Habitat-performance relationships: finding the right metric at a given spatial scale

Geochemical landscapes as drivers of wildlife reproductive success: Insights from a high-Arctic ecosystem

The bioavailability of essential and non-essential elements in vegetation is expected to influence the performance of free-ranging terrestrial herbivores. However, attempts to relate the use of geochemical landscapes by animal populations directly to reproductive output are currently lacking. Here we measured concentrations of 14 essential and non-essential elements in soil and vegetation samples collected in the Zackenberg valley, northeast Greenland, and linked these to environmental conditions to spatially predict and map geochemical landscapes. We then used long-term (1996-2021) survey data of muskoxen (Ovibos moschatus) to quantify annual variation in the relative use of essential and non-essential elements in vegetated sites and their relationship to calf recruitment the following year. Results showed that the relative use of the geochemical landscape by muskoxen varied substantially between years and differed among elements. Selection for vegetated sites with higher levels of the essential elements N, Cu, Se, and Mo was positively linked to annual calf recruitment. In contrast, selection for vegetated sites with higher concentrations of the non-essential elements As and Pb was negatively correlated to annual calf recruitment. Based on the concentrations measured in our study, we found no apparent associations between annual calf recruitment and levels of C, Mn, Co, Zn, Cd, Ba, Hg, and C:N ratio in the vegetation. We conclude that the spatial distribution and access to essential and non-essential elements are important drivers of reproductive output in muskoxen, which may also apply to other wildlife populations. The value of geochemical landscapes to assess habitat-performance relationships is likely to increase under future environmental change.

Spatial scaling in bed-site selection by roe deer fawns: Implications for mitigating neonatal mortality during mowing

When habitat use by field-dwelling animals coincides in space and time with agricultural practices such as spring mowing of meadows, human-wildlife conflicts can have deadly consequences for wildlife. Roe deer (Capreolus capreolus L.) fawns are particularly vulnerable because they hide in meadows during the rearing phase. Thus, a better understanding of the habitat drivers of bed-site selection is critical to mitigating fawn mortality during mowing. Here, we tease apart the among-field (presumably driven by maternal behaviour) and within-field (driven by fawn behaviour) components of bed-site selection of roe deer during the spring mowing season. We collected over 600 fawn bed sites across an environmentally diverse study region. At the among-field scale, we implemented a used versus available design and employed a two-part statistical model (GAMLSS) to identify habitat characteristics that were linked to either fawn presence (vs. absence) or abundance on a given field. At the within-field scale, we compared habitat characteristics at fawn bed-sites with paired random sites using a conditional logistic regression model. At the among-field scale, fawns were more likely to be present, and were more abundant, in fields within more diverse, rural landscapes, with nearby woodland. Surprisingly, fawns were more often present in fields that were near roads and had lower vegetation productivity. At the within-field scale, however, fawns preferred bed-sites which were further from both roads and woodland, but that provided the best visual cover to minimise predation risk. Our findings revealed substantial and novel scale-dependent differences in the drivers of habitat selection of mothers and fawns, which, together, determine the precise locations of bed-sites between and within meadows. These results may aid wildlife managers in identifying areas where there is a high probability of encountering a roe deer fawn so as to initiate targeted searches prior to mowing and, ultimately, mitigate fawn mowing mortality.

Estimating survival in continuous space from mark-dead-recovery data - Towards a continuous version of the multinomial dead recovery model

Understanding spatially varying survival is crucial for understanding the ecology and evolution of migratory animals, which may ultimately help to conserve such species. We develop an approach to estimate an annual survival probability function varying continuously in geographic space, if the recovery probability is constant over space. This estimate is based on a density function over continuous geographic space and the discrete age at death obtained from dead recovery data. From the same density function, we obtain an estimate for animal distribution in space corrected for survival, i.e., migratory connectivity. This is possible, when migratory connectivity can be separated from recovery probability. In this article, we present the method how spatially and continuously varying survival and the migratory connectivity corrected for survival can be obtained, if a constant recovery probability can be assumed reasonably. The model is a stepping stone in developing a model allowing for disentangling spatially heterogeneous survival and migratory connectivity corrected for survival from a spatially heterogeneous recovery probability. We implement the method using kernel density estimates in the R-package CONSURE. Any other density estimation technique can be used as an alternative. In a simulation study, the estimators are unbiased but show edge effects in survival and migratory connectivity. Applying the method to a real-world data set of European robins Erithacus rubecula results in biologically reasonable continuous heat-maps for survival and migratory connectivity.

Recolonization following past persecution questions the importance of persistent snow cover as a range limiting factor for wolverines

Globally, climate is changing rapidly, which causes shifts in many species' distributions, stressing the need to understand their response to changing environmental conditions to inform conservation and management. Northern latitudes are expected to experience strongest changes in climate, with milder winters and decreasing snow cover. The wolverine (Gulo gulo) is a circumpolar, threatened carnivore distributed in northern tundra, boreal, and subboreal habitats. Previous studies have suggested that wolverine distribution and reproduction are constrained by a strong association with persistent spring snow cover. We assess this hypothesis by relating spatial distribution of 1589 reproductive events, a fitness-related proxy for female reproduction and survival, to snow cover over two decades. Wolverine distribution has increased and number of reproductive events increased 20 times in areas lacking spring snow cover during our study period, despite low monitoring effort where snow is sparse. Thus, the relationship between reproductive events and persistent spring snow cover weakened during this period. These findings show that wolverine reproductive success and hence distribution are less dependent on spring snow cover than expected. This has important implications for projections of future habitat availability, and thus distribution, of this threatened species. Our study also illustrates how past persecution, or other factors, that have restricted species distribution to remote areas can mask actual effects of environmental parameters, whose importance reveals when populations expand beyond previously restricted ranges. Overwhelming evidence shows that climate change is affecting many species and ecological processes, but forecasting potential consequences on a given species requires longitudinal data to revisit hypotheses and reassess the direction and magnitude of climate effects with new data. This is especially important for conservation-oriented management of species inhabiting dynamic systems where environmental factors and human activities interact, a common scenario for many species in different ecosystems around the globe.

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

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

Habitat fragmentation reduces survival and drives source-sink dynamics for a large carnivore

Rigorous understanding of how environmental conditions impact population dynamics is essential for species conservation, especially in mixed-use landscapes where source-sink dynamics may be at play. Conservation of large carnivore populations in fragmented, human-dominated landscapes is critical for their long-term persistence. However, living in human-dominated landscapes comes with myriad costs, including direct anthropogenic mortality and sublethal energetic costs. How these costs impact individual fitness and population dynamics are not fully understood, partly due to the difficulty in collecting long-term demographic data for these species. Here, we analyzed an 11-year dataset on puma (Puma concolor) space use, mortality, and reproduction in the Santa Cruz Mountains, California, USA, to quantify how living in a fragmented landscape impacts individual survival and population dynamics. Long-term exposure to housing density drove mortality risk for female pumas, resulting in an 18-percentage-point reduction in annual survival for females in exurban versus remote areas. While the overall population growth rate appeared stable, reduced female survival in more developed areas resulted in source-sink dynamics across the study area, with 42.1% of the Santa Cruz Mountains exhibiting estimated population growth rates <1. Since habitat selection is often used as a proxy for habitat quality, we also assessed whether puma habitat selection predicted source and sink areas. Patterns of daytime puma habitat selection predicted source areas, while time-of-day-independent habitat selection performed less well as a proxy. These results illuminate the individual- and population-level consequences of habitat fragmentation for large carnivores, illustrating that habitat fragmentation can produce source-sink dynamics that may not be apparent from other metrics of habitat quality. Locally, conserving high-quality source habitat within the Santa Cruz Mountains is necessary to support long-term puma population persistence. More broadly, source-sink dynamics may at play for other carnivore populations in similar fragmented systems, and linking landscape conditions to population dynamics is essential for effective conservation. Caution should be used in inferring habitat quality from habitat selection alone, but these results shed light on metrics of selection that may be better or worse proxies to identify source areas for large carnivores.

Demography and space-use of Eastern Red-backed Salamanders (Plethodon cinereus) between mature and successional forests

Space-use and demographic processes are critical to the persistence of populations across space and time. Despite their importance, estimates of these processes are often derived from a limited number of populations spanning broad habitat or environmental gradients. With increasing appreciation of the role fine-scale environmental variation in microgeographic adaptation, there is a need and value to assessing within-site variation in space-use and demographic patterns. In this study, we analyze 3 years of spatial capture-recapture data on the Eastern Red-backed Salamander collected from a mixed-use deciduous forest site in central Ohio, USA. Study plots were situated in both a mature forest stand and successional forest stand separated by <100-m distance. Our results showed that salamander density was reduced on successional plots, which corresponded with greater distance between nearest neighbors, less overlap in core use areas, greater space-use, and greater shifts in activity centers when compared to salamanders occupying the mature habitat. By contrast, individual growth rates of salamanders occupying the successional forest were significantly greater than salamanders in the mature forest. These estimates result in successional plot salamanders reaching maturity more than 1 year earlier than salamanders on the mature forest plots and increasing their estimated lifetime fecundity by as much as 43%. The patterns we observed in space-use and individual growth are likely the result of density-dependent processes, potentially reflecting differences in resource availability or quality. Our study highlights how fine-scale, within-site variation can shape population demographics. As research into the demographic and population consequences of climate change and habitat loss and alteration continue, future research should take care to acknowledge the role that fine-scale variation may play, especially for abiotically sensitive organisms with limited vagility.

Dispersal and distribution of a generalist predator in habitats with multiple food resources

The ability to locate suitable food resources affects fitness in animals. Therefore, movements are necessary to optimize foraging in habitats where food is distributed in patches of different qualities. The aim of this work was to investigate the dispersal and distribution of females and males of the omnivorous mirid D. hesperus in mesocosms composed by food patches of different values in terms of fitness. In agreement with the Marginal Value Theorem (MVT) and the Ideal Free Distribution (IFD), individuals were expected to aggregate in the highest quality patches. Besides, the proportion of individuals in patches was predicted to be proportional to fitness, and interference among individuals was expected to rise as the density of individuals increased. Emigration rates were predicted to be higher for low- than for high-quality patches, while the opposite was predicted for immigration. Three types of habitats each with different combinations of food resources were tested: (1) habitat including patches of tomato plants with no-prey, and patches infested with either mite or whitefly; (2) with no-prey and whitefly; (3) with no-prey and mites. Each type of habitat was set up in a tomato greenhouse compartment and replicated four times. Individuals were tracked by mark-recapture methods using luminous paintings. The number of females and males in whitefly patches was significantly higher than in mite and no-prey patches, but a significant interaction sex*habitat and sex*patch was found. In habitats with only one type of prey, D. hesperus adults fitted the IFD, while in mixed prey habitats their distribution diverged from IFD. Interference was found to be significant, with female fitness decreasing as their density increased. Emigration rates were significantly lower for whitefly patches with a significant interaction patch*sex; the opposite was found for immigration. This research shows that it is unlikely that D. hesperus forage according to the omniscient principle of IFD and MVT; in contrast, it strongly suggests that it uses some simple rules to make decisions about inter-patch movement, and emigration from habitats and patches.

Integrated animal movement and spatial capture-recapture models: Simulation, implementation, and inference

Over the last decade, spatial capture-recapture (SCR) models have become widespread for estimating demographic parameters in ecological studies. However, the underlying assumptions about animal movement and space use are often not realistic. This is a missed opportunity because interesting ecological questions related to animal space use, habitat selection, and behavior cannot be addressed with most SCR models, despite the fact that the data collected in SCR studies - individual animals observed at specific locations and times - can provide a rich source of information about these processes and how they relate to demographic rates. We developed SCR models that integrated more complex movement processes that are typically inferred from telemetry data, including a simple random walk, correlated random walk (i.e., short-term directional persistence), and habitat-driven Langevin diffusion. We demonstrated how to formulate, simulate from, and fit these models with standard SCR data using data-augmented Bayesian analysis methods. We evaluated their performance through a simulation study, in which we varied the detection, movement, and resource selection parameters. We also examined different numbers of sampling occasions and assessed performance gains when including auxiliary location data collected from telemetered individuals. Across all scenarios, the integrated SCR movement models performed well in terms of abundance, detection, and movement parameter estimation. We found little difference in bias for the simple random walk model when reducing the number of sampling occasions from T = 25 to T = 15. We found some bias in movement parameter estimates under several of the correlated random walk scenarios, but incorporating auxiliary location data improved parameter estimates and significantly improved mixing during model fitting. The Langevin movement model was able to recover resource selection parameters from standard SCR data, which is particularly appealing because it explicitly links the individual-level movement process with habitat selection and population density. We focused on closed population models, but the movement models developed here can be extended to open SCR models. The movement process models could also be easily extended to accommodate additional "building blocks" of random walks, such as central tendency (e.g., territoriality) or multiple movement behavior states, thereby providing a flexible and coherent framework for linking animal movement behavior to population dynamics, density, and distribution.

Risky business: How an herbivore navigates spatiotemporal aspects of risk from competitors and predators

Understanding factors that influence animal behavior is central to ecology. Basic principles of animal ecology imply that individuals should seek to maximize survival and reproduction, which means carefully weighing risk against reward. Decisions become increasingly complex and constrained, however, when risk is spatiotemporally variable. We advance a growing body of work in predator-prey behavior by evaluating novel questions where a prey species is confronted with multiple predators and a potential competitor. We tested how fine-scale behavior of female mule deer (Odocoileus hemionus) during the reproductive season shifted depending upon spatial and temporal variation in risk from predators and a potential competitor. We expected female deer to avoid areas of high risk when movement activity of predators and a competitor were high. We used GPS data collected from 76 adult female mule deer, 35 adult female elk, 33 adult coyotes, and six adult mountain lions. Counter to our expectations, female deer exhibited selection for multiple risk factors, however, selection for risk was dampened by the exposure to risk within home ranges of female deer, producing a functional response in habitat selection. Furthermore, temporal variation in movement activity of predators and elk across the diel cycle did not result in a shift in movement activity by female deer. Instead, the average level of risk within their home range was the predominant factor modulating the response to risk by female deer. Our results counter prevailing hypotheses of how large herbivores navigate risky landscapes and emphasize the importance of accounting for the local environment when identifying effects of risk on animal behavior. Moreover, our findings highlight additional behavioral mechanisms used by large herbivores to mitigate multiple sources of predation and potential competitive interactions.

Modeling abundance, distribution, movement and space use with camera and telemetry data

Studies of animal abundance and distribution are often conducted independently of research on movement, despite the important links between processes. Movement can cause rapid changes in spatial variation in density, and movement influences detection probability and therefore estimates of abundance from inferential methods such as spatial capture-recapture (SCR). Technological developments including camera traps and GPS telemetry have opened new opportunities for studying animal demography and movement, yet statistical models for these two data types have largely developed along parallel tracks. We present a hierarchical model in which both datasets are conditioned on a movement process for a clearly defined population. We fitted the model to data from 60 camera traps and 23,572 GPS telemetry locations collected on 17 male white-tailed deer in the Big Cypress National Preserve, Florida, USA during July 2015. Telemetry data were collected on a 3-4 h acquisition schedule, and we modeled the movement paths of all individuals in the region with a Ornstein-Uhlenbeck process that included individual-specific random effects. Two of the 17 deer with GPS collars were detected on cameras. An additional 20 male deer without collars were detected on cameras and individually identified based on their unique antler characteristics. Abundance was 126 (95% CI: 88-177) in the 228 km² region, only slightly higher than estimated using a standard SCR model: 119 (84-168). The standard SCR model, however, was unable to describe individual heterogeneity in movement rates and space use as revealed by the joint model. Joint modeling allowed the telemetry data to inform the movement model and the SCR encounter model, while leveraging information in the camera data to inform abundance, distribution and movement. Unlike most existing methods for population-level inference on movement, the joint SCR-movement model can yield unbiased inferences even if non-uniform sampling is used to deploy transmitters. Potential extensions of the model include the addition of resource selection parameters, and relaxation of the closure assumption when interest lies in survival and recruitment. These developments would contribute to the emerging holistic framework for the study of animal ecology, one that uses modern technology and spatio-temporal statistics to learn about interactions between behavior and demography.

Survival and reproduction in Arctic caribou are associated with summer forage and insect harassment

Investigators have speculated that the climate-driven “greening of the Arctic” may benefit barren-ground caribou populations, but paradoxically many populations have declined in recent years. This pattern has raised concerns about the influence of summer habitat conditions on caribou demographic rates, and how populations may be impacted in the future. The short Arctic summer provides caribou with important forage resources but is also the time they are exposed to intense harassment by insects, factors which are both being altered by longer, warmer growing seasons. To better understand the effects of summer forage and insect activity on Arctic caribou demographic rates, we investigated the influence of estimated forage biomass, digestible energy (DE), digestible nitrogen (DN), and mosquito activity on the reproductive success and survival of adult females in the Central Arctic Herd on the North Slope of Alaska. We tested the hypotheses that greater early summer DN would increase subsequent reproduction (parturition and late June calving success) while greater biomass and DE would increase adult survival (September–May), and that elevated mosquito activity would reduce both demographic rates. Because the period when abundant forage DN is limited and overlaps with the period of mosquito harassment, we also expected years with low DN and high harassment to synergistically reduce caribou reproductive success. Examining these relationships at the individual-level, using GPS-collared females, and at the population-level, using long-term monitoring data, we generally found support for our expectations. Greater early summer DN was associated with increased subsequent calving success, while greater summer biomass was associated with increased adult survival. Mosquito activity was associated with reductions in adult female parturition, late June calving success, and survival, and in years with low DN, had compounding effects on subsequent late June calving success. Our findings indicate that summer nutrition and mosquito activity collectively influence the demographic rates of Arctic caribou, and may impact the dynamics of populations in the future under changing environmental conditions.

Habitat selection in a fluctuating ground squirrel population: Density‐dependence and fitness consequences

Investigating individual‐based habitat settlement decisions is a central theme in ecology, yet studies that quantify density‐dependent habitat selection or tie fitness to resource selection decisions remain rare. We quantified habitat selection in golden‐mantled ground squirrels (Callospermophilus lateralis) across two spatial scales (home‐range placement, and occurrence within the home range) by using 11 consecutive years of data on individual space use, and we used resource selection functions and multilevel modeling to address how habitat preferences may be influenced by density or linked to fitness outcomes. Squirrels preferred dry meadow over other habitat types (wet meadow, aspen, spruce, and willow) at both spatial scales. Squirrels were more likely to use dry meadow that contained shorter vegetation and vision‐enhancing prominences such as rocks (“perches”). The use of dry meadow at each scale was not influenced by changes in density. The use of dry meadow did not lead to increased litter size, pre‐hibernation mass, or survival. However, squirrels that experienced a greater number of perches or lower local densities had higher survival rates. Our results suggest that a lack of visual obstruction, probably facilitating detection of predators, drives habitat selection in this system. Surprisingly, squirrels maintained their preference for dry meadow as density increased, and they experienced reduced survival as a result. This work furthers our understanding about the causes and consequences of changes in habitat use, informing wildlife management and conservation.

Targeting Sagebrush (Artemisia Spp.) Restoration Following Wildfire with Greater Sage-Grouse (Centrocercus Urophasianus) Nest Selection and Survival Models

Unprecedented conservation efforts for sagebrush (Artemisia spp.) ecosystems across the western United States have been catalyzed by risks from escalated wildfire activity that reduces habitat for sagebrush-obligate species such as Greater Sage-Grouse (Centrocercus urophasianus). However, post-fire restoration is challenged by spatial variation in ecosystem processes influencing resilience to disturbance and resistance to non-native invasive species, and spatial and temporal lags between slower sagebrush recovery processes and faster demographic responses of sage-grouse to loss of important habitat. Decision-support frameworks that account for these factors can help users strategically apply restoration efforts by predicting short and long-term ecological benefits of actions. Here, we developed a framework that strategically targets burned areas for restoration actions (e.g., seeding or planting sagebrush) that have the greatest potential to positively benefit sage-grouse populations through time. Specifically, we estimated sagebrush recovery following wildfire and risk of non-native annual grass invasion under four scenarios: passive recovery, grazing exclusion, active restoration with seeding, and active restoration with seedling transplants. We then applied spatial predictions of integrated nest site selection and survival models before wildfire, immediately following wildfire, and at 30 and 50 years post-wildfire based on each restoration scenario and measured changes in habitat. Application of this framework coupled with strategic planting designs aimed at developing patches of nesting habitat may help increase operational resilience for fire-impacted sagebrush ecosystems.

Plant community and native primate as drivers of habitat use by an exotic primate (Saimiri spp. Linnaeus, 1758) in an Atlantic Forest fragment

Understanding how and why exotic species use their habitats is crucial for defining effective conservation strategies. We aimed to investigate habitat use by an exotic population of squirrel monkeys living in an Atlantic Forest fragment and identify factors associated with their habitat preferences. Over 6 months of scan sampling observations, we collected data on native and exotic plants consumed by the squirrel monkeys, food availability, and interactions between the squirrel monkeys and the native common marmosets. We also georeferenced the estimated centroid point of the study group during each scan. Squirrel monkeys used Secondary Old Forest habitats more often than the other habitats available. The consumption of native and exotic plants and the association with common marmoset appear to have influenced the habitat use of the exotic squirrel monkeys; however, the choice habitat did not demonstrate to be associated with food availability. The exotic squirrel monkeys preferred to use less disturbed habitats to consume a high amount of food (often associated with the common marmoset), potentially optimizing their food intake. Our findings demonstrated the adaptive success of an exotic primate in its non-natural habitat and the key role of the plant community in maintaining this population.

Estimation in the multinomial reencounter model - Where do migrating animals go and how do they survive in their destination area?

Spatial variation in survival has individual fitness consequences and influences population dynamics. Which space animals use during the annual cycle determines how they are affected by this spatial variability. Therefore, knowing spatial patterns of survival and space use is crucial to understand demography of migrating animals. Extracting information on survival and space use from observation data, in particular dead recovery data, requires explicitly identifying the observation process. We build a fully stochastic model for animals marked in populations of origin, which were found dead in spatially discrete destination areas. The model acts on the population level and includes parameters for use of space, survival and recovery probability. It is based on the division coefficient and the multinomial reencounter model. We use a likelihood-based approach, derive Restricted Maximum Likelihood-like estimates for all parameters and prove their existence and uniqueness. In a simulation study we demonstrate the performance of the model by using Bayesian estimators derived by the Markov chain Monte Carlo method. We obtain unbiased estimates for survival and recovery probability if the sample size is large enough. Moreover, we apply the model to real-world data of European robins Erithacus rubecula ringed at a stopover site. We obtain annual survival estimates for different spatially discrete non-breeding areas. Additionally, we can reproduce already known patterns of use of space for this species.

The battle about the box: competition as the main factor behind the choice for resting sites of hazel dormice

Nest boxes and nest tubes are widely used to survey and monitor hazel dormice (Muscardinus avellanarius). A two-year study was conducted in order to compare the performance of the two devices. In one year hazel dormice clearly preferred nest tubes over nest boxes but preferred nest boxes over nest tubes in the other year. The preference for one or other device was mainly influenced by competition for nest boxes with Apodemus mice, which preferred nest boxes over nest tubes during one year when they were abundant. This has to be considered when comparing performance of methods.

Memory drives the formation of animal home ranges: Evidence from a reintroduction

Most animals live in home ranges, and memory is thought to be an important process in their formation. However, a general memory-based model for characterising and predicting home range emergence has been lacking. Here, we use a mechanistic movement model to: (1) quantify the role of memory in the movements of a large mammal reintroduced into a novel environment, and (2) predict observed patterns of home range emergence in this experimental setting. We show that an interplay between memory and resource preferences is the primary process influencing the movements of reintroduced roe deer (Capreolus capreolus). Our memory-based model fitted with empirical data successfully predicts the formation of home ranges, as well as emergent properties of movement and spatial revisitation observed in the reintroduced animals. These results provide a mechanistic framework for combining memory-based movements, resource preferences, and the formation of home ranges in nature.

Understanding Species–Habitat Associations: A Case Study with the World’s Bears

Habitat modeling is one of the most common practices in ecology today, aimed at understanding complex associations between species and an array of environmental, bioclimatic, and anthropogenic factors. This review of studies of seven species of terrestrial bears (Ursidae) occupying four continents examines how habitat models have been employed, and the functionality of their predictions for management and conservation. Bear occurrence data have been obtained at the population level, as presence points (e.g., sign surveys or camera trapping), or as locations of individual radio-collared animals. Radio-collars provide greater insights into how bears interact with their environment and variability within populations; they are more commonly used in North America and Europe than in South America and Asia. Salient problematic issues apparent from this review included: biases in presence data; predictor variables being poor surrogates of actual behavioral drivers; predictor variables applied at a biologically inappropriate scale; and over-use of data repositories that tend to detach investigators from the species. In several cases, multiple models in the same area yielded different predictions; new presence data occurred outside the range of predicted suitable habitat; and future range projections, based on where bears presently exist, underestimated their adaptability. Findings here are likely relevant to other taxa.

Individual differences in habitat selection mediate landscape level predictions of a functional response

Predicting future space use by animals requires models that consider both habitat availability and individual differences in habitat selection. The functional response in habitat selection posits animals adjust their habitat selection to availability, but population-level responses to availability may differ from individual responses. Generalized functional response (GFR) models account for functional responses by including fixed effect interactions between habitat availability and selection. Population-level resource selection functions instead account for individual selection responses to availability with random effects. We compared predictive performance of both approaches using a functional response in elk (Cervus canadensis) selection for mixed forest in response to road proximity, and avoidance of roads in response to mixed forest availability. We also investigated how performance changed when individuals responded differently to availability from the rest of the population. Individual variation in road avoidance decreased performance of both models (random effects: β = 0.69, 95% CI 0.47, 0.91; GFR: β = 0.38, 95% CI 0.05, 0.71). Changes in individual road and forest availability affected performance of neither model, suggesting individual responses to availability different from the functional response mediated performance. We also found that overall, both models performed similarly for predicting mixed forest selection (F_{1, 58} = 0.14, p = 0.71) and road avoidance (F_{1, 58} = 0.28, p = 0.60). GFR estimates were slightly better, but its larger number of covariates produced greater variance than the random effects model. Given this bias-variance trade-off, we conclude that neither model performs better for future space use predictions.

Incorporating Geographical Scale and Multiple Environmental Factors to Delineate the Breeding Distribution of Sea Turtles

Temperature is often used to infer how climate influences wildlife distributions; yet, other parameters also contribute, separately and combined, with effects varying across geographical scales. Here, we used an unoccupied aircraft system to explore how environmental parameters affect the regional distribution of the terrestrial and marine breeding habitats of threatened loggerhead sea turtles (Caretta caretta). Surveys spanned four years and ~620 km coastline of western Greece, encompassing low (<10 nests/km) to high (100–500 nests/km) density nesting areas. We recorded 2395 tracks left by turtles on beaches and 1928 turtles occupying waters adjacent to these beaches. Variation in beach track and inwater turtle densities was explained by temperature, offshore prevailing wind, and physical marine and terrestrial factors combined. The highest beach-track densities (400 tracks/km) occurred on beaches with steep slopes and higher sand temperatures, sheltered from prevailing offshore winds. The highest inwater turtle densities (270 turtles/km) occurred over submerged sandbanks, with warmer sea temperatures associated with offshore wind. Most turtles (90%) occurred over nearshore submerged sandbanks within 10 km of beaches supporting the highest track densities, showing the strong linkage between optimal marine and terrestrial environments for breeding. Our findings demonstrate the utility of UASs in surveying marine megafauna and environmental data at large scales and the importance of integrating multiple factors in climate change models to predict species distributions.

On this side of the fence: Functional responses to linear landscape features shape the home range of large herbivores

Understanding the consequences of global change for animal movement is a major issue for conservation and management. In particular, habitat fragmentation generates increased densities of linear landscape features that can impede movements. While the influence of these features on animal movements has been intensively investigated, they may also play a key role at broader spatial scales (e.g. the home range scale) as resources, cover from predators/humans, corridors/barriers, or landmarks. How space use respond to varying densities of linear features has been mostly overlooked in large herbivores, in contrast to studies done on predators. Focusing on large herbivores should provide additional insights to understand how animals solve the trade-off between energy acquisition and mortality risk. Here, we investigated the role of anthropogenic (roads and tracks) and natural (ridges, valley bottoms and forest edges) linear features on home range features in five large herbivores. We analysed an extensive GPS monitoring data base of 710 individuals across nine populations, ranging from mountain areas mostly divided by natural features to lowlands that were highly fragmented by anthropogenic features. Nearly all of the linear features studied were found at the home range periphery, suggesting that large herbivores primarily use them as landmarks to delimit their home range. In contrast, for mountain species, ridges often occurred in the core range, probably related to their functional role in terms of resources and refuge. When the density of linear features was high, they no longer occurred predominantly at the home range periphery, but instead were found across much of the home range. We suggest that, in highly fragmented landscapes, large herbivores are constrained by the costs of memorising the spatial location of key features, and by the requirement for a minimum area to satisfy their vital needs. These patterns were mostly consistent in both males and females and across species, suggesting that linear features have a preponderant influence on how large herbivores perceive and use the landscape.

Prospecting and informed dispersal: Understanding and predicting their joint eco-evolutionary dynamics

The ability of individuals to leave a current breeding area and select a future one is important, because such decisions can have multiple consequences for individual fitness, but also for metapopulation dynamics, structure, and long-term persistence through non-random dispersal patterns. In the wild, many colonial and territorial animal species display informed dispersal strategies, where individuals use information, such as conspecific breeding success gathered during prospecting, to decide whether and where to disperse. Understanding informed dispersal strategies is essential for relating individual behavior to subsequent movements and then determining how emigration and settlement decisions affect individual fitness and demography. Although numerous theoretical studies have explored the eco-evolutionary dynamics of dispersal, very few have integrated prospecting and public information use in both emigration and settlement phases. Here, we develop an individual-based model that fills this gap and use it to explore the eco-evolutionary dynamics of informed dispersal. In a first experiment, in which only prospecting evolves, we demonstrate that selection always favors informed dispersal based on a low number of prospected patches relative to random dispersal or fully informed dispersal, except when individuals fail to discriminate better patches from worse ones. In a second experiment, which allows the concomitant evolution of both emigration probability and prospecting, we show the same prospecting strategy evolving. However, a plastic emigration strategy evolves, where individuals that breed successfully are always philopatric, while failed breeders are more likely to emigrate, especially when conspecific breeding success is low. Embedding information use and prospecting behavior in eco-evolutionary models will provide new fundamental understanding of informed dispersal and its consequences for spatial population dynamics.

Do Review Papers on Bird–Vegetation Relationships Provide Actionable Information to Forest Managers in the Eastern United States?

Forest management planning requires the specification of measurable objectives as desired future conditions at spatial extents ranging from stands to landscapes and temporal extents ranging from a single growing season to several centuries. Effective implementation of forest management requires understanding current conditions and constraints well enough to apply the appropriate silvicultural strategies to produce desired future conditions, often for multiple objectives, at varying spatial and temporal extents. We administered an online survey to forest managers in the eastern US to better understand how wildlife scientists could best provide information to help meet wildlife-related habitat objectives. We then examined more than 1000 review papers on bird–vegetation relationships in the eastern US compiled during a systematic review of the primary literature to see how well this evidence-base meets the information needs of forest managers. We identified two main areas where wildlife scientists could increase the relevance and applicability of their research. First, forest managers want descriptions of wildlife species–vegetation relationships using the operational metrics of forest management (forest type, tree species composition, basal area, tree density, stocking rates, etc.) summarized at the operational spatial units of forest management (stands, compartments, and forests). Second, forest managers want information about how to provide wildlife habitats for many different species with varied habitat needs across temporal extents related to the ecological processes of succession after harvest or natural disturbance (1–2 decades) or even longer periods of stand development. We provide examples of review papers that meet these information needs of forest managers and topic-specific bibliographies of additional review papers that may contain actionable information for foresters who wish to meet wildlife management objectives. We suggest that wildlife scientists become more familiar with the extensive grey literature on forest bird–vegetation relationships and forest management that is available in natural resource management agency reports. We also suggest that wildlife scientists could reconsider everything from the questions they ask, the metrics they report on, and the way they allocate samples in time and space, to provide more relevant and actionable information to forest managers.

Habitat selection of Himalayan Musk Deer Moschus leucogaster (Mammalia: Artiodactyla: Moschidae) with respect to biophysical attributes in Annapurna Conservation Area of Nepal

Himalayan or White-bellied Musk Deer Moschus leucogaster, an IUCN indexed endangered species, is distributed in isolated pockets in the Himalaya. The deer population is decreasing owing to several pressures that include habitat loss and fragmentation, and poaching. It is essential to identify preferred habitat characteristics to support appropriate management strategies for conserving this endangered species. This study was carried out in the Nysheang basin of Annapurna Conservation Area of Nepal to identify habitats preferred by the musk deer. Habitat field parameters were collected using transect surveys. To analyze vegetation use and availability, nested quadrate plots size 20 m2 were established. Ivlev’s electivity index (IV) (-1 to +1) was employed to determine habitat preference, and one-way ANOVA (F) and chi-square tests (χ2) were used to examine different habitat parameters. Similarly, the importance value index (IVI) of the vegetation was calculated. Our results showed that the Himalayan Musk Deer strongly preferred habitats at 3601–3800 m altitude (IV= 0.3, F= 4.58, P <0.05), with 21–30º slope (IV= 0.2, F= 4.14, P <0.05), 26–50 % crown cover (IV= 0.25, F= 4.45, P <0.05), 26–50 % ground cover (IV= 0.15, F= 4.13, P <0.05), and mixed forest (IV= 0.29, χ2= 28.82, df= 3, p <0.001). Among the trees, Abies spectabilis (IVI= 74.87, IV= 0.035) and Rhododendron arboretum (IVI= 55.41, IV= 0.02) were the most preferred, while Rhododendron lepidotum, Cassiope fastigiata (IV= 0.35) and Berberis aristata (IV= 0.25) were the most preferred shrubs, and Primula denticulata (IV= 0.87) and Primula rotundifolia (IV= 0.31) were the most preferred herbs. These preferred habitat conditions should be maintained and conserved to sustain a viable population of deer in the study area. Further studies will be required to assess the effects of climate change on habitat suitability. 

How animals distribute themselves in space: energy landscapes of Antarctic avian predators

BACKGROUND

Energy landscapes provide an approach to the mechanistic basis of spatial ecology and decision-making in animals. This is based on the quantification of the variation in the energy costs of movements through a given environment, as well as how these costs vary in time and for different animal populations. Organisms as diverse as fish, mammals, and birds will move in areas of the energy landscape that result in minimised costs and maximised energy gain. Recently, energy landscapes have been used to link energy gain and variable energy costs of foraging to breeding success, revealing their potential use for understanding demographic changes.

METHODS

Using GPS-temperature-depth and tri-axial accelerometer loggers, stable isotope and molecular analyses of the diet, and leucocyte counts, we studied the response of gentoo (Pygoscelis papua) and chinstrap (Pygoscelis antarcticus) penguins to different energy landscapes and resources. We compared species and gentoo penguin populations with contrasting population trends.

RESULTS

Between populations, gentoo penguins from Livingston Island (Antarctica), a site with positive population trends, foraged in energy landscape sectors that implied lower foraging costs per energy gained compared with those around New Island (Falkland/Malvinas Islands; sub-Antarctic), a breeding site with fluctuating energy costs of foraging, breeding success and populations. Between species, chinstrap penguins foraged in sectors of the energy landscape with lower foraging costs per bottom time, a proxy for energy gain. They also showed lower physiological stress, as revealed by leucocyte counts, and higher breeding success than gentoo penguins. In terms of diet, we found a flexible foraging ecology in gentoo penguins but a narrow foraging niche for chinstraps.

CONCLUSIONS

The lower foraging costs incurred by the gentoo penguins from Livingston, may favour a higher breeding success that would explain the species' positive population trend in the Antarctic Peninsula. The lower foraging costs in chinstrap penguins may also explain their higher breeding success, compared to gentoos from Antarctica but not their negative population trend. Altogether, our results suggest a link between energy landscapes and breeding success mediated by the physiological condition.

Behavioural patterns of free roaming wild boar in a spatiotemporal context

Although the almost worldwide distributed wild boar Sus scrofa is a well-studied species, little is known about the behaviour of autochthonous, free living wild boar in a spatiotemporal context which can help to better understand wild boar in conflict terms with humans and to find solutions. The use of camera traps is a favourable and non-invasive method to study them. To observe natural behaviour, 60 camera traps were placed for three months in a state forest of 17.8 km2 in the region of the Luneburg Heath in northern Germany. In this area wild boar, roe deer, red deer, wolves and humans are common. The cameras recorded 20 s length video clips when animals passed the detection zone and could be triggered again immediately afterwards. In total 38 distinct behavioural elements were observed, which were assigned to one of seven behavioural categories. The occurrence of the behavioural categories per day was evaluated to compare their frequencies and see which are more essential than others. Generalised Additive Models were used to analyse the occurrence of each behaviour in relation to habitat and activity time. The results show that essential behavioural categories like foraging behaviour, locomotion and vigilance behaviour occurred more frequently than behaviour that "just" served for the well-being of wild boar. These three behavioural categories could be observed together mostly in the night in broad-leaved forests with a herb layer of 50-100%, comfort behaviour occurred mostly at the ponds in coniferous forest. It is also observable that the behavioural categories foraging and comfort behaviour alternated several times during the night which offers the hypothesis that foraging is mostly followed by comfort behaviour. These findings pave the way towards implementing effective control strategies in the wild and animal welfare in captivity.

Wildfire and the ecological niche: Diminishing habitat suitability for an indicator species within semi-arid ecosystems

Globally accelerating frequency and extent of wildfire threatens the persistence of specialist wildlife species through direct loss of habitat and indirect facilitation of exotic invasive species. Habitat specialists may be especially prone to rapidly changing environmental conditions because their ability to adapt lags behind the rate of habitat alteration. As a result, these populations may become increasingly susceptible to ecological traps by returning to suboptimal breeding habitats that were dramatically altered by disturbance. We demonstrate a multistage modeling approach that integrates habitat selection and survival during the key nesting life-stage of a bird species of high conservation concern, the greater sage-grouse (Centrocercus urophasianus; hereafter, sage-grouse). We applied these spatially explicit models to a spatiotemporally robust dataset of sage-grouse nest locations and fates across wildfire-altered sagebrush ecosystems of the Great Basin ecoregion, western United States. Female sage-grouse exhibited intricate habitat selection patterns that varied across regional gradients of ecological productivity among sagebrush communities, but often selected nest sites that disproportionately resulted in nest failure. For example, 23% of nests occurred in wildfire-affected habitats characterized by reduced sagebrush cover and greater composition of invasive annual grasses. We found survival of nests was negatively associated with wildfire-affected areas, but positively associated with higher elevations with increased ruggedness and overall shrub cover. Strong site fidelity likely drove sage-grouse to continue nesting in habitats degraded by wildfire. Hence, increasing frequency and extent of wildfire may contribute disproportionately to reduced reproductive success by creating ecological traps that act as population sinks. Identifying such habitat mismatches between selection and survival facilitates deeper understanding of the mechanisms driving reduced geographic niche space and population decline at broad spatiotemporal scales, while guiding management actions to areas that would be most beneficial to the species.

Habitat complexity and lifetime predation risk influence mesopredator survival in a multi-predator system

Variability in habitat selection can lead to differences in fitness; however limited research exists on how habitat selection of mid-ranking predators can influence population-level processes in multi-predator systems. For mid-ranking, or mesopredators, differences in habitat use might have strong demographic effects because mesopredators need to simultaneously avoid apex predators and acquire prey. We studied spatially-explicit survival of cheetahs (Acinonyx jubatus) in the Mun-Ya-Wana Conservancy, South Africa, to test hypotheses related to spatial influences of predation risk, prey availability, and vegetation complexity, on mesopredator survival. For each monitored cheetah, we estimated lion encounter risk, prey density, and vegetation complexity within their home range, on short-term (seasonal) and long-term (lifetime) scales and estimated survival based on these covariates. Survival was lowest for adult cheetahs and cubs in areas with high vegetation complexity on both seasonal and lifetime scales. Additionally, cub survival was negatively related to the long-term risk of encountering a lion. We suggest that complex habitats are only beneficial to mesopredators when they are able to effectively find and hunt prey, and show that spatial drivers of survival for mesopredators can vary temporally. Collectively, our research illustrates that individual variation in mesopredator habitat use can scale-up and have population-level effects.

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

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

Relationships between survival and habitat suitability of semi-aquatic mammals

Spatial distribution and habitat selection are integral to the study of animal ecology. Habitat selection may optimize the fitness of individuals. Hutchinsonian niche theory posits the fundamental niche of species would support the persistence or growth of populations. Although niche-based species distribution models (SDMs) and habitat suitability models (HSMs) such as maximum entropy (Maxent) have demonstrated fair to excellent predictive power, few studies have linked the prediction of HSMs to demographic rates. We aimed to test the prediction of Hutchinsonian niche theory that habitat suitability (i.e., likelihood of occurrence) would be positively related to survival of American beaver (Castor canadensis), a North American semi-aquatic, herbivorous, habitat generalist. We also tested the prediction of ideal free distribution that animal fitness, or its surrogate, is independent of habitat suitability at the equilibrium. We estimated beaver monthly survival probability using the Barker model and radio telemetry data collected in northern Alabama, United States from January 2011 to April 2012. A habitat suitability map was generated with Maxent for the entire study site using landscape variables derived from the 2011 National Land Cover Database (30-m resolution). We found an inverse relationship between habitat suitability index and beaver survival, contradicting the predictions of niche theory and ideal free distribution. Furthermore, four landscape variables selected by American beaver did not predict survival. The beaver population on our study site has been established for 20 or more years and, subsequently, may be approaching or have reached the carrying capacity. Maxent-predicted increases in habitat use and subsequent intraspecific competition may have reduced beaver survival. Habitat suitability-fitness relationships may be complex and, in part, contingent upon local animal abundance. Future studies of mechanistic SDMs incorporating local abundance and demographic rates are needed.

Territorial landscapes: incorporating density-dependence into wolf habitat selection studies

Habitat selection is a process that spans space, time and individual life histories. Ecological analyses of animal distributions and preferences are most accurate when they account for inherent dynamics of the habitat selection process. Strong territoriality can constrain perception of habitat availability by individual animals or groups attempting to colonize or establish new territory. Because habitat selection is a function of habitat availability, broad-scale changes in habitat availability or occupancy can drive density-dependent habitat functional responses. We investigated density-dependent habitat selection over a 19-year period of grey wolf (Canis lupus) recovery in Michigan, USA, using a generalized linear mixed model framework to develop a resource selection probability function (RSPF) with habitat coefficients conditioned on random effects for wolf packs and random year intercepts. In addition, we allowed habitat coefficients to vary as interactions with increasing wolf density over space and time. Results indicated that pack presence was driven by factors representing topography, human development, winter prey availability, forest structure, roads, streams and snow. Importantly, responses to many of these predictors were density-dependent. Spatio-temporal dynamics and population changes can cause considerable variation in wildlife-habitat relationships, possibly confounding interpretation of conventional habitat selection models. By incorporating territoriality into an RSPF analysis, we determined that wolves' habitat use in Michigan shifted over time, for example, exhibiting declining responses to winter prey indices and switching from positive to negative responses with respect to stream densities. We consider this an important example of a habitat functional response in wolves, driven by colonization, density-dependence and changes in occupancy during a time period of range expansion and population increase.