Applications of step-selection functions in ecology and conservation

Spatial heterogeneity facilitates carnivore coexistence

Competitively dominant carnivore species can limit the population sizes and alter the behavior of inferior competitors. Established mechanisms that enable carnivore coexistence include spatial and temporal avoidance of dominant predator species by subordinates, and dietary niche separation. However, spatial heterogeneity across landscapes could provide inferior competitors with refuges in the form of areas with lower competitor density and/or locations that provide concealment from competitors. Here, we combine temporally overlapping telemetry data from dominant lions (Panthera leo) and subordinate African wild dogs (Lycaon pictus) with high-resolution remote sensing in an integrated step selection analysis to investigate how fine-scaled landscape heterogeneity might facilitate carnivore coexistence in South Africa's Hluhluwe-iMfolozi Park, where both predators occur at exceptionally high densities. We ask whether the primary lion-avoidance strategy of wild dogs is spatial avoidance of lions or areas frequented by lions, or if wild dogs selectively use landscape features to avoid detection by lions. Within this framework, we also test whether wild dogs rely on proactive or reactive responses to lion risk. In contrast to previous studies finding strong spatial avoidance of lions by wild dogs, we found that the primary wild dog lion-avoidance strategy was to select landscape features that aid in avoidance of lion detection. This habitat selection was routinely used by wild dogs, and especially when in areas and during times of high lion-encounter risk, suggesting a proactive response to lion risk. Our findings suggest that spatial landscape heterogeneity could represent an alternative mechanism for carnivore coexistence, especially as ever-shrinking carnivore ranges force inferior competitors into increased contact with dominant species.

Where did they not go? Considerations for generating pseudo-absences for telemetry-based habitat models

BACKGROUND

Habitat suitability models give insight into the ecological drivers of species distributions and are increasingly common in management and conservation planning. Telemetry data can be used in habitat models to describe where animals were present, however this requires the use of presence-only modeling approaches or the generation of 'pseudo-absences' to simulate locations where animals did not go. To highlight considerations for generating pseudo-absences for telemetry-based habitat models, we explored how different methods of pseudo-absence generation affect model performance across species' movement strategies, model types, and environments.

METHODS

We built habitat models for marine and terrestrial case studies, Northeast Pacific blue whales (Balaenoptera musculus) and African elephants (Loxodonta africana). We tested four pseudo-absence generation methods commonly used in telemetry-based habitat models: (1) background sampling; (2) sampling within a buffer zone around presence locations; (3) correlated random walks beginning at the tag release location; (4) reverse correlated random walks beginning at the last tag location. Habitat models were built using generalised linear mixed models, generalised additive mixed models, and boosted regression trees.

RESULTS

We found that the separation in environmental niche space between presences and pseudo-absences was the single most important driver of model explanatory power and predictive skill. This result was consistent across marine and terrestrial habitats, two species with vastly different movement syndromes, and three different model types. The best-performing pseudo-absence method depended on which created the greatest environmental separation: background sampling for blue whales and reverse correlated random walks for elephants. However, despite the fact that models with greater environmental separation performed better according to traditional predictive skill metrics, they did not always produce biologically realistic spatial predictions relative to known distributions.

CONCLUSIONS

Habitat model performance may be positively biased in cases where pseudo-absences are sampled from environments that are dissimilar to presences. This emphasizes the need to carefully consider spatial extent of the sampling domain and environmental heterogeneity of pseudo-absence samples when developing habitat models, and highlights the importance of scrutinizing spatial predictions to ensure that habitat models are biologically realistic and fit for modeling objectives.

Resource selection of a nomadic ungulate in a dynamic landscape

Nomadic movements are often a consequence of unpredictable resource dynamics. However, how nomadic ungulates select dynamic resources is still understudied. Here we examined resource selection of nomadic Mongolian gazelles (Procapra gutturosa) in the Eastern Steppe of Mongolia. We used daily GPS locations of 33 gazelles tracked up to 3.5 years. We examined selection for forage during the growing season using the Normalized Difference Vegetation Index (NDVI). In winter we examined selection for snow cover which mediates access to forage and drinking water. We studied selection at the population level using resource selection functions (RSFs) as well as on the individual level using step-selection functions (SSFs) at varying spatio-temporal scales from 1 to 10 days. Results from the population and the individual level analyses differed. At the population level we found selection for higher than average NDVI during the growing season. This may indicate selection for areas with more forage cover within the arid steppe landscape. In winter, gazelles selected for intermediate snow cover, which may indicate preference for areas which offer some snow for hydration but not so much as to hinder movement. At the individual level, in both seasons and across scales, we were not able to detect selection in the majority of individuals, but selection was similar to that seen in the RSFs for those individuals showing selection. Difficulty in finding selection with SSFs may indicate that Mongolian gazelles are using a random search strategy to find forage in a landscape with large, homogeneous areas of vegetation. The combination of random searches and landscape characteristics could therefore obscure results at the fine scale of SSFs. The significant results on the broader scale used for the population level RSF highlight that, although individuals show uncoordinated movement trajectories, they ultimately select for similar vegetation and snow cover.

Northern gannets (Morus bassanus) are strongly affected by operating offshore wind farms during the breeding season

Northern gannets (Morus bassanus) have been ranked as one of the most vulnerable species in terms of collision with offshore wind farm (OWF) turbines, and strong avoidance of OWFs has been documented for this species. Gannets increasingly encounter OWFs within the ranges of their largest breeding colonies along the European coasts. However, information on their actual reactions to OWFs during the breeding season is lacking. We investigated the possible effects of OWFs located 23-35 km north of the colony on Helgoland in the southern North Sea on breeding gannets. GPS tags were applied to 28 adult gannets breeding on Helgoland for several weeks over 2 years. Most gannets (89%) predominantly avoided the OWFs in both years, but 11% frequently entered them when foraging or commuting between the colony and foraging areas. Flight heights inside the OWFs were close to the rotor-blade zone, especially for individuals predominantly avoiding the OWFs. Gannets preferred distances of 250-450 m to the turbines when being inside the OWF. A point process modelling approach revealed that the gannets resource selection of the OWF area compared with the surroundings (outside OWF = up to 15 km from the OWF border) was reduced by 21% in 2015 and 37% in 2016. This study provides the first detailed characterisation of individual reactions of gannets to OWFs during the breeding season and one of the first comprehensive studies of OWF effects on this species based on telemetry data. The documented effects need to be considered during the planning processes for future OWFs, especially those located close to large seabird breeding colonies.

What you see is where you go: visibility influences movement decisions of a forest bird navigating a three-dimensional-structured matrix

Animal spatial behaviour is often presumed to reflect responses to visual cues. However, inference of behaviour in relation to the environment is challenged by the lack of objective methods to identify the information that effectively is available to an animal from a given location. In general, animals are assumed to have unconstrained information on the environment within a detection circle of a certain radius (the perceptual range; PR). However, visual cues are only available up to the first physical obstruction within an animal's PR, making information availability a function of an animal's location within the physical environment (the effective visual perceptual range; EVPR). By using LiDAR data and viewshed analysis, we modelled forest birds' EVPRs at each step along a movement path. We found that the EVPR was on average 0.063% that of an unconstrained PR and, by applying a step-selection analysis, that individuals are 1.55 times more likely to move to a tree within their EVPR than to an equivalent tree outside it. This demonstrates that behavioural choices can be substantially impacted by the characteristics of an individual's EVPR and highlights that inferences made from movement data may be improved by accounting for the EVPR.

Multi-scale habitat assessment of pronghorn migration routes

We studied the habitat selection of pronghorn (Antilocapra americana) during seasonal migration; an important period in an animal's annual cycle associated with broad-scale movements. We further decompose our understanding of migration habitat itself as the product of both broad- and fine-scale behavioral decisions and take a multi-scale approach to assess pronghorn spring and fall migration across the transboundary Northern Sagebrush Steppe region. We used a hierarchical habitat selection framework to assess a suite of natural and anthropogenic features that have been shown to influence selection patterns of pronghorn at both broad (migratory neighborhood) and fine (migratory pathway) scales. We then combined single-scale predictions into a scale-integrated step selection function (ISSF) map to assess its effectiveness in predicting migration route habitat. During spring, pronghorn selected for native grasslands, areas of high forage productivity (NDVI), and avoided human activity (i.e., roads and oil and natural gas wells). During fall, pronghorn selected for native grasslands, larger streams and rivers, and avoided roads. We detected avoidance of paved roads, unpaved roads, and wells at broad spatial scales, but no response to these features at fine scales. In other words, migratory pronghorn responded more strongly to anthropogenic features when selecting a broad neighborhood through which to migrate than when selecting individual steps along their migratory pathway. Our results demonstrate that scales of migratory route selection are hierarchically nested within each other from broader (second-order) to finer scales (third-order). In addition, we found other variables during particular migratory periods (i.e., native grasslands in spring) were selected for across scales indicating their importance for pronghorn. The mapping of ungulate migration habitat is a topic of high conservation relevance. In some applications, corridors are mapped according to telemetry location data from a sample of animals, with the assumption that the sample adequately represents habitat for the entire population. Our use of multi-scale modelling to predict resource selection during migration shows promise and may offer another relevant alternative for use in future conservation planning and land management decisions where telemetry-based sampling is unavailable or incomplete.

Inferring an animal's environment through biologging: quantifying the environmental influence on animal movement

BACKGROUND

Animals respond to environmental variation by changing their movement in a multifaceted way. Recent advancements in biologging increasingly allow for detailed measurements of the multifaceted nature of movement, from descriptors of animal movement trajectories (e.g., using GPS) to descriptors of body part movements (e.g., using tri-axial accelerometers). Because this multivariate richness of movement data complicates inference on the environmental influence on animal movement, studies generally use simplified movement descriptors in statistical analyses. However, doing so limits the inference on the environmental influence on movement, as this requires that the multivariate richness of movement data can be fully considered in an analysis.

METHODS

We propose a data-driven analytic framework, based on existing methods, to quantify the environmental influence on animal movement that can accommodate the multifaceted nature of animal movement. Instead of fitting a simplified movement descriptor to a suite of environmental variables, our proposed framework centres on predicting an environmental variable from the full set of multivariate movement data. The measure of fit of this prediction is taken to be the metric that quantifies how much of the environmental variation relates to the multivariate variation in animal movement. We demonstrate the usefulness of this framework through a case study about the influence of grass availability and time since milking on cow movements using machine learning algorithms.

RESULTS

We show that on a one-hour timescale 37% of the variation in grass availability and 33% of time since milking influenced cow movements. Grass availability mostly influenced the cows' neck movement during grazing, while time since milking mostly influenced the movement through the landscape and the shared variation of accelerometer and GPS data (e.g., activity patterns). Furthermore, this framework proved to be insensitive to spurious correlations between environmental variables in quantifying the influence on animal movement.

CONCLUSIONS

Not only is our proposed framework well-suited to study the environmental influence on animal movement; we argue that it can also be applied in any field that uses multivariate biologging data, e.g., animal physiology, to study the relationships between animals and their environment.

SUPPLEMENTARY INFORMATION

Supplementary information accompanies this paper at 10.1186/s40462-020-00228-4.

Behavioral modifications by a large-northern herbivore to mitigate warming conditions

BACKGROUND

Temperatures in arctic-boreal regions are increasing rapidly and pose significant challenges to moose (Alces alces), a heat-sensitive large-bodied mammal. Moose act as ecosystem engineers, by regulating forest carbon and structure, below ground nitrogen cycling processes, and predator-prey dynamics. Previous studies showed that during hotter periods, moose displayed stronger selection for wetland habitats, taller and denser forest canopies, and minimized exposure to solar radiation. However, previous studies regarding moose behavioral thermoregulation occurred in Europe or southern moose range in North America. Understanding whether ambient temperature elicits a behavioral response in high-northern latitude moose populations in North America may be increasingly important as these arctic-boreal systems have been warming at a rate two to three times the global mean.

METHODS

We assessed how Alaska moose habitat selection changed as a function of ambient temperature using a step-selection function approach to identify habitat features important for behavioral thermoregulation in summer (June-August). We used Global Positioning System telemetry locations from four populations of Alaska moose (n = 169) from 2008 to 2016. We assessed model fit using the quasi-likelihood under independence criterion and conduction a leave-one-out cross validation.

RESULTS

Both male and female moose in all populations increasingly, and nonlinearly, selected for denser canopy cover as ambient temperature increased during summer, where initial increases in the conditional probability of selection were initially sharper then leveled out as canopy density increased above ~ 50%. However, the magnitude of selection response varied by population and sex. In two of the three populations containing both sexes, females demonstrated a stronger selection response for denser canopy at higher temperatures than males. We also observed a stronger selection response in the most southerly and northerly populations compared to populations in the west and central Alaska.

CONCLUSIONS

The impacts of climate change in arctic-boreal regions increase landscape heterogeneity through processes such as increased wildfire intensity and annual area burned, which may significantly alter the thermal environment available to an animal. Understanding habitat selection related to behavioral thermoregulation is a first step toward identifying areas capable of providing thermal relief for moose and other species impacted by climate change in arctic-boreal regions.

Using movement to inform conservation corridor design for Mojave desert tortoise

BACKGROUND

Preserving corridors for movement and gene flow among populations can assist in the recovery of threatened and endangered species. As human activity continues to fragment habitats, characterizing natural corridors is important in establishing and maintaining connectivity corridors within the anthropogenic development matrix. The Mojave desert tortoise (Gopherus agassizii) is a threatened species occupying a variety of habitats in the Mojave and Colorado Deserts. Desert tortoises have been referred to as corridor-dwellers, and understanding how they move within suitable habitat can be crucial to defining corridors that will sustain sufficient gene flow to maintain connections among populations amidst the increases in human development.

METHODS

To elucidate how tortoises traverse available habitat and interact with potentially inhospitable terrain and human infrastructure, we used GPS dataloggers to document fine-scale movement of individuals and estimate home ranges at ten study sites along the California/Nevada border. Our sites encompass a variety of habitats, including mountain passes that serve as important natural corridors connecting neighboring valleys, and are impacted by a variety of linear anthropogenic features. We used path selection functions to quantify tortoise movements and develop resistance surfaces based on landscape characteristics including natural features, anthropogenic alterations, and estimated home ranges with autocorrelated kernel density methods. Using the best supported path selection models and estimated home ranges, we determined characteristics of known natural corridors and compared them to mitigation corridors (remnant habitat patches) that have been integrated into land management decisions in the Ivanpah Valley.

RESULTS

Tortoises avoided areas of high slope and low perennial vegetation cover, avoided moving near low-density roads, and traveled along linear barriers (fences and flood control berms).

CONCLUSIONS

We found that mitigation corridors designated between solar facilities should be wide enough to retain home ranges and maintain function. Differences in home range size and movement resistance between our two natural mountain pass corridors align with differences in genetic connectivity, suggesting that not all natural corridors provide the same functionality. Furthermore, creation of mitigation corridors with fences may have unintended consequences and may function differently than natural corridors. Understanding characteristics of corridors with different functionality will help future managers ensure that connectivity is maintained among Mojave desert tortoise populations.

Open-Source 3D Printable GPS Tracker to Characterize the Role of Human Population Movement on Malaria Epidemiology in River Networks: A Proof-of-Concept Study in the Peruvian Amazon

Human movement affects malaria epidemiology at multiple geographical levels; however, few studies measure the role of human movement in the Amazon Region due to the challenging conditions and cost of movement tracking technologies. We developed an open-source low-cost 3D printable GPS-tracker and used this technology in a cohort study to characterize the role of human population movement in malaria epidemiology in a rural riverine village in the Peruvian Amazon. In this pilot study of 20 participants (mean age = 40 years old), 45,980 GPS coordinates were recorded over 1 month. Characteristic movement patterns were observed relative to the infection status and occupation of the participants. Applying two analytical animal movement ecology methods, utilization distributions (UDs) and integrated step selection functions (iSSF), we showed contrasting environmental selection and space use patterns according to infection status. These data suggested an important role of human movement in the epidemiology of malaria in the Peruvian Amazon due to high connectivity between villages of the same riverine network, suggesting limitations of current community-based control strategies. We additionally demonstrate the utility of this low-cost technology with movement ecology analysis to characterize human movement in resource-poor environments.

Seasonal and daily shifts in behavior and resource selection: how a carnivore navigates costly landscapes

The dynamic environmental conditions in highly seasonal systems likely have a strong influence on how species use the landscape. Animals must balance seasonal and daily changes to landscape risk with the underlying resources provided by that landscape. One way to balance the seasonal and daily changes in the costs and benefits of a landscape is through behaviorally-explicit resource selection and temporal partitioning. Here, we test whether resource selection of coyotes (Canis latrans) in Cape Breton Highlands National Park, Nova Scotia, Canada is behaviorally-explicit and responsive to the daily and seasonal variation to presumed costs and benefits of moving on the landscape. We used GPS data and local convex hulls to estimate space use and Hidden Markov Models to estimate three types of movement behavior: encamped, foraging, and traveling. We then used integrated step-selection analysis to investigate behaviorally explicit resource selection across times of day (diurnal, crepuscular, and nocturnal) and season (snow-free and snow). We found that throughout the day and seasonally coyotes shifted foraging behavior and altered behavior and resource choices to avoid moving across what we could be a challenging landscape. These changes in behavior suggest that coyotes have a complex response to land cover, terrain, and linear corridors that are not only scale dependent but also vary by behavior, diel period, and season. By examining the resource selection across three axes (behavior, time of day, and season), we have a more nuanced understanding of how a predator balances the cost and benefits of a stochastic environment.

Novel step selection analyses on energy landscapes reveal how linear features alter migrations of soaring birds

Human modification of landscapes includes extensive addition of linear features, such as roads and transmission lines. These can alter animal movement and space use and affect the intensity of interactions among species, including predation and competition. Effects of linear features on animal movement have seen relatively little research in avian systems, despite ample evidence of their effects in mammalian systems and that some types of linear features, including both roads and transmission lines, are substantial sources of mortality. Here, we used satellite telemetry combined with step selection functions designed to explicitly incorporate the energy landscape (el-SSFs) to investigate the effects of linear features and habitat on movements and space use of a large soaring bird, the golden eagle Aquila chrysaetos, during migration. Our sample consisted of 32 adult eagles tracked for 45 spring and 39 fall migrations from 2014 to 2017. Fitted el-SSFs indicated eagles had a strong general preference for south-facing slopes, where thermal uplift develops predictably, and that these areas are likely important aspects of migratory pathways. el-SSFs also provided evidence that roads and railroads affected movement during both spring and fall migrations, but eagles selected areas near roads to a greater degree in spring compared to fall and at higher latitudes compared to lower latitudes. During spring, time spent near linear features often occurred during slower-paced or stopover movements, perhaps in part to access carrion produced by vehicle collisions. Regardless of the behavioural mechanism of selection, use of these features could expose eagles and other soaring species to elevated risk via collision with vehicles and/or transmission lines. Linear features have previously been documented to affect the ecology of terrestrial species (e.g. large mammals) by modifying individuals' movement patterns; our work shows that these effects on movement extend to avian taxa.

No room to roam: King Cobras reduce movement in agriculture

BACKGROUND

Studying animal movement provides insights into how animals react to land-use changes. As agriculture expands, we can use animal movement to examine how animals change their behaviour in response. Recent reviews show a tendency for mammalian species to reduce movements in response to increased human landscape modification, but reptile movements have not been as extensively studied.

METHODS

We examined movements of a large reptilian predator, the King Cobra (Ophiophagus hannah), in Northeast Thailand. We used a consistent regime of radio telemetry tracking to document movements across protected forest and adjacent agricultural areas. Using dynamic Brownian Bridge Movement Model derived motion variance, Integrated Step-Selection Functions, and metrics of site reuse, we examined how King Cobra movements changed in agricultural areas.

RESULTS

Motion variance values indicated that King Cobra movements increased in forested areas and tended to decrease in agricultural areas. Our Integrated Step-Selection Functions revealed that when moving in agricultural areas King Cobras restricted their movements to remain within vegetated semi-natural areas, often located along the banks of irrigation canals. Site reuse metrics of residency time and number of revisits appeared unaffected by distance to landscape features (forests, semi-natural areas, settlements, water bodies, and roads). Neither motion variance nor reuse metrics were consistently affected by the presence of threatening landscape features (e.g. roads, human settlements), suggesting that King Cobras will remain in close proximity to threats, provided habitat patches are available.

CONCLUSIONS

Although King Cobras displayed individual heterogeneity in their response to agricultural landscapes, the overall trend suggested reduced movements when faced with fragmented habitat patches embedded in an otherwise inhospitable land-use matrix. Movement reductions are consistent with findings for mammals and forest specialist species.

Wolf habitat selection when sympatric or allopatric with brown bears in Scandinavia

Habitat selection of animals depends on factors such as food availability, landscape features, and intra- and interspecific interactions. Individuals can show several behavioral responses to reduce competition for habitat, yet the mechanisms that drive them are poorly understood. This is particularly true for large carnivores, whose fine-scale monitoring is logistically complex and expensive. In Scandinavia, the home-range establishment and kill rates of gray wolves (Canis lupus) are affected by the coexistence with brown bears (Ursus arctos). Here, we applied resource selection functions and a multivariate approach to compare wolf habitat selection within home ranges of wolves that were either sympatric or allopatric with bears. Wolves selected for lower altitudes in winter, particularly in the area where bears and wolves are sympatric, where altitude is generally higher than where they are allopatric. Wolves may follow the winter migration of their staple prey, moose (Alces alces), to lower altitudes. Otherwise, we did not find any effect of bear presence on wolf habitat selection, in contrast with our previous studies. Our new results indicate that the manifestation of a specific driver of habitat selection, namely interspecific competition, can vary at different spatial-temporal scales. This is important to understand the structure of ecological communities and the varying mechanisms underlying interspecific interactions.

Within Reach? Habitat Availability as a Function of Individual Mobility and Spatial Structuring

Organisms need access to particular habitats for their survival and reproduction. However, even if all necessary habitats are available within the broader environment, they may not all be easily reachable from the position of a single individual. Many species distribution models consider populations in environmental (or niche) space, hence overlooking this fundamental aspect of geographical accessibility. Here, we develop a formal way of thinking about habitat availability in environmental spaces by describing how limitations in accessibility can cause animals to experience a more limited or simply different mixture of habitats than those more broadly available. We develop an analytical framework for characterizing constrained habitat availability based on the statistical properties of movement and environmental autocorrelation. Using simulation experiments, we show that our general statistical representation of constrained availability is a good approximation of habitat availability for particular realizations of landscape-organism interactions. We present two applications of our approach, one to the statistical analysis of habitat preference (using step-selection functions to analyze harbor seal telemetry data) and a second that derives theoretical insights about population viability from knowledge of the underlying environment. Analytical expressions for habitat availability, such as those we develop here, can yield gains in analytical speed, biological realism, and conceptual generality by allowing us to formulate models that are habitat sensitive without needing to be spatially explicit.

Rattlesnake migrations and the implications of thermal landscapes

BACKGROUND

The importance of thermal resources to terrestrial ectotherms has been well documented but less often considered in larger-scale analyses of habitat use and selection, such as those routinely conducted using standard habitat features such as vegetation and physical structure. Selection of habitat based on thermal attributes may be of particular importance for ectothermic species, especially in colder climates. In Canada, Western Rattlesnakes (Crotalus oreganus) reach their northern limits, with limited time to conduct annual migratory movements between hibernacula and summer habitat. We radio-tracked 35 male snakes departing from 10 different hibernacula. We examined coarse-scale differences in migratory movements across the region, and then compared the route of each snake with thermal landscapes and ruggedness GIS maps generated for different periods of the animals' active season.

RESULTS

We observed dichotomous habitat use (grasslands versus upland forests) throughout most of the species' northern range, reflected in different migratory movements of male snakes emanating from different hibernacula. Snakes utilizing higher-elevation forests moved further during the course of their annual migrations, and these snakes were more likely to use warmer areas of the landscape.

CONCLUSION

In addition to thermal benefits, advantages gained from selective migratory patterns may include prey availability and outbreeding. Testing these alternative hypotheses was beyond the scope of this study, and to collect the data to do so will require overcoming certain challenges. Still, insight into migratory differences between rattlesnake populations and the causal mechanism(s) of migrations will improve our ability to assess the implications of landscape change, management, and efficacy of conservation planning. Our findings suggest that such assessments may need to be tailored to individual dens and the migration strategies of their inhabitants. Additionally, local and landscape-scale migration patterns, as detected in this study, will have repercussions for snakes under climate-induced shifts in ecosystem boundaries and thermal regimes.

Arctic avian predators synchronise their spring migration with the northern progression of snowmelt

Migratory species display a range of migration patterns between irruptive (facultative) to regular (obligate), as a response to different predictability of resources. In the Arctic, snow directly influences resource availability. The causes and consequences of different migration patterns of migratory species as a response to the snow conditions remains however unexplored. Birds migrating to the Arctic are expected to follow the spring snowmelt to optimise their arrival time and select for snow-free areas to maximise prey encounter en-route. Based on large-scale movement data, we compared the migration patterns of three top predator species of the tundra in relation to the spatio-temporal dynamics of snow cover. The snowy owl, an irruptive migrant, the rough-legged buzzard, with an intermediary migration pattern, and the peregrine falcon as a regular migrant, all followed, as expected, the spring snowmelt during their migrations. However, the owl stayed ahead, the buzzard stayed on, and the falcon stayed behind the spatio-temporal peak in snowmelt. Although none of the species avoided snow-covered areas, they presumably used snow presence as a cue to time their arrival at their breeding grounds. We show the importance of environmental cues for species with different migration patterns.

Oceanographic drivers of winter habitat use in Cassin's Auklets

Reduced prey abundance and severe weather can lead to a greater risk of mortality for seabirds during the non-breeding winter months. Resource patterns in some regions are shifting and becoming more variable in relation to past conditions, potentially further impacting survival and carryover to the breeding season. As animal tracking technologies and methods to analyze movement data have advanced, it has become increasingly feasible to draw fine-scale inference about how environmental variation affects foraging behavior and habitat use of seabirds during this critical period. Here, we used archival light-sensing tags to evaluate how interannual variation in oceanography affected the winter distribution of Cassin's Auklets from Southeast Farallon Island, California. Thirty-five out of 93 geolocators deployed from 2015 to 2017 were recovered and successfully recorded light-level data, from which geographic positions were estimated. Step-selection functions were applied to identify environmental covariates that best explained winter movement decisions and habitat use, revealing Cassin's Auklets dispersed farther from the colony during a winter with warm SST anomalies, but remained more centralized near the breeding colony during two average winters. Movement patterns were driven by avoidance of areas with higher sea surface temperatures and possible limits of dispersal from the breeding colony, and selection for areas with well-defined mesoscale fronts and cooler surface waters. Through multiple years of tagging and the application of step-selection functions, a robust and widely applied approach for analyzing animal movement in terrestrial species, we show how interannual differences in the movement patterns of a small seabird are driven by oceanographic variability across years. Understanding the winter habitat use of seabirds can help inform changes in population structure and measures of reproductive success, aiding managers in determining potential causes of breeding failures.

Killer whale presence drives bowhead whale selection for sea ice in Arctic seascapes of fear

The effects of predator intimidation on habitat use and behavior of prey species are rarely quantified for large marine vertebrates over ecologically relevant scales. Using state space movement models followed by a series of step selection functions, we analyzed movement data of concurrently tracked prey, bowhead whales (Balaena mysticetus; n = 7), and predator, killer whales (Orcinus orca; n = 3), in a large (63,000 km²), partially ice-covered gulf in the Canadian Arctic. Our analysis revealed pronounced predator-mediated shifts in prey habitat use and behavior over much larger spatiotemporal scales than previously documented in any marine or terrestrial ecosystem. The striking shift from use of open water (predator-free) to dense sea ice and shorelines (predators present) was exhibited gulf-wide by all tracked bowheads during the entire 3-wk period killer whales were present, constituting a nonconsumptive effect (NCE) with unknown energetic or fitness costs. Sea ice is considered quintessential habitat for bowhead whales, and ice-covered areas have frequently been interpreted as preferred bowhead foraging habitat in analyses that have not assessed predator effects. Given the NCEs of apex predators demonstrated here, however, unbiased assessment of habitat use and distribution of bowhead whales and many marine species may not be possible without explicitly incorporating spatiotemporal distribution of predation risk. The apparent use of sea ice as a predator refuge also has implications for how bowhead whales, and likely other ice-associated Arctic marine mammals, will cope with changes in Arctic sea ice dynamics as historically ice-covered areas become increasingly ice-free during summer.

Effects of linear features on resource selection and movement rates of wood bison (Bison bison athabascae)

Human-mediated disturbances can lead to novel environmental features that can affect native biota beyond simple habitat loss. In boreal forests of western Canada, linear features (LFs; e.g., pipelines, seismic lines, and roads) are known to alter behaviour, movements, and interactions among species. Understanding LF impacts on native species has therefore been a management priority. Here, we investigate how LFs affect the spatial behaviour of wood bison (Bison bison athabascae Rhoads, 1898), which are designated as “threatened” in Canada. Using data collected from the Ronald Lake population in northeastern Alberta, we assessed how LFs influenced habitat selection and movement of bison by testing support among three hypotheses explaining whether LFs (i) increased forage availability, (ii) enhanced movement efficiency, or (iii) increased predation risk. Results supported the movement efficiency hypothesis as bison were generally ambivalent toward LFs, showing weak selection or avoidance depending on land-cover type, but moved slightly faster when on them. These findings contrast with avoidance behaviours reported for sympatric woodland caribou (Rangifer tarandus caribou (Gmelin, 1788)), which are also “threatened.” Our results should inform critical habitat decisions for wood bison, but we caution that further research is needed to understand the effects of LFs on bison demography.

Seeking snow and breathing hard - Behavioral tactics in high elevation mammals to combat warming temperatures

The world glaciers and areas of persistent summer snowpack are being lost due to warming temperatures. For cold-adapted species, habitat features may offer opportunities for cooling during summer heat yet the loss of snow and ice may compromise derived thermoregulatory benefits. Herein we offer insights about habitat selection for snow and the extent to which other behavioral adjustments reduce thermal debt among high elevation mammals. Specifically, we concentrate on respiration in mountain goats (Oreamnos americanus), a species whose native distribution is currently tied to northern mountain ranges of North America, where large patches of persistent summer snow are declining, and which became extinct during geologically warmer epochs. To examine sensitivity to possible thermal stressors and use of summer snow cover, we tracked marked and unmarked mountain goats in Glacier National Park, Montana, USA, to test hypotheses about selection for cold microclimates including shade and snow during periods of relatively high temperature. To understand functional responses of habitat choices, we measured microhabitat temperatures and a component of goat physiology–breaths per minute–as an index for metabolic expenditure. Individuals 1) selected areas closer to snow on warmer summer days, and 2) on snow had a 15% mean reduction in respiration when accounting for other factors, which suggests remnant snow plays an important role in mediating effects of air temperature. The use of shade was not as an important variable in models explaining respiration. Despite the loss of 85% of glaciers in in Glacier National Park, summer’s remnant snow patches are an important reservoir by which animals reduce heat stress and potential hyperthermia. Our findings, when contextualized with behavioral strategies deployed by other high elevation mammalian taxa help frame how ambient temperatures may be modulated, and they offer a direct way by which to assess susceptibility to increasing heat in cold-adapted species.

Habitat heterogeneity and social factors drive behavioral plasticity in giraffe herd-size dynamics

Behavioral plasticity, or the mechanism by which an organism can adjust its behavior in response to exogenous change, has been highlighted as a potential buffer against extinction risk. Giraffes (Giraffa spp.) are gregarious, long-lived, highly mobile megaherbivores with a large brain size, characteristics that have been associated with high levels of behavioral plasticity. However, while there has been a recent focus on genotypic variability and morphological differences among giraffe populations, there has been relatively little discussion centered on behavioral flexibility within giraffe populations. In large wild herbivores, one measure of behavioral plasticity is the ability to adjust herd size in line with local environmental conditions. Here, we examine whether a genetically isolated population of Angolan giraffes (G. g. angolensis) in a heterogeneous environment adjust their herd sizes in line with spatiotemporal variation in habitat. Our results suggest that ecological factors play a role in driving herd size, but that social factors also shape and stabilize herd-size dynamics. Specifically, we found that 1) mixed-sex herds were larger than single-sex herds, suggesting that sexual composition of herds played a role in driving herd size; 2) the presence of young did not influence herd size, suggesting that giraffes did not make use of the dilution effect to safeguard their young from predation; and 3) there was a strong relationship between herd size and spatial, but not seasonal, variation in food biomass availability, suggesting stability in herd sizes over time, but temporary variation in line with resource availability. These findings indicate that giraffes adjust herd size in line with local exogenous factors, signaling high behavioral plasticity, but also suggest that this mechanism operates within the constraints of the social determinants of giraffe herd size.

Deer movement and resource selection during Hurricane Irma: implications for extreme climatic events and wildlife

Extreme climatic events (ECEs) are increasing in frequency and intensity and this necessitates understanding their influence on organisms. Animal behaviour may mitigate the effects of ECEs, but field studies are rare because ECEs are infrequent and unpredictable. Hurricane Irma made landfall in southwestern Florida where we were monitoring white-tailed deer (Odocoileus virginianus seminolus) with GPS collars. We report on an opportunistic case study of behavioural responses exhibited by a large mammal during an ECE, mitigation strategies for reducing the severity of the ECE effects, and the demographic effect of the ECE based on known-fate of individual animals. Deer altered resource selection by selecting higher elevation pine and hardwood forests and avoiding marshes. Most deer left their home ranges during Hurricane Irma, and the probability of leaving was inversely related to home range area. Movement rates increased the day of the storm, and no mortality was attributed to Hurricane Irma. We suggest deer mobility and refuge habitat allowed deer to behaviourally mitigate the negative effects of the storm, and ultimately, aid in survival. Our work contributes to the small but growing body of literature linking behavioural responses exhibited during ECEs to survival, which cumulatively will provide insight for predictions of a species resilience to ECEs and improve our understanding of how behavioural traits offset the negative impacts of global climate change.

Burrow usage patterns and decision-making in meerkat groups

Choosing suitable sleeping sites is a common challenge faced by animals across a range of taxa, with important implications for the space usage patterns of individuals, groups, and ultimately populations. A range of factors may affect these decisions, including access to resources nearby, shelter from the elements, safety from predators, territorial defense, and protection of offspring. We investigated the factors driving patterns of sleeping site use in wild Kalahari meerkats (Suricata suricatta), a cooperatively breeding, territorial mongoose species that forages on scattered resources and makes use of multiple sleeping sites (burrows). We found that meerkat groups used some burrows much more often than others. In particular, large burrows near the center of the territory were used more often than small and peripheral burrows, and groups became even more biased toward central burrows when rearing pups. Meerkats also used their sleeping burrows in a nonrandom order. When they changed sleeping burrows, they moved disproportionately to nearby burrows but did not always select the closest burrow. Burrow decisions also reflected responses to short-term conditions: rates of switching burrows increased after encounters with predators and when resources were depleted, whereas group splits were associated with a reduced probability of switching. The group’s dominant female appeared to have disproportionate influence over burrow decisions, as groups were more likely to switch burrows when her foraging success was low. Our results link behavioral and movement ecology to show that a multitude of environmental and social factors shape daily group decisions of where to spend the night.

Navigating through the r packages for movement

The advent of miniaturized biologging devices has provided ecologists with unprecedented opportunities to record animal movement across scales, and led to the collection of ever-increasing quantities of tracking data. In parallel, sophisticated tools have been developed to process, visualize and analyse tracking data; however, many of these tools have proliferated in isolation, making it challenging for users to select the most appropriate method for the question in hand. Indeed, within the r software alone, we listed 58 packages created to deal with tracking data or 'tracking packages'. Here, we reviewed and described each tracking package based on a workflow centred around tracking data (i.e. spatio-temporal locations (x, y, t)), broken down into three stages: pre-processing, post-processing and analysis, the latter consisting of data visualization, track description, path reconstruction, behavioural pattern identification, space use characterization, trajectory simulation and others. Supporting documentation is key to render a package accessible for users. Based on a user survey, we reviewed the quality of packages' documentation and identified 11 packages with good or excellent documentation. Links between packages were assessed through a network graph analysis. Although a large group of packages showed some degree of connectivity (either depending on functions or suggesting the use of another tracking package), one third of the packages worked in isolation, reflecting a fragmentation in the r movement-ecology programming community. Finally, we provide recommendations for users when choosing packages, and for developers to maximize the usefulness of their contribution and strengthen the links within the programming community.

Moose, caribou, and fire: have we got it right yet?

Natural disturbance plays a key role in shaping community dynamics. Within Canadian boreal forests, the dominant form of natural disturbance is fire, and its effects are thought to influence the dynamics between moose (Alces alces (Linnaeus, 1758)) and the boreal ecotype of woodland caribou (Rangifer tarandus caribou (Gmelin, 1788)). Boreal caribou are considered “threatened” and population declines are attributed, at least in part, to disturbance-mediated apparent competition (DMAC) with moose. Here, we tested a primary prediction of the DMAC hypothesis: that moose respond positively to burns within and adjacent to the caribou range. We assessed moose selection for ≤25-year-old burns (when selection is predicted to be strongest) at multiple spatial scales and evaluated whether moose density was correlated with the extent of ≤40-year-old burns (a time frame predicted to negatively affect caribou). Against expectation, moose showed avoidance and low use of ≤25-year-old burns at all scales, regardless of burn age, season, and type of land cover burned. These findings mirrored the demographic response, as we found no correlation between ≤40-year-old burns and moose density. By contradicting the prevailing hypothesis linking fires to caribou population declines, our results highlight the need to understand regional variation in disturbance impacts on caribou populations.

Optimizing the use of biologgers for movement ecology research

The paradigm-changing opportunities of biologging sensors for ecological research, especially movement ecology, are vast, but the crucial questions of how best to match the most appropriate sensors and sensor combinations to specific biological questions and how to analyse complex biologging data, are mostly ignored. Here, we fill this gap by reviewing how to optimize the use of biologging techniques to answer questions in movement ecology and synthesize this into an Integrated Biologging Framework (IBF). We highlight that multisensor approaches are a new frontier in biologging, while identifying current limitations and avenues for future development in sensor technology. We focus on the importance of efficient data exploration, and more advanced multidimensional visualization methods, combined with appropriate archiving and sharing approaches, to tackle the big data issues presented by biologging. We also discuss the challenges and opportunities in matching the peculiarities of specific sensor data to the statistical models used, highlighting at the same time the large advances which will be required in the latter to properly analyse biologging data. Taking advantage of the biologging revolution will require a large improvement in the theoretical and mathematical foundations of movement ecology, to include the rich set of high-frequency multivariate data, which greatly expand the fundamentally limited and coarse data that could be collected using location-only technology such as GPS. Equally important will be the establishment of multidisciplinary collaborations to catalyse the opportunities offered by current and future biologging technology. If this is achieved, clear potential exists for developing a vastly improved mechanistic understanding of animal movements and their roles in ecological processes and for building realistic predictive models.