Geology topics

Alyson B. Courtemanch

Publications and source records attributed to Alyson B. Courtemanch.

11 recordsLinked to original sources

USGS2026

Space between houses influences movement and habitat selection of ungulates: Width as a novel metric of development

Wildlife often lose access to habitat due to housing development. The magnitude of indirect habitat loss can be conditional on the configuration of individual houses, but commonly used metrics (i.e. density or distance) can overlook the configuration of development. We introduce a novel framework to index the configuration of development based on the width of space between houses and associated structures. We use resource selection functions to assess the degree that GPS-collared elk ( Cervus canadensis ), mule deer ( Odocoileus hemionus ), pronghorn and moose ( Alces alces ) on winter range and on migration routes use space between houses within northwest Wyoming, USA, near the towns of Cody and Jackson. Further, to help inform regulations aiming to promote wildlife movement across a gradient of land uses, we differentiated between individuals residing in primarily rural and exurban areas. Rural populations of elk, mule deer, pronghorn and moose avoided spaces narrower than 2 km and never used spaces narrower than 50 m between houses, whereas exurban populations of elk, mule deer and moose selected for spaces narrower than 2 km but avoided spaces narrower than 50 m. We identified cutoffs in rural and exurban areas where space may become too narrow for most animals to use. Through this metric, managers and policy makers can inform the necessary width to maintain wildlife movement through corridors. Our width metric can be applied to other systems and our workflow is publicly available ( https://wildlifemovetools.org/width-calculator ) so users can estimate the width of space between structures in their focal areas. Synthesis and applications . In rural areas, maintaining spaces between houses >500 m will likely facilitate ungulate movement. To fully conserve functional habitat, such as unimpeded habitat use along migration corridors, maintaining spaces approximately >2.5 km between houses will likely be necessary.

Wyoming↗

USGS2025

Expression and mechanisms of behavioral plasticity in large mammals

Behavioral plasticity, the alteration of behavior in response to stimuli, is becoming increasingly important in the context of human-induced rapid environmental change. Theoretical and empirical studies suggest that the expression and magnitude of behavioral plasticity are likely facilitated or constrained primarily by two factors: environmental variation and endogenous traits such as body size. The contextual role of these factors on behavioral plasticity, however, is poorly understood; there are relatively few studies that have compared the magnitude and potential drivers of behavioral plasticity at different levels (i.e., population and individual) across species, especially in free-ranging animals with diverse behavioral traits such as large mammals. Here, we quantify and test potential hypotheses for the mechanisms underpinning behavioral plasticity at the individual and population level in response to variation in summer temperatures for 1068 animal-years in 17 populations across nine species of large mammals. All populations displayed behavioral plasticity in response to increased temperatures, modifying their relative selection for heat-relieving habitat attributes (e.g., elevation) and heat-generating behavior (i.e., movement speed). We found strong support for the hypothesis that the variability of the physical environment is an important driver of behavioral plasticity—both mean population behavioral plasticity and variation among individuals within each population in plasticity were lower with increased heterogeneity of habitat attributes such as tree cover. Yet, the variability in environmental conditions (i.e., the magnitude of the temperature increase) had no effect on behavioral plasticity within and among populations. We did not detect an effect of endogenous traits on the expression of behavioral plasticity; however, we note that data availability limited our tests of this hypothesis to a select few endogenous traits (body size, feeding guild, and sex of the tracked individuals) that predominantly vary at the species level, for which we had one to three replicate populations per species. Our results provide an integrative and generalizable understanding of the expression of behavioral plasticity among populations of large mammals in temperate environments and emphasize the important but nuanced role of environmental variation in determining the scope of behavioral plasticity in these populations.

Wyoming↗

USGS2024

Estimating ungulate migration corridors from sparse movement data

Many ungulates migrate between distinct summer and winter ranges, and identifying, mapping, and conserving these migration corridors have become a focus of local, regional, and global conservation efforts. Brownian bridge movement models (BBMMs) are commonly used to empirically identify these seasonal migration corridors; however, they require location data sampled at relatively frequent intervals to obtain a robust estimate of an animal’s movement path. Fitting BBMMs to sparse location data violates the assumption of conditional random movement between successive locations, overestimating the area (and width) of a migration corridor when creating individual and population-level occurrence distributions, and precluding the use of low-frequency, or sparse, data in mapping migration corridors. In an effort to expand the utility of BBMMs to include sparse global positioning system (GPS) data, we propose an alternative approach to model migration corridors from sparse GPS data. We demonstrate this method using GPS data collected every 2 hours from four mule deer (Odocoileus hemionus) and four elk (Cervus canadensis) herds within Wyoming and Idaho. First, we used BBMMs to estimate a baseline corridor for the 2-hour data. We then subsampled the 2-hour data to one location every 12 hours (a proxy for sparse data) and fitted BBMMs to the 12-hour data using a fixed motion variance (FMV) value, instead of estimating the Brownian motion variance empirically. A range of FMV values was tested to identify the value that best approximated the baseline migration corridor. FMV values within a species-specific range (mule deer: 400–1,200 m2; elk: 600–1,600 m2) successfully delineated migration corridors similar to the 2-hour baseline corridors; overall, lower values delineated narrower corridors and higher values delineated wider corridors. Optimal FMV values of 800 m2 (mule deer) and 1,000 m2 (elk) decreased the inflation of the 12-hour corridors relative to the 2-hour corridors from traditional BBMMs. This FMV approach thus enables using sparse movement data to approximate realistic migration corridor dimensions, providing an important alternative when movement data are collected infrequently. This approach greatly expands the number of datasets that can be used for migration corridor mapping—a useful tool for management and conservation across the globe.

Idaho, Wyoming↗

USGS2024

Infection–nutrition feedbacks: Fat supports pathogen clearance but pathogens reduce fat in a wild mammal

Though far less obvious than direct effects (clinical disease or mortality), the indirect influences of pathogens are difficult to estimate but may hold fitness consequences. Here, we disentangle the directional relationships between infection and energetic reserves, evaluating the hypotheses that energetic reserves influence infection status of the host and that infection elicits costs to energetic reserves. Using repeated measures of fat reserves and infection status in individual bighorn sheep ( Ovis canadensis ) in the Greater Yellowstone Ecosystem, we documented that fat influenced ability to clear pathogens ( Mycoplasma ovipneumoniae ) and infection with respiratory pathogens was costly to fat reserves. Costs of infection approached, and in some instances exceeded, costs of rearing offspring to independence in terms of reductions to fat reserves. Fat influenced probability of clearing pathogens, pregnancy and over-winter survival; from an energetic perspective, an animal could survive for up to 23 days on the amount of fat that was lost to high levels of infection. Cost of pathogens may amplify trade-offs between reproduction and survival. In the absence of an active outbreak, the influence of resident pathogens often is overlooked. Nevertheless, the energetic burden of pathogens likely has consequences for fitness and population dynamics, especially when food resources are insufficient.

Wyoming↗

USGS2023

Forage senescence and disease influence elk pregnancy across the Greater Yellowstone Ecosystem

For various temperate ungulate species, recent research has highlighted the potential for spring vegetation phenology (“green-up”) to influence individual condition, with purported benefits to population productivity. However, few studies have been able to measure the benefit on vital rates directly, and fewer still have investigated the comparative influence of other phenological periods on ungulate vital rates. In this study, we tracked phenological changes throughout the duration of the growing season and examined how their timing affected the probability of pregnancy in an ungulate population. We did this for elk ( Cervus canadensis ) across the Greater Yellowstone Ecosystem (GYE) by sampling 1106 adult females in winter at 25 sites over a 13-year period and assessing sources of variation in pregnancy using a Bayesian hierarchical model. Pregnancy rates were generally high across the GYE (82.4%), and the primary influences on probability of pregnancy were the timing of vegetation senescence (“brown-down”) in autumn and exposure to the reproductive disease brucellosis. Earlier forage brown-down in fall negatively influenced the probability of pregnancy of elk aged 6–9 years by an estimated 17.2% within the range (ca. 32 days) of observed brown-down end dates. While summer habitat quality has been inferred to influence elk pregnancy previously, our findings specify the key influence of foraging conditions later in the seasonal cycle, immediately before the breeding season. The reproductive disease brucellosis was also an important factor, reducing the probability of pregnancy by 12.4% in elk in the 6- to 9-year age class. Because pregnancy was tested before most disease-induced abortions occur, the apparent mechanism for this effect is a prolonged reduction in fertility beyond the period of initial exposure in which fetal mortality is typically expected. Our results prompt greater scrutiny of the combined effects of late-season phenology and disease on reproductive rates and population productivity in temperate ungulates.

Idaho, Montana, Wyoming↗

USGS2021

Life-history theory provides a framework for detecting resource limitation: A test of the Nutritional Buffer Hypothesis

For ungulates and other long-lived species, life-history theory predicts that nutritional reserves are allocated to reproduction in a state-dependent manner because survival is highly conserved. Further, as per capita food abundance and nutritional reserves decline (i.e., density dependence intensifies), reproduction and recruitment become increasingly sensitive to weather. Thus, the degree to which weather influences vital rates should be associated with proximity to nutritional carrying capacity—a notion that we refer to as the Nutritional Buffer Hypothesis. We tested the Nutritional Buffer Hypothesis using six moose ( Alces alces ) populations that varied in calf recruitment (33–69 calves/100 cows). We predicted that populations with high calf recruitment were nutritionally buffered against the effects of unfavorable weather, and thus were below nutritional carrying capacity. We applied a suite of tools to quantify habitat and nutritional condition of each population and found that increased browse condition, forage quality, and body fat were associated with increased pregnancy and calf recruitment, thereby providing multiple lines of evidence that declines in calf recruitment were underpinned by resource limitation. From 2001 to 2015, recruitment was more sensitive to interannual variation in weather (e.g., winter severity, drought) and plant phenology (e.g., duration of spring) for populations with reduced browse condition, forage quality, and body fat, suggesting these populations lacked the nutritional reserves necessary to buffer demographic performance against the effects of unfavorable weather. Further, average within-population calf recruitment was determined by regional climatic variation, suggesting that the pattern of reduced recruitment near the southern range boundary of moose stems from an interaction between climate and resource limitation. When coupled with information on habitat, nutrition, weather, and climate, life-history theory provides a framework to estimate nutritional limitation, proximity to nutritional carrying capacity, and impacts of climate change for ungulates.

Colorado, Utah, Wyoming↗

USGS2021

Drivers of site fidelity in ungulates

While the tendency to return to previously visited locations—termed ‘site fidelity’—is common in animals, the cause of this behaviour is not well understood. One hypothesis is that site fidelity is shaped by an animal's environment, such that animals living in landscapes with predictable resources have stronger site fidelity. Site fidelity may also be conditional on the success of animals’ recent visits to that location, and it may become stronger with age as the animal accumulates experience in their landscape. Finally, differences between species, such as the way memory shapes site attractiveness, may interact with environmental drivers to modulate the strength of site fidelity. We compared inter-year site fidelity in 669 individuals across eight ungulate species fitted with GPS collars and occupying a range of environmental conditions in North America and Africa. We used a distance-based index of site fidelity and tested hypothesized drivers of site fidelity using linear mixed effects models, while accounting for variation in annual range size. Mule deer Odocoileus hemionus and moose Alces alces exhibited relatively strong site fidelity, while wildebeest Connochaetes taurinus and barren-ground caribou Rangifer tarandus granti had relatively weak fidelity. Site fidelity was strongest in predictable landscapes where vegetative greening occurred at regular intervals over time (i.e. high temporal contingency). Species differed in their response to spatial heterogeneity in greenness (i.e. spatial constancy). Site fidelity varied seasonally in some species, but remained constant over time in others. Elk employed a ‘win-stay, lose-switch’ strategy, in which successful resource tracking in the springtime resulted in strong site fidelity the following spring. Site fidelity did not vary with age in any species tested. Our results provide support for the environmental hypothesis, particularly that regularity in vegetative phenology shapes the strength of site fidelity at the inter-annual scale. Large unexplained differences in site fidelity suggest that other factors, possibly species-specific differences in attraction to known sites, contribute to variation in the expression of this behaviour. Understanding drivers of variation in site fidelity across groups of organisms living in different environments provides important behavioural context for predicting how animals will respond to environmental change.

Journal of Animal Ecology↗

USGS2019

Plasticity in elk migration timing is a response to changing environmental conditions

Migration is an effective behavioral strategy for prolonging access to seasonal resources and may be a resilient strategy for ungulates experiencing changing climatic conditions. In the Greater Yellowstone Ecosystem (GYE), elk are the primary ungulate, with approximately 20,000 individuals migrating to exploit seasonal gradients in forage while also avoiding energetically costly snow conditions. How climate-induced changes in plant phenology and snow accumulation are influencing elk migration timing is unknown. We present the most complete record of elk migration across the GYE, spanning 9 herds and 414 individuals from 2001 to 2017, to evaluate the drivers of migration timing and test for temporal shifts. The timing of elk departure from winter range involved a trade-off between current and anticipated forage conditions, while snow melt governed summer range arrival date. Timing of elk departure from summer range and arrival on winter range were both influenced by snow accumulation and exposure to hunting. At the GYE scale, spring and fall migration timing changed through time, most notably with winter range arrival dates becoming almost 50 days later since 2001. Predicted herd-level changes in migration timing largely agreed with observed GYE-wide changes—except for predicted winter range arrival dates which did not reflect the magnitude of change detected in the elk telemetry data. Snow melt, snow accumulation, and spring green-up dates all changed through time, with different herds experiencing different rates and directions of change. We conclude that elk migration is plastic, is a direct response to environmental cues, and that these environmental cues are not changing in a consistent manner across the GYE. The impacts of changing elk migration timing on predator–prey dynamics, carnivore–livestock conflict, disease ecology, and harvest management across the GYE are likely to be significant and complex.

Idaho, Montana, Wyoming↗

USGS2018

Examining speed versus selection in connectivity models using elk migration as an example

Context Landscape resistance is vital to connectivity modeling and frequently derived from resource selection functions (RSFs). RSFs estimate relative probability of use and tend to focus on understanding habitat preferences during slow, routine animal movements (e.g., foraging). Dispersal and migration, however, can produce rarer, faster movements, in which case models of movement speed rather than resource selection may be more realistic for identifying habitats that facilitate connectivity. Objective To compare two connectivity modeling approaches applied to resistance estimated from models of movement rate and resource selection. Methods Using movement data from migrating elk, we evaluated continuous time Markov chain (CTMC) and movement-based RSF models (i.e., step selection functions [SSFs]). We applied circuit theory and shortest random path (SRP) algorithms to CTMC, SSF and null (i.e., flat) resistance surfaces to predict corridors between elk seasonal ranges. We evaluated prediction accuracy by comparing model predictions to empirical elk movements. Results All connectivity models predicted elk movements well, but models applied to CTMC resistance were more accurate than models applied to SSF and null resistance. Circuit theory models were more accurate on average than SRP models. Conclusions CTMC can be more realistic than SSFs for estimating resistance for fast movements, though SSFs may demonstrate some predictive ability when animals also move slowly through corridors (e.g., stopover use during migration). High null model accuracy suggests seasonal range data may also be critical for predicting direct migration routes. For animals that migrate or disperse across large landscapes, we recommend incorporating CTMC into the connectivity modeling toolkit.

Landscape Ecology↗

USGS2017

Linking spring phenology with mechanistic models of host movement to predict disease transmission risk

Disease models typically focus on temporal dynamics of infection, while often neglecting environmental processes that determine host movement. In many systems, however, temporal disease dynamics may be slow compared to the scale at which environmental conditions alter host space-use and accelerate disease transmission. Using a mechanistic movement modelling approach, we made space-use predictions of a mobile host (elk [ Cervus Canadensis ] carrying the bacterial disease brucellosis) under environmental conditions that change daily and annually (e.g., plant phenology, snow depth), and we used these predictions to infer how spring phenology influences the risk of brucellosis transmission from elk (through aborted foetuses) to livestock in the Greater Yellowstone Ecosystem. Using data from 288 female elk monitored with GPS collars, we fit step selection functions (SSFs) during the spring abortion season and then implemented a master equation approach to translate SSFs into predictions of daily elk distribution for five plausible winter weather scenarios (from a heavy snow, to an extreme winter drought year). We predicted abortion events by combining elk distributions with empirical estimates of daily abortion rates, spatially varying elk seroprevelance and elk population counts. Our results reveal strong spatial variation in disease transmission risk at daily and annual scales that is strongly governed by variation in host movement in response to spring phenology. For example, in comparison with an average snow year, years with early snowmelt are predicted to have 64% of the abortions occurring on feedgrounds shift to occurring on mainly public lands, and to a lesser extent on private lands. Synthesis and applications . Linking mechanistic models of host movement with disease dynamics leads to a novel bridge between movement and disease ecology. Our analysis framework offers new avenues for predicting disease spread, while providing managers tools to proactively mitigate risks posed by mobile disease hosts. More broadly, we demonstrate how mechanistic movement models can provide predictions of ecological conditions that are consistent with climate change but may be more extreme than has been observed historically.

Journal of Applied Ecology↗

USGS2017

Alternative foraging strategies enable a mountain ungulate to persist after migration loss

The persistence of many migratory ungulate populations worldwide is threatened due to anthropogenic impacts to seasonal ranges and migration routes. While many studies have linked migratory ungulate declines to migration disruption or loss, very few have explored the underlying factors that determine whether a population perishes or persists. In some cases, populations undergo severe declines and extirpation after migration loss; however, others appear able to persist as residents. We predict that to persist, populations must replace the traditional benefits of migration by altering the foraging strategies they employ as residents within one seasonal range. We propose the alternative foraging strategies (AFS) hypothesis as a framework for identifying various behavioral strategies that populations may use to cope with migration loss. We tested the hypothesis using the formerly migratory Teton bighorn sheep population in northwest Wyoming, which ceased migrating over 60 yr ago, but has persisted as a resident population. We used global positioning system data to evaluate winter and summer habitat selection and seasonal elevational movements for 28 adult female bighorn sheep ( Ovis canadensis ) from 2008 to 2010. Resource selection functions revealed that bighorn sheep employ winter foraging strategies to survive as residents by seeking out rugged, high-elevation, windswept ridgelines. Seasonal movement analyses indicated that bighorn sheep undergo a newly documented “abbreviated migration” strategy that is closely synchronized with vegetation green-up patterns within their one range. Bighorn sheep descend 500 m in elevation and travel up to 10 km in spring, gaining access to newly emergent forage approximately 30 d before it appears on their high-elevation winter and summer ranges. Our findings indicate that the Teton bighorn sheep population has persisted due to its habitat selection, AFS, and unique movement patterns, which allow migration loss to be mediated to some extent. The identification of AFS and the habitats that support them can help reveal the underlying benefits of migration and conserve populations in the face of future migration loss.

Wyoming↗