Search Results (8)

The deployment of wildlife fences in Africa serves as a crucial intervention to balance wildlife conservation with human safety and agricultural productivity. This review synthesizes current research and case studies to provide a comprehensive understanding of the implications, benefits, and drawbacks of wildlife fencing in Africa. Information was drawn from 54 articles selected through a thorough search of the Web of Science and Scopus databases. Results indicate that the primary reason for fencing was the mitigation of human–wildlife conflicts. Electric fences were the most commonly mentioned type, prominently used to protect agricultural lands from crop-raiding species. In addition, the prevention of livestock depredation and disease transmission was also an important driver for fencing. Elephants were the most studied species concerning wildlife fencing, and they caused the most damage to fences, creating pathways for other species to move beyond protected areas. Antelopes and large carnivores were also common targets for wildlife fences. Fences were found to be effective mainly against crop raiding particularly when well-maintained through frequent inspections for damages and permeability. Several authors documented challenges in fencing against primates, burrowers, and high-jumping species like leopards. The cost of fences varied depending on the materials, design, and maintenance, significantly impacting local communities near conservation areas. Despite their benefits, wildlife fences posed ecological challenges, such as habitat fragmentation and restricted animal movement, necessitating integrated management approaches that include wildlife corridors and crossing structures. This review provides insights for policymakers and conservationists to optimize the use of fences in the diverse environmental contexts of the African continent. Full article

The Pendjari Biosphere Reserve is one of the protected areas of Benin where biodiversity conservation policies intertwine with the economic development of local populations. It is located in the Atacora region in northern Benin, which has a high prevalence of poverty and food insecurity among households. Agriculture and livestock farming are the primary activities of the local communities in the villages surrounding the reserve. However, wild animals sometimes cause damage to people’s fields or livestock. To deal with the damage caused by wild animals, local populations have developed several mitigation measures that may not be effective, leading them into a vulnerable situation. Vulnerability is often associated with the impacts of natural disasters and their management, anticipation, and recovery. In the context of human–wildlife conflict, vulnerability refers to the level of risk farmers face from issues such as crop raiding, livestock depredation, and human injury caused by wildlife, as well as farmers’ ability to cope with such damage. To assess the vulnerability of households, we used the Livelihood Vulnerability Index (LVI). Data were collected from July to December 2019 through questionnaires and interviews. We surveyed 320 households to collect data on their socio-demographics, livelihoods, social networks, natural capital, food and water security, and the incidence and severity of human–wildlife conflicts. The results showed that farmers around the Pendjari Biosphere Reserve are highly sensitive to human–wildlife conflicts, with a low adaptive capacity, revealing their vulnerability. More precisely, farmers are vulnerable in terms of major components of the LVI such as water, food, social networks, and livelihoods. Conservation policies are expected to pay more attention to local populations’ vulnerability to human–wildlife conflicts in order to improve their tolerance towards wildlife and guarantee the success of conservation efforts. Full article

Our study assessed patterns of Asiatic black bear (Ursus thibetanus)–human conflicts within the Guthichaur rural municipality, Jumla, Nepal. Through semi-structured interviews with villagers, focus group discussions (FGDs), and key informant interviews (KIIs), we gathered black bear–human conflict information from 2009 to 2019. We identified three primary types of black bear–human interactions: crop damage, livestock depredation, and human injuries. Of these, crop damage (77.03%) emerged as the most prevalent issue. Notably, peak occurrences were observed during autumn (September–October) typically between 9 PM and 3 AM. Livestock depredations were more frequent during nighttime in April–August, with cows/ox (70.12%) being the most depredated animal. Our data also revealed five recorded cases of black bear attacks on humans, which transpired from September to October, primarily in farmland areas in varying years. Despite a prevailing negative perception of bears, a notable level of support exists for their conservation efforts among local communities. Furthermore, these conflicts could be mitigated by reinforcing indigenous crop protection methods and implementing targeted mitigation strategies, as observed in other regions with successful black bear–human interaction management. Full article

Wild pigs (Sus scrofa) cause damage to agricultural crops in their native range as well as in the portions of the globe where they have been introduced. In the US, states with the highest introduced wild pig populations are Alabama, Arkansas, California, Florida, Georgia, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, and Texas. The present study summarizes the first survey-based effort to value the full extent of wild pig damage to producers of six crops in these eleven US states. The survey was distributed by the USDA National Agricultural Statistical Service in the summer of 2022 to a sample of 11,495 producers of corn (Zea mays), soybeans (Glycine max), wheat (Triticum spp.), rice (Oryza sativa), peanuts (Arachis hypogaea), and sorghum (Sorghum bicolor) in these 11 states. Our findings suggest that the economic burden of wild pigs on producers of these crops is substantial and not limited to the direct and most identifiable categories of crop damage (i.e., production value lost due to depredation, trampling and rooting). We estimate that the annual cost to producers of these six crops in the surveyed states in 2021 was almost USD 700 million. Full article

Improving agricultural production in response to the increasing food demand remains a major challenge in agroecology. The world has made significant efforts to meet this issue by developing several cultivation techniques, such as the use of chemical fertilizers and arable land conversion into agricultural land. However, most of these techniques have caused a significant loss of biodiversity and ecosystems services. Recent data suggest that biological conservation within and around agroforestry systems are potential solutions that can both reduce biodiversity loss and guarantee crop production. This logic is based on the hypothesis that increasing plant diversity in and around agricultural systems can limit the pest attack rate and increase crop yield. We tested this hypothesis using structural equation modeling on empirical data collected in agroforestry systems around the Pendjari biosphere reserve in West Africa. We measured crop diversity, crop yield, arthropod pest diversity, abundance, the rate of crop herbivory, and the diversity of plants in surrounding natural vegetation in 32 permanent plots. We estimated arthropod diversity and abundance using pitfall traps. We found a direct positive effect for plant diversity and a direct negative effect of arthropod herbivory on crop yield. The diversity of plants in surrounding natural vegetation had a direct positive effect on arthropod pest diversity but a marginal negative direct effect on the rate of crop herbivory. We found no significant direct or indirect effect for crop diversity. Our findings underline the important role of biodiversity conservation in agricultural production improvement. We suggest that the conservation of plant diversity around agroforestry systems may be an effective option to control herbivory damage. Its combination with other pest control techniques may further limit crop depredation and ensure the long-term conservation of wildlife. Full article

Agriculture and animals are two crucial factors for ecological balance. Human–wildlife conflict is increasing day-by-day due to crop damage and livestock depredation by wild animals, causing local farmer’s economic loss resulting in the deepening of poverty. Techniques are needed to stop the crop damage caused by animals. The most prominent technique used to protect crops from animals is fencing, but somehow, it is not a full-proof solution. Most fencing techniques are harmful to animals. Thousands of animals die due to the side effects of fencing techniques, such as electrocution. This paper introduces a virtual fence to solve these issues. The proposed virtual fence is invisible to everyone, because it is an optical fiber sensor cable, which is laid 12-inches-deep in soil. A laser light is used at the start of the fiber sensor cable, and a detector detects at the end of the cable. The technique is based on the reflection of light inside the fiber optic cable. The interferometric technique is used to predict the changes in the pattern of the laser light. The fiber cable sensors are connected to a microprocessor, which can predict the intrusion of any animal. The use of machine learning techniques to pattern detection makes this technique highly efficient. The machine learning algorithms developed for the identification of animals can also classify the animal. The paper proposes an economical and feasible machine-learning-based solution to save crops from animals and to save animals from dangerous fencing. The description of the complete setup of optical fiber sensors, methodology, and machine learning algorithms are covered in this paper. This concept was implemented and regressive tests were carried out. Tests were performed on the data, which were not used for training purposes. Sets of people (50 people in each set) were randomly moved into the fiber optic cable sensor in order to test the effectiveness of the detection. There have been very few instances where the algorithm has been unable to categorize the detections into different animal classes. Three datasets were tested for configuration effectiveness. The complete setup was also tested in a zoo to test the identification of elephants and tigers. The efficiency of identification is 94% for human, 80% for tiger, and 75% for elephant. Full article

In Thailand, crop depredation by wild elephants intensified, impacting the quality of life of local communities and long-term conservation of wild elephant populations. Yet, fewer studies explore the landscape-scale spatiotemporal distribution of human–elephant conflict (HEC). In this study, we modeled the potential HEC distribution in ten provinces adjacent to protected areas in Eastern Thailand from 2009 to 2018. We applied the time-calibrated maximum entropy method and modeled the relative probability of HEC in varying scenarios of resource suitability and direct human pressure in wet and dry seasons. The environmental dynamic over the 10-year period was represented by remotely sensed vegetation, meteorological drought, topographical, and human-pressure data. Results were categorized in HEC zones using the proposed two-dimensional conflict matrix. Logistic regression was applied to determine the relevant contribution of each scenario. The results showed that although HEC probability varied across seasons, overall HEC-prone areas expanded in all provinces from 2009 to 2018. The largest HEC areas were estimated during dry seasons with Chantaburi, Chonburi, Nakhon Ratchasima, and Rayong provinces being the HEC hotspots.However, the HEC potential was reduced during severe and prolonged droughts caused by El Nino events. Direct human pressure caused a more gradual increase of HEC probability around protected areas. On the other hand, resource suitability showed large variation across seasons. We recommend zone-dependent management actions towards a fine-balance between human development and the conservation of wild elephants. Full article

The scope of Tulsi (Ocimum sanctum) as an alternative crop and means of livelihood, particularly for the rural poor, has not been extensively explored. Tulsi is in much demand for its medicinal and aromatic properties, particularly in Ayurveda. With increased depredation of cereal crops by wildlife, increased pest incidence, and decreasing availability of water for agriculture, an attempt was made to explore alternative livelihoods through Tulsi cultivation and value chain development. Using cross-sectional survey data of beneficiary households, the study employed the ordinary least squares method to examine the relationship between total crop income and the income from Tulsi for 2016 and 2017. The findings suggest that the average household’s gross profit more than doubled within a span of two years. Total crop income of beneficiary farmers increased by 0.8 percent for every 1 percent increase in income from Tulsi. Most importantly, the intervention has shown a tremendous adoption rate. Initially, in 2013, 200 farmers cultivated Tulsi on 8.72 hectors of unirrigated and fallow land in the five beneficiary villages, but by 2017, towards the end of the intervention period, 400 farmers were cultivating the crop on 19.6 hectors of unirrigated, fallow land in 19 villages in Chamoli District. Tulsi farming and value chain development intervention not only provided marginal and smallholder farmers in these villages with a sustainable alternative additional livelihood option but also an opportunity where they were able to sustainably generate income from unirrigated, fallow land. Full article