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

Animals may exhibit various strategies to mitigate the adverse effects of phenological mismatch. In species experiencing coat colour mismatch, the effects of lost camouflage on the susceptibility to predation may be compensated for with other antipredator traits, such as altered foraging decisions, and may further depend on the intensity of risk. We artificially simulated coat colour mismatch and predation risk in wild-caught snowshoe hares and measured their forage intake rate of black spruce browse, intraspecific selection for forage quality, i.e., % nitrogen of browse, and resulting body mass loss across different risk levels, simulated by cover or lack thereof. We found that hares did not adjust their intake rate in response to mismatch, but hares in our high-risk treatment ate significantly more than hares in our low-risk treatment. Mismatched brown hares, however, selected for more nitrogen-rich forage than their matched brown counterparts. Mismatched white hares lost 4.55% more body mass than their matched white counterparts, despite not reducing their intake rate. Hares in our high-risk treatment lost 1.29% more body mass than those in covered enclosures. We suggest that the increased selection for nitrogen-rich forage observed in brown mismatched hares may occur to mitigate the body mass loss consequences of mismatch. Similarly, the increased intake rate of hares in clear roof enclosures relative to those in opaque roof enclosures may be a compensatory behavioural response to increased body mass loss. Our results highlight the potential indirect effects of coat colour mismatch on snowshoe hares, but also the corresponding behavioural mechanisms that may partially mitigate these effects.

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

Organisms moving across landscapes connect ecosystems in space and time, mediating nutrient, energy, and biomass exchanges. Meta-ecosystem ecology offers a framework to study how these flows affect ecosystem functions in space and time. However, meta-ecosystem models often represent consumer movement as diffusion along gradients of resources. Crucially, this assumes that consumer movement connects the same trophic compartments among patches of the same ecosystem. Yet, empirical evidence shows that organisms move across different ecosystems and connect diverse trophic compartments in diffusive and non-diffusive ways. Here, we derive a two-patch meta-ecosystem model that accounts for both types of organismal movement, and we investigate their influences on local and meta-ecosystem functions. We integrate two novel approaches in this classic meta-ecosystem model: a dispersers’ pool to capture the fraction of moving organisms and time scales separation to partition local and regional dynamics. We show that non-diffusive consumer movement increases landscape heterogeneity while diffusive consumer movement enhances source-sink dynamics. Local ecosystem differences driven by consumer movement type are less prevalent at meta-ecosystem extents. Thus, movement type is essential for predicting local ecosystem dynamics. Our results support recent calls to explicitly consider the role of consumers in shaping and maintaining ecosystem functions in space and time.

Approximatively 25 chemical elements are essential for the maintenance, growth and reproduction of all living organisms. Hence, the movement, distribution, and relative proportions of those elements on the landscape should have significant influence on the structure and functioning of biological communities. Yet our basic understanding for the spatial distribution of elements across landscapes and the drivers of those patterns are limited. Here, we propose a novel framework to apply tools from community and landscape ecology to study spatial patterns in elements. We illustrate this framework with an empirical proof of concept in the boreal forest and demonstrate how spatial grain and spatial dissimilarity of elements interact leading to predictable patterns in elemental distributions at various spatial scales. In particular, we observe that at finer spatial grains, sites with high contributions to elemental dissimilarity cluster together. As grain size increases, the landscape becomes more homogeneous with larger patches of sites with intermediate contributions to elemental dissimilarity emerging near aquatic-terrestrial boundaries. Meanwhile, an analysis revealed that the most important elemental contributors to spatial dissimilarity in this landscape are potassium and calcium, two infrequently studied elements in community ecology, raising new questions about their role in, or response to, distributions of biodiversity and ecosystem functions. Our novel framework demonstrates how we can use community metrics (e.g., dissimilarity) to investigate variability of individual elements, the building blocks of stoichiometric ratios, across landscapes. As a field, ecology is just beginning to fully acknowledge the contribution of biotic factors in shaping biogeochemical processes, but here we provide a framework for integrating abiotic and biotic processes. We conclude by hypothesizing that changes in the evenness or beta-diversity of elements should reflect the structure of biotic communities, providing a long-sought mechanistic link between community and ecosystem processes that can be measured directly in the field.

Herbivores making space use decisions must consider the trade-off between perceived predation risk and forage quality. Herbivores, specifically snowshoe hares (Lepus americanus), must constantly navigate landscapes that vary in predation risk and food quality, providing researchers with the opportunity to explore the factors that govern their foraging decisions. Herein, we tested predictions that intersect the risk allocation hypothesis (RAH) and optimal foraging theory (OFT) in a spatially explicit ecological stoichiometry framework to assess the trade-off between predation risk and forage quality. We used individual and population estimates of snowshoe hare (n = 29) space use derived from biotelemetry across three summers. We evaluated resource forage quality for lowbush blueberry (Vaccinium angustifolium), a common and readily available forage species within our system, using carbon:nitrogen and carbon:phosphorus ratios. We used habitat complexity to proxy perceived predation risk. We analyzed how forage quality of blueberry, perceived predation risk, and their interaction impact the intensity of herbivore space use. We used generalized mixed effects models, structured to enable us to make inferences at the population and individual home range level. We did not find support for RAH and OFT. However, variation in the individual-level reactions norms in our models showed that individual hares have unique responses to forage quality and perceived predation risk. Our finding of individual-level responses indicates that there is fine-scale decision-making by hares, although we did not identify the mechanism. Our approach illustrates spatially explicit empirical support for individual behavioral responses to the food quality–predation risk trade-off.

Intraspecific feeding choices comprise a large portion of herbivore foraging decisions. Plant resource quality is heterogeneously distributed, affected by nutrient availability and growing conditions. Herbivores navigate landscapes, foraging not only according to food qualities, but also energetic and nutritional demands. We test three non-exclusive foraging hypotheses using the snowshoe hare (Lepus americanus): (1) herbivore feeding choices and body conditions respond to intraspecific plant quality variation; (2) high energetic demands mitigate feeding responses; and (3) feeding responses are inflated when nutritional demands are high. We measured black spruce (Picea mariana) nitrogen, phosphorus and terpene compositions, as indicators of quality, within a snowshoe hare trapping grid and found plant growing conditions to explain spruce quality variation (R2

Climate warming is causing asynchronies between animal phenology and environments. Mismatched traits, like coat color change mismatched with snow, can decrease survival. However, coat change does not serve a singular adaptive benefit of camouflage, and alternate coat change functions may confer advantages that supersede mismatch costs. We found that mismatch reduced rather than increased, autumn mortality risk of snowshoe hares in Yukon by 86.5 %. We suggest that the increased coat insulation and lower metabolic rates of winter acclimatized hares confer energetic advantages to white mismatched hares that reduce their mortality risk. We found that white mismatched hares forage 17-77 minutes less per day than matched brown hares between 0 and -10 °C, thus lowering their predation risk and increasing survival. We found no effect of mismatch on spring mortality risk, where mismatch occurred at warmer temperatures, suggesting a potential temperature limit where the costs of conspicuousness outweigh energetic benefits.

Spatially explicit correlates of foliar elemental, stoichiometric, and phytochemical (ESP) traits represent links to landscape patterns of resource quality. We investigate spatial correlates for multiple foliar ESP traits at the species level and across species at the trait level for five boreal forest understory plants. On the island of Newfoundland, Canada, we collected plot-level foliar material from four chronosequenced forest grids. We integrate plot-level response variables of foliar elemental (C, N, P, percent and quantity), stoichiometric (C:N, C:P, N:P), and phytochemical (terpenoids) traits, with spatial predictors available for the whole landscape to test multiple competing hypotheses. These hypotheses include the effects of land cover (e.g., coniferous, deciduous, mixedwood), productivity (e.g., enhanced vegetation index), biotic (e.g., stand age/height, canopy closure) and abiotic (e.g., elevation, aspect, slope) factors. Spatial correlates of foliar ESP traits were generally species specific. However, at the trait level, some species shared spatial predictors, notably for foliar percent carbon, C:P, N:P, sesquiterpene traits. Here we highlight that foliar C, C:P, and sesquiterpene traits between different species were explained by abiotic spatial correlates alone. Similarly, foliar terpenoid traits between different species were related to a combination of abiotic and biotic factors (mean R2 = 0.26). Spatial-trait relationships mainly occur at the species level, with some commonalities at the trait level. By linking plot-level foliar ESP traits to spatial predictors, we can map plant chemical composition patterns that influence landscape-scale ecosystem processes and thus inform sustainable landscape management.

Group size can vary in relation to population density, habitat, and season. Habitat and season may also interact with population density and affect group size through varying foraging benefits of social aggregation in different ecological contexts. We tested the hypothesis that group size varies across ecological contexts, including population density, habitat type, and season, for woodland caribou (Rangifer tarandus) in ten herds over 25 years in Newfoundland, Canada. We predicted that group size would increase as a function of population density. Based on the foraging benefits of social aggregation, we predicted larger groups as habitat openness increased because open areas tend to have higher quality foraging resources. We predicted larger groups during winter when foraging resources are covered in snow because caribou and other social animals exploit social information about the location of foraging resources. In contrast to our prediction, group size decreased as a function of population density. In support of our prediction, group size was larger in winter than calving and summer, and we found that group size increased with habitat openness in some, but not all, cases. Patterns of animal grouping are context-dependent and the additive effect of different ecological contexts on variation in group size informs our understanding of the implicit trade-offs between competition, predation risk, and profitability of forage.

Social groups exist because individuals within the group accrue a net benefit from sharing space. The profitability of sociality, however, varies with ecological context. As ecological context varies, tension emerges among the costs and benefits of social grouping. Fission-fusion societies are fluid in their group dynamics across spatial and temporal contexts, permitting insights into how context affects whether animals choose to join or depart a group. We tested four non-mutually exclusive hypotheses driving variation in fission and fusion in caribou: the risky places, environment heterogeneity, activity budget, and social familiarity hypotheses. The risky places hypothesis predicts animals are unlikely to diffuse when habitats are open and risk of predation is elevated. The habitat heterogeneity hypothesis predicts that fission is more likely in a heterogeneous landscape due to the rising conflicts of interest between group members. The activity budget hypothesis predicts dyads associate by body size due to similar food passage rates. The social cohesion hypothesis predicts that familiar individuals are less likely to fission. We tested the hypotheses using time-to-event (time before fission) analyses and a linear model that assesses spatial, social, and body size relationships among female caribou (n = 22) on Fogo Island, Newfoundland, Canada. Contrary to our prediction for risky places, probability of fission was not influenced by habitat openness. The hypothesis of environmental heterogeneity was partially supported, as caribou remained less cohesive in environments with a higher richness of habitats. No direct evidence emerged to support the activity budget hypothesis. However, it appears that caribou maintain the strongest social bonds among variably sized individuals and these social bonds do decrease the propensity to split. Collectively, our findings showed that social interactions may depend not only on individual identity and characteristics, but also the spatial context in which these interactions occur.

Foragers must balance the costs and gains inherent in the pursuit of their next meal. Classical functional responses formulations describe consumption rates driven by prey density and are naive to predator foraging costs. Here, we integrated foraging costs into functional responses to add mechanism and precision to foundational ideas. Specifically, using a model system with a single predator and two prey, we express a functional response emerging from variable energy and time costs of each predation phase: searching, attacking, or consuming prey. The utility of our model is explored through a focused example where prey can exert variable influence on predator foraging costs through antipredator traits. Dissimilarity between prey in their foraging costs influence the energy gain rate of the predator through optimal prey switching. We found that a small subset of prey antipredator traits and density conditions generated a stabilizing Type III (sigmoidal) functional response - the pattern often thought to typify a generalist predator switching between prey species. The sigmoid functional response occurred for highly profitable prey only when the costly prey was 1. at a high density and 2. their antipredator traits increased energy or time costs following an encounter. We outline testable predictions regarding foraging costs from our model. We provide guidance for how to apply optimal foraging theory to empirical scenarios where predator foraging costs vary due to prey type, predator type, or environmental conditions. Our framework represents a synergy of foundational and contemporary theory across disciplines, facilitating the discovery of shared principles and context-dependent variation across varied predator-prey systems.

Allocare, investment in offspring from non-parents, poses an evolutionary enigma. While the fitness trade-offs driving parental care are universal, alloparents may be driven by kin selection, reciprocation, the need to acquire parenting skills (‘learning-to-parent’), an indiscriminate attraction towards infants (‘natal attraction’), or a combination of multiple drivers. Among belugas (Delphinapterus leucas), allocare has been reported in wild and captive populations, but its underlying mechanisms remain untested. Using over 1800 focal observations, we quantified alloparental associations in St. Lawrence Estuary (SLE) belugas to determine whether the learning-to-parent and natal attraction hypotheses are consistent with patterns of allocare in this population. We found that subadults showed little interest in providing allocare and that alloparental investment remained constant across offspring age classes. As the observed patterns of allocare are inconsistent with both the learning-to-parent and natal attraction hypotheses, allocare in SLE belugas is likely driven by kin selection, reciprocation, or a combination thereof.

The interplay of predator encounters and antipredator responses is an integral part of understanding predator–prey interactions and spatial co-occurrence and avoidance can elucidate these interactions. We conducted hard-part dietary analysis of coyotes (Canis latrans Say, 1823) and space use of coyotes and woodland caribou (Rangifer tarandus caribou (Gmelin, 1788)) to test two competing hypotheses about coyote and caribou predator–prey spatial dynamics using resource selection functions. The high encounter hypothesis predicts that coyotes would maximize encounters with caribou via high spatial co-occurrence, whereas the predator stealth hypothesis predicts that through low spatial co-occurrence with caribou, coyotes act as stealth predators by avoiding habitats that caribou typically select. Our dietary analysis revealed that ∼46% of sampled coyote diet is composed of caribou. We found that coyote share space with caribou in lichen-barren habitat in both summer and winter and that coyotes co-occur with caribou in forested habitat during summer, but not during winter. Our findings support predictions associated with the high encounter predator hypothesis whereby coyotes and caribou have high spatial co-occurrence promoting caribou in coyote diet.

In Focus: Formica, V., Donald, H., Marti, H., Irgebay, Z., Brodie III, E. Social network position experiences more variable selection than weaponry in wild subpopulations of forked fungus beetles. Journal of Animal Ecology, 90, 168-182, https://doi.org/10.1111/1365-2656.13322. That social network traits can exhibit consistent-individual differences among individuals and confer a fitness benefit or cost is increasingly well-established. However, how selection-natural or sexual-affects those social traits and at what scale remains an open question. In this Special Feature, Formica and colleagues employ a meta-population of forked fungus beetles to test and contrast whether sexual selection on social network traits contrasted to morphological traits occurs at the local (soft) or global (hard) scales. The authors demonstrate that morphological traits are largely under hard directional positive selection, whereas social traits are under soft and variable selection. The findings are compelling and raise interesting discussion of multi-level selection and the evolution of social traits in a meta-population.

Density dependence is a fundamental ecological process. Patterns of animal habitat selection and social behaviour are often density-dependent and density-dependent traits should affect reproduction and survival, and subsequently affect fitness and population dynamics. The Ideal Free Distribution and Optimal Foraging Theory present distinct predictions about how the effect of habitat selection on fitness differs across a population density gradient. Using a social ungulate (Rangifer tarandus) as a model system, we test competing hypotheses about how (co)variance in habitat specialization, social behaviour, and fitness vary across a population density gradient. Within a behavioural reaction norm framework, we estimated repeatability, phenotypic plasticity, and phenotypic covariance among social behaviours and habitat selection to demonstrate the adaptive value of these phenotypes across a population density gradient. In support of Optimal Foraging Theory, but not the Ideal Free Distribution, we found that at high density habitat specialists had higher fitness than generalists, but were also less social than habitat generalists, suggesting the possibility that specialists were inhibited from being social. Our findings illustrate that social strength and habitat specialization varied consistently among individuals across a density gradient, but that habitat specialists maximized fitness at high density. Taken together, our study provides preliminary support for Optimal Foraging Theory as the driving mechanism for density-dependent habitat specialization.

Herbivores consider the variation of forage qualities (nutritional content and digestibility) as well as quantities (biomass) when foraging. Such selection patterns may change based on the scale of foraging, particularly in the case of ungulates that forage at many scales.To test selection for quality and quantity in free‐ranging herbivores across scales, however, we must first develop landscape‐wide quantitative estimates of both forage quantity and quality. Stoichiometric distribution models (StDMs) bring opportunity to address this because they predict the elemental measures and stoichiometry of resources at landscape extents.Here, we use StDMs to predict elemental measures of understory white birch quality (% nitrogen) and quantity (g carbon/m2) across two boreal landscapes. We analyzed global positioning system (GPS) collared moose (n = 14) selection for forage quantity and quality at the landscape, home range, and patch extents using both individual and pooled resource selection analyses. We predicted that as the scale of resource selection decreased from the landscape to the patch, selection for white birch quantity would decrease and selection for quality would increase.Counter to our prediction, pooled‐models showed selection for our estimates of quantity and quality to be neutral with low explanatory power and no scalar trends. At the individual‐level, however, we found evidence for quality and quantity trade‐offs, most notably at the home‐range scale where resource selection models explain the largest amount of variation in selection. Furthermore, individuals did not follow the same trade‐off tactic, with some preferring forage quantity over quality and vice versa.Such individual trade‐offs show that moose may be flexible in attaining a limiting nutrient. Our findings suggest that herbivores may respond to forage elemental compositions and quantities, giving tools like StDMs merit toward animal ecology applications. The integration of StDMs and animal movement data represents a promising avenue for progress in the field of zoogeochemistry., We use novel stoichiometric distribution models (StDMs) to test if moose follow scale‐dependent forage quality and quantity expectations across a forested landscape in Newfoundland, Canada. Using elemental measures for forage quantity and quality as our only two explanatory covariates, and three scales of resource selection analyses, we were able to explain variation in resource selection by individual moose. We found no scalar pattern, counter to our prediction, but we uncovered divergent, individual‐based quantity–quality trade‐off tactics.

The use of social network analysis to quantify animal social relationships has increased exponentially over the last two decades. A popular aspect of social network analysis is the use of individually based network metrics. Despite the diversity of social network metrics that exist and the large number of studies that generate network metrics, little guidance exists on the number and type of metrics that should be analysed in a single study. Here, we comment on the ‘hypothesize after results are known’ (HARKing) phenomenon in the context of social network analysis, a practice that we term ‘metric hacking’ and define as the use of statistical criteria to select which metrics to use rather than a priori choice based on a research hypothesis. We identify three situations where metric hacking can occur in studies quantifying social network metrics: (1) covariance among network metrics as explanatory variables in the same model; (2) covariance among network metrics as response variables in multiple models; and (3) covariance between response and explanatory variables in the same model. We outline several quantitative and qualitative issues associated with metric hacking, provide alternative options and guidance on the appropriate use of multiple network metrics to avoid metric hacking. By increasing awareness of the use of multiple social network metrics, we hope to encourage better practice for the selection and use of social network metrics in animal social network analysis.

Movement provides a link between individual behavioral ecology and the spatial and temporal variation in an individual's landscape. Individual variation in movement traits is an important axis of animal personality, particularly in the context of foraging ecology. We tested whether individual caribou (Rangifer tarandus) displayed plasticity in movement and space-use behavior across a gradient of resource aggregation. We quantified first-passage time and range-use ratio as proxies for movement-related foraging behavior and examined how these traits varied at the individual level across a foraging resource gradient. Our results suggest that individuals adjusted first-passage time but not range-use ratio to maximize access to high-quality foraging resources. First-passage time was repeatable, and intercepts for first-passage time and range-use ratio were negatively correlated. Individuals matched first-passage time but not range-use ratio to the expectations of our patch-use model that maximized access to foraging resources, a result that suggests that individuals acclimated their movement patterns to accommodate both intra- and interannual variation in foraging resources on the landscape. Collectively, we highlight repeatable movement and space-use tactics and provide insight into how individual plasticity in movement interacts with landscape processes to affect the distribution of behavioral phenotypes and potentially fitness and population dynamics.

Population monitoring is a critical part of effective wildlife management, but methods are prone to biases that can hinder our ability to accurately track changes in populations through time. Calf survival plays an important role in ungulate population dynamics and can be monitored using telemetry and herd composition surveys. These methods, however, are susceptible to unrepresentative sampling and violations of the assumption of equal detectability, respectively. Here, we capitalized on 55 herd‐wide estimates of woodland caribou (Rangifer tarandus caribou) calf survival in Newfoundland, Canada, using telemetry (n = 1,175 calves) and 249 herd‐wide estimates of calf:cow ratios (C:C) using herd composition surveys to investigate these potential biases. These data included 17 herd‐wide estimates replicated from both methods concurrently (n = 448 calves and n = 17 surveys) which we used to understand which processes and sampling biases contributed to disagreement between estimates of herd‐wide calf survival. We used Cox proportional hazards models to determine whether estimates of calf mortality risk were biased by the date a calf was collared. We also used linear mixed‐effects models to determine whether estimates of C:C ratios were biased by survey date and herd size. We found that calves collared later in the calving season had a higher mortality risk and that C:C tended to be higher for surveys conducted later in the autumn. When we used these relationships to modify estimates of herd‐wide calf survival derived from telemetry and herd composition surveys concurrently, we found that formerly disparate estimates of woodland caribou calf survival now overlapped (within a 95% confidence interval) in a majority of cases. Our case study highlights the potential of under‐appreciated biases to impact our understanding of population dynamics and suggests ways that managers can limit the influence of these biases in the two widely applied methods for estimating herd‐wide survival., We investigated whether estimates of calf mortality risk and calf:cow ratios were biased by unrepresentative sampling and violations of equal detectability, respectively, using 35 years of caribou monitoring data. We found that caribou calves collared later in the calving season had a higher mortality risk and caribou calf:cow ratios were higher when surveys were conducted later in the autumn. If these biases go undetected, they could impact management.

Variation in social environment can mitigate risks and rewards associated with occupying a particular patch. We aim to integrate Ideal Free Distribution (IFD) and Geometry of the Selfish Herd (GSH) to address an apparent conflict in their predictions of equal mean fitness between patches (IFD) and declining fitness benefits within a patch (GSH). We tested these hypotheses in a socio-spatial context using individual caribou that were aggregated or disaggregated during calving and varied in their annual reproductive success (ARS). We then tested individual consistency of these spatial tactics. We reveal that two socio-spatial tactics accorded similar mean ARS (IFD); however, ARS for aggregated individuals declined near the periphery (GSH). Individuals near the aggregation periphery exhibited flexibility, whereas others were consistent. The integration of classical theories through a contemporary lens of consistent individual differences provides evidence for an integrated GSH and IFD strategy that may represent an evolutionary stable state.

Habitat selection is adaptive, but habitats where animals exhibit elevated glucocorticoid production are often associated with lower fitness. The perception of fitness costs persists in part because glucocorticoid samples rarely represent the internal state of individuals at the time of sampling, making it difficult to demonstrate a causal link between glucocorticoid production and habitat selection at fine temporal and spatial scales. We show how to test this fine-scale causal link by integrating movement ecology with stress physiology. We first synthesize physiological evidence that effect of glucocorticoid production on movement aligns with habitat selection theory. We distinguish whether habitat selection exposes individuals to stressors that elevate their glucocorticoid levels, or whether elevated glucocorticoids stimulate selection for better habitat. We then test the directionality of these two pathways using movement-based habitat selection analysis at the individual level. We capitalize on a combination of individual movement data and the predictable time required for glucocorticoids to peak in samples like hair, feathers, and feces from individuals. Our proof-of-concept shows how to distinguish when glucocorticoids stimulate adaptive habitat selection. Finally, we suggest a potential evolutionary role for glucocorticoids in habitat specialization, offering a mechanism by which populations might adapt to their environments over generations.

Nutritional ecologists aim to predict population or landscape-level effects of food availability, but the tools to extrapolate nutrition from small to large extents are often lacking. The appropriate nutritional ecology currencies should be able to represent consumer responses to food while simultaneously be simple enough to expand such responses to large spatial extents and link them to ecosystem functioning. Ecological stoichiometry (ES), a framework of nutritional ecology, can meet these demands, but it is typically associated with ecosystem ecology and nutrient cycling, and less often used to study wildlife nutrition. Despite the emerging zoogeochemical evidence that animals, and thus their diets, play critical roles in nutrient movement, wildlife nutritional ecology has not fully embraced ES, and ES has not incorporated nutrition in many wildlife studies. Here, we discuss how elemental currencies are "nutritionally, organismally, and ecologically explicit" in the context of terrestrial herbivore nutritional ecology. We add that ES and elemental currencies offer a means to measure resource quality across landscapes and compare nutrient availability among regions. Further, we discuss ES shortcomings and solutions, and list future directions to advance the field. As ecological studies increasingly grow in spatial extent, and attempt to link multiple levels of biological organization, integrating more simple and unifying currencies into nutritional studies, like elements, is necessary for nutritional ecology to predict herbivore occurrences and abundances across regions.

The Anthropocene marks great changes to environments and the animals that inhabit them. Changes, such as disturbance, can affect the manner in which animals interact with their environments, such as moving and selecting habitats. To test how animals might respond to changing disturbance regimes, we employ an experimental approach to movement ecology. We used integrated step selection analysis (iSSA) to test the behavioural responses of individually-marked grove snails (Cepaea nemoralis) exposed to a gradient of physical disturbance in their habitat. We used a before-after control-impact (BACI) experimental design within semi-controlled mesocosms to manipulate edge and disturbance variables by altering the area of the mesocosm covered by bricks. We showed that grove snails perceive edges of enclosures and edges of bricks as risks, and responded to such risks by altering their movement. Grove snails displayed a bimodal response to risk by taking shelter in place or moving faster to be farther from the disturbance. Furthermore, individuals tended to modulate their behavioural response to the degree of risk. Our study highlights the usefulness of experimental mesocosms in movement ecology and in determining the effects of habitat alteration and human-imposed risk on movement behaviour.

Animals are faced with unprecedented challenges as environmental conditions change. Animals must display behavioral plasticity to acclimate to changing conditions, or phenotypic variation must exist within the population to allow for natural selection to change the distribution of trait values. The timing of migration and parturition relative to important annual environmental changes such as snowmelt and vegetation green-up and how they co-vary may influence reproductive success. We tested for plasticity and individual differences in migration and parturition timing as a function of the timing of snowmelt and green-up in a migratory herbivore (caribou; Rangifer tarandus, n = 92) using behavioral reaction norms. We tested whether timing of parturition, plasticity in parturition timing, or timing of green-up were correlated with calf survival. Migration and parturition timing were plastic to the timing of spring conditions, and we found moderate repeatability for migration timing, but no repeatability in timing of parturition. We detected a novel behavioral syndrome where timing of migration and timing of parturition were correlated. Our results suggest that observed shifts in caribou parturition timing in other populations are due to plasticity as opposed to an evolutionary response to changing conditions. We did not detect a correlation between annual reproductive success and either the timing of spring or plasticity to the timing of spring events. While this provides evidence that many populations may be buffered from the consequences of climate change via plasticity, we caution that a lack of repeatability in parturition timing could impede adaptation as climate warming increases.Significance StatementAnimals have evolved to reproduce when resources are abundant. Climate change has altered the timing of annual events, resulting in earlier peaks in resource abundance. Animals can cope with this change in two ways. Individuals can display plasticity and alter the timing of reproductive activities to match the change in the environment, or consistent differences among individuals can result in sufficient variation to drive an evolutionary response. We tested these two alternative hypotheses in caribou (Rangifer tarandus) using an individual-based modelling framework. Caribou displayed plasticity in both when they migrated and gave birth, suggesting they can acclimate to changing conditions, but we did not find evidence of differences among individuals that would be likely to result in an evolutionary response.

Invasive species are a major contributor to biodiversity loss worldwide. Wild pigs (Sus scrofa Linnaeus, 1758) are highly invasive in their introduced ranges; they modify habitat and threaten native species. As recent invaders in Canada, it is unknown what habitats wild pigs occupy at the northern edge of their range and how they affect mammalian diversity. We examined habitat factors that we predicted would affect co-occurrence of wild pigs with native mammals. We randomly placed 17 camera traps in four stratified habitat types (deciduous forest, grassland, cropland, and wetland) for 2 years to examine species co-occurrence in these habitats. We analyzed camera-trap data using nonmetric multidimensional scaling. Wild pig detection during winter was greatest in wetland and cropland and positively associated with occurrence of moose (Alces alces (Linnaeus, 1758)) and coyote (Canis latrans Say, 1823) and negatively associated with the presence of white-tailed deer (Odocoileus virginianus (Zimmermann, 1780)), mule deer (Odocoileus hemionus (Rafinesque, 1817)), and humans. In summer, we detected wild pigs only in grassland; these detections were positively associated with moose and mule deer and negatively associated with domesticated cattle (Bos taurus Linnaeus, 1758), elk (Cervus canadensis Erxleben, 1777), and humans. We conclude that invasive wild pig occurrence at the northern edge of their Canadian range varies seasonally, by habitat, and is negatively affected by the presence of humans. Moreover, apparent co-occurrence with native fauna and avoidance of domestic species provides early evidence for potential competitive interactions.

The increased popularity and accessibility of social network analysis has improved our ability to test hypotheses about complex animal social structures. To gain a deeper understanding of the use and application of animal social network analysis, we systematically surveyed the literature and extracted information on publication trends from articles using social network analysis. We synthesize trends in social network research over time and highlight variation in the use of different aspects of social network analysis. The use of social network analysis in empirical articles has increased over time. In the context of social network methods, we found that many studies did not use an association index to account for missing individuals or observations of individuals; that the number and type of social network metrics calculated in a given study varied substantially (median = 2); and that focal observation was by far the most common method used to generate social networks, although the use of biologging devices increased over time. We also observed that most species studied using social networks are mammals (55%) or birds (23%), and that the majority are species of least concern (59%; International Union for the Conservation of Nature, IUCN, www.iucn.org ). Based on our findings, we highlight four key recommendations for future studies: (1) the use of association indices is almost always necessary; (2) the a priori selection of specific network metrics and associated hypotheses increases transparency; (3) combination of focal observation with biologging devices could improve our understanding of remotely sensed behaviours; and (4) because most studies rarely study species of conservation concern, it may be practical to generate networks for similar species or populations, which could help inform management decisions. We highlight emerging trends in social network research that may be valuable for distinct groups of social network researchers: students new to social network analysis, experienced behavioural ecologists interested in using social network analysis and advanced social network users interested in trends of social network research. Our findings also shed light on past research and provide guidance for future studies using social network analysis.

Context Conserving and managing habitat for animals requires robust models to predict their space use. The functional response in habitat selection posits that animals adjust their habitat selection according to availability. Objectives Habitat availability can change over short time periods and small spatial distances, and thus failing to account for changes in habitat availability while modelling may not produce reliable predictions in the near–term or future. However, because individuals may respond to habitat availability differently, the functional response is also limited for predicting habitat selection by individuals. Methods Using a functional response in elk (Cervus canadensis) selection for mixed forest in response to road proximity, we compared habitat selection predictions made by population-level resource selection functions (RSFs) with random effects to incorporate individual differences in selection, to generalized functional response (GFR) RSFs. Results We found that since not all individuals followed the road-dependent functional response, the random effects model both predicted the distributions of individuals more accurately (R2 = 0.62 vs. R2 = 0.51) and produced coefficient estimates that matched their selection for mixed forest and distance from roads better than the GFR model (RMSE = 0.25 vs. RMSE = 0.29 and 0.37 vs. 0.46). Conclusions Individual habitat selection often varies within populations, and revealing those differences shows how individuals help populations respond to environmental change. We suggest that evaluating individual differences using multiple predictive approaches is necessary to forecast long–term habitat selection.

Avoiding death infects biological processes, including behavior. Habitat selection, movement, and sociality are highly flexible behaviors that influence the mortality risks and subsequent fitness of individuals. In the Anthropocene, animals are experiencing increased risks from direct human causes and increased spread of infectious diseases. Using integrated step selection analysis, we tested how the habitat selection, movement, and social behaviors of grey wolves vary as an individual dies due to humans or canine distemper virus (CDV) and how those behaviors may vary in the lead up to death. Behaviors that changed prior to death were strongly related to how an animal eventually died. Wolves killed by humans moved slower than wolves that survived and selected to be nearer roads closer in time to their death. Wolves that died due to CDV moved progressively slower as they neared death and reduced their avoidance of wet habitats. All animals, regardless of dying or not maintained strong selection to be near packmates across time, which seemingly contributed to disease dynamics in the packs that became infected with CDV. Habitat selection, movement, and sociality interact to put individuals and groups at greater risks, influencing their cause-specific mortality.Lay SummaryNot much is known about behaviors prior to death in wild animals. Grey wolves killed by humans selected to be in riskier areas increasingly prior to their deaths. Wolves that died due to disease moved slower and changed their habitat selection to be in areas with more water as they became sicker. Sick wolves also continued to select for packmates, increasing the chances that the whole pack would succumb to the disease.

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.

Sample size sufficiency is a critical consideration for conducting Resource-Selection Analyses (RSAs) from GPS-based animal telemetry. Cited thresholds for sufficiency include a number of captured animals M ≥ 30 and as many relocations per animal N as possible. These thresholds render many RSA-based studies misleading if large sample sizes were truly insufficient, or unpublishable if small sample sizes were sufficient but failed to meet reviewer expectations.We provide the first comprehensive solution for RSA sample size by deriving closed-form mathematical expressions for the number of animals M and the number of relocations per animal N required for model outputs to a given degree of precision. The sample sizes needed depend on just 2 biologically meaningful quantities: habitat selection strength and a novel measure of landscape complexity, which we define rigorously. The mathematical expressions are calculable for any environmental dataset at any spatial scale and are applicable to any study involving resource selection (including sessile organisms). We validate our analytical solutions using globally relevant empirical data including 5,678,623 GPS locations from 511 animals from 10 species (omnivores, carnivores, and herbivores living in boreal, temperate, and tropical forests, montane woodlands, swamps, and arctic tundra).Our analytic expressions show that the required M and N must decline with increasing selection strength and increasing landscape complexity, and this decline is insensitive to the definition of availability used in the analysis. Our results contradict conventional wisdom by demonstrating that the most biologically relevant effects on the utilization distribution (i.e. those landscape conditions with the greatest absolute magnitude of resource selection) can often be estimated with far fewer data than is commonly assumed.We identify several critical steps in implementing these equations, including (i) a priori selection of expected model coefficients, and (ii) sampling intensity for background (absence/pseudo-absence) data within a given definition of availability. We show that random sampling of background data violates the underlying mathematics of RSA, leading to incorrect values for necessary M and N and potentially incorrect RSA model outputs. We argue that these equations should be a mandatory component for all future RSA studies.