Microbiome diversity and zoonotic bacterial pathogen prevalence in Peromyscus mice from agricultural landscapes and synanthropic habitat.

Rodents are key reservoirs of zoonotic pathogens and play an important role in disease transmission to humans. Importantly, anthropogenic land-use change has been found to increase the abundance of rodents that thrive in human-built environments (synanthropic rodents), particularly rodent reservoirs of zoonotic disease. Anthropogenic environments also affect the microbiome of synanthropic wildlife, influencing wildlife health and potentially introducing novel pathogens. Our objective was to examine the effect of agricultural development and synanthropic habitat on microbiome diversity and the prevalence of zoonotic bacterial pathogens in wild Peromyscus mice to better understand the role of these rodents in pathogen maintenance and transmission. We conducted 16S amplicon sequencing on faecal samples using long-read nanopore sequencing technology to characterize the rodent microbiome. We compared microbiome diversity and composition between forest and synanthropic habitats in agricultural and undeveloped landscapes and screened for putative pathogenic bacteria. Microbiome richness, diversity, and evenness were higher in the agricultural landscape and synanthropic habitat compared to undeveloped-forest habitat. Microbiome composition also differed significantly between agricultural and undeveloped landscapes and forest and synanthropic habitats. We detected overall low diversity and abundance of putative pathogenic bacteria, though putative pathogens were more likely to be found in mice from the agricultural landscape. Our findings show that landscape- and habitat-level anthropogenic factors affect Peromyscus microbiomes and suggest that landscape-level agricultural development may be important to predict zoonotic pathogen prevalence. Ultimately, understanding how anthropogenic land-use change and synanthropy affect rodent microbiomes and pathogen prevalence is important to managing transmission of rodent-borne zoonotic diseases to humans.

Effects of food supplementation and helminth removal on space use and spatial overlap in wild rodent populations.

Animal space use and spatial overlap can have important consequences for population-level processes such as social interactions and pathogen transmission. Identifying how environmental variability and inter-individual variation affect spatial patterns and in turn influence interactions in animal populations is a priority for the study of animal behaviour and disease ecology. Environmental food availability and macroparasite infection are common drivers of variation, but there are few experimental studies investigating how they affect spatial patterns of wildlife. Bank voles (Clethrionomys glareolus) are a tractable study system to investigate spatial patterns of wildlife and are amenable to experimental manipulations. We conducted a replicated, factorial field experiment in which we provided supplementary food and removed helminths in vole populations in natural forest habitat and monitored vole space use and spatial overlap using capture-mark-recapture methods. Using network analysis, we quantified vole space use and spatial overlap. We compared the effects of food supplementation and helminth removal and investigated the impacts of season, sex and reproductive status on space use and spatial overlap. We found that food supplementation decreased vole space use while helminth removal increased space use. Space use also varied by sex, reproductive status and season. Spatial overlap was similar between treatments despite up to threefold differences in population size. By quantifying the spatial effects of food availability and macroparasite infection on wildlife populations, we demonstrate the potential for space use and population density to trade-off and maintain consistent spatial overlap in wildlife populations. This has important implications for spatial processes in wildlife including pathogen transmission.

Modeling the risk of aquatic species invasion spread through boater movements and river connections.

Aquatic invasive species (AIS) are one of the greatest threats to the functioning of aquatic ecosystems worldwide. Once an invasive species has been introduced to a new region, many governments develop management strategies to reduce further spread. Nevertheless, managing AIS in a new region is challenging because of the vast areas that need protection and limited resources. Spatial heterogeneity in invasion risk is driven by environmental suitability and propagule pressure, which can be used to prioritize locations for surveillance and intervention activities. To better understand invasion risk across aquatic landscapes, we developed a simulation model to estimate the likelihood of a waterbody becoming invaded with an AIS. The model included waterbodies connected via a multilayer network that included boater movements and hydrological connections. In a case study of Minnesota, we used zebra mussels (Dreissena polymorpha) and starry stonewort (Nitellopsis obtusa) as model species. We simulated the impacts of management scenarios developed by stakeholders and created a decision-support tool available through an online application provided as part of the AIS Explorer dashboard. Our baseline model revealed that 89% of new zebra mussel invasions and 84% of new starry stonewort invasions occurred through boater movements, establishing it as a primary pathway of spread and offering insights beyond risk estimates generated by traditional environmental suitability models alone. Our results highlight the critical role of interventions applied to boater movements to reduce AIS dispersal.

Modelo del riesgo de la invasión de especies acuáticas dispersadas por movimiento de botes y conexiones entre ríos Resumen Las especies acuáticas invasoras (EAI) son una de las principales amenazas para el funcionamiento de los ecosistemas acuáticos a nivel mundial. Una vez que una especie invasora ha sido introducida a una nueva región, muchos gobiernos desarrollan estrategias de manejo para disminuir la dispersión. Sin embargo, el manejo de las especies acuáticas invasoras en una nueva región se complica debido a las amplias áreas que necesitan protección y los recursos limitados. La heterogeneidad espacial de un riesgo de invasión es causada por la idoneidad ambiental y la presión de propágulo, que puede usarse para priorizar la ubicación de las actividades de vigilancia e intervención. Desarrollamos una simulación para estimar la probabilidad de que un cuerpo de agua sea invadido por EAI para tener un mejor entendimiento del riesgo de invasión en los paisajes acuáticos. El modelo incluyó cuencas conectadas a través de una red multicapa que incluía movimiento de botes y conexiones hidrológicas. Usamos como especies modelo a Dreissena polymorpha y a Nitellopsis obtusa en un estudio de caso en Minnesota. Simulamos el impacto de los escenarios de manejo desarrollado por los actores y creamos una herramienta de decisiones por medio de una aplicación en línea proporcionada como parte del tablero del Explorer de EAI. Nuestro modelo de línea base reveló que el 89% de las invasiones nuevas de D. polymorpha y el 84% de las de N. obtusa ocurrieron debido al movimiento de los botes, lo que lo estableció como una vía primaria de dispersión y nos proporcionó información más allá de las estimaciones de riesgo generadas por los modelos tradicionales de idoneidad ambiental. Nuestros resultados resaltan el papel crítico de las intervenciones aplicadas al movimiento de los botes para reducir la dispersión de especies acuáticas invasoras.

The spectral underpinnings of pathogen spread on animal networks.

Predicting what factors promote or protect populations from infectious disease is a fundamental epidemiological challenge. Social networks, where nodes represent hosts and edges represent direct or indirect contacts between them, are important in quantifying these aspects of infectious disease dynamics. However, how network structure and epidemic parameters interact in empirical networks to promote or protect animal populations from infectious disease remains a challenge. Here we draw on advances in spectral graph theory and machine learning to build predictive models of pathogen spread on a large collection of empirical networks from across the animal kingdom. We show that the spectral features of an animal network are powerful predictors of pathogen spread for a variety of hosts and pathogens and can be a valuable proxy for the vulnerability of animal networks to pathogen spread. We validate our findings using interpretable machine learning techniques and provide a flexible web application for animal health practitioners to assess the vulnerability of a particular network to pathogen spread.

Defining an epidemiological landscape that connects movement ecology to pathogen transmission and pace-of-life.

Pathogen transmission depends on host density, mobility and contact. These components emerge from host and pathogen movements that themselves arise through interactions with the surrounding environment. The environment, the emergent host and pathogen movements, and the subsequent patterns of density, mobility and contact form an 'epidemiological landscape' connecting the environment to specific locations where transmissions occur. Conventionally, the epidemiological landscape has been described in terms of the geographical coordinates where hosts or pathogens are located. We advocate for an alternative approach that relates those locations to attributes of the local environment. Environmental descriptions can strengthen epidemiological forecasts by allowing for predictions even when local geographical data are not available. Environmental predictions are more accessible than ever thanks to new tools from movement ecology, and we introduce a 'movement-pathogen pace of life' heuristic to help identify aspects of movement that have the most influence on spatial epidemiology. By linking pathogen transmission directly to the environment, the epidemiological landscape offers an efficient path for using environmental information to inform models describing when and where transmission will occur.

Parasites as conservation tools.

Parasite success typically depends on a close relationship with one or more hosts; therefore, attributes of parasitic infection have the potential to provide indirect details of host natural history and are biologically relevant to animal conservation. Characterization of parasite infections has been useful in delineating host populations and has served as a proxy for assessment of environmental quality. In other cases, the utility of parasites is just being explored, for example, as indicators of host connectivity. Innovative studies of parasite biology can provide information to manage major conservation threats by using parasite assemblage, prevalence, or genetic data to provide insights into the host. Overexploitation, habitat loss and fragmentation, invasive species, and climate change are major threats to animal conservation, and all of these can be informed by parasites.

Los Parásitos como Herramienta de Conservación Resumen El éxito de los parásitos depende típicamente de la relación cercana con uno o más hospederos; por lo tanto, las características de la infección parasitaria tienen potencial para proporcionar detalles indirectos de la historia natural del hospedero y son biológicamente relevantes para la conservación animal. La caracterización de las infecciones parasitarias ha sido útil para definir a las poblaciones hospederas y ha servido como sustituto para la evaluación de la calidad ambiental. Los estudios innovadores de la biología de parásitos pueden proporcionar información para manejar las principales amenazas a la conservación mediante la información proporcionada por el conjunto de parásitos, su prevalencia o genética que proporciona conocimiento sobre el hospedero. La sobreexplotación, la pérdida del hábitat y la fragmentación, las especies invasoras y el cambio climático son las principales amenazas para la conservación animal y a todas pueden ser informadas mediante los parásitos.

Comparison of Antimicrobial-Resistant Escherichia coli Isolates from Urban Raccoons and Domestic Dogs.

Wildlife can be exposed to antimicrobial-resistant bacteria (ARB) via multiple pathways. Spatial overlap with domestic animals is a prominent exposure pathway. However, most studies of wildlife-domestic animal interfaces have focused on livestock and little is known about the wildlife-companion animal interface. Here, we investigated the prevalence and phylogenetic relatedness of extended-spectrum cephalosporin-resistant (ESC-R) Escherichia coli from raccoons (Procyon lotor) and domestic dogs (Canis lupus familiaris) in the metropolitan area of Chicago, IL, USA. To assess the potential importance of spatial overlap with dogs, we explored whether raccoons sampled at public parks (i.e., parks where people and dogs could enter) differed in prevalence and phylogenetic relatedness of ESC-R E. coli to raccoons sampled at private parks (i.e., parks where people and dogs could not enter). Raccoons had a significantly higher prevalence of ESC-R E. coli (56.9%) than dogs (16.5%). However, the richness of ESC-R E. coli did not vary by host species. Further, core single-nucleotide polymorphism (SNP)-based phylogenetic analyses revealed that isolates did not cluster by host species, and in some cases displayed a high degree of similarity (i.e., differed by less than 20 core SNPs). Spatial overlap analyses revealed that ESC-R E. coli were more likely to be isolated from raccoons at public parks than raccoons at private parks, but only for parks located in suburban areas of Chicago, not urban areas. That said, ESC-R E. coli isolated from raccoons did not genetically cluster by park of origin. Our findings suggest that domestic dogs and urban/suburban raccoons can have a diverse range of ARB, some of which display a high degree of genetic relatedness (i.e., differ by less than 20 core SNPs). Given the differences in prevalence, domestic dogs are unlikely to be an important source of exposure for mesocarnivores in urbanized areas. IMPORTANCE Antimicrobial-resistant bacteria (ARB) have been detected in numerous wildlife species across the globe, which may have important implications for human and animal health. Wildlife can be exposed to ARB via numerous pathways, including via spatial overlap with domestic animals. However, the interface with domestic animals has mostly been explored for livestock and little is known about the interface between wild animals and companion animals. Our work suggests that urban and suburban wildlife can have similar ARB to local domestic dogs, but local dogs are unlikely to be a direct source of exposure for urban-adapted wildlife. This finding is important because it underscores the need to incorporate wildlife into antimicrobial resistance surveillance efforts, and to investigate whether certain urban wildlife species could act as additional epidemiological pathways of exposure for companion animals, and indirectly for humans.

A mechanistic, stigmergy model of territory formation in solitary animals: Territorial behavior can dampen disease prevalence but increase persistence.

Although movement ecology has leveraged models of home range formation to explore the effects of spatial heterogeneity and social cues on movement behavior, disease ecology has yet to integrate these potential drivers and mechanisms of contact behavior into a generalizable disease modeling framework. Here we ask how dynamic territory formation and maintenance might contribute to disease dynamics in a territorial, solitary predator for an indirectly transmitted pathogen. We developed a mechanistic individual-based model where stigmergy-the deposition of signals into the environment (e.g., scent marking, scraping)-dictates local movement choices and long-term territory formation, but also the risk of pathogen transmission. Based on a variable importance analysis, the length of the infectious period was the single most important variable in predicting outbreak success, maximum prevalence, and outbreak duration. Host density and rate of pathogen decay were also key predictors. We found that territoriality best reduced maximum prevalence in conditions where we would otherwise expect outbreaks to be most successful: slower recovery rates (i.e., longer infectious periods) and higher conspecific densities. However, for slower pathogen decay rates, stigmergy-driven movement increased outbreak durations relative to random movement simulations. Our findings therefore support a limited version of the "territoriality benefits" hypothesis-where reduced home range overlap leads to reduced opportunities for pathogen transmission, but with the caveat that reduction in outbreak severity may increase the likelihood of pathogen persistence. For longer infectious periods and higher host densities, key trade-offs emerged between the strength of pathogen load, the strength of the stigmergy cue, and the rate at which those two quantities decayed; this finding raises interesting questions about the evolutionary nature of these competing processes and the role of possible feedbacks between parasitism and territoriality. This work also highlights the importance of considering social cues as part of the movement landscape in order to better understand the consequences of individual behaviors on population level outcomes.

Group density, disease, and season shape territory size and overlap of social carnivores.

The spatial organization of a population can influence the spread of information, behaviour and pathogens. Group territory size and territory overlap and components of spatial organization, provide key information as these metrics may be indicators of habitat quality, resource dispersion, contact rates and environmental risk (e.g. indirectly transmitted pathogens). Furthermore, sociality and behaviour can also shape space use, and subsequently, how space use and habitat quality together impact demography. Our study aims to identify factors shaping the spatial organization of wildlife populations and assess the impact of epizootics on space use. We further aim to explore the mechanisms by which disease perturbations could cause changes in spatial organization. Here we assessed the seasonal spatial organization of Serengeti lions and Yellowstone wolves at the group level. We use network analysis to describe spatial organization and connectivity of social groups. We then examine the factors predicting mean territory size and mean territory overlap for each population using generalized additive models. We demonstrate that lions and wolves were similar in that group-level factors, such as number of groups and shaped spatial organization more than population-level factors, such as population density. Factors shaping territory size were slightly different than factors shaping territory overlap; for example, wolf pack size was an important predictor of territory overlap, but not territory size. Lion spatial networks were more highly connected, while wolf spatial networks varied seasonally. We found that resource dispersion may be more important for driving territory size and overlap for wolves than for lions. Additionally, canine distemper epizootics may have altered lion spatial organization, highlighting the importance of including infectious disease epizootics in studies of behavioural and movement ecology. We provide insight about when we might expect to observe the impacts of resource dispersion, disease perturbations, and other ecological factors on spatial organization. Our work highlights the importance of monitoring and managing social carnivore populations at the group level. Future research should elucidate the complex relationships between demographics, social and spatial structure, abiotic and biotic conditions and pathogen infections.

Bidirectional interactions between host social behaviour and parasites arise through ecological and evolutionary processes.

An animal's social behaviour both influences and changes in response to its parasites. Here we consider these bidirectional links between host social behaviours and parasite infection, both those that occur from ecological vs evolutionary processes. First, we review how social behaviours of individuals and groups influence ecological patterns of parasite transmission. We then discuss how parasite infection, in turn, can alter host social interactions by changing the behaviour of both infected and uninfected individuals. Together, these ecological feedbacks between social behaviour and parasite infection can result in important epidemiological consequences. Next, we consider the ways in which host social behaviours evolve in response to parasites, highlighting constraints that arise from the need for hosts to maintain benefits of sociality while minimizing fitness costs of parasites. Finally, we consider how host social behaviours shape the population genetic structure of parasites and the evolution of key parasite traits, such as virulence. Overall, these bidirectional relationships between host social behaviours and parasites are an important yet often underappreciated component of population-level disease dynamics and host-parasite coevolution.

Disease outbreak thresholds emerge from interactions between movement behavior, landscape structure, and epidemiology.

Disease models have provided conflicting evidence as to whether spatial heterogeneity promotes or impedes pathogen persistence. Moreover, there has been limited theoretical investigation into how animal movement behavior interacts with the spatial organization of resources (e.g., clustered, random, uniform) across a landscape to affect infectious disease dynamics. Importantly, spatial heterogeneity of resources can sometimes lead to nonlinear or counterintuitive outcomes depending on the host and pathogen system. There is a clear need to develop a general theoretical framework that could be used to create testable predictions for specific host-pathogen systems. Here, we develop an individual-based model integrated with movement ecology approaches to investigate how host movement behaviors interact with landscape heterogeneity (in the form of various levels of resource abundance and clustering) to affect pathogen dynamics. For most of the parameter space, our results support the counterintuitive idea that fragmentation promotes pathogen persistence, but this finding was largely dependent on perceptual range of the host, conspecific density, and recovery rate. For simulations with high conspecific density, slower recovery rates, and larger perceptual ranges, more complex disease dynamics emerged, and the most fragmented landscapes were not necessarily the most conducive to outbreaks or pathogen persistence. These results point to the importance of interactions between landscape structure, individual movement behavior, and pathogen transmission for predicting and understanding disease dynamics.

Investigating the Dynamics of Elk Population Size and Body Mass in a Seasonal Environment Using a Mechanistic Integral Projection Model.

Environmentally mediated changes in body size often underlie population responses to environmental change, yet this is not a universal phenomenon. Understanding when phenotypic change underlies population responses to environmental change is important for obtaining insights and robust predictions of population dynamics in a changing world. We develop a dynamic integral projection model that mechanistically links environmental conditions to demographic rates and phenotypic traits (body size) via changes in resource availability and individual energetics. We apply the model to the northern Yellowstone elk population and explore population responses to changing patterns of seasonality, incorporating the interdependence of growth, demography, and density-dependent processes operating through population feedback on available resources. We found that small changes in body size distributions can have large impacts on population dynamics but need not cause population responses to environmental change. Environmental changes that altered demographic rates directly, via increasing or decreasing resource availability, led to large population impacts in the absence of substantial changes to body size distributions. In contrast, environmentally driven shifts in body size distributions could occur with little consequence for population dynamics when the effect of environmental change on resource availability was small and seasonally restricted and when strong density-dependent processes counteracted expected population responses. These findings highlight that a robust understanding of how associations between body size and demography influence population responses to environmental change will require knowledge of the shape of the relationship between phenotypic distributions and vital rates, the population status with regard to its carrying capacity, and importantly the nature of the environmentally driven change in body size and carrying capacity.

Genotype and sex-based host variation in behaviour and susceptibility drives population disease dynamics.

Host heterogeneity in pathogen transmission is widespread and presents a major hurdle to predicting and minimizing disease outbreaks. Using Drosophila melanogaster infected with Drosophila C virus as a model system, we integrated experimental measurements of social aggregation, virus shedding, and disease-induced mortality from different genetic lines and sexes into a disease modelling framework. The experimentally measured host heterogeneity produced substantial differences in simulated disease outbreaks, providing evidence for genetic and sex-specific effects on disease dynamics at a population level. While this was true for homogeneous populations of single sex/genetic line, the genetic background or sex of the index case did not alter outbreak dynamics in simulated, heterogeneous populations. Finally, to explore the relative effects of social aggregation, viral shedding and mortality, we compared simulations where we allowed these traits to vary, as measured experimentally, to simulations where we constrained variation in these traits to the population mean. In this context, variation in infectiousness, followed by social aggregation, was the most influential component of transmission. Overall, we show that host heterogeneity in three host traits dramatically affects population-level transmission, but the relative impact of this variation depends on both the susceptible population diversity and the distribution of population-level variation.

Cross-species transmission and evolutionary dynamics of canine distemper virus during a spillover in African lions of Serengeti National Park.

The outcome of pathogen spillover from a reservoir to a novel host population can range from a "dead-end" when there is no onward transmission in the recipient population, to epidemic spread and even establishment in new hosts. Understanding the evolutionary epidemiology of spillover events leading to discrete outcomes in novel hosts is key to predicting risk and can lead to a better understanding of the mechanisms of emergence. Here we use a Bayesian phylodynamic approach to examine cross-species transmission and evolutionary dynamics during a canine distemper virus (CDV) spillover event causing clinical disease and population decline in an African lion population (Panthera leo) in the Serengeti Ecological Region between 1993 and 1994. Using 21 near-complete viral genomes from four species we found that this large-scale outbreak was likely  ignited by a single cross-species spillover event from a canid reservoir to noncanid hosts <1 year before disease detection and explosive spread of CDV in lions. Cross-species transmission from other noncanid species probably fuelled the high prevalence of CDV across spatially structured lion prides. Multiple lines of evidence suggest that spotted hyenas (Crocuta crocuta) could have acted as the proximate source of CDV exposure in lions. We report 13 nucleotide substitutions segregating CDV strains found in canids and noncanids. Our results are consistent with the hypothesis that virus evolution played a role in CDV emergence in noncanid hosts following spillover during the outbreak, suggest that host barriers to clinical infection can limit outcomes of CDV spillover in novel host species.

Microbial associations and spatial proximity predict North American moose (Alces alces) gastrointestinal community composition.

Microbial communities are increasingly recognized as crucial for animal health. However, our understanding of how microbial communities are structured across wildlife populations is poor. Mechanisms such as interspecific associations are important in structuring free-living communities, but we still lack an understanding of how important interspecific associations are in structuring gut microbial communities in comparison with other factors such as host characteristics or spatial proximity of hosts. Here, we ask how gut microbial communities are structured in a population of North American moose Alces alces. We identify key microbial interspecific associations within the moose gut and quantify how important they are relative to key host characteristics, such as body condition, for predicting microbial community composition. We sampled gut microbial communities from 55 moose in a population experiencing decline due to a myriad of factors, including pathogens and malnutrition. We examined microbial community dynamics in this population utilizing novel graphical network models that can explicitly incorporate spatial information. We found that interspecific associations were the most important mechanism structuring gut microbial communities in moose and detected both positive and negative associations. Models only accounting for associations between microbes had higher predictive value compared to models including moose sex, evidence of previous pathogen exposure or body condition. Adding spatial information on moose location further strengthened our model and allowed us to predict microbe occurrences with ~90% accuracy. Collectively, our results suggest that microbial interspecific associations coupled with host spatial proximity are vital in shaping gut microbial communities in a large herbivore. In this case, previous pathogen exposure and moose body condition were not as important in predicting gut microbial community composition. The approach applied here can be used to quantify interspecific associations and gain a more nuanced understanding of the spatial and host factors shaping microbial communities in non-model hosts.

Endemic infection can shape exposure to novel pathogens: Pathogen co-occurrence networks in the Serengeti lions.

Pathogens are embedded in a complex network of microparasites that can collectively or individually alter disease dynamics and outcomes. Endemic pathogens that infect an individual in the first years of life, for example, can either facilitate or compete with subsequent pathogens thereby exacerbating or ameliorating morbidity and mortality. Pathogen associations are ubiquitous but poorly understood, particularly in wild populations. We report here on 10 years of serological and molecular data in African lions, leveraging comprehensive demographic and behavioural data to test if endemic pathogens shape subsequent infection by epidemic pathogens. We combine network and community ecology approaches to assess broad network structure and characterise associations between pathogens across spatial and temporal scales. We found significant non-random structure in the lion-pathogen co-occurrence network and identified both positive and negative associations between endemic and epidemic pathogens. Our results provide novel insights on the complex associations underlying pathogen co-occurrence networks.

Transmission ecology of canine parvovirus in a multi-host, multi-pathogen system.

Understanding multi-host pathogen maintenance and transmission dynamics is critical for disease control. However, transmission dynamics remain enigmatic largely because they are difficult to observe directly, particularly in wildlife. Here, we investigate the transmission dynamics of canine parvovirus (CPV) using state-space modelling of 20 years of CPV serology data from domestic dogs and African lions in the Serengeti ecosystem. We show that, although vaccination reduces the probability of infection in dogs, and despite indirect enhancement of population seropositivity as a result of vaccine shedding, the vaccination coverage achieved has been insufficient to prevent CPV from becoming widespread. CPV is maintained by the dog population and has become endemic with approximately 3.5-year cycles and prevalence reaching approximately 80%. While the estimated prevalence in lions is lower, peaks of infection consistently follow those in dogs. Dogs exposed to CPV are also more likely to become infected with a second multi-host pathogen, canine distemper virus. However, vaccination can weaken this coupling, raising questions about the value of monovalent versus polyvalent vaccines against these two pathogens. Our findings highlight the need to consider both pathogen- and host-level community interactions when seeking to understand the dynamics of multi-host pathogens and their implications for conservation, disease surveillance and control programmes.

Urbanization impacts apex predator gene flow but not genetic diversity across an urban-rural divide.

Apex predators are important indicators of intact natural ecosystems. They are also sensitive to urbanization because they require broad home ranges and extensive contiguous habitat to support their prey base. Pumas (Puma concolor) can persist near human developed areas, but urbanization may be detrimental to their movement ecology, population structure, and genetic diversity. To investigate potential effects of urbanization in population connectivity of pumas, we performed a landscape genomics study of 130 pumas on the rural Western Slope and more urbanized Front Range of Colorado, USA. Over 12,000 single nucleotide polymorphisms (SNPs) were genotyped using double-digest, restriction site-associated DNA sequencing (ddRADseq). We investigated patterns of gene flow and genetic diversity, and tested for correlations between key landscape variables and genetic distance to assess the effects of urbanization and other landscape factors on gene flow. Levels of genetic diversity were similar for the Western Slope and Front Range, but effective population sizes were smaller, genetic distances were higher, and there was more admixture in the more urbanized Front Range. Forest cover was strongly positively associated with puma gene flow on the Western Slope, while impervious surfaces restricted gene flow and more open, natural habitats enhanced gene flow on the Front Range. Landscape genomic analyses revealed differences in puma movement and gene flow patterns in rural versus urban settings. Our results highlight the utility of dense, genome-scale markers to document subtle impacts of urbanization on a wide-ranging carnivore living near a large urban center.

"One Health" or Three? Publication Silos Among the One Health Disciplines.

The One Health initiative is a global effort fostering interdisciplinary collaborations to address challenges in human, animal, and environmental health. While One Health has received considerable press, its benefits remain unclear because its effects have not been quantitatively described. We systematically surveyed the published literature and used social network analysis to measure interdisciplinarity in One Health studies constructing dynamic pathogen transmission models. The number of publications fulfilling our search criteria increased by 14.6% per year, which is faster than growth rates for life sciences as a whole and for most biology subdisciplines. Surveyed publications clustered into three communities: one used by ecologists, one used by veterinarians, and a third diverse-authorship community used by population biologists, mathematicians, epidemiologists, and experts in human health. Overlap between these communities increased through time in terms of author number, diversity of co-author affiliations, and diversity of citations. However, communities continue to differ in the systems studied, questions asked, and methods employed. While the infectious disease research community has made significant progress toward integrating its participating disciplines, some segregation--especially along the veterinary/ecological research interface--remains.

Host migration strategy is shaped by forms of parasite transmission and infection cost.

Most studies on the evolution of migration focus on food, mates and/or climate as factors influencing these movements, whereas negative species interactions such as predators, parasites and pathogens are often ignored. Although infection and its associated costs clearly have the potential to influence migration, thoroughly studying these interactions is challenging without a solid theoretical framework from which to develop testable predictions in natural systems. Here, we aim to understand when parasites favour the evolution of migration. We develop a general model which enables us to explore a broad range of biological conditions and to capture population and infection dynamics over both ecological and evolutionary time-scales. We show that when migration evolves depends on whether the costs of migration and infection are paid in reduced fecundity or survival. Also important are the parasite transmission mode and spatiotemporal dynamics of infection and recovery (if it occurs). Finally, we find that partial migration (where only a fraction of the population migrates) can evolve but only when parasite transmission is density-dependent. Our results highlight the critical, if overlooked, role of parasites in shaping long-distance movement patterns, and suggest that infection should be considered alongside more traditional drivers of migration in both empirical and theoretical studies.