Abstract Research on endangered wildlife is vital to inform conservation, but may risk adverse welfare impacts. Following predictions that African wild dog ( Lycaon pictus ) populations could collapse as global temperatures rise, we initiated a thermal ecophysiology study to better understand weather impacts on this endangered species. Four institutional ethics committees approved our plan to surgically implant small (3.3g) thermal data loggers, using methods previously applied safely in similar species. One confirmed, and one unconfirmed, incident of adverse effects led us to refine our protocols and reduce target sample sizes. We experienced difficulties in detecting and responding to ill-effects, and our refined protocols approached the limit of what was possible with this wide-ranging species. Hence, any attempt to repeat our study would need to be carefully considered and strongly justified. Future projects performing novel invasive procedures on endangered species should recruit study animals gradually, using intensive post-surgery monitoring to inform recruitment decisions.

Understanding animal movements at different spatial scales presents a significant challenge as their patterns can vary widely from daily foraging behaviours to broader migration or territorial movements. This challenge is of general interest because it impacts the ability to manage wildlife populations effectively. In this study, we conduct diffusion analysis based on European badger (Meles meles) movement data obtained from three different regions in the UK (Gloucestershire, Cornwall, and Northern Ireland) and fit a generalised linear mixed-effects model to examine the relationship between variables. We also feature a novel application of extended dynamic mode decomposition (EDMD) to uncover patterns relating to badger social organisation. By applying our approach to these different populations, we were able to assess its performance across a range of badger densities. A key result was that in some areas, EDMD clusters matched observed group home ranges, whilst in others, discrepancies likely arose because of population management interventions, such as badger culling. The methods presented offer a promising approach for studying territoriality and the impacts of management strategies on animal movement behaviour.

Abstract In the United Kingdom, the management of bovine tuberculosis (bTB) challenges the coexistence of people and wildlife. Control of this cattle disease is hindered by transmission of its causative agent, Mycobacterium bovis, between cattle and badgers Meles meles. Badger culling has formed an element of bTB control policy for decades, but current government policy envisions expanding badger vaccination. Farming leaders are sceptical, citing concerns that badger vaccination would be impractical and potentially ineffective. We report on a 4‐year badger vaccination initiative in an 11 km2 area which, atypically, was initiated by local farmers, delivered by scientists and conservationists, and co‐funded by all three. Participating landholders cited controversies around culling and a desire to support neighbours as their primary reasons for adopting vaccination. The number of badgers vaccinated per km2 (5.6 km−2 in 2019) exceeded the number culled on nearby land (2.9 km−2 in 2019), and the estimated proportion vaccinated (74%, 95% confidence interval [CI] 40%–137%) exceeded the 30% threshold predicted by models to be necessary to control M. bovis. Farmers were content with how vaccination was delivered, and felt that it built trust with wildlife professionals. The percentage of badgers testing positive for M. bovis declined from 16.0% (95% CI 4.5%–36.1%) at the start of vaccination to 0% (95% CI 0%–9.7%) in the final year. With neither replication nor unvaccinated controls, this small‐scale case study does not demonstrate a causal link between badger vaccination and bTB epidemiology, but it does suggest that larger‐scale evaluation of badger vaccination would be warranted. Farmers reported that their enthusiasm for badger vaccination had increased after participating for 4 years. They considered vaccination to have been effective, and good value for money, and wished to continue with it. Synthesis and applications: Although small‐scale, this case study suggests that badger vaccination can be a technically effective and socially acceptable component of bTB control. A wider rollout of badger vaccination is more likely if it is led by the farming community, rather than by conservationists or government, and is combined with scientific monitoring. Read the free Plain Language Summary for this article on the Journal blog.

Abstract Accurate and precise assessment of population density plays a critical role in effective wildlife management, but reliable estimates are often difficult to obtain. Camera traps have emerged as valuable noninvasive tools for studying elusive species, offering cost‐effective solutions for both marked and unmarked populations. We evaluated the consistency of badger (Meles meles) density estimates obtained from the random encounter model (REM) and camera trap distance sampling (CT‐DS) with independent estimates from spatial mark‐resight (SMR) models and quantified the bias in CT‐DS arising from animals reacting to camera traps. Six camera trap surveys were conducted in Cornwall, UK, in 2019 and 2021, and data were used to estimate badger density using the REM and CT‐DS. Four sites were included in a badger vaccination research project, providing an opportunity to mark badgers with uniquely identifiable fur clips to facilitate resighting within a SMR framework. We found consistency in the density estimates across all methods, but results had wide confidence intervals. Density estimates derived from CT‐DS tended to be higher than those from the REM and were sensitive to the exclusion of reactive sequences, resulting in a twofold decrease in the estimated density in one case. The REM tended to be the most precise method; however, where badger density was low, precision was low using all methods. Practical implication: our findings suggest animal density can be assessed from camera traps in the absence of individual identification; however, it is important to account for reactive behaviours, especially where such behaviour is prevalent. In these circumstances, we recommend utilising the REM which offers a clear methodology for addressing bias arising from reactive sequences. In addition, we emphasise the need for improved precision to ensure the effectiveness of these methods in the context of wildlife management. We offer practical considerations to facilitate the broader application of these methods, drawing upon the example of disease control through badger vaccination.

Abstract The use of camera traps to study wildlife has increased markedly in the last two decades. Camera surveys typically produce large data sets which require processing to isolate images containing the species of interest. This is time consuming and costly, particularly if there are many empty images that can result from false triggers. Computer vision technology can assist with data processing, but existing artificial intelligence algorithms are limited by the requirement of a training data set, which itself can be challenging to acquire. Furthermore, deep‐learning methods often require powerful hardware and proficient coding skills. We present Sherlock, a novel algorithm that can reduce the time required to process camera trap data by removing a large number of unwanted images. The code is adaptable, simple to use and requires minimal processing power. We tested Sherlock on 240,596 camera trap images collected from 46 cameras placed in a range of habitats on farms in Cornwall, United Kingdom, and set the parameters to find European badgers (Meles meles). The algorithm correctly classified 91.9% of badger images and removed 49.3% of the unwanted ‘empty’ images. When testing model parameters, we found that faster processing times were achieved by reducing both the number of sampled pixels and ‘bouncing’ attempts (the number of paths explored to identify a disturbance), with minimal implications for model sensitivity and specificity. When Sherlock was tested on two sites which contained no livestock in their images, its performance greatly improved and it removed 92.3% of the empty images. Although further refinements may improve its performance, Sherlock is currently an accessible, simple and useful tool for processing camera trap data.

In the second investigation in a pair of analyses which re-evaluates the Randomised Badger Culling Trial (RBCT), we estimate the effects of proactive badger culling on the incidence of tuberculosis (TB) in cattle populations in unculled neighbouring areas. Throughout peer-reviewed analyses of the RBCT, proactive culling was estimated to have detrimental effects on the incidence of herd breakdowns (i.e. TB incidents) in neighbouring areas. Using previously published, publicly available data, we appraise a variety of frequentist and Bayesian models as we estimate the effects of proactive culling on confirmed herd breakdowns in unculled neighbouring areas. For the during trial period from the initial culls until 4 September 2005, we estimate consistently high probabilities that proactive culling had adverse effects on confirmed herd breakdowns in unculled neighbouring areas, thus supporting the theory of heightened risk of TB for the neighbouring cattle populations. Negligible culling effects are estimated in the post-trial period across the statistical approaches and imply unsustained long-term effects for unculled neighbouring areas. Therefore, when considered alongside estimated beneficial effects within proactive culling areas, these conflicting adverse side effects render proactive culling complex, and thus, decision making regarding potential culling strategies should include (i) ecological, geographical and scientific considerations and (ii) cost-benefit analyses.

Rabies is a highly virulent viral disease that has been associated with large-scale population declines of the endangered African wild dog (Lycaon pictus). Rabies vaccination may be a valuable conservation tool in this species, but studies indicate that a single dose does not always confer protective immunity. We examined 47 serum samples from 22 captive African wild dogs (sampled opportunistically for other purposes) to assess whether serum antibody levels after vaccination correlated with the number of doses received and whether other factors affected outcomes. Results of the fluorescent antibody virus neutralization test showed that median antibody titers were 0.085 IU/mL prevaccination, 0.660 IU/mL after a single vaccination, and 22.150 IU/mL after a booster vaccination. Antibody titers above 0.5 IU/mL, internationally accepted as the threshold for seroconversion, were found in none of the samples taken prevaccination, 66.67% of samples taken after primary vaccination, and 90.90% of samples collected after booster vaccination. This study illustrates the probable protective benefit a rabies booster vaccination may provide in African wild dogs and serves as a basis for future research to improve vaccination protocols contributing to the conservation of this endangered species.

Rabies vaccination in domestic dog populations has increased globally in a bid to protect human health. Surveillance efforts, however, are inconsistent in endemic regions such as in sub-Saharan Africa, due to fragmented reporting and limited diagnostic capacity for suspected cases, limiting successful monitoring and evaluation of vaccination campaigns. Here, we conducted a pilot study aiming to strengthen rabies surveillance by combining community-based surveillance with field-based diagnostic testing in pastoral and agro-pastoral communities in central Kenya; communities which are frequently marginalised from health systems. During the 6-month pilot study, there were 14 alerts of suspected rabid dogs in the community, of which eight were tested and five diagnostically confirmed as rabid. Two positive samples processed successfully for whole genome sequencing indicated that the rabies variant circulating in central Kenya during the study period belonged to the Africa 1b subclade, which is similar to variants identified in eastern Kenya and Tanzania, suggesting regional transmission. This pilot study indicates that rabies continues to circulate in the region and that community-based surveillance, when combined with enhanced diagnostic testing, can help alleviate underreporting and guide vaccination campaigns.

Zoos are valuable resources for research, providing scientists with access to rare and elusive species in an easy to observe environment. Animal-attached loggers (aka biologgers) offer profound insight into animal behaviour. Their use in zoos has high yet largely untapped potential to collect data relevant for wild animal research and conservation but also welfare and enrichment monitoring of the zoo animals themselves. However, affixing biologgers to study animals can be problematic in captive settings, limiting the accessibility of this technology for use on zoo species which ordinarily need to be sedated for the fitting of such devices, including large carnivores. Here we show that biologging collars and crate-training allow collection of novel datasets on captive animals with high welfare and conservation value, using endangered African wild dogs ( Lycaon pictus ) tagged with tri-axial accelerometer and tri-axial magnetometer loggers, as a case study. Two yearling female wild dogs were fitted with biologging collars while sedated in preparation for translocation from London to Whipsnade Zoo, with data collected for 10–26 hours until collar detachment. Two adult male wild dogs at London Zoo were trained to accept collars in a modified crate in exchange for a food reward, which allowed fitting and detaching the collars without sedation, with data collected for 28 days. First, we show how accelerometer and magnetometer data allow detection of fine-scale individual differences in the recovery from sedation as well as within- and between-individual variation in activity patterns in relation to the type of food received (tong vs. rabbit and pony carcass). Using the vectorial dynamic body acceleration metric (VeDBA), a proxy for movement-related energy expenditure, further shows that daily energy expenditure was higher on days with partial pony carcass feeds compared to rabbit feeds but varied considerably between days where flesh pieces were fed with tongs. Using the dead-reckoning method allowed reconstruction of fine-scale (1 Hz locations) movement paths within enclosures, indoors and outdoors, allowing visualisation and quantification of fine-scale movement and space use differences between individuals and over time, for example in response to different enrichment methods. Using multi-sensor biologgers, combined with training captive animals to accept collars without the use of anaesthetic, can enable flexible, experimental approaches to data collection with minimal impact on study animals, providing novel understanding of relevance for both zoo and wild animals.

It has been suggested that animals may have evolved cooperative breeding strategies in response to extreme climatic conditions. Climate change, however, may push species beyond their ability to cope with extreme climates, and reduce the group sizes in cooperatively breeding species to a point where populations are no longer viable. Predicting the impact of future climates on these species is challenging as modelling the impact of climate change on their population dynamics requires information on both group- and individual-level responses to climatic conditions. Using a single-sex individual-based model incorporating demographic responses to ambient temperature in an endangered species, the African wild dog Lycaon pictus, we show that there is a threshold temperature above which populations of the species are predicted to collapse. For simulated populations with carrying capacities equivalent to the median size of real-world populations (nine packs), extinction risk increases once temperatures exceed those predicted in the best-case climate warming scenario (Representative Concentration Pathway [RCP] 2.6). The threshold is higher (between RCP 4.5 and RCP 6.0) for larger simulated populations (30 packs), but 84% of real-world populations number <30 packs. Simulated populations collapsed because, at high ambient temperatures, juvenile survival was so low that packs were no longer recruiting enough individuals to persist, leading them to die out. This work highlights the importance of social dynamics in determining impacts of climatic variables on social species, and the critical role that recruitment can play in driving population-level impacts of climate change. Population models parameterised on long-term data are essential for predicting future population viability under climate change.

Reliable estimates of population size and demographic rates are central to assessing the status of threatened species. However, obtaining individual-based demographic rates requires long-term data, which is often costly and difficult to collect. Photographic data offer an inexpensive, non-invasive method for individual-based monitoring of species with unique markings, and could therefore increase available demographic data for many species. However, selecting suitable images and identifying individuals from photographic catalogues is prohibitively time-consuming. Automated identification software can significantly speed up this process. Nevertheless, automated methods for selecting suitable images are lacking, as are studies comparing the performance of the most prominent identification software packages. In this study, we develop a framework that automatically selects images suitable for individual identification, and compare the performance of three commonly used identification software packages; Hotspotter, I3S-Pattern, and WildID. As a case study, we consider the African wild dog Lycaon pictus, a species whose conservation is limited by a lack of cost-effective large-scale monitoring. To evaluate intra-specific variation in the performance of software packages, we compare identification accuracy between two populations (in Kenya and Zimbabwe) that have markedly different coat colouration patterns. The process of selecting suitable images was automated using Convolutional Neural Nets that crop individuals from images, filter out unsuitable images, separate left and right flanks, and remove image backgrounds. Hotspotter had the highest image-matching accuracy for both populations. However, the accuracy was significantly lower for the Kenyan population (62%), compared to the Zimbabwean population (88%). Our automated image pre-processing has immediate application for expanding monitoring based on image-matching. However, the difference in accuracy between populations highlights that population-specific detection rates are likely and may influence certainty in derived statistics. For species such as the African wild dog, where monitoring is both challenging and expensive, automated individual recognition could greatly expand and expedite conservation efforts.

Abstract Reliable estimates of population size and demographic rates are central to assessing the status of threatened species. However, obtaining individual‐based demographic rates requires long‐term data, which is often costly and difficult to collect. Photographic data offer an inexpensive, noninvasive method for individual‐based monitoring of species with unique markings, and could therefore increase available demographic data for many species. However, selecting suitable images and identifying individuals from photographic catalogs is prohibitively time‐consuming. Automated identification software can significantly speed up this process. Nevertheless, automated methods for selecting suitable images are lacking, as are studies comparing the performance of the most prominent identification software packages. In this study, we develop a framework that automatically selects images suitable for individual identification, and compare the performance of three commonly used identification software packages; Hotspotter, I3S‐Pattern, and WildID. As a case study, we consider the African wild dog, Lycaon pictus, a species whose conservation is limited by a lack of cost‐effective large‐scale monitoring. To evaluate intraspecific variation in the performance of software packages, we compare identification accuracy between two populations (in Kenya and Zimbabwe) that have markedly different coat coloration patterns. The process of selecting suitable images was automated using convolutional neural networks that crop individuals from images, filter out unsuitable images, separate left and right flanks, and remove image backgrounds. Hotspotter had the highest image‐matching accuracy for both populations. However, the accuracy was significantly lower for the Kenyan population (62%), compared to the Zimbabwean population (88%). Our automated image preprocessing has immediate application for expanding monitoring based on image matching. However, the difference in accuracy between populations highlights that population‐specific detection rates are likely and may influence certainty in derived statistics. For species such as the African wild dog, where monitoring is both challenging and expensive, automated individual recognition could greatly expand and expedite conservation efforts.

We provide a preliminary assessment of a previously overlooked wildlife trade, the legal trade in badgers (Meles leucurus and Arctonyx spp.) and badger-derived products in South Korea. A new phase of the trade emerged in the 1990s with the establishment of wildlife farms to supply demand for badger as an edible and medicinal resource, including as a substitute for Asiatic black bear (Ursus thibetanus), a Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) Appendix I species. We trace the continued existence of badger farms to supply trade between 2001 and 2020, supplemented by imported badger-derived products and some apparent illegal harvesting of wild Meles leucurus in South Korea. The range of badger-derived products available to consumers has diversified during the last two decades and now encompasses human food, traditional medicine, cosmetics, dietary supplements, and accessories. We recommend improved monitoring and regulation of the trade, given that legal farming, and potential illegal wild harvest, may present important risks to: (i) wild Meles leucurus populations in South Korea and Arctonyx spp. populations in Asia, which are currently poorly monitored; (ii) the welfare of traded badgers, as territorial mammals with specific social and housing needs; (iii) human health, with mustelid farms now in greater focus as potential sources of novel zoonotic diseases.

Abstract Wildlife fences are often considered an important tool in conservation. Fences are used in attempts to prevent human–wildlife conflict and reduce poaching, despite known negative impacts on landscape connectivity and animal movement patterns. Such impacts are likely to be particularly important for wide-ranging species, such as the African wild dog Lycaon pictus, which requires large areas of continuous habitat to fulfil its resource requirements. Laikipia County in northern Kenya is an important area for wild dogs but new wildlife fences are increasingly being built in this ecosystem. Using a long-term dataset from the area's free-ranging wild dog population, we evaluated the effect of wildlife fence structure on the ability of wild dogs to cross them. The extent to which fences impeded wild dog movement differed between fence designs, although individuals crossed fences of all types. Purpose-built fence gaps increased passage through relatively impermeable fences. Nevertheless, low fence permeability can lead to packs, or parts of packs, becoming trapped on the wrong side of a fence, with consequences for population dynamics. Careful evaluation should be given to the necessity of erecting fences; ecological impact assessments should incorporate evaluation of impacts on animal movement patterns and should be undertaken for all large-scale fencing interventions. Where fencing is unavoidable, projects should use the most permeable fencing structures possible, both in the design of the fence and including as many purpose-built gaps as possible, to minimize impacts on wide-ranging wildlife.

Recently, canine distemper virus (CDV) has been linked to population declines in the endangered African wild dog (Lycaon pictus). As CDV appears able to persist in wildlife, threats to free-ranging wild dogs cannot be eliminated by vaccinating domestic dogs. Conservation managers may therefore consider CDV vaccination of wild dogs in highly threatened populations. For use in field conservation, the ideal CDV vaccine would be safe, immunogenic, and readily available in Africa. The CDV vaccine type most commonly used for domestic dogs (modified live vaccine) is available in Africa, and apparently immunogenic in wild dogs, but has been linked to fatal vaccine-induced distemper in captive wild dogs. However, alternatives are either ineffective (inactivated vaccine) or difficult to obtain in Africa (recombinant vaccine). Data from a questionnaire survey of zoo vaccination practices were therefore combined with studbook tracing to assess the safety of modified live CDV vaccine in captive African wild dogs. Among 135 wild dog pups given modified live CDV vaccine for the first time, there was a single, unconfirmed, case of potential vaccine-induced distemper. Pups given modified live vaccine survived better than those given inactivated vaccine or no vaccine. Although studbook tracing revealed higher overall pup survival at zoos which responded to the questionnaire than at zoos which did not, tracing of all pups born during a 20-yr period that lived long enough to be vaccinated (n = 698 pups in 155 litters) revealed no mortality events consistent with vaccine-induced distemper. Modified live CDV vaccine thus appears to carry low mortality risks for African wild dog pups in captivity, and may warrant trials in free-ranging populations.

Managing infectious disease demands understanding pathogen transmission. In Britain, transmission of Mycobacterium bovis from badgers (Meles meles) to cattle hinders the control of bovine tuberculosis (TB), but the mechanism of such transmission is uncertain. As badgers and cattle seldom interact directly, transmission might occur in their shared environment through contact with contamination such as faeces, urine and saliva. We used concurrent GPS collar tracking of badgers and cattle at four sites in Cornwall, southwest Britain, to test whether each species used locations previously occupied by the other species, within the survival time of M. bovis bacteria. Although analyses of the same data set showed that badgers avoided cattle, we found no evidence that this avoidance persisted over time: neither GPS-collared badgers nor cattle avoided space which had been occupied by the other species in the preceding 36 h. Defining a contact event as an animal being located <5 m from space occupied by the other species within the previous 36 h, we estimated that a herd of 176 cattle (mean herd size in our study areas) would contact badgers at least 6.0 times during an average 24-h period. Similarly, we estimated that a social group of 3.5 badgers (mean group size in our study areas) would contact cattle at least 0.76 times during an average night. Such frequent successive use of the same shared space, within the survival time of M. bovis bacteria, could potentially facilitate M. bovis transmission via the environment.

A number of mathematical models have been developed for canine rabies to explore dynamics and inform control strategies. A common assumption of these models is that naturally acquired immunity plays no role in rabies dynamics. However, empirical studies have detected rabies-specific antibodies in healthy, unvaccinated domestic dogs, potentially due to immunizing, non-lethal exposure. We developed a stochastic model for canine rabies, parameterised for Laikipia County, Kenya, to explore the implications of different scenarios for naturally acquired immunity to rabies in domestic dogs. Simulating these scenarios using a non-spatial model indicated that low levels of immunity can act to limit rabies incidence and prevent depletion of the domestic dog population, increasing the probability of disease persistence. However, incorporating spatial structure and human response to high rabies incidence allowed the virus to persist in the absence of immunity. While low levels of immunity therefore had limited influence under a more realistic approximation of rabies dynamics, high rates of exposure leading to immunizing non-lethal exposure were required to produce population-level seroprevalences comparable with those reported in empirical studies. False positives and/or spatial variation may contribute to high empirical seroprevalences. However, if high seroprevalences are related to high exposure rates, these findings support the need for high vaccination coverage to effectively control this disease.