Wildlife Resources Research Articles

Effects of Oil Exploration on Wildlife Resources in Murchison-Semliki Landscape

Effects of Oil Exploration on Wildlife Resources in Murchison-Semliki Landscape

Use of wildlife-friendly structures in residential gardens by animal wildlife: evidence from citizen scientists in a global biodiversity hotspot

Private gardens comprise a large component of greenspace in cities and can offer substantial conservation opportunities. There has been strong advocacy from researchers, policymakers, and conservation practitioners to engage householders in wildlife-friendly gardening practices to increase the quantity, quality and connection of habitat resources for urban wildlife. Despite this call to action, there remains limited knowledge on the use and benefit of some wildlife-friendly structures within gardens, such as artificial refuges and water sources. In collaboration with 131 citizen scientists in southwestern Australia, we examined the use of seven wildlife-friendly structure types by four vertebrate taxa groups. Following 2841 wildlife surveys undertaken between 31 July 2022 and 22 February 2023, we found that all structures were used primarily by target taxa, water sources were often used by relatively common species, certain structures such as possum shelters were used by rare and threatened species (e.g. western ringtail possum), and that there was evidence of animals making use of the wildlife-friendly structures for reproduction (e.g. bird eggs in nest boxes and tadpoles in water sources). Water sources were used more frequently and by a greater diversity of wildlife than artificial refuges. In particular, bird baths were used by the highest number of species (mainly birds) while ponds were used by the greatest variety of taxa (birds, reptiles, frogs, mammals). Our findings provide evidence-based support for the advocacy of wildlife-friendly gardening practices and further highlight the role of residential gardens for biodiversity conservation.

Survey of the medicinal use of wild animals and their by-products in Ibadan, Southwestern Nigeria

ABSTRACT In many tropical countries, the use of wild animals, plants and their by-products for traditional medicine is very popular. The Bode Wasinmi Wildlife Market in the Ibadan metropolis was intentionally selected for this study to investigate which wild animals and/or their body parts, were being sold for traditional medicinal purposes. The study was conducted using both quantitative and qualitative research designs, with data being collected by randomly administering 150 semi-structured questionnaires, coupled with key informant interviews, to traditional medicine vendors and ‘Baba Oloja’. In total, 15 bird, 13 mammal and 5 reptile species or their various parts were sold and used for medicinal purposes. Various parts of wild animals and their derivatives are commonly sold at the market for either spiritual fortification or curing illnesses ranging from viral infections to aches and pains to epilepsy. In terms of the conservation statuses of the wild animal species on display in the market, 12 were common (not of concern by (IUCN) International Union for Conservation of Nature status), 11 were of least concern, 4 were vulnerable, 2 were endangered and 5 were critically endangered. We conclude that the use of wild animals for traditional medicine is widespread in the area regardless of the conservation status of the species. Improved access to effective and affordable health care as well as conservation education is therefore recommended as a long-term solution to prevent the further depletion of wildlife resources.

Reviewing the role of AI in environmental monitoring and conservation: A data-driven revolution for our planet

The rapid increase in human activities is causing significant damage to our planet's ecosystems, necessitating innovative solutions to preserve biodiversity and counteract ecological threats. Artificial Intelligence (AI) has emerged as a transformative force, providing unparalleled capabilities for environmental monitoring and conservation. This research paper explores the applications of AI in ecosystem management, including wildlife tracking, habitat assessment, biodiversity analysis, and natural disaster prediction. AI's role in environmental monitoring and conservation includes wildlife tracking, habitat assessment, resource conservation, biodiversity analysis, and species identification. AI algorithms analyze camera trap footage, drone imagery, and GPS data to identify and estimate population sizes, leading to improved anti-poaching efforts and enhanced protection of diverse species. Habitat assessment and resource conservation involve AI-powered image analysis, which aids in assessing forest health, detecting deforestation, and identifying areas in need of restoration. Biodiversity analysis and species identification are achieved through AI algorithms that analyze acoustic recordings, environmental DNA (eDNA), and camera trap footage. These innovations identify different species, assess biodiversity levels, and even discover new or endangered species. AI-powered flood prediction systems provide early warnings, empowering communities with better preparedness and evacuation efforts. Challenges, such as data quality and availability, algorithmic bias, and infrastructure limitations, are acknowledged as opportunities for growth and improvement. In policy and regulation, the paper advocates for clear frameworks prioritizing data privacy and security, algorithmic transparency, and equitable access. Responsible development and ethical use of AI are emphasized as foundational pillars, ensuring that the integration of AI into environmental conservation aligns with principles of fairness, transparency, and societal benefit.

Satellite-based phenology analysis of the Hyrcanian forest in the Alborz mountains and Caspian Sea shores, Iran

ABSTRACT The Caspian Sea and the Hyrcanian forest rely on each other to maintain balanced hydrological and climatological conditions and preserve the local wildlife and natural resources. Climate variation impacts this balance and the ecological status of the forest. In this study, thermal and phenological seasonality in three Hyrcanian protected areas is evaluated over a period of 33 years (1987–2019). The results suggest extensions of 3–18 days per decade in growing seasons. This could be mitigated by applying policies such as the expansion of protected areas, stringent endangered species conservation, updated silviculture practices, social awareness and cross-sectoral management.

Leveraging limited data from wildlife monitoring in a conflict affected region in Venezuela

Efficient monitoring of biodiversity-rich areas in conflict-affected areas with poor rule of law requires a combination of different analytical approaches to account for data biases and incompleteness. In the upland Amazon region of Venezuela, in Canaima National Park, we initiated biodiversity monitoring in 2015, but it was interrupted by the establishment of a large-scale mining development plan in 2016, compromising the temporal and geographical extent of monitoring and the security of researchers. We used a resource selection function model framework that considers imperfect detectability and supplemented detections from camera trap surveys with opportunistic off-camera records (including animal tracks and direct sighting) to (1) gain insight into the value of additional occurrence records to accurately predict wildlife resource use in the perturbated area (deforestation, fire, swidden agriculture, and human settlements vicinity), (2) when faced with security and budget constraints. Our approach maximized the use of available data and accounted for biases and data gaps. Adding data from poorly sampled areas had mixed results on estimates of resource use for restricted species, but improved predictions for widespread species. If budget or resources are limited, we recommend focusing on one location with both on-camera and off-camera records over two with cameras. Combining camera trap records with other field observations (28 mammals and 16 birds) allowed us to understand responses of 17 species to deforestation, 15 to fire, and 13 to swidden agriculture. Our study encourages the use of combinations of methods to support conservation in high-biodiversity sites, where access is restricted, researchers are vulnerable, and unequal sampling efforts exist.

A mixed black and whitelist approach for wildlife trade regulation in China: Biodiversity conservation is made of shades of gray

AbstractThe Kunming‐Montreal Global Biodiversity Framework requires effective actions to bend the curve of biodiversity loss by 2030. Wildlife trade, a direct drive of biodiversity decline, calls for more effective regulations to both protect wildlife populations in the wild and facilitate sustainable use of wildlife resources to meet human needs. This call has become particularly urgent in light of the COVID‐19 pandemic. In 2021, China's List of State Key Protected Wild Animals, a list of fauna under the strictest protection by national legislation, has been updated in the year 2021, 32 years after its first release, increasing its coverage (from the original 13%) an 11% of species across taxa. Combined with the updated List of State Protected Terrestrial Wild Animals which covers species with lower protection priority, these two national lists already cover 77% terrestrial vertebrate species of China. Such a blacklist approach, placing threatened species under a list of legal protection, is a common practice globally in species conservation. We discussed pros and cons of this dominant strategy and further explored the potential integration with a whitelist approach, listing all wildlife and only permitting regulated uses of certain species. We propose a mixed approach combining black and whitelists at different administration levels which could perhaps be first adopted in China. This is mainly due to the fact that in addition to illegal harvesting from the wild, traded wildlife in China are mostly from captive breeding and related laundering of wild‐caught animals.

Enhancing unmanned aerial vehicle capabilities: integrating YOLO algorithms for diverse industrial applications

The integration of UAVs with advanced deep learning algorithms, particularly the You Only Look Once models, has opened new horizons in various industries. This paper explores the transformative impact of YOLO-based systems across diverse sectors, including agriculture, forest fire detection, ecology, marine science, target detection, and UAV navigation. We delve into the specific applications of different YOLO models, ranging from YOLOv3 to the lightweight YOLOv8, highlighting their unique contributions to enhancing UAV functionalities. In agriculture, UAVs equipped with YOLO algorithms have revolutionized disease detection, crop monitoring, and weed management, contributing to sustainable farming practices. The application in forest fire management showcases the capability of these systems in real-time fire localization and analysis. In ecological and marine sciences, the use of YOLO models has significantly improved wildlife monitoring, environmental surveillance, and resource management. Target detection studies reveal the efficacy of YOLO models in processing complex UAV imagery for accurate and efficient object recognition. Moreover, advancements in UAV navigation, through YOLO-based visual landing recognition and operation in challenging environments, underscore the versatility and efficiency of these integrated systems. This comprehensive analysis demonstrates the profound impact of YOLO-based UAV technologies in various fields, underscoring their potential for future innovations and applications.

Potential of floral and fruit resources for wildlife of tree species suitable for urban afforestation in São Paulo: in search of a biodiverse city

RESUMO Árvores fornecem habitat e recursos para a fauna residente e transiente nas cidades. A escolha de espécies arbóreas para plantio urbano segue critérios multifatoriais, mas pouco considera os recursos que elas disponibilizam para a fauna. Objetivamos identificar grupos funcionais de 154 espécies arbóreas nativas indicadas para plantio urbano do município de São Paulo a partir dos recursos florais e frutíferos disponibilizados para visitantes florais e frutíferos potenciais. Observamos um número proporcional de espécies com dispersão abiótica e biótica e um predomínio de espécies de arbóreas polinizadas por abelhas ou com frutos carnosos consumidos por aves. Propusemos oito grupos funcionais caracterizados pelo compartilhamento de visitantes florais e frugívoros potenciais que apresentaram uma riqueza desigual. Uma escolha focada na identificação taxonômica e porte das espécies pode promover uma alta redundância funcional e impactar a riqueza de interações planta-animal e diminuir a permeabilidade das cidades para fauna.

Utilization Practices and Conservation Impacts of Endangered Wildlife in Asian Countries

The Asian region is globally renowned for its unparalleled biodiversity, rich ecosystems, and unique cultural heritage. However, the delicate equilibrium between human societies and the diverse flora and fauna faces increasing challenges due to the region's rich biodiversity and escalating utilization of wildlife resources. Hence, this paper aims to document the utilization of endangered wildlife across Asian countries and to report the existing conservation measures and recommendations for sustainable wildlife management over the years. We employed prominent academic databases, specifically SCOPUS, to explore the dynamics of wildlife utilization and its associated implications. From the findings, 9,989 records were successfully identified. However, only 65 articles were included in the review after the screening process. A total of 61 species, comprising 30 mammals, 22 reptiles, one amphibian, and eight birds, all endangered, were identified as subjects of wildlife utilization in 16 Asian countries. China possessed the highest count for wildlife utilization across all categories, including 15 species used for trading purposes. In conclusion, this research underscores the critical need for integrated approaches that balance human needs and conservation imperatives to ensure a sustainable future for Asia's wildlife biodiversity.

AUTOMATIC VIDEO DETECTION FOR GOLDEN MONKEYS IN SHENNONGJIA NATIONAL PARK, CHINA

Abstract. Infrared-triggered cameras serve as essential tools for wildlife resource surveys, allowing camera traps to capture wildlife activity while minimizing the impact on the ecosystem. Traditional monitoring methods heavily rely on human resources for visual discrimination, which is inefficient and susceptible to environmental influences. Therefore, this paper focuses on Shennongjia National Park as a case study to address the limitations of traditional approaches. We constructed a Shennongjia wildlife object detection dataset using video data from the fixed-erected infrared cameras and proposed a supervised learning-based automatic monitoring method for golden monkeys, aiming to achieve intelligent target detection. With these processing results, we were able to capture golden monkeys' tracks and conduct statistical analysis of their life range and distribution characteristics. Through the integration of sensors and deep learning techniques, we developed a golden monkeys detection monitoring system to visualize the monitoring results and assess the spatial and temporal distribution characteristics of golden monkeys’ activities.

Trophic downgrading of an adaptable carnivore in an urbanising landscape

Urbanisation critically alters wildlife habitat and resource distribution, leading to shifts in trophic dynamics. The loss of apex predators in human-transformed landscapes can result in changes in the ecological roles of the remaining mesocarnivores. Decreased top–down control together with increased bottom–up forcing through greater availability of anthropogenic foods can result in a predation paradox. Understanding these changes is important for conserving ecological function and biodiversity in rapidly urbanising systems. Here, we use stable isotope analysis to provide insight into longer term changes in trophic position, niche width and overlap of an elusive, medium-sized urban adapter, the caracal (Caracal caracal) in and around the city of Cape Town, South Africa. Using fur samples (n = 168) from individuals along a gradient of urbanisation we find that overall caracals have a broad isotopic dietary niche that reflects their large variation in resource use. When accounting for underlying environmental differences, the intensity of anthropogenic pressure, measured using the Human Footprint Index (HFI), explained variation in both food subsidy use (δ13C values) and trophic status (δ15N values). The significantly higher δ13C values (P < 0.01) and lower δ15N values (P < 0.001) of caracals in more urbanised areas suggest that predator subsidy consumption occurs via predictable, anthropogenic resource subsidies to synanthropic prey. These prey species are predominantly primary consumers, resulting in shifts in diet composition towards lower trophic levels. Further, caracals using areas with higher HFI had narrower isotope niches than those in less impacted areas, likely due to their hyperfocus on a few lower trophic level prey species. This pattern of niche contraction in urban areas is retained when accounting for caracal demographics, including sex and age. The removal of apex predators in human-transformed landscapes together with reliable resource availability, including abundant prey, may paradoxically limit the ecological influence of the remaining predators, and bring about a degree of predator trophic downgrading. The dampening of top–down control, and thus ecosystem regulation, likely points to widespread disruption of trophic dynamics in rapidly developing areas globally.

Land-Use Conflicts and an Alternative Wildlife Management Option for the Loliondo Game-controlled Area, Tanzania: Insights from a Community Survey

Summary This tourism case study pays attention to natural resource management conflicts surrounding the Loliondo Game-controlled Area which encompasses 4000 km 2 adjacent to Serengeti National Park and Ngorongoro Conservation Area in Tanzania. Maasai, the largest nomadic pastoralist ethnic group in Tanzania, accounts for the overwhelming majority of the population residing in the Loliondo Game-controlled Area. The Loliondo Game-controlled Area has suffered from land-use and property-right conflicts among stakeholders despite establishing a series of wildlife management policies concerning the area. Trophy-hunting tourism has been operated in the Loliondo Game-controlled Area by a transnational private corporation with the Tanzanian government’s exclusive permission. Trophy hunting conflicts with other land uses in the Loliondo Game-controlled Area, including non-consumptive tourism, pastoral livelihoods, and crop farming. Although the Village Land Act 1999 recognizes customary rights vested with local villages to wildlife management in the Game-controlled Areas, the Maasai communities in the Loliondo Game-controlled Area have yet to reap benefits from trophy hunting or photography tourism. To identify an alternative wildlife management option preferred by the Maasai communities, a community survey was conducted in 2018. A sample of 330 households was surveyed, with 55 in each of the six selected villages in the Loliondo Game-controlled Area. The survey confirmed that the Maasai communities were not involved in the decision-making process for wildlife management. This study has found that the Maasai communities strongly support establishing a Joint Venture Wildlife Management Area of 1500 km 2 within the Loliondo Game-controlled Area, with the remaining 2500 km 2 being allocated to grazing, farming, and human settlements. Under the Joint Venture Wildlife Management Area scheme, local villages would jointly manage wildlife and be entitled to rights to manage and use wildlife and other natural resources in the region. The overwhelming majority of the participants in the community survey were optimistic that the co-management scheme would help enhance natural resource management efficiency and social equity. Information © The Authors 2023

Characterizing North Carolina black bear (Ursus americanus) populations using UrsaPlex v2.0

American black bears (Ursus americanus) have been successfully restored in North Carolina (NC) due to management and research efforts by the North Carolina Wildlife Resources Commission and various partners. Investigations by law enforcement in NC involving black bears typically center on a) illegal take, b) purchase, possession, and sale of bear parts, or c) human-bear interactions. Effective prosecution of illegal parties requires methods that permit individual identification of black bears. Typically, individualization is achieved using robust DNA profiling and comparison to accepted genetic databases. Currently, a genetic database of highly variable loci genotyped from black bears across their range in NC does not exist. To address this, we focused on genotyping NC black bears using an updated version of UrsaPlex (UrsaPlex v2.0), a short tandem repeat (STR) panel of 11 loci and three sex-linked markers, previously developed to permit individualization for California black bears. Biological samples were obtained from NC black bears following IACUC approved protocols. Total genomic DNA was isolated from each sample and genotyped using UrsaPlex v2.0. The number of alleles in the final genotyped population (n = 173) ranged from five (UamD118 and UamB8) to 33 (UamA9). The observed heterozygosity (Ho) ranged from 0.471 (UamB1) to 0.872 (UamA9), while the expected heterozygosity (He) ranged from 0.469 (UamB1) to 0.919 (UamA9). The probability of identity (PID) was calculated as 6.9 × 10-13. These results demonstrate the potential utility of UrsaPlex v2.0 for permitting individual identification of NC black bears for use in forensic casework and for population management.

Developing One Health capacity and networks through virtual training

The Food and Agriculture Organization of the United Nations (FAO) Virtual Learning Centers (VLCs) deliver online tutored courses with the aim of developing field capacity to integrate wildlife and ecosystem elements to approach One Health challenges. These courses also aim to create networks of professionals under the One Health umbrella. These courses cater to professionals from a variety of organizations and with a wide range of expertise, including animal health, public health, wildlife and natural resource management. The courses combine self-directed interactive modules with virtual workshops focusing on problem-based learning case studies (PBLs). Additionally, participants are encouraged to participate in an online asynchronous discussion forum. Each course is delivered for multiple countries within a FAO region and is tailored to cover specific One Health topic areas. Once the topic area is defined, subject matter experts and the regional VLC build the training activities by developing course-specific PBLs and selecting up to five self-directed modules that introduce concepts related to those PBLs from the course catalog of training materials. The development of the training materials and the delivery of each course involves a multidisciplinary team of professionals from different countries and backgrounds. The course was piloted for the Pacific Islands in 2021 and then run for other regions such as Southern Africa and Eastern Africa. In the future, this training activity could also be delivered in a blended format, combining virtual learning with face-to-face workshops.

Rational Use of Specially Protected Natural Areas of the Rostov Region, as Elements of the Ecological Framework of the Region

The unfavorable ecological situation, as a result of anthropogenic activity, contributed to the emergence of the need to protect natural massifs and the formation of specially protected natural territories (ООPT). Currently, protected areas perform the most important function of preserving and re-storing wildlife resources, thereby being the most effective mechanism for maintaining the ecological balance of territories and preserving natural biodiversity. The article deals with specially protected natural areas of the Rostov region as elements of the region's ecological framework system.

Check List, Status, Threat and Perception of Some Wildlife Species in the Three Ecological Zones of Adamawa State, Nigeria

The study was conducted to produce the status of some wildlife species and determine the threat factors and perceptions of wildlife species in the three (3) ecological zones of Adamawa state. The study tool consists of a structured questionnaire, multi-stage and simple random sampling techniques used for data collection. Descriptive statistics with Kiringe and Okello (2007) model were used for data analysis. Results indicated that 70, 72 and 75 species of wildlife belonging to 36, 38 and 39 families were listed in the Sudan, Northern guinea and Southern guinea savannah zones, respectively. Most of the species in the three zones were either rare, endangered or have gone into local extinction. Only nine (9) species were common in the Sudan savannah zone, eleven (11) in the Northern guinea savannah zone and twenty-two (22) in the Southern guinea savannah zone. There were no abundant species in the three (3) zones. The threat factors which consistently showed the highest prevalent threat index were farming (26.0 - 45.4), hunting (32.2 – 55.4), logging (12.5 - 80) and grazing (11.2 – 17.0). The wildlife habitat susceptibility index was highest in the Sudan savannah zone (100%) but least in the Southern guinea zone (83%). Hunting (0.32 – 0.55), farming (0.26 – 0.45), logging (0.13 – 0.18) and grazing (0.12 – 0.17) consistently showed the highest mean score threat factors in the three zones. Similarly, hunting (0.00033 – 0.00010), farming (0.0023 – 0.00028), logging (0.0009 – 0.00020) and grazing (0.0009 – 0.00013) consistently showed the highest relative threat factors severity index in the three zones. Wildlife species were perceived as something good by the majority of respondents in the three (3) ecological zones. The study recommended the acquisition of skills in areas such as craft making, tailoring, shoe and bag making, motor mechanic, carpentry, mason and modern agricultural practice to prevent the local dwellers from hunting, indiscriminate expansion of agricultural land areas, illegal logging, grazing and wildfires. Policy on population control should be formulated by the government in view of increasing pressure on natural resources, which include wildlife resources. Adequate policy and institutional framework should be put in place for the purpose of management and conservation of wildlife resources at the grass root level. The state government should strengthen its conservation education programmes on the intrinsic value of wildlife to society and stiffer penalties for illegal poachers and hunters to mitigate further illegal harvesting of wildlife.

A method for automatic identification and separation of wildlife images using ensemble learning

Camera traps have revolutionized wildlife resource surveys by enabling the acquisition of comprehensive ecosystem information. Camera traps usually produce massive images. Snapshot datasets captured in nature reserves proximate to human habitation often comprise a significant volume of human activity images containing humans or livestock. Manually identifying and labeling wildlife images from large-scale datasets is a labor-intensive task that necessitates a substantial number of professionals and incurs expensive personnel costs. By harnessing the capabilities of deep learning technology to automatically differentiate between wildlife and human activity images, ecologists can solely focus on manually labeling wildlife images that account for a minor fraction of the dataset. This strategic shift can significantly reduce personnel expenses and enhance work efficiency. Existing research usually treats human activity images as ordinary categories and utilizes species recognition methods to automatically identify and filter them. However, when human activity images overwhelmingly predominate the dataset, established species recognition methods are susceptible to misclassifying a substantial proportion of wildlife images as human activity images. This misclassification can potentially result in ecologists missing opportunities to discover or observe wildlife. To tackle this challenge, we proposed an ensemble learning method based on a conservative strategy and current mainstream deep learning frameworks to automatically identify wildlife and human activity images. We validated our method on a camera trap dataset from Lasha Mountain (LSM) in Yunnan, China. The experimental results demonstrated that our method automatically identified wildlife images from the dataset with accuracy, recall, and precision of 95.75%, 94.07%, and 83.89%, respectively. This led to an approximately 80% reduction in personnel costs.

{NCIFD} — An Internal R Package for a Fisheries Agency

We developed an R package for the Inland Fisheries Division of the North Carolina Wildlife Resources Commission to help team members share R functions and data sets. The {NCIFD} package stores several functions that were developed for agency research, including cleanBIODE(), which cleans query results from a database of standardized fish samples and imports the data into an R session. In addition, {NCIFD} stores a variety of data sets including observations from ongoing research projects, hatchery records, and administrative information. Stored in a package, data sets are instantly available for exploration and analysis in an R session, can share a common naming convention, and retain their metadata. Although developing an R package requires effort, we believe it is a useful tool that other fisheries agencies should encourage interested staff to explore. We share advice to help others get started while avoiding some missteps we encountered.

An osteometric analysis of elk (Cervus elaphus manitobensis) from Great Smoky Mountains National Park

AbstractTeeth are commonly preserved in the zooarchaeological record and can be used to estimate the age of individuals in a faunal assemblage. However, there are currently no criteria for discerning the sex of elk based on dental metric characteristics. Here, we present the results of an osteometric analysis of modern elk (Cervus elaphus manitobensis) from Great Smoky Mountains National Park to create an age profile for the sample, establish metrical parameters for evaluating sex, and discern the relationship between age and size. The analysis of tooth development stages in younger elk was combined with the assessment of occlusal wear in older elk to create an age profile of our sample population. The length and breadth of mandibular third molars produced bimodal distributions that suggest these measurements can be used to differentiate sex in this population, and diastema length showed a curvilinear association with age (R2 = 0.71). This dataset provides a useful comparative sample for future studies on ageing and sexing in zooarchaeology, conservation paleobiology, and wildlife resources management.