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At least 829 records · Page 46Linked to original sources

USGS2024

Chronic wasting disease alters the movement behavior and habitat use of mule deer during clinical stages of infection

Integrating host movement and pathogen data is a central issue in wildlife disease ecology that will allow for a better understanding of disease transmission. We examined how adult female mule deer ( Odocoileus hemionus ) responded behaviorally to infection with chronic wasting disease (CWD). We compared movement and habitat use of CWD-infected deer ( n = 18) to those that succumbed to starvation (and were CWD-negative by ELISA and IHC; n = 8) and others in which CWD was not detected ( n = 111, including animals that survived the duration of the study) using GPS collar data from two distinct populations collared in central Wyoming, USA during 2018–2022. CWD and predation were the leading causes of mortality during our study (32/91 deaths attributed to CWD and 27/91 deaths attributed to predation). Deer infected with CWD moved slower and used lower elevation areas closer to rivers in the months preceding death compared with uninfected deer that did not succumb to starvation. Although CWD-infected deer and those that died of starvation moved at similar speeds during the final months of life, CWD-infected deer used areas closer to streams with less herbaceous biomass than starved deer. These behavioral differences may allow for the development of predictive models of disease status from movement data, which will be useful to supplement field and laboratory diagnostics or when mortalities cannot be quickly retrieved to assess cause-specific mortality. Furthermore, identifying individuals who are sick before predation events could help to assess the extent to which disease mortality is compensatory with predation. Finally, infected animals began to slow down around 4 months prior to death from CWD. Our approach for detecting the timing of infection-induced shifts in movement behavior may be useful in application to other disease systems to better understand the response of wildlife to infectious disease.

Wyoming↗

USGS2015

Integrated survival analysis using an event-time approach in a Bayesian framework

Event-time or continuous-time statistical approaches have been applied throughout the biostatistical literature and have led to numerous scientific advances. However, these techniques have traditionally relied on knowing failure times. This has limited application of these analyses, particularly, within the ecological field where fates of marked animals may be unknown. To address these limitations, we developed an integrated approach within a Bayesian framework to estimate hazard rates in the face of unknown fates. We combine failure/survival times from individuals whose fates are known and times of which are interval-censored with information from those whose fates are unknown, and model the process of detecting animals with unknown fates. This provides the foundation for our integrated model and permits necessary parameter estimation. We provide the Bayesian model, its derivation, and use simulation techniques to investigate the properties and performance of our approach under several scenarios. Lastly, we apply our estimation technique using a piece-wise constant hazard function to investigate the effects of year, age, chick size and sex, sex of the tending adult, and nesting habitat on mortality hazard rates of the endangered mountain plover (Charadrius montanus) chicks. Traditional models were inappropriate for this analysis because fates of some individual chicks were unknown due to failed radio transmitters. Simulations revealed biases of posterior mean estimates were minimal (≤ 4.95%), and posterior distributions behaved as expected with RMSE of the estimates decreasing as sample sizes, detection probability, and survival increased. We determined mortality hazard rates for plover chicks were highest at <5 days old and were lower for chicks with larger birth weights and/or whose nest was within agricultural habitats. Based on its performance, our approach greatly expands the range of problems for which event-time analyses can be used by eliminating the need for having completely known fate data.

Ecology and Evolution↗

USGS2018

An analytical framework for estimating aquatic species density from environmental DNA

Environmental DNA (eDNA) analysis of water samples is on the brink of becoming a standard monitoring method for aquatic species. This method has improved detection rates over conventional survey methods and thus has demonstrated effectiveness for estimation of site occupancy and species distribution. The frontier of eDNA applications, however, is to infer species density. Building upon previous studies, we present and assess a modeling approach that aims at inferring animal density from eDNA. The modeling combines eDNA and animal count data from a subset of sites to estimate species density (and associated uncertainties) at other sites where only eDNA data are available. As a proof of concept, we first perform a cross-validation study using experimental data on carp in mesocosms. In these data, fish densities are known without error, which allows us to test the performance of the method with known data. We then evaluate the model using field data from a study on a stream salamander species to assess the potential of this method to work in natural settings, where density can never be known with absolute certainty. Two alternative distributions (Normal and Negative Binomial) to model variability in eDNA concentration data are assessed. Assessment based on the proof of concept data (carp) revealed that the Negative Binomial model provided much more accurate estimates than the model based on a Normal distribution, likely because eDNA data tend to be overdispersed. Greater imprecision was found when we applied the method to the field data, but the Negative Binomial model still provided useful density estimates. We call for further model development in this direction, as well as further research targeted at sampling design optimization. It will be important to assess these approaches on a broad range of study systems.

Ecology and Evolution↗

USGS2019

Complex immune responses and molecular reactions to pathogens and disease in a desert reptile (Gopherus agassizii)

Immune function plays an important role in an animal's defense against infectious disease. In reptiles, immune responses may be complex and counterintuitive, and diagnostic tools used to identify infection, such as induced antibody responses are limited. Recent studies using gene transcription profiling in tortoises have proven useful in identifying immune responses to various intrinsic and extrinsic stressors. As part of a larger experiment with Mojave desert tortoises ( Gopherus agassizii ), we facilitated the transmission of the pathogenic bacteria, Mycoplasma agassizii (Myag), to naïve adults and measured innate and induced immune reactions over time. Specifically, we evaluated clinical condition, presence of Myag in the nasal/oral cavity, induced antibody responses specific to Myag, and measured molecular reactions (gene transcript profiles) in 15 captive tortoises classified as naïve, exposed, or infected and 14 wild tortoises for comparison. Myag was confirmed inside the nasal/oral cavity in exposed tortoises within 30–60 days of introduction to infected animals, yet we did not detect Myag specific induced antibody responses in these individuals until 420–595 days post exposure. Surprisingly, we found no overall differences in the gene transcript profiles between our experimental treatment groups throughout this study. This work highlights the complexities in assessing immune function and diagnosing pathogen related infections in tortoises and other reptiles.

Ecology and Evolution↗

USGS2020

Paleo-metagenomics of North American fossil packrat middens: Past biodiversity revealed by ancient DNA

Fossil rodent middens are powerful tools in paleoecology. In arid parts of western North America, packrat ( Neotoma spp.) middens preserve plant and animal remains for tens of thousands of years. Midden contents are so well preserved that fragments of endogenous ancient DNA (aDNA) can be extracted and analyzed across millennia. Here, we explore the use of shotgun metagenomics to study the aDNA obtained from packrat middens up to 32,000 C 14 years old. Eleven Illumina HiSeq 2500 libraries were successfully sequenced, and between 0.11% and 6.7% of reads were classified using Centrifuge against the NCBI “nt” database. Eukaryotic taxa identified belonged primarily to vascular plants with smaller proportions mapping to ascomycete fungi, arthropods, chordates, and nematodes. Plant taxonomic diversity in the middens is shown to change through time and tracks changes in assemblages determined by morphological examination of the plant remains. Amplicon sequencing of ITS2 and rbcL provided minimal data for some middens, but failed at amplifying the highly fragmented DNA present in others. With repeated sampling and deep sequencing, analysis of packrat midden aDNA from well-preserved midden material can provide highly detailed characterizations of past communities of plants, animals, bacteria, and fungi present as trace DNA fossils. The prospects for gaining more paleoecological insights from aDNA for rodent middens will continue to improve with optimization of laboratory methods, decreasing sequencing costs, and increasing computational power.

Ecology and Evolution↗

USGS2021

Gut microbial ecology of the Critically Endangered Fijian crested iguana (Brachylophus vitiensis): Effects of captivity status and host reintroduction on endogenous microbiomes

Animals often exhibit distinct microbial communities when maintained in captivity as compared to when in the wild. Such differentiation may be significant in headstart and reintroduction programs where individuals spend some time in captivity before release into native habitats. Using 16S rRNA gene sequencing, we (i) assessed differences in gut microbial communities between captive and wild Fijian crested iguanas ( Brachylophus vitiensis ) and (ii) resampled gut microbiota in captive iguanas released onto a native island to monitor microbiome restructuring in the wild. We used both cloacal swabs and fecal samples to further increase our understanding of gut microbial ecology in this IUCN Critically Endangered species. We found significant differentiation in gut microbial community composition and structure between captive and wild iguanas in both sampling schemes. Approximately two months postrelease, microbial communities in cloacal samples from formerly captive iguanas closely resembled wild counterparts. Interestingly, microbial communities in fecal samples from these individuals remained significantly distinct from wild conspecifics. Our results indicate that captive upbringings can lead to differences in microbial assemblages in headstart iguanas as compared to wild individuals even after host reintroduction into native conditions. This investigation highlights the necessity of continuous monitoring of reintroduced animals in the wild to ensure successful acclimatization and release.

Ecology and Evolution↗

USGS2022

Face-off: Novel depredation and nest defense behaviors between an invasive and a native predator in the Greater Everglades Ecosystem, Florida, USA

We describe several photo-documented novel interactions between intraguild predators in southern Florida—the native bobcat ( Lynx rufus ) and the invasive Burmese python ( Python bivittatus ). Over several days we documented a bobcat's depredation of an unguarded python nest and subsequent python nest defense behavior following the return of both animals to the nest. This is the first documentation of any animal in Florida preying on python eggs, and the first evidence or description of such antagonistic interactions at a python nest.

Florida↗

USGS2022

Scat as a source of DNA for population monitoring

Sampling fecal droppings (scat) to genetically identify individual animals is an established method for monitoring mammal populations and could be highly useful for monitoring reptile populations. Whereas existing protocols for obtaining DNA from reptile scat focus on analyses of whole, fresh scat deposited during animal handling, the collection of scat naturally deposited by reptiles in situ, as required for non-invasive population monitoring, requires protocols to extract highly degraded DNA. Using surface swabs from such scats can reduce PCR inhibition, ecological impacts of removing scat, and zoonotic risks. We report on three related but independently designed studies of DNA analyses from scat swabs of herbivorous reptiles under natural desert conditions: two free-ranging desert tortoise species (Agassiz's desert tortoise, Gopherus agassizii , California, US, and Morafka's desert tortoise, G. morafkai , Arizona, US) and the common chuckwalla (Sauromalus atar ) (Arizona, US, and Sonora, MX). We analyzed samples from both tortoise species with the same set of 16 microsatellites and chuckwalla samples with four mtDNA markers; studies also varied in swab preservation medium and DNA extraction method. Microsatellite amplification success per sample, defined as ≥9 loci with amplification, varied between studies, with 15% for Agassiz's desert tortoise and 42% Morafka's desert tortoise. For chuckwallas, we successfully amplified and sequenced 50% of samples. We recovered fragments up to 400 bp for tortoises and 980 bp for chuckwallas from scat swab samples. This study demonstrates that genotypes can successfully be obtained from swabs of herbivorous reptile scat collected in the field under natural environmental conditions and emphasizes that repeat amplifications are necessary for genetic identification of individuals from non-invasive samples.

Arizona, California↗

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↗

USGS2016

To cross or not to cross: modeling wildlife road crossings as a binary response variable with contextual predictors

Roads are significant barriers to landscape-scale movements of individuals or populations of many wildlife taxa. The decision by an animal near a road to either cross or not cross may be influenced by characteristics of the road, environmental conditions, traits of the individual animal, and other aspects of the context within which the decision is made. We considered such factors in a mixed-effects logistic regression model describing the nightly road crossing probabilities of invasive nocturnal Brown Treesnakes ( Boiga irregularis ) through short-term radiotracking of 691 snakes within close proximity to 50 road segments across the island of Guam. All measures of road magnitude (traffic volume, gap width, surface type, etc.) were significantly negatively correlated with crossing probabilities. Snake body size was the only intrinsic factor associated with crossing rates, with larger snakes crossing roads more frequently. Humidity was the only environmental variable affecting crossing rate. The distance of the snake from the road at the start of nightly movement trials was the most significant predictor of crossings. The presence of snake traps with live mouse lures during a portion of the trials indicated that localized prey cues reduced the probability of a snake crossing the road away from the traps, suggesting that a snake's decision to cross roads is influenced by local foraging opportunities. Per capita road crossing rates of Brown Treesnakes were very low, and comparisons to historical records suggest that crossing rates have declined in the 60+ yr since introduction to Guam. We report a simplified model that will allow managers to predict road crossing rates based on snake, road, and contextual characteristics. Road crossing simulations based on actual snake size distributions demonstrate that populations with size distributions skewed toward larger snakes will result in a higher number of road crossings. Our method of modeling per capita road crossing probabilities as a binary response variable, influenced by contextual factors, may be useful for describing or predicting road crossings by individuals of other taxa provided that appropriate spatial and temporal resolution can be achieved and that potentially influential covariate data can be obtained.

Ecosphere↗

USGS2018

Effects of environmental variables on invasive amphibian activity: Using model selection on quantiles for counts

Many different factors influence animal activity. Often, the value of an environmental variable may influence significantly the upper or lower tails of the activity distribution. For describing relationships with heterogeneous boundaries, quantile regressions predict a quantile of the conditional distribution of the dependent variable. A quantile count model extends linear quantile regression methods to discrete response variables, and is useful if activity is quantified by trapping, where there may be many tied (equal) values in the activity distribution, over a small range of discrete values. Additionally, different environmental variables in combination may have synergistic or antagonistic effects on activity, so examining their effects together, in a modeling framework, is a useful approach. Thus, model selection on quantile counts can be used to determine the relative importance of different variables in determining activity, across the entire distribution of capture results. We conducted model selection on quantile count models to describe the factors affecting activity (numbers of captures) of cane toads ( Rhinella marina ) in response to several environmental variables (humidity, temperature, rainfall, wind speed, and moon luminosity) over eleven months of trapping. Environmental effects on activity are understudied in this pest animal. In the dry season, model selection on quantile count models suggested that rainfall positively affected activity, especially near the lower tails of the activity distribution. In the wet season, wind speed limited activity near the maximum of the distribution, while minimum activity increased with minimum temperature. This statistical methodology allowed us to explore, in depth, how environmental factors influenced activity across the entire distribution, and is applicable to any survey or trapping regime, in which environmental variables affect activity.

Ecosphere↗

USGS2020

Assessing population-level consequences of anthropogenic stressors for terrestrial wildlife

Human activity influences wildlife. However, the ecological and conservation significances of these influences are difficult to predict and depend on their population‐level consequences. This difficulty arises partly because of information gaps, and partly because the data on stressors are usually collected in a count‐based manner (e.g., number of dead animals) that is difficult to translate into rate‐based estimates important to infer population‐level consequences (e.g., changes in mortality or population growth rates). However, ongoing methodological developments can provide information to make this transition. Here, we synthesize tools from multiple fields of study to propose an overarching, spatially explicit framework to assess population‐level consequences of anthropogenic stressors on terrestrial wildlife. A key component of this process is using ecological information from affected animals to upscale from count‐based field data on individuals to rate‐based demographic inference. The five steps to this framework are (1) framing the problem to identify species, populations, and assessment parameters; (2) field‐based measurement of the effect of the stressor on individuals; (3) characterizing the location and size of the populations of interest; (4) demographic modeling for those populations; and (5) assessing the significance of stressor‐induced changes in demographic rates. The tools required for each of these steps are well developed, and some have been used in conjunction with each other, but the entire group has not previously been unified together as we do in this framework. We detail these steps and then illustrate their application for two species affected by different anthropogenic stressors. In our examples, we use stable hydrogen isotope data to infer a catchment area describing the geographic origins of affected individuals, as the basis to estimate population size for that area. These examples reveal unexpectedly greater potential risks from stressors for the more common and widely distributed species. This work illustrates key strengths of the framework but also important areas for subsequent theoretical and technical development to make it still more broadly applicable.

Ecosphere↗

USGS2020

Model-based clustering reveals patterns in central place use of a marine top predator

Satellite telemetry data are commonly used to quantify habitat selection, examine animal movements, and delineate home ranges. These data also contain valuable information concerning dens, nests, roosts, and other central places that are often associated with important life history events and may exhibit unique characteristics; however, using satellite telemetry data to study central places is complicated by common nuances like locational error and animal movement. We coupled a novel modeling framework that accounts for these nuances with an Argos satellite telemetry dataset to examine the spatiotemporal behavior associated with harbor seal haul-out sites on Kodiak Island, Alaska, USA. The methodology incorporates an observation model that accommodates multiple sources of uncertainty in telemetry data and a flexible Bayesian nonparametric model to uncover latent clustering in the telemetry locations. We also contribute extensions to examine the effect of covariates on site selection and to obtain population-level inference concerning central place use. Harbor seal haul-out sites generally occurred in inlets and bays, areas that are isolated from the open water of the Gulf of Alaska. Most individuals selected haul-out sites that were protected from wave exposure. The effects of bathymetry and shoreline complexity on haul-out site selection were variable among individual seals, as were the effects of time of day, time since low tide, and day of year on temporal patterns of haul-out use. As repositories of satellite telemetry data on a wide variety of species accumulate, so do opportunities for using this information to learn about the locations of central places, as well as the temporal patterns in their use. The model-based approach we describe offers a practical and rigorous means for gaining insight concerning these sensitive locations, knowledge of which is important for the effective management and conservation of many species.

Alaska↗

USGS2021

Responses of American black bears to spring resources

In temperate regions of the world, food resources are seasonally limited, which causes some wildlife species to seek out nutrient-rich resources to better meet their caloric needs. Animals that utilize high-quality resources may reap fitness benefits as they prepare for mating, migration, or hibernation. American black bears ( Ursus americanus ) are omnivores that consume both plant and animal food resources to meet macronutrient needs. Black bears capitalize on high-quality food resources, such as soft mast in summer and hard mast during autumn, but we know less about the importance of resource quality during spring. Therefore, we sought to understand the relationship between the spatiotemporal variation in the availability of food and resource selection of black bears during spring. We also aimed to infer potential changes in foraging tactics, from opportunistic foraging to more active selection. Although black bears are described as opportunistic omnivores, we hypothesized they select areas with high-quality forage when available. We instrumented 7 black bears with GPS collars in 2017 and 2018 and estimated fine-scale resource selection with integrated step-selection functions. We found evidence that black bear movements were influenced by forage quality of vegetative food resources. However, we failed to find evidence that black bears actively alter their movements to take advantage of seasonal neonate elk. Although black bears represent a substantial cause of mortality for neonate elk, we found that black bears likely feed on neonates encountered opportunistically while traveling between patches of high-quality forage. Few studies have shown evidence of an omnivorous species capitalizing on spatiotemporal variation in forage quality, yet our data suggest this may be an important strategy for species with diverse diets, particularly where resources are seasonally limited.

Montana, Wyoming↗

USGS2023

PopEquus: a predictive modeling tool to support management decisions for free-roaming horse populations

Feral horse ( Equus caballus ) population management is a challenging problem around the world because populations often exhibit density-independent growth, can exert negative ecological effects on ecosystems, and require great cost to be managed. However, strong value-based connections between people and horses cause contention around management decisions. To help make informed decisions, natural resource managers might benefit from more detailed understanding of how horse management alternatives, including combinations of removals and fertility control methods, could achieve objectives of sustainable, multiple-use ecosystems while minimizing overall horse handling and fiscal costs. Here, we describe a modeling tool that simulates horse management alternatives and estimates trade-offs in predicted metrics related to population size, animal handling, and direct costs of management. The model considers six management actions for populations (removals for adoption or long-term holding; fertility control treatment with three vaccines, intrauterine devices, and mare sterilization), used alone or in combination. We simulated 19 alternative management scenarios at 2-, 3-, and 4-year management return intervals and identified efficiency frontiers among alternatives for trade-offs between predicted population size and six management metrics. Our analysis identified multiple alternatives that could maintain populations within target population size ranges, but some alternatives (e.g., removal and mare sterilization, removal and GonaCon treatment) performed better at minimizing overall animal handling requirements and management costs. Cost savings increased under alternatives with more effective, longer lasting fertility control techniques over longer management intervals compared with alternatives with less-effective, shorter lasting fertility control techniques. We built a user-friendly website application, PopEquus , that decision makers and interested individuals can use to simulate management alternatives and evaluate trade-offs among management and cost metrics. Our results and website application provide quantitative trade-off tools for horse population management decisions and can help support value-based management decisions for wild or feral horse populations and ecosystems at local and regional scales around the world.

Ecosphere↗

USGS2024

Geographic distribution of feather δ34S in Europe

Geographic distribution models of environmentally stable isotopes (the so-called “isoscapes”) are widely employed in animal ecology, and wildlife forensics and conservation. However, the application of isoscapes is limited to elements and regions for which the spatial patterns have been estimated. Here, we focused on the ubiquitous yet less commonly used stable sulfur isotopes (δ 34 S). To predict the European δ 34 S isoscape, we used 242 feather samples from Eurasian Reed Warbler ( Acrocephalus scirpaceus ) formed at 69 European wetland sites. We quantified the relationships between sample δ 34 S and environmental covariates using a random forest regression model and applied the model to predict the geographic distribution of δ 34 S. We also quantified within-site variation in δ 34 S and complementarity with other isotopes on both individual and isoscape levels. The predicted feather δ 34 S isoscape shows only slight differences between the central and southern parts of Europe while the coastal regions were most enriched in 34 S. The most important covariates of δ 34 S were distance to coastline, surface elevation, and atmospheric concentrations of SO 2 gases. The absence of a systematic spatial pattern impedes the application of the δ 34 S isoscape, but high complementarity with other isoscapes advocates the combination of multiple isoscapes to increase the precision of animal tracing. Feather δ 34 S compositions showed considerable within-site variation with highest values in inland parts of Europe, likely attributed to wetland anaerobic conditions and redox sensitivity of sulfur. The complex European geography and topography as well as using δ 34 S samples from wetlands may contribute to the absence of a systematic spatial gradient of δ 34 S values in Europe. We thus encourage future studies to focus on the geographic distribution of δ 34 S using tissues from diverse taxa collected in various habitats over large land masses in the world (i.e., Africa, South America, or East Asia).

Ecosphere↗

USGS2025

Assessing the effects of climate and visitor use on amphibian occupancy in a protected landscape with long-term data

Determining where animals are, and if they are persisting across protected landscapes, is necessary to implement appropriate management and conservation actions. For long-lived animals and those with boom-and-bust life histories, perspective across time contributes to discerning temporal trends in occupancy and persistence, and potentially in identifying mechanisms affecting those parameters. Long-term data are particularly useful in protected areas to quantify indicators of change that may be less obvious or occur more slowly. We used long-term amphibian data from Rocky Mountain National Park (RMNP) in a Bayesian occupancy modeling framework to estimate changes in occupancy, colonization, and persistence of amphibians over three decades and to explore the effects of climate, landscape change, and visitor use as mechanisms behind observed changes. Our results indicate that colonization and persistence are low and/or declining for Pseudacris maculata , Lithobates sylvaticus , and Ambystoma mavortium , and that occupied catchments are increasingly isolated. We found visitor use to have a consistently negative effect on occupancy and persistence of amphibians in RMNP, and that all species are more likely to occupy catchments with more complex habitat and a higher proportion of wetlands. While these results are sobering, they also provide a way forward where mitigation efforts can target identified drivers of change.

Colorado↗

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↗