Modeling current and potential distributions of mammal species using presence?only data: a case study on British deer

Aim: Decisions on wildlife conservation, management, and epidemiological risk are best based on robust evidence. The continual improvement of species distributions, such that they can be relied upon in decision?making, is important. Here we seek to refine aspects of a generic modelling approach and improve the utility of speciesdistribution maps.Location: Great Britain (GB).Methods: We applied a modeling framework based on hierarchical Bayesian species distribution models exploiting opportunistic occurrence records from citizen science datasets to predict both current and potential distributions for each of the six deerspecies known to be present in GB. Using the resulting maps, we performed a simple analysis of the overlap between species to illustrate possible contact, which we interpret as the relative risk of potential disease spread given an introduction.Results: Predicted distribution maps showed good agreement with the broader scale occurrence reported by a recent national deer survey with an average True Skill Statistics and AUC of 0.69 and 0.89, respectively. Aggregation of the maps for all species highlighted regions of central and eastern England as well as parts of Scotlandwhere extensive areas of range overlap could result in interspecific contact with consequences for risk assessments for diseases of deer. However, if populations are allowed to expand to their predicted potential, then areas of overlap, and therefore disease interspecific transmission risk, will become extensive and widespread across all of mainland Britain.Main conclusions: The generic modeling approach outlined performed well across all of the deer species tested, offering a robust and reliable tool through which current and potential animal distributions can be estimated and presented. Our application,intended to inform quantitative risk assessments, demonstrates the practical use of such outputs to generate the valuable evidence required to inform policy decisions on issues such as management strategy

Landscape as a Model: The Importance of Geometry

In all models, but especially in those used to predict uncertain processes (e.g., climate change and nonnative species establishment), it is important to identify and remove any sources of bias that may confound results. This is critical in models designed to help support decisionmaking. The geometry used to represent virtual landscapes in spatially explicit models is a potential source of bias. The majority of spatial models use regular square geometry, although regular hexagonal landscapes have also been used. However, there are other ways in which space can be represented in spatially explicit models. For the first time, we explicitly compare the range of alternative geometries available to the modeller, and present a mechanism by which uncertainty in the representation of landscapes can be incorporated. We test how geometry can affect cell-to-cell movement across homogeneous virtual landscapes and compare regular geometries with a suite of irregular mosaics. We show that regular geometries have the potential to systematically bias the direction and distance of movement, whereas even individual instances of landscapes with irregular geometry do not. We also examine how geometry can affect the gross representation of real-world landscapes, and again show that individual instances of regular geometries will always create qualitative and quantitative errors. These can be reduced by the use of multiple randomized instances, though this still creates scale-dependent biases. In contrast, virtual landscapes formed using irregular geometries can represent complex real-world landscapes without error. We found that the potential for bias caused by regular geometries can be effectively eliminated by subdividing virtual landscapes using irregular geometry. The use of irregular geometry appears to offer spatial modellers other potential advantages, which are as yet underdeveloped. We recommend their use in all spatially explicit models, but especially for predictive models that are used in decisionmaking

Animal Research beyond the Laboratory:Report from a Workshop on Places Other than Licensed Establishments (POLEs) in the UK

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Research involving animals that occurs outside the laboratory raises an array of unique challenges. With regard to UK legislation, however, it receives only limited attention in terms of official guidelines, support, and statistics, which are unsurprisingly orientated towards the laboratory environment in which the majority of animal research takes place. In September 2019, four social scientists from the Animal Research Nexus program gathered together a group of 13 experts to discuss nonlaboratory research under the Animals (Scientific Procedures) Act (A(SP)A) of 1986 (mirroring European Union (EU) Directive 2010/63/EU), which is the primary mechanism for regulating animal research in the UK. Such nonlaboratory research under the A(SP)A often occurs at Places Other than Licensed Establishments (POLEs). The primary objective of the workshop was to assemble a diverse group with experience across a variety of POLEs (e.g., wildlife field sites, farms, fisheries, veterinary clinics, zoos) to explore the practical, ethical, and regulatory challenges of conducting research at POLEs. While consensus was not sought, nor reached on every point of discussion, we collectively identified five key areas that we propose require further discussion and attention. These relate to: (1) support and training; (2) ethical review; (3) cultures of care, particularly in nonregulated research outside of the laboratory; (4) the setting of boundaries; and (5) statistics and transparency. The workshop generated robust discussion and thereby highlighted the value of focusing on the unique challenges posed by POLEs, and the need for further opportunities for exchanging experiences and sharing best practice relating to research projects outside of the laboratory in the UK and elsewhere

Between roost contact is essential for maintenance of European bat lyssavirus type-2 in Myotis daubentonii bat reservoir: 'The Swarming Hypothesis'

Many high-consequence human and animal pathogens persist in wildlife reservoirs. An understanding of the dynamics of these pathogens in their reservoir hosts is crucial to inform the risk of spill-over events, yet our understanding of these dynamics is frequently insufficient. Viral persistence in a wild bat population was investigated by combining empirical data and in-silico analyses to test hypotheses on mechanisms for viral persistence. A fatal zoonotic virus, European Bat lyssavirus type 2 (EBLV-2), in Daubenton's bats (Myotis daubentonii) was used as a model system. A total of 1839 M. daubentonii were sampled for evidence of virus exposure and excretion during a prospective nine year serial cross-sectional survey. Multivariable statistical models demonstrated age-related differences in seroprevalence, with significant variation in seropositivity over time and among roosts. An Approximate Bayesian Computation approach was used to model the infection dynamics incorporating the known host ecology. The results demonstrate that EBLV-2 is endemic in the study population, and suggest that mixing between roosts during seasonal swarming events is necessary to maintain EBLV-2 in the population. These findings contribute to understanding how bat viruses can persist despite low prevalence of infection, and why infection is constrained to certain bat species in multispecies roosts and ecosystems

European Bat Lyssavirus in Scottish Bats

Daubenton bats may roost infrequently in human dwellings, so risk for human contact is low

The risk of foot-and-mouth disease becoming endemic in a wildlife host is driven by spatial extent rather than density.

In the past 20 years, free living populations of feral wild boar have re-established in several locations across the UK. One of the largest populations is in the Forest of Dean where numbers have been steadily increasing since monitoring began in 2008, with estimates from 2016 reporting a population of more than 1500. Feral wild boar have significant ecological and environmental impacts and may present a serious epidemiological risk to neighbouring livestock as they are a vector for a number of important livestock diseases. This includes foot-and-mouth disease (FMD) which is currently absent from the UK. We developed an individual-based spatially explicit modelling approach to simulate feral wild boar populations in the Forest of Dean (England, UK) and use it to explore whether current or future populations might be sufficient to produce long-lived outbreaks of FMD in this potential wildlife reservoir. Our findings suggest that if you exclude the spread from feral wild boar to other susceptible species, the current population of boar is insufficient to maintain FMD, with 95% of unmanaged simulations indicating disease burn-out within a year (not involving boar management specifically for disease). However, if boar are allowed to spread beyond their current range into the adjacent landscape, they might maintain a self-sustaining reservoir of infection for the disease

Data from: Demographic variation in the U.K. serotine bat: filling gaps in knowledge for management

Species of conservation concern, or those in conflict with man, are most efficiently managed with an understanding of their population dynamics. European bats exemplify the need for successful and cost-effective management for both reasons, often simultaneously. Across Europe, bats are protected, and the concept of Favourable Conservation Status (FCS) is used as a key tool for the assessment and licensing of disruptive actions to populations. However, for efficient decision-making, this assessment requires knowledge on the demographic rates and long-term dynamics of populations. We used capture–mark–recapture to describe demographic rates for the Serotine bat (Eptesicus serotinus) at two sites in England and investigate the transition rates between three stages: juveniles, immatures, and breeders. We then use these rates in an individual-based population dynamics model to investigate the expected trajectories for both populations. Our results demonstrate for the first time the presence and scale of temporal variation in this species' demography. We describe the lengthy prereproductive period (3.5 years) that female Serotines experience. Finally, we show how site-specific variation in demographic rates can produce divergent population trajectories. Effective management of European bat populations can be achieved through the understanding of life histories, and local demographic rates and population dynamics, in order to anticipate the presence of source and sink sites in the landscape. Using the Serotine bat in England, we show that these can be obtained from rigorous and systematic studies of long-term demographic datasets