distributions to describe movement constraints, interactions to allow movements to depend on local environmental features, and random effects and latent states to account for within‐ and among‐individual variability. Although the SSF is a relatively simple statistical model, its presentation has not been consistent in the literature, leading to confusion about model flexibility and interpretation. We believe that part of the confusion has arisen from the conflation of the SSF model with the methods used for statistical inference, and in particular, parameter estimation. Notably, conditional logistic regression (CLR) can be used to fit SSFs in exponential form, and this model fitting approach is often presented interchangeably with the actual model (the SSF itself). However, reliance on CLR reduces model flexibility, and suggests a misleading interpretation of step selection analysis as being equivalent to a case–control study. In this review, we explicitly distinguish between model formulation and inference technique, presenting a coherent framework to fit SSFs based on numerical integration and maximum likelihood estimation. We provide an overview of common numerical integration techniques (including Monte Carlo integration, importance sampling and quadrature), and explain how they relate to popular methods used in step selection analyses. This general framework unifies different model fitting techniques for SSFs, and opens the way for improved inferential methods. In this approach, it is straightforward to model movement with distributions outside the exponential family, and to apply different SSF model formulations to the same data set and compare them with AIC. By separating the model formulation from the inference technique, we hope to clarify many important concepts in step selection analysis.

Ocelots in the moonlight: Influence of lunar phase on habitat selection and movement of two sympatric felids.

Various landscape and environmental factors influence animal movement and habitat selection. Lunar illumination affects nocturnal visual perception of many species and, consequently, may influence animal activity and habitat selection. However, the effects of varying moon stage may differ across taxa. Prey species often reduce activity during highly visible periods of night while predators may increase activity or alter their habitat use. Ocelots (Leopardus pardalis) and bobcats (Lynx rufus), two nocturnal predatory felids that coexist in southern Texas, may also alter their behavior in response to the phase of the moon. To evaluate the effects of lunar phase on habitat selection of ocelots and bobcats, we executed a step selection analysis using high-frequency GPS-telemetry data collected on each species (ocelot, N = 8; bobcat, N = 13) in southern Texas during 2017-2021 and compared step length during new versus full moons. We predicted that ocelots would increase use of dense thornshrub to reduce their visibility during a full moon. However, as bobcats are habitat generalists and are more active during crepuscular periods, we predicted less influence of moon phase on activity. Ocelots did not alter habitat selection in response to lunar phase but moved shorter distances during full moon phases. Conversely, bobcats selected for greater vegetation cover during full moons, possibly to facilitate hunting during brighter periods, but exhibited no difference in movement across lunar phase. We provide, to our knowledge, the first example of habitat selection by predators in relation to lunar phase and show differences across new versus full moons by ocelots and bobcats such that ocelots alter step length but not habitat selection while bobcats altered habitat selection but not step length in response to shifting lunar phase. Further, we suggest the high potential for ocelot-vehicle collisions on darker nights due to increased movement by ocelots and poor visibility for drivers.

Coyotes in the Great Basin desert do not exhibit a spatial response following the removal of anthropogenic water sources

Coyote (Canis latrans) range expansion into desert ecosystems has highlighted the role of anthropogenic water sources in arid ecosystems. Despite hypotheses that additional water facilitated this expansion, previous studies reported that coyotes did not exhibit a spatial or dietary response to removal of anthropogenic water. We used GPS data to examine if coyotes responded to water removal at a finer spatial scale than previously investigated. Our integrated step selection analysis did not find evidence that coyotes adjusted their distance to water following water removal. Vegetation was an important factor in habitat selection of coyotes, with riparian and agricultural areas being the most selected among vegetation types. Coyotes selected for locations where hunting and trapping was prohibited. Possibly the cause of increased coyote abundance in our study area was not due to the introduction of anthropogenic water sources but rather due to the cessation of regional lethal predator control programs. These two management decisions both occurred in the 1970s, therefore, their influences on the subsequent increase of coyote abundance may have been conflated. Our results, in combination with previous studies, provide evidence that coyotes are desert-adapted carnivores that do not rely on anthropogenic water sources.

Movement behavior, habitat selection, and functional responses to habitat availability among four species of wintering waterfowl in California

IntroductionHabitat selection analyses provide a window into the perceived value of habitats by animals and how those perceptions compare with other animals, change across time, or change in relation to availability (termed functional responses). Habitat selection analysis and functional responses can be used to develop strategies to avoid habitat limitations, guide habitat management, and set attainable conservation goals. GPS relocations of marked animals are the principal data used in habitat selection analysis. The accuracy and frequency with which tracking devices collect data are increasing and may result in non-stationary point processes that result from latent behaviors previously unidentifiable in sparse data.MethodsWe investigated non-stationary step length distributions and integrated a two-mixture model of animal movement with step selection analysis to identify patterns of activity among four species of co-occurring waterfowl that winter in the Central Valley of California, United States. We evaluated relative strength of selection and compared functional responses across a range of habitat types for two goose and two dabbling duck species.ResultsGoose species (greater white-fronted goose [Anser albifrons] and lesser snow goose [Anser caerulescens caerulescens]) used habitats similarly and displayed similar functional responses with habitat availability. Northern pintail (Anas acuta) displayed functional responses for habitats that provided primary food resources and sanctuary from hunting that were more similar to geese than to mallard (Anas platyrhynchos), which expressed a more generalist pattern of habitat selection.DiscussionOur results define conditions where food resource competition between geese and ducks could operate, which indicate that some species may be more impacted than others. Specifically, early season food limitation may manifest more strongly in snow geese due to longer movements and stronger functional response with rice availability. Late season limitations may manifest in northern pintail, which remain reliant on rice later but may not be reflected in habitat selection patterns due to a consistent functional response with rice availability. We show that multiple movement processes present in high-resolution data can be used to obtain a variety of information about animal behavior and that subsequent step selection analyses may demonstrate unique functional responses relative to alternate habitat selection methods that warrant additional investigation.

Behavioral-dependent recursive movements and implications for resource selection

Within home ranges, animals repeatedly visit certain areas. Recursive movement patterns are widespread throughout the animal kingdom, but are rarely considered when developing resource selection models. We examined how behavioral state-dependent recursive movements influenced reource selection of eastern wild turkey (Meleagris gallopavo silvestris) broods as they aged from day 1 to 28. Because broods become more plastic in behaviors once they begin roosting off the ground, we separated data into broods that were ground roosting (1–13 days) and tree roosting (14–28 days). We used Hidden Markov Models to identify 2 behavioral states (restricted and mobile). We extracted state-specific recursive movements based on states and specific step lengths, which we integrated into a step selection analysis to evaluate resource selection. We found that in a restricted state, ground roosting broods spent less time in areas of mixed pine-hardwoods and more time in areas with greater vegetation density. Tree roosting broods revisited areas closer to shrub/scrub landcover types, and areas with greater vegetation density. Tree roosting broods also spent less time near mixed pine-hardwoods, while spending more time in areas with greater vegetation density. We found that in a mobile state, ground roosting broods revisited areas closer to secondary roads and mixed pine-hardwoods, but farther from hardwoods. Tree roosting broods revisited areas farther from secondary roads and with greater vegetation density. Tree roosting broods also spent more time in areas closer to pine. Resource selection varied depending on behavioral state and recursive movements. However, revisitation and residence time impacted selection in both ground and tree roosting broods. Our findings highlight the need to consider how behaviors can influence movement decisions and ultimately resource selection.

Accounting for unobserved spatial variation in step selection analyses of animal movement via spatial random effects

Abstract Step selection analysis (SSA) is a common framework for understanding animal movement and resource selection using telemetry data. Such data are, however, inherently autocorrelated in space, a complication that could impact SSA‐based inference if left unaddressed. Accounting for spatial correlation is standard statistical practice when analysing spatial data, and its importance is increasingly recognized in ecological models (e.g. species distribution models). Nonetheless, no framework yet exists to account for such correlation when analysing animal movement using SSA. Here, we extend the popular method integrated step selection analysis (iSSA) by including a Gaussian field (GF) in the linear predictor to account for spatial correlation. For this, we use the Bayesian framework R‐INLA and the stochastic partial differential equations (SPDE) technique. We show through a simulation study that our method provides accurate fixed effects estimates, quantifies their uncertainty well and improves the predictions. In addition, we demonstrate the practical utility of our method by applying it to three wolverine (Gulo gulo) tracks. Our method solves the problems of assuming spatially independent residuals in the SSA framework. In addition, it offers new possibilities for making long‐term predictions of habitat usage.

Habitat selection of southern giant petrels: potential environmental monitors of the Antarctic Peninsula

AbstractThe southern giant petrel (Macronectes giganteus) is a widely distributed top predator of the Southern Ocean. To define the fine-scale foraging areas and habitat use of Antarctic breeding populations, 47 southern giant petrels from Nelson Island were GPS-tracked during the summers of 2019–2020 and 2021–2022. Step-selection analysis was applied to test the effects of environmental variables on habitat selection. Visual overlap with seal haul-out sites and fishing areas was also analysed. Birds primarily used waters to the south of the colony in the Weddell and Bellingshausen seas. Females showed a broader distribution, reaching up to -70°S to the west of Nelson Island, while males were mainly concentrated in waters off the northern Antarctic Peninsula. Habitat selection of both sexes was associated with water depth and proximity to penguin colonies. Both overlapped their foraging areas with fishing sites and females in particular overlapped with toothfish fishery blocks in Antarctica and with fishing areas in the Patagonian Shelf. Due to their habitat associations and overlap with fisheries, when harnessed with tracking devices and animal-borne cameras, giant petrels can act as platforms for monitoring the condition and occurrence of penguin colonies, haul-out sites and unregulated fisheries on various temporal and spatial scales in Antarctica.

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.

Activity modulation and selection for forests help giant anteaters to cope with temperature changes

Mammals use thermoregulatory behavioural strategies to reduce the cost of physiological thermoregulation. Environmental temperatures should, therefore, impact their decisions. We investigated the effect of environmental temperature on the movement decisions of a large mammal with low capacity for physiological thermoregulation: the giant anteater, Myrmecophaga tridactyla. We GPS-tracked 14 giant anteaters in the Brazilian Pantanal wetland over 5 years. We used hidden Markov models to identify two behavioural states (encamping, as a proxy of resting, and moving, as a proxy of being active) across individuals' trajectories. Then, we estimated the effect of environmental temperature on the probability of moving across the hours of the day in open and forested habitats. We also used integrated step selection analysis to understand how environmental temperature drives giant anteater's habitat selection across the day. Giant anteaters showed three important behavioural thermoregulatory strategies in response to environmental temperature changes: they modulated activity duration, completely shifted activity period on a scale of days and selected forests as thermal shelters. With increasing environmental temperature, giant anteaters increased activity duration, nocturnality and diurnal selection for forests, increasing energy intake while avoiding heat gain by solar radiation. With decreasing environmental temperature, they decreased activity duration, increased diurnality and increased nocturnal selection for forests, thus gaining heat from solar radiation when active and taking shelter in milder microclimates when resting. Besides their high short-term behavioural plasticity regarding activity, giant anteaters also used forests to thermoregulate. These results provide insights into how other mammals could respond to climate change. In particular, we highlight the importance of forests as thermal shelters, offering milder temperatures than adjacent open areas during both hot and cold weather spells. Thermal shelters will become more and more indispensable to animal thermoregulation as the frequency and intensity of extreme weather events increase.