Spatial risk modeling of cattle depredation by black vultures in the midwestern United States

ock operations through depredation of stock are a cause of human‐wildlife conflict. Management of such conflict requires identifying environmental and non‐environmental factors specific to a wildlife species\u27 biology and ecology that influence the potential for livestock depredation to occur. Identification of such factors can improve understanding of the conditions placing livestock at risk. Black vultures (Coragyps atratus) have expanded their historical range northward into the midwestern United States. Concomitantly, an increase in concern among agricultural producers regarding potential black vulture attacks on livestock has occurred. We estimated area with greater or lesser potential for depredation of domestic cattle by black vultures across a 6‐state region in the midwestern United States using an ensemble of small models (ESM). Specifically, we identified landscape‐scale spatial factors, at a zip code resolution, associated with reported black vulture depredation on cattle in midwestern landscapes to predict future potential livestock depredation. We hypothesized that livestock depredation would be greatest in areas with intensive beef cattle production close to preferred black vulture habitat (e.g., areas with fewer old fields and early successional vegetation paired with more direct edge between older forest and agricultural lands). We predicted that the density of cattle within the county, habitat structure, and proximity to anthropogenic landscape features would be the strongest predictors of black vulture livestock‐depredation risk. Our ESM estimated the relative risk of black vulture‐cattle depredation to be between 0.154–0.631 across our entire study area. Consistent with our hypothesis, areas of greatest predicted risk of depredation correspond with locations that are favorable to vulture life‐history requirements and increased potential to encounter livestock. Our results allow wildlife managers the ability to predict where black vulture depredation of cattle is more likely to occur in the future. It is in these areas where extension and outreach efforts aimed at mitigating this conflict should be focused. Researchers and wildlife managers interested in developing or employing tools aimed at mitigating livestock‐vulture conflicts can also leverage our results to select areas where depredation is most likely to occur

Fusion of visible and thermal images improves automated detection and classification of animals for drone surveys

Visible and thermal images acquired from drones (unoccupied aircraft systems) have substantially improved animal monitoring. Combining complementary information from both image types provides a powerful approach for automating detection and classification of multiple animal species to augment drone surveys. We compared eight image fusion methods using thermal and visible drone images combined with two supervised deep learning models, to evaluate the detection and classification of white-tailed deer (Odocoileus virginianus), domestic cow (Bos taurus), and domestic horse (Equus caballus). We classified visible and thermal images separately and compared them with the results of image fusion. Fused images provided minimal improvement for cows and horses compared to visible images alone, likely because the size, shape, and color of these species made them conspicuous against the background. For white-tailed deer, which were typically cryptic against their backgrounds and often in shadows in visible images, the added information from thermal images improved detection and classification in fusion methods from 15 to 85%. Our results suggest that image fusion is ideal for surveying animals inconspicuous from their backgrounds, and our approach uses few image pairs to train compared to typical machine-learning methods. We discuss computational and field considerations to improve drone surveys using our fusion approach. Supplemental files attached below

Feed processing parameters and their effects on nursery pig growth performance

A total of 180 nursery pigs (PIC 327 × 1050; initially 27.8 lb) were used in an 18-d study to determine the effects of conditioning parameters and feed form on pig performance. All diets were the same corn, dried distillers grains with solubles (DDGS), and soybean meal-based formulation with different processing parameters used to create the experimental treatments. Treatments included: (1) negative control mash diet, (2) positive control pelleted diet conditioned at 60 rpm, (3) pelleted diet conditioned at 30 rpm and reground, (4) pelleted diet conditioned at 60 rpm and reground, and (5) pelleted diet conditioned at 90 rpm and reground. The different rpm values among treatments represent the time in the conditioner during processing. The lower the rpm value, the longer time feed was in the conditioner. Pigs were weaned and fed a common acclimation diet for 21 d prior to the start of the experiment. Average daily gain and F/G did not differ (P > 0.12) between treatments overall, but ADFI decreased (P = 0.03) for pigs fed the pelleted, positive control diet compared with all other diets. Although no overall treatment effects were significant for ADG or F/G, the experiment was designed more specifically to evaluate treatment differences using preplanned comparisons. When considering preplanned contrasts, we observed that pigs fed mash diets tended to have greater (P = 0.10) ADG than those fed pelleted and reground diets, suggesting that processing may have had a negative influence on feed utilization, a hypothesis that is further supported because pigs fed mash diets tended to have greater (P = 0.06) ADG compared with those fed diets that were heat-processed, regardless of regrinding. Considering these results, it was not surprising that pigs fed mash diets had greater (P = 0.05) ADG and ADFI (P = 0.01) than those fed pelleted diets. When directly comparing diets conditioned at 60 rpm, fed either as whole pellets or reground to mash consistency, pigs fed pelleted diets had improved (P = 0.01) F/G due to lower ADFI (P = 0.004) but similar ADG (P = 0.60). This unexpected negative impact of pelleting on ADG may be due to a negative influence of heat treatment on palatability. The expected improvement in F/G from pelleting (6.8%) was observed but lost when diets were reground to near original mash particle size. This result may indicate that diet form (high-quality pellets vs. mash) affects F/G more than degree of starch gelatinization or other intrinsic factors associated with conditioning ingredients

Novel Naphthalene-Based Inhibitors of Trypanosoma brucei RNA Editing Ligase 1

African sleeping sickness is a devastating disease that plagues sub-Saharan Africa. Neglected tropical diseases like African sleeping sickness cause significant death and suffering in the world's poorest countries. Current treatments for African sleeping sickness either have high costs, terrible side effects, or limited effectiveness. Consequently, new medicines are urgently needed. RNA editing ligase 1 is an important protein critical for the survival of Trypanosoma brucei, the unicellular parasite that causes African sleeping sickness. In this paper, we describe our recent efforts to use advanced computer techniques to identify chemicals predicted to prevent RNA editing ligase 1 from functioning properly. We subsequently tested our predicted chemicals and confirmed that a number of them inhibited the protein's function. Additionally, one of the chemicals was effective at stopping the growth of the parasite in culture. Although substantial work remains to be done in order to optimize these chemicals so they are effective and safe to use in human patients, the identification of these parasite-killing compounds is nevertheless a valuable step towards finding a better cure for this devastating disease

Dataset for Controllable factors affecting accuracy and precision of human identification of animals from drone imagery

Dataset from the results of an experiment to determine how three controllable factors, flight altitude, camera angle, and time of day, affect human identification and counts of animals from drone images to inform best practices to survey animal communities with drones. We used a drone (unoccupied aircraft system, or UAS) to survey known numbers of eight animal decoy species, representing a range of body sizes and colors, at four GSD (ground sampling distance) values (0.35, 0.70, 1.06, 1.41 cm/pixel) representing equivalent flight altitudes (15.2, 30.5, 45.7, 61.0 m) at two camera angles (45° and 90°) and across a range of times of day (morning to late afternoon). Expert human observers identified and counted animals in drone images to determine how the three controllable factors affected accuracy and precision. Observer precision was high and unaffected by tested factors. However, results for observer accuracy revealed an interaction among all three controllable factors. Increasing flight altitude resulted in decreased accuracy in animal counts overall; however, accuracy was best at midday compared to morning and afternoon hours, when decoy and structure shadows were present or more pronounced. Surprisingly, the 45° camera enhanced accuracy compared to 90°, but only when animals were most difficult to identify and count, such as at higher flight altitudes or during the early morning and late afternoon. We provide recommendations based on our results to design future surveys to improve human accuracy in identifying and counting animals from drone images for monitoring animal populations and communities

Consequences of Intraspecific Variation in Seed Dispersal for Plant Demography, Communities, Evolution and Global Change

As the single opportunity for plants to move, seed dispersal has an important impact on plant fitness, species distributions and patterns of biodiversity. However, models that predict dynamics such as risk of extinction, range shifts and biodiversity loss tend to rely on the mean value of parameters and rarely incorporate realistic dispersal mechanisms. By focusing on the mean population value, variation among individuals or variability caused by complex spatial and temporal dynamics is ignored. This calls for increased efforts to understand individual variation in dispersal and integrate it more explicitly into population and community models involving dispersal. However, the sources, magnitude and outcomes of intraspecific variation in dispersal are poorly characterized, limiting our understanding of the role of dispersal in mediating the dynamics of communities and their response to global change. In this manuscript, we synthesize recent research that examines the sources of individual variation in dispersal and emphasize its implications for plant fitness, populations and communities. We argue that this intraspecific variation in seed dispersal does not simply add noise to systems, but, in fact, alters dispersal processes and patterns with consequences for demography, communities, evolution and response to anthropogenic changes. We conclude with recommendations for moving this field of research forward

Consequences of Intraspecific Variation in Seed Dispersal for Plant Demography, Communities, Evolution and Global Change

As the single opportunity for plants to move, seed dispersal has an important impact on plant fitness, species distributions and patterns of biodiversity. However, models that predict dynamics such as risk of extinction, range shifts and biodiversity loss tend to rely on the mean value of parameters and rarely incorporate realistic dispersal mechanisms. By focusing on the mean population value, variation among individuals or variability caused by complex spatial and temporal dynamics is ignored. This calls for increased efforts to understand individual variation in dispersal and integrate it more explicitly into population and community models involving dispersal. However, the sources, magnitude and outcomes of intraspecific variation in dispersal are poorly characterized, limiting our understanding of the role of dispersal in mediating the dynamics of communities and their response to global change. In this manuscript, we synthesize recent research that examines the sources of individual variation in dispersal and emphasize its implications for plant fitness, populations and communities. We argue that this intraspecific variation in seed dispersal does not simply add noise to systems, but, in fact, alters dispersal processes and patterns with consequences for demography, communities, evolution and response to anthropogenic changes. We conclude with recommendations for moving this field of research forward

Measurements of Transverse Energy Flow in Deep-Inelastic Scattering at HERA

Measurements of transverse energy flow are presented for neutral current deep-inelastic scattering events produced in positron-proton collisions at HERA. The kinematic range covers squared momentum transfers Q^2 from 3.2 to 2,200 GeV^2, the Bjorken scaling variable x from 8.10^{-5} to 0.11 and the hadronic mass W from 66 to 233 GeV. The transverse energy flow is measured in the hadronic centre of mass frame and is studied as a function of Q^2, x, W and pseudorapidity. A comparison is made with QCD based models. The behaviour of the mean transverse energy in the central pseudorapidity region and an interval corresponding to the photon fragmentation region are analysed as a function of Q^2 and W.Comment: 26 pages, 8 figures, submitted to Eur. Phys.

The Association between Hypertension and Depression and Anxiety Disorders: Results from a Nationally-Representative Sample of South African Adults

OBJECTIVE:Growing evidence suggests high levels of comorbidity between hypertension and mental illness but there are few data from low- and middle-income countries. We examined the association between hypertension and depression and anxiety in South Africa. METHODS:Data come from a nationally-representative survey of adults (n = 4351). The Composite International Diagnostic Interview was used to measure DSM-IV mental disorders during the previous 12-months. The relationships between self-reported hypertension and anxiety disorders, depressive disorders and comorbid anxiety-depression were assessed after adjustment for participant characteristics including experience of trauma and other chronic physical conditions. RESULTS:Overall 16.7% reported a previous medical diagnosis of hypertension, and 8.1% and 4.9% were found to have a 12-month anxiety or depressive disorder, respectively. In adjusted analyses, hypertension diagnosis was associated with 12-month anxiety disorders [Odds ratio (OR) = 1.55, 95% Confidence interval (CI) = 1.10-2.18] but not 12-month depressive disorders or 12-month comorbid anxiety-depression. Hypertension in the absence of other chronic physical conditions was not associated with any of the 12-month mental health outcomes (p-values all <0.05), while being diagnosed with both hypertension and another chronic physical condition were associated with 12-month anxiety disorders (OR = 2.25, 95% CI = 1.46-3.45), but not 12-month depressive disorders or comorbid anxiety-depression. CONCLUSIONS:These are the first population-based estimates to demonstrate an association between hypertension and mental disorders in sub-Saharan Africa. Further investigation is needed into role of traumatic life events in the aetiology of hypertension as well as the temporality of the association between hypertension and mental disorders

Forward pi^0 Production and Associated Transverse Energy Flow in Deep-Inelastic Scattering at HERA

Deep-inelastic positron-proton interactions at low values of Bjorken-x down to x \approx 4.10^-5 which give rise to high transverse momentum pi^0 mesons are studied with the H1 experiment at HERA. The inclusive cross section for pi^0 mesons produced at small angles with respect to the proton remnant (the forward region) is presented as a function of the transverse momentum and energy of the pi^0 and of the four-momentum transfer Q^2 and Bjorken-x. Measurements are also presented of the transverse energy flow in events containing a forward pi^0 meson. Hadronic final state calculations based on QCD models implementing different parton evolution schemes are confronted with the data.Comment: 27 pages, 8 figures and 3 table