A comparison of wild boar and domestic pig microbiota does not reveal a loss of microbial species but an increase in alpha diversity and opportunistic genera in domestic pigs.

The microbiome of wild animals is believed to be co-evolved with host species, which may play an important role in host physiology. It has been hypothesized that the rigorous hygienic practices in combination with antibiotics and diets with simplified formulas used in the modern swine industry may negatively affect the establishment and development of the gut microbiome. In this study, we evaluated the fecal microbiome of 90 domestic pigs sampled from nine farms in Canada and 39 wild pigs sampled from three different locations on two continents (North America and Europe) using 16S rRNA gene amplicon sequencing. Surprisingly, the gut microbiome in domestic pigs exhibited higher alpha-diversity indices than wild pigs (P < 0.0001). The wild pig microbiome showed a lower Firmicutes-to-Bacteroidetes ratio and a higher presence of bacterial phyla Elusimicrobiota, Verrucomicrobiota, Cyanobacteria, and Fibrobacterota when compared to their domestic counterparts. At the genus level, the wild pig microbiome had enriched genera that were known for fiber degradation and short-chain fatty acid production. Interestingly, the phylum Fusobacteriota was only observed in domestic pigs. We identified 31 ASVs that were commonly found in the pig gut microbiome, regardless of host sources, which could be recognized as members of the core gut microbiome. Interestingly, we found five ASVs missing in domestic pigs that were prevalent in wild ones, whereas domestic pigs harbored 59 ASVs that were completely absent in wild pigs. The present study sheds light on the impact of domestication on the pig gut microbiome, including the gain of new genera, which might provide the basis to identify novel targets to manipulate the pig gut microbiome for improved health. IMPORTANCE: The microbiome of pigs plays a crucial role in shaping host physiology and health. This study sought to identify if domestication and current rearing practices have resulted in a loss of co-evolved bacterial species by comparing the microbiome of wild boar and conventionally raised pigs. It provides a comparison of domestic and wild pigs with the largest sample sizes and is the first to examine wild boars from multiple sites and continents. We were able to identify core microbiome members that were shared between wild and domestic populations, and on the contrary to expectation, few microbes were identified to be lost from wild boar. Nevertheless, the microbiome of wild boars had a lower abundance of important pathogenic genera and was distinct from domestic pigs. The differences in the microbial composition may identify an opportunity to shift the microbial community of domestic pigs towards that of wild boar with the intent to reduce pathogen load.

Characterizing feral swine movement across the contiguous United States using neural networks and genetic data.

Globalization has led to the frequent movement of species out of their native habitat. Some of these species become highly invasive and capable of profoundly altering invaded ecosystems. Feral swine (Sus scrofa × domesticus) are recognized as being among the most destructive invasive species, with populations established on all continents except Antarctica. Within the United States (US), feral swine are responsible for extensive crop damage, the destruction of native ecosystems, and the spread of disease. Purposeful human-mediated movement of feral swine has contributed to their rapid range expansion over the past 30 years. Patterns of deliberate introduction of feral swine have not been well described as populations may be established or augmented through small, undocumented releases. By leveraging an extensive genomic database of 18,789 samples genotyped at 35,141 single nucleotide polymorphisms (SNPs), we used deep neural networks to identify translocated feral swine across the contiguous US. We classified 20% (3364/16,774) of sampled animals as having been translocated and described general patterns of translocation using measures of centrality in a network analysis. These findings unveil extensive movement of feral swine well beyond their dispersal capabilities, including individuals with predicted origins >1000 km away from their sampling locations. Our study provides insight into the patterns of human-mediated movement of feral swine across the US and from Canada to the northern areas of the US. Further, our study validates the use of neural networks for studying the spread of invasive species.

Full wave function cloning for improving convergence of the multiconfigurational Ehrenfest method: Tests in the zero-temperature spin-boson model regime.

In this paper, we report a new algorithm for creating an adaptive basis set in the Multiconfigurational Ehrenfest (MCE) method, which is termed Full Cloning (FC), and test it together with the existing Multiple Cloning (MC) using the spin-boson model at zero-temperature as a benchmark. The zero-temperature spin-boson regime is a common hurdle in the development of methods that seek to model quantum dynamics. Two versions of MCE exist. We demonstrate that MC is vital for the convergence of MCE version 2 (MCEv2). The first version (MCEv1) converges much better than MCEv2, but FC improves its convergence in a few cases where it is hard to converge it with the help of a reasonably small size of the basis set.

Tracking the fecal mycobiome through the lifespan of production pigs and a comparison to the feral pig.

IMPORTANCE: This work provides evidence that early-life fungal community composition, or host genetics, influences long-term mycobiome composition. In addition, this work provides the first comparison of the feral pig mycobiome to the mycobiome of intensively raised pigs.

Unregulated Online Sales are High-Risk Sources of Domestic Swine (Sus scrofa) in Canada: Implications for Invasive Wild Pig and AfricanSwine Fever Risk Preparedness.

Free-ranging wild pig (Sus scrofa) populations may cause widespread environmental damage and transmit diseases at the wildlife-livestock interface. For example, African swine fever (ASF) is a highly contagious viral disease of pigs capable of causing catastrophic economic losses. Prevention and preparedness for ASF require understanding wild and domestic pig movements and distribution. We characterized a "grey" swine market and described the risks it poses, contributing to the threats associated with wild pig populations. We monitored www.kijiji.ca, a Canadian internet classified advertising service, for sales of domestic wild boar, pot-bellied pigs, other breeds, and their hybrids across Canada from 28 April to 30 June 2021. Data collected included seller-defined breed, age, sex, number for sale, sexual intactness, presence of identifying tags or tattoos, and the date and location of listings. Advertisement locations were mapped and compared with existing wild pig distributions, identifying areas new populations might be established, and existing populations supplemented or genetically diversified. We identified 151 advertisements on Kijiji: 34% (n=52/151) from Ontario, 29% (n=44/151) from Alberta, 41% (n=62/151) from existing wild pig populations, and 59% (n=89/151) from areas where wild pigs have not yet been identified. We propose requiring the use of individual animal identifiers (tags/tattoos), genetic analysis, and mandatory reporting for all pig sales in Canada to aid in ASF preparedness and to increase regulation and enforcement of the online swine market.

Understanding and strengthening wildlife and zoonotic disease policy processes: A research imperative.

The COVID-19 pandemic highlights the urgency and importance of monitoring, managing and addressing zoonotic diseases, and the acute challenges of doing so with sufficient inter-jurisdictional coordination in a dynamic global context. Although wildlife pathogens are well-studied clinically and ecologically, there is very little systematic scholarship on their management or on policy implications. The current global pandemic therefore presents a unique social science research imperative: to understand how decisions are made about preventing and responding to wildlife diseases, especially zoonoses, and how those policy processes can be improved as part of early warning systems, preparedness and rapid response. To meet these challenges, we recommend intensified research efforts towards: (i) generating functional insights about wildlife and zoonotic disease policy processes, (ii) enabling social and organizational learning to mobilize those insights, (iii) understanding epistemic instability to address populist anti-science and (iv) anticipating evolving and new zoonotic emergences, especially their human dimensions. Since policy processes for zoonoses can be acutely challenged during the early stages of an epidemic or pandemic, such insights can provide a pragmatic, empirically-based roadmap for enhancing their robustness and efficacy, and benefiting long-term decision-making efforts.

Enhancing inter-organizational collaboration for wildlife disease surveillance in Sri Lanka.

Management of zoonotic infectious diseases is an urgent global heath imperative. Interdisciplinary approaches for zoonosis management exist in literature, but collaboratively implementing them is a pervasive challenge. The Sri Lanka Wildlife Health Centre (SLWHC) was created in 2011 to coordinate wildlife disease surveillance and response among government agencies. We interviewed SLWHC-affiliated personnel about existing communication and collaboration channels to identify operational needs as well as potential enhancements for the SLWHC's operations. We used the Policy Sciences' analytical framework to identify opportunities and challenges for the SLWHC. Study participants held both human and animal health as the utmost priorities. However, their observations indicate that inter-organizational communication barriers and intra-organizational hierarchies still need to be overcome for the Centre's partnering organizations to collaborate to their fullest potential. Any interventions to enhance the SLWHC's collaborative capacity for detecting and managing zoonotic disease outbreaks could be strengthened by appealing to participants' shared value orientations towards enlightenment and respect. A common interest was the desire to collaborate and combine resources, knowledge and personnel to detect, reduce and prevent the incidence of zoonotic disease outbreaks in Sri Lanka. These lessons about institutionalizing communication have considerable relevance for organizational responses to the current SARS-CoV2 pandemic and other zoonoses.

Improving the accessibility and transferability of machine learning algorithms for identification of animals in camera trap images: MLWIC2.

Motion-activated wildlife cameras (or "camera traps") are frequently used to remotely and noninvasively observe animals. The vast number of images collected from camera trap projects has prompted some biologists to employ machine learning algorithms to automatically recognize species in these images, or at least filter-out images that do not contain animals. These approaches are often limited by model transferability, as a model trained to recognize species from one location might not work as well for the same species in different locations. Furthermore, these methods often require advanced computational skills, making them inaccessible to many biologists. We used 3 million camera trap images from 18 studies in 10 states across the United States of America to train two deep neural networks, one that recognizes 58 species, the "species model," and one that determines if an image is empty or if it contains an animal, the "empty-animal model." Our species model and empty-animal model had accuracies of 96.8% and 97.3%, respectively. Furthermore, the models performed well on some out-of-sample datasets, as the species model had 91% accuracy on species from Canada (accuracy range 36%-91% across all out-of-sample datasets) and the empty-animal model achieved an accuracy of 91%-94% on out-of-sample datasets from different continents. Our software addresses some of the limitations of using machine learning to classify images from camera traps. By including many species from several locations, our species model is potentially applicable to many camera trap studies in North America. We also found that our empty-animal model can facilitate removal of images without animals globally. We provide the trained models in an R package (MLWIC2: Machine Learning for Wildlife Image Classification in R), which contains Shiny Applications that allow scientists with minimal programming experience to use trained models and train new models in six neural network architectures with varying depths.

Indigenous community perspectives on dogs in Northern Canada after 10 years of veterinary services indicates improved animal and human welfare.

Access to veterinary services in marginalized communities has important implications for people and animals around the world. Subsidized veterinary services are occasionally provided, however, they are seldom evaluated for their value to stakeholders and overall animal health. In 2017, we evaluated a decade-long veterinary program in four remote communities in the Sahtu Settlement Area of the Northwest Territories, Canada to understand if there were changes in dog husbandry and community perceptions of, and experiences with, dogs since an initial assessment at the beginning of the program in 2008. Using questionnaires and a dog census, we found a significant increase over time in dog health indicators, including the proportion of dogs that had received preventive veterinary care and had been sterilized. We documented significant changes in the described purpose of dogs, husbandry practices, experiences with dogs, and attitudes towards dogs and veterinary services. In 2017, respondents commonly described their dog(s) as companions and as part of their family. However, communities differed in the way dogs were housed and fed and in their attitudes towards dogs and dog-related issues. These inter-community differences are noteworthy as they impact service provision, uptake, and evaluation and must be taken into consideration in order to develop effective programs. Regular program evaluations are critical to check in with stakeholders, to ensure the program is meeting community needs, and to optimize effective use of resources.

Correction: Publication reform to safeguard wildlife from researcher harm.

[This corrects the article DOI: 10.1371/journal.pbio.3000193.].

Predicting functional responses in agro-ecosystems from animal movement data to improve management of invasive pests.

Functional responses describe how changing resource availability affects consumer resource use, thus providing a mechanistic approach to prediction of the invasibility and potential damage of invasive alien species (IAS). However, functional responses can be context dependent, varying with resource characteristics and availability, consumer attributes, and environmental variables. Identifying context dependencies can allow invasion and damage risk to be predicted across different ecoregions. Understanding how ecological factors shape the functional response in agro-ecosystems can improve predictions of hotspots of highest impact and inform strategies to mitigate damage across locations with varying crop types and availability. We linked heterogeneous movement data across different agro-ecosystems to predict ecologically driven variability in the functional responses. We applied our approach to wild pigs (Sus scrofa), one of the most successful and detrimental IAS worldwide where agricultural resource depredation is an important driver of spread and establishment. We used continental-scale movement data within agro-ecosystems to quantify the functional response of agricultural resources relative to availability of crops and natural forage. We hypothesized that wild pigs would selectively use crops more often when natural forage resources were low. We also examined how individual attributes such as sex, crop type, and resource stimulus such as distance to crops altered the magnitude of the functional response. There was a strong agricultural functional response where crop use was an accelerating function of crop availability at low density (Type III) and was highly context dependent. As hypothesized, there was a reduced response of crop use with increasing crop availability when non-agricultural resources were more available, emphasizing that crop damage levels are likely to be highly heterogeneous depending on surrounding natural resources and temporal availability of crops. We found significant effects of crop type and sex, with males spending 20% more time and visiting crops 58% more often than females, and both sexes showing different functional responses depending on crop type. Our application demonstrates how commonly collected animal movement data can be used to understand context dependencies in resource use to improve our understanding of pest foraging behavior, with implications for prioritizing spatiotemporal hotspots of potential economic loss in agro-ecosystems.

Evaluating Cost-Effective Methods for Rapid and Repeatable National Scale Detection and Mapping of Invasive Species Spread.

Invasive species can spread rapidly at local and national scales, creating significant environmental and economic impacts. A central problem in mitigation efforts is identifying methods that can rapidly detect invasive species in a cost-effective and repeatable manner. This challenge is particularly acute for species that can spread over large areas (>1 million km2). Wild pigs (Sus scrofa) are one of the most prolific invasive mammals on Earth and cause extensive damage to agricultural crops, native ecosystems, and livestock, and are reservoirs of disease. They have spread from their native range in Eurasia and North Africa into large areas of Australia, Africa, South America, and North America. We show that the range of invasive wild pigs has increased exponentially in Canada over the last 27 years following initial and ongoing releases and escapes from domestic wild boar farms. The cumulative range of wild pigs across Canada is 777,783 km2, with the majority of wild pig distribution occurring in the Prairie Provinces. We evaluate eight different data collection and evaluation/validation methods for mapping invasive species over large areas, and assess their benefits and limitations. Our findings effectively map the spread of a highly invasive large mammal and demonstrate that management efforts should ideally rely on a set of complementary independent monitoring methods. Mapping and evaluating resulting species occurrences provide baseline maps against which future changes can be rapidly evaluated.

Publication reform to safeguard wildlife from researcher harm.

Despite abundant focus on responsible care of laboratory animals, we argue that inattention to the maltreatment of wildlife constitutes an ethical blind spot in contemporary animal research. We begin by reviewing significant shortcomings in legal and institutional oversight, arguing for the relatively rapid and transformational potential of editorial oversight at journals in preventing harm to vertebrates studied in the field and outside the direct supervision of institutions. Straightforward changes to animal care policies in journals, which our analysis of 206 journals suggests are either absent (34%), weak, incoherent, or neglected by researchers, could provide a practical, effective, and rapidly imposed safeguard against unnecessary suffering. The Animals in Research: Reporting On Wildlife (ARROW) guidelines we propose here, coupled with strong enforcement, could result in significant changes to how animals involved in wildlife research are treated. The research process would also benefit. Sound science requires animal subjects to be physically, physiologically, and behaviorally unharmed. Accordingly, publication of methods that contravenes animal welfare principles risks perpetuating inhumane approaches and bad science.

Spatio-temporal trends in crop damage inform recent climate-mediated expansion of a large boreal herbivore into an agro-ecosystem.

Large-scale climatic fluctuations have caused species range shifts. Moose (Alces alces) have expanded their range southward into agricultural areas previously not considered moose habitat. We found that moose expansion into agro-ecosystems is mediated by broad-scale climatic factors and access to high-quality forage (i.e., crops). We used crop damage records to quantify moose presence across the Canadian Prairies. We regressed latitude of crop damage against North Atlantic Oscillation (NAO) and crop area to test the hypotheses that NAO-mediated wetland recharge and occurrence of more nutritious crop types would result in more frequent occurrences of crop damage by moose at southerly latitudes. We examined local-scale land use by generating a habitat selection model to test our hypothesis that moose selected for areas of high crop cover in agro-ecosystems. We found that crop damage by moose occurred farther south during dry winters and in years with greater coverage of oilseeds. The results of our analyses support our hypothesis that moose movement into cropland is mediated by high-protein crops, but not by thermoregulatory habitat at the scale examined. We conclude that broad-scale climate combined with changing land-use regimes are causal factors in species' range shifts and are important considerations when studying changing animal distributions.

Fencing Large Predator-Free and Competitor-Free Landscapes for the Recovery of Woodland Caribou in Western Alberta: An Ineffective Conservation Option.

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Density-dependent habitat selection and partitioning between two sympatric ungulates.

Theory on density-dependent habitat selection predicts that as population density of a species increases, use of higher quality (primary) habitat by individuals declines while use of lower quality (secondary) habitat rises. Habitat partitioning is often considered the primary mechanism for coexistence between similar species, but how this process evolves with changes in population density remains to be empirically tested for free-ranging ungulates. We used resource-selection functions to quantify density effects on landscape-scale habitat selection of two sympatric species of ungulates [moose (Alces alces) and elk (Cervus canadensis manitobensis)] in Riding Mountain National Park, Manitoba, Canada (2000-2011). The density of elk was actively reduced from 1.2 to 0.4 elk km(-2) through increased hunting effort during the period of study, while moose density decreased without additional human influence from 1.6-0.7 moose km(-2). Patterns of habitat selection during winter by both species changed in accordance to expectations from density-dependent habitat-selection theory. At low intraspecific density, moose and elk did not partition habitat, as both species selected strongly for mixed forest (primary habitat providing both food and cover), but did so in different areas segregated across an elevational gradient. As intraspecific density increased, selection for primary habitat by both species decreased, while selection for secondary, lower quality habitat such as agricultural fields (for elk) and built-up areas (for moose) increased. We show that habitat-selection strategies during winter for moose and elk, and subsequent effects on habitat partitioning, depend heavily on the position in state space (density) of both species.

Impacts of wildlife baiting and supplemental feeding on infectious disease transmission risk: a synthesis of knowledge.

Baiting and supplemental feeding of wildlife are widespread, yet highly controversial management practices, with important implications for ecosystems, livestock production, and potentially human health. An often underappreciated threat of such feeding practices is the potential to facilitate intra- and inter-specific disease transmission. We provide a comprehensive review of the scientific evidence of baiting and supplemental feeding on disease transmission risk in wildlife, with an emphasis on large herbivores in North America. While the objectives of supplemental feeding and baiting typically differ, the effects on disease transmission of these practices are largely the same. Both feeding and baiting provide wildlife with natural or non-natural food at specific locations in the environment, which can result in large congregations of individuals and species in a small area and increased local densities. Feeding can lead to increased potential for disease transmission either directly (via direct animal contact) or indirectly (via feed functioning as a fomite, spreading disease into the adjacent environment and to other animals). We identified numerous diseases that currently pose a significant concern to the health of individuals and species of large wild mammals across North America, the spread of which are either clearly facilitated or most likely facilitated by the application of supplemental feeding or baiting. Wildlife diseases also have important threats to human and livestock health. Although the risk of intra- and inter-species disease transmission likely increases when animals concentrate at feeding stations, only in a few cases was disease prevalence and transmission measured and compared between populations. Mostly these were experimental situations under controlled conditions, limiting direct scientific evidence that feeding practices exacerbates disease occurrence, exposure, transmission, and spread in the environment. Vaccination programs utilizing baits have received variable levels of success. Although important gaps in the scientific literature exist, current information is sufficient to conclude that providing food to wildlife through supplemental feeding or baiting has great potential to negatively impact species health and represents a non-natural arena for disease transmission and preservation. Ultimately, this undermines the initial purpose of feeding practices and represents a serious risk to the maintenance of biodiversity, ecosystem functioning, human health, and livestock production. Managers should consider disease transmission as a real and serious concern in their decision to implement or eliminate feeding programs. Disease surveillance should be a crucial element within the long-term monitoring of any feeding program in combination with other available preventive measures to limit disease transmission and spread.

Targeting hunter distribution based on host resource selection and kill sites to manage disease risk.

Endemic and emerging diseases are rarely uniform in their spatial distribution or prevalence among cohorts of wildlife. Spatial models that quantify risk-driven differences in resource selection and hunter mortality of animals at fine spatial scales can assist disease management by identifying high-risk areas and individuals. We used resource selection functions (RSFs) and selection ratios (SRs) to quantify sex- and age-specific resource selection patterns of collared (n = 67) and hunter-killed (n = 796) nonmigratory elk (Cervus canadensis manitobensis) during the hunting season between 2002 and 2012, in southwestern Manitoba, Canada. Distance to protected area was the most important covariate influencing resource selection and hunter-kill sites of elk (AICw = 1.00). Collared adult males (which are most likely to be infected with bovine tuberculosis (Mycobacterium bovis) and chronic wasting disease) rarely selected for sites outside of parks during the hunting season in contrast to adult females and juvenile males. The RSFs showed selection by adult females and juvenile males to be negatively associated with landscape-level forest cover, high road density, and water cover, whereas hunter-kill sites of these cohorts were positively associated with landscape-level forest cover and increasing distance to streams and negatively associated with high road density. Local-level forest was positively associated with collared animal locations and hunter-kill sites; however, selection was stronger for collared juvenile males and hunter-killed adult females. In instances where disease infects a metapopulation and eradication is infeasible, a principle goal of management is to limit the spread of disease among infected animals. We map high-risk areas that are regularly used by potentially infectious hosts but currently underrepresented in the distribution of kill sites. We present a novel application of widely available data to target hunter distribution based on host resource selection and kill sites as a promising tool for applying selective hunting to the management of transmissible diseases in a game species.