Long-term data reveal fitness costs of anthropogenic prey depletion for a subordinate competitor, the African wild dog (Lycaon pictus)

Within carnivore guilds, dominant competitors (e.g., lions, Panthera leo) are limited primarily by the density of prey, while subordinate competitors (e.g., African wild dogs, Lycaon pictus) have been limited by the density of dominant competitors. Historically, the fitness and population density of subordinate competitors have not been tightly linked to prey density. However, populations of large herbivores have declined substantially across sub-Saharan Africa due to human impacts, and where prey depletion is severe, fitness costs for competitive subordinates may begin to outweigh the benefits of competitive release. Using long-term intensive monitoring of African wild dogs in Zambia's Luangwa Valley Ecosystem (LVE), we tested the effects of prey depletion on survival and reproduction. We hypothesized that African wild dog fitness would be lower in prey-depleted areas, despite lower lion densities. Our study area included four contiguous regions that varied in protection level, prey density, and lion density. We fit Bayesian Cormack-Jolly-Seber and closed-capture models to estimate effects on survival and population density, and generalized linear models to estimate effects on reproductive success. We found that the LVE is a stronghold for African wild dogs, with an estimated median density of 4.0 individuals/100 km(2). Despite this high density, survival and reproduction differed among regions, and both components of fitness were substantially reduced in the region with the lowest prey density. Anthropogenic prey depletion is becoming an important limiting factor for African wild dogs. If prey depletion (or any other form of habitat degradation) becomes severe enough that its fitness costs outweigh the benefits of competitive release, such changes can fundamentally alter the balance between limiting factors for competitively subordinate species

Meta-Analysis of Relationships between Human Offtake, Total Mortality and Population Dynamics of Gray Wolves (Canis lupus)

Following the growth and geographic expansion of wolf (Canis lupus) populations reintroduced to Yellowstone National Park and central Idaho in 1995–1996, Rocky Mountain wolves were removed from the endangered species list in May 2009. Idaho and Montana immediately established hunting seasons with quotas equaling 20% of the regional wolf population. Combining hunting with predator control, 37.1% of Montana and Idaho wolves were killed in the year of delisting. Hunting and predator control are well-established methods to broaden societal acceptance of large carnivores, but it is unprecedented for a species to move so rapidly from protection under the Endangered Species Act to heavy direct harvest, and it is important to use all available data to assess the likely consequences of these changes in policy. For wolves, it is widely argued that human offtake has little effect on total mortality rates, so that a harvest of 28–50% per year can be sustained. Using previously published data from 21 North American wolf populations, we related total annual mortality and population growth to annual human offtake. Contrary to current conventional wisdom, there was a strong association between human offtake and total mortality rates across North American wolf populations. Human offtake was associated with a strongly additive or super-additive increase in total mortality. Population growth declined as human offtake increased, even at low rates of offtake. Finally, wolf populations declined with harvests substantially lower than the thresholds identified in current state and federal policies. These results should help to inform management of Rocky Mountain wolves

Limitations to estimating bacterial cross-species transmission using genetic and genomic markers: inferences from simulation modeling

Cross-species transmission (CST) of bacterial pathogens has major implications for human health, livestock, and wildlife management because it determines whether control actions in one species may have subsequent effects on other potential host species. The study of bacterial transmission has benefitted from methods measuring two types of genetic variation: variable number of tandem repeats (VNTRs) and single nucleotide polymorphisms (SNPs). However, it is unclear whether these data can distinguish between different epidemiological scenarios. We used a simulation model with two host species and known transmission rates (within and between species) to evaluate the utility of these markers for inferring CST. We found that CST estimates are biased for a wide range of parameters when based on VNTRs and a most parsimonious reconstructed phylogeny. However, estimations of CST rates lower than 5% can be achieved with relatively low bias using as low as 250 SNPs. CST estimates are sensitive to several parameters, including the number of mutations accumulated since introduction, stochasticity, the genetic difference of strains introduced, and the sampling effort. Our results suggest that, even with whole-genome sequences, unbiased estimates of CST will be difficult when sampling is limited, mutation rates are low, or for pathogens that were recently introduced

Higher Order Chemistry Models in the CFD Simulation of Laser-Ablated Carbon Plumes

Production of single-walled carbon nanotubes (SWNT) has taken place for a number of years and by a variety of methods such as laser ablation, chemical vapor deposition, and arc-jet ablation. Yet, little is actually understood about the exact chemical kinetics and processes that occur in SWNT formation. In recent time, NASA Johnson Space Center has devoted a considerable effort to the experimental evaluation of the laser ablation production process for SWNT originally developed at Rice University. To fully understand the nature of the laser ablation process it is necessary to understand the development of the carbon plume dynamics within the laser ablation oven. The present work is a continuation of previous studies into the efforts to model plume dynamics using computational fluid dynamics (CFD). The ultimate goal of the work is to improve understanding of the laser ablation process, and through that improved understanding, refine the laser ablation production of SWNT

Spatiotemporal Variability in Biomass and Forage Quality Across a Temperate Landscape with Heterogeneous Phenology Patterns (Poster)

Although spatial and temporal heterogeneity in grassland biomass and forage quality is well-recognized to play an important role in migratory ungulate population dynamics, attempts to directly quantify biomass and forage quality across temperate landscapes throughout the growing season are limited. It is generally recognized that biomass and forage quality are directly related to phenology, but little is known about how seasonal biomass and forage quality differs across land use and biophysical gradients with varying phenology patterns. This study uses field estimates of biomass, chlorophyll concentration, crude protein, and in vitro dry matter digestibility collected from 20, 250m2 grassland plots throughout the summers of 2013 and 2014 to quantify how biomass and forage quality differ across land uses and biophysical gradients in the migratory elk (Cervus elaphus) range in the Upper Yellowstone River Basin. Key findings were that irrigated agriculture had overall greater and longer available biomass and forage quality throughout the growing season compared to private and public grasslands with natural phenology patterns. And that areas that begin growth later in the season had overall greater biomass and forage quality than areas with mid and early phenology characteristics, but availability was shorter. These results suggest that seasonal patterns of biomass and forage quality differ with phenological characteristics across temperate landscapes. This information should be incorporated in our understanding of spatiotemporal patterns of vegetation important for studying migratory ungulate ecology and predicting the effects of climate change and human land use on vegetation dynamics in temperate landscapes

Population Density, Group Size or Something in Between: Effects of a Variable Social Structure on Parasite Transmission

Critical to our understanding of disease dynamics and effective disease control strategies is the relationship between host density and parasite transmission rates. To accurately describe this relationship, it is important to measure host density at the scale in which transmission is occurring. In social species, for example, transmission may be more related to group size than the population as a whole. But when aggregation patterns vary in size across space and time, our ability to quantify the density-transmission relationship may depend on measuring density somewhere in between population density and group size. To address this issue, we examined elk (Cervus elaphus) populations in western Wyoming that have been exposed to the bacteria (Brucella abortus) that causes brucellosis. We measured elk density at multiple scales ranging from population density to group size, and evaluated the functional relationship between density and brucellosis seroprevalence. Our study found that low elk density did not explain why Brucella had not effectively invaded several populations. However, in populations with multiple years of seropositive test results, the rates of increase in seroprevalence saturate with increasing elk density regardless of the density measure used. The different densities were poorly correlated with one another, and therefore high elk densities at broad scales did not guarantee high elk densities at fine scales, but both may be important to the transmission of Brucella. This suggests that reducing or altering elk density may not effectively reduce transmission

African wild dog movements show contrasting responses to long and short term risk of encountering lions: analysis using dynamic Brownian bridge movement models

Background Prey depletion is a threat to the world's large carnivores, and is likely to affect subordinate competitors within the large carnivore guild disproportionately. African lions limit African wild dog populations through interference competition and intraguild predation. When lion density is reduced as a result of prey depletion, wild dogs are not competitively released, and their population density remains low. Research examining distributions has demonstrated spatial avoidance of lions by wild dogs, but the effects of lions on patterns of movement have not been tested. Movement is one of the most energetically costly activities for many species and is particularly costly for cursorial hunters like wild dogs. Therefore, testing how top-down, bottom-up, and anthropogenic variables affect movement patterns can provide insight into mechanisms that limit wild dogs (and other subordinate competitors) in resource-depleted ecosystems. Methods We measured movement rates using the motion variance from dynamic Brownian Bridge Movement Models (dBBMMs) fit to data from GPS-collared wild dogs, then used a generalized linear model to test for effects on movement of predation risk from lions, predictors of prey density, and anthropogenic and seasonal variables. Results Wild dogs proactively reduced movement in areas with high lion density, but reactively increased movement when lions were immediately nearby. Predictors of prey density had consistently weaker effects on movement than lions did, but movements were reduced in the wet season and when dependent offspring were present. Conclusion Wild dogs alter their patterns of movement in response to lions in ways that are likely to have important energetic consequences. Our results support the recent suggestion that competitive limitation of wild dogs by lions remains strong in ecosystems where lion and wild dog densities are both low as a result of anthropogenic prey depletion. Our results reinforce an emerging pattern that movements often show contrasting responses to long-term and short-term variation in predation risk

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 (\u3c1 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\u27s 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

Elk Contact Patterns and Potential Disease Transmission

Understanding the drivers of contact rates among individuals is critical to understanding disease dynamics and implementing targeted control measures. We studied the interaction patterns of 149 female elk (Cervus elaphus) distributed across five different regions of western Wyoming over three years, defining a contact as an approach within one body length (~2m). Using hierarchical models that account for correlations within individuals, pairs and groups, we found that pairwise contact rates within a group declined by a factor of three as group sizes increased 30-fold. Meanwhile, per capita contact rates increased with group size due to the increasing number of potential pairs. We found similar patterns for the duration of contacts. Supplemental feeding of elk had a limited impact on pairwise interaction rates and durations, but increased per capita rates more than two times higher. Variation in contact patterns were driven more by environmental factors such as group size than either individual or pairwise differences. Female elk in this region fall between the expectation of contact rates that linearly increase with group size (as assumed by pseudo-mass action models of disease transmission) or are constant with changes in group size (as assumed by frequency dependent transmission models). Our statistical approach decomposes the variation in contact rate into individual, dyadic, and environmental effects, which provides insight into those factors that are important for effective disease control programs