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Infectious wildlife diseases that circulate at the interface with domestic animals pose significant threats worldwide and require early detection and warning. Although animal tracking technologies are used to discern behavioural changes, they are rarely used to monitor wildlife diseases. Common disease-induced behavioural changes include reduced activity and lethargy ('sickness behaviour'). Here, we investigated whether accelerometer sensors could detect the onset of African swine fever (ASF), a viral infection that induces high mortality in suids for which no vaccine is currently available. Taking advantage of an experiment designed to test an oral ASF vaccine, we equipped 12 wild boars with an accelerometer tag and quantified how ASF affects their activity pattern and behavioural fingerprint, using overall dynamic body acceleration. Wild boars showed a daily reduction in activity of 10–20% from the healthy to the viremia phase. Using change point statistics and comparing healthy individuals living in semi-free and free-ranging conditions, we show how the onset of disease-induced sickness can be detected and how such early detection could work in natural settings. Timely detection of infection in animals is crucial for disease surveillance and control, and accelerometer technology on sentinel animals provides a viable complementary tool to existing disease management approaches. [ABSTRACT FROM AUTHOR]

Bio-telemetry from small tags attached to animals is one of the principal methods for studying the ecology and behaviour of wildlife. The field has constantly evolved over the last 80 years as technological improvement enabled a diversity of sensors to be integrated into the tags (e.g., GPS, accelerometers, etc.). However, retrieving data from tags on free-ranging animals remains a challenge since satellite and GSM networks are relatively expensive and or power hungry. Recently a new class of low-power communication networks have been developed and deployed worldwide to connect the internet of things (IoT). Here, we evaluated one of these, the Sigfox IoT network, for the potential as a real-time multi-sensor data retrieval and tag commanding system for studying fauna across a diversity of species and ecosystems. We tracked 312 individuals across 30 species (from 25 g bats to 3 t elephants) with seven different device concepts, resulting in more than 177,742 successful transmissions. We found a maximum line of sight communication distance of 280 km (on a flying cape vulture [Gyps coprotheres]), which sets a new documented record for animal-borne digital data transmission using terrestrial infrastructure. The average transmission success rate amounted to 68.3% (SD 22.1) on flying species and 54.1% (SD 27.4) on terrestrial species. In addition to GPS data, we also collected and transmitted data products from accelerometers, barometers, and thermometers. Further, we assessed the performance of Sigfox Atlas Native, a low-power method for positional estimates based on radio signal strengths and found a median accuracy of 12.89 km (MAD 5.17) on animals. We found that robust real-time communication (median message delay of 1.49 s), the extremely small size of the tags (starting at 1.28 g without GPS), and the low power demands (as low as 5.8 µAh per transmitted byte) unlock new possibilities for ecological data collection and global animal observation. [ABSTRACT FROM AUTHOR]

Using geospatial data of wildlife presence to predict a species distribution across a geographic area is among the most common tools in management and conservation. The collection of high‐quality presence–absence (PA) data through structured surveys is, however, expensive, and managers usually have access to larger amounts of low‐quality presence‐only (PO) data collected by citizen scientists, opportunistic observations and culling returns for game species. Integrated species distribution models (ISDMs) have been developed to make the most of the data available by combining the higher‐quality, but usually scarcer and more spatially restricted, PA data with the lower‐quality, unstructured, but usually more extensive PO datasets. Joint‐likelihood ISDMs can be run in a Bayesian context using integrated nested laplace approximation methods that allow the addition of a spatially structured random effect to account for data spatial autocorrelation. Here, we apply this innovative approach to fit ISDMs to empirical data, using PA and PO data for the three prevalent deer species in Ireland: red, fallow and sika deer. We collated all deer data available for the past 15 years and fitted models predicting distribution and relative abundance at a 25 km2 resolution across the island. Model predictions were associated to spatial estimate of uncertainty, allowing us to assess the quality of the model and the effect that data scarcity has on the certainty of predictions. Furthermore, we checked the performance of the three species‐specific models using two datasets, independent deer hunting returns and deer densities based on faecal pellet counts. Our work clearly demonstrates the applicability of spatially explicit ISDMs to empirical data in a Bayesian context, providing a blueprint for managers to exploit unexplored and seemingly unusable data that can, when modelled with the proper tools, serve to inform management and conservation policies. [ABSTRACT FROM AUTHOR]

Since the introduction in Georgia in 2007 of an African swine fever (ASF) genotype 2 virus strain, the virus has rapidly spread to both Western European and Asian countries. It now constitutes a major threat for the global swine industry. The ongoing European transmission cycle has been related to the 'wild boar habitat' with closed transmission events between wild boar populations and incidental spillovers to commercial and non‐commercial (backyard) pig holdings. During the epidemic in Belgium, only wild boar were infected and although the introduction route has not yet been elucidated, the 'human factor' is highly suspected. While ASF was successfully contained in a small region in the Southern part of Belgium without affecting domestic pigs, the risk of spillover at the wild/domestic interface remains poorly assessed. In this study, we used a semi‐quantitative method, involving national and international experts, to assess the risk associated with different transmission routes for ASF introduction from wild boar to domestic pig holdings and subsequent dissemination between holdings in the Belgian epidemiological context. Qualitative responses obtained by our questionnaire were numerically transformed and statistically processed to provide a semi‐quantitative assessment of the occurrence of the hazard and a ranking of all transmission routes. 'Farmer', 'bedding material', 'veterinarian' and 'professionals from the pig sector' were considered as the most important transmission routes for ASF introduction from the wild reservoir to pig holdings. 'Animal movements', 'farmer', 'veterinarian', 'iatrogenic', 'animal transport truck' and 'animal care equipment' were considered as the most important transmission routes posing a risk of ASF spread between pig holdings. Combined with specific biosecurity checks in the holdings, this assessment helps in prioritizing risk mitigation measures against ASF introduction and further spread in the domestic pig industry, particularly while the ASF situation in Western Europe is worsening. [ABSTRACT FROM AUTHOR]

Norway spruce (Picea abies (L.) Karst.) is a major production tree species for the European wood industry. However, it is highly sensitive to bark stripping (BS) by red deer (Cervus elaphus L.), which causes large timber losses. Because the red deer population has increased over the last decades, a better understanding of the underlying causes driving BS is urgently needed. BS outbreaks are multifactorial: winter food shortage, local and regional deer abundance and stand properties (thermal and visual cover, and scarcity of herbaceous layers) have been found to drive BS rates. Although the influence of each of these factors is well studied, there is still no consensus on their relative contributions to BS or what mitigation strategy is best. In this study, we made use of a long-term, large-scale BS inventory (13 years over 2570 km2) to fill these gaps. We modeled winter and summer BS rates in response to the most explanatory variables, selected from a large set of environmental variables. Our results highlight the prevalence of deer abundance combined with high sensitivity of coniferous thickets and pronounced habitat selection by deer for these stands. Our findings show that the control of red deer populations is a key measure for reducing BS in Norway spruce stands. [ABSTRACT FROM AUTHOR]

African swine fever (ASF) is a fatal disease infectious to wild and domesticated suids. This disease entered the European Union in 2014 and recently reached western Europe, with the first cases observed in Belgium in September 2018. Carcasses of ASF‐infected wild boar play an important role in the spread and persistence of the virus in the environment. Thus, rapidly finding and removing carcasses is a crucial measure for effective ASF control. Using distribution modelling, we investigated whether the fine‐scale distribution of ASF‐infected animals can be predicted and support wild boar carcass searches. Our results suggest that ASF‐infected wild boar selected deathbeds in cool and moist habitats; thus, deathbed choice was mostly influenced by topographic and water‐dependent covariates. Furthermore, we show that in the case of an epidemic, it is important to quickly collect a minimum of 75–100 carcasses with exact locations to build a well‐performing and efficient carcass distribution model. The proposed model provides an indication of where carcasses are most likely to be found and can be used as a guide to strategically allocate resources. [ABSTRACT FROM AUTHOR]

Thanks to developments in animal tracking technology, detailed data on the movement tracks of individual animals are now attainable for many species. However, straightforward methods to decompose individual tracks into high-resolution, spatial modes are lacking but are essential to understand what an animal is doing., We developed an analytical approach that combines separately validated methods into a straightforward tool for converting animal GPS tracks into short-range movement modes. Our three-step analytical process comprises: (i) decomposing data into separate movement segments using behavioural change point analysis; (ii) defining candidate movement modes and translating them into nonlinear or linear equations between net squared displacement ( NSD) and time and (iii) fitting each candidate equation to NSD segments and determining the best-fitting modes using Concordance Criteria, Akaike's Information Criteria and other fine-scale segment characteristics. We illustrate our approach for three sub-adults, male wild boar Sus scrofa tracked at 15-min intervals over 4 months using GPS collars. We defined five candidate movement modes based on previously published studies of short-term movements: encamped, ranging, round trips (complete and partial) and wandering., Our approach successfully classified over 80% of the tracks into these movement modes lasting between 5 and 54 h and covering between 300 m to 20 km. Repeated analyses of GPS data resampled at different rates indicated that one positional fix every 3-4 h was sufficient for >70% classification success. Classified modes were consistent with published observations of wild boar movement, further validating our method., The proposed approach advances the status quo by permitting classification into multiple movement modes (where these are adequately discernable from spatial fixes) facilitating analyses at high temporal and spatial resolutions, and is straightforward, largely objective, and without restrictive assumptions, necessary parameterizations or visual interpretation. Thus, it should capture the complexity and variability of tracked animal movement mode for a variety of taxa across a wide range of spatial and temporal scales. [ABSTRACT FROM AUTHOR]

Seasonal changes in the distribution of animals can have an important impact on the ecosystem. In agricultural landscapes, the seasonal movement of the wild boar Sus scrofa towards field crops often results in damages and makes control of the population difficult. The plasticity of the species to cope with different habitats is largely proven, but the environmental and human drivers of this seasonal habitat shift at the population scale remain largely unknown. Using MaxEnt and two seasonally distinct presence datasets, we contrasted the distribution of wild boar in southern Belgium during the growing and hunting seasons to (i) analyse seasonal drivers of the distribution and (ii) forecast the potential spread of the species north to its current distribution. We demonstrated that during the growing season, wild boar range almost double, owing to the cover and food provided by agricultural areas, thereby enhancing the movement and spread of the species. We found that the seasonal distribution of wild boar in agricultural lands is mostly influenced by the search for cover and food provided alternatively by forest and field crops. Interestingly, it seems that this search for cover operates under the constraint of a threshold distance. Our results indeed reveal an increased probability of presence not only in the vicinity of forests but also above a threshold distance of 865 m from the forest edge, suggesting that wild boar can overcome the dependence to forest cover. The forecast distribution of wild boar highlighted a potential increase of the current range into suitable habitat between 63 and 168 km. To counteract the potential spread of the species into agricultural habitats and the consecutive damages, we insist on the need for the development of integrated management strategies, combining land use spatial configuration and wild boar spatial behaviour. [ABSTRACT FROM AUTHOR]

In recent decades, the wild boar S us scrofa has simultaneously increased its population size and colonized new habitats, causing more ecological and socio-economic concern than perhaps any other ungulate species. However, the drivers and mechanisms of the species' spatial ecology remain poorly understood. Thanks to a recently developed framework, the movement ecology of any organism can now be tackled within a consistent and unified theoretical approach., Based on this framework, we reviewed the literature on wild boar movement ecology to assess current knowledge and to identify important gaps., By using important navigational (e.g. olfactory sense) and cognitive (e.g. spatial memory, learning from conspecifics) abilities, wild boar have developed complex movement strategies to cope with external factors. However, there is a lack of detailed information on the role played by the internal state (motivation) and motion capacity in shaping the spatial ability of the species., Specific aspects of the movement ecology of the wild boar, together with its high diet plasticity and its high prolificacy, are probably the most important causes of the rapid spread of wild boar worldwide., We hope our review will inspire other scientists to apply their biological models to the movement ecology paradigms. Furthermore, we suggest that future researchers dealing with the movement ecology of any species should explicitly state the components and interactions of the framework investigated to facilitate further understanding and comparison among studies. [ABSTRACT FROM AUTHOR]

Studies about the movement of mammals have recently gained much emphasis thanks to the development of new tracking technology, allowing highly accurate recording of animal movement. However, the amount of data made available requires effective theoretical and analytical framework for appropriate scientific use, i.e. to answer questions of interest. Within this review, we used systematic reviewing technique and the movement ecology framework to assess current knowledge and gaps in wild boar Sus scrofa spatial behaviour, species of high economic, ecological and social interest. Specifically, we observed that the development of new tracking techniques (radio‐telemetry and global positioning system) has promoted movement‐related studies since the early 2000. However, the ecology of movement, i.e. the why, how, when and where exactly an individual is moving is rarely the focus of these studies, which instead lies in the consequences of wild boar movement, e.g. the spread of disease, seed dispersal or damage. Most of the current studies are thus concerned with the interaction between environmental factors and spatial behaviour of the species, while other components of movement, internal state, navigation, and motion capacity are seldom studied. Compared to others ungulates, we also observed that wild boar movement ecology is still poorly considered in the literature. This review highlights the need for more quantitative descriptions of movement and behavioural‐based approaches relating wild boar movement to its internal, navigational, and motion capacities. We expect that facilitated access to tracking technologies, in terms of cost and miniaturization, along with current interest in movement ecology will greatly promote increased knowledge in wild boar spatial behaviour. [ABSTRACT FROM AUTHOR]

Studies about the movement of mammals have recently gained much emphasis thanks to the development of new tracking technology, allowing highly accurate recording of animal movement. However, the amount of data made available requires effective theoretical and analytical framework for appropriate scientific use, i.e. to answer questions of interest. Within this review, we used systematic reviewing technique and the movement ecology framework to assess current knowledge and gaps in wild boar Sus scrofa spatial behaviour, species of high economic, ecological and social interest. Specifically, we observed that the development of new tracking techniques (radio‐telemetry and global positioning system) has promoted movement‐related studies since the early 2000. However, the ecology of movement, i.e. the why, how, when and where exactly an individual is moving is rarely the focus of these studies, which instead lies in the consequences of wild boar movement, e.g. the spread of disease, seed dispersal or damage. Most of the current studies are thus concerned with the interaction between environmental factors and spatial behaviour of the species, while other components of movement, internal state, navigation, and motion capacity are seldom studied. Compared to others ungulates, we also observed that wild boar movement ecology is still poorly considered in the literature. This review highlights the need for more quantitative descriptions of movement and behavioural‐based approaches relating wild boar movement to its internal, navigational, and motion capacities. We expect that facilitated access to tracking technologies, in terms of cost and miniaturization, along with current interest in movement ecology will greatly promote increased knowledge in wild boar spatial behaviour. [ABSTRACT FROM AUTHOR]

This paper is the first to report data on wildlife-vehicle collisions (WVC) in Wallonia, southern Belgium, characterised by one of the densest road network worldwide. With the collaboration of police we identified 3965 accidents involving "free ranging animal" between 2003 and 2011. We observed that these accidents with free ranging animals result in 13% of cases in injuries for the drivers or passengers, and in less than 1% of cases in fatalities (death). 78% of these casualties involve wild animals, among which wild boar take the largest part (39% ). During the covered period we observed an annual increase of WVC of 21%. For wild boar and red deer, this increase was significantly correlated with hunting statistics, used as an index of population density. The temporal analysis demonstrated an increase of WVC during night time with peak of accidents at dusk and dawn. Monthly distribution revealed the role of breeding, dispersal and hunting in shaping temporal patterns of accidents. Spatial analysis, focusing on wild boar, roe deer, red deer and red fox demonstrated clustering of accidents for all these species, until scale between 20 to 70 km. Mapping of accidents via Kernel density analysis permitted us to highlight areas with high risk of WVC risk. Our study suggests that the problem of car accidents due to wildlife is an increasing concern in Wallonia but results on spatial and temporal patterns should help for setting up mitigation measures in the most sensible areas. Moreover we suggest that police data source should be used for nationwide analysis and for comparison between countries. [ABSTRACT FROM AUTHOR]