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Deer (Cervidae) are key components of many ecosystems and estimating deer abundance or density is important to understanding these roles. Many field methods have been used to estimate deer abundance and density, but the factors determining where, when, and why a method was used, and its usefulness, have not been investigated. We systematically reviewed journal articles published during 2004–2018 to evaluate spatio-temporal trends in study objectives, methodologies, and deer abundance and density estimates, and determine how they varied with biophysical and anthropogenic attributes. We also reviewed the precision and bias of deer abundance estimation methods. We found 3,870 deer abundance and density estimates. Most estimates (58%) were for white-tailed deer (Odocoileus virginianus), red deer (Cervus elaphus), and roe deer (Capreolus capreolus). The 6 key methods used to estimate abundance and density were pedestrian sign (track or fecal) counts, pedestrian direct counts, vehicular direct counts, aerial direct counts, motion-sensitive cameras, and harvest data. There were regional differences in the use of these methods, but a general pattern was a temporal shift from using harvest data, pedestrian direct counts, and aerial direct counts to using pedestrian sign counts and motion-sensitive cameras. Only 32% of estimates were accompanied by a measure of precision. The most precise estimates were from vehicular spotlight counts and from capture–recapture analysis of images from motion-sensitive cameras. For aerial direct counts, capture–recapture methods provided the most precise estimates. Bias was robustly assessed in only 16 studies. Most abundance estimates were negatively biased, but capture–recapture methods were the least biased. The usefulness of deer abundance and density estimates would be substantially improved by 1) reporting key methodological details, 2) robustly assessing bias, 3) reporting the precision of estimates, 4) using methods that increase and estimate detection probability, and 5) staying up to date on new methods. The automation of image analysis using machine learning should increase the accuracy and precision of abundance estimates from direct aerial counts (visible and thermal infrared, including from unmanned aerial vehicles [drones]) and motion-sensitive cameras, and substantially reduce the time and cost burdens of manual image analysis.

There is increasing scrutiny of the animal welfare impacts of all animal use activities, including agriculture, the keeping of companion animals, racing and entertainment, research and laboratory use, and wildlife management programs. A common objective of animal welfare monitoring is to quantify the frequency of adverse animal events (e.g., injuries or mortalities). The frequency of such events can be used to provide pass/fail grades for animal use activities relative to a defined threshold and to identify areas for improvement through research. A critical question in these situations is how many animals should be sampled? There are, however, few guidelines available for data collection or analysis, and consequently sample sizes can be highly variable. To address this question, we first evaluated the effect of sample size on precision and statistical power in reporting the frequency of adverse animal welfare outcomes. We next used these findings to assess the precision of published animal welfare investigations for a range of contentious animal use activities, including livestock transport, horse racing, and wildlife harvesting and capture. Finally, we evaluated the sample sizes required for comparing observed outcomes with specified standards through hypothesis testing. Our simulations revealed that the sample sizes required for reasonable levels of precision (i.e., proportional distance to the upper confidence interval limit (δ) of ≤ 0.50) are greater than those that have been commonly used for animal welfare assessments (i.e., >300). Larger sample sizes are required for adverse events with low frequency (i.e., <5%). For comparison with a required threshold standard, even larger samples sizes are required. We present guidelines, and an online calculator, for minimum sample sizes for use in future animal welfare assessments of animal management and research programs.

1. Predicting the current and potential distributions of established invasive species is critical for evaluating management options, but methods for differentiating these distributions have received little attention. In particular, there is uncertainty among invasive species managers about the value of information from incidental sightings compared to data from designed field surveys. This study compares the two approaches, and develops a unifying framework, using the case of invasive sambar deer Cervus unicolor in Victoria, Australia. 2. We first used 391 incidental sightings of sambar deer and 12 biophysical variables to construct a presence-only habitat suitability model using Maxent. We then used that model to stratify field sampling, with proportionately greater sampling of cells with high predicted habitat suitability. Field sampling, consisting of faecal pellet surveys, sign surveys and camera trapping, was conducted in 80 4-km² grid cells. A Bayesian state-space occupancy model was used to predict probability of suitable habitat from the field data. 3. The Maxent and occupancy models predicted similar spatial distributions of habitat suitability for sambar deer in Victoria and there was a strong positive correlation between the rankings of cells by the two approaches. The congruence of the two models suggests that any spatial and detection biases in the presence-only data were relatively unimportant in our study. 4. We predicted the extent of suitable habitat from the occupancy model using a threshold that gave a false negative error rate of 0·05. The current distribution was the suitable habitat within a kernel that had a 99·5% chance of including the presence locations pooled from incidental sightings and field surveys: the potential distribution was suitable habitat outside that kernel. Several discrete areas of potential distribution were identified as priorities for surveillance monitoring with the aim of detecting and managing incursions of sambar deer. 5. Synthesis and applications. Our framework enables managers to robustly estimate the current and potential distributions of established invasive species using either presence-only and/or presence-absence data. Managers can then focus control and/or containment actions within the current distribution and establish surveillance monitoring to detect incursions within the potential distribution.

Dingoes/wild dogs (Canis dingo/familiaris) and red foxes (Vulpes vulpes) are widespread carnivores in southern Australia and are controlled to reduce predation on domestic livestock and native fauna. We used the occurrence of food items in 5875 dingo/wild dog scats and 11,569 fox scats to evaluate interspecific and geographic differences in the diets of these species within nine regions of Victoria, south-eastern Australia. The nine regions encompass a wide variety of ecosystems. Diet overlap between dingoes/wild dogs and foxes varied among regions, from low to near complete overlap. The diet of foxes was broader than dingoes/wild dogs in all but three regions, with the former usually containing more insects, reptiles and plant material. By contrast, dingoes/wild dogs more regularly consumed larger mammals, supporting the hypothesis that niche partitioning occurs on the basis of mammalian prey size. The key mammalian food items for dingoes/wild dogs across all regions were black wallaby (Wallabia bicolor), brushtail possum species (Trichosurus spp.), common wombat (Vombatus ursinus), sambar deer (Rusa unicolor), cattle (Bos taurus) and European rabbit (Oryctolagus cuniculus). The key mammalian food items for foxes across all regions were European rabbit, sheep (Ovis aries) and house mouse (Mus musculus). Foxes consumed 6.1 times the number of individuals of threatened Critical Weight Range native mammal species than did dingoes/wild dogs. The occurrence of intraguild predation was asymmetrical; dingoes/wild dogs consumed greater biomass of the smaller fox. The substantial geographic variation in diet indicates that dingoes/wild dogs and foxes alter their diet in accordance with changing food availability. We provide checklists of taxa recorded in the diets of dingoes/wild dogs and foxes as a resource for managers and researchers wishing to understand the potential impacts of policy and management decisions on dingoes/wild dogs, foxes and the food resources they interact with.

There is much interest in understanding how anthropogenic food resources subsidise carnivore populations. Carcasses of hunter-shot ungulates are a potentially substantial food source for mammalian carnivores. The sambar deer (Rusa unicolor) is a large (≥ 150 kg) exotic ungulate that can be hunted throughout the year in south-eastern Australia, and hunters are not required to remove or bury carcasses. We investigated how wild dogs/dingoes and their hybrids (Canis lupus familiaris/dingo), red foxes (Vulpes vulpes) and feral cats (Felis catus) utilised sambar deer carcasses during the peak hunting seasons (i.e. winter and spring). We placed carcasses at 1-km intervals along each of six transects that extended 4-km into forest from farm boundaries. Visits to carcasses were monitored using camera traps, and the rate of change in edible biomass estimated at ∼ 14-day intervals. Wild dogs and foxes fed on 70% and 60% of 30 carcasses, respectively, but feral cats seldom (10%) fed on carcasses. Spatial and temporal patterns of visits to carcasses were consistent with the hypothesis that foxes avoid wild dogs. Wild dog activity peaked at carcasses 2 and 3 km from farms, a likely legacy of wild dog control, whereas fox activity peaked at carcasses 0 and 4 km from farms. Wild dog activity peaked at dawn and dusk, whereas nearly all fox activity occurred after dusk and before dawn. Neither wild dogs nor foxes remained at carcasses for long periods and the amount of feeding activity by either species was a less important predictor of the loss of edible biomass than season. Reasons for the low impacts of wild dogs and foxes on sambar deer carcass biomass include the spatially and temporally unpredictable distribution of carcasses in the landscape, the rapid rate of edible biomass decomposition in warm periods, low wild dog densities and the availability of alternative food resources.

Identifying species occupying an area is essential for many ecological and conservation studies. Faecal DNA is a potentially powerful method for identifying cryptic mammalian species. In New Zealand, 10 species of ungulate (Order: Artiodactyla) have established wild populations and are managed as pests because of their impacts on native ecosystems. However, identifying the ungulate species present within a management area based on pellet morphology is unreliable. We present a method that enables reliable identification of 10 ungulate species (red deer, sika deer, rusa deer, fallow deer, sambar deer, white-tailed deer, Himalayan tahr, Alpine chamois, feral sheep, and feral goat) from swabs of faecal pellets. A high resolution melting (HRM) assay, targeting a fragment of the 12S rRNA gene, was developed. Species-specific primers were designed and combined in a multiplex PCR resulting in fragments of different length and therefore different melting behaviour for each species. The method was developed using tissue from each of the 10 species, and was validated in blind trials. Our protocol enabled species to be determined for 94% of faecal pellet swabs collected during routine monitoring by the New Zealand Department of Conservation. Our HRM method enables high-throughput and cost-effective species identification from low DNA template samples, and could readily be adapted to discriminate other mammalian species from faecal DNA.

The use of high-throughput sequencing has facilitated virus discovery in wild animals and helped determine their potential threat to humans and other animals. We report the complete genome sequence of a novel picornavirus identified by next-generation sequencing in faeces from Australian fallow deer. Genomic analysis revealed that this virus possesses a typical picornavirus-like genomic organisation of 7554 nt with a single open reading frame (ORF) encoding a polyprotein of 2225 amino acids. Based on the amino acid identity comparison and phylogenetic analysis of the P1, 2C, 3CD, and VP1 regions, this novel picornavirus was closely related to but distinct from known bopiviruses detected to date. This finding suggests that deer/bopivirus could belong to a novel species within the genus Bopivirus, tentatively designated as “Bopivirus C”. Epidemiological investigation of 91 deer (71 fallow, 14 sambar and 6 red deer) and 23 cattle faecal samples showed that six fallow deer and one red deer (overall prevalence 7.7%, 95% confidence interval [CI] 3.8–15.0%) tested positive, but deer/bopivirus was undetectable in sambar deer and cattle. In addition, phylogenetic and sequence analyses indicate that the same genotype is circulating in south-eastern Australia. To our knowledge, this study reports for the first time a deer-origin bopivirus and the presence of a member of genus Bopivirus in Australia. Further epidemiological and molecular studies are needed to investigate the geographic distribution and pathogenic potential of this novel Bopivirus species in other domestic and wild animal species.

Infections with the coccidian parasite Neospora caninum affect domestic and wild animals worldwide. In Australia, N. caninum infections cause considerable losses to the cattle industry with seroprevalence of 8.7% in beef and 10.9% in dairy cattle. Conversely, the role of wild animals, in maintaining the parasite cycle is also unclear. It is possible that native or introduced herbivorous species could be reservoir hosts of N. caninum in Australia, but to date, this has not been investigated. We report here the first large-scale screening of N. caninum antibodies in Australian wild deer, spanning three species (fallow, red and sambar deer). Consequently, we also assessed two commercial cELISA tests validated for detecting N. caninum in cattle for their ability to detect N. caninum antibodies in serum samples of wild deer. N. caninum antibodies were detected in 3.7% (7/189, 95% CI 1.8 – 7.45) of the wild deer serum samples collected in south-eastern Australia ( n  = 189), including 97 fallow deer ( Dama dama ), 14 red deer ( Cervus elaphus ), and 78 sambar deer ( Rusa unicolor ). Overall, our study provides the first detection of N. caninum antibodies in wild deer and quantifies deer's potential role in the sylvatic cycle of N. caninum .

Picobirnaviruses (PBVs) have been detected in several species of animals worldwide; however, data pertaining to their presence in Australian wild and domestic animals are limited. Although PBVs are mostly found in faecal samples, their detection in blood and respiratory tract samples raises questions concerning their tropism and pathogenicity. We report here PBV detection in wild deer and cattle from southeastern Australia. Through metagenomics, the presence of PBV genogroups I (GI) and II (GII) were detected in deer serum and plasma. Molecular epidemiology studies targeting the partial RNA-dependent RNA polymerase gene were performed in a wide range of specimens (serum, faeces, spleen, lung, nasal swabs, and trachea) collected from wild deer and cattle, with PCR amplification obtained in all specimen types except lung and spleen. Our results reveal the predominance of GI and concomitant detection of both genogroups in wild deer and cattle. In concordance with other studies, the detected GI sequences displayed high genetic diversity, however in contrast, GII sequences clustered into three distinct clades. Detection of both genogroups in the upper respiratory tract (trachea and nasal swab) of deer in the present study gives more evidence about the respiratory tract tropism of PBV. Although much remains unknown about the epidemiology and tropism of PBVs, our study suggests a wide distribution of these viruses in southeastern Australia.

Since deer were introduced into Australia in the mid-1800s, their wild populations have increased in size and distribution, posing a potential risk to the livestock industry, through their role in pathogen transmission cycles. In comparison to livestock, there are limited data on viral infections in all wildlife, including deer. The aim of this study was to assess blood samples from wild Australian deer for serological evidence of exposure to relevant viral livestock diseases. Blood samples collected across eastern Australia were tested by ELISA to detect antigens and antibodies against Pestivirus and antibodies against bovine herpesvirus 1. A subset of samples was also assessed by RT-PCR for Pestivirus, Simbu serogroup, epizootic hemorrhagic disease virus and bovine ephemeral fever virus. Our findings demonstrated a very low seroprevalence (3%) for ruminant Pestivirus, and none of the other viruses tested were detected. These results suggest that wild deer may currently be an incidental spill-over host (rather than a reservoir host) for Pestivirus. However, deer could be a future source of viral infections for domestic animals in Australia. Further investigations are needed to monitor pathogen activity and quantify possible future infectious disease impacts of wild deer on the Australian livestock industry.