A cyst-forming coccidian with large geographical range infecting forest and commensal rodents: Sarcocystis muricoelognathis sp. nov.

BACKGROUND: The geographic distribution and host-parasite interaction networks of Sarcocystis spp. in small mammals in eastern Asia remain incompletely known. METHODS: Experimental infections, morphological and molecular characterizations were used for discrimination of a new Sarcocystis species isolated from colubrid snakes and small mammals collected in Thailand, Borneo and China. RESULTS: We identified a new species, Sarcocystis muricoelognathis sp. nov., that features a relatively wide geographic distribution and infects both commensal and forest-inhabiting intermediate hosts. Sarcocystis sporocysts collected from rat snakes (Coelognathus radiatus, C. flavolineatus) in Thailand induced development of sarcocysts in experimental SD rats showing a type 10a cyst wall ultrastructure that was identical with those found in Rattus norvegicus from China and the forest rat Maxomys whiteheadi in Borneo. Its cystozoites had equal sizes in all intermediate hosts and locations, while sporocysts and cystozoites were distinct from other Sarcocystis species. Partial 28S rRNA sequences of S. muricoelognathis from M. whiteheadi were largely identical to those from R. norvegicus in China but distinct from newly sequenced Sarcocystis zuoi. The phylogeny of the nuclear 18S rRNA gene placed S. muricoelognathis within the so-called S. zuoi complex, including Sarcocystis attenuati, S. kani, S. scandentiborneensis and S. zuoi, while the latter clustered with the new species. However, the phylogeny of the ITS1-region confirmed the distinction between S. muricoelognathis and S. zuoi. Moreover, all three gene trees suggested that an isolate previously addressed as S. zuoi from Thailand (KU341120) is conspecific with S. muricoelognathis. Partial mitochondrial cox1 sequences of S. muricoelognathis were almost identical with those from other members of the group suggesting a shared, recent ancestry. Additionally, we isolated two partial 28S rRNA Sarcocystis sequences from Low's squirrel Sundasciurus lowii that clustered with those of S. scandentiborneensis from treeshews. CONCLUSIONS: Our results provide strong evidence of broad geographic distributions of rodent-associated Sarcocystis and host shifts between commensal and forest small mammal species, even if the known host associations remain likely only snapshots of the true associations.

Diet and the evolution of ADH7 across seven orders of mammals.

Dietary variation within and across species drives the eco-evolutionary responsiveness of genes necessary to metabolize nutrients and other components. Recent evidence from humans and other mammals suggests that sugar-rich diets of floral nectar and ripe fruit have favoured mutations in, and functional preservation of, the ADH7 gene, which encodes the ADH class 4 enzyme responsible for metabolizing ethanol. Here we interrogate a large, comparative dataset of ADH7 gene sequence variation, including that underlying the amino acid residue located at the key site (294) that regulates the affinity of ADH7 for ethanol. Our analyses span 171 mammal species, including 59 newly sequenced. We report extensive variation, especially among frugivorous and nectarivorous bats, with potential for functional impact. We also report widespread variation in the retention and probable pseudogenization of ADH7. However, we find little statistical evidence of an overarching impact of dietary behaviour on putative ADH7 function or presence of derived alleles at site 294 across mammals, which suggests that the evolution of ADH7 is shaped by complex factors. Our study reports extensive new diversity in a gene of longstanding ecological interest, offers new sources of variation to be explored in functional assays in future study, and advances our understanding of the processes of molecular evolution.

The supply of multiple ecosystem services requires biodiversity across spatial scales.

The impact of local biodiversity loss on ecosystem functioning is well established, but the role of larger-scale biodiversity dynamics in the delivery of ecosystem services remains poorly understood. Here we address this gap using a comprehensive dataset describing the supply of 16 cultural, regulating and provisioning ecosystem services in 150 European agricultural grassland plots, and detailed multi-scale data on land use and plant diversity. After controlling for land-use and abiotic factors, we show that both plot-level and surrounding plant diversity play an important role in the supply of cultural and aboveground regulating ecosystem services. In contrast, provisioning and belowground regulating ecosystem services are more strongly driven by field-level management and abiotic factors. Structural equation models revealed that surrounding plant diversity promotes ecosystem services both directly, probably by fostering the spill-over of ecosystem service providers from surrounding areas, and indirectly, by maintaining plot-level diversity. By influencing the ecosystem services that local stakeholders prioritized, biodiversity at different scales was also shown to positively influence a wide range of stakeholder groups. These results provide a comprehensive picture of which ecosystem services rely most strongly on biodiversity, and the respective scales of biodiversity that drive these services. This key information is required for the upscaling of biodiversity-ecosystem service relationships, and the informed management of biodiversity within agricultural landscapes.

Managing host-parasite interactions in humans and wildlife in times of global change.

Global change in the Anthropocene has modified the environment of almost any species on earth, be it through climate change, habitat modifications, pollution, human intervention in the form of mass drug administration (MDA), or vaccination. This can have far-reaching consequences on all organisational levels of life, including eco-physiological stress at the cell and organism level, individual fitness and behaviour, population viability, species interactions and biodiversity. Host-parasite interactions often require highly adapted strategies by the parasite to survive and reproduce within the host environment and ensure efficient transmission among hosts. Yet, our understanding of the system-level outcomes of the intricate interplay of within host survival and among host parasite spread is in its infancy. We shed light on how global change affects host-parasite interactions at different organisational levels and address challenges and opportunities to work towards better-informed management of parasite control. We argue that global change affects host-parasite interactions in wildlife inhabiting natural environments rather differently than in humans and invasive species that benefit from anthropogenic environments as habitat and more deliberate rather than erratic exposure to therapeutic drugs and other control efforts.

Challenges in modelling the dynamics of infectious diseases at the wildlife-human interface.

The Covid-19 pandemic is of zoonotic origin, and many other emerging infections of humans have their origin in an animal host population. We review the challenges involved in modelling the dynamics of wildlife-human interfaces governing infectious disease emergence and spread. We argue that we need a better understanding of the dynamic nature of such interfaces, the underpinning diversity of pathogens and host-pathogen association networks, and the scales and frequencies at which environmental conditions enable spillover and host shifting from animals to humans to occur. The major drivers of the emergence of zoonoses are anthropogenic, including the global change in climate and land use. These, and other ecological processes pose challenges that must be overcome to counterbalance pandemic risk. The development of more detailed and nuanced models will provide better tools for analysing and understanding infectious disease emergence and spread.

Disruption of Metapopulation Structure Reduces Tasmanian Devil Facial Tumour Disease Spread at the Expense of Abundance and Genetic Diversity.

Metapopulation structure plays a fundamental role in the persistence of wildlife populations. It can also drive the spread of infectious diseases and transmissible cancers such as the Tasmanian devil facial tumour disease (DFTD). While disrupting this structure can reduce disease spread, it can also impair host resilience by disrupting gene flow and colonisation dynamics. Using an individual-based metapopulation model we investigated the synergistic effects of host dispersal, disease transmission rate and inter-individual contact distance for transmission, on the spread and persistence of DFTD from local to regional scales. Disease spread, and the ensuing population declines, are synergistically determined by individuals' dispersal, disease transmission rate and within-population mixing. Transmission rates can be magnified by high dispersal and inter-individual transmission distance. The isolation of local populations effectively reduced metapopulation-level disease prevalence but caused severe declines in metapopulation size and genetic diversity. The relative position of managed (i.e., isolated) local populations had a significant effect on disease prevalence, highlighting the importance of considering metapopulation structure when implementing metapopulation-scale disease control measures. Our findings suggest that population isolation is not an ideal management method for preventing disease spread in species inhabiting already fragmented landscapes, where genetic diversity and extinction risk are already a concern.

Challenges in modeling the emergence of novel pathogens.

The emergence of infectious agents with pandemic potential present scientific challenges from detection to data interpretation to understanding determinants of risk and forecasts. Mathematical models could play an essential role in how we prepare for future emergent pathogens. Here, we describe core directions for expansion of the existing tools and knowledge base, including: using mathematical models to identify critical directions and paths for strengthening data collection to detect and respond to outbreaks of novel pathogens; expanding basic theory to identify infectious agents and contexts that present the greatest risks, over both the short and longer term; by strengthening estimation tools that make the most use of the likely range and uncertainties in existing data; and by ensuring modelling applications are carefully communicated and developed within diverse and equitable collaborations for increased public health benefit.

Optimizing noninvasive sampling of a zoonotic bat virus.

Outbreaks of infectious viruses resulting from spillover events from bats have brought much attention to bat-borne zoonoses, which has motivated increased ecological and epidemiological studies on bat populations. Field sampling methods often collect pooled samples of bat excreta from plastic sheets placed under-roosts. However, positive bias is introduced because multiple individuals may contribute to pooled samples, making studies of viral dynamics difficult. Here, we explore the general issue of bias in spatial sample pooling using Hendra virus in Australian bats as a case study. We assessed the accuracy of different under-roost sampling designs using generalized additive models and field data from individually captured bats and pooled urine samples. We then used theoretical simulation models of bat density and under-roost sampling to understand the mechanistic drivers of bias. The most commonly used sampling design estimated viral prevalence 3.2 times higher than individual-level data, with positive bias 5-7 times higher than other designs due to spatial autocorrelation among sampling sheets and clustering of bats in roosts. Simulation results indicate using a stratified random design to collect 30-40 pooled urine samples from 80 to 100 sheets, each with an area of 0.75-1 m2, and would allow estimation of true prevalence with minimum sampling bias and false negatives. These results show that widely used under-roost sampling techniques are highly sensitive to viral presence, but lack specificity, providing limited information regarding viral dynamics. Improved estimation of true prevalence can be attained with minor changes to existing designs such as reducing sheet size, increasing sheet number, and spreading sheets out within the roost area. Our findings provide insight into how spatial sample pooling is vulnerable to bias for a wide range of systems in disease ecology, where optimal sampling design is influenced by pathogen prevalence, host population density, and patterns of aggregation.

Disease control across urban-rural gradients.

Controlling the regional re-emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) after its initial spread in ever-changing personal contact networks and disease landscapes is a challenging task. In a landscape context, contact opportunities within and between populations are changing rapidly as lockdown measures are relaxed and a number of social activities re-activated. Using an individual-based metapopulation model, we explored the efficacy of different control strategies across an urban-rural gradient in Wales, UK. Our model shows that isolation of symptomatic cases or regional lockdowns in response to local outbreaks have limited efficacy unless the overall transmission rate is kept persistently low. Additional isolation of non-symptomatic infected individuals, who may be detected by effective test-and-trace strategies, is pivotal to reducing the overall epidemic size over a wider range of transmission scenarios. We define an 'urban-rural gradient in epidemic size' as a correlation between regional epidemic size and connectivity within the region, with more highly connected urban populations experiencing relatively larger outbreaks. For interventions focused on regional lockdowns, the strength of such gradients in epidemic size increased with higher travel frequencies, indicating a reduced efficacy of the control measure in the urban regions under these conditions. When both non-symptomatic and symptomatic individuals are isolated or regional lockdown strategies are enforced, we further found the strongest urban-rural epidemic gradients at high transmission rates. This effect was reversed for strategies targeted at symptomatic individuals only. Our results emphasize the importance of test-and-trace strategies and maintaining low transmission rates for efficiently controlling SARS-CoV-2 spread, both at landscape scale and in urban areas.

Description of Sarcocystis scandentiborneensis sp. nov. from treeshrews (Tupaia minor, T. tana) in northern Borneo with annotations on the utility of COI and 18S rDNA sequences for species delineation.

Sarcocystis scandentiborneensis sp. nov. was discovered in histological sections of striated musculature of treeshrews (Tupaia minor, T. tana) from Northern Borneo. Sarcocysts were cigar-shaped, 102 µm-545 µm long, and on average 53 µm in diameter. The striated cyst wall varied in thickness (2-10 µm), depending on whether the finger-like, villous protrusions (VP) were bent. Ultrastructurally, sarcocysts were similar to wall type 12 but basal microtubules extended into VPs that tapered off with a unique U-shaped, electron-dense apical structure. In phylogenetic trees of the nuclear 18S rRNA gene, S. scandentiborneensis formed a distinct branch within a monophyletic subclade of Sarcocystis spp. with (colubrid) snake-rodent life cycle. We mapped all intraspecific (two haplotypes) and interspecific nucleotide substitutions to the secondary structure of the 18S rRNA gene: in both cases, the highest variability occurred within helices V2 and V4 but intraspecific variability mostly related to transitions, while transition/transversion ratios between S. scandentiborneensis, S. zuoi, and S. clethrionomyelaphis were skewed towards transversions. Lack of relevant sequences restricted phylogenetic analysis of the mitochondrial Cytochrome C oxidase subunit I (COI) gene to include only one species of Sarcocystis recovered from a snake host (S. pantherophisi) with which the new species formed a sister relationship. We confirm the presence of the functionally important elements of the COI barcode amino acid sequence of S. scandentiborneensis, whereby the frequency of functionally important amino acids (Alanine, Serine) was markedly different to other taxa of the Sarcocystidae. We regard S. scandentiborneensis a new species, highlighting that structurally or functionally important aspects of the 18S rRNA and COI could expand their utility for delineation of species. We also address the question why treeshrews, believed to be close to primates, carry a parasite that is genetically close to a Sarcocystis lineage preferably developing in the Rodentia as intermediate hosts.

Distinct spread of DNA and RNA viruses among mammals amid prominent role of domestic species.

AIM: Emerging infectious diseases arising from pathogen spillover from mammals to humans constitute a substantial health threat. Tracing virus origin and predicting the most likely host species for future spillover events are major objectives in One Health disciplines.We assessed patterns of virus sharing among a large diversity of mammals, including humans and domestic species. LOCATION: Global. TIME PERIOD: Current. MAJOR TAXA STUDIED: Mammals and associated viruses. METHODS: We used network centrality analysis and trait-based Bayesian hierarchical models to explore patterns of virus sharing among mammals. We analysed a global database that compiled the associations between 1,785 virus species and 725 mammalian host species as sourced from automatic screening of meta-data accompanying published nucleotide sequences between 1950 and 2019. RESULTS: We show that based on current evidence, domesticated mammals hold the most central positions in networks of known mammal-virus associations. Among entire host-virus networks, Carnivora and Chiroptera hold central positions for mainly sharing RNA viruses, whereas ungulates hold central positions for sharing both RNA and DNA viruses with other host species. We revealed strong evidence that DNA viruses were phylogenetically more host specific than RNA viruses. RNA viruses exhibited low functional host specificity despite an overall tendency to infect phylogenetically related species, signifying high potential to shift across hosts with different ecological niches. The frequencies of sharing viruses among hosts and the proportion of zoonotic viruses in hosts were larger for RNA than for DNA viruses. MAIN CONCLUSIONS: Acknowledging the role of domestic species in addition to host and virus traits in patterns of virus sharing is necessary to improve our understanding of virus spread and spillover in times of global change. Understanding multi-host virus-sharing pathways adds focus to curtail disease spread.

Whipworms of south-east Asian rodents are distinct from Trichuris muris.

The whipworm Trichuris muris is known to be associated with various rodent species in the northern hemisphere, but the species identity of whipworm infecting rodents in the Oriental region remains largely unknown. We collected Trichuris of Muridae rodents in mainland and insular Southeast Asia between 2008 and 2015 and used molecular and morphological approaches to identify the systematic position of new specimens. We discovered two new species that were clearly distinct from T. muris, both in terms of molecular phylogenetic clustering and morphological features, with one species found in Thailand and another one in Borneo. We named the new species from Thailand as Trichuris cossoni and the species from Borneo as Trichuris arrizabalagai. Molecular phylogeny using internal transcribed spacer region (ITS1-5.8S-ITS2) showed a divergence between T. arrizabalagai n. sp., T. cossoni n. sp. and T. muris. Our findings of phylogeographically distinct Trichuris species despite some globally distributed host species requires further research into the distribution of different species, previously assumed to belong to T. muris, which has particular relevance for using these species as laboratory model organisms.

Models of spatiotemporal variation in rabbit abundance reveal management hot spots for an invasive species.

The European rabbit (Oryctolagus cuniculus) is a notorious economic and environmental pest species in its invasive range. To better understand the population and range dynamics of this species, 41 yr of abundance data have been collected from 116 unique sites across a broad range of climatic and environmental conditions in Australia. We analyzed this time series of abundance data to determine whether interannual variation in climatic conditions can be used to map historic, contemporary, and potential future fluctuations in rabbit abundance from regional to continental scales. We constructed a hierarchical Bayesian regression model of relative abundance that corrected for observation error and seasonal biases. The corrected abundances were regressed against environmental and disease variables in order to project high spatiotemporal resolution, continent-wide rabbit abundances. We show that rabbit abundance in Australia is highly variable in space and time, being driven primarily by internnual variation in temperature and precipitation in concert with the prevalence of a non-pathogenic virus. Moreover, we show that internnual variation in local spatial abundances can be mapped effectively at a continental scale using highly resolved spatiotemporal predictors, allowing "hot spots" of persistently high rabbit abundance to be identified. Importantly, cross-validated model performance was fair to excellent within and across distinct climate zones. Long-term monitoring data for invasive species can be used to map fine-scale spatiotemporal fluctuations in abundance patterns when accurately accounting for inherent sampling biases. Our analysis provides ecologists and pest managers with a clearer understanding of the determinants of rabbit abundance in Australia, offering an important new approach for predicting spatial abundance patterns of invasive species at the near-term temporal scales that are directly relevant to resource management.

Extinction filters mediate the global effects of habitat fragmentation on animals.

Habitat loss is the primary driver of biodiversity decline worldwide, but the effects of fragmentation (the spatial arrangement of remaining habitat) are debated. We tested the hypothesis that forest fragmentation sensitivity-affected by avoidance of habitat edges-should be driven by historical exposure to, and therefore species' evolutionary responses to disturbance. Using a database containing 73 datasets collected worldwide (encompassing 4489 animal species), we found that the proportion of fragmentation-sensitive species was nearly three times as high in regions with low rates of historical disturbance compared with regions with high rates of disturbance (i.e., fires, glaciation, hurricanes, and deforestation). These disturbances coincide with a latitudinal gradient in which sensitivity increases sixfold at low versus high latitudes. We conclude that conservation efforts to limit edges created by fragmentation will be most important in the world's tropical forests.

Eleven years' data of grassland management in Germany.

BACKGROUND: The 150 grassland plots were located in three study regions in Germany, 50 in each region. The dataset describes the yearly grassland management for each grassland plot using 116 variables.General information includes plot identifier, study region and survey year. Additionally, grassland plot characteristics describe the presence and starting year of drainage and whether arable farming had taken place 25 years before our assessment, i.e. between 1981 and 2006. In each year, the size of the management unit is given which, in some cases, changed slightly across years.Mowing, grazing and fertilisation were systematically surveyed: Mowing is characterised by mowing frequency (i.e. number of cuts per year), dates of cutting and different technical variables, such as type of machine used or usage of conditioner.For grazing , the livestock species and age (e.g. cattle, horse, sheep), the number of animals, stocking density per hectare and total duration of grazing were recorded. As a derived variable, the mean grazing intensity was then calculated by multiplying the livestock units with the duration of grazing per hectare [LSU days/ha]. Different grazing periods during a year, partly involving different herds, were summed up to an annual grazing intensity for each grassland.For fertilisation , information on the type and amount of different types of fertilisers was recorded separately for mineral and organic fertilisers, such as solid farmland manure, slurry and mash from a bioethanol factory. Our fertilisation measures neglect dung dropped by livestock during grazing. For each type of fertiliser, we calculated its total nitrogen content, derived from chemical analyses by the producer or agricultural guidelines (Table 3).All three management types, mowing, fertilisation and grazing, were used to calculate a combined land use intensity index (LUI) which is frequently used to define a measure for the land use intensity. Here, fertilisation is expressed as total nitrogen per hectare [kg N/ha], but does not consider potassium and phosphorus.Information on additional management practices in grasslands was also recorded including levelling, to tear-up matted grass covers, rolling, to remove surface irregularities, seed addition, to close gaps in the sward. NEW INFORMATION: Investigating the relationship between human land use and biodiversity is important to understand if and how humans affect it through the way they manage the land and to develop sustainable land use strategies. Quantifying land use (the 'X' in such graphs) can be difficult as humans manage land using a multitude of actions, all of which may affect biodiversity, yet most studies use rather simple measures of land use, for example, by creating land use categories such as conventional vs. organic agriculture. Here, we provide detailed data on grassland management to allow for detailed analyses and the development of land use theory. The raw data have already been used for > 100 papers on the effect of management on biodiversity (e.g. Manning et al. 2015).

Synchronous shedding of multiple bat paramyxoviruses coincides with peak periods of Hendra virus spillover.

Within host-parasite communities, viral co-circulation and co-infections of hosts are the norm, yet studies of significant emerging zoonoses tend to focus on a single parasite species within the host. Using a multiplexed paramyxovirus bead-based PCR on urine samples from Australian flying foxes, we show that multi-viral shedding from flying fox populations is common. We detected up to nine bat paramyxoviruses shed synchronously. Multi-viral shedding infrequently coalesced into an extreme, brief and spatially restricted shedding pulse, coinciding with peak spillover of Hendra virus, an emerging fatal zoonotic pathogen of high interest. Such extreme pulses of multi-viral shedding could easily be missed during routine surveillance yet have potentially serious consequences for spillover of novel pathogens to humans and domestic animal hosts. We also detected co-occurrence patterns suggestive of the presence of interactions among viruses, such as facilitation and cross-immunity. We propose that multiple viruses may be interacting, influencing the shedding and spillover of zoonotic pathogens. Understanding these interactions in the context of broader scale drivers, such as habitat loss, may help predict shedding pulses of Hendra virus and other fatal zoonoses.

Opsin genes of select treeshrews resolve ancestral character states within Scandentia.

Treeshrews are small, squirrel-like mammals in the order Scandentia, which is nested together with Primates and Dermoptera in the superordinal group Euarchonta. They are often described as living fossils, and researchers have long turned to treeshrews as a model or ecological analogue for ancestral primates. A comparative study of colour vision-encoding genes within Scandentia found a derived amino acid substitution in the long-wavelength sensitive opsin gene (OPN1LW) of the Bornean smooth-tailed treeshrew (Dendrogale melanura). The opsin, by inference, is red-shifted by ca 6 nm with an inferred peak sensitivity of 561 nm. It is tempting to view this trait as a novel visual adaptation; however, the genetic and functional diversity of visual pigments in treeshrews is unresolved outside of Borneo. Here, we report gene sequences from the northern smooth-tailed treeshrew (Dendrogale murina) and the Mindanao treeshrew (Tupaia everetti, the senior synonym of Urogale everetti). We found that the opsin genes are under purifying selection and that D. murina shares the same substitution as its congener, a result that distinguishes Dendrogale from other treeshrews, including T. everetti. We discuss the implications of opsin functional variation in light of limited knowledge about the visual ecology of smooth-tailed treeshrews.

Host Specificity in Variable Environments.

Host specificity encompasses the range and diversity of host species that a parasite is capable of infecting and is considered a crucial measure of a parasite's potential to shift hosts and trigger disease emergence. Yet empirical studies rarely consider that regional observations only reflect a parasite's 'realized' host range under particular conditions: the true 'fundamental' range of host specificity is typically not approached. We provide an overview of challenges and directions in modelling host specificity under variable environmental conditions. Combining tractable modelling frameworks with multiple data sources that account for the strong interplay between a parasite's evolutionary history, transmission mode, and environmental filters that shape host-parasite interactions will improve efforts to quantify emerging disease risk in times of global change.

The Australian National Rabbit Database: 50 yr of population monitoring of an invasive species.

With ongoing introductions into Australia since the 1700s, the European rabbit (Oryctolagus cuniculus) has become one of the most widely distributed and abundant vertebrate pests, adversely impacting Australia's biodiversity and agroeconomy. To understand the population and range dynamics of the species and its impacts better, occurrence and abundance data have been collected by researchers and citizens from sites covering a broad spectrum of climatic and environmental conditions in Australia. The lack of a common and accessible repository for these data has, however, limited their use in determining important spatiotemporal drivers of the structure and dynamics of the geographical range of rabbits in Australia. To meet this need, we created the Australian National Rabbit Database, which combines more than 50 yr of historical and contemporary survey data collected from throughout the range of the species in Australia. The survey data, obtained from a suite of complementary monitoring methods, were combined with high-resolution weather, climate, and environmental information, and an assessment of data quality. The database provides records of rabbit occurrence (689,265 records) and abundance (51,241 records, >120 distinct sites) suitable for identifying the spatiotemporal drivers of the rabbit's distribution and for determining spatial patterns of variation in its key life-history traits, including maximum rates of population growth. Because all data are georeferenced and date stamped, they can be coupled with information from other databases and spatial layers to explore the potential effects of rabbit occurrence and abundance on Australia's native wildlife and agricultural production. The Australian National Rabbit Database is an important tool for understanding and managing the European rabbit in its invasive range and its effects on native biodiversity and agricultural production. It also provides a valuable resource for addressing questions related to the biology, success, and impacts of invasive species more generally. No copyright or proprietary restrictions are associated with the use of this data set other than citation of this Data Paper.

Individual and temporal variation in pathogen load predicts long-term impacts of an emerging infectious disease.

Emerging infectious diseases increasingly threaten wildlife populations. Most studies focus on managing short-term epidemic properties, such as controlling early outbreaks. Predicting long-term endemic characteristics with limited retrospective data is more challenging. We used individual-based modeling informed by individual variation in pathogen load and transmissibility to predict long-term impacts of a lethal, transmissible cancer on Tasmanian devil (Sarcophilus harrisii) populations. For this, we employed approximate Bayesian computation to identify model scenarios that best matched known epidemiological and demographic system properties derived from 10 yr of data after disease emergence, enabling us to forecast future system dynamics. We show that the dramatic devil population declines observed thus far are likely attributable to transient dynamics (initial dynamics after disease emergence). Only 21% of matching scenarios led to devil extinction within 100 yr following devil facial tumor disease (DFTD) introduction, whereas DFTD faded out in 57% of simulations. In the remaining 22% of simulations, disease and host coexisted for at least 100 yr, usually with long-period oscillations. Our findings show that pathogen extirpation or host-pathogen coexistence are much more likely than the DFTD-induced devil extinction, with crucial management ramifications. Accounting for individual-level disease progression and the long-term outcome of devil-DFTD interactions at the population-level, our findings suggest that immediate management interventions are unlikely to be necessary to ensure the persistence of Tasmanian devil populations. This is because strong population declines of devils after disease emergence do not necessarily translate into long-term population declines at equilibria. Our modeling approach is widely applicable to other host-pathogen systems to predict disease impact beyond transient dynamics.