Cranes soar on thermal updrafts behind cold fronts as they migrate across the sea.

Thermal soaring conditions above the sea have long been assumed absent or too weak for terrestrial migrating birds, forcing obligate soarers to take long detours and avoid sea-crossing, and facultative soarers to cross exclusively by costly flapping flight. Thus, while atmospheric convection does develop at sea and is used by some seabirds, it has been largely ignored in avian migration research. Here, we provide direct evidence for routine thermal soaring over open sea in the common crane, the heaviest facultative soarer known among terrestrial migrating birds. Using high-resolution biologging from 44 cranes tracked across their transcontinental migration over 4 years, we show that soaring performance was no different over sea than over land in mid-latitudes. Sea-soaring occurred predominantly in autumn when large water-air temperature difference followed mid-latitude cyclones. Our findings challenge a fundamental migration research paradigm and suggest that obligate soarers avoid sea-crossing not due to the absence or weakness of thermals but due to their low frequency, for which they cannot compensate with prolonged flapping. Conversely, facultative soarers other than cranes should also be able to use thermals over the sea. Marine cold air outbreaks, imperative to global energy budget and climate, may also be important for bird migration.

Variation in herbivore space use: comparing two savanna ecosystems with different anthrax outbreak patterns in southern Africa.

BACKGROUND: The distribution of resources can affect animal range sizes, which in turn may alter infectious disease dynamics in heterogenous environments. The risk of pathogen exposure or the spatial extent of outbreaks may vary with host range size. This study examined the range sizes of herbivorous anthrax host species in two ecosystems and relationships between spatial movement behavior and patterns of disease outbreaks for a multi-host environmentally transmitted pathogen. METHODS: We examined range sizes for seven host species and the spatial extent of anthrax outbreaks in Etosha National Park, Namibia and Kruger National Park, South Africa, where the main host species and outbreak sizes differ. We evaluated host range sizes using the local convex hull method at different temporal scales, within-individual temporal range overlap, and relationships between ranging behavior and species contributions to anthrax cases in each park. We estimated the spatial extent of annual anthrax mortalities and evaluated whether the extent was correlated with case numbers of a given host species. RESULTS: Range size differences among species were not linearly related to anthrax case numbers. In Kruger the main host species had small range sizes and high range overlap, which may heighten exposure when outbreaks occur within their ranges. However, different patterns were observed in Etosha, where the main host species had large range sizes and relatively little overlap. The spatial extent of anthrax mortalities was similar between parks but less variable in Etosha than Kruger. In Kruger outbreaks varied from small local clusters to large areas and the spatial extent correlated with case numbers and species affected. Secondary host species contributed relatively few cases to outbreaks; however, for these species with large range sizes, case numbers positively correlated with outbreak extent. CONCLUSIONS: Our results provide new information on the spatiotemporal structuring of ranging movements of anthrax host species in two ecosystems. The results linking anthrax dynamics to host space use are correlative, yet suggest that, though partial and proximate, host range size and overlap may be contributing factors in outbreak characteristics for environmentally transmitted pathogens.

Categorizing the geometry of animal diel movement patterns with examples from high-resolution barn owl tracking.

BACKGROUND: Movement is central to understanding the ecology of animals. The most robustly definable segments of an individual's lifetime track are its diel activity routines (DARs). This robustness is due to fixed start and end points set by a 24-h clock that depends on the individual's quotidian schedule. An analysis of day-to-day variation in the DARs of individuals, their comparisons among individuals, and the questions that can be asked, particularly in the context of lunar and annual cycles, depends on the relocation frequency and spatial accuracy of movement data. Here we present methods for categorizing the geometry of DARs for high frequency (seconds to minutes) movement data. METHODS: Our method involves an initial categorization of DARs using data pooled across all individuals. We approached this categorization using a Ward clustering algorithm that employs four scalar "whole-path metrics" of trajectory geometry: 1. net displacement (distance between start and end points), 2. maximum displacement from start point, 3. maximum diameter, and 4. maximum width. We illustrate the general approach using reverse-GPS data obtained from 44 barn owls, Tyto alba, in north-eastern Israel. We conducted a principle components analysis (PCA) to obtain a factor, PC1, that essentially captures the scale of movement. We then used a generalized linear mixed model with PC1 as the dependent variable to assess the effects of age and sex on movement. RESULTS: We clustered 6230 individual DARs into 7 categories representing different shapes and scale of the owls nightly routines. Five categories based on size and elongation were classified as closed (i.e. returning to the same roost), one as partially open (returning to a nearby roost) and one as fully open (leaving for another region). Our PCA revealed that the DAR scale factor, PC1, accounted for 86.5% of the existing variation. It also showed that PC2 captures the openness of the DAR and accounted for another 8.4% of the variation. We also constructed spatio-temporal distributions of DAR types for individuals and groups of individuals aggregated by age, sex, and seasonal quadrimester, as well as identify some idiosyncratic behavior of individuals within family groups in relation to location. Finally, we showed in two ways that DARs were significantly larger in young than adults and in males than females. CONCLUSION: Our study offers a new method for using high-frequency movement data to classify animal diel movement routines. Insights into the types and distributions of the geometric shape and size of DARs in populations may well prove to be more invaluable for predicting the space-use response of individuals and populations to climate and land-use changes than other currently used movement track methods of analysis.

Coursing hyenas and stalking lions: The potential for inter- and intraspecific interactions.

Resource partitioning promotes coexistence among guild members, and carnivores reduce interference competition through behavioral mechanisms that promote spatio-temporal separation. We analyzed sympatric lion and spotted hyena movements and activity patterns to ascertain the mechanisms facilitating their coexistence within semi-arid and wetland ecosystems. We identified recurrent high-use (revisitation) and extended stay (duration) areas within home ranges, as well as correlated movement-derived measures of inter- and intraspecific interactions with environmental variables. Spatial overlaps among lions and hyenas expanded during the wet season, and occurred at edges of home ranges, around water-points, along pathways between patches of high-use areas. Lions shared more of their home ranges with spotted hyenas in arid ecosystems, but shared more of their ranges with conspecifics in mesic environments. Despite shared space use, we found evidence for subtle temporal differences in the nocturnal movement and activity patterns between the two predators, suggesting a fine localized-scale avoidance strategy. Revisitation frequency and duration within home ranges were influenced by interspecific interactions, after land cover categories and diel cycles. Intraspecific interactions were also important for lions and, important for hyenas were moon illumination and ungulates attracted to former anthrax carcass sites in Etosha, with distance to water in Chobe/Linyanti. Recursion and duration according to locales of competitor probabilities were similar among female lions and both sexes of hyenas, but different for male lions. Our results suggest that lions and spotted hyenas mediate the potential for interference competition through subtle differences in temporal activity, fine-scale habitat use differentiation, and localized reactive-avoidance behaviors. These findings enhance our understanding of the potential effects of interspecific interactions among large carnivore space-use patterns within an apex predator system and show adaptability across heterogeneous and homogeneous environments. Future conservation plans should emphasize the importance of inter- and intraspecific competition within large carnivore communities, particularly moderating such effects within increasingly fragmented landscapes.

Comparing invasive and noninvasive faecal sampling in wildlife microbiome studies: A case study on wild common cranes.

In ecological and conservation studies, responsible researchers strive to obtain rich data while minimizing disturbance to wildlife and ecosystems. We assessed if samples collected noninvasively can be used for faecal microbiome research, comparing microbiota of noninvasively collected faecal samples to those collected from trapped common cranes at the same sites over the same periods. We found significant differences in faecal microbial composition (alpha and beta diversity), which likely did not result from noninvasive sample exposure to soil contaminants, as assessed by comparing bacterial oxygen use profiles. Differences might result from trapped birds' exposure to sedatives or stress. We conclude that if all samples are collected in the same manner, comparative analyses are valid, and noninvasive sampling may better represent host faecal microbiota because there are no trapping effects. Experiments with fresh and delayed sample collection can elucidate effects of environmental exposures on microbiota. Further, controlled tests of stressing or sedation may unravel how trapping affects wildlife microbiota.

Linking migration and microbiota at a major stopover site in a long-distance avian migrant.

Migration is one of the most physical and energetically demanding periods in an individual bird's life. The composition of the bird's gut or cloacal microbiota can temporarily change during migration, likely due to differences in diets, habitats and other environmental conditions experienced en route. However, how physiological condition, migratory patterns, and other drivers interact to affect microbiota composition of migratory birds is still unclear. We sampled the cloacal bacterial microbiota of a long-distance migrant, the steppe buzzard (Buteo buteo vulpinus), at an important spring stopover bottleneck in Eilat, Israel, after crossing the ca. 1800 km Sahara Desert. We examined whether diversity and composition of the cloacal microbiota varied with body condition, sex, movement patterns (i.e., arrival time and migration distance), and survival. Early arrival to Eilat was associated with better body condition, longer post-Eilat spring migration distance, higher microbial α-diversity, and differences in microbiota composition. Specifically, early arrivals had higher abundance of the phylum Synergistota and five genera, including Jonquetella and Peptococcus, whereas the phylum Proteobacteria and genus Escherichia-Shigella (as well as three other genera) were more abundant in later arrivals. While the differences in α-diversity and Escherichia-Shigella seem to be mainly driven by body condition, other compositional differences associated with arrival date could be indicators of longer migratory journeys (e.g., pre-fueling at wintering grounds or stopover habitats along the way) or migratory performance. No significant differences were found between the microbiota of surviving and non-surviving individuals. Overall, our results indicate that variation in steppe buzzard microbiota is linked to variation in migratory patterns (i.e., capture/arrival date) and body condition, highlighting the importance of sampling the microbiota of GPS-tracked individuals on multiple occasions along their migration routes to gain a more detailed understanding of the links between migration, microbiota, and health in birds.

A comparison of COVID-19 outbreaks across US Combined Statistical Areas using new methods for estimating R0 and social distancing behaviour.

We investigated the initial outbreak rates and subsequent social distancing behaviour over the initial phase of the COVID-19 pandemic across 29 Combined Statistical Areas (CSAs) of the United States. We used the Numerus Model Builder Data and Simulation Analysis (NMB-DASA) web application to fit the exponential phase of a SCLAIV+D (Susceptible, Contact, Latent, Asymptomatic infectious, symptomatic Infectious, Vaccinated, Dead) disease classes model to outbreaks, thereby allowing us to obtain an estimate of the basic reproductive number R0 for each CSA. Values of R0 ranged from 1.9 to 9.4, with a mean and standard deviation of 4.5±1.8. Fixing the parameters from the exponential fit, we again used NMB-DASA to estimate a set of social distancing behaviour parameters to compute an epidemic flattening index cflatten. Finally, we applied hierarchical clustering methods using this index to divide CSA outbreaks into two clusters: those presenting a social distancing response that was either weaker or stronger. We found cflatten to be more influential in the clustering process than R0. Thus, our results suggest that the behavioural response after a short initial exponential growth phase is likely to be more determinative of the rise of an epidemic than R0 itself.

Simulation applications to support teaching and research in epidemiological dynamics.

BACKGROUND: An understanding of epidemiological dynamics, once confined to mathematical epidemiologists and applied mathematicians, can be disseminated to a non-mathematical community of health care professionals and applied biologists through simple-to-use simulation applications. We used Numerus Model Builder RAMP Ⓡ (Runtime Alterable Model Platform) technology, to construct deterministic and stochastic versions of compartmental SIR (Susceptible, Infectious, Recovered with immunity) models as simple-to-use, freely available, epidemic simulation application programs. RESULTS: We take the reader through simulations used to demonstrate the following concepts: 1) disease prevalence curves of unmitigated outbreaks have a single peak and result in epidemics that 'burn' through the population to become extinguished when the proportion of the susceptible population drops below a critical level; 2) if immunity in recovered individuals wanes sufficiently fast then the disease persists indefinitely as an endemic state, with possible dampening oscillations following the initial outbreak phase; 3) the steepness and initial peak of the prevalence curve are influenced by the basic reproductive value R0, which must exceed 1 for an epidemic to occur; 4) the probability that a single infectious individual in a closed population (i.e. no migration) gives rise to an epidemic increases with the value of R0>1; 5) behavior that adaptively decreases the contact rate among individuals with increasing prevalence has major effects on the prevalence curve including dramatic flattening of the prevalence curve along with the generation of multiple prevalence peaks; 6) the impacts of treatment are complicated to model because they effect multiple processes including transmission, recovery and mortality; 7) the impacts of vaccination policies, constrained by a fixed number of vaccination regimens and by the rate and timing of delivery, are crucially important to maximizing the ability of vaccination programs to reduce mortality. CONCLUSION: Our presentation makes transparent the key assumptions underlying SIR epidemic models. Our RAMP simulators are meant to augment rather than replace classroom material when teaching epidemiological dynamics. They are sufficiently versatile to be used by students to address a range of research questions for term papers and even dissertations.

A framework for integrating inferred movement behavior into disease risk models.

Movement behavior is an important contributor to habitat selection and its incorporation in disease risk models has been somewhat neglected. The habitat preferences of host individuals affect their probability of exposure to pathogens. If preference behavior can be incorporated in ecological niche models (ENMs) when data on pathogen distributions are available, then variation in such behavior may dramatically impact exposure risk. Here we use data from the anthrax endemic system of Etosha National Park, Namibia, to demonstrate how integrating inferred movement behavior alters the construction of disease risk maps. We used a Maximum Entropy (MaxEnt) model that associated soil, bioclimatic, and vegetation variables with the best available pathogen presence data collected at anthrax carcass sites to map areas of most likely Bacillus anthracis (the causative bacterium of anthrax) persistence. We then used a hidden Markov model (HMM) to distinguish foraging and non-foraging behavioral states along the movement tracks of nine zebra (Equus quagga) during the 2009 and 2010 anthrax seasons. The resulting tracks, decomposed on the basis of the inferred behavioral state, formed the basis of step-selection functions (SSFs) that used the MaxEnt output as a potential predictor variable. Our analyses revealed different risks of exposure during different zebra behavioral states, which were obscured when the full movement tracks were analyzed without consideration of the underlying behavioral states of individuals. Pathogen (or vector) distribution models may be misleading with regard to the actual risk faced by host animal populations when specific behavioral states are not explicitly accounted for in selection analyses. To more accurately evaluate exposure risk, especially in the case of environmentally transmitted pathogens, selection functions could be built for each identified behavioral state and then used to assess the comparative exposure risk across relevant states. The scale of data collection and analysis, however, introduces complexities and limitations for consideration when interpreting results.

First detection of avian influenza subtype H4N6 in Israel in a wild mallard (Anas platyrhynchos).

Avian influenza viruses (AIV) are a worldwide threat to animal and human health. As wild waterfowl circulate and spread these viruses around the world, investigations of AIV prevalence in wild populations are critical for understanding pathogen transmission, as well as predicting disease outbreaks in domestic animals and humans. Surveillance efforts in this study have isolated H4N6 for the first time in Israel from a faecal sample of a wild mallard (Anas platyrhynchos). Phylogenetic analyses of the HA and NA genes revealed that this strain is closely related to isolates from Europe and Asia. This Eurasian origin, together with Israel serving as an important migratory bottleneck of the mid Palearctic-African flyway, suggests a potential introduction of this strain by migratory birds. Additional phylogenetic analysis of the isolate's internal genes (PB1, PB2, PA, NP, M and NS) revealed high levels of phylogenetic relatedness with other AIV subtypes, indicating previous reassortment events. High reassortment rates are characteristic for H4N6 viruses, which, together with this subtype's ability to infect pigs and adaptability to the human receptor binding domain, raises the concern that it would potentially become zoonotic in the future. These results emphasize the importance of continuous AIV monitoring in migratory birds.

A continent-wide high genetic load in African buffalo revealed by clines in the frequency of deleterious alleles, genetic hitchhiking and linkage disequilibrium.

A high genetic load can negatively affect population viability and increase susceptibility to diseases and other environmental stressors. Prior microsatellite studies of two African buffalo (Syncerus caffer) populations in South Africa indicated substantial genome-wide genetic load due to high-frequency occurrence of deleterious alleles. The occurrence of these alleles, which negatively affect male body condition and bovine tuberculosis resistance, throughout most of the buffalo's range were evaluated in this study. Using available microsatellite data (2-17 microsatellite loci) for 1676 animals from 34 localities (from 25°S to 5°N), we uncovered continent-wide frequency clines of microsatellite alleles associated with the aforementioned male traits. Frequencies decreased over a south-to-north latitude range (average per-locus Pearson r = -0.22). The frequency clines coincided with a multilocus-heterozygosity cline (adjusted R2 = 0.84), showing up to a 16% decrease in southern Africa compared to East Africa. Furthermore, continent-wide linkage disequilibrium (LD) at five linked locus pairs was detected, characterized by a high fraction of positive interlocus associations (0.66, 95% CI: 0.53, 0.77) between male-deleterious-trait-associated alleles. Our findings suggest continent-wide and genome-wide selection of male-deleterious alleles driven by an earlier observed sex-chromosomal meiotic drive system, resulting in frequency clines, reduced heterozygosity due to hitchhiking effects and extensive LD due to male-deleterious alleles co-occurring in haplotypes. The selection pressures involved must be high to prevent destruction of allele-frequency clines and haplotypes by LD decay. Since most buffalo populations are stable, these results indicate that natural mammal populations, depending on their genetic background, can withstand a high genetic load.

A runtime alterable epidemic model with genetic drift, waning immunity and vaccinations.

We present methods for building a Java Runtime-Alterable-Model Platform (RAMP) of complex dynamical systems. We illustrate our methods by building a multivariant SEIR (epidemic) RAMP. Underlying our RAMP is an individual-based model that includes adaptive contact rates, pathogen genetic drift, waning and cross-immunity. Besides allowing parameter values, process descriptions and scriptable runtime drivers to be easily modified during simulations, our RAMP can used within R-Studio and other computational platforms. Process descriptions that can be runtime altered within our SEIR RAMP include pathogen variant-dependent host shedding, environmental persistence, host transmission and within-host pathogen mutation and replication. They also include adaptive social distancing and adaptive application of vaccination rates and variant-valency of vaccines. We present simulation results using parameter values and process descriptions relevant to the current COVID-19 pandemic. Our results suggest that if waning immunity outpaces vaccination rates, then vaccination rollouts may fail to contain the most transmissible variants, particularly if vaccine valencies are not adapted to deal with escape mutations. Our SEIR RAMP is designed for easy use by others. More generally, our RAMP concept facilitates construction of highly flexible complex systems models of all types, which can then be easily shared as stand-alone application programs.

Modeling the population effects of escape mutations in SARS-CoV-2 to guide vaccination strategies.

SARS-Cov-2 escape mutations (EM) have been detected and are spreading. Vaccines may need adjustment to respond to these or future mutations. We designed a population level model integrating both waning immunity and EM. We also designed a set of criteria for elaborating and fitting this model to cross-neutralization and other data with a goal of minimizing vaccine decision errors. We formulated four related models. These differ regarding which strains can drift to escape immunity in the host when that immunity was elicited by different strains. Across changing waning and escape mutation parameter values, these model variations led to patterns where: 1) EM are rare in the first epidemic, 2) rebound outbreaks after the first outbreak are accelerated by increasing waning and by increasing drifting, 3) the long term endemic level of infection is determined mostly by waning rates with small effects of the drifting parameter, 4) EM caused loss of vaccine effectiveness, and under some conditions: vaccines induced EM that caused higher levels of infection with vaccines than without them. The differences and similarities across the four models suggest paths for developing models specifying the epitopes where EM act. This model provides a base on which to construct epitope specific evolutionary models using new high-throughput assay data from population samples to guide vaccine decisions.

Drivers of change and stability in the gut microbiota of an omnivorous avian migrant exposed to artificial food supplementation.

Human activities shape resources available to wild animals, impacting diet and probably altering their microbiota and overall health. We examined drivers shaping microbiota profiles of common cranes (Grus grus) in agricultural habitats by comparing gut microbiota and crane movement patterns (GPS-tracking) over three periods of their migratory cycle, and by analysing the effect of artificially supplemented food provided as part of a crane-agriculture management programme. We sampled faecal droppings in Russia (nonsupplemented, premigration) and in Israel in late autumn (nonsupplemented, postmigration) and winter (supplemented and nonsupplemented, wintering). As supplemented food is typically homogenous, we predicted lower microbiota diversity and different composition in birds relying on supplementary feeding. We did not observe changes in microbial diversity with food supplementation, as diversity differed only in samples from nonsupplemented wintering sites. However, both food supplementation and season affected bacterial community composition and led to increased abundance of specific genera (mostly Firmicutes). Cranes from the nonsupplemented groups spent most of their time in agricultural fields, probably feeding on residual grain when available, while food-supplemented cranes spent most of their time at the feeding station. Thus, nonsupplemented and food-supplemented diets probably diverge only in winter, when crop rotation and depletion of anthropogenic resources may lead to a more variable diet in nonsupplemented sites. Our results support the role of diet in structuring bacterial communities and show that they undergo both seasonal and human-induced shifts. Movement analyses provide important clues regarding host diet and behaviour towards understanding how human-induced changes shape the gut microbiota in wild animals.

Disease or drought: environmental fluctuations release zebra from a potential pathogen-triggered ecological trap.

When a transmission hotspot for an environmentally persistent pathogen establishes in otherwise high-quality habitat, the disease may exert a strong impact on a host population. However, fluctuating environmental conditions lead to heterogeneity in habitat quality and animal habitat preference, which may interrupt the overlap between selected and risky habitats. We evaluated spatio-temporal patterns in anthrax mortalities in a plains zebra (Equus quagga) population in Etosha National Park, Namibia, incorporating remote-sensing and host telemetry data. A higher proportion of anthrax mortalities of herbivores was detected in open habitats than in other habitat types. Resource selection functions showed that the zebra population shifted habitat selection in response to changes in rainfall and vegetation productivity. Average to high rainfall years supported larger anthrax outbreaks, with animals congregating in preferred open habitats, while a severe drought forced animals into otherwise less preferred habitats, leading to few anthrax mortalities. Thus, the timing of anthrax outbreaks was congruent with preference for open plains habitats and a corresponding increase in pathogen exposure. Given shifts in habitat preference, the overlap in high-quality habitat and high-risk habitat is intermittent, reducing the adverse consequences for the population.

Ensemble machine learning of factors influencing COVID-19 across US counties.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) the causal agent for COVID-19, is a communicable disease spread through close contact. It is known to disproportionately impact certain communities due to both biological susceptibility and inequitable exposure. In this study, we investigate the most important health, social, and environmental factors impacting the early phases (before July, 2020) of per capita COVID-19 transmission and per capita all-cause mortality in US counties. We aggregate county-level physical and mental health, environmental pollution, access to health care, demographic characteristics, vulnerable population scores, and other epidemiological data to create a large feature set to analyze per capita COVID-19 outcomes. Because of the high-dimensionality, multicollinearity, and unknown interactions of the data, we use ensemble machine learning and marginal prediction methods to identify the most salient factors associated with several COVID-19 outbreak measure. Our variable importance results show that measures of ethnicity, public transportation and preventable diseases are the strongest predictors for both per capita COVID-19 incidence and mortality. Specifically, the CDC measures for minority populations, CDC measures for limited English, and proportion of Black- and/or African-American individuals in a county were the most important features for per capita COVID-19 cases within a month after the pandemic started in a county and also at the latest date examined. For per capita all-cause mortality at day 100 and total to date, we find that public transportation use and proportion of Black- and/or African-American individuals in a county are the strongest predictors. The methods predict that, keeping all other factors fixed, a 10% increase in public transportation use, all other factors remaining fixed at the observed values, is associated with increases mortality at day 100 of 2012 individuals (95% CI [1972, 2356]) and likewise a 10% increase in the proportion of Black- and/or African-American individuals in a county is associated with increases total deaths at end of study of 2067 (95% CI [1189, 2654]). Using data until the end of study, the same metric suggests ethnicity has double the association as the next most important factors, which are location, disease prevalence, and transit factors. Our findings shed light on societal patterns that have been reported and experienced in the U.S. by using robust methods to understand the features most responsible for transmission and sectors of society most vulnerable to infection and mortality. In particular, our results provide evidence of the disproportionate impact of the COVID-19 pandemic on minority populations. Our results suggest that mitigation measures, including how vaccines are distributed, could have the greatest impact if they are given with priority to the highest risk communities.

Anthrax Surveillance and the Limited Overlap Between Obligate Scavengers and Endemic Anthrax Zones in the United States.

Anthrax is a zoonosis caused by the spore-forming bacterium Bacillus anthracis, with potential for high fatality rate, especially in herbivores. Upon host death, spores can enter the soil surrounding the carcass and be ingested by other animals feeding in the same location. Accordingly, surveillance to quickly identify and decontaminate anthrax carcasses is crucial to outbreak prevention. In endemic anthrax areas such as Texas and Africa, vultures are used as a surveillance tool for identifying presence and location of dead animals. However, many anthrax outbreaks in the United States have occurred in areas outside the ranges of both black and turkey vultures. Here, we used a longitudinal camera trap survey at carcass sites in southwestern Montana to investigate the utility of facultative avian scavengers on disease and carcass surveillance in a reemerging anthrax risk zone. From August 2016 to September 2018, camera traps at 11 carcass sites were triggered 1996 times by avian scavengers. While the majority were facultative avian scavengers such as corvids and eagles, our results suggest that facultative scavengers cannot replace vultures as a surveillance tool in this ecosystem due to their absence during the anthrax risk period (June to August), reduced search efficiency, or low flight patterns. We found that the conditions in Montana likely parallel systems elsewhere in the continental United States. Using ecological niche models of B. anthracis distribution overlaid with relative abundance maps of turkey vultures, we found that much of North Dakota, South Dakota, Minnesota, Wyoming, Nebraska, and Iowa have areas of anthrax risk, but low or absent turkey vulture populations. Without vultures in these areas, surveillance capacity is reduced, and it becomes more difficult to identify anthrax cases, meaning fewer carcasses are decontaminated, and consequently, outbreaks could become more frequent or severe.

A versatile web app for identifying the drivers of COVID-19 epidemics.

BACKGROUND: No versatile web app exists that allows epidemiologists and managers around the world to comprehensively analyze the impacts of COVID-19 mitigation. The http://covid-webapp.numerusinc.com/ web app presented here fills this gap. METHODS: Our web app uses a model that explicitly identifies susceptible, contact, latent, asymptomatic, symptomatic and recovered classes of individuals, and a parallel set of response classes, subject to lower pathogen-contact rates. The user inputs a CSV file of incidence and, if of interest, mortality rate data. A default set of parameters is available that can be overwritten through input or online entry, and a user-selected subset of these can be fitted to the model using maximum-likelihood estimation (MLE). Model fitting and forecasting intervals are specifiable and changes to parameters allow counterfactual and forecasting scenarios. Confidence or credible intervals can be generated using stochastic simulations, based on MLE values, or on an inputted CSV file containing Markov chain Monte Carlo (MCMC) estimates of one or more parameters. RESULTS: We illustrate the use of our web app in extracting social distancing, social relaxation, surveillance or virulence switching functions (i.e., time varying drivers) from the incidence and mortality rates of COVID-19 epidemics in Israel, South Africa, and England. The Israeli outbreak exhibits four distinct phases: initial outbreak, social distancing, social relaxation, and a second wave mitigation phase. An MCMC projection of this latter phase suggests the Israeli epidemic will continue to produce into late November an average of around 1500 new case per day, unless the population practices social-relaxation measures at least 5-fold below the level in August, which itself is 4-fold below the level at the start of July. Our analysis of the relatively late South African outbreak that became the world's fifth largest COVID-19 epidemic in July revealed that the decline through late July and early August was characterised by a social distancing driver operating at more than twice the per-capita applicable-disease-class (pc-adc) rate of the social relaxation driver. Our analysis of the relatively early English outbreak, identified a more than 2-fold improvement in surveillance over the course of the epidemic. It also identified a pc-adc social distancing rate in early August that, though nearly four times the pc-adc social relaxation rate, appeared to barely contain a second wave that would break out if social distancing was further relaxed. CONCLUSION: Our web app provides policy makers and health officers who have no epidemiological modelling or computer coding expertise with an invaluable tool for assessing the impacts of different outbreak mitigation policies and measures. This includes an ability to generate an epidemic-suppression or curve-flattening index that measures the intensity with which behavioural responses suppress or flatten the epidemic curve in the region under consideration.

Factors influencing scavenger guilds and scavenging efficiency in Southwestern Montana.

Scavenging of carrion shapes ecological landscapes by influencing scavenger population demography, increasing inter- and intra-specific interactions, and generating ecosystem services such as nutrient cycling and disease moderation. Previous research found the cues promoting, or the constraints limiting, an individual's propensity or ability to scavenge vary widely, depending on anthropogenic and environmental factors. Here we investigated differences in scavenging patterns in a complex scavenger guild in Southwestern Montana. We used camera traps established at 13 carcass sites to monitor carcass detection, visitation, and consumption times, during 2016-2018 and generalized linear models to explore the influence of carcass characteristics, habitat features, and seasonality, on carcass selection and scavenging efficiency. We found that scavenger species diversity was higher at higher elevations and in grassland habitats. Scavenging efficiency was influenced inter alia by seasonality, distance to water, and elevation. We found that most carcass consumption was via facultative scavengers (bears, wolves, magpies, Corvus spp.) rather than turkey vultures, the only obligate scavengers in the study area. However, growing populations of turkey vultures may lead to increased competition with facultative scavengers over carrion, and could have cascading effects on food webs in this ecosystem.