Geology topics

W. David Walter

Publications and source records attributed to W. David Walter.

At least 19 recordsLinked to original sources

USGS2026

Intraspecific contact among white-tailed deer: A literature review and chronic wasting disease case study

White-tailed deer ( Odocoileus virginianus ) are a valuable game mammal in the eastern United States necessitating detailed understanding of disease transmission. We conducted a literature review on intraspecific contact (i.e., interactions wherein disease transmission may occur) among deer. From 69 studies, we identified five themes underlying research on intraspecific deer contact: physical touch, social groups, spatial overlap, association rates, and social networks. Visual observations determined physical touch to be infrequent (< 2 touches/h) and indicated deer social groups were dependent on spatial dynamics of parturition and dispersal; most females remained with matriarchal family groups while males dispersed and formed bachelor groups. Assessed using global positioning system (GPS) monitoring, spatial overlap and association rates (i.e., instances of deer in close spatial–temporal proximity) were higher in correspondence to within-group social dynamics, and between-group scores were correspondingly low. Social network analyses indicated between-group transmission may be driven by socially dominant males, often termed super-spreaders (i.e., hosts infecting disproportionately high numbers of healthy individuals). We investigated these themes via a case study of deer infected with chronic wasting disease (CWD) in southcentral Pennsylvania, United States. We assessed spatial overlap and association rates using GPS monitoring data from 180 deer. Our results supported findings in the literature, showing strong correlations among spatial overlap, association rates, and correlated movements. Further, CWD-infected deer exhibited similar association rates to deer in which CWD was not detected. Our literature review and case study indicate direct transmission of CWD and other diseases is likely greatest within social groups following seasonal behavioral dynamics and that between-group transmission is likely driven by males via dispersal and mating interactions. Our results may be used to inform population management models with future work focused on high resolution spatial assessments of transmission in localized areas.

Pennsylvania↗

USGS2026

Statewide agent-based model for management of chronic wasting disease in white-tailed deer: PAOvCWD

Chronic wasting disease (CWD) is an always-fatal disease infecting wild cervids globally. Ecologically and economically important, CWD presents a challenge for managing white-tailed deer ( Odocoileus virginianus ). We built an agent-based model to simulate CWD transmission and assess potential management actions that could slow disease spread: PAOvCWD . We developed PAOvCWD using contact rates and other behavioral and ecological metrics estimated from deer monitored in Pennsylvania, USA. We programmed potential management responses (e.g., culling, altered hunter harvest) for all 22 Pennsylvania wildlife management units and validated the efficacy of PAOvCWD using a deer population in south-central Pennsylvania infected with CWD for > 10 years. To support applications of our model, we developed a user-friendly R pipeline that allows implementation with relatively minor modifications. Our pipeline includes four steps: • Steps 1 and 2 generate regional percent forest cover rasters and curate population-level demographics. • Step 3 initializes landscapes and agents using our PAOvPOP model. • Step 4 assesses CWD transmission and management responses using our PAOvCWD model.

Pennsylvania↗

USGS2026

Generating geochemical and mineralogy distributions of soil in the conterminous United States using Bayesian hierarchical spatial models

Characterizing geochemical and mineralogical soil distributions across large spatial extents is essential for understanding mineral resources, ecosystem processes, and environmental risks. Rasters of soil geochemical distributions for the conterminous United States, however, are limited. We present a Bayesian modeling workflow and tool for generating predictive geochemical and mineralogy distribution maps for the conterminous United States using integrated nested Laplace approximation (INLA) with the stochastic partial differential equation approach. By modeling soil geostatistical data with environmental covariates (soil properties, topography, climate, and land cover), we generate predictive distributions of soil geochemistry that can be mapped or extracted for further analyses. As an example, we model the spatial distribution of trace elements in soil relevant to vertebrate health (cobalt, copper, iron, manganese, selenium, and zinc) and provide a workflow that can be used to generate and visualize predictive distributions of 39 other major and trace elements and 21 minerals of the soil survey, supporting a variety of ecological, environmental, and agricultural applications.

MethodsX↗

USGS2025

Viral outbreak dynamics and evolution in wildlife at the interface with humans

In this study, we used a multi-faceted approach to understand patterns of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission and persistence in a wild white-tailed deer ( Odocoileus virginianus ) population. Serology data indicated transmission of SARS-CoV-2 and persistence during the seven-month sampling period. Traditional disease modelling based on deer-to-deer transmission indicated relatively low prevalence with an R 0 of 1.9 and recovery period of 7 days; however, individual-based modelling informed by GPS tracked-movement data captured a potential transmission event. Phylogenetic analyses revealed a recurring pattern of divergent groups of deer-derived sequences with human-derived sequences falling close to each deer-derived cluster. Further, human-derived sequences were frequently sampled months prior to the deer-derived sequences, indicating repeated human to deer spillover. Using multiple types of data as well as both fine and broad scale analyses, we have characterized a pattern of localized outbreaks of SARS-CoV-2 within white-tailed deer populations that are likely recurring due to frequent spillover events. Our results suggest that while deer-to-deer transmission occurs over small spatiotemporal scales, SARS-CoV-2 persistence over longer periods and across larger regions is likely driven by repeated spillover from human populations.

Pennsylvania↗

USGS2025

Development of high-throughput genomic resources to inform white-tailed deer population and disease management

White-tailed deer ( Odocoileus virginianus ) are the most abundant and widespread cervid in North America. Genetic data are used as a tool to monitor populations and make management decisions for this game species. However, the development and use of genomic tools that can generate a set of markers suitable for longitudinal genomic data collection, whether for management purposes or to study the demographic and evolutionary processes of widely distributed species, have been challenging. This is mainly due to the cost required to fully implement and interpret the data produced. Here, we generated whole genome resequencing data for 44 free-ranging deer from three regions in their central and eastern North American range and identified over 89 million single nucleotide polymorphisms (SNPs). We used a subset of these SNPs to develop two nested SNP tools, a high-density array (702,183 SNPs) and a medium-density array (72,723 SNPs) to support deer and chronic wasting disease (CWD) management and research. SNPs were selected to ensure an even distribution across scaffolds of the reference genome and include SNPs associated with CWD susceptibility. Using genotyping results for 469 deer from 15 states in the US and Mexico generated by the high-density array and 1335 deer from 18 states generated by the medium-density array, we assessed genotyping success across different populations and explored some insights into population structure. These genomic tools offer a standard set of markers that will enable researchers and managers to address important questions related to white-tailed deer and CWD management. Our SNP arrays also offer the opportunity to examine aspects of white-tailed deer ecology and evolutionary history that were previously difficult to address.

Molecular Ecology Resources↗

USGS2025

Expanding national-scale wildlife disease surveillance systems with research networks

Efficient learning about disease dynamics in free-ranging wildlife systems can benefit from active surveillance that is standardized across different ecological contexts. For example, active surveillance that targets specific individuals and populations with standardized sampling across ecological contexts (landscape-scale targeted surveillance) is important for developing a mechanistic understanding of disease emergence, which is the foundation for improving risk assessment of zoonotic or wildlife-livestock disease outbreaks and predicting hotspots of disease emergence. However, landscape-scale targeted surveillance systems are rare and challenging to implement. Increasing experience and infrastructure for landscape-scale targeted surveillance will improve readiness for rapid deployment of this type of surveillance in response to new disease emergence events. Here, we describe our experience developing and rapidly deploying a landscape-scale targeted surveillance system for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in two free-ranging deer species across their ranges in the United States. Our surveillance system was designed to collect data across individual, population, and landscape scales for future analyses aimed at understanding mechanisms and risk factors of SARS-CoV-2 transmission, evolution, and persistence. Our approach leveraged partnerships between state and federal public service sectors and academic researchers in a landscape-scale targeted surveillance research network. Methods describe our approach to developing the surveillance network and sampling design. Results report challenges with implementing our intended sampling design, specifically how the design was adapted as different challenges arose and summarize the sampling design that has been implemented thus far. In the discussion, we describe strategies that were important for the successful deployment of landscape-scale targeted surveillance, development and operation of the research network, construction of similar networks in the future, and analytical approaches for the data based on the sampling design.

Ecology and Evolution↗

USGS2025

Evaluation of SARS-CoV-2 antibody detection methods for wild Cervidae

Wildlife surveillance programs often use serological data to monitor exposure to pathogens. Diagnostic sensitivity and specificity of a serological assay quantify the true positive and negative rates of the diagnostic assay, respectively. However, an assay’s accuracy can be affected by wild animals’ pathogen exposure history and quality of the sample collected, requiring separate estimates of an assay’s detection ability for wild-sampled animals where an animal’s true disease status is unknown (referred to hereafter as sampling sensitivity and specificity). We assessed the sampling sensitivity and specificity of a Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) surrogate virus neutralization test (sVNT) and conventional virus neutralization tests (cVNT) to detect antibodies for ancestral and Omicron B.1.1.529 variants of SARS-CoV-2 in wild white-tailed deer ( Odocoileus virginianus ) and mule deer ( Odocoileus hemionus ). We studied the influence of sample collection method using paired blood samples collected in serum separator tubes and on Nobuto strips from the same animal. Mean estimates of sampling sensitivity and specificity ranged from 0.21–0.95 and 0.94–1.00, respectively, varying by sample collection method, host species, and SARS-CoV-2 variant targeted by the assay. Broadly, sampling sensitivity was estimated to be higher for 1) sera collected in tubes, 2) detecting pre-Omicron SARS-CoV-2 variants, and 3) sVNT relative to cVNT assays. Sampling specificity tended to be high for all tests. We augmented our study with SARS-CoV-2 spike protein sequences derived from sampling locations and times coincident with white-tailed deer captures, finding common amino acid mutations relative to the sVNT Omicron antigen variant. The mutations may indicate that the SARS-CoV-2 variants circulating in cervids from 2021 through 2024 may be better adapted to cervid hosts and more closely related to variants that circulated in humans prior to Omicron variants. We conclude our study with an inter-test comparison of sVNT results, revealing that 40 % inhibition is an optimal threshold for test positivity when testing deer sera for responses to Omicron variant B.1.1.529, compared to the 30 % inhibition recommended for ancestral variants.

Colorado, Illinois, Minnesota, New York, Pennsylva↗

USGS2025

Overview of North American isolates of chronic wasting disease used for strain research

Chronic Wasting Disease (CWD) is a prion disease that affects Cervidae species, and is the only known prion disease transmitted among wildlife species. The key pathological feature is the conversion of the normal prion protein (PrP C ) misfolding into abnormal forms (PrP Sc ), triggering the onset of CWD infections. The misfolding can generate distinct PrP Sc conformations (strains) giving rise to diverse disease phenotypes encompassing pathology, incubation period, and clinical signs. These phenotypes operationally define distinct prion strains, a pivotal element in monitoring CWD spread and zoonotic potential—a complex endeavor compounded by defining and tracking CWD strains. This review pursues a tripartite objective: 1. to address the intricate challenges inherent in ongoing CWD strain classification; 2. to provide an overview of the known CWD-infected isolates, the strains they represent and their passage history; and 3. to describe the spatial diversity of CWD strains in North America, enriching our understanding of CWD strain dynamics. By delving into these dimensions, this review sheds light on the intricate interplay among polymorphisms, biochemical properties, and clinical expressions of CWD. This endeavor aims to elevate the trajectory of CWD research, advancing our insight into prion disease.

Pathogens↗

USGS2025

Relatedness of white-tailed deer from culling efforts within chronic wasting disease management zones in Minnesota

In white-tailed deer ( Odocoileus virginianus ), closely related females form social groups, avoiding other social groups. Consequently, females infected with chronic wasting disease (CWD) are more likely to infect social group members. Culling has been used to reduce CWD transmission in high-risk areas; however, its effectiveness in removing related individuals has not been assessed. We analyzed 11 microsatellites and a mitochondrial DNA fragment to assess: (1) the genetic structure in white-tailed deer in Minnesota, USA and (2) the effectiveness of localized culling to remove related deer. For (1), we genotyped deer culled in 2019 and 2021 in three CWD management zones, and deer collected in between zones. For (2), we only included culled deer, defining “culled groups” as deer obtained in the same township-range-section and year. We compared mean relatedness among deer from the same culled group (intra-group relatedness) and among deer from different culled groups (inter-group relatedness). We did not find evidence of genetic structure, suggesting that an outbreak in any of the management zones could naturally spread to the others. Culling removed deer that were on average more related than expected by chance (intra-group relatedness > inter-group relatedness), and most highly-related deer were culled in the same bait site.

Minnesota↗

USGS2024

Neonatal antipredator tactics shape female movement patterns in large herbivores

Caring for newborn offspring hampers resource acquisition of mammalian females, curbing their ability to meet the high energy expenditure of early lactation. Newborns are particularly vulnerable, and large herbivores have evolved a continuum of neonatal anti-predator tactics, ranging from immobile hider to highly mobile follower offspring. How these tactics constrain female movements around parturition is unknown, particularly within the current context of increasing habitat fragmentation and earlier plant phenology caused by global warming. Using a analysis across 54 populations of 23 species of large herbivores, we show that mothers adjust their movements to variation in resource productivity and heterogeneity according to their offspring’s neonatal tactic. Mothers with hider offspring are unable to exploit environments where the variability of resources occurs at a broad scale, which might alter resource allocation compared to mothers with follower offspring. Our findings reveal that the overlooked neonatal tactic plays a key role for predicting how species are coping with environmental variation.

Nature Ecology & Evolution↗

USGS2024

Large-scale assessment of genetic structure to assess risk of populations of a large herbivore to disease

Chronic wasting disease (CWD) can spread among cervids by direct and indirect transmission, the former being more likely in emerging areas. Identifying subpopulations allows the delineation of focal areas to target for intervention. We aimed to assess the population structure of white-tailed deer ( Odocoileus virginianus ) in the northeastern United States at a regional scale to inform managers regarding gene flow throughout the region. We genotyped 10 microsatellites in 5701 wild deer samples from Maryland, New York, Ohio, Pennsylvania, and Virginia. We evaluated the distribution of genetic variability through spatial principal component analysis and inferred genetic structure using non-spatial and spatial Bayesian clustering algorithms (BCAs). We simulated populations representing each inferred wild cluster, wild deer in each state and each physiographic province, total wild population, and a captive population. We conducted genetic assignment tests using these potential sources, calculating the probability of samples being correctly assigned to their origin. Non-spatial BCA identified two clusters across the region, while spatial BCA suggested a maximum of nine clusters. Assignment tests correctly placed deer into captive or wild origin in most cases (94%), as previously reported, but performance varied when assigning wild deer to more specific origins. Assignments to clusters inferred via non-spatial BCA performed well, but efficiency was greatly reduced when assigning samples to clusters inferred via spatial BCA. Differences between spatial BCA clusters are not strong enough to make assignment tests a reliable method for inferring the geographic origin of deer using 10 microsatellites. However, the genetic distinction between clusters may indicate natural and anthropogenic barriers of interest for management.

Maryland, New York, Ohio, Pennsylvania, West Virgi↗

USGS2024

Evaluation of DNA yield from various tissue and sampling sources for use in single nucleotide polymorphism panels

Genetics studies are used by wildlife managers and researchers to gain inference into a population of a species of interest. To gain these insights, microsatellites have been the primary method; however, there currently is a shift from microsatellites to single nucleotide polymorphisms (SNPs). With the different DNA requirements between microsatellites and SNPs, an investigation into which samples can provide adequate DNA yield is warranted. Using samples that were collected from previous genetic projects from regions in the USA from 2014 to 2021, we investigated the DNA yield of eight sample categories to gain insights into which provided adequate DNA to be used in ddRADseq or already developed high- or medium-density SNP panels. We found seven sample categories that met the DNA requirements for use in all three panels, and one sample category that did not meet any of the three panels requirements; however, DNA integrity was highly variable and not all sample categories that met panel DNA requirements could be considered high quality DNA. Additionally, we used linear random-effects models to determine which covariates would have the greatest influence on DNA yield. We determined that all covariates (tissue type, storage method, preservative, DNA quality, time until DNA extraction and time after DNA extraction) could influence DNA yield.

Minnesota, New York, Pennsylvania↗

USGS2024

Prion forensics: A multidisciplinary approach to investigate CWD at an illegal deer carcass disposal site

Infectious prions are resistant to degradation and remain infectious in the environment for several years. Chronic wasting disease (CWD) has been detected in cervids inhabiting North America, the Nordic countries, and South Korea. CWD-prion spread is partially attributed to carcass transport and disposal. We employed a forensic approach to investigate an illegal carcass dump site connected with a CWD-positive herd. We integrated anatomic, genetic, and prion amplification methods to discover CWD-positive remains from six white-tailed deer ( Odocoileus virginianus ) and, using microsatellite markers, confirmed a portion originated from the CWD-infected herd. This approach provides a foundation for future studies of carcass prion transmission risk.

Minnesota↗

USGS2024

Comparing risk of chronic wasting disease occurrence using Bayesian hierarchical spatial models and different surveillance types

Spatial modeling of wildlife diseases can be used to describe patterns of disease risk, understand biological mechanisms of disease occurrence, and for spatial prediction. Risk of wildlife disease occurrence in relation to environmental variables is often modeled and predicted using Markov chain Monte Carlo (MCMC) methods, which are unsuitable for large datasets and those covering large spatial extents. Integrated nested Laplace approximation (INLA) and INLA using the stochastic partial differential equation (INLA-SPDE) approach have become popular alternatives to MCMC for Bayesian inference because of their fast computational time and ability to process large datasets. Studies investigating risk of disease occurrence in wildlife, to our knowledge, have not yet compared Bayesian hierarchical spatial models over large spatial extents using real world data. Using chronic wasting disease (CWD) surveillance data from white-tailed deer ( Odocoileus virginianus ) collected in Pennsylvania, United States, as a case study, we first demonstrate how parameter estimates compare among MCMC, INLA, and INLA-SPDE modeling frameworks. We then model CWD (detected/non-detected) using INLA-SPDE over a much larger spatial extent than has been conducted previously for this disease to determine how surveillance type (e.g., hunter harvest, roadkill, or all surveillance) influences model parameters and predicted risk of CWD occurrence at locations not sampled. Fixed effects considered in the models included deer age and sex, elevation, slope, distance to streams, percent clay, and proportion of two habitat classes (forest and open) known to influence deer movements. We found INLA to produce comparable estimates to MCMC and permit modeling large datasets covering expansive spatial extents much faster and more efficiently than MCMC. We identified potential biases in surveillance types, indicating the value of including all surveillance in models rather than only a single type. Comparing modeling tools available for mapping diseases of wildlife in relation to ecological variables at large spatial extents will guide future modeling efforts for CWD and other wildlife diseases. Understanding spatial patterns of CWD using different surveillance types can help improve understanding of CWD disease outbreaks, assist with control of CWD through geographical targeting, and inform future CWD surveillance efforts.

Ecological Modeling↗

USGS2024

Predicting the odds of chronic wasting disease with Habitat Risk software

Chronic wasting disease (CWD) is a transmissible spongiform encephalopathy that was first detected in captive cervids in Colorado, United States (US) in 1967, but has since spread into free-ranging white-tailed deer ( Odocoileus virginianus ) across the US and Canada as well as to Scandinavia and South Korea. In some areas, the disease is considered endemic in wild deer populations, and governmental wildlife agencies have employed epidemiological models to understand long-term environmental risk. However, continued rapid spread of CWD into new regions of the continent has underscored the need for extension of these models into broader tools applicable for wide use by wildlife agencies. Additionally, efforts to semi-automate models will facilitate access of technical scientific methods to broader users. We introduce software (Habitat Risk) designed to link a previously published epidemiological model with spatially referenced environmental and disease testing data to enable agency personnel to make up-to-date, localized, data-driven predictions regarding the odds of CWD detection in surrounding areas after an outbreak is discovered. Habitat Risk requires pre-processing publicly available environmental datasets and standardization of disease testing (surveillance) data, after which an autonomous computational workflow terminates in a user interface that displays an interactive map of disease risk. We demonstrated the use of the Habitat Risk software with surveillance data of white-tailed deer from Tennessee, USA.

Tennessee↗

USGS2024

Comparison of butorphanol-azaperone-medetomidine and nalbuphine-medetomidine-azaperone in free-ranging elk (Cervus canadensis) in Pennsylvania, USA

Chemical immobilization is commonly used to capture and handle free-ranging elk ( Cervus canadensis ). Butorphanol-azaperone-medetomidine (BAM) and nalbuphine-medetomidine-azaperone (NalMed-A) are compounded drug combinations that are lower-scheduled in the US than drugs historically used for elk immobilizations. We compared BAM and NalMed-A for immobilization of free-ranging elk using free-darting and Clover trapping. From January 2020 to April 2022, 196 female elk were immobilized in Pennsylvania, USA. We report vital rates, induction and recovery times, and the need for supplemental drugs. We built mixed-effects logistic regression models to describe differences between drug choice based on induction and recovery times, capture method, and individual variation. Several models were competing, including our null model, which suggests that BAM and NalMed-A are comparable based on the parameters we evaluated. Supplemental drug administration was more frequently needed in NalMed-A immobilizations (21.2%) than in BAM immobilizations (9.0%). Overall, we found minor differences between BAM and NalMed-A, both of which appear to be effective for immobilizing elk in both free-darting and Clover trapping scenarios when performing moderately invasive, minimally painful procedures on free-ranging elk.

Pennsylvania↗

USGS2023

Change-point models for identifying behavioral transitions in wild animals

Animal behavior can be difficult, time-consuming, and costly to observe in the field directly. Innovative modeling methods, such as hidden Markov models (HMMs), allow researchers to infer unobserved animal behaviors from movement data, and implementations often assume that transitions between states occur multiple times. However, some behavioral shifts of interest, such as parturition, migration initiation, and juvenile dispersal, may only occur once during an observation period, and HMMs may not be the best approach to identify these changes. We present two change-point models for identifying single transitions in movement behavior: a location-based change-point model and a movement metric-based change-point model. We first conducted a simulation study to determine the ability of these models to detect a behavioral transition given different amounts of data and the degree of behavioral shifts. We then applied our models to two ungulate species in central Pennsylvania that were fitted with global positioning system collars and vaginal implant transmitters to test hypotheses related to parturition behavior. We fit these models in a Bayesian framework and directly compared the ability of each model to describe the parturition behavior across species. Our simulation study demonstrated that successful change point estimation using either model was possible given at least 12 h of post-change observations and 15 min fix interval. However, our models received mixed support among deer and elk in Pennsylvania due to behavioral variation between species and among individuals. Our results demonstrate that when the behavior follows the dynamics proposed by the two models, researchers can identify the timing of a behavioral change. Although we refer to detecting parturition events, our results can be applied to any behavior that results in a single change in time.

Movement Ecology↗

USGS2023

Spatial modeling of two mosquito vectors of West Nile virus using integrated nested Laplace approximations

The abundance of Culex restuans and Culex pipiens in relation to ecological predictors is poorly understood in regions of the United States where their ranges overlap. It is suspected that these species play different roles in spreading West Nile virus (WNV) in these regions, but few studies have modeled these species separately or accounted for spatial correlation using Bayesian methods. We used mosquito surveillance data collected by the Pennsylvania Department of Environmental Protection from 2002 to 2016 and integrated nested Laplace approximations with the stochastic partial differential equation approach to predict C. restuans and C. pipiens abundance in relation to several ecological predictors. We then made a predictive risk surface of abundance for each species at locations that were not sampled. Explanatory variables in the models included ecological variables previously described to be important predictors of the abundance of these mosquito species. Developed habitat, temperature, and precipitation were important predictor variables for the abundance of C. restuans , whereas developed habitat, snow water equivalent, and normalized difference water index were important predictor variables for the abundance of C. pipiens . The abundance of C. restuans had a negative relationship with developed habitat in contrast to C. pipiens abundance, which had a positive relationship with developed habitat. Julian date was modeled as a temporal trend for both species and showed C. restuans to be more abundant from late April through late June and C. pipiens to be more abundant from July through September. A seasonal crossover was observed between these two species on Julian day 185, 4 July. We observed different spatial patterns of abundance in the predictive risk maps of each of the species. Our results indicate that modeling the abundance of these species spatially and separately in regions where these two mosquito vectors coexist can help gain further insight into understanding the epidemiology of WNV in human and susceptible animal populations.

Pennsylvania↗