Landscape change and age ratios for mule deer (Odocoileus hemionus) herd units in Wyoming,1980-2019
No abstract available.
Wyoming↗
Geology topics
Aaron N. Johnston
Publications and source records attributed to Aaron N. Johnston.
The interplay of habitat quality and temperature shape demographic patterns of mule deer (Odocoileus hemionus) in North America
Mule deer ( Odocoileus hemionus ) are declining in abundance across their broad distribution in western North America. Identifying drivers of mule deer demography could inform habitat restoration. However, linking habitat quality to vital rates is challenging and often done indirectly using proxy metrics. We combine habitat selection with climate-related effects to identify synergistic influences affecting mule deer age ratios (fawn:doe). We used location data from 1473 female deer over 22 years in Wyoming to fit seasonal resource selection models, predict habitat suitability, and model age ratios as a function of drought conditions, winter severity, and seasonal habitat. Here we show temperature had the largest effect on mule deer recruitment with age ratios declining following hotter summers and colder winters. Age ratios increased with higher proportions of habitat with high-quality summer habitat of particular importance. Given the likely increases in summer temperatures and extreme winter weather events, populations may struggle to increase recruitment over the next half-century. Targeted management supporting forage quantity and quality, especially on summer range, could buffer the effects of decades-long drought conditions. Our findings also indicate mule deer avoid areas with high densities of oil and gas development. By delineating important mule deer habitat, we offer spatial tools for development siting and mitigation in Wyoming and a framework for broader application across the western United States.
Wyoming↗
Integrating climate and anthropogenic dynamics can inform multifaceted management for declining mule deer populations
Wildlife and their habitats face profound challenges from climate and landscape-scale changes that extend beyond the influence and time horizon of most biologists and land managers. In this changing environment, long-term datasets can enhance assessments of how demographic trends respond to interactions among local (e.g., habitat restoration decisions) and broad extent drivers, including energy development, to shape wildlife populations. Although many studies evaluate habitat selection or demographics for a single population, our multipopulation, multiscale study quantifies the influence of local management actions given broader environmental forces using both immediate and lagged effects. This approach may be particularly important for species with high site fidelity that may have less adaptive capacity, including mule deer ( Odocoileus hemionus ), which are experiencing widespread population declines. We analyzed a 40-year (1980–2019) dataset for 37 mule deer populations across Wyoming, USA, to test hypotheses about and quantify the relative influence of conditions within winter use areas on annual rates of juvenile recruitment. Recruitment has been strongly affected by multiple factors largely beyond the control of managers. Land cover (agriculture and shrubland) had the largest positive effects on recruitment, with estimates more than twice the magnitude of other variables, but also had limited presence in some winter use areas. The next strongest effect sizes were shared by energy developments (including oil/gas and wind energy) and climatic conditions, which, except for wind turbines, had broad distributions across winter use areas. Recruitment increased with higher mean winter temperatures and summer precipitation, but declined with wind, oil and gas developments, cumulative drought, and wildfire. Expected increases in drought and decreases in summer precipitation may constrain options to sustain mule deer populations. Although mule deer recruitment may sometimes be enhanced through habitat restoration, effects varied with treatment type, habitat type, and time since treatment. Given large constraining effects of temperature and drought, supporting drought resiliency for important habitat may be useful. Our results can be used to weigh the relative strength of threats and the value of restoration actions, interpret historic demographic change, prioritize populations for conservation, and optimize options for wildlife habitat management.
Wyoming↗
Potential risks of vegetation treatments to introduce and increase invasive annual grasses in rangelands of Montana, North Dakota, and South Dakota— A science synthesis to inform National Environmental Policy Act analyses
The U.S. Geological Survey is working with Federal land management agencies to develop a series of planned structured science syntheses to support environmental effects analyses that agencies conduct under the National Environmental Policy Act (NEPA). This report synthesizes science information relevant to environmental effects analyses concerned with potential increases in the distribution and abundance of invasive annual grasses (IAGs) from proposed vegetation treatments for habitat restoration. The focal environments for this synthesis are rangelands in the intermontane valleys of Montana and the northern Great Plains of Montana, North Dakota, and South Dakota. The synthesis is organized to align with the standard elements of NEPA analyses and provides information on relevant scientific studies, data availability, analysis methods, and mitigation measures. We found that the likelihood of increasing IAGs from vegetation treatments depends on treatment type and environmental context. In sagebrush ecosystems of the focal region, prescribed fire often reduces or does not increase IAGs. Treatments that cause soil disturbances, such as mechanical removals of sagebrush or firebreak constructions, are more likely to increase IAGs than other treatments. Herbicides applied to reduce sagebrush cover have not increased the proportion of IAGs in the plant community. Temperature and precipitation have been strong factors in determining IAG responses to vegetation treatments in sagebrush ecosystems of the focal region, where more precipitation in spring and summer likely provides a competitive edge to native, perennial grasses more than winter annual grasses like Bromus tectorum L. (cheatgrass). In grasslands, prescribed fire often reduces IAGs, but effects depend on the abundance of native species and are often short lived. Mowing can increase or decrease IAGs in grassland ecosystems. Grassland site conditions, such as southeast-facing slopes, sandier or rockier sites, or lower native species cover or richness affect the likelihood of invasion by annual grasses. Maintaining adequate cover of perennial vegetation creates rangelands that are resistant and resilient to annual grass invasions. Managers can minimize invasion potential by focusing on treatment type, placement, and seasonal timing. Herbicides also can provide effective mitigation, especially in combination with other controls such as prescribed fire or grazing. This report can be incorporated by reference in NEPA documentation, included in a project record, or provide a general reference for understanding and identifying literature about increases in IAGs associated with vegetation treatments in rangelands in this focal region.
Montana, North Dakota, South Dakota↗
Greater sage-grouse seasonal habitat associations: A review and considerations for interpretation and management applications
Habitat features needed by wildlife can change in composition throughout the year, particularly in temperate ecosystems, leading to distinct seasonal spatial-use patterns. Studies of species-habitat associations therefore often focus on understanding relationships within discrete seasonal periods with common goals of prediction (e.g., habitat mapping) and inference (e.g., interpreting model coefficients). Across the range of the greater sage-grouse ( Centrocercus urophasianus ) of western North America, the increasing use of high-frequency tracking devices has led to a surge in habitat association studies covering multiple temporal periods and spatial extents. We reviewed the literature for seasonal habitat association studies corresponding to the second and third orders of selection (Johnson 1980). Our objectives were to summarize the methodological approaches used to estimate habitat associations to aid understanding in cross-study comparisons and identify common habitat features reported as selected or avoided within different seasonal periods. We reviewed 71 second- and third-order studies published from 2007–2023 that evaluated covariates collected in a geographic information system (GIS) and modeled probability of selection or intensity of use. The most common study design evaluated a single level of selection (third-order) and was multi-scale (i.e., covariates were measured at varying spatial grains). The most common model approach estimated habitat associations using resource selection functions (RSFs) fit with logistic regression. Studies mostly focused on the breeding periods and winter, but all seasons throughout the annual cycle were covered. There was clear support for selection of sagebrush and avoidance of trees and rugged terrain across seasons, and strong selection of mesic conditions in summer. However, habitat associations for most covariates were mixed, with proportionally equivalent selection and avoidance reported, even within the same seasons. Different factors hampered cross-study comparisons, including variation in study design, but additional contributors likely included important context-dependent habitat associations, such as functional responses to changing habitat availability. We suggest collaborative studies leveraging multiple datasets can help improve seasonal habitat inference by removing the effects of variable study designs.
Journal of Wildlife Management↗
Effects of noise from oil and gas development on raptors and songbirds—A science synthesis to inform National Environmental Policy Act analyses
The U.S. Geological Survey is working with Federal land management agencies to develop a series of science syntheses to support environmental effects analyses that agencies conduct to comply with the National Environmental Policy Act (NEPA). This report synthesizes science information about the potential effects of noise from oil and gas development on North American raptors, songbirds, and other small avian species. We conducted a structured search of published scientific literature to find information about noise levels produced during oil and gas development, methods for analyzing sound propagation, the effects of noise on avian species, and measures to reduce noise emissions. We follow the organization first established in U.S. Geological Survey Scientific Investigations Report 2023-5114, in which the report sections align with standard elements of NEPA analyses. We found that oil and gas development is a common source of human-caused noise on public lands and includes noise sources such as heavy construction and drilling machinery, long-term production machinery, truck traffic, and aircraft. Common techniques for predicting potential noise include field data collection using a sound level meter, inference from previously published data, and sound propagation modeling. The effects of human-caused noise on songbirds are well researched, whereas, among raptors, only owl species have been well-studied in relation to noise. Several studies have established that noise can reduce owl hunting success because many owl species are heavily reliant on hearing prey when hunting. The effects of noise on songbirds depend on several factors. Typically, birds that rely on vocal communication for mating, predator detection, and spatial orientation, and that are less able to adjust the frequencies of their vocalizations, are more vulnerable to behavioral changes and decreased fitness in noisy areas. Techniques suggested in the literature for reducing noise emissions include artificial sound barriers, seasonal and daily timing restrictions, traffic control measures, and siting infrastructure to take advantage of natural sound barriers. Public land managers can use this report by incorporating it by reference in NEPA documentation, as supplemental information, or as a general reference to find literature or identify gaps in the literature about the effects of noise from oil and gas development on raptors and songbirds.
Scientific Investigations Report↗
Structured science syntheses to inform decision making on Federal public lands
The U.S. Geological Survey, Bureau of Land Management, and U.S. Fish and Wildlife Service partnered to develop a new type of science product: the structured science synthesis. Structured science syntheses are peer-reviewed reports that synthesize science information about a priority resource management issue on public lands. Structured science syntheses are developed explicitly to facilitate the application of science to decision making. Key characteristics of structured science syntheses include that they are coproduced with resource managers, developed using clear, repeatable methods and designed for ease of use. The syntheses include different types of science information needed for analyses completed under the National Environmental Policy Act.
Fact Sheet↗
Effects of culverts on habitat connectivity in streams—A science synthesis to inform National Environmental Policy Act analyses
The U.S. Geological Survey is working with Federal land management agencies to develop a series of science syntheses to support environmental effects analyses that agencies conduct to comply with the National Environmental Policy Act (NEPA). This report synthesizes science information about the potential effects of culverts on stream connectivity and subsequent effects on fish. We conducted a structured search of published scientific literature to find information about (1) culvert design, installation, and degradation; (2) methods for analyzing culvert condition and quantifying stream connectivity; and (3) the effects of changes to stream connectivity on freshwater fish. We follow the organization first established in U.S. Geological Survey Scientific Investigations Report 2023-5114, in which the report sections align with standard elements of NEPA analyses. We found that, while the effects of dams on stream biota are well documented, smaller barriers at road crossings, like culverts, are prevalent and collectively have a substantial effect on habitat connectivity. Individual culverts differ in the degree to which they impede the movement of aquatic organisms, and we documented methods to assess and estimate the permeability of a culvert, or the ability of aquatic organisms to pass through it. Finally, we outlined methods for using culvert location and permeability information to quantify connectivity in a watershed based on the Dendritic Connectivity Index. Studies have shown that channel constriction, perched outlets, and extreme flow velocities are some of the characteristics of culverts that may hinder aquatic organism passage. Culverts can serve as daily and seasonal barriers to fish, disrupting access to habitat and essential resources like cold water or overwintering refuges. Reduced connectivity can have population-level effects, leading to lower fish species richness and abundance in affected watersheds. Public land managers can use this report by incorporating it by reference in NEPA documentation, as supplemental information, or as a general reference for literature about the effects of culverts on stream connectivity and freshwater fish.
Scientific Investigations Report↗
Effects of noise from oil and gas development on ungulates and small mammals—A science synthesis to inform National Environmental Policy Act analyses
The U.S. Geological Survey is working with Federal land management agencies to develop a series of science syntheses to support environmental effects analyses that agencies conduct to comply with the National Environmental Policy Act (NEPA). This report synthesizes science information about the potential effects of noise from oil and gas development on North American ungulates and small mammals, including rodents and leporids. We conducted a structured search of published scientific literature to find information about noise levels produced during oil and gas development, methods for analyzing sound propagation, the effects of noise on ungulates and small mammals, and measures to reduce noise emissions. We organized the sections of this synthesis to align with standard elements of NEPA analyses. We found that oil and gas development is a common source of human-caused noise on public lands and includes noise sources such as heavy construction and drilling machinery, long-term production machinery, truck traffic, and aircraft. Common techniques for predicting potential noise include field data collection using a sound level meter, inference from previously published data, and sound propagation modeling. A substantial body of research shows that human-caused noise can affect wildlife health and behavior, with variation in sensitivity to noise among species. Studies have shown consistent, detectable effects of noise on ungulates, but the amount of literature on ungulates is very small, and additional research could improve our understanding of differences in effects among species, seasons, and individual indicators of fitness. Several species of small mammals are dependent on audible signals for predator detection and communication, and noise has been shown to affect their vigilance and foraging behavior. However, other studies have documented no effects to rodents in noisy areas, and the effects of noise on small mammals may differ by species and study system. Techniques suggested in the literature for reducing noise emissions include sound barriers, seasonal and daily timing restrictions, traffic control measures, and siting infrastructure to take advantage of natural sound barriers. Public land managers can use this report by incorporating it by reference in NEPA documentation, as supplemental information, or as a general reference for literature about the effects of noise from oil and gas development on ungulates and small mammals.
Scientific Investigations Report↗
Hidden Markov movement models reveal diverse seasonal movement patterns in two North American ungulates
Animal movement is the mechanism connecting landscapes to fitness, and understanding variation in seasonal animal movements has benefited from the analysis and categorization of animal displacement. However, seasonal movement patterns can defy classification when movements are highly variable. Hidden Markov movement models (HMMs) are a class of latent-state models well-suited to modeling movement data. Here, we used HMMs to assess seasonal patterns of variation in the movement of pronghorn ( Antilocapra americana ), a species known for variable seasonal movements that challenge analytical approaches, while using a population of mule deer ( Odocoileus hemionus ), for whom seasonal movements are well-documented, as a comparison. We used population-level HMMs in a Bayesian framework to estimate a seasonal trend in the daily probability of transitioning between a short-distance local movement state and a long-distance movement state. The estimated seasonal patterns of movements in mule deer closely aligned with prior work based on indices of animal displacement: a short period of long-distance movements in the fall season and again in the spring, consistent with migrations to and from seasonal ranges. We found seasonal movement patterns for pronghorn were more variable, as a period of long-distance movements in the fall was followed by a winter period in which pronghorn were much more likely to further initiate and remain in a long-distance movement pattern compared with the movement patterns of mule deer. Overall, pronghorn were simply more likely to be in a long-distance movement pattern throughout the year. Hidden Markov movement models provide inference on seasonal movements similar to other methods, while providing a robust framework to understand movement patterns on shorter timescales and for more challenging movement patterns. Hidden Markov movement models can allow a rigorous assessment of the drivers of changes in movement patterns such as extreme weather events and land development, important for management and conservation.
Wyoming↗
Beyond presence mapping: Predicting fractional cover of non-native vegetation in Sentinel-2 imagery using an ensemble of MaxEnt models
Non-native species maps are important tools for understanding and managing biological invasions. We demonstrate a novel approach to extend presence modeling to map fractional cover (FC) of non-native yellow sweet clover Melilotus officinalis in the Northern Great Plains, USA. We used ensembles of MaxEnt models to map FC across landscapes from satellite imagery trained from regional aerial imagery that was trained by local unmanned aerial vehicle (UAV) imagery. Clover cover from field surveys and classified UAV imagery were nearly identical ( n = 22, R 2 = 0.99). Two classified UAV images provided training data to map clover presence with MaxEnt and National Agricultural Imagery Program (NAIP) aerial imagery. We binned cover predictions from NAIP imagery within each Sentinel-2 pixel into eight cover classes to create pure (100%) and FC (20%–95%) training data and modeled each class separately using MaxEnt and Sentinel-2 imagery. We mapped pure clover with one classification threshold and compared its performance to 15 candidate maps that included FC predictions outside pure predictions. Each FC map represented alternative combinations of five MaxEnt thresholds and three approaches to assign cover to pixels with multiple predictions from the FC ensemble. Evaluations of performance with independent datasets revealed maps including FC corresponded to field ( n = 32, R 2 range: 0.39–0.68) and UAV ( n = 20, R 2 range: 0.61–0.84) data better than pure clover maps ( R 2 = 0.15 and 0.31, respectively). Overall, the pure clover map predicted 3.2% cover, whereas the three best performing FC maps predicted 6.6%–8.0% cover. Including FC predictions increased accuracy and cover predictions which can improve ecological understanding of invasions. Our method allows efficient FC mapping for vegetative species discernible in UAV imagery and may be especially useful for mapping rare, irruptive or patchily distributed species with poor representation in field data, which challenges landscape-level mapping.
Montana, South Dakota↗
Wind-energy development alters pronghorn migration at multiple scales
Migration is a critical behavioral strategy necessary for population persistence and ecosystem functioning, but migration routes have been increasingly disrupted by anthropogenic activities, including energy development. Wind energy is the world's fastest growing source of electricity and represents an important alternative to hydrocarbon extraction, but its effects on migratory species beyond birds and bats are not well understood. We evaluated the effects of wind-energy development on pronghorn migration, including behavior and habitat selection, to assess potential effects on connectivity and other functional benefits including stopovers. We monitored GPS-collared female pronghorn from 2010 to 2012 and 2018 to 2020 in south-central Wyoming, USA, an area with multiple wind-energy facilities in various stages of development and operation. Across all time periods, we collected 286 migration sequences from 117 individuals, including 121 spring migrations, 123 fall migrations, and 42 facultative winter migrations. While individuals continued to migrate through wind-energy facilities, pronghorn made important behavioral adjustments relative to turbines during migration. These included avoiding turbines when selecting stopover sites in spring and winter, selecting areas farther from turbines at a small scale in spring and winter, moving more quickly near turbines in spring (although pronghorn moved more slowly near turbines in the fall), and reducing fidelity to migration routes relative to wind turbines under construction in both spring and fall. For example, an increase in distance to turbine from 0 to 1 km translated to a 33% and 300% increase in the relative probability of selection for stopover sites in spring and winter, respectively. The behavioral adjustments pronghorn made relative to wind turbines could reduce the functional benefits of their migration, such as foraging success or the availability of specific routes, over the long term.
Wyoming↗
Eyes on the herd: Quantifying ungulate density from satellite, unmanned aerial systems, and GPScollar data
Novel approaches to quantifying density and distributions could help biologists adaptively manage wildlife populations, particularly if methods are accurate, consistent, cost-effective, rapid, and sensitive to change. Such approaches may also improve research on interactions between density and processes of interest, such as disease transmission across multiple populations. We assess how satellite imagery, unmanned aerial system (UAS) imagery, and Global Positioning System (GPS) collar data vary in characterizing elk density, distribution, and count patterns across times with and without supplemental feeding at the National Elk Refuge (NER) in the US state of Wyoming. We also present the first comparison of satellite imagery data with traditional counts for ungulates in a temperate system. We further evaluate seven different aggregation metrics to identify the most consistent and sensitive metrics for comparing density and distribution across time and populations. All three data sources detected higher densities and aggregation locations of elk during supplemental feeding than non-feeding at the NER. Kernel density estimates (KDEs), KDE polygon areas, and the first quantile of interelk distances detected differences with the highest sensitivity and were most highly correlated across data sources. Both UAS and satellite imagery provide snapshots of density and distribution patterns of most animals in the area at lower cost than GPS collars. While satellite-based counts were lower than traditional counts, aggregation metrics matched those from UAS and GPS data sources when animals appeared in high contrast to the landscape, including brown elk against new snow in open areas. UAS counts of elk were similar to traditional ground-based counts on feed grounds and are the best data source for assessing changes in small spatial extents. Satellite, UAS, or GPS data can provide appropriate data for assessing density and changes in density from adaptive management actions. For the NER, where high elk densities are beneath controlled airspace, GPS collar data will be most useful for evaluating how management actions, including changes in the dates of supplemental feeding, influence elk density and aggregation across large spatial extents. Using consistent and sensitive measures of density may improve research on the drivers and effects of density within and across a wide range of species.
Wyoming↗
Foreword to the special Issue on ‘The rapidly expanding role of drones as a tool for wildlife research’
Drones have emerged as a popular wildlife research tool, but their use for many species and environments remains untested and research is needed on validation of sampling approaches that are optimised for unpiloted aircraft. Here, we present a foreword to a special issue that features studies pushing the taxonomic and innovation boundaries of drone research and thus helps address these knowledge and application gaps. We then conclude by highlighting future drone research ideas that are likely to push biology and conservation in exciting new directions.
Wildlife Research↗
Variable effects of wind-energy development on seasonal habitat selection of pronghorn
In the face of climate change, wind energy represents an important alternative to oil and gas extraction to meet increasing energy demands, but it has the potential to disrupt wildlife populations. Because behavioral adjustments, such as altered habitat selection, are a primary way that long-lived species respond to novel disturbances, we evaluated effects of wind energy development on pronghorn ( Antilocapra americana ) space use and habitat selection. Using data from GPS-collared female pronghorn in the Shirley Basin of south-central Wyoming, USA, we tested four potential effects of wind turbines on pronghorn space use during the summer and winter: (1) displacement away from wind turbines, (2) increase in size of home ranges, (3) short-term avoidance behavior within home ranges, and (4) changes in avoidance behavior within home ranges over time. We monitored 166 individuals over five summers (2010, 2011, 2018, 2019, and 2020) and 142 individuals over five winters (2009/2010, 2010/2011, 2011/2012, 2018/2019, and 2019/2020) and used resource selection functions to evaluate selection relative to turbines after controlling for other habitat factors, such as snow depth. Although a lack of consistent negative effects of wind turbines on pronghorn across years suggested that wind energy development may have less severe and more intermittent effects on pronghorn than oil and gas development has had on other ungulates, there was a trend toward increased displacement during the study and behavioral avoidance was apparent for individuals in close proximity to turbines. However, pronghorn were highly variable in their fine-scale habitat selection, across both individuals and years, which could make effects of wind energy development difficult to detect. Nevertheless, some individuals, particularly those close to wind-energy facilities, did avoid turbines, which could translate to population-level behavioral or demographic changes over time and affect the resilience and stability of the population. Over time, the accumulation of development, including wind turbines, roads, and fences, can both limit movement and fragment habitat, potentially reaching a critical threshold beyond which populations are negatively impacted.
Wyoming↗
U.S. Geological Survey science for the Wyoming Landscape Conservation Initiative—2018 annual report
The Wyoming Landscape Conservation Initiative (WLCI) was established in 2007 as a collaborative interagency partnership to develop and implement science-based conservation actions. During the past 11 years, partners from U.S. Geological Survey (USGS), State and Federal land management agencies, universities, and the public have collaborated to implement a long-term (more than 10 years) science-based program that assesses and enhances the quality and quantity of wildlife habitats in the southwest Wyoming region while facilitating responsible development. The USGS WLCI Science Team completes scientific research and develops tools that inform and support WLCI partner planning, decision making, and on-the-ground management actions. In fiscal year 2018, the USGS initiated 3 new projects and continued efforts on 21 ongoing science and web-development projects. The first new project was initiated to support Secretarial Order 3362 which calls on the USGS to assist Western States in mapping big-game migration corridors and developing new mapping tools. During 2018, the USGS hosted a workshop in Laramie, Wyoming, which included more than 70 State and Federal wildlife experts from Colorado, New Mexico, Texas, and Wyoming. Most of the mapping and migration tool curricula used in the workshop were derived from prior WLCI studies and mapping efforts of big-game migration movement in habitats undergoing large-scale energy development. The second new project was in response for WLCI partners to better understand sedimentation and hydrogeomorphic processes in a cold-desert headwater and the third new project was designed to improve our approach for people to access, manage, and analyze WLCI data and WLCI resource information. The USGS published 18 products (including peer-reviewed journal articles, USGS series publications, and data releases) and provided more than a dozen professional oral and poster presentations at scientific meetings and numerous informal presentations to WLCI partners at meetings and workshops. This report summarizes the objectives and status of each project and highlights the USGS 2018 accomplishments and products.
Wyoming↗
Human activities and weather drive contact rates of wintering elk
Wildlife aggregation patterns can influence disease transmission. However, limited research evaluates the influence of anthropogenic and natural factors on aggregation. Many managers would like to reduce wildlife contact rates, driven by aggregation, to limit disease transmission. We develop a novel analytical framework to quantify how management activities such as supplemental feeding and hunting versus weather drive contact rates while accounting for correlated contacts. We apply the framework to the National Elk Refuge (NER), Wyoming, USA, where the probable arrival of chronic wasting disease (CWD) has magnified concerns. We used a daily proximity index to measure contact rates among 68 global positioning system collared elk from 2016 to 2019. We modelled contact rates as a function of abiotic weather‐related effects, anthropogenic effects and aggregation from the prior day. The winter of 2017–2018 had greater natural forage availability and little snow, which led to a rare non‐feeding year on the NER and provided a unique opportunity to evaluate the effect of feeding on contact rates relative to other conditions. Supplemental feeding was the strongest predictor of aggregation, and contact rates were 2.6 times larger while feeding occurred compared to the baseline rate (0.34 and 0.13, respectively). Snow‐covered area was the second strongest predictor of contact rates highlighting the importance of abiotic factors to elk aggregation, but this effect had half the strength of feeding. These results are the first to show, even in animals that congregate naturally, how greatly supplemental feeding amplifies aggregation. Contact rates were also 23% lower during times when elk hunting was active (0.10) compared to the baseline. Synthesis and applications . Supplemental feeding increased contacts between elk well above the natural effects of weather, even after accounting for correlated movement expected in wintering ungulates. Similarly, differences in hunting season timing with adjacent areas led to an increase in contacts, suggesting an additional management option for reducing aggregation. The analytical framework presented supports the evaluation of temporally varying management actions that influence aggregation broadly and can be easily implemented whether the interest in changing aggregation is related to reduction of disease transmission, human–wildlife conflict or inter‐species competition.
Wyoming↗
Freezing in a warming climate: Marked declines of a subnivean hibernator after a snow drought
Recent snow droughts associated with unusually warm winters are predicted to increase in frequency and affect species dependent upon snowpack for winter survival. Changes in populations of some cold‐adapted species have been attributed to heat stress or indirect effects on habitat from unusually warm summers, but little is known about the importance of winter weather to population dynamics and how responses to snow drought vary among sympatric species. We evaluated changes in abundance of hoary marmots ( Marmota caligata ) over a period that included a year of record‐low snowpack to identify mechanisms associated with weather and snowpack. To consider interspecies comparisons, our analysis used the same a priori model set as a concurrent study that evaluated responses of American pikas ( Ochotona princeps ) to weather and snowpack in the same study area of North Cascades National Park, Washington, USA. We hypothesized that marmot abundance reflected mechanisms related to heat stress, cold stress, cold exposure without an insulating snowpack, snowpack duration, atmospheric moisture, growing‐season precipitation, or select combinations of these mechanisms. Changes in marmot abundances included a 74% decline from 2007 to 2016 and were best explained by an interaction of chronic dryness with exposure to acute cold without snowpack in winter. Physiological stress during hibernation from exposure to cold, dry air appeared to be the most likely mechanism of change in marmot abundance. Alternative mechanisms associated with changes to winter weather, including early emergence from hibernation or altered vegetation dynamics, had less support. A post hoc assessment of vegetative phenology and productivity did not support vegetation dynamics as a primary driver of marmot abundance across years. Although marmot and pika abundances were explained by strikingly similar models over periods of many years, details of the mechanisms involved likely differ between species because pika abundances increased in areas where marmots declined. Such differences may lead to diverging geographic distributions of these species as global change continues.
Washington↗