A taste of space: Remote animal observations and discrete-choice models provide new insights into foraging and density dynamics for a large subarctic herbivore

Competition for resources and space can drive forage selection of large herbivores from the bite through the landscape scale. Animal behaviour and foraging patterns are also influenced by abiotic and biotic factors. Fine-scale mechanisms of density-dependent foraging at the bite scale are likely consistent with density-dependent behavioural patterns observed at broader scales, but few studies have directly tested this assertion. Here, we tested if space use intensity, a proxy of spatiotemporal density, affects foraging mechanisms at fine spatial scales similarly to density-dependent effects observed at broader scales in caribou. We specifically assessed how behavioural choices are affected by space use intensity and environmental processes using behavioural state and forage selection data from caribou (Rangifer tarandus granti) observed from GPS video-camera collars using a multivariate discrete-choice modelling framework. We found that the probability of eating shrubs increased with increasing caribou space use intensity and cover of Salix spp. shrubs, whereas the probability of eating lichen decreased. Insects also affected fine-scale foraging behaviour by reducing the overall probability of eating. Strong eastward winds mitigated negative effects of insects and resulted in higher probabilities of eating lichen. At last, caribou exhibited foraging functional responses wherein their probability of selecting each food type increased as the availability (% cover) of that food increased. Space use intensity signals of fine-scale foraging were consistent with density-dependent responses observed at larger scales and with recent evidence suggesting declining reproductive rates in the same caribou population. Our results highlight potential risks of overgrazing on sensitive forage species such as lichen. Remote investigation of the functional responses of foraging behaviours provides exciting future applications where spatial models can identify high-quality habitats for conservation.

The coastal breeding habitat of Bank Swallows (Riparia riparia) in an Atlantic Canada National Park: assessing habitat use in relation to availability

Understanding bird habitat selection has become a priority in conservation, particularly for bird species facing long-term population declines. The Bank Swallow (Riparia riparia Linnaeus, 1758), a species whose eastern distribution limit is in Atlantic Canada, declined by 98% between 1970 and 2011, prompting its listing as a Threatened species in 2017. Its decline is hypothesized to be due in part to habitat loss and, hence, this study aimed to identify critical habitats within a protected area along Prince Edward Island. We used two types of survey to examine the availability and use of three breeding habitats: dunes, glacial till and sandstone cliffs. A goodness-of-fit test revealed that the habitats were not used in proportion to their availability. Among them sandstone cliffs and, to a lesser extent, till cliffs, were used significantly more than expected (i.e., selected). Instead, sand dunes were used less (i.e., avoided) as a breeding habitat. These results suggest that Bank Swallow selection is driven by characteristics associated with the sandstone and till habitats, and more attention and possibly protection should be given to them. Further studies should also explore whether similar patterns of selection are evident in the region’s historical records and in similar coastline areas.

The contribution of plant spatial arrangement to bumble bee flower constancy

Floral constancy of foraging bees influences plant reproduction. Constancy as observed in nature arises from at least four distinct mechanisms frequently confounded in the literature: context-independent preferences for particular plant species, preferential visitation to the same species as the previous plant visited (simple constancy), the spatial arrangement of plants, and the relative abundances of co-flowering species. To disentangle these mechanisms, we followed individual bee flight paths within patches where all flowering plants were mapped, and we used step selection models to estimate how each mechanism influences the probability of selecting any particular plant given the available plants in a multi-species community. We found that simple constancy was positive: bees preferred to visit the same species sequentially. In addition, bees preferred to travel short distances and maintain their direction of travel between plants. After accounting for distance, we found no significant effect of site-level plant relative abundances on bee foraging choices. To explore the importance of the spatial arrangement of plants for bee foraging choices, we compared our full model containing all parameters to one with spatial arrangement removed. Due to bees' tendency to select nearby plants, combined with strong intraspecific plant clumping, spatial arrangement was responsible for about 50% of the total observed constancy. Our results suggest that floral constancy may be overestimated in studies that do not account for the spatial arrangement of plants, especially in systems with intraspecific plant clumping. Plant spatial patterns at within-site scales are important for pollinator foraging behavior and pollination success.

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

Habitat selection is a fundamental animal behavior that shapes a wide range of ecological processes, including animal movement, nutrient transfer, trophic dynamics and population distribution. Although habitat selection has been a focus of ecological studies for decades, technological, conceptual and methodological advances over the last 20 yr have led to a surge in studies addressing this process. Despite the substantial literature focused on quantifying the habitat-selection patterns of animals, there is a marked lack of guidance on best analytical practices. The conceptual foundations of the most commonly applied modeling frameworks can be confusing even to those well versed in their application. Furthermore, there has yet to be a synthesis of the advances made over the last 20 yr. Therefore, there is a need for both synthesis of the current state of knowledge on habitat selection, and guidance for those seeking to study this process. Here, we provide an approachable overview and synthesis of the literature on habitat-selection analyses (HSAs) conducted using selection functions, which are by far the most applied modeling framework for understanding the habitat-selection process. This review is purposefully non-technical and focused on understanding without heavy mathematical and statistical notation, which can confuse many practitioners. We offer an overview and history of HSAs, describing the tortuous conceptual path to our current understanding. Through this overview, we also aim to address the areas of greatest confusion in the literature. We synthesize the literature outlining the most exciting conceptual advances in the field of habitat-selection modeling, discussing the substantial ecological and evolutionary inference that can be made using contemporary techniques. We aim for this paper to provide clarity for those navigating the complex literature on HSAs while acting as a reference and best practices guide for practitioners.

Seasonal food preferences and group activity pattern of Blackbuck Antilope cervicapra (L., 1758) (Mammalia: Cetartiodactyla: Bovidae) in a semi-arid region of western Haryana, India

To evaluate food preferences and group activity patterns, a fragmented population of Blackbuck Antilope cervicapra was selected for observation in a semi-arid ecosystem of western Haryana. A field survey was conducted fortnightly, from dawn to dusk, between September 2019 and August 2020, covering every season. Scan sampling and quadrat methods were used to record data on group size and vegetation. Group sizes ranged from 3 to 72 individuals. Based on visual observation, blackbuck seasonally consumed 26 species belonging to 25 families with varied preferences, out of a total of 53 plant species documented from the study site. Some plant species with high medicinal and therapeutic values were preferred, including Artemisia scoparia, Cucumis callous, Ziziphus jujuba, and Ziziphus nummularia. Unlike most herbivores, Blackbuck also consumed the toxic and medicinally rich Calotropis procera. We suggest that zoos which house blackbuck include these preferred wild plant species in their diet. Observations on group activity were analyzed on hourly, monthly and seasonal bases, and converted into time percentages. Group foraging activity was at a maximum in the monsoon (62%) and minimum in winter (50%), followed by resting: maximum in winter (21%) and minimum (12%) in monsoon, largely influenced by food availability. Foraging/walking ratio was at a maximum (5.2) in monsoon and minimum (3.1) in winter, and was correlated with the number of group sightings (maximum in winter and minimum in monsoon) in nearby farmland, when the animals faced food scarcity in their natural habitat and fed on crops. 

Aerial survey estimates of polar bears and their tracks in the Chukchi Sea

Polar bears are of international conservation concern due to climate change but are difficult to study because of low densities and an expansive, circumpolar distribution. In a collaborative U.S.-Russian effort in spring of 2016, we used aerial surveys to detect and estimate the abundance of polar bears on sea ice in the Chukchi Sea. Our surveys used a combination of thermal imagery, digital photography, and human observations. Using spatio-temporal statistical models that related bear and track densities to physiographic and biological covariates (e.g., sea ice extent, resource selection functions derived from satellite tags), we predicted abundance and spatial distribution throughout our study area. Estimates of 2016 abundance ([Formula: see text]) ranged from 3,435 (95% CI: 2,300-5,131) to 5,444 (95% CI: 3,636-8,152) depending on the proportion of bears assumed to be missed on the transect line during Russian surveys (g(0)). Our point estimates are larger than, but of similar magnitude to, a recent estimate for the period 2008-2016 ([Formula: see text]; 95% CI 1,522-5,944) derived from an integrated population model applied to a slightly smaller area. Although a number of factors (e.g., equipment issues, differing platforms, low sample sizes, size of the study area relative to sampling effort) required us to make a number of assumptions to generate estimates, it establishes a useful lower bound for abundance, and suggests high spring polar bear densities on sea ice in Russian waters south of Wrangell Island. With future improvements, we suggest that springtime aerial surveys may represent a plausible avenue for studying abundance and distribution of polar bears and their prey over large, remote areas.

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

Habitat‐selection analyses allow researchers to link animals to their environment via habitat‐selection or step‐selection functions, and are commonly used to address questions related to wildlife management and conservation efforts. Habitat‐selection analyses that incorporate movement characteristics, referred to as integrated step‐selection analyses, are particularly appealing because they allow modelling of both movement and habitat‐selection processes.

Despite their popularity, many users struggle with interpreting parameters in habitat‐selection and step‐selection functions. Integrated step‐selection analyses also require several additional steps to translate model parameters into a full‐fledged movement model, and the mathematics supporting this approach can be challenging for many to understand.

Using simple examples, we demonstrate how weighted distribution theory and the inhomogeneous Poisson point process can facilitate parameter interpretation in habitat‐selection analyses. Furthermore, we provide a ‘how to’ guide illustrating the steps required to implement integrated step‐selection analyses using the amt package

By providing clear examples with open‐source code, we hope to make habitat‐selection analyses more understandable and accessible to end users.

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.

Personality differences in the selection of dynamic refugia have demographic consequences for a winter-adapted bird

For overwintering species, individuals' ability to find refugia from inclement weather and predators probably confers strong fitness benefits. How animals use their environment can be mediated by their personality (e.g. risk-taking), but does personality mediate how overwintering species select refugia? Snow cover is a dynamic winter characteristic that can influence crypsis or provide below-the-snow refugia. We explored how wintering ruffed grouse (Bonasa umbellus) selected snow roosting sites, a behaviour that reduces stress and cold exposure. We linked selection for approximately 700 roosts with survival of 42 grouse, and showed that grouse generally selected deeper snow and warmer areas. Grouse found in shallow snow were less likely to survive winter. However, individuals that selected deep snow improved their survival, suggesting that demographic consequences of selecting winter refugia are mediated by differences in personality. Our study provides a crucial, and seldom addressed, link between personality in resource selection and resulting demographic consequences.

Predicting population change from models based on habitat availability and utilization

The need to understand the impacts of land management for conservation, agriculture and disease prevention are driving demand for new predictive ecology approaches that can reliably forecast future changes in population size. Currently, although the link between habitat composition and animal population dynamics is undisputed, its function has not been quantified in a way that enables accurate prediction of population change in nature. Here, using 12 house sparrow colonies as a proof-of-concept, we apply recent theoretical advances to predict population growth or decline from detailed data on habitat composition and habitat selection. We show, for the first time, that statistical population models using derived covariates constructed from parametric descriptions of habitat composition and habitat selection can explain an impressive 92% of observed population variation. More importantly, they provide excellent predictive power under cross-validation, anticipating 81% of variability in population change. These models may be embedded in readily available generalized linear modelling frameworks, allowing their rapid application to field systems. Furthermore, we use optimization on our sample of sparrow colonies to demonstrate how such models, linking populations to their habitats, permit the design of practical and environmentally sound habitat manipulations for managing populations.

Are polar bear habitat resource selection functions developed from 1985-1995 data still useful?

Greenhouse-gas-induced warming in the Arctic has caused declines in sea ice extent and changed its composition, raising concerns by all circumpolar nations for polar bear conservation.Negative impacts have been observed in three well-studied polar bear subpopulations. Most subpopulations, however, receive little or no direct monitoring, hence, resource selection functions (RSF) may provide a useful proxy of polar bear distributions. However, the efficacy of RSFs constructed from past data, that is, reference RSFs, may be degraded under contemporary conditions, especially in a rapidly changing environment.We assessed published Arctic-wide reference RSFs using tracking data from adult female polar bears captured in the Beaufort Sea. We compared telemetry-derived seasonal distributions of polar bears to RSF-defined optimal sea ice habitat during the period of RSF model development, 1985-1995, and two subsequent periods with diminished sea ice: 1996-2006 and 2007-2016. From these comparisons, we assessed the applicability of the reference RSFs for contemporary polar bear conservation.In the two decades following the 1985-1995 reference period, use and availability of optimal habitat by polar bears declined during the ice melt, ice minimum, and ice growth seasons. During the ice maximum season (i.e., winter), polar bears used the best habitat available, which changed relatively little across the three decades of study. During the ice melt, ice minimum, and ice growth seasons, optimal habitat in areas used by polar bears decreased and was displaced north and east of the Alaska Beaufort Sea coast. As optimal habitat diminished in these seasons, polar bears expanded their range and occupied greater areas of suboptimal habitat.Synthesis and applications: Sea ice declines due to climate change continue to challenge polar bears and their conservation. The distribution of Southern Beaufort Sea polar bears remained similar during the ice maximum season, so the reference RSFs developed from data collected >20 years ago continue to accurately model their winter distribution. In contrast, reference RSFs for the ice transitional and minimum seasons showed diminished predictive efficacy but were useful in revealing that contemporary polar bears have been increasingly forced to use suboptimal habitats during those seasons.

Whooping crane use of riverine stopover sites

Migratory birds like endangered whooping cranes (Grus americana) require suitable nocturnal roost sites during twice annual migrations. Whooping cranes primarily roost in shallow surface water wetlands, ponds, and rivers. All these features have been greatly impacted by human activities, which present threats to the continued recovery of the species. A portion of one such river, the central Platte River, has been identified as critical habitat for the survival of the endangered whooping crane. Management intervention is now underway to rehabilitate habitat form and function on the central Platte River to increase use and thereby contribute to the survival of whooping cranes. The goal of our analyses was to develop habitat selection models that could be used to direct riverine habitat management activities (i.e., channel widening, tree removal, flow augmentation, etc.) along the central Platte River and throughout the species' range. As such, we focused our analyses on two robust sets of whooping crane observations and habitat metrics the Platte River Recovery Implementation Program (Program or PRRIP) and other such organizations could influence. This included channel characteristics such as total channel width, the width of channel unobstructed by dense vegetation, and distance of forest from the edge of the channel and flow-related metrics like wetted width and unit discharge (flow volume per linear meter of wetted channel width) that could be influenced by flow augmentation or reductions during migration. We used 17 years of systematic monitoring data in a discrete-choice framework to evaluate the influence these various metrics have on the relative probability of whooping crane use and found the width of channel unobstructed by dense vegetation and distance to the nearest forest were the best predictors of whooping crane use. Secondly, we used telemetry data obtained from a sample of 38 birds of all ages over the course of seven years, 2010-2016, to evaluate whooping crane use of riverine habitat within the North-central Great Plains, USA. For this second analysis, we focused on the two metrics found to be important predictors of whooping crane use along the central Platte River, unobstructed channel width and distance to nearest forest or wooded area. Our findings indicate resource managers, such as the Program, have the potential to influence whooping crane use of the central Platte River through removal of in-channel vegetation to increase the unobstructed width of narrow channels and through removal of trees along the bank line to increase unforested corridor widths. Results of both analyses also indicated that increases in relative probability of use by whooping cranes did not appreciably increase with unobstructed views ≥200 m wide and unforested corridor widths that were ≥330 m. Therefore, managing riverine sites for channels widths >200 m and removing trees beyond 165 m from the channel's edge would increase costs associated with implementing management actions such as channel and bank-line disking, removing trees, augmenting flow, etc. without necessarily realizing an additional appreciable increase in use by migrating whooping cranes.

Resource-Area-Dependence Analysis: Inferring animal resource needs from home-range and mapping data

An animal's home-range can be expected to encompass the resources it requires for surviving or reproducing. Thus, animals inhabiting a heterogeneous landscape, where resource patches vary in size, shape and distribution, will naturally have home-ranges of varied sizes, so that each home-range encompasses a minimum required amount of a resource. Home-range size can be estimated from telemetry data, and often key resources, or proxies for them such as the areas of important habitat types, can be mapped. We propose a new method, Resource-Area-Dependence Analysis (RADA), which uses a sample of tracked animals and a categorical map to i) infer in which map categories important resources are accessible, ii) within which home range cores they are found, and iii) estimate the mean minimum areas of these map categories required for such resource provision. We provide three examples of applying RADA to datasets of radio-tracked animals from southern England: 15 red squirrels Sciurus vulgaris, 17 gray squirrels S. carolinensis and 114 common buzzards Buteo buteo. The analyses showed that each red squirrel required a mean (95% CL) of 0.48 ha (0.24--0.97) of pine wood within the outermost home-range, each gray squirrel needed 0.34 ha (0.11-1.12) ha of mature deciduous woodland and 0.035-0.046 ha of wheat, also within the outermost home-range, while each buzzard required 0.54 ha (0.35-0.82) of rough ground close to the home-range center and 14 ha (11-17) of meadow within an intermediate core, with 52% of them also relying on 0.41 ha (0.29-0.59) of suburban land near the home-range center. RADA thus provides a useful tool to infer key animal resource requirements during studies of animal movement and habitat use.

Sora (Porzana carolina) autumn migration habitat use

Palustrine wetland management across the USA is often conducted under a moist soil management framework aimed at providing energetic resources for non-breeding waterfowl. Moist soil management techniques typically include seasonal water-level manipulations and mechanical soil disturbance to create conditions conducive to germination and growth of early successional, seed-producing wetland plants. The assumption is that providing stopover and wintering habitat for non-breeding waterfowl will also accommodate life-history needs of a broader suite of migratory waterbirds including shorebirds, wading birds and marsh birds. Although studies of wetlands provide some evidence to support this assumption for shorebirds and wading birds, there is less information on how other marshbirds respond. Sora (Porzana carolina) are a species of migratory rail that depend on wetlands year round as they migrate across North America. It is a species for which the consequences of wetland management decisions directed towards non-breeding waterfowl are unknown. We conducted nocturnal surveys on 10 public properties in Missouri, USA during autumn migration during 2012-2016 to examine sora habitat use in wetland impoundments managed to enhance the production of moist soil vegetation. We found a positive relationship with sora presence and mean water depth and annual moist soil vegetation; sora used, on average, deeper water than was available across surveyed impoundments and used locations with a higher percentage of annual moist soil vegetation than was available. We found a negative relationship with sora use and upland vegetation, woody vegetation and open water. We found sora using deeper water than have previously been reported for autumn migration, and that moist soil management techniques used on Missouri's intensively managed public wetland areas may be compatible with sora autumn migration stopover habitat requirements.

Identifying the critical habitat of Canadian vertebrate species at risk

Identification of critical habitat is central to major conservation laws protecting endangered species in North America and around the world. Yet the actual ecological research that is required to identify which habitats are critical to the survival or recovery of species is rarely discussed and poorly documented. Here we quantitatively assess the information and methods used to identify critical habitat in the recovery strategies of 53 vertebrates at risk in Canada. Of the critical habitat identifications assessed, 17% were based on habitat occupancy information, 28% on habitat characteristics and (or) functions, and 40% assessed habitat suitability by linking functional use and biophysical characteristics. However, only 15% of the recovery strategies we evaluated examined relationships between habitat and population viability, abundance, individual fitness, or survival. Furthermore, the breadth of evidence used to assess critical habitats was weaker among long-lived taxa and did not improve over time. Hence, although any approach used to identify critical habitat is likely to be a step in the right direction in minimally protecting and maintaining habitats supporting critical life-cycle processes, there is a persistent gap between the widely recognized importance of critical habitat and our ability to quantitatively link habitats to population trends and individual fitness.

Resource selection by an ectothermic predator in a dynamic thermal landscape

Predicting the effects of global climate change on species interactions has remained difficult because there is a spatiotemporal mismatch between regional climate models and microclimates experienced by organisms. We evaluated resource selection in a predominant ectothermic predator using a modeling approach that permitted us to assess the importance of habitat structure and local real‐time air temperatures within the same modeling framework. We radio‐tracked 53 western ratsnakes (Pantherophis obsoletus) from 2010 to 2013 in central Missouri, USA, at study sites where this species has previously been linked to prey population demographics. We used Bayesian discrete choice models within an information theoretic framework to evaluate the seasonal effects of fine‐scale vegetation structure and thermal conditions on ratsnake resource selection. Ratsnake resource selection was influenced most by canopy cover, canopy cover heterogeneity, understory cover, and air temperature heterogeneity. Ratsnakes generally preferred habitats with greater canopy heterogeneity early in the active season, and greater temperature heterogeneity later in the season. This seasonal shift potentially reflects differences in resource requirements and thermoregulation behavior. Predicted patterns of space use indicate that ratsnakes preferentially selected open habitats in spring and early summer and forest–field edges throughout the active season. Our results show that downscaled temperature models can be used to enhance our understanding of animal resource selection at scales that can be addressed by managers. We suggest that conservation of snakes or their prey in a changing climate will require consideration of fine‐scale interactions between local air temperatures and habitat structure.

Relative Selection Strength: Quantifying effect size in habitat- and step-selection inference

Habitat‐selection analysis lacks an appropriate measure of the ecological significance of the statistical estimates—a practical interpretation of the magnitude of the selection coefficients. There is a need for a standard approach that allows relating the strength of selection to a change in habitat conditions across space, a quantification of the estimated effect size that can be compared both within and across studies. We offer a solution, based on the epidemiological risk ratio, which we term the relative selection strength (RSS). For a “used‐available” design with an exponential selection function, the RSS provides an appropriate interpretation of the magnitude of the estimated selection coefficients, conditional on all other covariates being fixed. This is similar to the interpretation of the regression coefficients in any multivariable regression analysis. Although technically correct, the conditional interpretation may be inappropriate when attempting to predict habitat use across a given landscape. Hence, we also provide a simple graphical tool that communicates both the conditional and average effect of the change in one covariate. The average‐effect plot answers the question: What is the average change in the space use probability as we change the covariate of interest, while averaging over possible values of other covariates? We illustrate an application of the average‐effect plot for the average effect of distance to road on space use for elk (Cervus elaphus) during the hunting season. We provide a list of potentially useful RSS expressions and discuss the utility of the RSS in the context of common ecological applications.

Diffusion in the presence of a local attracting factor: Theory and interdisciplinary applications

In many complex diffusion processes the drift of random walkers is not caused by an external force, as in the case of Brownian motion, but by local variations of fitness perceived by the random walkers. In this paper, a simple but general framework is presented that describes such a type of random motion and may be of relevance in different problems, such as opinion dynamics, cultural spreading, and animal movement. To this aim, we study the problem of a random walker in d dimensions moving in the presence of a local heterogeneous attracting factor expressed in terms of an assigned position-dependent "attractiveness function." At variance with standard Brownian motion, the attractiveness function introduced here regulates both the advection and diffusion of the random walker, thus providing testable predictions for a specific form of fluctuation-relations. We discuss the relation between the drift-diffusion equation based on the attractiveness function and that describing standard Brownian motion, and we provide some explicit examples illustrating its relevance in different fields, such as animal movement, chemotactic diffusion, and social dynamics.

Robust Inference from Conditional Logistic Regression Applied to Movement and Habitat Selection Analysis

Conditional logistic regression (CLR) is widely used to analyze habitat selection and movement of animals when resource availability changes over space and time. Observations used for these analyses are typically autocorrelated, which biases model-based variance estimation of CLR parameters. This bias can be corrected using generalized estimating equations (GEE), an approach that requires partitioning the data into independent clusters. Here we establish the link between clustering rules in GEE and their effectiveness to remove statistical biases in variance estimation of CLR parameters. The current lack of guidelines is such that broad variation in clustering rules can be found among studies (e.g., 14-450 clusters) with unknown consequences on the robustness of statistical inference. We simulated datasets reflecting conditions typical of field studies. Longitudinal data were generated based on several parameters of habitat selection with varying strength of autocorrelation and some individuals having more observations than others. We then evaluated how changing the number of clusters impacted the effectiveness of variance estimators. Simulations revealed that 30 clusters were sufficient to get unbiased and relatively precise estimates of variance of parameter estimates. The use of destructive sampling to increase the number of independent clusters was successful at removing statistical bias, but only when observations were temporally autocorrelated and the strength of inter-individual heterogeneity was weak. GEE also provided robust estimates of variance for different magnitudes of unbalanced datasets. Our simulations demonstrate that GEE should be estimated by assigning each individual to a cluster when at least 30 animals are followed, or by using destructive sampling for studies with fewer individuals having intermediate level of behavioural plasticity in selection and temporally autocorrelated observations. The simulations provide valuable information to build reliable habitat selection and movement models that allow for robustness of statistical inference without removing excessive amounts of ecological information.

Habitat-mediated timing of migration in polar bears: an individual perspective

Migration phenology is largely determined by how animals respond to seasonal changes in environmental conditions. Our perception of the relationship between migratory behavior and environmental cues can vary depending on the spatial scale at which these interactions are measured. Understanding the behavioral mechanisms behind population‐scale movements requires knowledge of how individuals respond to local cues. We show how time‐to‐event models can be used to predict what factors are associated with the timing of an individual's migratory behavior using data from GPS collared polar bears (Ursus maritimus) that move seasonally between sea ice and terrestrial habitats. We found the concentration of sea ice that bears experience at a local level, along with the duration of exposure to these conditions, was most associated with individual migration timing. Our results corroborate studies that assume thresholds of >50% sea ice concentration are necessary for suitable polar bear habitat; however, continued periods (e.g., days to weeks) of exposure to suboptimal ice concentrations during seasonal melting were required before the proportion of bears migrating to land increased substantially. Time‐to‐event models are advantageous for examining individual movement patterns because they account for the idea that animals make decisions based on an accumulation of knowledge from the landscapes they move through and not simply the environment they are exposed to at the time of a decision. Understanding the migration behavior of polar bears moving between terrestrial and marine habitat, at multiple spatiotemporal scales, will be a major aspect of quantifying observed and potential demographic responses to climate‐induced environmental changes.

Habitat use of bats in relation to wind turbines revealed by GPS tracking

Worldwide, many countries aim at countering global climate change by promoting renewable energy. Yet, recent studies highlight that so-called green energy, such as wind energy, may come at environmental costs, for example when wind turbines kill birds and bats. Using miniaturized GPS loggers, we studied how an open-space foraging bat with high collision risk with wind turbines, the common noctule Nyctalus noctula (Schreber, 1774), interacts with wind turbines. We compared actual flight trajectories to correlated random walks to identify habitat variables explaining the movements of bats. Both sexes preferred wetlands but used conventionally managed cropland less than expected based on availability. During midsummer, females traversed the land on relatively long flight paths and repeatedly came close to wind turbines. Their flight heights above ground suggested a high risk of colliding with wind turbines. In contrast, males recorded in early summer commuted straight between roosts and foraging areas and overall flew lower than the operating range of most turbine blades, suggesting a lower collision risk. Flight heights of bats suggest that during summer the risk of collision with wind turbines was high for most studied bats at the majority of currently installed wind turbines. For siting of wind parks, preferred bat habitats and commuting routes should be identified and avoided.

Emergent weak home-range behaviour without spatial memory

Space-use problems have been well investigated. Spatial memory capacity is assumed in many home-range algorithms; however, actual living things do not always exploit spatial memory, and living entities can exhibit adaptive and flexible behaviour using simple cognitive capacity. We have developed an agent-based model wherein the agent uses only detected local regions and compares global efficiencies for a habitat search within its local conditions based on memorized information. Here, memorized information was acquired by scanning locally perceived environments rather than remembering resource locations. When memorized information matched to its current environments, the agent changed resource selection rules. As a result, the agent revisited previous resource sites while exploring new sites, which was demonstrating a weak home-range property.

Caribou, water, and ice - fine-scale movements of a migratory arctic ungulate in the context of climate change

BACKGROUND

Freshwater lakes and rivers of the Northern Hemisphere have been freezing increasingly later and thawing increasingly earlier during the last century. With reduced temporal periods during which ice conditions are favourable for locomotion, freshwater bodies could become impediments to the inter-patch movements, dispersion, or migration of terrestrial animals that use ice-covered lakes and rivers to move across their range. Studying the fine-scale responses of individuals to broad-scale changes in ice availability and phenology would help to understand how animals react to ongoing climate change, and contribute to the conservation and management of endangered species living in northern environments. Between 2007 and 2014, we equipped 96 migratory caribou Rangifer tarandus caribou from the Rivière-aux-Feuilles herd in northern Québec (Canada) with GPS telemetry collars and studied their space use. We measured contemporary (digital MODIS maps updated every 8 days, 2000-2014) and historical (annual observations, 1947-1985) variations in freshwater-ice availability and evaluated the concurrent responses of caribou to these changes.

RESULTS

Ice had a positive influence on caribou movement rates and directionality, and caribou selected ice and avoided water when moving across or in the vicinity of large water bodies. When ice was unavailable, caribou rarely swam across (6 % of crossings) and frequently circumvented water bodies for several km. Although ice phenology did not change significantly during our study, climate projections indicated that ice availability could decrease considerably before the end of the century, generating a ~28 % increase in distance travelled by caribou during the early spring and fall migrations.

CONCLUSIONS

We demonstrated that ice availability influenced the movements of a migratory arctic ungulate. Warmer air temperatures in the Arctic will undoubtedly modify the phenology of ice forming on freshwater lakes and rivers. If migratory caribou are unable to adjust the timing of their migrations, they could be forced to circumvent unfrozen water bodies more frequently and over broader areas, which may increase the distance, time, and energy they use to reach wintering areas. The long-term conservation of wide-ranging species will ultimately depend on our ability to identify the fine-scale behavioural reactions of individuals to broad-scale changes in climate and land use.