Effective wildlife disease management and research rely on trustworthy disease diagnostics. For chronic wasting disease (CWD), immunohistochemistry (IHC) is recognized as the gold standard, and ELISA is a reliable high-throughput screening method validated for use on obex and retropharyngeal lymph node (RPLN) tissues. However, diagnostic performance of the assays when used on tissues from elk (Cervus canadensis) varies, particularly under varying CWD population prevalence. We used hierarchical Bayesian modeling to predict sensitivity and specificity of ELISA on obex and RPLN and IHC on obex, RPLN, and rectoanal mucosa-associated lymphoid tissue (RAMALT) from elk. We detected CWD prion in at least one tissue from 46/283 individuals tested postmortem between 2016 and 2020. Specificity of ELISA was nearly perfect, providing strong confidence in CWD-detected results. Predicted mean test sensitivity was greater for ELISA than for IHC and slightly greater for RPLN tissue than for obex. The most sensitive individual test was ELISA RPLN, whereas the most reliable CWD diagnosis was achieved by parallel testing of both the obex and RPLN by ELISA, with serial confirmation by IHC. Although RAMALT can be used for antemortem testing, its low sensitivity makes negative results unreliable for proving an animal is disease free. When positive and negative predictive values of these methods were evaluated, we found the reliability of diagnostic results varied widely within the observed range of disease prevalence, and poor reliability was exaggerated by low diagnostic performance. Test-negative results are more likely to be true early in disease invasion, whereas the risk of a false-negative result grows with increasing disease prevalence in the sampled population. Wildlife managers should consider both the objectives and the stage of disease invasion when interpreting diagnostic test results.

Effects of a mega wildfire on small mammals and ticks in a boreal forest in Sweden.

Passive acoustic monitoring (PAM) is a widely used technique in wildlife research, enabling the collection of extensive data on species presence, distribution, and behavior over large spatial and temporal scales in a non-invasive and cost-effective manner. However, the resulting data volumes pose significant computational challenges, potentially creating processing bottlenecks. In this study, we evaluated the effectiveness of integrating PAM with BirdNET, a convolutional neural network originally developed for avian vocalization detection, to monitor two critically endangered lemurs, Indri indri and Varecia variegata, in Madagascar's Maromizaha rainforest. We collected 55,091 recordings over 4 years (2020-2023) and retrained BirdNET for lemur vocalization detection using labeled recordings. We then tested models with different training datasets and confidence thresholds achieving one with a high performance (precision, recall, and accuracy ∼90% for both species). Using this best-performing model, we analyzed the recordings to investigate temporal patterns in vocal behavior. Indri indri exhibited a clear diurnal calling pattern with peak activity between 08:00 and 09:00, supporting its use of morning songs for territorial advertisement. Vocal activity also peaked during the warm season (October-March). In contrast, Varecia variegata showed an irregular calling pattern throughout the day, including at night, and lacked clear seasonal vocal peaks, consistent with previous descriptions of its more flexible activity. Spatial analysis further revealed detection variability across sites, likely influenced by habitat structure and population distribution. This work demonstrates the feasibility and value of combining PAM with machine learning for long-term primate monitoring, providing a potentially replicable and scalable method for studying species' ecology and informing conservation strategies.

Populations of cervids in many areas in North America, especially relative to white-tailed deer, have expanded substantially, resulting in increased damage to agriculture, altered plant communities, and higher prevalence of disease within cervid populations and at wildlife–livestock interfaces. The efforts of research biologists with the National Wildlife Research Center of the United States Department of Agriculture, Animal Plant and Animal Health Inspection Service, Wildlife Services have played a role in developing practical and scientifically robust strategies for addressing these issues. Here we review and synthesize these efforts within the broad key themes of: mitigation of disease transmission and crop damage; disease ecology and management; development of research and management tools and strategies; and deer ecology and management. Collectively, these lines of investigation have led to practical tools and strategies that are being employed by practitioners and informing modern cervid management based on scientific evidence and risk-orientated strategies. We also identify outstanding challenges and future research directions, especially as related to scalable biosecurity and the integration of multiple non-lethal and lethal methods to achieve management goals.

The use of rodenticides is a primary method for eradicating rodents from islands for conservation purposes. Rodenticide residue monitoring is often incorporated into rodent eradication project planning to understand the potential effects on nontarget species, but robust long-term sampling is often challenging due to logistical and financial constraints. We documented more than two years of rodenticide residues at fine-scale intervals with over 570 samples associated with a rodent eradication attempt. Brodifacoum-25D Conservation was applied in an attempt to eradicate house mice (Mus musculus) from Midway Atoll National Wildlife Refuge in the Northwestern Hawaiian Islands. As a cooperating agency, USDA National Wildlife Research Center collected and tested environmental samples for brodifacoum residues, targeting compartments (invertebrates, vertebrates, water, soil, and plants) that may affect the health of humans and wildlife. Brodifacoum residues in invertebrates peaked immediately after bait application and persisted in low levels until becoming undetectable nine months after bait application. Brodifacoum residues decreased over time but persisted in some vertebrate species (geckos, fish, birds) throughout the one-year sampling period after bait applications. All soil and water environmental samples had either no detectable residues or were under method limit of quantitation. No detectable residues were found in drinking water systems or food plant samples. The adaptive environmental monitoring, which included rapid turnaround of analytical chemistry results, enabled real-time management decisions for nontarget species, mitigation approaches, and community action.

Infectious disease is a growing threat to wildlife, with zoonotic transmission most likely at the human-wildlife interface. One underappreciated activity at this interface is fieldwork with wild animals, but associated risks can be mitigated through field hygiene (FH) practices, such as using personal protective equipment and other appropriate behaviors. Following the dissemination of International Union for Conservation of Nature FH guidelines for bat researchers, we investigated factors that affect bat researchers' intent to use FH practices under a theory of planned behavior (TPB) framework. Under the TPB, a person's intent to perform a behavior is influenced by their attitude toward, their subjective norms around, and their perceived behavioral control (PBC) about the behavior. We invited researchers who had recently conducted bat-related fieldwork to complete a qualitative questionnaire, generating data that we used to build a quantitative survey, which we disseminated widely to bat researchers. We analyzed ∼1000 survey responses with structural equation modeling and assessed the role of career stage, research focus, and socioeconomic status of the research location on intent. Bat researchers' intent to adopt FH practices was high overall. For those who do not focus on disease projects, the subjective norm was a strong driver of intent, with mentors the most influential norm referents; authoritative bodies that set regulations and peers were influential too. The only modeled barrier to intent was PBC-with beliefs that FH practices are impractical or uncomfortable contributing most to PBC. We concluded that senior researchers should be encouraged to use FH practices and encourage their mentees to do likewise. Technical solutions and education to mitigate impracticality and discomfort issues should also be encouraged. Although we focused on bat researchers, all wildlife fieldwork entails pathogen transmission risks. To mitigate them, FH practices must become entrenched in the wildlife research community; achieving this goal requires regulatory and social measures.

Disentangling the contributions of different hosts to disease transmission is highly complex but critical for improving predictions, surveillance and response. This is particularly challenging in wildlife, with pathogens often infecting multiple species and data collection being difficult. Using the emergence of Usutu virus (USUV) in the Netherlands as a case study, we demonstrate the use of an approximate Bayesian computation framework on diverse data sources to uncover drivers of spatiotemporal wildlife disease emergence. We calibrated single- and multi-host mechanistic transmission models to five types of wildlife surveillance and research data, describing molecular and serological evidence of USUV in birds. Although Eurasian blackbirds, the primary target species for surveillance, were most severely affected, our models indicated that USUV could not persist in blackbirds alone. Our framework provided statistical support for additional, unobserved bird species to have contributed to transmission. This population of bird species is characterized by limited infection mortality, a longer lifespan and likely further dispersal than blackbirds. Immunity in this population appears to have protected blackbirds from further USUV-related population decline. Our results underscore the importance of considering multiple host populations to understand outbreak dynamics. Neglecting the multi-host context of transmission can impact the reliability of predictions and projected impact of interventions.

Since the return of the grey wolf (Canis lupus) to Germany in the late 1990s, the Federal Documentation and Consultation Centre on Wolves has been conducting nationwide population monitoring, with animals found dead representing an important source of information. In addition to the standardized necropsy at the Leibniz Institute for Zoo and Wildlife Research, 182 male wolves were examined for their reproductive status between 2020 and 2024. Testis mass was measured and spermatogenic activity was determined by flow cytometric ploidy analyses of dissociated testis tissue and the presence of epididymal sperm. These reproductive parameters were evaluated with regard to age class (juvenile, subadult, adult) and month of death (seasonality). Deciphering seasonality in subadult and adult males showed that haploid cells and epididymal sperm are not only present during the mating season (January to March) but also before (October to December), as meiotic activity already begins in late summer. Almost no spermatogenic activity was detected between May and August. While the body mass of (sub)adult males remained relatively constant throughout the year, testis/body mass ratio increased with spermatogenic activity. Spermatogenic activity already occurred in juvenile males, but it was delayed, and the average level of reproductive parameters increased from juvenile to subadult males, reaching their maximum in adult wolves. Sperm production varied greatly among juveniles and was related to their body and testis mass. Basic sexual maturity was only reached at a body mass of more than 25 kg and a testis mass of more than 5 g.

Robust estimation of wildlife populations represents a cornerstone of wildlife research and provides critical information to guide management, including identifying at-risk species, setting harvest rates, and evaluating predator and invasive species control programs. Efforts to enhance population estimation have long included influences one species may have on another, beginning with direct effects of predation on prey populations. More recently, researchers have incorporated co-occurrence effects, such as fear of a competitor, into Lotka-Volterra competition models to generate more robust wildlife population estimates. Here, we introduce two modified Lotka-Volterra competition models, which incorporate one- and two-way co-occurrence effects, to estimate populations of two competing species. Using the test case of northern spotted (Strix occidentalis caurina) and barred owl (Strix varia) populations in the Pacific Northwest region of the United States, we evaluate if these new co-occurrence models can generate more robust population estimates than previous models. We then evaluate if potential co-occurrence effects among barred and northern spotted owls are uni- or bidirectional. Lastly, we leverage the best-performing model to evaluate the degree to which a recently proposed barred owl culling program may help recover northern spotted owl populations. Our model results suggest that incorporating co-occurrence effects improves model fit compared to classical Lotka-Volterra competition models. We found strong evidence for unidirectional co-occurrence effects of barred owls on northern spotted owls, but not vice versa. Our simulations of barred owl culling suggest that barred owls would need to be culled from approximately 40% of all occupied barred owl territories each year to reverse ongoing northern spotted owl population declines.

Satellite-derived vegetation indices provide a powerful means to quantify habitat variation in long-term ecological studies, but their reliability as proxies for forage availability in wild herbivore populations remains underexplored. We used three decades of Landsat satellite imagery (1991-2023) to generate a 30 m resolution dataset of a proxy for annual vegetation greenness - the Normalised Difference Vegetation Index (NDVI) - for the Isle of Rum, Scotland, home to a long-term study of wild red deer (Cervus elaphus). We ground-truthed the NDVI data against live vegetation biomass data collected from calcareous grassland, which is preferred by the deer, and compared it with a coarser-resolution (500 m) MODIS Enhanced Vegetation Index (EVI) metric. Landsat NDVI was positively correlated with both live biomass and EVI, supporting its ecological relevance as a measure of forage availability. All three metrics have increased over the last three decades, indicating a long-term greening trend, with the higher resolution Landsat dataset revealing variation in the rate of change among vegetation groups, including grassland habitats preferred by deer. These findings suggest an increase in forage availability over time, which may have important consequences for the red deer on Rum. Our approach provides a transferable framework for integrating satellite data with individual-based field studies, demonstrating how remote sensing can enhance ecological inference in long-term wildlife research.

ABSTRACT Introduction Faecal DNA is increasingly used in non‐invasive genetic studies, offering a valuable tool for wildlife research, especially for elusive or protected species. It enables genetic analysis with minimal or no impact on animal welfare. Aims Here we review scientific publications using faecal pellets as a source of DNA in wild lagomorphs, provide a critical overview of field and laboratory methodologies and provide suggested improvements for future genetic studies. Methods Using the Scopus database, 45 publications from 1996 to 2024 were identified and analysed. Key aspects examined include sampling strategies, storage methods, DNA extraction protocols, molecular markers, and the intended applications of faecal DNA. Results Although lagomorphs are widely studied, only a limited number of investigations used faecal pellets as a DNA source. These focused on 7 genera and 15 species, mainly Lepus (69%) and Sylvilagus (33%). Most studies were conducted in North America ( n = 20) and Europe ( n = 16), addressing species and individual identification, sexing, hybridisation and methodological validation. Mitochondrial DNA sequencing and microsatellite genotyping were the most common applications, respectively, for species determination and individual identification or population‐level analyses. Discussion This review highlights the usefulness of faecal pellets for genetic investigations on this taxon; however, improvements are needed. We prompt for methodological standardisations and for the development of taxon‐specific SNP panels that could assure data reproducibility and comparability. We are confident that this review will provide a valuable starting point for future studies and assist researchers starting non‐invasive genetic investigations on lagomorph populations.

The western-European hedgehog (Erinaceus europaeus) is a near-threatened mammal frequently admitted to wildlife rescue centres. In early 2025, an outbreak of haemorrhagic enteritis affected 28 hoglets and juvenile hedgehogs at the Ria Formosa Wildlife Recovery and Research Centre (RIAS) in Portugal, resulting in a mortality rate exceeding 35%. Clinical signs included appetite and weight loss, and diarrhoea (including bloody diarrhoea). Diagnostic testing (parasitology, virology, bacteriology and histopathology) was conducted and Salmonella enterica subsp. enterica, was isolated from internal organs (liver, spleen, intestine, and lung) of four necropsied individuals. Following antimicrobial susceptibility testing, treatment with trimethoprim-sulfamethoxazole associated with critical care led to clinical improvement in surviving animals. This case underscores the challenges in diagnosing and managing infectious disease outbreaks in wildlife rescue centres and highlights the zoonotic risk of diseases that can affect hedgehogs, as salmonellosis. The findings emphasise the need for enhanced surveillance, rapid diagnostics, and effective biosecurity protocols in conservation centres to ensure animal welfare, good recovery rates and mitigate public health risks.

Tropical forests support exceptional biodiversity yet remain underrepresented in long-term wildlife research and monitoring programs due to logistical, financial, and methodological constraints. Conventional ground-based survey methods are often ineffective in these environments, particularly for rare, cryptic, or arboreal species. Drone-mounted thermal cameras (thermal drones) offer a promising alternative by detecting endothermic animals from above based on their thermal signatures, with advantages for surveying inaccessible or densely forested habitats. This review synthesises the application of thermal drones for research on tropical forest fauna and provides a practical framework to support conservation practitioners in their deployment. Drawing on 38 studies published between 2018 and 2025, we examine how biological traits, environmental conditions, and technical parameters influence detection outcomes and evaluate whether thermal drones have potential to improve upon conventional methods. While most studies remain at the pilot stage, with limited progression to population inference, the available evidence indicates that thermal drones can outperform ground-based methods for detecting arboreal mammals in tropical forests when protocols are tailored to species behaviour and conditions that maximise thermal contrast. Based on the evidence, we summarise operational challenges and methodological limitations and highlight key constraints on inference, including variable detectability and species misclassification. We distil findings from the literature to provide best practice guidance for survey planning, flight configuration, and detection validation, supported by a decision tree to guide protocol design. Integration with long-term monitoring programs, improved error quantification, and broader taxonomic application will be essential to realise the potential of thermal drones for tropical biodiversity research.

Wildlife conservation in Saudi Arabia is gaining much attention from the authorities. Habitat destruction, climate change, and human encroachment, as well as disease outbreaks, negatively impact conservation efforts. Hemoparasites among endangered Saudi wildlife have not been studied before. This study aims to investigate the prevalence of hemoparasites among two endangered gazelle species, Gazella marica (Reem) and Gazella arabica (Idmi), raised at King Khalid Wildlife Research Center (KKWRC) for breeding and reintroduction purposes. A total of 233 blood samples were collected from the jugular veins of gazelles and examined microscopically for the detection of piroplasm or any relevant blood parasites. Ticks were collected from some gazelles at KKWRC to identify them and see their potential role in the transmission of hemoparasites. DNA was extracted from the collected blood and ticks for the detection of hemoparasites and amplified, targeting the partial 18S rRNA gene. The prevalence of intraerythrocytic bodies suggestive of Theileria sp. was detected in 41 (17.9%) gazelles of both species, whereas PCR products of Theileria sp. DNA was detected in 65 (27.9%) gazelles. The sensitivity of the molecular technique compared to the direct microscopy was 76.74%, whereas the specificity was 83.16%. Ticks were morphologically identified as Hyalomma impeltatum and confirmed with molecular techniques. Sequences obtained from Theileria sp. from both Reem and Idmi gazelles were identical, except for a single mutation (transition) at position 140: a T in Reem sequences, whereas it was a C in all Idmi sequences. Phylogenetic studies indicated that sequences obtained from gazelles in the present study group were related to Theileria sp., which was isolated from the Chinkara gazelle from Pakistan and related to isolates from the dama gazelle. Theileria sp. DNA was amplified from two ticks collected from Reem gazelles and found to be identical to the Theileria sp. sequences obtained from Reem gazelles. This finding suggested that H. impeltatum may carry Theileria DNA; however, vector competence requires further investigations. The prevalence of Theileria infection in gazelles at KKWRC in Saudi Arabia was reported for the first time. The possible vector responsible for the transmission was also identified.

This research note introduces a scenario-based interview technique to investigate wildlife value orientations within China's distinct sociocultural context. Standard qualitative methods often struggle to elicit authentic insights in cross-cultural settings, especially where abstract concepts like “values” lack linguistic or conceptual equivalence. Through six carefully constructed, culturally resonant, and context-rich scenarios, the study revealed latent values underpinning human–wildlife interactions in China, highlighting culturally grounded orientations such as hierarchical harmony, pragmatic consumption, and deference to authority, dimensions often overlooked in Western-centric frameworks. Findings demonstrate that scenario-based techniques effectively capture latent value systems and illuminate participants' underlying reasoning processes. This methodological approach offers significant implications for conservation professionals and researchers seeking context-sensitive tools to inform culturally appropriate wildlife management and policy strategies, underscoring the necessity of culturally attuned methods in global human dimensions of wildlife research.

Chronic wasting disease (CWD) is a widespread and incurable cervid disease. Despite continuing investments, the logistical challenges of CWD have required wildlife managers and researchers to navigate changing priorities with conflicting public perceptions. When overcoming difficult management problems, leveraging exploratory methods may identify previously unrecognized hypotheses. In this study, we interviewed wildlife managers and researchers to describe the diverse experiences of experts in the CWD management community. Our study asked about common management strategies used, challenges experienced, and attempted to understand how decision-making in CWD management is shaped and constrained. Our study participants experienced a wide range of constraining factors, primarily related to external influences. We also identified connections between these constraints and a common concern for staff and public burnout. The results of this study provide insight on constraints limiting CWD management success and possible explanations for some commonly recognized challenges resulting from social and ecological interactions.

Monitoring vulnerable Houbara bustards, birds of both ecological and cultural significance, and detecting intruders that can pose a threat to their nests, is critical for effective conservation of these iconic species. Deep learning-based object detection offers an efficient solution for automating large-scale monitoring, yet its application to Houbara research has been hindered by the lack of comprehensive datasets. To address this gap, we present a new dataset of 24,318 camera-trap images, including 15,070 Houbara bustard images and 9,248 intruder images, all annotated with bounding boxes. Collected between 2011 and 2023 at various times of the day, and using 14 camera models, this dataset provides high diversity and complexity, enabling studies on Houbaras and other bustard species in similar habitats. We benchmarked 10 state-of-the-art object detection models, demonstrating that YOLOv10 outperforms others across evaluation metrics. This dataset represents a significant contribution to wildlife monitoring and conservation, supporting vulnerable Houbara bustard research while offering a foundation for broader applications by providing a valuable resource for wildlife researchers and practitioners.

Identifying the drivers of wildlife immunity is critical for assessing stressor impacts and zoonotic risks. However, such studies are limited by logistical challenges of wildlife research and lack of species-specific reagents. We adapt flow cytometry, typically confined to laboratory settings, to field settings to profile cellular immunity with small blood volumes and extended sample holding times. We apply these methods to analyze immune cell seasonality in migratory Mexican free-tailed bats (Tadarida brasiliensis). We confirmed four antibodies recognizing CD3, CD79a, MHCII, and CD11b that were originally validated in Egyptian fruit bats (Rousettus aegyptiacus), allowing us to quantify T and B cells, macrophages, and neutrophils, respectively. Flow cytometry outperformed hematology in quantifying leukocyte profiles and revealed pronounced immune cell seasonality. Adaptive cells steadily increased between spring and fall migration. Neutrophils were most abundant during the reproductive period and decreased during migrations, whereas B cells were most abundant after reproduction and before fall migration; granulocytes as a whole, macrophages, and T cells had no seasonality. Females had more B cells than males but did not differ in other cells. Our findings lay the groundwork for applying flow cytometry to field studies of wildlife and provide important insights into the seasonality of bat immunity.

The accelerating impacts of climate change, widespread forest degradation, and escalating biodiversity loss have intensified global concern about the complex and interdependent relationships among climate, forest, and wildlife systems. These interactions influence ecosystem structure, habitat suitability, species distribution, and wildlife behaviour, thereby reshaping human and natural systems across multiple spatial and temporal scales. Over the past two decades, scientific literature addressing climate, forest, and wildlife dynamics has expanded significantly, exhibiting an annual growth rate of 15.06%, driven by advances in ecological modelling, remote sensing, biodiversity monitoring, climate analytics, and international conservation and policy frameworks. This study employs a comprehensive bibliometric approach to systematically examine the evolution, structure, and collaborative patterns of global research on climate, forest, and wildlife interactions. A total of 8,271 documents published between 2000 and 2025 were retrieved from the Scopus and Web of Science databases, spanning 1,423 scholarly sources. The dataset included 19,760 author keywords and 20,933 Keywords Plus, reflecting the thematic breadth and conceptual diversity of the field. Bibliographic records were analysed using the Bibliometrix package in RStudio to evaluate publication trends, source dynamics, citation impact, thematic diversity, keyword evolution, authorship patterns, and international collaboration networks, thereby revealing the intellectual structure and developmental trajectory of this research domain. The findings indicate that this field is rapidly expanding, strongly interdisciplinary, and characterized by robust collaboration alongside an increasingly diverse thematic scope. While the diversity of keywords and publication sources reflects conceptual richness and methodological innovation, it also highlights the absence of a standardized vocabulary and limited thematic consolidation. Growing global collaboration further underscores the increasing relevance of climate, forest, and wildlife research in addressing contemporary environmental challenges and informing policy decisions.

AviFluMap: An interactive tool to assess H5N1 avian influenza incursion risk in Australia via migratory birds