Geology topics

Jerrold L. Belant

Publications and source records attributed to Jerrold L. Belant.

At least 19 recordsLinked to original sources

USGS2026

Local and landscape-level environmental conditions drive habitat selection across terrestrial mammal species

Aim Animal movements are a fundamental process affecting communities and ecosystems. Quantifying habitat selection across species and habitats is key for understanding how animals respond to environmental change. Currently, we lack comparative studies that examine how habitat selection varies across species traits and landscapes. We aim to quantify global patterns of habitat selection to help understand the fundamental drivers of movement behaviour. Location Global. Time Period Contemporary. Major Taxa Studied Terrestrial mammals. Methods We estimated selection coefficients for terrain ruggedness, vegetation productivity, human population density and distance to roads of individual terrestrial mammals through step-selection analysis of 1344 GPS tracks across 48 species. We quantified intra- and interspecific variation and tested whether selection coefficients were associated with species traits and habitat availability. Results We observe an overall avoidance of roads and areas of high human population density as well as rugged terrain, with a large proportion of individuals selecting for areas of intermediate NDVI. However, we also found large intraspecific variation in habitat selection and show that this variation is predicted by local and landscape-level environmental conditions rather than species traits. Individuals in more remote areas exhibited weaker functional responses to human presence than those in more disturbed areas. Avoidance of rugged terrain is also context-dependent, with stronger avoidance when local ruggedness is high. The only exception to the observed intraspecific variability is consistent species-level responses to road proximity. Main Conclusions Our findings contribute to the understanding of habitat selection by terrestrial mammals, showing that selection is largely shaped by environmental conditions and that animals exhibit high plasticity in their responses. Our results also provide further evidence for the significant impact of roads on animal movement. These insights can help us to understand the potential effects of environmental change on the behaviour of mammal species around the world.

Global Ecology and Biogeography↗

USGS2026

Interacting effects of human presence and landscape modification on birds and mammals

Sustainable human–wildlife coexistence requires a mechanistic understanding of the many ways that humans affect animals. However, progress is hampered by the lack of accessible data measuring the dynamic presence of people. Here, we leverage mobile-device data to disentangle how human presence and landscape modification differentially influence the use of geographic and environmental space for 37 mammal and bird species across the United States. Human presence affected more than 65% of species, with substantial variation across species. For ~60% of species that responded to human activities, the effects were interdependent—animals tended to react more strongly to human presence in less modified habitats. Our results demonstrate that human presence and landscape modification have complex combined effects on wildlife, which need to be considered for effective management.

Science↗

USGS2025

The influence of human presence and footprint on animal space use in US national parks

Given the importance of protected areas for biodiversity, the growth of visitation to many areas has raised concerns about the effects of humans on wildlife. In 2020, the COVID-19 pandemic led to temporary closure of national parks in the United States, offering a pseudonatural experiment to tease apart the effects of permanent infrastructure and transient human presence on animals. We compiled GPS tracking data from 229 individuals of 10 mammal species in 14 parks and used third-order hierarchical resource selection functions to evaluate the influence of the human footprint on animal space use in 2019 and 2020. Averaged across all parks and species, animals avoided the human footprint, whether the park was open or closed. However, although animals in remote areas showed consistent avoidance, on average those in more developed areas switched from avoidance to selection when protected areas were closed. Findings varied across species: some responded consistently negatively to the footprint (wolves, mountain goats), some positively (mule deer, red fox) and others had a strong exposure-mediated response (elk, mountain lion). Furthermore, some species responded more strongly to the park closure (black bear, moose). This study advances our understanding of complex interactions between recreation and wildlife in protected areas.

western United States↗

USGS2024

Intrinsic and environmental drivers of pairwise cohesion in wild Canis social groups

Animals within social groups respond to costs and benefits of sociality by adjusting the proportion of time they spend in close proximity to other individuals in the group (cohesion). Variation in cohesion between individuals, in turn, shapes important group-level processes such as subgroup formation and fission–fusion dynamics. Although critical to animal sociality, a comprehensive understanding of the factors influencing cohesion remains a gap in our knowledge of cooperative behavior in animals. We tracked 574 individuals from six species within the genus Canis in 15 countries on four continents with GPS telemetry to estimate the time that pairs of individuals within social groups spent in close proximity and test hypotheses regarding drivers of cohesion. Pairs of social canids ( Canis spp.) varied widely in the proportion of time they spent together (5%–100%) during seasonal monitoring periods relative to both intrinsic characteristics and environmental conditions. The majority of our data came from three species of wolves (gray wolves, eastern wolves, and red wolves) and coyotes. For these species, cohesion within social groups was greatest between breeding pairs and varied seasonally as the nature of cooperative activities changed relative to annual life history patterns. Across species, wolves were more cohesive than coyotes. For wolves, pairs were less cohesive in larger groups, and when suitable, small prey was present reflecting the constraints of food resources and intragroup competition on social associations. Pair cohesion in wolves declined with increased anthropogenic modification of the landscape and greater climatic variability, underscoring challenges for conserving social top predators in a changing world. We show that pairwise cohesion in social groups varies strongly both within and across Canis species, as individuals respond to changing ecological context defined by resources, competition, and anthropogenic disturbance. Our work highlights that cohesion is a highly plastic component of animal sociality that holds significant promise for elucidating ecological and evolutionary mechanisms underlying cooperative behavior.

Ecology↗

USGS2024

Climate, food and humans predict communities of mammals in the United States

Aim The assembly of species into communities and ecoregions is the result of interacting factors that affect plant and animal distribution and abundance at biogeographic scales. Here, we empirically derive ecoregions for mammals to test whether human disturbance has become more important than climate and habitat resources in structuring communities. Location Conterminous United States. Time Period 2010–2021. Major Taxa Studied Twenty-five species of mammals. Methods We analysed data from 25 mammal species recorded by camera traps at 6645 locations across the conterminous United States in a joint modelling framework to estimate relative abundance of each species. We then used a clustering analysis to describe 8 broad and 16 narrow mammal communities. Results Climate was the most important predictor of mammal abundance overall, while human population density and agriculture were less important, with mixed effects across species. Seed production by forests also predicted mammal abundance, especially hard-mast tree species. The mammal community maps are similar to those of plants, with an east–west split driven by different dominant species of deer and squirrels. Communities vary along gradients of temperature in the east and precipitation in the west. Most fine-scale mammal community boundaries aligned with established plant ecoregions and were distinguished by the presence of regional specialists or shifts in relative abundance of widespread species. Maps of potential ecosystem services provided by these communities suggest high herbivory in the Rocky Mountains and eastern forests, high invertebrate predation in the subtropical south and greater predation pressure on large vertebrates in the west. Main Conclusions Our results highlight the importance of climate to modern mammals and suggest that climate change will have strong impacts on these communities. Our new empirical approach to recognizing ecoregions has potential to be applied to expanded communities of mammals or other taxa.

Conterminous United States↗

USGS2023

Behavioral responses of terrestrial mammals to COVID-19 lockdowns

COVID-19 lockdowns reduced human mobility, providing an opportunity to disentangle its effects on animals from those of landscape modifications. Using GPS data, we compared movements and road avoidance of 2300 terrestrial mammals (43 species) during the 2020 lockdowns to the same period in 2019. Individual responses were variable, with no change in average movements or road avoidance behavior, likely due to variable lockdown conditions. However, under strict lockdowns,10-day, 95th percentile displacements increased by 73%, suggesting increased landscape permeability. In areas of high human footprint, animals' 1-hour, 95th percentile displacements declined by 12%, and animals were 36% closer to roads, indicating reduced avoidance during lockdowns. Overall, lockdowns rapidly altered some spatial behaviors, highlighting the variable but substantial impact of human mobility on wildlife worldwide.

Science↗

USGS2023

The unmarked R package: Twelve years of advances in occurrence and abundance modelling in ecology

Species distribution models (SDMs) are widely applied to understand the processes governing spatial and temporal variation in species abundance and distribution but often do not account for measurement errors such as false negatives and false positives. We describe unmarked , a package for the freely available and open-source R software that provides a complete workflow for modelling species distribution and abundance while explicitly accounting for measurement errors. Here we focus on recent advances in unmarked functionality to support multi-species, multi-state, and multi-season data, as well as support for fitting models with random effects. For illustration, we present an analysis of Acadian Flycatcher Empidonax virescens abundance on Roanoke River National Wildlife Refuge, North Carolina, USA, over 18 years. We found that Acadian Flycatcher abundance was initially greater in hardwood plantation habitat relative to bottomland hardwood forest along river levees but that abundance declined over time in both habitats. We plan for unmarked development to keep pace with advances in hierarchical modelling in ecology, including better handling of continuous-time data from camera trap and automated recording units and integrated models for multiple data streams.

Methods in Ecology & Evolution↗

USGS2023

Perception and trust influence acceptance for black bears more than bear density or conflicts

Introduction: To sustain black bear (Ursus americanus) populations, wildlife managers should understand the coupled socio-ecological systems that influence acceptance capacity for bears. Method: In a study area encompassing a portion of New York State, we spatially matched datasets from three sources: human-bear conflict reports between 2006 and 2018, estimates of local bear density in 2017–2018, and responses to a 2018 property owner survey (n=1,772). We used structural equation modeling to test hypothesized relationships between local human-bear conflict, local bear density, and psychological variables. Results: The final model explained 57% of the variance in acceptance. The effect of bear population density on acceptance capacity for bears was relatively small and was mediated by a third variable: perception of proximity to the effects of human-bear interactions. The variables that exerted a direct effect on acceptance were perception of bear-related benefits, perception of bear-related risks, perceived proximity to effects of human-bear interactions, and being a hunter. Perception of bear-related benefits had a greater effect on acceptance than perception of bear-related risks. Perceived proximity to effects of human-bear interactions was affected by local bear density, but also was affected by social trust. Increased social trust had nearly the same effect on perceived proximity as decreased bear density. Social trust had the greatest indirect effect on acceptance of any variable in the model. Discussion: Findings suggest wildlife agencies could maintain public acceptance for bears through an integrated approach that combines actions to address bear-related perceptions and social trust along with active management of bear populations.

New York↗

USGS2022

Integrating data types to estimate spatial patterns of avian migration across the Western Hemisphere

For many avian species, spatial migration patterns remain largely undescribed, especially across hemispheric extents. Recent advancements in tracking technologies and high-resolution species distribution models (i.e., eBird Status and Trends products) provide new insights into migratory bird movements and offer a promising opportunity for integrating independent data sources to describe avian migration. Here, we present a three-stage modeling framework for estimating spatial patterns of avian migration. First, we integrate tracking and band re-encounter data to quantify migratory connectivity, defined as the relative proportions of individuals migrating between breeding and nonbreeding regions. Next, we use estimated connectivity proportions along with eBird occurrence probabilities to produce probabilistic least-cost path (LCP) indices. In a final step, we use generalized additive mixed models (GAMMs) both to evaluate the ability of LCP indices to accurately predict (i.e., as a covariate) observed locations derived from tracking and band re-encounter datasets versus pseudo-absence locations during migratory periods, and to create a fully integrated (i.e., eBird occurrence, LCP, and tracking/band re-encounter data) spatial prediction index for mapping species-specific seasonal migrations. To illustrate this approach, we apply this framework to describe seasonal migrations of 12 bird species across the Western Hemisphere during pre- and post-breeding migratory periods (i.e., spring and fall, respectively). We found that including LCP indices with eBird occurrence in GAMMs generally improved the ability to accurately predict observed migratory locations, when compared to models with eBird occurrence alone. Using three performance metrics, the eBird + LCP model demonstrated equivalent or superior fit relative to the eBird-only model for 22 of 24 species-season GAMMs. In particular, the integrated index filled in spatial gaps for species with over-water movements and those that migrated over land where there were few eBird sightings, and thus, low predictive ability of eBird occurrence probabilities (e.g., Amazonian rainforest in South America). This methodology of combining individual-based seasonal movement data with temporally dynamic species distribution models provides a comprehensive approach for integrating multiple data types to describe broad-scale spatial patterns of animal movement. Further development and customization of this approach will continue to advance knowledge about the full annual cycle and conservation of migratory birds.

Ecological Applications↗

USGS2022

Africa’s drylands in a changing world: Challenges for wildlife conservation under climate and land-use changes in the Greater Etosha Landscape

Proclaimed in 1907, Etosha National Park in northern Namibia is an iconic dryland system with a rich history of wildlife conservation and research. A recent research symposium on wildlife conservation in the Greater Etosha Landscape (GEL) highlighted increased concern of how intensification of global change will affect wildlife conservation based on participant responses to a questionnaire. The GEL includes Etosha and surrounding areas, the latter divided by a veterinary fence into large, private farms to the south and communal areas of residential and farming land to the north. Here, we leverage our knowledge of this ecosystem to provide insight into the broader challenges facing wildlife conservation in this vulnerable dryland environment. We first look backward, summarizing the history of wildlife conservation and research trends in the GEL based on a literature review, providing a broad-scale understanding of the socioecological processes that drive dryland system dynamics. We then look forward, focusing on eight key areas of challenge and opportunity for this ecosystem: climate change, water availability and quality, vegetation and fire management, adaptability of wildlife populations, disease risk, human-wildlife conflict, wildlife crime, and human dimensions of wildlife conservation. Using this model system, we summarize key lessons and identify critical threats highlighting future research needs to support wildlife management. Research in the GEL has followed a trajectory seen elsewhere reflecting an increase in complexity and integration across biological scales over time. Yet, despite these trends, a gap exists between the scope of recent research efforts and the needs of wildlife conservation to adapt to climate and land-use changes. Given the complex nature of climate change, in addition to locally existing system stressors, a framework of forward-thinking adaptive management to address these challenges, supported by integrative and multidisciplinary research could be beneficial. One critical area for growth is to better integrate research and wildlife management across land-use types. Such efforts have the potential to support wildlife conservation efforts and human development goals, while building resilience against the impacts of climate change. While our conclusions reflect the specifics of the GEL ecosystem, they have direct relevance for other African dryland systems impacted by global change.

Africa, Greater Etosha Landscape↗

USGS2020

Relative reproductive phenology and synchrony affect neonate survival in a nonprecocial ungulate

Degree of reproductive synchronization in prey is hypothesized as a predator defense strategy reducing prey risk via predator satiation or predator avoidance. Species with precocial young, especially those exposed to specialist predators, should be highly synchronous to satiate predators (predator satiation hypothesis), while prey with nonprecocial (i.e. altricial) young, especially those exposed to generalist predators, should become relatively asynchronous to avoid predator detection (predator avoidance hypothesis). The white-tailed deer Odocoileus virginianus in North America is an example of a nonprecocial ungulate that uses the hider strategy early in life; its primary predator (coyote; Canis latrans ) is a generalist, making white-tailed deer a good model species to test the predator avoidance hypothesis. We used birth dates and known fates of white-tailed deer neonates ( n = 1,032) across nine study sites varying in relative synchrony and predator assemblages to test the predator avoidance hypothesis. We predicted that relative birthing asynchrony of the population would increase relative survival at the population level; therefore, at the individual scale, neonate birth date nearer to mean birthing date in a respective population would not influence individual survival. Coyotes were responsible for the majority of predation events, and survival of those neonates increased the closer the individual was born to peak birthing season in each respective population. Also, at the population level, reproductive asynchronization negatively affected survival. Contrary to the predator avoidance hypothesis, our data indicate patterns in neonate survival for white-tailed deer better support the predator satiation hypothesis at the individual and population level. Additionally, coyotes may present a selective force great enough to shift reproductive synchrony such that predator satiation may become a feasible defense strategy for neonates at local spatial scales. Our results indicate that synchronizing reproduction may still be the most effective strategy to reduce individual predation risk from generalist predators, particularly when the window of heightened resource availability to the prey is narrow.

Alabama, Louisiana, Michigan, North Carolina, Penn↗

USGS2020

Effects of body size on estimation of mammalian area requirements

Accurately quantifying species’ area requirements is a prerequisite for effective area-based conservation. This typically involves collecting tracking data on species of interest and then conducting home-range analyses. Problematically, autocorrelation in tracking data can result in space needs being severely underestimated. Based on the previous work, we hypothesized the magnitude of underestimation varies with body mass, a relationship that could have serious conservation implications. To evaluate this hypothesis for terrestrial mammals, we estimated home-range areas with global positioning system (GPS) locations from 757 individuals across 61 globally distributed mammalian species with body masses ranging from 0.4 to 4000 kg. We then applied block cross-validation to quantify bias in empirical home-range estimates. Area requirements of mammals <10 kg were underestimated by a mean approximately15%, and species weighing approximately100 kg were underestimated by approximately50% on average. Thus, we found area estimation was subject to autocorrelation-induced bias that was worse for large species. Combined with the fact that extinction risk increases as body mass increases, the allometric scaling of bias we observed suggests the most threatened species are also likely to be those with the least accurate home-range estimates. As a correction, we tested whether data thinning or autocorrelation-informed home-range estimation minimized the scaling effect of autocorrelation on area estimates. Data thinning required an approximately93% data loss to achieve statistical independence with 95% confidence and was, therefore, not a viable solution. In contrast, autocorrelation-informed home-range estimation resulted in consistently accurate estimates irrespective of mass. When relating body mass to home range size, we detected that correcting for autocorrelation resulted in a scaling exponent significantly >1, meaning the scaling of the relationship changed substantially at the upper end of the mass spectrum.

Conservation Biology↗

USGS2020

Ecological insights from three decades of animal movement tracking across a changing Arctic

The Arctic is entering a new ecological state, with alarming consequences for humanity. Animal-borne sensors offer a window into these changes. Although substantial animal tracking data from the Arctic and subarctic exist, most are difficult to discover and access. Here, we present the new Arctic Animal Movement Archive (AAMA), a growing collection of more than 200 standardized terrestrial and marine animal tracking studies from 1991 to the present. The AAMA supports public data discovery, preserves fundamental baseline data for the future, and facilitates efficient, collaborative data analysis. With AAMA-based case studies, we document climatic influences on the migration phenology of eagles, geographic differences in the adaptive response of caribou reproductive phenology to climate change, and species-specific changes in terrestrial mammal movement rates in response to increasing temperature.

Science↗

USGS2019

An analysis of autocorrelation and bias in home range estimation

Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated-Gaussian reference function AKDE, Silvermans rule of thumb, and least squares cross-validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half-sample cross-validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ( N̂ area ) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID-based estimates by a mean factor of 2. The median number of cross-validated locations included in the hold-out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing N̂ area . To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animals movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small N̂ area . While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an N̂ area >1,000, where 30% had an N̂ area <30. In this frequently encountered scenario of small N̂ area , AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.

Ecological Monographs↗

USGS2018

Genetic diversity, effective population size, and structure among black bear populations in the Lower Mississippi Alluvial Valley, USA

Multiple small populations of American black bears Ursus americanus , including the recently delisted Louisiana black bear subspecies U. a. luteolus , occupy a fragmented landscape in the Lower Mississippi Alluvial Valley, USA (LMAV). Populations include bears native to the LMAV, bears translocated from Minnesota during the 1960s, and recently reintroduced and colonizing populations sourced from within the LMAV. We estimated population structure, gene flow, and genetic parameters important to conservation of small populations using genotypes at 23 microsatellite markers for 265 bears from seven populations. We inferred five genetic clusters corresponding to the following populations: White River and western Mississippi, Tensas River and Three Rivers, Upper Atchafalaya, Lower Atchafalaya, and Minnesota. Upper Atchafalaya was suggested as the product of Minnesota-sourced translocations, but those populations have since diverged, likely because of a founder effect followed by genetic drift and isolation. An admixture zone recently developed in northeastern Louisiana and western Mississippi between migrants from White River and Tensas River, resulting in a Wahlund effect. However, gene flow among most populations has been limited and considerable genetic differentiation accumulated (global F ST = 0.22), particularly among the three Louisiana black bear populations that existed when federal listing occurred. Consistent with previous bottlenecks, founder effects, and persisting isolation, all LMAV bear populations had low genetic diversity ( A R = 2.08–4.81; H E = 0.36–0.63) or small effective population size ( N E = 3–49). Translocating bears among populations as part of a regional genetic restoration program may help improve genetic diversity and increase effective population sizes.

Lower Mississippi Alluvial Valley↗

USGS2018

Body size and lean mass of brown bears across and within four diverse ecosystems

Variation in body size across populations of brown bears (Ursus arctos) is largely a function of the availability and quality of nutritional resources while plasticity within populations reflects utilized niche width with implications for population resiliency. We assessed skull size, body length, and lean mass of adult female and male brown bears in four Alaskan study areas that differed in climate, primary food resources, population density, and harvest regime. Full body-frame size, as evidenced by asymptotic skull size and body length, was achieved by 8 to 14 years of age across populations and sexes. Lean body mass of both sexes continued to increase throughout their life. Differences between populations existed for all morphological measures in both sexes, bears in ecosystems with abundant salmon were generally larger. Within all populations, broad variation was seen in body size measures of adults with females displaying roughly a 2-fold difference in lean mass and males showing a 3- to 4-fold difference. The high level of intraspecific variation seen across and within populations suggests the presence of multiple life-history strategies and niche variation relative to resource partitioning, risk tolerance or aversion, and competition. Further, this level of variation indicates broad potential to adapt to changes within a given ecosystem and across the species’ range.

Alaska↗

USGS2018

Plasticity in physiological condition of female brown bears across diverse ecosystems

Variation in life history strategies facilitates the near global distribution of mammals by expanding realized niche width. We investigated physiological plasticity in the spring body composition of adult female brown bears ( Ursus arctos ) across 4 diverse Alaskan ecosystems. Brown bears are a highly intelligent omnivore with a historic range spanning much of North America, Europe, and Asia. We hypothesized that body mass, fat mass, lean mass, and total caloric content would increase across populations with increasing food resource availability. Throughout their range, brown bears enter a period of torpor during winter months, decreasing their metabolic rate as an adaptation to this period of reduced food availability. They also give birth to and nourish offspring during this time. Due to this specific life history strategy, we further hypothesized that proportional body fat and the proportion of total calories derived from fat would be consistent across populations. Our results supported our first hypothesis: body, fat, and lean masses, and caloric content of bears across populations increased with the quality and abundance of available food. However, the proportional body fat content and proportion of calories from fat differed across populations indicating population-specific strategies to meet the demands of reduced seasonal food availability, offspring production and rearing, and climate as well as some plasticity to respond to environmental change or ecosystem perturbations. Investigations of body condition and energetics benefit from combined assessments of absolute, proportional, and caloric metrics to understand the nuances of brown bear physiological dynamics across and within populations.

Alaska↗

USGS2018

Influences of landscape heterogeneity on home-range sizes of brown bears

Animal space use is influenced by many factors and can affect individual survival and fitness. Under optimal foraging theory, individuals use landscapes to optimize high-quality resources while minimizing the amount of energy used to acquire them. The spatial resource variability hypothesis states that as patchiness of resources increases, individuals use larger areas to obtain the resources necessary to meet energetic requirements. Additionally, under the temporal resource variability hypothesis, seasonal variation in available resources can reduce distances moved while providing a variety of food sources. Our objective was to determine if seasonal home ranges of brown bears ( Ursus arctos ) were influenced by temporal availability and spatial distribution of resources and whether individual reproductive status, sex, or size (i.e., body mass) mediated space use. To test our hypotheses, we radio collared brown bears ( n = 32 [9 male, 23 female]) in 2014–2016 and used 18 a priori selected linear models to evaluate seasonal utilization distributions (UD) in relation to our hypotheses. Our top-ranked model by AIC c , supported the spatial resource variability hypothesis and included percentage of like adjacency (PLADJ) of all cover types (P < 0.01), reproductive class (P > 0.17 for males, solitary females, and females with dependent young), and body mass (kg; P = 0.66). Based on this model, for every percentage increase in PLADJ, UD area was predicted to increase 1.16 times for all sex and reproductive classes. Our results suggest that landscape heterogeneity influences brown bear space use; however, we found that bears used larger areas when landscape homogeneity increased, presumably to gain a diversity of food resources. Our results did not support the temporal resource variability hypothesis, suggesting that the spatial distribution of food was more important than seasonal availability in relation to brown bear home range size.

Alaska↗