Bayesian latent-class modelling of quarantine testing procedures for American Bison (Bison bison) in the Greater Yellowstone Area to determine Brucella abortus freedom.

OBJECTIVE: American bison (Bison bison) quarantine protocols were established to prevent transmission of brucellosis outside the Greater Yellowstone Area, while allowing for distribution of wild bison for conservation and cultural purposes. Quarantine standards require rigorous testing over 900 days which has led to the release of over 200 bison to Native American tribes. Standards were evaluated using 15 years of laboratory and management data to minimize the burden of testing and increase the number of brucellosis-free bison available for distribution. ANIMALS: All bison (n = 578) from Yellowstone National Park were corralled by the National Park Service and United States Department of Agriculture. PROCEDURES: A statistical and management evaluation of the bison quarantine program was performed. Bayesian latent-class modeling was used to predict the probability of nondetection of a seroreactor at various time points, as well as the probability of seroconversion by days in quarantine. RESULTS: At 300 days, 1 in 1,000 infected bison (0.0014 probability) would not be detected but could potentially seroconvert; the seroconversion model predicted 99.9% would seroconvert by day 294, and 12.8% of bison enrolled in quarantine would seroconvert over time. Using a 300-day quarantine period, it would take 30 years to potentially miss 1 seroreactor out of over 8,000 bison enrolled in the quarantine program. CLINICAL RELEVANCE: Reducing the quarantine program requirements from over 900 days to 300 days would allow management of quarantined bison in coordination with seasonal movement of bison herds and triple the number of brucellosis-free bison available for distribution.

Feast or famine: How is global change affecting forage supply for Yellowstone's ungulate herds?

The ecological integrity of US national parks and other protected areas are under threat in the Anthropocene. For Yellowstone National Park (YNP), the impacts that global change has already had on the park's capacity to sustain its large migratory herds of wild ungulates is incompletely understood. Here we examine how two understudied components of global change, the historical increase in atmospheric CO2 and the spread of nonnative, invasive plant species, may have altered the capacity of YNP to provide forage for ungulates over the last 200-plus years. We performed two experiments: (1) a growth chamber study that determined the growth rates of important invasive and native YNP grasses that are forages for ungulates under preindustrial (280 ppm) versus modern (410 ppm) CO2 levels and (2) a field study that compared the effect of defoliation (clipping) on the shoot growth of invasive and native mesic grassland plants under ambient CO2 conditions in 2019. The growth chamber experiment revealed that modern CO2 increased the growth rates of both invasive and native grasses, and invasive grasses grew faster regardless of CO2 conditions. The field results showed a continuum of positive to negative responses of shoot growth to defoliation, with a subgroup of invasive species responding most positively. Altogether the results indicated that the historical increase in CO2 and the spread of invasive species, some of which were planted to provide forage for ungulates in the early and mid-1900s, have likely increased the capacity of forage production in YNP. However, rising CO2 has also resulted in regional warming and increased aridity in YNP, which will likely reduce grassland productivity. The challenge for global change biologists and park managers is to determine how competing components of global change have already affected and will increasingly affect forage dynamics and the sustainability of Yellowstone's iconic ungulate herds in the Anthropocene.

The precautionary principle and dietary DNA metabarcoding: Commonly used abundance thresholds change ecological interpretation.

Dietary DNA metabarcoding enables researchers to identify and characterize trophic interactions with a high degree of taxonomic precision. It is also sensitive to sources of bias and contamination in the field and laboratory. One of the earliest and most common strategies for dealing with such sensitivities has been to remove all low-abundance sequences and conduct ecological analyses based on the presence or absence of food taxa. Although this step is now often perceived to be necessary, evidence of its sufficiency is lacking and more attention to the risk of introducing other errors is needed. Using computer simulations, we demonstrate that common strategies to remove low-abundance sequences can erroneously eliminate true dietary sequences in ways that impact downstream inferences. Using real data from well-studied wildlife populations in Yellowstone National Park, we further show how these strategies can markedly alter the composition of dietary profiles in ways that scale-up to obscure ecological interpretations about dietary generalism, specialism, and composition. Although the practice of removing low-abundance sequences may continue to be a useful strategy to address research questions that focus on a subset of relatively abundant foods, its continued widespread use risks generating misleading perceptions about the structure of trophic networks. Researchers working with dietary DNA metabarcoding data-or similar data such as environmental DNA, microbiomes, or pathobiomes-should be aware of drawbacks and consider alternative bioinformatic, experimental, and statistical solutions.

How climate impacts the composition of wolf-killed elk in northern Yellowstone National Park.

While the functional response of predators is commonly measured, recent work has revealed that the age and sex composition of prey killed is often a better predictor of prey population dynamics because the reproductive value of adult females is usually higher than that of males or juveniles. Climate is often an important mediating factor in determining the composition of predator kills, but we currently lack a mechanistic understanding of how the multiple facets of climate interact with prey abundance and demography to influence the composition of predator kills. Over 20 winters, we monitored 17 wolf packs in Yellowstone National Park and recorded the sex, age and nutritional condition of kills of their dominant prey-elk-in both early and late winter periods when elk are in relatively good and relatively poor condition, respectively. Nutritional condition (as indicated by per cent marrow fat) of wolf-killed elk varied markedly with summer plant productivity, snow water equivalent (SWE) and winter period. Moreover, marrow was poorer for wolf-killed bulls and especially for calves than it was for cows. Wolf prey composition was influenced by a complex set of climatic and endogenous variables. In early winter, poor plant growth in either year t or t - 1, or relatively low elk abundance, increased the odds of wolves killing bulls relative to cows. Calves were most likely to get killed when elk abundance was high and when the forage productivity they experienced in utero was poor. In late winter, low SWE and a relatively large elk population increased the odds of wolves killing calves relative to cows, whereas low SWE and poor vegetation productivity 1 year prior together increased the likelihood of wolves killing a bull instead of a cow. Since climate has a strong influence on whether wolves prey on cows (who, depending on their age, are the key reproductive components of the population) or lower reproductive value of calves and bulls, our results suggest that climate can drive wolf predation to be more or less additive from year to year.

Migrating bison engineer the green wave.

Newly emerging plants provide the best forage for herbivores. To exploit this fleeting resource, migrating herbivores align their movements to surf the wave of spring green-up. With new technology to track migrating animals, the Green Wave Hypothesis has steadily gained empirical support across a diversity of migratory taxa. This hypothesis assumes the green wave is controlled by variation in climate, weather, and topography, and its progression dictates the timing, pace, and extent of migrations. However, aggregate grazers that are also capable of engineering grassland ecosystems make some of the world's most impressive migrations, and it is unclear how the green wave determines their movements. Here we show that Yellowstone's bison (Bison bison) do not choreograph their migratory movements to the wave of spring green-up. Instead, bison modify the green wave as they migrate and graze. While most bison surfed during early spring, they eventually slowed and let the green wave pass them by. However, small-scale experiments indicated that feedback from grazing sustained forage quality. Most importantly, a 6-fold decadal shift in bison density revealed that intense grazing caused grasslands to green up faster, more intensely, and for a longer duration. Our finding broadens our understanding of the ways in which animal movements underpin the foraging benefit of migration. The widely accepted Green Wave Hypothesis needs to be revised to include large aggregate grazers that not only move to find forage, but also engineer plant phenology through grazing, thereby shaping their own migratory movements.

Bayesian Modeling of Prion Disease Dynamics in Mule Deer Using Population Monitoring and Capture-Recapture Data.

Epidemics of chronic wasting disease (CWD) of North American Cervidae have potential to harm ecosystems and economies. We studied a migratory population of mule deer (Odocoileus hemionus) affected by CWD for at least three decades using a Bayesian framework to integrate matrix population and disease models with long-term monitoring data and detailed process-level studies. We hypothesized CWD prevalence would be stable or increase between two observation periods during the late 1990s and after 2010, with higher CWD prevalence making deer population decline more likely. The weight of evidence suggested a reduction in the CWD outbreak over time, perhaps in response to intervening harvest-mediated population reductions. Disease effects on deer population growth under current conditions were subtle with a 72% chance that CWD depressed population growth. With CWD, we forecasted a growth rate near one and largely stable deer population. Disease effects appear to be moderated by timing of infection, prolonged disease course, and locally variable infection. Long-term outcomes will depend heavily on whether current conditions hold and high prevalence remains a localized phenomenon.

Maintenance of brucellosis in Yellowstone bison: linking seasonal food resources, host-pathogen interaction, and life-history trade-offs.

The seasonal availability of food resources is an important factor shaping the life-history strategies of organisms. During times of nutritional restriction, physiological trade-offs can induce periods of immune suppression, thereby increasing susceptibility to infectious disease. Our goal was to provide a conceptual framework describing how the endemic level bovine brucellosis (Brucella abortus) may be maintained in Yellowstone bison based on the seasonality of food resources and the life-history strategies of the host and pathogen. Our analysis was based on active B. abortus infection (measured via bacterial culture), nutritional indicators (measured as metabolites and hormones in plasma), and carcass measurements of 402 slaughtered bison. Data from Yellowstone bison were used to investigate (1) whether seasonal changes in diet quality affect nutritional condition and coincide with the reproductive needs of female bison; (2) whether active B. abortus infection and infection intensities vary with host nutrition and nutritional condition; and (3) the evidence for seasonal changes in immune responses, which may offer protection against B. abortus, in relation to nutritional condition. Female bison experienced a decline in nutritional condition during winter as reproductive demands of late gestation increased while forage quality and availability declined. Active B. abortus infection was negatively associated with bison age and nutritional condition, with the intensity of infection negatively associated with indicators of nutrition (e.g., dietary protein and energy) and body weight. Data suggest that protective cell-mediated immune responses may be reduced during the B. abortus transmission period, which coincides with nutritional insufficiencies and elevated reproductive demands during spring. Our results illustrate how seasonal food restriction can drive physiological trade-offs that suppress immune function and create infection and transmission opportunities for pathogens.

AGE AND REPEATED BIOPSY INFLUENCE ANTEMORTEM PRP(CWD) TESTING IN MULE DEER (ODOCOILEUS HEMIONUS) IN COLORADO, USA.

Biopsy of rectal mucosa-associated lymphoid tissue provides a useful, but imperfect, live-animal test for chronic wasting disease (CWD) in mule deer (Odocoileus hemionus). It is difficult and expensive to complete these tests on free-ranging animals, and wildlife health managers will benefit from methods that can accommodate test results of varying quality. To this end, we developed a hierarchical Bayesian model to estimate the probability that an individual is infected based on test results. Our model was estimated with the use of data on 210 adult female mule deer repeatedly tested during 2010-14. The ability to identify infected individuals correctly declined with age and may have been influenced by repeated biopsy. Fewer isolated lymphoid follicles (where PrP(CWD) accumulates) were obtained in biopsies of older deer and the proportion of follicles showing PrP(CWD) was reduced. A deer's genotype in the prion gene (PRNP) also influenced detection. At least five follicles were needed in a biopsy to assure a 95% accurate test in PRNP genotype 225SS deer.

Predicting bison migration out of Yellowstone National Park using bayesian models.

Long distance migrations by ungulate species often surpass the boundaries of preservation areas where conflicts with various publics lead to management actions that can threaten populations. We chose the partially migratory bison (Bison bison) population in Yellowstone National Park as an example of integrating science into management policies to better conserve migratory ungulates. Approximately 60% of these bison have been exposed to bovine brucellosis and thousands of migrants exiting the park boundary have been culled during the past two decades to reduce the risk of disease transmission to cattle. Data were assimilated using models representing competing hypotheses of bison migration during 1990-2009 in a hierarchal bayesian framework. Migration differed at the scale of herds, but a single unifying logistic model was useful for predicting migrations by both herds. Migration beyond the northern park boundary was affected by herd size, accumulated snow water equivalent, and aboveground dried biomass. Migration beyond the western park boundary was less influenced by these predictors and process model performance suggested an important control on recent migrations was excluded. Simulations of migrations over the next decade suggest that allowing increased numbers of bison beyond park boundaries during severe climate conditions may be the only means of avoiding episodic, large-scale reductions to the Yellowstone bison population in the foreseeable future. This research is an example of how long distance migration dynamics can be incorporated into improved management policies.