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Protected areas serve as population strongholds for many large carnivores, with multi‐use landscapes along their borders forming the front‐lines of wildlife conservation. Understanding large carnivore population dynamics within working landscapes is difficult where anthropogenic mortality is high and unregulated. This study focused on working ranches, where killing jaguars (Panthera onca) and their prey was prohibited, to gain insight into jaguar population potential across multi‐use landscapes. Faced with forest fragmentation, presence of domestic livestock, and dynamic land‐use practices, we expected jaguar populations in working landscapes to be predominantly male and transient, with low cub production, and inflated population densities in remnant forest patches, versus protected areas where we expected native forest habitat and stable jaguar territories. Using camera traps and spatial‐capture recapture analyses, we observed that male jaguars demonstrated larger‐scale movements and were more detectable than females (0.07 ± 0.01 SE vs. 0.02 ± 0.01 SE) in both working and protected landscapes. Female jaguars in ranches traveled farther than females in parks. Carnivore density increased with forest cover and wild prey activity, decreased with domestic prey activity, and was marginally higher in ranches (4.08 individuals/100 km2 ± 0.73 SE) than in parks (3.59 individuals/100 km2 ± 0.64 SE). Females outnumbered males in both landscapes (2.20–2.60 females/100 km2 vs. ~1.60 males/100 km2), although local male density reached up to 11.00 males/100 km2 in ranches (vs. 3.50 males/100 km2 in parks). While overall jaguar density was patchier in protected areas (x̿ = 0.69 parks, 0.54 ranches), inter‐annual patchiness was higher within ranches (Moran's I = 0.49–0.60 ranches, 0.69–0.70 parks), reflecting changes in cattle management. Despite major habitat alterations, working landscapes can support carnivore densities equivalent to (or exceeding that of) unmodified forest habitat, provided that wildlife‐tolerant ranching practices are maintained. [ABSTRACT FROM AUTHOR]

Human‐wildlife conflict represents a substantial threat to rural livelihoods and species persistence. Directed harassment (i.e., hazing) is one method for mitigating conflict, though gauging its effectiveness is often complicated by a lack of replication, controls, or effective contrasts. Herein we assessed whether African lions (Panthera leo) shifted their space use in response to a hazing program intended to deter lions from community lands adjacent to Hwange National Park, Zimbabwe. Using GPS‐collared lions (n = 16) from unique prides, we investigated the degree to which individuals exhibited (a) a large‐scale response by shifting their home ranges away from community lands, or (b) a fine‐scale response by increasingly avoiding areas near households post‐program initiation. Responses between "at‐risk" (those exposed to the program; n = 5) and "protected" (n = 11) lions varied, with at‐risk males shifting their home ranges to include 12.08% more national park and 9.04% less community lands post‐program (median), a shift not replicated by at‐risk females nor protected lions. However, the majority of at‐risk lions demonstrated increased attraction to households post‐program. We demonstrated that while aversive stimulus approaches may alter large‐scale space use by individual lions, constraints imposed by social structure and available habitat alternatives will affect the level of effort required to achieve program success. [ABSTRACT FROM AUTHOR]

Abstract: Evaluating range‐wide habitat use by a target species requires information on species occurrence over broad geographic regions, a process made difficult by species rarity, large spatiotemporal sampling domains and imperfect detection. We address these challenges in an assessment of habitat use for jaguars (Panthera onca) outside protected areas in Central America. Occurrence records were acquired within 12 putative corridors using interviews with knowledgeable corridor residents. We developed a Bayesian hierarchical occupancy model to gain robust inference, allowing for heterogeneity introduced in the sampling process over space and time, using records of jaguar occurrence prone to false positives and false negatives. Probability of false detection of jaguars increased with the number of interviews conducted per unit (from 5.42% to 7.74% given <4 and ≥4 observers per unit). True probability of detection (p = 0.58) increased with the number of days interviewees spent in a survey unit per year. Failing to account for false positives biased predicted habitat use high (c. 1.8×), especially where occurrence records were sparse. Probability of site use by jaguars increased with greater forest cover, prey richness, and distance from human settlements, and decreased with greater agricultural cover, elevation, and distance from protected areas. Site use probabilities averaged 0.15–0.97 by corridor, providing relatively fine‐scale resolution of predicted jaguar occurrence consistent with known patterns of jaguar gene flow across Central America. Model validation, accounting for both false positives and negatives in the observation process, indicated moderate correspondence between model‐predicted observations and actual observations for withheld data (0.65, 95% CRI 0.59–0.71), with sensitivity and specificity rates of 0.69 (0.61–0.77) and 0.59 (0.50–0.68), respectively. These results demonstrate that reliable predictions can be achieved despite the complexity of large‐scale, interview‐based analyses of species occurrence. Synthesis and applications. Our Bayesian hierarchical occupancy model accommodated heterogeneity caused by typical sampling inequities and idiosyncrasies associated with interview data, yielding robust estimates of jaguar habitat use. Our approach is applicable to any wide‐ranging and readily identifiable species and has particular utility for rare species in human‐dominated landscapes where traditional survey techniques (e.g. camera traps) may be impractical. [ABSTRACT FROM AUTHOR]

ABSTRACT Density estimates accounting for differential animal detectability are difficult to acquire for wide-ranging and elusive species such as mammalian carnivores. Pairing distance sampling with call-response surveys may provide an efficient means of tracking changes in populations of coyotes ( Canis latrans), a species of particular interest in the eastern United States. Blind field trials in rural New York State indicated 119-m linear error for triangulated coyote calls, and a 1.8-km distance threshold for call detectability, which was sufficient to estimate a detection function with precision using distance sampling. We conducted statewide road-based surveys with sampling locations spaced ≥6 km apart from June to August 2010. Each detected call (be it a single or group) counted as a single object, representing 1 territorial pair, because of uncertainty in the number of vocalizing animals. From 524 survey points and 75 detections, we estimated the probability of detecting a calling coyote to be 0.17 ± 0.02 SE, yielding a detection-corrected index of 0.75 pairs/10 km2 (95% CI: 0.52-1.1, 18.5% CV) for a minimum of 8,133 pairs across rural New York State. Importantly, we consider this an index rather than true estimate of abundance given the unknown probability of coyote availability for detection during our surveys. Even so, pairing distance sampling with call-response surveys provided a novel, efficient, and noninvasive means of monitoring populations of wide-ranging and elusive, albeit reliably vocal, mammalian carnivores. Our approach offers an effective new means of tracking species like coyotes, one that is readily extendable to other species and geographic extents, provided key assumptions of distance sampling are met. © 2015 The Wildlife Society. [ABSTRACT FROM AUTHOR]

We employed stable carbon (δ13C) and nitrogen (δ15N) isotopes within a hypothetico-deductive framework to explore potential resource partitioning among terrestrial mammalian carnivores. Isotope values were acquired using guard hair samples from bobcat (Lynx rufus), coyote (Canis latrans), gray fox (Urocyon cinereoargenteus), and red fox (Vulpes vulpes) in the Adirondack Park, NY, USA. Enrichment along the δ13C axis was expected to reflect the use of human sources of food (reflecting a corn subsidy), and by extension tolerance for human-modified environments, whereas enrichment along the δ15N axis was expected to reflect a higher level of carnivory (i.e. amount of animal-based protein in the diet) – two mechanisms by which these now sympatric species may achieve a dynamic coexistence. Although bobcats were the only obligate carnivore, all four species shared a similar δ15N space. In contrast, bobcat had a lower and distinct δ13C signature compared to foxes, consistent with the a priori expectation of bobcats being the species least tolerant of human activities. Isotope signatures for coyotes, which colonized the region in the 1920s, overlapped all three native carnivores, bobcats the least, gray fox the most, indicating their potential competitive influence on this suite of native carnivores. [ABSTRACT FROM AUTHOR]

Abstract: As the use of short-rotation coppice willow crops increases, this vegetation type will comprise a greater extent of the landscape, yet its attendant effects on biodiversity remain poorly understood. In this study we characterized the avian and small mammal communities of willow crops that were established for phytoremediation and biomass production in industrial settling basins and compared these communities to those of surrounding areas of naturally-established perennial herbaceous-woody vegetation. Overall, we observed 33 bird species and five small mammal species in five focal sites (i.e., areas consisting of willow crops and adjacent vegetation) and 20 bird species and four small mammal species in two reference sites (i.e., areas of the settling basins without willow crops). For birds and small mammals, focal sites supported slightly greater average species richness and average abundances of all species combined than reference sites. Within focal sites, willow crops supported fewer species and similar combined abundances compared to adjacent areas. Importantly, community and individual species responses varied with the duration of time since coppicing. More small mammal species and individuals used willow crops in the year following coppicing because of their herbaceous undergrowth, while more birds tended to use older willow crops. Collectively, these results indicate that willow crops located within areas of perennial herbaceous-woody vegetation provide some benefits to bird and small mammal populations and that promoting a herbaceous layer in willow crops and maintaining multiple age classes of willows in the landscape simultaneously are likely to enhance the value of willow crops for biodiversity. [Copyright &y& Elsevier]

Global positioning system (GPS) technologies collect unprecedented volumes of animal location data, providing ever greater insight into animal behaviour. Despite a certain degree of inherent imprecision and bias in GPS locations, little synthesis regarding the predominant causes of these errors, their implications for ecological analysis or solutions exists. Terrestrial deployments report 37 per cent or less non-random data loss and location precision 30 m or less on average, with canopy closure having the predominant effect, and animal behaviour interacting with local habitat conditions to affect errors in unpredictable ways. Home-range estimates appear generally robust to contemporary levels of location imprecision and bias, whereas movement paths and inferences of habitat selection may readily become misleading. There is a critical need for greater understanding of the additive or compounding effects of location imprecision, fix-rate bias, and, in the case of resource selection, map error on ecological insights. Technological advances will help, but at present analysts have a suite of ad hoc statistical corrections and modelling approaches available-tools that vary greatly in analytical complexity and utility. The success of these solutions depends critically on understanding the error-inducing mechanisms, and the biggest gap in our current understanding involves species-specific behavioural effects on GPS performance. [ABSTRACT FROM AUTHOR]

1. The ecological footprint of a road may extend for several kilometres with overlapping effects from neighbouring roads causing a nonlinear accumulation of road effects in the landscape. Availability of preferred habitat, spatial dependencies between roads and habitat types, and fidelity to traditionally used areas further confound our ability to predict population-level responses of animals to growing road networks. 2. To isolate these effects, we developed an individually based movement model using elk Cervus elaphus L. as a model system. Empirically derived movement rules redistributed elk under different amounts of preferred habitat (clearcuts), road densities, and road development schemes. We tracked potential mortality risk (given time spent near roads) and emigration rates (given declining accessibility of foraging habitat). 3. Design of the road network accounted for up to 30–55% difference in mortality risk and emigration rates, with the largest differences occurring at intermediate road densities (1–1·5 km km−2) when road effects began to saturate the landscape. Maintaining roads in association with clearcuts caused a decline in habitat accessibility equivalent to replacing 50–75% of these foraging patches with conifer forest. A nine-fold difference in potential emigration was observed after varying elk tolerance for declining habitat accessibility despite holding local movement biases constant. 4. Elk responses to growing road networks were non-linear, exposing thresholds for road density that were reflected in the home range occupancy patterns of a large sample of elk in the region. 5. Synthesis and applications. Our approach provides a means of scaling-up complex movement decisions to population-level redistribution, separating the confounding effects of landscape context from road effects, and exposing thresholds in connectivity and mortality risks for wildlife caused by infrastructure growth. Our model indicated that road densities ≤ 0·5 km km−2 yielded the highest probability of elk occurrence where elk were hunted (and sensitive to roads), but disassociating roads from foraging habitats or managing human access to roads may maintain effective elk habitat at substantially higher road densities. [ABSTRACT FROM AUTHOR]

To maximize success, reintroduction programs generally select predator-free release areas having high habitat quality. Past studies provide little insight into recovery efforts where multiple, potentially novel, mortality hazards occur. The ability of translocated animals to cope with novel environments can be affected by both pre- and postrelease experiences with habitat and mortality risks. We experimentally released elk (Cervus elaphus) having different background experiences into an area where predators and hunters were prevalent and habitat quality varied. Using a competing risks approach, we predicted the postrelease survival of individuals and their fidelity to release areas as a function of animal source and postrelease encounters with forage resources and areas used by wolves (Canis lupus) or humans. Mortality patterns were consistent with prerelease exposure to mortality risks but not habitat differences among source areas. Wolf predation, poaching, and legal Native hunting were equivalent in magnitude and accounted for the majority of elk mortalities. Familiarity with either wolves or hunters prior to release yielded first-year survival rates 1.9-2.2 times greater than observed for animals naïve to both risks. These 2 primary sources of mortality traded off temporally as well as spatially given the proximity of roads, which wolves avoided. The prevalence of forage resources in release areas increased fidelity to release sites but coincided with higher mortality risk during the critical first year, potentially setting an ecological trap for animals naïve to local risks. Translocated individuals largely mediated their respective vulnerabilities over time, showing second-year survival rates equivalent to resident elk. In addition to using source populations that are able to adjust to mortality risks in release areas, spatial and temporal variation in mortality risks might be exploited when planning releases to increase the success of translocations into risky landscapes. [ABSTRACT FROM AUTHOR]

Journal of Applied Ecology (2004) 41, 201–212 [ABSTRACT FROM AUTHOR]

Estimating species distribution and abundance is foundational to effective management and conservation.Using an integrated species distribution model that combines presence‐only data from various sources with detection/non‐detection data from structured surveys, we estimated the distribution and expected abundance of three difficult‐to‐monitor mammals of management concern across New York State, namely, coyotes (Canis latrans), bobcats (Lynx rufus) and black bears (Ursus americanus). Three distinct landscape‐scale camera trap surveys provided detection/non‐detection data over 9 years between 2013 and 2021, and we augmented those data with incidental records of our focal species from public repositories. We used an inhomogeneous Poisson point process to construct an integrated model that fit both data types simultaneously.We demonstrate a simple application of spatial point density of all species records in the accessed public databases to inform the thinning process to account for unknown spatial sampling in the presence‐only data, often referred to as the 'magic covariate'. Using this approach, we examine habitat associations and provide spatially explicit estimates in expected abundance across the entirety of New York State for all three focal species.As expected, coyotes were the most widely distributed and abundant species, with a strong positive association with agricultural land uses. Bobcats exhibited low expected abundance throughout the state and showed positive associations with deciduous forest and forest edge, and a negative association with road density. Finally, we observed considerable spatial variation in abundance of black bears with expected abundance increasing in association with various forest cover and composition covariates and decreasing with crop cover. We present insights into habitat associations and spatial variation in abundance, and provide management implications for each of the species of interest.Synthesis and applications. Our integrated modelling method allows for managers to use citizen sightings combined with detection/non‐detection surveys to estimate robust indices of abundance for both high‐ and low‐density, and wide‐spread versus patchily distributed species. Through comparison with previous studies, we highlight how broad‐scale programmes, such as the statewide efforts to estimate species distributions undertaken here, can benefit substantively from integrated models that leverage additional data (here, incidental records) from a larger region of space, and thus capture more landscape heterogeneity than is plausible within formalized surveys alone. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article "Carnivore occurrence: do interview-based surveys produce unreliable results?" by N. Caruso and colleagues which appeared in the previous issue of the journal.

Establishing protected areas, where human activities and land cover changes are restricted, is among the most widely used strategies for biodiversity conservation. This practice is based on the assumption that protected areas buffer species from processes that drive extinction. However, protected areas can maintain biodiversity in the face of climate change and subsequent shifts in distributions have been questioned. We evaluated the degree to which protected areas influenced colonization and extinction patterns of 97 avian species over 20 years in the northeastern United States. We fitted single‐visit dynamic occupancy models to data from Breeding Bird Atlases to quantify the magnitude of the effect of drivers of local colonization and extinction (e.g., climate, land cover, and amount of protected area) in heterogeneous landscapes that varied in the amount of area under protection. Colonization and extinction probabilities improved as the amount of protected area increased, but these effects were conditional on landscape context and species characteristics. In this forest‐dominated region, benefits of additional land protection were greatest when both forest cover in a grid square and amount of protected area in neighboring grid squares were low. Effects did not vary with species' migratory habit or conservation status. Increasing the amounts of land protection benefitted the range margins species but not the core range species. The greatest improvements in colonization and extinction rates accrued for forest birds relative to open‐habitat or generalist species. Overall, protected areas stemmed extinction more than they promoted colonization. Our results indicate that land protection remains a viable conservation strategy despite changing habitat and climate, as protected areas both reduce the risk of local extinction and facilitate movement into new areas. Our findings suggest conservation in the face of climate change favors creation of new protected areas over enlarging existing ones as the optimal strategy to reduce extinction and provide stepping stones for the greatest number of species. Article impact statement: Protected areas reduce extinction risk and facilitate range shifts, making them valuable for biodiversity conservation under climate change. [ABSTRACT FROM AUTHOR]

Global energy demand has driven expansion of oil and gas extraction into African protected areas, raising concern about potential deleterious impacts on wildlife. Efforts aim to restore extraction sites to their original condition, but may take many years to be successful. We analysed the impact of human disturbance (road density, distance to border, sound levels and the presence of restored oil drill pads) on mammal distributions in Murchison Falls Conservation Area (MFCA), Uganda. We detected 27 mammal species using camera trap surveys within three disturbance‐related strata: restored (<500 m from a restored drill pad), disturbed matrix (within the disturbed landscape but >1 km from a disturbance feature) and remote (>3 km from any disturbance). Herbivore species richness was greater within the disturbed matrix and at restored sites compared to remote areas, whereas species richness did not vary by strata for other guilds. Occupancy models fit for 15 relatively common species indicated no difference in occupancy probability across the three strata, but giraffe occupancy was higher at sites with more restored drill pads. Most species did not avoid areas of high human disturbance in this study, and new vegetation growth may attract some herbivores to restored oil sites. [ABSTRACT FROM AUTHOR]

Atlas data provide biodiversity information at a relatively fine spatial grain over a broad spatial extent and, increasingly, at multiple points in time, which make them invaluable for understanding processes that affect species distributions over time. The effect of survey effort on species detection has long been appreciated and Atlases typically include survey standards and records of effort, but challenges remain in analysing Atlas data that have not been collected using a repeated sampling protocol designed to correct for imperfect detection., We developed a single-visit dynamic occupancy model to quantify the effects of climatic and land-use drivers on local species extinction and colonization while accounting for imperfect detection using repeat Atlas data. We evaluated model stability using data simulated under alternative scenarios and, ultimately, applied the model to empirical data for Canada warbler Cardellina canadensis, a wide-spread species exhibiting a long-term population decline., At sample sizes that are realistic for many Atlases ( n = 1000-10 000 independent survey blocks), our models produced unbiased estimates of detection, occupancy, colonization and extinction parameters. Slope estimates for explanatory covariates were somewhat less stable than overall occupancy, colonization and extinction rates, with covariate effects being sensitive to the total number of, and relationships among, explanatory variables., In comparison to other analyses of Canada warbler distributions that indicated minor changes over time, our approach identified a widespread decline in occupancy probability across New York, consistent with the broader population trend, particularly in the areas where it was initially more likely to occur., Synthesis and applications. A single-visit dynamic occupancy model is a novel method for analysing common, ecologically valuable datasets, such as Atlases, that lack repeated sampling necessary to correct for imperfect detection using alternative multi-season occupancy modelling approaches. As a result, using this method can improve understanding of species distributions and factors that shape them over time, thereby providing more accurate information to guide conservation and management. [ABSTRACT FROM AUTHOR]

Understanding how individual movement scales with body size is of fundamental importance in predicting ecological relationships for diverse species. One-dimensional movement metrics scale consistently with body size yet vary over different temporal scales. Knowing how temporal scale influences the relationship between animal body size and movement would better inform hypotheses about the efficiency of foraging behaviour, the ontogeny of energy budgets, and numerous life-history trade-offs., We investigated how the temporal scaling of allometric patterns in movement varies over the course of a year, specifically during periods of motivated (directional and fast movement) and unmotivated (stationary and tortuous movement) behaviour. We focused on a recently diverged group of species that displays wide variation in movement behaviour - giant Galapagos tortoises ( Chelonoidis spp.) - to test how movement metrics estimated on a monthly basis scaled with body size., We used state-space modelling to estimate seven different movement metrics of Galapagos tortoises. We used log-log regression of the power law to evaluate allometric scaling for these movement metrics and contrasted relationships by species and sex., Allometric scaling of movement was more apparent during motivated periods of movement. During this period, allometry was revealed at multiple temporal intervals (hourly, daily and monthly), with values observed at daily and monthly intervals corresponding most closely to the expected one-fourth scaling coefficient, albeit with wide credible intervals. We further detected differences in the magnitude of scaling among taxa uncoupled from observed differences in the temporal structuring of their movement rates., Our results indicate that the definition of temporal scales is fundamental to the detection of allometry of movement and should be given more attention in movement studies. Our approach not only provides new conceptual insights into temporal attributes in one-dimensional scaling of movement, but also generates valuable insights into the movement ecology of iconic yet poorly understood Galapagos giant tortoises. [ABSTRACT FROM AUTHOR]

In the Adirondack Park region of northern New York, USA, white-tailed deer (Odocoileus virginianus) and moose (Alces alces) co-occur along a temperate-boreal forest ecotone. In this region, moose exist as a small and vulnerable low-density population and over-browsing by white-tailed deer is known to reduce regeneration, sustainability, and health of forests. Here, we assess the distribution and abundance of white-tailed deer at a broad spatial scale relevant for deer and moose management in northern New York. We used density surface modeling (DSM) under a conventional distance sampling framework, tied to a winter aerial survey, to create a spatially explicit estimate of white-tailed deer abundance and density across a vast, northern forest region. We estimated 16,352 white-tailed deer (95% CI 11,762–22,734) throughout the Adirondack Park with local density ranging between 0.00–5.73 deer/km2. Most of the Adirondack Park (91.2%) supported white-tailed deer densities of ≤2 individuals/km2. White-tailed deer density increased with increasing proximity to anthropogenic land cover such as timber cuts, roads, and agriculture and decreased in areas with increasing elevation and days with snow cover. We conclude that climate change will be more favorable for white-tailed deer than for moose because milder winters and increased growing seasons will likely have a pronounced influence on deer abundance and distribution across the Adirondack Park. Therefore, identifying specific environmental conditions facilitating the expansion of white-tailed deer into areas with low-density moose populations can assist managers in anticipating potential changes in ungulate distribution and abundance and to develop appropriate management actions to mitigate negative consequences such as disease spread and increased competition for limiting resources. [ABSTRACT FROM AUTHOR]

Monitoring large herbivores across their core range has been readily accomplished using aerial surveys and traditional distance sampling. But for peripheral populations, where individuals may occur in patchy, low‐density populations, precise estimation of population size and trend remains logistically and statistically challenging. For moose (Alces alces) along their southern range margin in northern New York, USA, we sought robust estimates of moose distribution, abundance, and population trend (2016–2019) using a combination of aerial surveys (line transect distance‐sampling), repeated surveys in areas where moose were known to occur to boost the number of detections, and density surface modeling (DSM) with spatial covariates. We achieved a precise estimate of density (95% CI = 0.00–0.29 moose/km2) for this small population (656 moose, 95% CI = 501–859), which was patchily distributed across a large and heavily forested region (the 24,280‐km2 Adirondack Park). Local moose abundance was positively related to active timber management, elevation, and snow cover, and negatively related to large bodies of water. As expected, moose abundance in this peripheral population was low relative to its core range in other northern forest states. Yet, in areas where abundance was greatest, moose densities in New York approached those where epizootics of winter tick (Dermacentor albipictus) have been reported, underscoring the need for effective and efficient monitoring. By incorporating autocorrelation in observations and landscape covariates, DSM provided spatially explicit estimates of moose density with greater precision and no additional field effort over traditional distance sampling. Combined with repeated surveys of areas with known moose occurrence to achieve viable sample sizes, DSM is a useful tool for effectively monitoring low density and patchy populations. [ABSTRACT FROM AUTHOR]

Aim: Populations of cold‐adapted species at the trailing edges of geographic ranges are particularly vulnerable to the negative effects of climate change from the combination of exposure to warm temperatures and high sensitivity to heat. Many of these species are predicted to decline under future climate scenarios, but they could persist if they can adapt to warming climates either physiologically or behaviourally. We aim to understand local variation in contemporary habitat use and use this information to identify signs of adaptive capacity. We focus on moose (Alces alces), a charismatic species of conservation and public interest. Location: The northeastern United States, along the trailing edge of the moose geographic range in North America. Methods: We compiled data on occurrences and habitat use of moose from remote cameras and GPS collars across the northeastern United States. We use these data to build habitat suitability models at local and regional spatial scales and then to predict future habitat suitability under climate change. We also use fine‐scale GPS data to model relationships between habitat use and temperature on a daily temporal scale and to predict future habitat use. Results: We find that habitat suitability for moose will decline under a range of climate change scenarios. However, moose across the region differ in their use of climatic and habitat space, indicating that they could exhibit adaptive capacity. We also find evidence for behavioural responses to weather, where moose increase their use of forested wetland habitats in warmer places and/or times. Main conclusions: Our results suggest that there will be significant shifts in moose distribution due to climate change. However, if there is spatial variation in thermal tolerance, trailing‐edge populations could adapt to climate change. We highlight that prioritizing certain habitats for conservation (i.e., thermal refuges) could be crucial for this adaptation. [ABSTRACT FROM AUTHOR]

Opportunistic records of animal occurrence may be problematic for inferring species distribution and habitat requirements because of unknown and uncontrolled sources of sampling variance. In this study, we used occurrence records for river otters (Lontra canadensis) derived from sign surveys, road kills, trapper bycatch, and opportunistic sightings (n = 185 records collected 2001–2012) to assess the potential distribution and habitat relationships of otters across central and western New York, USA. To mitigate for obvious observation biases, we standardized observation intensity across regions a priori and restricted inference to readily accessible areas (i.e., ≤700 m from the nearest road). Model selection, and the direction of covariate effects, proved robust to these sampling biases although effect sizes varied −7.1% to +48.0% after bias correction, with the coefficient for the proportion of available shoreline being the most unstable. Ultimately, the top bias‐corrected model proved a reliable index for otter probability of occurrence given a strong, positive, and linear relationship with a withheld set of standardized survey records for otters collected in winter 2016–2017 (n = 57; R2 = 0.90). This model indicated that approximately 20% of the study area represented high probability of otter occurrence. We demonstrated that reliable inference on wildlife habitat requirements can be obtained from disparate records of animal occurrence provided that data biases are known and effectively mitigated. © 2020 The Wildlife Society. Opportunistic data can be successfully integrated into species distribution models following ad hoc corrections to control for sampling bias. We demonstrate that such data can be successfully used to model otter occurrence across central and western New York, USA. [ABSTRACT FROM AUTHOR]

Animal movement strategies including migration, dispersal, nomadism, and residency are shaped by broad-scale spatial-temporal structuring of the environment, including factors such as the degrees of spatial variation, seasonality and inter-annual predictability. Animal movement strategies, in turn, interact with the characteristics of individuals and the local distribution of resources to determine local patterns of resource selection with complex and poorly understood implications for animal fitness. Here we present a multi-scale investigation of animal movement strategies and resource selection. We consider the degree to which spatial variation, seasonality, and inter-annual predictability in resources drive migration patterns among different taxa and how movement strategies in turn shape local resource selection patterns. We focus on adult Galapagos giant tortoises Chelonoidis spp. as a model system since they display many movement strategies and evolved in the absence of predators of adults. Specifically, our analysis is based on 63 individuals among four taxa tracked on three islands over six years and almost 106 tortoise re-locations. Tortoises displayed a continuum of movement strategies from migration to sedentarism that were linked to the spatio-temporal scale and predictability of resource distributions. Movement strategies shaped patterns of resource selection. Specifically, migratory individuals displayed stronger selection toward areas where resources were more predictable among years than did non-migratory individuals, which indicates a selective advantage for migrants in seasonally structured, more predictable environments. Our analytical framework combines large-scale predictions for movement strategies, based on environmental structuring, with finer-scale analysis of space-use. Integrating different organizational levels of analysis provides a deeper understanding of the eco-evolutionary dynamics at play in the emergence and maintenance of migration and the critical role of resource predictability. Our results highlight that assessing the potential benefits of differential behavioral responses first requires an understanding of the interactions among movement strategies, resource selection and individual characteristics. [ABSTRACT FROM AUTHOR]

Models of habitat preference are widely used to quantify animal-habitat relationships, to describe and predict differential space use by animals, and to identify habitat that is important to an animal (i.e. that is assumed to influence fitness). Quantifying habitat preference involves the statistical comparison of samples of habitat use and availability. Preference is therefore contingent upon both of these samples. The inferences that can be made from use versus availability designs are influenced by subjectivity in defining what is available to the animal, the problem of quantifying the accessibility of available resources and the framework in which preference is modelled. Here, we describe these issues, document the conditional nature of preference and establish the limits of inferences that can be drawn from these analyses. We argue that preference is not interpretable as reflecting the intrinsic behavioural motivations of the animal, that estimates of preference are not directly comparable among different samples of availability and that preference is not necessarily correlated with the value of habitat to the animal. We also suggest that preference is context-dependent and that functional responses in preference resulting from changing availability are expected. We conclude by describing advances in analytical methods that begin to resolve these issues. [ABSTRACT FROM AUTHOR]

While the mechanistic links between animal movement and population dynamics are ecologically obvious, it is much less clear when knowledge of animal movement is a prerequisite for understanding and predicting population dynamics. GPS and other technologies enable detailed tracking of animal location concurrently with acquisition of landscape data and information on individual physiology. These tools can be used to refine our understanding of the mechanistic links between behaviour and individual condition through 'spatially informed' movement models where time allocation to different behaviours affects individual survival and reproduction. For some species, socially informed models that address the movements and average fitness of differently sized groups and how they are affected by fission-fusion processes at relevant temporal scales are required. Furthermore, as most animals revisit some places and avoid others based on their previous experiences, we foresee the incorporation of long-term memory and intention in movement models. The way animals move has important consequences for the degree of mixing that we expect to find both within a population and between individuals of different species. The mixing rate dictates the level of detail required by models to capture the influence of heterogeneity and the dynamics of intra- and interspecific interaction. [ABSTRACT FROM AUTHOR]

With the advent of new technologies, animal locations are being collected at ever finer spatiotemporal scales. We review analytical methods for dealing with correlated data in the context of resource selection, including post hoc variance inflation techniques, 'two-stage' approaches based on models fit to each individual, generalized estimating equations and hierarchical mixed-effects models. These methods are applicable to a wide range of correlated data problems, but can be difficult to apply and remain especially challenging for use-availability sampling designs because the correlation structure for combinations of used and available points are not likely to follow common parametric forms. We also review emerging approaches to studying habitat selection that use finescale temporal data to arrive at biologically based definitions of available habitat, while naturally accounting for autocorrelation by modelling animal movement between telemetry locations. Sophisticated analyses that explicitly model correlation rather than consider it a nuisance, like mixed effects and state-space models, offer potentially novel insights into the process of resource selection, but additional work is needed to make them more generally applicable to large datasets based on the use-availability designs. Until then, variance inflation techniques and two-stage approaches should offer pragmatic and flexible approaches to modelling correlated data. [ABSTRACT FROM AUTHOR]

Quantifying kill rates and sources of variation in kill rates remains an important challenge in linking predators to their prey. We address current approaches to using global positioning system (GPS)- based movement data for quantifying key predation components of large carnivores. We review approaches to identify kill sites from GPS movement data as a means to estimate kill rates and address advantages of using GPS-based data over past approaches. Despite considerable progress, modelling the probability that a cluster of GPS points is a kill site is no substitute for field visits, but can guide our field efforts. Once kill sites are identified, time spent at a kill site (handling time) and time between kills (killing time) can be determined. We show how statistical models can be used to investigate the influence of factors such as animal characteristics (e.g. age, sex, group size) and landscape features on either handling time or killing efficiency. If we know the prey densities along paths to a kill, we can quantify the 'attack success' parameter in functional response models directly. Problems remain in incorporating the behavioural complexity derived from GPS movement paths into functional response models, particularly in multi-prey systems, but we believe that exploring the details of GPS movement data has put us on the right path. [ABSTRACT FROM AUTHOR]

Animal movement studies regularly use movement states (e.g., slow and fast) derived from remotely sensed locations to make inferences about strategies of resource use. However, the number of movement state categories used is often arbitrary and rarely inferred from the data. Identifying groups with similar movement characteristics is a statistical problem. We present a framework based on k-means clustering and gap statistic for evaluating the number of movement states without making a priori assumptions about the number of clusters. This allowed us to distinguish 4 movement states using turning angle and step length derived from Global Positioning System locations and head movements derived from tip switches in a neck collar of free-ranging elk (Cervus elaphus) in west central Alberta, Canada. Based on movement characteristics and on the linkage between each state and landscape features, we were able to identify inter-patch movements, intra-patch foraging, rest, and inter-patch foraging movements. Linking behavior to environment (e.g., state-dependent habitat use) can inform decisions on landscape management for wildlife. [ABSTRACT FROM AUTHOR]

To understand how migratory behavior evolved and to predict how migratory species will respond to global environmental change it is important to quantify the fitness consequences of intra‐ and inter‐individual variation in migratory behavior. Intra‐individual variation includes behavioral responses to changing environmental conditions and hence behavioral plasticity in the context of novel or variable conditions. Inter‐individual variation determines the degree of variation on which selection can act and the rate of evolutionary responses to changes in average and extreme environmental conditions. Here we focus on variation in the partial migratory behavior of giant Galápagos tortoises (Chelonoidis spp.) and its energetic consequences. We evaluate the extent and mechanisms by which tortoises adjust migration timing in response to varying annual environmental conditions, and integrate movement data within a bioenergetic model of tortoise migration to quantify the fitness consequences of migration timing. We find strong inter‐individual variation in the timing of migration, which was not affected by environmental conditions prevailing at the time of migration but rather by average expectations estimated from multi‐annual averaged conditions. This variation is associated with an average annual loss in efficiency of ~15% relative to optimal timing based on year‐specific conditions. These results point towards a limited ability of tortoises to adjust the timing of their migrations based on prevailing (and, by extension, future) conditions, suggesting that the adaptability of tortoise migratory behavior to changing conditions is predicated more by past "normal" conditions than responses to prevailing, changing conditions. Our work offers insights into the level of environmental‐tuning in migratory behavior and a general framework for future research across taxa. [ABSTRACT FROM AUTHOR]