Conceptual and methodological advances in habitat-selection modeling: guidelines for ecology and evolution

Combining potential and realized distribution modeling of telemetry data for a bycatch risk assessment

Establishing marine species distributions is essential for guiding management and can be estimated by identifying potential favorable habitat at a population level and incorporating individual-level information (e.g., movement constraints) to inform realized space use. In this research, we applied a combined modeling approach to tracking data of adult female and juvenile South American sea lions (Otaria flavescens; n = 9) from July to November 2011 to make habitat predictions for populations in northern Chile. We incorporated topographic and oceanographic predictors with sea lion locations and environmentally based pseudo-absences in a generalized linear model for estimating population-level distribution. For the individual approach, we used a generalized linear mixed-effects model with a negative exponential kernel variable to quantify distance-dependent movement from the colony. Spatial predictions from both approaches were combined in a bivariate color map to identify areas of agreement. We then used a GIS-based risk model to characterize bycatch risk in industrial and artisanal purse-seine fisheries based on fishing set data from scientific observers and artisanal fleet logs (2010-2015), the bivariate sea lion distribution map, and criteria ratings of interaction characteristics. Our results indicate population-level associations with productive, shallow, low slope waters, near to river-mouths, and with high eddy activity. Individual distribution was restricted to shallow slopes and cool waters. Variation between approaches may reflect intrinsic factors restricting use of otherwise favorable habitat; however, sample size was limited, and additional data are needed to establish the full range of individual-level distributions. Our bycatch risk outputs identified highest risk from industrial fisheries operating nearshore (within 5 NM) and risk was lower, overall, for the artisanal fleet. This research demonstrates the potential for integrating potential and realized distribution models within a spatial risk assessment and fills a gap in knowledge on this species' distribution, providing a basis for targeting bycatch mitigation outreach and interventions.

The adaptive value of density-dependent habitat specialization and social network centrality

Density dependence is a fundamental ecological process. In particular, animal habitat selection and social behavior often affect fitness in a density-dependent manner. The Ideal Free Distribution (IFD) and niche variation hypothesis (NVH) present distinct predictions associated with Optimal Foraging Theory about how the effect of habitat selection on fitness varies with population density. Using caribou (Rangifer tarandus) in Canada as a model system, we test competing hypotheses about how habitat specialization, social behavior, and annual reproductive success (co)vary across a population density gradient. Within a behavioral reaction norm framework, we estimate repeatability, behavioral plasticity, and covariance among social behavior and habitat selection to investigate the adaptive value of sociality and habitat selection. In support of NVH, but not the IFD, we find that at high density habitat specialists had higher annual reproductive success than generalists, but were also less social than generalists, suggesting the possibility that specialists were less social to avoid competition. Our study supports niche variation as a mechanism for density-dependent habitat specialization.

Using Activity Measures and GNSS Data from a Virtual Fencing System to Assess Habitat Preference and Habitat Utilisation Patterns in Cattle

There has been an increased focus on new technologies to monitor habitat use and behaviour of cattle to develop a more sustainable livestock grazing system without compromising animal welfare. One of the currently used methods for monitoring cattle behaviour is tri-axial accelerometer data from systems such as virtual fencing technology or bespoke monitoring technology. Collection and transmission of high-frequency accelerometer and GNSS data is a major energy cost, and quickly drains the battery in contemporary virtual fencing systems, making it unsuitable for long-term monitoring. In this paper, we explore the possibility of determining habitat preference and habitat utilisation patterns in cattle using low-frequency activity and location data. We achieve this by (1) calculating habitat selection ratios, (2) determining daily activity patterns, and (3) based on those, inferring grazing and resting sites in a group of cattle wearing virtual fencing collars in a coastal setting with grey, wooded, and decalcified dunes, humid dune slacks, and salt meadows. We found that GNSS data, and a measure of activity, combined with accurate mapping of habitats can be an effective tool in assessing habitat preference. The animals preferred salt meadows over the other habitats, with wooded dunes and humid dune slacks being the least preferred. We were able to identify daily patterns in activity. By comparing general trends in activity levels to the existing literature, and using a Gaussian mixture model, it was possible to infer resting and grazing behaviour in the different habitats. According to our inference of behaviour the herd predominantly used the salt meadows for resting and ruminating. The approach used in this study allowed us to use GNSS location data and activity data and combine it with accurate habitat mapping to assess habitat preference and habitat utilisation patterns, which can be an important tool for guiding management decisions.

Spatial ecology and microhabitat selection of the nocturnal pitviper Viridovipera stejnegeri (Squamata: Viperidae) in relation to prey

Habitat is fundamental for facilitating various life activities in animals, for instance, snakes procure essential energy for survival and reproduction by selecting ambush microhabitats. While there has been extensive research on the selection of microhabitat for feeding in terrestrial and aquatic snakes, little is known about arboreal snakes. In the present study, we analyzed the ambush microhabitat preferences of Viridovipera stejnegeri, a widely distributed Asian pitviper in China, conducted association analysis between snake microhabitat and prey microhabitat and abundance to determine the ro5le of microhabitat selection in feeding. Employing random forest analysis and habitat selection functions, we further constructed a predictive framework for assessing the probability of ambush site selection by V. stejnegeri. Our results revealed that V. stejnegeri exhibited a distinct microhabitat preference for ambush prey. Among the 13 environmental factors assessed, V. stejnegeri showed pronounced preferences towards 12 of these factors, including climatic factors, geographical factors, and vegetation factors. Furthermore, although the preferences of V. stejnegeri overlapped substantially with those of its prey across multiple habitat factors, food abundance shows no significant association with various habitat factors of V. stejnegeri, and does not have significant predictive effect on habitat selection of V. stejnegeri. Therefore, we infer that V. stejnegeri does not preferentially select microhabitats with the highest food abundance, which does not support the hypothesis that "snakes select habitats based on the spatial distribution of prey abundance." By analyzing the characteristics of vegetation, geography, and climate, we conclude that V. stejnegeri tends to choose microhabitats with better ambush conditions to increase attack success rate, thereby achieving the optimal feeding success rate at the microhabitat scale, which is in line with the predictions of optimal foraging theory. This study provides new insights into the predation ecology and habitat selection of snakes.

Vegetation biomass and topography are associated with seasonal habitat selection and fall translocation behavior in Arctic hares

Habitat selection theory suggests that environmental features selected at coarse scales reveal fundamental factors affecting animal fitness. When these factors vary across seasons, they may lead to large-scale movements, including long-distance seasonal migrations. We analyzed the seasonal habitat selection of 25 satellite-tracked Arctic hares from a population on Ellesmere Island (Nunavut, Canada) that relocated over 100 km in the fall. Since no other lagomorph is known to perform such extensive movements, this population offered an ideal setting to test animal movement and habitat selection theory. On summer grounds hares selected low elevation areas, while on winter grounds they selected high vegetation biomass, high elevation, and steep slopes. During fall relocation, they alternated between stopover and traveling behavioral states (ratio 2:1). Stopover locations were characterized by higher vegetation heterogeneity and lower rugosity than traveling locations, while vegetation biomass and elevation interacted to explain stopover locations in a more complex way. The selected combination of environmental features thus varied across seasons and behavioral states, in a way broadly consistent with predictions based on the changing food and safety needs of hares. Although causality was not demonstrated, our results improve our understanding of long-distance movements and habitat selection in Arctic hares, as well as herbivore ecology in the polar desert. Results also provide strong support to animal movement and habitat selection theory, by showing how some important hypotheses hold when tested in a species phylogenetically distinct from most animal models used in this research field.

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.

Modular switches shift monarch butterfly migratory flight behavior at their Mexican overwintering sites

Eastern North American migratory monarch butterflies exhibit migratory behavioral states in fall and spring characterized by sun-dependent oriented flight. However, it is unclear how monarchs transition between these behavioral states at their overwintering site. Using a modified Mouritsen-Frost flight simulator, we confirm individual directionality and compass-based orientation (leading to group orientation) in fall migrants, and also uncover sustained flight propensity and direction-based flight reinforcement as distinctly migratory behavioral traits. By testing monarchs at their Mexican overwintering sites, we show that overwintering monarchs show reduced propensity for sustained flight and lose individual directionality, leading to the loss of group-level orientation. Overwintering fliers orient axially in a time-of-day dependent manner, which may indicate local versus long-distance directional heading. These results support a model of migratory flight behavior in which modular, state-dependent switches for flight propensity and orientation control are highly dynamic and are controlled in season- and location-dependent manners.

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.

A model-based hypothesis framework to define and estimate the diel niche via the 'Diel.Niche' R package

How animals use the diel period (24-h light-dark cycle) is of fundamental importance to understand their niche. While ecological and evolutionary literature abound with discussion of diel phenotypes (e.g. diurnal, nocturnal, crepuscular, cathemeral), they lack clear and explicit quantitative definitions. As such, inference can be confounded when evaluating hypotheses of animal diel niche switching or plasticity across studies because researchers may be operating under different definitions of diel phenotypes. We propose quantitative definitions of diel phenotypes using four alternative hypothesis sets (maximizing, traditional, general and selection) aimed at achieving different objectives. Each hypothesis set is composed of mutually exclusive hypotheses defined based on the activity probabilities in the three fundamental periods of light availability (twilight, daytime and night-time). We develop a Bayesian modelling framework that compares diel phenotype hypotheses using Bayes factors and estimates model parameters using a multinomial model with linear inequality constraints. Model comparison, parameter estimation and visualizing results can be done in the Diel.Niche R package. A simplified R Shiny web application is also available. We provide extensive simulation results to guide researchers on the power to discriminate among hypotheses for a range of sample sizes (10-1280). We also work through several examples of using data to make inferences on diel activity, and include online vignettes on how to use the Diel.Niche package. We demonstrate how our modelling framework complements other analyses, such as circular kernel density estimators and animal movement modelling. Our aim is to encourage standardization of the language of diel activity and bridge conceptual frameworks and hypotheses in diel research with data and models. Lastly, we hope more research focuses on the ecological and conservation importance of understanding how animals use diel time.

Movement ecology of an endangered mesopredator in a mining landscape

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

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

Effects of temperature heterogeneity on freshwater turtle habitat selection at their northern range limit

Environmental temperature is a crucial resource for ectotherms, affecting their physiology, behaviour and fitness. To maintain body temperatures within a suitable performance range, ectotherms select thermally-favourable locations, but this selection may be challenging in environments with high spatio-temporal heterogeneity. We assessed thermal habitat selection in two freshwater turtles (Emydoidea blandingii; Chrysemys picta) within a thermally heterogeneous environment at two spatial scales (selection of home ranges within the landscape, selection of locations within home ranges) and across seasons, by comparing temperatures at turtle locations vs. those available in the environment. Turtles selected warmer locations compared to those available in aquatic and terrestrial habitats only within home ranges, but did not show any temperature preferences when selecting home ranges at the larger scale. Turtles selected locations that were less thermally-variable than their surroundings, both at the home range scale and within home ranges. Thermal habitat selection was strongest during colder and more thermally-variable pre-nesting season compared to later periods. Despite differences in thermal mass between species, both species responded similarly to temperature variation. We conclude that freshwater turtles at their northern range margin select suitable microclimates within the suite of conditions that are naturally available.

Selection of summer feeding sites and food resources by female migratory caribou (Rangifer tarandus) determined using camera collars

Migratory caribou (Rangifer tarandus) is a socioeconomically and culturally key species for northern communities in the Arctic, and most of its populations are experiencing a sharp decline. Female migratory caribou depend on the availability of summer habitat resources to meet the needs associated with lactation and the accumulation of fat reserves to survive when resources are less abundant. Because of the large scales at which habitat and resource data are usually available, information on how female migratory caribou select habitat and resources at fine scales in the wild is lacking. To document selection of summer feeding sites, we equipped 60 female caribou with camera collars from 2016 to 2018. We collected a total of 65,150 10-sec videos between June 1st and September 1st for three years with contrasted spring phenology. We determined the selection at the feeding site scale (3rd scale of Johnson) and food item scale (4th scale of Johnson) using resource selection probability functions. Wetlands were highly selected as feeding sites in June and July while they were avoided in August. Shrublands were mostly selected in July and August. At the resources scale, lichen, birch, willow, and mushrooms were the most strongly selected resources. Our results provide precise and novel information on habitat selection at feeding sites and food resources selected by female caribou in the wild. This information will help understand foraging patterns and habitat selection behavior of female migratory caribou and will contribute to the management and conservation of its declining populations.

Accounting for behaviour in fine-scale habitat selection: A case study highlighting methodological intricacies

Animal habitat selection-central in both theoretical and applied ecology-may depend on behavioural motivations such as foraging, predator avoidance, and thermoregulation. Step-selection functions (SSFs) enable assessment of fine-scale habitat selection as a function of an animal's movement capacities and spatiotemporal variation in extrinsic conditions. If animal location data can be associated with behaviour, SSFs are an intuitive approach to quantify behaviour-specific habitat selection. Fitting SSFs separately for distinct behavioural states helped to uncover state-specific selection patterns. However, while the definition of the availability domain has been highlighted as the most critical aspect of SSFs, the influence of accounting for behaviour in the use-availability design has not been quantified yet. Using a predator-free population of high-arctic muskoxen Ovibos moschatus as a case study, we aimed to evaluate how (1) defining behaviour-specific availability domains, and/or (2) fitting separate behaviour-specific models impacts (a) model structure, (b) estimated selection coefficients and (c) model predictive performance as opposed to behaviour-unspecific approaches. To do so, we first applied hidden Markov models to infer different behavioural modes (resting, foraging, relocating) from hourly GPS positions (19 individuals, 153-1062 observation days/animal). Using SSFs, we then compared behaviour-specific versus behaviour-unspecific habitat selection in relation to terrain features, vegetation and snow conditions. Our results show that incorporating behaviour into the definition of the availability domain primarily impacts model structure (i.e. variable selection), whereas fitting separate behaviour-specific models mainly influences selection strength. Behaviour-specific availability domains improved predictive performance for foraging and relocating models (i.e. behaviours with medium to large spatial displacement), but decreased performance for resting models. Thus, even for a predator-free population subject to only negligible interspecific competition and human disturbance we found that accounting for behaviour in SSFs impacted model structure, selection coefficients and predictive performance. Our results indicate that for robust inference, both a behaviour-specific availability domain and behaviour-specific model fitting should be explored, especially for populations where strong spatiotemporal selection trade-offs are expected. This is particularly critical if wildlife habitat preferences are estimated to inform management and conservation initiatives.

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.

Feedback loops between 3D vegetation structure and ecological functions of animals

Ecosystems function in a series of feedback loops that can change or maintain vegetation structure. Vegetation structure influences the ecological niche space available to animals, shaping many aspects of behaviour and reproduction. In turn, animals perform ecological functions that shape vegetation structure. However, most studies concerning three-dimensional vegetation structure and animal ecology consider only a single direction of this relationship. Here, we review these separate lines of research and integrate them into a unified concept that describes a feedback mechanism. We also show how remote sensing and animal tracking technologies are now available at the global scale to describe feedback loops and their consequences for ecosystem functioning. An improved understanding of how animals interact with vegetation structure in feedback loops is needed to conserve ecosystems that face major disruptions in response to climate and land-use change.

Changes in movement, habitat use, and response to human disturbance accompany parturition events in bighorn sheep (Ovis canadensis)

Parturition and the early neonatal period are critical life history stages in ungulates with considerable implications for population growth and persistence. Understanding the changes in behaviour induced by ungulate parturition is important for supporting effective population management, but reliably identifying birth sites and dates presents a challenge for managers. Rocky Mountain bighorn sheep (Ovis canadensis canadensis) are one such highly valued and ecologically important species in montane and subalpine ecosystems of Western North America. In the face of changing patterns of anthropogenic land use, wildlife managers increasingly require site-specific knowledge of the movement and habitat selection characteristics of periparturient sheep to better inform land use planning initiatives and ensure adequate protections for lambing habitat. We used movement data from GPS collared parturient (n = 13) and non-parturient (n = 8) bighorn sheep in Banff National Park, Canada to (1) identify lambing events based on changes in key movement metrics, and (2) investigate how resource selection and responses to human use change during the periparturient period. We fit a hidden Markov model (HMM) to a multivariate characterization of sheep movement (step length, daily home range area, residence time) to predict realistic lambing dates for the animals in our study system. Leave-one-out cross validation of our model resulted in a 93% success rate for parturient females. Our model, which we parameterized using data from known parturient females, also predicted lambing events in 25% of known non-parturient ewes in a test dataset. Using a latent selection difference function and resource selection functions, we tested for postpartum changes in habitat use, as well as seasonal differences in habitat selection. Immediately following lambing, ewes preferentially selected high-elevation sites on solar aspects that were more rugged, closer to escape terrain, and further from roads. Within-home range habitat selection was similar between individuals in different reproductive states, but parturient ewes had stronger selection for low snow depth, sites closer to barren ground, and sites further from trails. We propose that movement-based approaches such as HMMs are a valuable tool for identifying critical parturition habitat in species with complex movement patterns and may have particular utility in study areas without access to extensive field observations or vaginal implant transmitters. Furthermore, our results suggest that managers should minimize human disturbance in lambing areas to avoid interfering with maternal behaviour and ensure access to a broad range of suitable habitat in the periparturient period.

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.

A utilization distribution for the global population of Cape Vultures (Gyps coprotheres) to guide wind energy development

The rapid development of wind energy in southern Africa represents an additional threat to the already fragile populations of African vultures. The distribution of the vulnerable Cape Vulture Gyps coprotheres overlaps considerably with wind energy development areas in South Africa, creating conflicts that can hinder both vulture conservation and sustainable energy development. To help address this conflict and aid in the safe placement of wind energy facilities, we map the utilization distribution (UD) of this species across its distributional range. Using tracking data from 68 Cape Vultures collected over the last 20 years, we develop a spatially explicit habitat use model to estimate the expected UDs around known colonies. Scaling the UDs by the number of vultures expected to use each of the colonies, we estimate the Cape Vulture population utilization distribution (PUD) and determine its exposure to wind farm impacts. To complement our results, we model the probability of a vulture flying within the rotor sweep area of a wind turbine throughout the species range and use this to identify areas that are particularly prone to collisions. Overall, our estimated PUD correlates well with reporting rates of the species from the Southern African Bird Atlas Project, currently used to assess potential overlap between Cape Vultures and wind energy developments, but it adds important benefits, such as providing a spatial gradient of activity estimates over the entire species range. We illustrate the application of our maps by analyzing the exposure of Cape Vultures in the Renewable Energy Development Zones (REDZs) in South Africa. This application is a scalable procedure that can be applied at different planning phases, from strategic, nationwide planning to project-level assessments.

Scale-sensitivity in the measurement and interpretation of environmental niches

Species environmental niches are central to ecology, evolution, and global change research, but their characterization and interpretation depend on the spatial scale (specifically, the spatial grain) of their measurement. We find that the spatial grain of niche measurement is usually uninformed by ecological processes and varies by orders of magnitude. We illustrate the consequences of this variation for the volume, position, and shape of niche estimates, and discuss how it interacts with geographic range size, habitat specialization, and environmental heterogeneity. Spatial grain significantly affects the study of niche breadth, environmental suitability, niche evolution, niche tracking, and climate change effects. These and other fields will benefit from a more mechanism-informed choice of spatial grain and cross-grain evaluations that integrate different data sources.

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.

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.

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.

The natural history and ecology of melanism in red wolf and coyote populations of the southeastern United States – evidence for Gloger’s rule

Background

Gloger’s rule postulates that animals should be darker colored in warm and humid regions where dense vegetation and dark environments are common. Although rare in Canis populations, melanism in wolves is more common in North America than other regions globally and is believed to follow Gloger’s rule. In the temperate forests of the southeastern United States, historical records of red wolf (Canis rufus) and coyote (Canis latrans) populations document a consistent presence of melanism. Today, the melanistic phenotype is extinct in red wolves while occurring in coyotes and red wolf-coyote hybrids who occupy the red wolf's historical range. To assess if Gloger’s rule could explain the occurrence and maintenance of melanistic phenotypes in Canis taxa, we investigated differences in morphology, habitat selection, and survival associated with pelage color using body measurements, GPS tracking data, and long-term capture-mark-recapture and radio-telemetry data collected on coyotes and hybrids across the southeastern United States.

Results

We found no correlation between morphometrics and pelage color for Canis taxa. However, we observed that melanistic coyotes and hybrids experienced greater annual survival than did their gray conspecifics. Furthermore, we observed that melanistic coyotes maintained larger home ranges and exhibited greater selection for areas with dense canopy cover and wetlands than did gray coyotes.

Conclusions

In the southeastern United States, pelage color influenced habitat selection by coyotes and annual survival of coyotes and hybrids providing evidence that Gloger’s rule is applicable to canids inhabiting regions with dense canopy cover and wetlands. Greater annual survival rates observed in melanistic Canis may be attributed to better concealment in areas with dense canopy cover such as coastal bottomland forests. We suggest that the larger home range sizes of melanistic coyotes may reflect the trade-off of reduced foraging efficiency in lower quality wetland habitat for improved survival. Larger home ranges and differential use of land cover by melanistic coyotes may facilitate weak assortative mating in eastern coyote populations, in which melanistic animals may have lower success of finding compatible mates in comparison to gray conspecifics. We offer that our observations provide a partial explanation for why melanism is relatively low (< 10%) but consistent within coyote populations throughout southeastern parts of their range.

What do caribou eat? A review of the literature on caribou diet

Historically the study of diet caribou and reindeer (Rangifer tarandus (Gmelin, 1788)) has been specific to herds and few comprehensive circumpolar analyses of Rangifer diet exist. As a result, the importance of certain diet items may play an outsized role in the caribou diet zeitgeist, e.g., lichen. It is incumbent to challenge this notion and test the relevant importance of various diet items within the context of prevailing hypotheses. We provide a systematic overview of 30 caribou studies reporting caribou diet and test biologically relevant hypotheses about spatial and temporal dietary variation. Our results indicate that in the winter caribou primarily consume lichen, but in warmer seasons, and primary productivity is lower, caribou primarily consume graminoids and other vascular plants. In more productive environments, where caribou have more competitors and predators, consumption of lichen increased. Overall, our description of caribou diet reveals that caribou diet is highly variable, but in circumstances where they can consume vascular plants, they will. As climate change affects Boreal and Arctic ecosystems, the type and volume of food consumed by caribou has become an increasingly important focus for conservation and management of caribou.