Human Activities Research Articles

CSI-Based Location-Independent Human Activity Recognition by Contrast Between Dual Stream Fusion Features

CSI-Based Location-Independent Human Activity Recognition by Contrast Between Dual Stream Fusion Features

Challenges and opportunities to location independent human activity recognition utilizing Wi-Fi sensing

Wireless sensing has emerged as a dynamic field with diverse applications across smart cities, healthcare, the internet of things (IoT), and virtual reality gaming. This burgeoning area capitalizes on the capacity to detect locations, activities, gestures, and vital signs by assessing their impact on ambient wireless signals. This review critically examines the prevailing challenges within wireless sensing and predicts future research trajectories. Even with the potential for nuanced signal processing facilitated by Wi-Fi propagation, its efficacy is impeded by noise interference in confined areas during transmission and reception. Consequently, this work aims to augment signal processing performance accuracy by delving into the most promising techniques and underexplored methods utilizing channel state information (CSI). Furthermore, the work offers a view into the potential of human activity recognition predicated on CSI properties. The study focusses on exploring location-independent sensing technique based on CSI, discussing relevant considerations and contemporary approaches used in Wi-Fi sensing tasks. The optimal practices in analysis are based on model design, data collection, and result interpretation. The discussions analysis investigates in detail the representative applications and outlines the major considerations of developing human activity recognition human activity recognition (HAR) based on Wi-Fi by analyzing the current critical issues of CSI-based behavior recognition methods and pointing out possible future research directions.

Predictors of Salmonella enterica contamination in agricultural and livestock-impacted natural watersheds.

Salmonella enterica (S. enterica), a ubiquitous zoonotic foodborne pathogen, remains a worldwide public health hazard and economic burden. In recent years, outbreaks associated with the consumption of plant-based foods probably contaminated by irrigation water highlights the importance of water sources. This study investigated anthropogenic and environmental factors influencing S. enterica occurrence in natural watersheds impacted by agricultural and livestock industries in a 10-month longitudinal study in Paraiba, Brazil. Water samples were obtained from multiple sites within the three major river basins by modified Moore Swabs (MMS) and processed by conventional S. enterica isolation methodologies. Physicochemical parameters, climate, and human activities near the water sources were recorded. A logistic regression model was fitted using Generalized Linear Model (GLM) and further adjusted according to the selected variables using the Least Absolute Shrinkage and Selection Operator (LASSO) method. A non-statistical decision tree model was also fitted using the rpart package in R. Season, rainfall regime, water physicochemical features, and anthropogenic activities were significantly associated with S. enterica contamination. According to the regression tree analysis, rainfall within the sampling month was the strongest predictor of S. enterica recovery, potentially due to leaching from soil or runoff from adjacent human and animal activities. The complexity of multivariate conditions driving S. enterica contamination in surface waters highlights the need for region-specific investigations.

Determination of present-day crustal deformation along the Kenyan rift system using InSAR

The Kenyan rift system is prone to deformation due to various geological processes and human activities, such as overexploitation of groundwater and exploitation of geothermal energy. Crustal deformation monitoring is essential for understanding the geodynamics of the rift and assessing potential hazards as the rift passes through densely populated areas. However, retrieving InSAR displacement measurements along the Kenya rift system is challenging due to the high variability in tropospheric delay caused by its location in the tropics and the significant topographic variations along the rift. Here, we leverage Sentinel-1 data to analyze both local and large-scale deformation in the rift using multi-temporal InSAR processing with an improved tropospheric correction method, which we previously proposed with a modification on variance covariance modeling. We provide evidence for the previously reported ground displacement of 5-7.5 cm southwest of the Suswa volcano as being a misidentification of a tropospheric delay, that was dominant on March 27, 2018. Moreover, we observe episodic ground displacement at Suswa and Longonot, attributable to magma movement. Our results indicate that Suswa experienced a 9 cm movement towards the satellite line of sight between 2018-2020, while Longonot moved 4 cm towards satellite line of sight between 2016-2018 and also underwent 3 cm displacement away from the satellite line of sight between 2019-2021. In addition, we observe land subsidence associated with geothermal exploitation in the range of 1-3.6 cm/yr in Olkaria as well as in multiple locations in Nairobi at a rate of up to 6 cm/yr, primarily attributed to groundwater overexploitation. Moreover, we detect undocumented ground displacement at the Chalbi salt flat and along the Elgeiyo escarpment, at rates of up to 4.8 cm/yr and 5.7 cm/yr, respectively. Long-wavelength, low-amplitude deformation at the Turkana depression aligned well with the current kinematics of the Kenyan rift system. We find that localized deformations, caused by magmatism and human activity, dominate the south segment of the rift, whereas large-scale low-amplitude deformations dominate the north segment. In summary, our results emphasize the importance of tropospheric delay correction in retrieving InSAR-derived displacement measurements along the Kenyan rift system.Graphical

Urban soil ecological risk assessment based on "climate change- resilience".

Under the dual pressures of global climate change and rapid urbanization, urban soil ecosystems face increasingly complex risks and challenges. Existing urban soil ecological risk assessment methods are primarily limited to single-dimensional analysis or linear assessment models, making it difficult to reveal the complex interaction mechanisms among soil, climate, and human activities. This study pioneers the integration of social-ecological system theory with multi-criteria decision-making methods to innovatively construct a dynamic coupling assessment framework. This framework employs the AHP-DEMATEL method to identify causal relationships and feedback mechanisms between indicators, while utilizing the VIKOR method for comprehensive quantitative risk assessment. Through an empirical analysis of 11 prefecture-level cities in Zhejiang Province, this study reveals that: (1) climate change-related indicators demonstrate dominant weights, with the impact of extreme weather (C3) reaching a comprehensive weight of 0.1082, significantly higher than other indicators; (2) soil biodiversity (C8) exhibits the highest centrality (10.112), forming a key feedback node in the assessment system, highlighting the crucial role of biological factors in maintaining soil system stability; (3) green infrastructure coverage (C16) shows the highest cause degree (2.261), generating complex cascade effects through its influence on soil temperature, moisture, and biodiversity; (4) urban risk levels display significant spatial heterogeneity, with Lishui performing optimally (group benefit value S = 0.069) and Zhoushan performing poorest (S = 1.000), quantifying the impact of economic development patterns and geographical location on soil ecological risk. The dynamic coupling assessment framework and quantitative indicator system established in this study provide a new paradigm for understanding the complexity of urban soil ecosystems.

Zooplankton distribution and its associated hydrology across Indian Sundarbans over the last decade: Insights from current trends and future directions.

Zooplankton play a crucial role in estuarine ecosystems by aiding nutrient cycling through trophic chains and contributing to large-scale water filtration. The present review highlights the zooplankton research conducted over the last decade (2014-2024) in the Indian Sundarbans, with a focus on research trends, species distribution, hydrological associations, and long-term monitoring and conservation strategies. The study reveals a surge in zooplankton research after 2019, with an emphasis on both small- and large-scale studies. However, tidal creek/canals remain less explored compared to rivers. A lack of methodological standardization in zooplankton research is evident across the Indian Sundarbans. The Saptamukhi-Thakuran-Matla river stretch exhibited the highest species diversity, with 70 species recorded. Similarly, the tidal creeks and canals of Sagar Island were identified as species-rich habitats, with 63 species reported. Oithona brevicornis was found in seven riverine stretches, while Paracalanus parvus and Labidocera euchaeta were each recorded from six rivers, but Bestiolina similis was mostly reported as the numerically predominant zooplankton species. Salinity emerged as the most influential hydrological factor for zooplankton distribution, followed by dissolved oxygen and water temperature. However, increasing pollution, climate change-induced cyclones, salinization, and human activities are threatening zooplankton communities of the Indian Sundarbans. Furthermore, the review underscores the need for long-term monitoring strategies in the Sundarbans, by addressing the integration of remote sensing method, automated devices, data repositories, and ecological modeling approaches. Additionally, the present review recommends future policies for zooplankton conservation, emphasizing habitat protection, water quality assessment, stakeholder engagement, and securing funding to implement long-term monitoring initiatives.

Analysis of the Distribution Pattern of Asparagus in China Under Climate Change Based on a Parameter-Optimized MaxEnt Model

Asparagus (Asparagus officinalis L.) has high health and nutritional values, but the lack of scientific and rational cultivation planning has resulted in a decline in asparagus quality and yield. Important soil, climatic, anthropogenic, and topographic environmental factors influencing the distribution of asparagus cultivation were chosen for this study. The Kuenm package in the R language (v4.2.1) was employed to optimize the maximum entropy model (MaxEnt). Pearson’s correlation analysis, optimized MaxEnt, and geographic information spatial technology were then utilized to identify the main environmental factors that influence suitable habitats for asparagus in China. Potential distribution patterns, migration, and changes in trends concerning the suitability of asparagus in China under various historical and future climate scenarios were modeled and projected. Human activities and climate factors were found to be the primary environmental factors that influence the suitability distribution of asparagus cultivation in China, followed by soil and topographic factors. Historical suitable habitats covered 345.6 × 105 km2, accounting for 36% of China. These habitats are projected to expand considerably under future climatic conditions. This research offers a basis for the rational planning and sustainable development of asparagus cultivation.

Wavelet-Based Method for Variations of Microplastics over a Monthly Lunar Tidal Cycle in Beach Sediments of Maowei Bay, China.

While microplastics from lake, beach and ocean environment has become a growing global concern, tidal variations of microplastics in beach sediments are not well documented. Here, sediments were sampled over one monthly lunar tidal cycle during low tidal period in Shajing Beach along the Maowei Bay, China. The shape and abundance of microplastics were measured in sediments to determine their periodic variations by wavelet analysis method. The results showed that microplastics are generally granule, fiber and film shapes on Shajing Beach. The dominant type was fiber, followed by the granule. Meanwhile, the microplastic abundances showed a periodic change about 15 days. The granule and fiber but not film also followed such periodic variations. Tourism and human activities along the bay are the most likely causes for microplastics in Shajing Beach, while half-mouth of tidal cycle is responsible for the periodic variation of microplastic abundances and types.

Understanding the role of moths (Insecta: Lepidoptera) as pollinators of apple (Malus domestica)

ABSTRACT Given their economic and nutritional value, apples are among the most valuable crops. However, apple production requires cross-pollination. Climate change and various human activities have decreased pollinator diversity in apple orchards, leading many farmers to use honeybee colonies to increase productivity. Studying the pollinators of apple crops is crucial for future pollinator management. While diurnal pollination of apple flowers has been explored, the role of nocturnal pollinators in general and moths in particular has not been thoroughly studied. To assess the role of moths in apple pollination, we studied the effectiveness of moths and other nocturnal flower visitors in depositing pollen grains on the stigma of apple flowers (single-visit pollen deposition) at Shergaon Apple Garden, Arunachal Pradesh (East Himalaya, India). The mean single-visit pollen deposition on apple flowers by nocturnal flower visitors is calculated to be 112.92 ± 10.98. Among all nocturnal flower visitors, moths are the most effective pollen depositors with a mean single-visit pollen deposition of 152 ± 19.9. Thirty moth species are found to carry apple pollen on their proboscides. Of them, three species Nyctemera arctata Walker, 1856 (Erebidae), Pyrrhia umbra (Hufnagel, 1766) (Noctuidae) and Chiasmia azataria (Swinhoe, 1893) (Geometridae) are found to be the highest carriers of apple pollen load. This study indicates that moths are the most significant for nocturnal pollination of apple.

Impact of microplastic exposure on the health of tropical seagrass (Enhalus acoroides) seedlings.

The early stages of seagrass life are marked by the development of seagrass seedlings. Enhalus acoroides is a persistent seagrass species with a high prevalence in tropical waters. The decline in water quality caused by human activities, such as microplastic contamination, is suspected to affect the growth and development of seagrass seedlings. This study examines the impact of microplastic exposure on the growth, chlorophyll content, and anatomical structure of Enhalus acoroides seedlings. This experimental research included four treatments: Treatment A (no microplastics), Treatment B (0.5g/L microplastics), Treatment C (1.0g/L microplastics), and Treatment D (1.5g/L microplastics). The results show that increasing microplastic concentrations disrupt photosynthesis in seagrass seedlings, indicated by a decrease in chlorophyll content, which leads to reduced growth and lower survival rates in seedlings (Treatment D). Based on this study, it is suggested that higher microplastic exposure may prevent seedlings from developing into mature seagrass individuals.

A comparative analysis of LSTM models aided with attention and squeeze and excitation blocks for activity recognition.

Human Activity Recognition plays a vital role in various fields, such as healthcare and smart environments. Traditional HAR methods rely on sensor or video data, but sensor-based systems have gained popularity due to their non-intrusive nature. Current challenges in HAR systems include variability in sensor data influenced by factors like sensor placement, user differences, and environmental conditions. Additionally, imbalanced datasets and computational complexity hinder the performance of these systems in real-world applications. To address these challenges, this paper proposes an LSTM-based HAR model enhanced with attention and squeeze-and-excitation blocks. The LSTM captures temporal dependencies, while the attention mechanism dynamically focuses on important parts of the input sequence. The squeeze-and-excitation block recalibrates channel-wise feature importance, allowing the model to emphasize the most informative features. The proposed model demonstrated a 99% accuracy rate, showcasing its effectiveness in recognizing various activities from sensor data. The integration of attention and squeeze-and-excitation mechanisms further boosted the model's ability to handle complex datasets. Comparative analysis with existing LSTM models confirms that the proposed approach improves accuracy and reduces computational complexity, making it a highly suitable model for real-world applications.

Hydrological Response of Land Use and Climate Change Impact on Sediment Rate in Upper Citarum Watershed

The Citarum Watershed is indeed a critical water resource in Indonesia, playing a significant role in providing water to Jakarta and other areas in West Java. However, it faces severe environmental stress due to land use changes and climate changes. The Upper Citarum Watershed, considered to be a conservation area, has experienced rapid development due to human activities and economic growth. Climate change not only affects the rainfall value but also the rainfall patterns and sediment flow. The sedimentation process significantly impacts the soil characteristics around the river body. Several factors such as topography, flow velocity, and soil texture influence the sediment characteristics. Given the critical condition of climate and land use change, this study aims to analyse the impacts of the hydrological response of land use and climate change on the sediment rate in the Upper Citarum Watershed. The land use change analysis was conducted by comparing the land use data in 2000, 2010, and 2023 in the Upper Citarum Watershed. The deposition process of solid particles such as sand, silt, and gravel that are transported in the Upper Citarum River were examined in a soil investigation. The sediment rate and deposition by river flow were analysed using HEC-RAS quasi-unsteady flow. The impact of climate change in this study was assessed by simulating the discharge in three conditions, with the first simulation using the discharge from 2000 to 2010, the second simulation using the discharge from 2011 to 2023, and the last simulation using the discharge from 2000 to 2023. Due to the land use change, the developed area increased from 4% to 24% between 2000 until 2023. The magnitude of low flow during the simulation step for three discharge gauges (Majalaya, Dayeuhkolot, and Nanjung) decreased up to 48%, but, on other hand, the sediment rate increased by 20% in Dayeuhkolot.

Analysis of Energy Use and Environmental Impacts of Pistachio (Pistacia vera L.) in Conventional and Bio-friendly Production Systems

Humankind and natural ecosystems are facing global changes. There is a clear influence of human activities due to the use of contaminant energies among other factors. Therefore, it is a priority to find clean energies with less environmental impacts coming from bio-friendly production systems. Therefore, the main aim of this research is to examine energy use patterns, greenhouse gas emission (CO2, N2O, and CH4) and life cycle assessment (LCA) in pistachio (Pistacia vera L.) production systems. As experimental plots, we selected one plantation located in the North Khorasan province of Iran. Data were collected from two pistachio orchards with conventional (CPS) and with bio-friendly production systems (BPS). In 2 seasonal years, from 2020 to 2021, a functional unit of 1000 kg pistachio was used. The results indicated that total energy consumption in the conventional pistachio production system reached 58,759.86 MJ ha−1 in comparison to bio-friendly pistachio production systems with 31,149.02 MJ ha−1, accounting for 36.0% of fertilizer energy, 26% of diesel energy, and 12.7% of electricity. The energy use efficiency for the CPS and BPS was respectively 0.38 and 0.73, and also energy productivity for CPS reached 0.01 kg MJ ha−1 and BPS 0.02 kg MJ ha−1. Results indicated that the direct energy for CPS was 19.6% and for BPS 39.03%, but indirect energy inputs for CPS and BPS registered 76.4 and 60.5%, respectively. It was found that the non-renewable form of energy input for CPS was 83.8% and for BPS just 57.6%. We conclude that chemicals (pesticides, fertilizers), fuel and electricity were the most important inputs for the pistachio production system, which also influenced total CO2, N2O and CH4 emissions due to chemical inputs for CPS. In CPS and BPS, the total global warming potential (GWP) was 2445.24 and 1507.99 kg CO2eq ha−1, respectively. Compared to CPS, the application of the BPS method reduces total damage to human health, ecosystems, and resources.

Comprehensive evaluation of groundwater quality in population-dense and extensive agricultural regions and study on its relationship with agricultural production and human activities.

Extensive agricultural regions commonly face issues of poor groundwater management, non-standard agricultural production practices, and unordered discharge of domestic pollution, leading to a continuous decline in groundwater quality and a sharp increase in risks. A comprehensive understanding of groundwater conditions and pollution is a crucial step in effectively addressing the water quality crisis. This study employs the Comprehensive Water Quality Index, Irrigation parameter, and Pollution Index to comprehensively investigate the groundwater quality in a typical agricultural area in Shandong, China, and assesses the suitability of groundwater for irrigation and the risks to human health. Furthermore, multivariate statistical analysis methods are utilized to analyze the relationship between groundwater quality and agricultural production and human activities. The results of the comprehensive quality evaluation indicate that the groundwater in the study area is primarily characterized as weakly alkaline hard freshwater and slightly brackish water, with a hydrochemical type of HCO3-Ca. 42% of the groundwater is unsuitable for drinking, with the main pollutants being TDS, TH, F-, and NO3-. The shallow groundwater level and high soil permeability provide favorable conditions for pollutant migration. Residual Sodium Carbonate (RSC) and Potential Salinity (PS) indicate that 37% of the water samples have excessive bicarbonate levels and 5% have excessive salinity, making them unsuitable for irrigation. Nitrate poses non-carcinogenic risks to all three age groups. Multivariate analysis results show that agricultural pollution dominates in the groundwater, with major pollutants including SO42-, NO3-, COD, NH4-N, F-, etc. Domestic pollution mainly increases the concentrations of ions such as Ca2+, Na+, Mg2+, and also contributes to Cl- and NO3-. The findings of this study contribute to enhancing the rational utilization of groundwater quality in agricultural areas, standardizing agricultural production activities, and promoting the sustainable development of green agriculture.

Human recreational activity does not influence open cup avian nest survival in urban green spaces

The breeding period of birds is a critical and sensitive portion of the annual cycle. Understanding how human use of urban green spaces affects nest survival can improve our understanding of conserving breeding bird populations in cities and support science-based management of urban green spaces that benefit both people and nature. We conducted a nest survival field study between April and August of 2023 in multiple green spaces in Montreal, Quebec, Canada, the country’s second-largest city. We asked whether human presence (distance to trails and amount of human activity) influences the nest survival of four common open-cup nesting bird species: American robins (Turdus migratorius), gray catbirds (Dumetella carolinensis), Northern cardinals (Cardinalis cardinalis), and yellow warblers (Setophaga petechia). We also asked if variables traditionally associated with nest survival, such as vegetation concealment and seasonality, would influence nest survival. Our analyses surprisingly revealed no significant influence of human activity, vegetation concealment, and seasonality on nest survival for our target species. We found for nests that did fail, nests established during the earlier part of the nesting period failed faster. American robin nests were the most successful of our study’s four target species, whereas Northern cardinal nests were the least successful. Within the limitations of our study system, our findings suggest that human presence on trails is not negatively impacting the nesting success for our target bird species using urban green spaces. Our study provides integrated science advice to land managers so they can support opportunities for people to connect with nature without causing trade-offs with biodiversity conservation.

The Sikkim flood of October 2023: Drivers, causes and impacts of a multihazard cascade.

On 3 October 2023, a multihazard cascade in the Sikkim Himalaya, India, was triggered by 14.7 million m3 of frozen lateral moraine collapsing into South Lhonak Lake, generating an ~20 m tsunami-like impact wave, breaching the moraine, and draining ~50 million m3 of water. The ensuing Glacial Lake Outburst Flood (GLOF) eroded ~270 million m3 of sediment, which overwhelmed infrastructure, including hydropower installations along the Teesta River. The physical scale and human and economic impact of this event prompts urgent reflection on the role of climate change and human activities in exacerbating such disasters. Insights into multihazard evolution are pivotal for informing policy development, enhancing Early Warning Systems (EWS), and spurring paradigm shifts in GLOF risk management strategies in the Himalaya and other mountain environments.

Declines in anthropogenic mercury emissions in the Global North and China offset by the Global South.

Human activities have emitted substantial mercury into the atmosphere, significantly impacting ecosystems and human health worldwide. Currently, consistent methodologies to evaluate long-term mercury emissions across countries and industries are scant, hindering efforts to prioritize emission controls. Here, we develop a high-spatiotemporal-resolution dataset to comprehensively analyze global anthropogenic mercury emission patterns. We show that global emissions increased 330% during 1960-2021, with declines in developed Global North countries since the 1990s and China since the 2010s completely offset by rapid growth in Global South countries (excluding China). Consequently, global emissions have continued to rise slightly since the 2013 Minamata Convention. In 2021, Global South countries produced two-thirds of global emissions, despite comprising only one-fifth of the global economy. We predict that, although large uncertainties exist, continued emission growth in Global South countries under a business-as-usual scenario could increase 10%-50% global mercury emissions by 2030. Our findings demonstrate that global control of anthropogenic mercury emissions has reached a critical juncture, highlighting the urgent need to target reductions in Global South countries to prevent worsening health and environmental impacts.

Transgression of planetary boundaries and the effects on child health through an infectious diseases lens.

Life on earth, as we know it, is changing. The likelihood of more frequent pandemics and disease outbreaks is something that current global healthcare infrastructure is ill equipped to navigate. Human activity is forcing our planet into a new geologic epoch, the Anthropocene, which is typified by increased uncertainty resulting from human disruption of earth's life-giving ecosystems. Plagues and pandemics have always been unfortunate partners to periods of disruption, as they will be again if the frequency and severity of climate and conflict-mediated disasters increase in coming years. If we continue to exceed and degrade the planetary boundaries that protect human health, our children and their children will reap the consequences. Scientists have defined nine 'safe operating' planetary boundaries for life in all its glorious diversity to thrive on planet earth. Recent evidence suggests that six of these nine boundaries have already been transgressed, but the potential implications for these transgressions upon child health is not well articulated. We highlight how contravention of these boundaries will impact infectious disease risk and humans' ability to survive and thrive. We reflect specifically on how paediatricians are called upon to speak up for the most vulnerable members of our species, young children and as yet unborn future generations. Post COVID-19 initiatives to improve pandemic preparedness and response are certainly warranted, but pandemic prevention should include committed efforts not to exceed safe planetary boundaries. Willingly exceeding these boundaries has deep moral consequences that are poorly articulated by current ethical frameworks. Paediatricians are best placed to develop and champion the neglected 'third dimension' of medical ethics, recognizing the moral imperative to protect the long-term best interests of children and future generations.

Machine learning models for water safety enhancement.

Humans encounter both natural and artificial radiation sources, including cosmic rays, primordial radionuclides, and radiation generated by human activities. These radionuclides can infiltrate the human body through various pathways, potentially leading to cancer and genetic mutations. A study was conducted using random sampling to assess the concentrations of radioactive isotopes and heavy metals in mineral water from Iran, consumable at Arak City. Notably, specific radiation levels of Ra-226 were not detected, whereas the concentrations of Th-232, K-40, and Cs-137 were found to be below the thresholds established by the World Health Organization (WHO). The annual effective doses derived from the consumption of bottled water were significantly lower than the limits set by the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR), thereby reducing the risk of cancer. Furthermore, heavy metals such as lead and chromium were not present in the samples, thereby contributing to the overall safety of the water. The Machine Learning (ML) models employed in this study provided accurate predictions, ensuring reliability across various demographic groups and reinforcing the robustness of the findings. Overall, the results suggest that consumable mineral water consumption poses minimal health risks.

Conserving Traditional Medicinal Plants Amidst Deforestation: Insights from Fakai, Nigeria

Deforestation and vegetation loss can trigger various environmental issues, including climate change, desertification, soil erosion, reduced crop yields, loss of vegetation cover, flooding, and other related problems. The study was conducted to examine the impact of deforestation on traditional medicinal plants in the Fakai local government area of Kebbi state. Two out of four districts in Fakai were chosen for their relevance to the study. Data was gathered through questionnaires and in-depth interviews and subsequently analyzed using frequency counts, percentages, and charts. The research findings showed that diverse plant species and their parts have been used to treat various ailments since time immaterial. Additionally, it was discovered that deforestation poses a significant threat to plants, particularly traditional medicinal plants in treating multiple diseases. This threat stems from the community's ongoing tree felling for commercial wood fuel harvesting, charcoal production, and bush burning to expand agricultural lands. The study also revealed that measures to curb deforestation were either non-existent or ineffective. The research concluded that while most of the studied community relies on traditional plants for treating health-related issues, human activities are detrimental to this practice, and there is a lack of stringent measures to address deforestation. The study recommends implementing community-based conservation efforts and promoting alternative energy sources to curb deforestation. Other interventions may include seedlings provision, poverty eradication, and legal action against illegal logging to ensure the sustainable use of medicinal plants.