Comparing the Efficacy of Two Immobilization Drug Combinations for the Chemical Restraint of Bobcats (Lynx rufus).

Chemical immobilization agents that provide rapid induction time, short duration of action, wide margin of safety, and postreversal recovery are important attributes to the handling process of immobilized animals. We evaluated differences in induction, recovery, and physiologic parameters in 23 (13 female, nine adults and four yearlings; 10 male, nine adults and one yearling) free-ranging bobcats (Lynx rufus) chemically immobilized with an intramuscular combination of ketamine (10 mg/kg) and xylazine (KX; 1.5 mg/kg; n=11) or a combination of butorphanol (0.8 mg/kg), azaperone (0.27 mg/kg), and medetomidine (BAM; 0.32 mg/kg; n=12). Induction parameters, time to first effect, hemoglobin oxygen saturation, and anesthesia between bobcats administered KX and BAM were similar. Pulse rate was significantly higher for KX than for BAM. Time to standing and full recovery after reversal were faster for bobcats administered BAM than KX. Six of 11 (55%) bobcats given KX were effectively immobilized with a single injection, and five required additional drugs to allow adequate time for processing. Of 12 bobcats given BAM, six (50%) were effectively immobilized with a single injection, three (25%) individuals were not completely immobilized and required additional doses to allow adequate time for processing, and three (25%) required additional doses after complete arousal during processing. We found that BAM provided reduced sedation and processing times (<30 min), whereas KX provided extended sedation and processing times beyond 30 min. We suggest that researchers increase initial BAM drug volumes for yearling and adult bobcats at time of processing and consider taking appropriate safety precautions when handling free-ranging bobcats.

Hunting and mountain sheep: Do current harvest practices affect horn growth?

The influence of human harvest on evolution of secondary sexual characteristics has implications for sustainable management of wildlife populations. The phenotypic consequences of selectively removing males with large horns or antlers from ungulate populations have been a topic of heightened concern in recent years. Harvest can affect size of horn-like structures in two ways: (a) shifting age structure toward younger age classes, which can reduce the mean size of horn-like structures, or (b) selecting against genes that produce large, fast-growing males. We evaluated effects of age, climatic and forage conditions, and metrics of harvest on horn size and growth of mountain sheep (Ovis canadensis ssp.) in 72 hunt areas across North America from 1981 to 2016. In 50% of hunt areas, changes in mean horn size during the study period were related to changes in age structure of harvested sheep. Environmental conditions explained directional changes in horn growth in 28% of hunt areas, 7% of which did not exhibit change before accounting for effects of the environment. After accounting for age and environment, horn size of mountain sheep was stable or increasing in the majority (~78%) of hunt areas. Age-specific horn size declined in 44% of hunt areas where harvest was regulated solely by morphological criteria, which supports the notion that harvest practices that are simultaneously selective and intensive might lead to changes in horn growth. Nevertheless, phenotypic consequences are not a foregone conclusion in the face of selective harvest; over half of the hunt areas with highly selective and intensive harvest did not exhibit age-specific declines in horn size. Our results demonstrate that while harvest regimes are an important consideration, horn growth of harvested male mountain sheep has remained largely stable, indicating that changes in horn growth patterns are an unlikely consequence of harvest across most of North America.

Weather and landscape factors affect white-tailed deer neonate survival at ecologically important life stages in the Northern Great Plains.

Offspring survival is generally more variable than adult survival and may limit population growth. Although white-tailed deer neonate survival has been intensively investigated, recent work has emphasized how specific cover types influence neonate survival at local scales (single study area). These localized investigations have often led to inconsistences within the literature. Developing specific hypotheses describing the relationships among environmental, habitat, and landscape factors influencing white-tailed deer neonate survival at regional scales may allow for detection of generalized patterns. Therefore, we developed 11 hypotheses representing the various effects of environmental (e.g., winter and spring weather), habitat (e.g., hiding and escape cover types), and landscape factors (e.g., landscape configuration regardless of specific cover type available) on white-tailed deer neonate survival up to one-month and from one- to three-months of age. At one-month, surviving fawns experienced a warmer lowest recorded June temperature and more June precipitation than those that perished. At three-months, patch connectance (percent of patches of the corresponding patch type that are connected within a predefined distance) positively influenced survival. Our results are consistent with white-tailed deer neonate ecology: increased spring temperature and precipitation are likely associated with a flush of nutritional resources available to the mother, promoting increased lactation efficiency and neonate growth early in life. In contrast, reduced spring temperature with increased precipitation place neonates at risk to hypothermia. Increased patch connectance likely reflects increased escape cover available within a neonate's home range after they are able to flee from predators. If suitable escape cover is available on the landscape, then managers could focus efforts towards manipulating landscape configuration (patch connectance) to promote increased neonate survival while monitoring spring weather to assess potential influences on current year survival.

Associations among Habitat Characteristics and Meningeal Worm Prevalence in Eastern South Dakota, USA.

Few studies have evaluated how wetland and forest characteristics influence the prevalence of meningeal worm ( Parelaphostrongylus tenuis ) infection of deer throughout the grassland biome of central North America. We used previously collected, county-level prevalence data to evaluate associations between habitat characteristics and probability of meningeal worm infection in white-tailed deer ( Odocoileus virginianus ) across eastern South Dakota, US. The highest-ranked binomial regression model for detecting probability of meningeal worm infection was spring temperature + summer precipitation + percent wetland; weight of evidence (wi=0.71) favored this model over alternative models, though predictive capability was low (Receiver operating characteristic=0.62). Probability of meningeal worm infection increased by 1.3- and 1.6-fold for each 1-cm and 1-C increase in summer precipitation and spring temperature, respectively. Similarly, probability of infection increased 1.2-fold for each 1% increase in wetland habitat. Our findings highlight the importance of wetland habitat in predicting meningeal worm infection across eastern South Dakota. Future research is warranted to evaluate the relationships between climatic conditions (e.g., drought, wet cycles) and deer habitat selection in maintaining P. tenuis along the western boundary of the parasite.

Influence of Habitat and Intrinsic Characteristics on Survival of Neonatal Pronghorn.

Increased understanding of the influence of habitat (e.g., composition, patch size) and intrinsic (e.g., age, birth mass) factors on survival of neonatal pronghorn (Antilocapra americana) is a prerequisite to successful management programs, particularly as they relate to population dynamics and the role of population models in adaptive species management. Nevertheless, few studies have presented empirical data quantifying the influence of habitat variables on survival of neonatal pronghorn. During 2002-2005, we captured and radiocollared 116 neonates across two sites in western South Dakota. We documented 31 deaths during our study, of which coyote (Canis latrans) predation (n = 15) was the leading cause of mortality. We used known fate analysis in Program MARK to investigate the influence of intrinsic and habitat variables on neonatal survival. We generated a priori models that we grouped into habitat and intrinsic effects. The highest-ranking model indicated that neonate mortality was best explained by site, percent grassland, and open water habitat; 90-day survival (0.80; 90% CI = 0.71-0.88) declined 23% when grassland and water increased from 80.1 to 92.3% and 0.36 to 0.40%, respectively, across 50% natal home ranges. Further, our results indicated that grassland patch size and shrub density were important predictors of neonate survival; neonate survival declined 17% when shrub density declined from 5.0 to 2.5 patches per 100 ha. Excluding the site covariates, intrinsic factors (i.e., sex, age, birth mass, year, parturition date) were not important predictors of survival of neonatal pronghorns. Further, neonatal survival may depend on available land cover and interspersion of habitats. We have demonstrated that maintaining minimum and maximum thresholds for habitat factors (e.g., percentages of grassland and open water patches, density of shrub patches) throughout natal home ranges will in turn, ensure relatively high (>0.50) neonatal survival rates, especially as they relate to coyote predation. Thus, landscape level variables (particularly percentages of open water, grassland habitats, and shrub density) should be incorporated into the development or implementation of pronghorn management plans across sagebrush steppe communities of the western Dakotas, and potentially elsewhere within the geographic range of pronghorn.

Effects of climate and plant phenology on recruitment of moose at the southern extent of their range.

Climate plays a fundamental role in limiting the range of a species, is a key factor in the dynamics of large herbivores, and is thought to be involved in declines of moose populations in recent decades. We examined effects of climate and growing-season phenology on recruitment (8-9 months old) of young Shiras moose (Alces alces shirasi) over three decades, from 18 herds, across a large geographic area encompassing much of the southern extent of their range. Recruitment declined in 8 of 18 herds during 1980-2009, whereas others did not exhibit a temporal trend (none showed a positive trend). During those three decades, seasonal temperatures increased, spring-summer precipitation decreased, and spring occurred earlier, became shorter in duration, and green-up occurred faster. Recruitment was influenced negatively by warm temperatures during the year before young were born, but only for herds with declining recruitment. Dry spring-summers of the previous year and rapid rates of spring green-up in the year of birth had similar negative influences across declining and stable herds. Those patterns indicate both direct (year(t)) and delayed (year(t-1)) effects of weather and plant phenology on recruitment of young, which we hypothesize was mediated through effects on maternal nutritional condition. Suppressed nutrition could have been induced by (1) increased thermoregulatory costs associated with warming temperatures and (2) shortened duration of availability of high-quality forage in spring. Progressive reductions in net energetic gain for species that are sensitive to climate may continue to hamper individual fitness and population dynamics.

Influence of ecologic factors on prevalence of meningeal worm (Parelaphostrongylus tenuis) infection in South Dakota, USA.

The meningeal worm (Parelaphostrongylus tenuis) is a nematode parasite that commonly infects white-tailed deer (Odocoileus virginianus; WTD) throughout the deciduous forest biome and deciduous-coniferous ecotone of eastern and central North America; the species is not known to occur west of the grassland biome of central North America. We used county-specific prevalence data to evaluate potential effects of landscape and climatologic factors on the spatial distribution of meningeal worm infection in South Dakota, US. Probability of infection increased 4-fold between eastern and western South Dakota and 1.3-fold for each 1-cm increase in summer precipitation. Sixty-three percent of WTD had only a single worm in the cranium. Expansion of meningeal worm infection across western South Dakota may be inherently low due to the combined effects of arid climate and potential attributes of the Missouri River that limit regional movements by infected WTD. Use of landscape genetic analyses to identify potential relationships between landscape features and population genetic structure of infected deer and parasites may contribute to a greater understanding of regional heterogeneity in meningeal worm infection rates across South Dakota, particularly in counties adjacent to the Missouri River. Future research evaluating heterogeneity in prevalence and intensity of infection between fawn and yearling deer, and the potential role of yearling male deer as dispersal agents of meningeal worms across the Missouri River, also is warranted.

Re-evaluating neonatal-age models for ungulates: does model choice affect survival estimates?

New-hoof growth is regarded as the most reliable metric for predicting age of newborn ungulates, but variation in estimated age among hoof-growth equations that have been developed may affect estimates of survival in staggered-entry models. We used known-age newborns to evaluate variation in age estimates among existing hoof-growth equations and to determine the consequences of that variation on survival estimates. During 2001-2009, we captured and radiocollared 174 newborn (≤24-hrs old) ungulates: 76 white-tailed deer (Odocoileus virginianus) in Minnesota and South Dakota, 61 mule deer (O. hemionus) in California, and 37 pronghorn (Antilocapra americana) in South Dakota. Estimated age of known-age newborns differed among hoof-growth models and varied by >15 days for white-tailed deer, >20 days for mule deer, and >10 days for pronghorn. Accuracy (i.e., the proportion of neonates assigned to the correct age) in aging newborns using published equations ranged from 0.0% to 39.4% in white-tailed deer, 0.0% to 3.3% in mule deer, and was 0.0% for pronghorns. Results of survival modeling indicated that variability in estimates of age-at-capture affected short-term estimates of survival (i.e., 30 days) for white-tailed deer and mule deer, and survival estimates over a longer time frame (i.e., 120 days) for mule deer. Conversely, survival estimates for pronghorn were not affected by estimates of age. Our analyses indicate that modeling survival in daily intervals is too fine a temporal scale when age-at-capture is unknown given the potential inaccuracies among equations used to estimate age of neonates. Instead, weekly survival intervals are more appropriate because most models accurately predicted ages within 1 week of the known age. Variation among results of neonatal-age models on short- and long-term estimates of survival for known-age young emphasizes the importance of selecting an appropriate hoof-growth equation and appropriately defining intervals (i.e., weekly versus daily) for estimating survival.

Disease and predation: sorting out causes of a bighorn sheep (Ovis canadensis) decline.

Estimating survival and documenting causes and timing of mortality events in neonate bighorn sheep (Ovis canadensis) improves understanding of population ecology and factors influencing recruitment. During 2010-2012, we captured and radiocollared 74 neonates in the Black Hills, South Dakota, of which 95% (70) died before 52 weeks of age. Pneumonia (36%) was the leading cause of mortality followed by predation (30%). We used known fate analysis in Program MARK to estimate weekly survival rates and investigate the influence of intrinsic variables on 52-week survival. Model {S1 wk, 2-8 wks, >8 wks} had the lowest AIC c (Akaike's Information Criterion corrected for small sample size) value, indicating that age (3-stage age-interval: 1 week, 2-8 weeks, and >8 weeks) best explained survival. Weekly survival estimates for 1 week, 2-8 weeks, and >8 weeks were 0.81 (95% CI = 0.70-0.88), 0.86 (95% CI = 0.81-0.90), and 0.94 (95% CI = 0.91-0.96), respectively. Overall probability of surviving 52 weeks was 0.02 (95% CI = 0.01-0.07). Of 70 documented mortalities, 21% occurred during the first week, 55% during weeks 2-8, and 23% occurred >8 weeks of age. We found pneumonia and predation were temporally heterogeneous with lambs most susceptible to predation during the first 2-3 weeks of life, while the greatest risk from pneumonia occurred from weeks 4-8. Our results indicated pneumonia was the major factor limiting recruitment followed by predation. Mortality from predation may have been partly compensatory to pneumonia and its effects were less pronounced as alternative prey became available. Given the high rates of pneumonia-caused mortality we observed, and the apparent lack of pneumonia-causing pathogens in bighorn populations in the western Black Hills, management activities should be geared towards eliminating contact between diseased and healthy populations.

Habitat, wildlife, and one health: Arcanobacterium pyogenes in Maryland and Upper Eastern Shore white-tailed deer populations.

BACKGROUND: Understanding the distribution of disease in wildlife is key to predicting the impact of emerging zoonotic one health concerns, especially for wildlife species with extensive human and livestock interfaces. The widespread distribution and complex interactions of white-tailed deer (Odocoileus virginianus) with humans suggest deer population health and management may have implications beyond stewardship of the animals. The intracranial abscessation suppurative meningitis (IASM) disease complex in deer has been linked to Arcanobacterium pyogenes, an under-diagnosed and often misdiagnosed organism considered commensal in domestic livestock but associated with serious disease in numerous species, including humans. METHODS: Our study used standard bacterial culture techniques to assess A. pyogenes prevalence among male deer sampled across six physiogeographic regions in Maryland and male and female deer in the Upper Eastern Shore under Traditional Deer Management (TDM) and Quality Deer Management (QDM), a management protocol that alters population demographics in favor of older male deer. Samples were collected from antler pedicles for males, the top of the head where pedicles would be if present for females, or the whole dorsal frontal area of the head for neonates. We collected nasal samples from all animals by swabbing the nasopharyngeal membranes. A gram stain and catalase test were conducted, and aerobic bacteria were identified to genus and species when possible. We evaluated the effect of region on whether deer carried A. pyogenes using Pearson's chi-square test with Yates' continuity correction. For the white-tailed deer management study, we tested whether site, age class and sex predisposed animals to carrying A. pyogenes using binary logistic regression. RESULTS: A. pyogenes was detected on deer in three of the six regions studied, and was common in only one region, the Upper Eastern Shore. In the Upper Eastern Shore, 45% and 66% of antler and nasal swabs from deer were positive for A. pyogenes, respectively. On the Upper Eastern Shore, prevalence of A. pyogenes cultured from deer did not differ between management areas, and was abundant among both sexes and across all age classes. No A. pyogenes was cultured from a small sample of neonates. CONCLUSION: Our study indicates A. pyogenes may be carried widely among white-tailed deer regardless of sex or age class, but we found no evidence the pathogen is acquired in utero. The distribution of A. pyogenes across regions and concentration in a region with low livestock levels suggests the potential for localized endemicity of the organism and the possibility that deer may serve as a maintenance reservoir for an emerging one health concern.

Animal migration amid shifting patterns of phenology and predation: lessons from a Yellowstone elk herd.

Migration is a striking behavioral strategy by which many animals enhance resource acquisition while reducing predation risk. Historically, the demographic benefits of such movements made migration common, but in many taxa the phenomenon is considered globally threatened. Here we describe a long-term decline in the productivity of elk (Cervus elaphus) that migrate through intact wilderness areas to protected summer ranges inside Yellowstone National Park, USA. We attribute this decline to a long-term reduction in the demographic benefits that ungulates typically gain from migration. Among migratory elk, we observed a 21-year, 70% reduction in recruitment and a 4-year, 19% depression in their pregnancy rate largely caused by infrequent reproduction of females that were young or lactating. In contrast, among resident elk, we have recently observed increasing recruitment and a high rate of pregnancy. Landscape-level changes in habitat quality and predation appear to be responsible for the declining productivity of Yellowstone migrants. From 1989 to 2009, migratory elk experienced an increasing rate and shorter duration of green-up coincident with warmer spring-summer temperatures and reduced spring precipitation, also consistent with observations of an unusually severe drought in the region. Migrants are also now exposed to four times as many grizzly bears (Ursus arctos) and wolves (Canis lupus) as resident elk. Both of these restored predators consume migratory elk calves at high rates in the Yellowstone wilderness but are maintained at low densities via lethal management and human disturbance in the year-round habitats of resident elk. Our findings suggest that large-carnivore recovery and drought, operating simultaneously along an elevation gradient, have disproportionately influenced the demography of migratory elk. Many migratory animals travel large geographic distances between their seasonal ranges. Changes in land use and climate that disparately influence such seasonal ranges may alter the ecological basis of migratory behavior, representing an important challenge for, and a powerful lens into, the ecology and conservation of migratory taxa.

Inferential consequences of modeling rather than measuring snow accumulation in studies of animal ecology.

It is increasingly common for studies of animal ecology to use model-based predictions of environmental variables as explanatory or predictor variables, even though model prediction uncertainty is typically unknown. To demonstrate the potential for misleading inferences when model predictions with error are used in place of direct measurements, we compared snow water equivalent (SWE) and snow depth as predicted by the Snow Data Assimilation System (SNODAS) to field measurements of SWE and snow depth. We examined locations on elk (Cervus canadensis) winter ranges in western Wyoming, because modeled data such as SNODAS output are often used for inferences on elk ecology. Overall, SNODAS predictions tended to overestimate field measurements, prediction uncertainty was high, and the difference between SNODAS predictions and field measurements was greater in snow shadows for both snow variables compared to non-snow shadow areas. We used a simple simulation of snow effects on the probability of an elk being killed by a predator to show that, if SNODAS prediction uncertainty was ignored, we might have mistakenly concluded that SWE was not an important factor in where elk were killed in predatory attacks during the winter. In this simulation, we were interested in the effects of snow at finer scales (< 1 km2) than the resolution of SNODAS. If bias were to decrease when SNODAS predictions are averaged over coarser scales, SNODAS would be applicable to population-level ecology studies. In our study, however, averaging predictions over moderate to broad spatial scales (9-2200 km2) did not reduce the differences between SNODAS predictions and field measurements. This study highlights the need to carefully evaluate two issues when using model output as an explanatory variable in subsequent analysis: (1) the model's resolution relative to the scale of the ecological question of interest and (2) the implications of prediction uncertainty on inferences when using model predictions as explanatory or predictor variables.

Predicting breeding habitat for amphibians: a spatiotemporal analysis across Yellowstone National Park.

The ability to predict amphibian breeding across landscapes is important for informing land management decisions and helping biologists better understand and remediate factors contributing to declines in amphibian populations. We built geospatial models of likely breeding habitats for each of four amphibian species that breed in Yellowstone National Park (YNP). We used field data collected in 2000-2002 from 497 sites among 16 basins and predictor variables from geospatial models produced from remotely sensed data (e.g., digital elevation model, complex topographic index, landform data, wetland probability, and vegetative cover). Except for 31 sites in one basin that were surveyed in both 2000 and 2002, all sites were surveyed once. We used polytomous regression to build statistical models for each species of amphibian from (1) field survey site data only, (2) field data combined with data from geospatial models, and (3) data from geospatial models only. Based on measures of receiver operating characteristic (ROC) scores, models of the second type best explained likely breeding habitat because they contained the most information (ROC values ranged from 0.70 to 0.88). However, models of the third type could be applied to the entire YNP landscape and produced maps that could be verified with reserve field data. Accuracy rates for models built for single years were highly variable, ranging from 0.30 to 0.78. Accuracy rates for models built with data combined from multiple years were higher and less variable, ranging from 0.60 to 0.80. Combining results from the geospatial multiyear models yielded maps of "core" breeding areas (areas with high probability values for all three years) surrounded by areas that scored high for only one or two years, providing an estimate of variability among years. Such information can highlight landscape options for amphibian conservation. For example, our models identify alternative areas that could be protected for each species, including 6828-10 764 ha for tiger salamanders, 971-3017 ha for western toads, 4732-16 696 ha for boreal chorus frogs, and 4940-19 690 ha for Columbia spotted frogs.

An online operational rainfall-monitoring resource for epidemic malaria early warning systems in Africa.

Periodic epidemics of malaria are a major public health problem for many sub-Saharan African countries. Populations in epidemic prone areas have a poorly developed immunity to malaria and the disease remains life threatening to all age groups. The impact of epidemics could be minimized by prediction and improved prevention through timely vector control and deployment of appropriate drugs. Malaria Early Warning Systems are advocated as a means of improving the opportunity for preparedness and timely response. Rainfall is one of the major factors triggering epidemics in warm semi-arid and desert-fringe areas. Explosive epidemics often occur in these regions after excessive rains and, where these follow periods of drought and poor food security, can be especially severe. Consequently, rainfall monitoring forms one of the essential elements for the development of integrated Malaria Early Warning Systems for sub-Saharan Africa, as outlined by the World Health Organization. The Roll Back Malaria Technical Resource Network on Prevention and Control of Epidemics recommended that a simple indicator of changes in epidemic risk in regions of marginal transmission, consisting primarily of rainfall anomaly maps, could provide immediate benefit to early warning efforts. In response to these recommendations, the Famine Early Warning Systems Network produced maps that combine information about dekadal rainfall anomalies, and epidemic malaria risk, available via their Africa Data Dissemination Service. These maps were later made available in a format that is directly compatible with HealthMapper, the mapping and surveillance software developed by the WHO's Communicable Disease Surveillance and Response Department. A new monitoring interface has recently been developed at the International Research Institute for Climate Prediction (IRI) that enables the user to gain a more contextual perspective of the current rainfall estimates by comparing them to previous seasons and climatological averages. These resources are available at no cost to the user and are updated on a routine basis.