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George Wittemyer

Publications and source records attributed to George Wittemyer.

9 recordsLinked to original sources

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

Dynamic riskscapes for prey: Disentangling the impact of human and cougar presence on deer behavior using GPS smartphone locations

Prey species adjust their behavior along human-use gradients by balancing risks from predators and humans. During hunting seasons, prey often exhibit strong antipredator responses to humans but may develop tolerance in suburban areas to exploit human-mediated resources. Additionally, areas with high human activity may offer reduced predation risk if apex predators avoid such locations. This study examined mule deer Odocoileus hemionus behavioral responses to risks from humans and their primary predators, cougars Puma concolor , contextualized by differences in risk levels between study sites, individual risk exposure, and human habituation. We framed our investigation using three non-mutually exclusive hypotheses: (H1) neutral impact, (H2) human shielding (human tolerance driven by cougar avoidance), and (H3) super-additive risk (human avoidance dominating behavior). We controlled for deer phenology and diel period, recognizing that deer behavior varies with these temporal dynamics. Spatiotemporal cougar encounter risk was quantified using GPS collar data, while spatiotemporal human encounter risk and use intensity were quantified using GPS smartphone data. Our results supported H2 and H3, emphasizing the significance of site- and individual-level variation in risk exposure and human use intensity. Deer managed cougar risk adaptively, but humans emerged as the dominant perceived risk, varying by study site. At the site with higher cougar density and lower human hunting pressure, deer exhibited antipredator responses to humans based on individual exposure to human activity, except during hunting season, when tolerance for cougars increased. Conversely, humans were the dominant risk at the site with lower cougar density and greater human hunting pressure. Deer behavior varied significantly across a gradient of human use, influenced by nuanced human presence and predation risks, which were discernible using human smartphone data.

Colorado, Utah

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

High winds and melting sea ice trigger landward movement in a polar bear population of concern

Some animal species are responding to climate change by altering the timing of events like mating and migration. Such behavioral plasticity can be adaptive, but it is not always. Polar bears ( Ursus maritimus ) from the southern Beaufort Sea subpopulation have mostly remained on ice year-round, but as the climate warms and summer sea ice declines, a growing proportion of the subpopulation is summering ashore. The triggers of this novel behavior are not well understood. Our study uses a parametric time-to-event model to test whether biological and/or time-varying environmental variables thought to influence polar bear movement and habitat selection also drive decisions to swim ashore. We quantified the time polar bears spent occupying offshore sea ice of varying ice concentrations. We evaluated variations in the ordinal date bears moved to land with respect to local environmental conditions such as sea ice concentration and wind across 10 years (2005–2015). Results from our study suggest that storm events (i.e., sustained high wind speeds) may force polar bears from severely degraded ice habitat and catalyze seasonal movements to land. Unlike polar bears long adapted to complete summer ice melt, southern Beaufort Sea bears that summer ashore appear more tolerant of poor-quality sea ice habitat and are less willing to abandon it. Our findings provide a window into emergent, climatically mediated behavior in an Arctic marine mammal vulnerable to rapid habitat decline.

Alaska

Defining an epidemiological landscape that connects movement ecology to pathogen transmission and pace-of-life

Pathogen transmission depends on host density, mobility and contact. These components emerge from host and pathogen movements that themselves arise through interactions with the surrounding environment. The environment, the emergent host and pathogen movements, and the subsequent patterns of density, mobility and contact form an ‘epidemiological landscape’ connecting the environment to specific locations where transmissions occur. Conventionally, the epidemiological landscape has been described in terms of the geographical coordinates where hosts or pathogens are located. We advocate for an alternative approach that relates those locations to attributes of the local environment. Environmental descriptions can strengthen epidemiological forecasts by allowing for predictions even when local geographical data are not available. Environmental predictions are more accessible than ever thanks to new tools from movement ecology, and we introduce a ‘movement-pathogen pace of life’ heuristic to help identify aspects of movement that have the most influence on spatial epidemiology. By linking pathogen transmission directly to the environment, the epidemiological landscape offers an efficient path for using environmental information to inform models describing when and where transmission will occur.

Ecology Letters

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

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

Africa, Greater Etosha Landscape

Mapping out a future for ungulate migrations

Migration of ungulates (hooved mammals) is a fundamental ecological process that promotes abundant herds, whose effects cascade up and down terrestrial food webs. Migratory ungulates provide the prey base that maintains large carnivore and scavenger populations and underpins terrestrial biodiversity (fig. S1). When ungulates move in large aggregations, their hooves, feces, and urine create conditions that facilitate distinct biotic communities. The migrations of ungulates have sustained humans for thousands of years, forming tight cultural links among Indigenous people and local communities. Yet ungulate migrations are disappearing at an alarming rate ( 1 ). Efforts by wildlife managers and conservationists are thwarted by a singular challenge: Most ungulate migrations have never been mapped in sufficient detail to guide effective conservation. Without a strategic and collaborative effort, many of the world's great migrations will continue to be truncated, severed, or lost in the coming decades. Fortunately, a combination of animal tracking datasets, historical records, and local and Indigenous knowledge can form the basis for a global atlas of migrations, designed to support conservation action and policy at local, national, and international levels.

Science

Movement reveals scale dependence in habitat selection of a large ungulate

Ecological processes operate across temporal and spatial scales. Anthropogenic disturbances impact these processes, but examinations of scale dependence in impacts are infrequent. Such examinations can provide important insight to wildlife–human interactions and guide management efforts to reduce impacts. We assessed spatiotemporal scale dependence in habitat selection of mule deer ( Odocoileus hemionus ) in the Piceance Basin of Colorado, USA, an area of ongoing natural gas development. We employed a newly developed animal movement method to assess habitat selection across scales defined using animal-centric spatiotemporal definitions ranging from the local (defined from five hour movements) to the broad (defined from weekly movements). We extended our analysis to examine variation in scale dependence between night and day and assess functional responses in habitat selection patterns relative to the density of anthropogenic features. Mule deer displayed scale invariance in the direction of their response to energy development features, avoiding well pads and the areas closest to roads at all scales, though with increasing strength of avoidance at coarser scales. Deer displayed scale-dependent responses to most other habitat features, including land cover type and habitat edges. Selection differed between night and day at the finest scales, but homogenized as scale increased. Deer displayed functional responses to development, with deer inhabiting the least developed ranges more strongly avoiding development relative to those with more development in their ranges. Energy development was a primary driver of habitat selection patterns in mule deer, structuring their behaviors across all scales examined. Stronger avoidance at coarser scales suggests that deer behaviorally mediated their interaction with development, but only to a degree. At higher development densities than seen in this area, such mediation may not be possible and thus maintenance of sufficient habitat with lower development densities will be a critical best management practice as development expands globally.

Colorado

Practical guidance on characterizing availability in resource selection functions under a use-availability design

Habitat selection is a fundamental aspect of animal ecology, the understanding of which is critical to management and conservation. Global positioning system data from animals allow fine-scale assessments of habitat selection and typically are analyzed in a use-availability framework, whereby animal locations are contrasted with random locations (the availability sample). Although most use-availability methods are in fact spatial point process models, they often are fit using logistic regression. This framework offers numerous methodological challenges, for which the literature provides little guidance. Specifically, the size and spatial extent of the availability sample influences coefficient estimates potentially causing interpretational bias. We examined the influence of availability on statistical inference through simulations and analysis of serially correlated mule deer GPS data. Bias in estimates arose from incorrectly assessing and sampling the spatial extent of availability. Spatial autocorrelation in covariates, which is common for landscape characteristics, exacerbated the error in availability sampling leading to increased bias. These results have strong implications for habitat selection analyses using GPS data, which are increasingly prevalent in the literature. We recommend researchers assess the sensitivity of their results to their availability sample and, where bias is likely, take care with interpretations and use cross validation to assess robustness.

Ecology