Longitudinal trends of metal(loid)s in nestling bald eagles (Haliaeetus leucocephalus) from Wisconsin.

Introduction Wildlife-based tourism (WBT) is a vital strategy for integrating biodiversity conservation with rural development in Tanzania's Wildlife Management Areas (WMAs). Although wildlife-related policies emphasize equitable benefit-sharing between conservation stakeholders and rural communities, there is limited empirical evidence on how these benefits are perceived by residents living within WMAs. Guided by social exchange theory (SET), this study posits that long-term community support for conservation depends on perceived fairness and relevance of WBT benefits. Understanding local perceptions of WBT benefits may be essential for shaping policy, such as determining which household-level benefits are acceptable and to whom, thereby ensuring long-term support for and the success of conservation efforts. Methods This study examined community perceptions of WBT benefits across three WMAs in northern Tanzania: Burunge, Enduimet, and Randilen. We administered 548 questionnaires and 20 key informant interviews. We assessed perceptions of different WBT benefits across four domains: employment, scholarships, capacity building and social services, including livelihood support. Using ordinal logistic regression, we examined how various socio-demographic variables predict perceived benefits and conducted a thematic analysis to contextualize the qualitative findings. Results While most respondents acknowledged some socioeconomic benefits from WBT, particularly in capacity building (70.0–87.3%) and access to social services and livelihood support (65.4–77.5%), these benefits were widely viewed as limited in both scope and impact. Employment emerged as the least perceived benefit (32.1–36.5%). Respondents' level of formal education, age, length of residence, and the WMA where they live explained perceived benefits from WBT. Conclusion Community perceptions are context-specific and tied to lived local experience. This emphasizes the need for designing context-specific benefit-sharing strategies that are inclusive, equitable and responsive to the diverse socio-economic needs of households within WMAs. Future WBT interventions should prioritize ensuring that rural communities receive the actual benefits and bridge the perceptual gap among residents with lower levels of formal education and those who are relatively new to the area, as these groups consistently reported lower recognition of WBT-related benefits. By tailoring engagement strategies and acknowledging socio-spatial diversity, WBT can better align benefits with community needs, enhance local support, and ensure the long-term success of conservation efforts.

Effectively managing human-wildlife interactions is crucial for fostering coexistence on shared landscapes. Management options are most effective when aligned with the preferences of people directly affected by wildlife, yet little is known about how socioecological factors influence these preferences. Integrating responses from 680 rural residents of northern Tanzania and remotely sensed data, we parameterized a Bayesian hierarchical model to test predictions of the hazard-acceptance model. We estimated how perceived costs and benefits, distance to protected areas, and the human footprint index mediate preferences for managing (preventing damage, compensating damage, reducing populations, and doing nothing) interactions with herbivore (elephant, giraffe, buffalo, zebra, wildebeest, and impala) and carnivore (lion, hyena, leopard, cheetah, honey badger, and jackal) species. Most respondents preferred management options that supported coexistence: prevention (41.9%), no management (38.0%), and compensation (11.1%). In contrast, population reduction (9.0%) was least preferred but more frequently selected for carnivores (13.4%) than herbivores (5.3%). Perceived costs strongly influenced management preferences. Respondents perceiving tangible costs were more likely to prefer prevention (posterior mean: 0.57 [95% credible interval 0.00 to 0.99]) over compensation (0.07 [0.00 to 0.66]) or population reduction (0.16 [0.00 to 0.87]), whereas those not perceiving costs leaned toward no management (0.40 [-0.74 to 1.78]). Though perceived benefits were less influential than costs, respondents associating species with intangible (0.10 [0.00 to 0.74]) or tourism benefits (0.06 [0.00 to 0.63]) were less likely to support population reduction than those perceiving no benefits (0.12 [0.00 to 0.82]). Distance to protected areas and the human footprint index had weaker, inconsistent effects, but random intercepts indicated substantial village-village variation in preferred management options. Our results suggest that conservation strategies should primarily address wildlife-related costs and foster coexistence by more equitably distributing benefits. A possible strategy could include investing tourism revenues into comanaged, locally tailored damage prevention measures.

Outdoor workers are at increased risk of tick-borne diseases, yet we poorly understand the interaction between occupational risk factors and worker behavior. This study integrates active tick surveillance with worker-reported survey data to assess how occupational behaviors, demographic characteristics, and tick-prevention knowledge influence exposure to infected ticks. We collected blacklegged ticks (Ixodes scapularis) from three Minnesota counties to determine the infection prevalence and density of infected ticks for Borrelia burgdorferi and Anaplasma phagocytophilum. Molecular surveillance was coupled with outdoor worker surveys that ascertained exposure characteristics to model individual-specific probabilities of encountering infected ticks during their job responsibilities. From May to July 2023-2024, 872 ticks were collected, where 45.6% (n = 398) were infected with B. burgdorferi and 7.2% (n = 78) were infected with A. phagocytophilum. Across both years, maximum infected tick densities peaked in Carlos Avery Wildlife Management Area at 0.80 (0.22 [IQR 0.16, 0.48]) per 100m2, were intermediate in Lake Elmo Park Reserve at 0.35 (0.12 [IQR 0.05, 0.18]) per 100m2, and lowest in Whitewater Wildlife Management Area at 0.25 (0.04 [IQR 0.02, 0.13]) per 100m2. Forty-two survey responses revealed individual probabilities of encountering infected ticks ranged from ~ 5 to 65% for B. burgdorferi and ~ 0-25% for A. phagocytophilum. Our results suggest that outdoor workers have a high probability of encountering infected ticks through occupational exposure, which was marginally associated with demographic factors (e.g., age) and preventive behaviors (e.g., tick checks, repellent use). This study reports elevated B. burgdorferi infection prevalence from adult (62.1%) and nymphal (36.5%) blacklegged ticks within Minnesota.

Ungulate browsing is a major driver of forest regeneration dynamics and habitat structure in managed temperate forests, influencing species composition, regeneration success, and long-term stand development. Traditional assessments of browsing impacts often rely on field-based indicators such as regeneration density or visual cover, but these metrics provide limited insight into three-dimensional habitat structure. Mobile handheld LiDAR offers highly detailed measurements of forest structure, enabling objective and reproducible quantification of structural complexity that complements and extends conventional field-based methods. In this study, we applied handheld LiDAR as an innovative indicator for habitat structure within the ungulate browsing zone (<2 m height) to evaluate structural development across sites differing in management context. Paired fenced and unfenced plots (12 × 12 m) were surveyed within the WiWaldI project framework in 2019 and 2023 and compared across three hunting regimes representing different degrees of ungulate population management. Structural complexity was quantified by deriving box-counting dimensions from LiDAR point clouds, providing a measure of spatial arrangement and density relevant to ungulate–vegetation interactions. To support interpretation and ecological context, we complemented LiDAR indicators with streamlined field assessments. Based on this framework, we assessed whether forest structural complexity and visual cover differ among regions and over time, and whether ungulate browsing induces detectable structural differences between fenced whether structural differences between fenced and unfenced plots are detectable. We further examined the relative importance of tree species composition, plant architecture, and hunting regime as drivers of three-dimensional habitat structure. A simplified octant method characterized the spatial distribution of woody regeneration, while a silhouette-based approach quantified visual cover from the perspective of a standard ungulate profile. These auxiliary measures contextualize visual and spatial aspects of structure that LiDAR metrics capture with minimal observer bias. LiDAR studies have previously demonstrated potential for linking high-resolution structural data to ungulate habitat use, and our approach extends this by focusing on structural complexity as a habitat indicator. Results show a consistent increase in LiDAR-derived structural complexity between 2019 and 2023 across all regions. This increase occurred across management contexts and was not consistently explained by fencing or hunting regime effects, suggesting that site conditions, forest composition, and successional processes were dominant drivers during the observation period. Hunting regime showed no statistically significant and no consistent effect on structural complexity across regions or years. Visual cover metrics varied strongly among regions and species and declined over time. These findings suggest that three-dimensional habitat structure information has the potential to enhance the evaluation of ungulate impacts and may support evidence-based forest and wildlife management, particularly when interpreted in the context of site conditions and successional dynamics. Beyond ungulate impact assessment, the presented handheld LiDAR approach provides a scalable remote sensing framework for precision forestry by capturing three-dimensional structural attributes that are directly linked to forest stability, resilience, growth dynamics, and stand-level species mixing, thereby supporting evidence-based forest management recommendations.

Competition plays a key role in shaping predator communities, but carrion abundance can alter these interactions. We investigated interactions between grey wolves (Canis lupus), an apex predator and golden jackals (Canis aureus), an opportunistic mesocarnivore, in carrion-rich regions of Greece, where livestock carcasses are frequently dumped by farmers. Using unmanned aerial vehicles with thermal imaging, handheld thermal cameras and camera traps, we recorded nearly 1100 wolf and over 9000 jackal sightings across landscapes. Our analyses showed that jackals fed and rested more often near abundant food, with larger carcasses leading to prolonged interactions. There was a strong positive relationship between carcass biomass and jackal group size, highly moderated by season, facilitating joint feeding and accelerating carrion consumption. Wolves feeding alongside jackals were mostly solitary, while jackals formed groups of around five, likely benefiting from reduced risk and greater feeding opportunities. Larger carcasses attracted more interactions between species, supporting our hypothesis that ample food supply reduces direct competition and fosters greater tolerance. However, competition persisted, as we recorded multiple cases of jackal food theft and a single fatal wolf-jackal encounter. These findings challenge rigid predator hierarchies, highlighting how resource abundance promotes coexistence and underscoring the need for effective wildlife management in food-abundant environments.

Conservation planning provides a structured, step-by-step process for making informed decisions by identifying, developing, and implementing actions to achieve specific goals and objectives. To date, there are limited examples within the academic literature that describe Indigenous-led conservation planning processes. Our research documents an Indigenous-led conservation planning initiative led by Xeni Gwet'in First Nation Government as they worked to design a wildlife management strategy for their Caretaker Area, located in British Columbia, Canada. Using a case-based approach, we describe the Xeni Gwet'in wildlife management strategy planning process- which included scoping, honoring the past, data inventory and review, action prioritization, and engagement- and associated strengths and challenges. Beyond the Xeni Gwet'in context, we distill adaptive planning tools and lessons learned for others- including Indigenous Nations and communities interested in conservation planning, and non-Indigenous governments and collaborators seeking to support Indigenous approaches to conservation, stewardship, and wildlife governance.

ABSTRACT Human – wildlife interactions range from beneficial to detrimental, affecting both biodiversity conservation and human well-being. In Europe, wild boar (Sus scrofa) populations have expanded due to environmental changes and conservation measures, intensifying conflicts and posing management challenges. This study examines these dynamics in southern Europe through the framework of nature’s contributions to people (NCP), using wild boar as a case study. Environmental rangers, who possess expert wildlife knowledge and maintain daily contact with rural residents, served as key informants to assess residents’ perceived beneficial and detrimental wild boar NCP, their relative importance, and the main social actors affected. We also evaluated rangers’ perceptions of wild boar population trends – anticipating links between trends and NCP – and documented management measures in use. Results indicate that, based on rangers’ knowledge, residents generally perceive wild boar as a conflict-causing species, with detrimental NCP outweighing beneficial NCP. Agricultural damage emerged as the primary detriment, making farmers the most affected group. Detrimental NCP were reported widely across surveyed areas regardless of socioeconomic context, whereas beneficial NCP were less frequent and lacked a consistent spatial pattern. Most management actions focus on species-level interventions, such as monitoring, population control, and recreational hunting, aiming to mitigate local-scale impacts. Overall, the study highlights the importance of recognizing both positive and negative roles of expanding wildlife in human societies. It further demonstrates the value of integrating local expert knowledge, such as that of rangers, with scientific approaches to inform holistic, adaptive wildlife management and to address the root causes of human – wildlife conflict.

As human activity increases worldwide, many ecologists have focused on how anthropogenic linear features (ALFs) such as roads and fences impact and disrupt animal space-use behavior and how this disruption could potentially affect population viability. The properties of an animal's occurrence distribution (OD), namely its size, shape, and habitat associations, reflect the animal's balance of costs and benefits and thus can act as indirect indicators of behavioral optimality. Measuring deviations from theoretical space-use optimality can provide insight into the non-lethal effects of ALFs on wildlife in different environmental contexts. Here, we focused on the seasonal space-use patterns of two wide-ranging, highly mobile species of great cultural and economic value: mule deer (Odocoileus hemionus; n = 3105) and pronghorn (Antilocapra americana; n = 320). We calculated the average use of six environmental and three ALF attributes, weighted by their intensity of use within the OD, and contrasted those with their respective average availability within a 100-km2 reference area centered on each animal's OD. We show that mule deer space-use is more impacted by roads, while pronghorn space-use is affected more by fences, specifically in the winter when snow depth may hinder their ability to cross fences. Our results highlight the dynamic nature of the availability domain and the importance of properly accounting for this dynamism in habitat selection analyses. This research expands on the theoretical literature of animal space use and their response to ALFs in a rapidly changing world and further provides practical strategies for wildlife managers to take when mitigating ALF impacts on their target species.

Robust monitoring of wildlife populations to guide interventions is fundamental to conservation and wildlife management. Understanding how landscape characteristics are influencing predator population dynamics is often vital to inform recovery strategies, management, and policy. The pine marten Martes martes is recovering in the UK; however, population spread has occurred at different rates across the country. We investigated how spatial variation in density of recovering pine marten populations is influenced by key habitat and human‐related factors. We genotyped non‐invasively collected pine marten hair samples collected through standardised surveys covering four landscapes in Scotland over three seasons. We applied a multi‐session, sex‐structured, spatial capture–recapture model to estimate within‐ and between‐landscapes spatial variation in density. We identify larger areas being used by individuals in recently recolonised areas compared to more established populations. We find significant differences in the spatial variation of density across landscapes ranging from 0.05 marten km − 2 (95% CI: 0.03–0.07) in the recently colonised Borders region of southern Scotland to 0.21 marten km − 2 (95% CI: 0.10–032) in the Trossachs region of central Scotland. There was substantial variation in pine marten density within landscapes. The amount of forest had a positive effect on population density, but not in the most recently recolonised population. Closer proximity to large gamebird shoots had a significant negative effect on pine marten density in one landscape suggesting that, despite being protected in law, pine martens suffer sufficiently elevated mortality close to some pheasant pens to locally depress their density. We did not find an effect of distance to nearest major road on spatial variation in population density in any landscape. While the mechanistic processes driving these patterns are not clear, our work highlights the importance of elucidating the processes underlying these effects of forest and land management.

Wildlife rehabilitation and relocation are valuable strategies to mitigate the biodiversity crisis caused by human activities. These processes, however, often face challenges such as high costs, habitat unsuitability, and increased post-release stress and mortality. The lack of proper guidelines, trained personnel, and ethical standards results in suboptimal outcomes, compromising both animal welfare and environmental health. This study examines ethical and technical dimensions of these practices, emphasizing their conservation implications. It combines a literature review with a survey of 104 wildlife managers from multiple countries, conducted between May and December 2022. The findings reveal central factors—procedural, political, social, biological and ecological—that determine the success of wildlife rehabilitation. Ethical concerns included excessive human–animal interaction, leading to imprinting, taming, and habituation. Other obstacles were veterinary errors, bureaucratic inefficiencies, and poor environmental education. Carnivores, primates, raptors, psittacine birds, and species facing extirpation threats were particularly prone to failure. To improve outcomes, it is important to critically assess current practices from planning to implementation. Ethical wildlife management requires acknowledging that Nature does not belong to us, and our participation should be guided by responsibility and limited to essential restoration efforts. Finally, true commitment to biodiversity conservation lies not in increasing interventions, but in reducing the human pressures that make them necessary in the first place.

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.

Abstract Accurate population estimates are essential for wildlife management, providing critical insights into species abundance and distribution. Traditional survey methods, including visual aerial counts and GNSS telemetry tracking, are widely used to monitor muskox ( Ovibos moschatus ) populations in Arctic regions. These approaches are resource‐intensive and constrained by logistical challenges. Advances in remote sensing, artificial intelligence, and high‐resolution aerial imagery offer promising alternatives for wildlife detection. Yet, the effectiveness of deep learning object detection models (ODMs) is often limited by small datasets, making it challenging to train robust ODMs for sparsely distributed species like muskoxen. This study investigates the integration of synthetic imagery, created with diffusion‐based models, to supplement limited training data and improve muskox detection in zero‐shot and few‐shot settings. We compared a baseline model trained solely on real imagery with five zero‐shot (ZS1–ZS5) and five few‐shot (FS1–FS5) models that incorporated progressively more synthetic imagery in the training set. For the zero‐shot models, where no real images were included in the training set, adding synthetic imagery improved detection performance. As more synthetic images were added, performance in precision, recall, and F1 score increased, but eventually plateaued, suggesting diminishing returns when synthetic images exceeded 100% of the baseline model training dataset. For few‐shot models, combining real and synthetic images led to better recall and slightly higher overall accuracy compared with using real images alone, though these improvements were not statistically significant. Our findings demonstrate the potential of synthetic images to train accurate ODMs when data are scarce, offering important perspectives for wildlife monitoring by enabling rare or inaccessible species to be monitored and to increase monitoring frequency. This approach could be used to initiate ODMs without real data and refine it as real images are acquired over time.

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.

The White-backed Vulture Gyps africanus is Critically Endangered because of its decline across its range in Africa, largely due to poisoning. The western corridor of the Serengeti ecosystem in northern Tanzania hosts a significant number of individuals of this species. However, there is no published information on the breeding population status and breeding success. Here, we report findings from five riparian aerial surveys conducted between 2013 and 2021 in the Ikorongo and Grumeti Game Reserves and the Ikona Wildlife Management Area, and examine changes in nest encounter rates. Nest surveys were conducted in 2021 and 2022 to examine breeding success and nesting site preferences. To better understand the potential drivers of the observed trends, we assessed changes in riparian tree cover between 2012 and 2020 using remote sensing techniques. The nest encounter rate within the survey area declined from 0.99 nests km−1 in 2013 to 0.43 nests km−1 in 2021. The breeding success was 29.4%, which was significantly lower than that reported in other sites. Tree cover declined by 28% during the study period and results suggest that habitat loss may be a contributing factor to the observed declines in the breeding population, but further investigation is needed. White-backed Vultures in the Serengeti ecosystem require continued monitoring, assessment of the drivers of tree cover decline and investigation of breeding population dynamics and the key factors influencing breeding success.

Abstract Accurate and reliable estimation of wildlife population density is fundamental to effective conservation and management. While camera traps show potential for monitoring ground‐dwelling mammal densities, labour‐intensive data processing remains a significant constraint. Ideally, conservation efforts would benefit from the continuous monitoring of multiple species across broad spatial scales; however, the time and effort required for data processing make achieving this challenging. We developed the RAD‐REST (Random Encounter and Staying Time model Relying on All Detections) model, an extension of the Random Encounter and Staying Time model, to enable multi‐species density monitoring with substantially reduced effort. By explicitly modelling the probabilistic process of animals entering a predefined focal area, our model allows density estimation by analysing entry counts and staying times in only a subset of videos, while incorporating trapping rates from all video data. We also developed a user‐friendly R package ‘ctrest’ to implement the model's fully Bayesian framework, including estimation of activity levels. Using data from the Boso Peninsula, Japan, we conducted Monte Carlo simulations to determine the number of videos required to achieve (1) standard precision for density estimation (coefficient of variation, ) and (2) more stringent wildlife management standards (). The RAD‐REST model produced unbiased estimates with appropriate coverage rate. Although the original REST model showed superior precision, RAD‐REST model achieved acceptable estimation precision with dramatically reduced analytical effort. To reach acceptable values (≤0.35) using a 200‐camera array, most species (10 of 12) required analysing only 100 videos for entry counts and measuring staying times in videos with ≥1 entry (approximately 60%–70% of analysed videos). For higher precision (), a larger 400‐camera network was necessary, requiring analysis of 7.00% (single‐species) or 6.45% (multi‐species) of total expected videos (>ca. 40,000 videos). Although precise estimates might still demand substantial effort, the RAD‐REST model enables cost‐effective monitoring by either supplementing photo‐trap arrays with a subset of video data or deploying dedicated video cameras across a portion of the network. This approach marks a critical advance towards large‐scale monitoring efforts, enabling more robust, multi‐species density estimation across diverse ecological contexts.

The National Park Service (NPS) faces a paradoxical dual mandate-to preserve invaluable environmental and cultural resources for future generations and to ensure their public accessibility for recreational enjoyment. Yet with >124 million visitors in 2019, the US national parks (NPs) are at risk of being "loved to death" a challenge faced by protected areas the world over. This growing demand for ecosystem services calls for new strategies to enhance public appreciation and commitment to protecting natural capital. Against this backdrop, we analyzed the structure and dynamics of the NP system through a public-facing lens constructed from >426,000 digital media articles mentioning at least one park by its official name. Our analysis reveals that from 2010 to 2019, NP media visibility grew by over 3,900%, outpacing 29% growth in visitation, and a 15% decline in federal budget support for NPs. We find that this disproportionate media growth is driven by tourism-oriented articles referencing multiple NPs, which has become the principal driver of NP system integration in the public sphere. Consequently, ecotourism marketing has displaced public attention from critical issues associated with environmental, wildfire and wildlife management. With many NPs operating at or near capacity, tourism-driven integration of the NP system may intensify fundamental tensions within the NPS dual mandate, as rising demand for ecosystem services collides with limited federal resources and growing environmental risks.

Automatic recognition of endangered animal behavior is crucial for biodiversity conservation and improving animal welfare, yet traditional manual observation remains inefficient and invasive. This work contributes directly to sustainable wildlife management by enabling non-invasive, scalable, and efficient monitoring, which supports long-term ecological balance and aligns with several United Nations Sustainable Development Goals (SDGs), particularly SDG 15 (Life on Land) and SDG 12 (Responsible Consumption and Production). The current deep learning approaches often struggle with the scarcity of behavioral data and complex environments, leading to poor model generalization. To address these challenges, this study focuses on endangered animal behavior monitoring and proposes a multimodal learning framework termed ABCLIP. This model leverages multimodal contrastive learning between video-and-text pairs, utilizing natural language supervision to enhance representation ability. The framework integrates pre-training, prompt learning, and fine-tuning to optimize performance specifically for small-scale animal behavior datasets, with a focus on the specific social and ecological behaviors of giant pandas. The experimental results demonstrate that ABCLIP achieves remarkable accuracy and robustness in recognizing endangered animal behaviors, attaining Top-1 and Top-5 accuracy of 82.50% and 99.25%, respectively, on the LoTE-Animal dataset, which outperforms strong baseline methods such as SlowFast (78.54%/97.55%). Furthermore, in zero-shot recognition scenarios for unseen behaviors, ABCLIP achieves an accuracy of 58.00%. This study highlights the potential of multimodal contrastive learning in wildlife monitoring and provides efficient technical support for precise protection measures and scientific management of endangered species.

Abstract Wildlife trafficking represents a significant and complex form of organised crime. This study aimed to understand the challenges and opportunities related to countering organised wildlife trafficking, based on the perceptions of wildlife law enforcement personnel and other experts. Interviews were conducted with 112 individuals working to counter wildlife trafficking in South Africa, Hong Kong, and Canada, and several additional relevant jurisdictions. Interviewees reported the use of organised crime tactics by wildlife traffickers, including money laundering, corruption, violence, marketing, countersurveillance, and compartmentalisation. Despite this, many interviewees often felt unsupported by their governments and expressed concerns that the issue is inadequately prioritised, under-resourced, and under-staffed. Wildlife law enforcement agencies face a multitude of barriers to sharing information and collaborating within and outside of their borders, including legal barriers, bureaucracy, politics, ego, trust, fear, and a lack of will/interest among supporting law enforcement agencies. Interviewees also noted that there is often a reluctance to conduct complex advanced investigations into wildlife trafficking syndicates. Significant changes to law enforcement organizational culture and broader systemic changes are required to more effectively combat the innovative strategies of wildlife traffickers.

The State of Alaska, USA, has a long and controversial history of controlling predators to enhance ungulate populations, including moose (Alces alces). Moose management is complicated by a dual system in which the Federal and State governments prioritize harvesting moose for human consumption over other considerations, such as trophy or sport hunting, but have conflicting regulations regarding who is eligible to harvest moose. Wildlife management for the State is overseen by the Alaska Board of Game (BOG), with advice from the Alaska Department of Fish and Game (ADFG). In accordance with its Intensive Management Policy, the BOG establishes regulations promoting the harvest of moose and other ungulates for human consumption. This typically occurs by controlling bears (Ursus americanus and U. arctos) and gray wolves (Canis lupus) in anticipation of increasing ungulate harvests, often without adequate information on the status and ecology of predator or ungulate populations. We provide a narrative and integrative review of moose population dynamics to help resolve those issues. We argue that the current management of moose and their predators in Alaska does not encompass a full range of management options and fails to consider or implement important aspects of their population dynamics. Predators maintain some moose populations at a low density, reducing the harvest of moose but promoting large-antlered individuals, which are of value to Alaska's professional guide and tourism industries. Using modern models of population dynamics of moose and other ungulates, we argue that if the proximity of the moose population to K (the ecological carrying capacity) is known, management strategies that increase the human harvest of moose and also promote large-antlered trophies are not mutually exclusive. We list life history and population characteristics to help determine the nutritional status of moose populations in relation to K, thereby guiding wise management of that valuable resource. We also recommend an adaptive management approach to assessing the effects of such activities. We caution, however, that to wisely manage these important wildlife resources, more information on the dynamics of moose and their predators is necessary. A system that embraces more biology and fewer politics would provide greater opportunities to employ the best science in the management of moose and their predators.