International Journal of Environment and Climate Change

Sustainable Transportation Systems and Climate Change in Developing Countries with Special Reference to India

Anil Maan — 2026-05-27

Concerns regarding climate change necessitate the prompt implementation of appropriate policy interventions and structural reforms aimed at safeguarding and sustaining economic activity within the transport sector. In particular, there is a growing imperative for coordinated action that both mitigates environmental impacts and ensures the long-term resilience and efficiency of transport systems, given their critical role in supporting broader economic development. India's transport sector has emerged as one of the foremost climate and public-health challenges of the twenty-first century. Road transport alone contributes 12 per cent of India's energy-related CO₂ emissions, and the sector's greenhouse gas (GHG) output is expanding faster than any other segment of the national economy. Against the backdrop of India's Nationally Determined Contribution (NDC) target to reduce the emission intensity of GDP by 45 per cent from 2005 levels by 2030 and its net-zero commitment by 2070, this paper undertakes a systematic empirical analysis of the nexus between sustainable transportation and climate change mitigation in a rapidly urbanising developing country. Drawing on data from the Ministry of Road Transport and Highways (MoRTH), the International Energy Agency (IEA), the Central Pollution Control Board (CPCB), the Council on Energy, Environment and Water (CEEW), NITI Aayog, and peer-reviewed literature (2015–2025), the study examines: (i) the magnitude and trajectory of transport-sector GHG emissions; (ii) co-pollutant air-quality impacts on urban populations; (iii) progress and gaps in electric-vehicle (EV) deployment; (iv) the performance of mass rapid transit (MRT) systems; and (v) policy pathways to sustainable mobility. Key findings reveal that while EV registrations grew eleven-fold—from 1.30 million in 2018 to 15.29 million by 2023—they constituted only 7.6 per cent of total new-vehicle sales in 2024, far below the national target of 30 per cent by 2030. India's metro network, the world's third largest at 1,013 km across 23 cities by 2025, carries over 11.2 million daily passengers but falls well short of projected ridership in many corridors. Average annual PM₂.₅ concentrations of 54.4 µg/m³ in 2023—more than ten times the WHO guideline—underscore the urgency of modal shift. The paper concludes with a multi-pronged policy framework encompassing stricter fuel-economy standards, accelerated fleet electrification, integrated multimodal transit, and green urban-freight reforms, offering transferable lessons for other developing economies confronting the intersection of climate commitments and mobility needs.

Artificial Intelligence-Based Site-Specific Weed Management in Cotton: A Comprehensive Review

Vaibhavkumar R. Dama — 2026-05-30

Weed infestation is one of the major biotic factors limiting cotton (Gossypium spp.) productivity, particularly during the early growth stages, where uncontrolled weed competition can result in yield losses ranging from 30 to 80%. The conventional weed management practices, such as manual weeding, mechanical cultivation and uniform herbicide application, are labour-intensive, costly and often environmentally unsustainable. In recent years, Site-Specific Weed Management (SSWM) integrated with Artificial Intelligence (AI) has emerged as an advanced precision agriculture approach for real-time weed detection and targeted herbicide application.

This review comprehensively summarizes recent developments in AI-based weed detection, machine vision systems, deep learning techniques and intelligent spraying technologies in cotton production systems. Earlier image-processing methods based on colour indices, shape descriptors and thresholding techniques achieved moderate weed classification accuracies ranging from 52 to 74% and showed limited adaptability under variable field conditions. The subsequent adoption of machine learning approaches, including SVMs, ANNs and wavelet-based feature extraction techniques, significantly improved weed identification performance, with accuracies exceeding 98% under controlled conditions. More recently, deep learning models, particularly CNNs and real-time object detection frameworks such as YOLO and Faster R-CNN, have demonstrated superior crop-weed discrimination capabilities with detection accuracies above 90 to 95% under dynamic field environments.

The integration of AI-enabled weed detection systems with precision spraying technologies, including variable-rate and micro-jet sprayers, has substantially improved herbicide application efficiency and operational accuracy. Several studies have reported herbicide savings ranging from 40 to 90% through site-specific spraying while maintaining effective weed control and reducing environmental contamination. In addition, intelligent sprayer systems equipped with embedded computing platforms, sensor fusion technologies and automated control mechanisms have facilitated real-time field implementation and enhanced input-use efficiency.

Despite considerable technological advancements, several challenges continue to hinder large-scale adoption of AI-based weed management systems. These include variability in illumination conditions, morphological similarities between crops and weeds, limited availability of annotated datasets and computational limitations associated with real-time field operations. Furthermore, there is a lack of region-specific AI models designed for Indian cotton production systems and diverse agro-climatic conditions.

Overall, this review highlights major research advancements, existing limitations and future opportunities in AI-driven weed management for cotton cultivation. The integration of robust datasets, adaptive learning algorithms, edge computing, robotics and IoT-enabled autonomous spraying systems can contribute significantly to the development of sustainable, economically viable and environmentally responsible weed management strategies in cotton production systems.

Multidisciplinary Innovations in Agriculture and Resource Management

Vandana Shukla — 2026-05-30

The main strategic goal of creative agronomic research in the upcoming decades should be the intensification of sustainable crop production. Crop production can be intensified in terms of higher output and productivity (efficiency) while also strengthening sustainability using a variety of farming practices, approaches, and technologies that are frequently highly location-specific. Encouraging farmers to employ environmentally suitable technologies and techniques and ensuring that farmers are increasingly adopting, utilising, and innovating sustainable agriculture practices are the primary challenges. Integrating farmers' local knowledge with formal knowledge based on science has a significant yet untapped potential. This integration aims to develop better practices and technological possibilities through beneficial institutional frameworks to support an innovation system. This also holds true for the design, implementation, and supervision of improved natural resource management that links local initiatives to new outside expertise. The different stages of the innovation system, such as technological adoption, adaptation, and diffusion at the farm level, should also be thoroughly measured. Additionally, the impact of agricultural policies on technical efficiency, technological change, and production intensification should be investigated. This study examines management techniques that support intensification and sustainable crop production systems in addition to attesting to improvements in crop and cultivar selection. Additionally, crop farming systems using a primarily ecosystem approach are described in the paper, along with the scientific application of this technique for controlling weed and insect populations. It also discusses the advantages and disadvantages of irrigation methods and examines the advancements in fertiliser and nutrient management, which form the cornerstone of productivity increase. Lastly, it offers a course of action based on seven shifts in agricultural development that emphasise the necessity of analysing how innovation takes place in the agricultural industry.

A Review on Carbon Trade and Related Policy in India

S. Nandhakumar — 2026-06-02

India’s carbon credit and trading framework has evolved through the integration of national climate policies, market-based mechanisms and agricultural sustainability initiatives. The Renewable Energy Certificate (REC) mechanism and the Perform, Achieve and Trade (PAT) scheme contributed to renewable energy expansion and industrial energy-efficiency improvements, while the Energy Conservation (Amendment) Act, 2022 established the foundation for the Carbon Credit Trading Scheme (CCTS). India’s installed solar capacity exceeded 63,000 MW by 2023, reflecting notable progress toward low-carbon development and industrial decarbonisation. Despite these achievements, agricultural participation in carbon markets remains limited due to small landholdings, inadequate awareness, high transaction costs and weak institutional access. Conservation agriculture, zero tillage and agroforestry demonstrate substantial potential for carbon sequestration, greenhouse gas mitigation and enhancement of farmer income. Agroforestry systems reported sequestration rates ranging from 0.25 to 23 Mg C ha⁻¹ yr⁻¹, while conservation agriculture practices showed potential carbon credit earnings of USD 16–30 per hectare. Institutions such as the Indian Council of Agricultural Research (ICAR), Krishi Vigyan Kendras (KVKs) and agricultural universities are increasingly promoting climate-smart agriculture, organic farming and carbon farming through research, extension and farmer training programs. The review highlights the quantitative gap between industrial decarbonisation and agrarian sustainability in India. While industries benefit from structured compliance mechanisms and policy incentives, agricultural systems remain inadequately integrated into formal carbon markets. Carbon credit mechanisms therefore offer significant opportunities to bridge this gap by incentivizing sustainable agricultural practices and strengthening rural participation in India’s green transition. The study concludes that inclusive policies, institutional coordination and farmer-centric market frameworks are essential for equitable low-carbon growth.

Influence of Agricultural Feedstock on the Physicochemical Properties and Performance of Biochar

Md. Shakibur Rahman — 2026-05-26

Limited understanding exists of how pyrolysis conditions affect the physicochemical properties of biochar derived from specific agricultural feedstocks. This study investigates coconut shell–derived biochar produced via oxygen-limited pyrolysis at 600 °C with a heating rate of 5 °C min⁻¹. X-ray diffraction revealed a predominantly amorphous structure (crystallinity index: 30.3%) with broad peaks at 2θ ≈ 23.15° and 43.80°, indicating high structural disorder that is favorable for adsorption. Dynamic light scattering showed a unimodal particle size distribution centered at ~1550 nm, while zeta potential measurements indicated a mean surface charge of −17 mV, confirming moderate colloidal stability and affinity for cationic contaminants. BET and BJH analyses demonstrated a hierarchical pore structure, with the cumulative pore volume reaching ~77 cc g⁻¹ in the 40–51 nm range and a micropore volume of ~0.13 cc g⁻¹. FTIR analysis confirmed the presence of –OH, C=O, and aromatic C=C functional groups, contributing to surface reactivity. Collectively, these structural, chemical, and electrokinetic properties position coconut shell biochar as a low-cost, high-performance material for environmental remediation and wastewater treatment, comparable in key characteristics to commercial activated carbon.

Assessing Forest Structure and Biomass Loss in Mount Cameroon National Park Using Remote Sensing and Machine Learning

Kato Samuel Namuene — 2026-05-26

Tropical montane forests of Cameroon represent disproportionately important per-unit-area carbon stocks and biodiversity repositories, yet remain among the least monitored protected landscapes in West and Central Africa. This study presents a comprehensive, multi-temporal remote sensing and machine learning assessment of forest structural dynamics and above-ground biomass (AGB) loss across the full extent of Mount Cameroon National Park (MCNP) between 2000 and 2023. Multi-source satellite data comprising Landsat 5/8, Sentinel-2, ALOS PALSAR-2 L-band SAR, and ICESat-2 ATL08 spaceborne LiDAR were integrated within Google Earth Engine. A Random Forest classifier achieved an overall land cover classification accuracy of 95.8% (Kappa = 0.942). AGB estimation models were calibrated against 6,842 GEDI L4A spaceborne retrievals and 4,614 ICESat-2 ATL08 segments across five altitudinal vegetation zones, yielding R² = 0.884 and RMSE = 20.31 Mg ha⁻¹, with multi-sensor fusion delivering an R² improvement of 0.150 over optical-only models. SHAP analysis identified PALSAR-2 HV backscatter as the dominant predictor (mean |SHAP| = 0.221), followed by ICESat-2 canopy height (0.179) and EVI (0.158). Dense closed-canopy forest declined from 37,309 ha (64.1%) in 2000 to 26,955 ha (46.3%) in 2023, representing a 176% increase in annual deforestation rate, from 358 ha yr⁻¹ to 987 ha yr⁻¹. Total AGB declined from 10.31 Tg to 7.04 Tg, generating cumulative carbon emissions of 5.04 Tg CO₂e. ICESat-2 ATL08 confirmed a mean canopy height reduction of 6.3 m in degraded forest zones between 2019 and 2023, with structural divergence between intact and degraded forest increasing from 8.4 m to 13.4 m. Road proximity was the dominant deforestation driver (Spearman ρ = -0.76), with the agricultural frontier migrating upslope by 350 m over the study period. These findings provide spatially explicit quantitative evidence supporting REDD+ Tier 2 carbon accounting and adaptive management in this critical Afromontane protected landscape.

Spatio-Seasonal Distribution of Water Quality Parameters and Heavy Metals in Plankton along the Mangaluru Coast, Southeastern Arabian Sea

Narendra Kumar Maurya — 2026-05-28

Aquatic ecosystems are increasingly polluted by heavy metals due to urbanisation, industrialisation, and poor waste management, especially in coastal regions. These metals accumulate in plankton and marine food chains, causing ecological damage and posing serious risks to human health through bioaccumulation and biomagnification. The current study examined the relationship between heavy metal accumulation in plankton and the physicochemical properties of coastal waters throughout a one-year period, from February 2024 to January 2025. The levels of selected heavy metals (Iron, Nickel, Zinc, Lead, Cadmium, Copper, Mercury, and Arsenic) were determined in plankton collected from six sites along the Mangaluru coast using an Atomic Absorption Spectrophotometer (AAS), the Thermo Scientific iCE 3300 series. The physicochemical indices of water quality, as well as heavy metal concentrations, varied dramatically among seasons and sites. The concentration of metals in plankton was in the same order: Fe > Zn > Ni > Cu > Pb > As > Cd > Hg. Throughout the monsoon season, Fe was the most prevalent metal, with a maximum concentration of 41.42 ± 10.54 µg g⁻¹ at station S1. In contrast, Cd and Hg had relatively lower quantities, with Hg remaining undetectable throughout the pre-monsoon. Ni, Pb, Hg, and As showed significant seasonal fluctuations (p < 0.05), whereas Fe, Ni, Pb, and Cu showed significant geographical differences. The study underlines the necessity of ongoing monitoring of coastal ecosystems throughout the Mangaluru coast and underscores the impact of anthropogenic inputs and monsoon-driven processes on heavy metal dynamics.

Accumulation of Heavy Metals by Earthworms Exposed to Soil Contaminated with Thermal Power Station Condensate and Used Transformer Oil in Delta State, Nigeria

Ogana Joy — 2026-05-29

Changes in soil properties that reduce environmental services always result in a decline in soil quality. A variety of stressors, which may be physical, chemical, or biological and originate from both human and natural causes, could lead to these modifications. Using conventional laboratory methods, this study examined the physicochemical properties and heavy metal concentrations of soil samples from the condensate dump site and the electric transformer site in Delta State, Nigeria, as well as the earthworms introduced into the soil samples at varying degrees of contamination. The majority of the physicochemical parameters were higher in the condensate dump site soil than in the electrical transformer site soil, according to the findings. The heavy metals analysis in condensate, electrical transformer oil, soil samples from condensate dump site, and electrical transformer sites shows metal concentrations ranging from Cu 0.03-7.54ppm, Zn 0.12 - 4.33ppm, As 1.26 8 4.88ppm, Cd 0.01 -1.72ppm, Pb 2.10 - 4.22ppm, Hg 0.25 -2.19ppm, Fe 0.29 -2.34ppm, and Cr 0.12-1.8ppm. The earthworm accumulated metals from the soil in a contamination-percentage-dependent manner. Except for cadmium, which was above the DPR-established limit, the soil's heavy metals were all within the acceptable DPR limits. The study revealed that exposure to thermal power station condensate and used transformer oil resulted in heavy metal accumulation in earthworms, highlighting the environmental risks associated with soil contamination and the need for proper monitoring of industrial waste disposal practices.

Seasonal Evaluation of Agrometeorological Advisory Services and Farmer Response in Sugarcane Cultivation under GKMS

Ramanand Patel — 2026-05-30

Agrometeorological Advisory Services (AAS) blend weather cues with local insights, to give farmers more trustable, weather-driven agronomy suggestions that back climate resilient farming in a practical way. In this study, we look at how well the advisory services work in different seasons, especially those sent through the Gramin Krishi Mausam Sewa (GKMS) and the District Agromet Unit, demonstration program, focusing on sugarcane cultivation during 2022 in Bulandshahr district. For the analysis, data was taken from 1,392 farmers spread over four separate seasons. These were grouped using Standard Meteorological Weeks (SMWs) i.e. pre-monsoon, monsoon, post-monsoon and winter. What we observed was that the adoption of agromet advisories stayed fairly high throughout the year, about 81.03% up to 87.93%. The top value showed up in the post-monsoon season, when farm activities are usually less chaotic, and field operations can go more smoothly. On the satisfaction side, farmers also reported high levels. The satisfaction scores reached their best in winter and pre-monsoon, while the monsoon period showed lower satisfaction. The main reason mentioned was operational pressure and also the limited access to advisories during that time, which makes timely follow-up kind of harder. The study also points out a clear positive association between advisory relevance and farmer satisfaction, meaning when the guidance feels more location-appropriate and arrives on time, the overall experience improves noticeably. Yet, there was a negative impact on advisory effectiveness when there were delays in communication and slow response time. The ANOVA results indicated significant seasonal variation in farmers’ adoption behavior, confirming that weather conditions strongly influence the utilization of advisory services. Overall, the study demonstrates that agrometeorological advisories play a crucial role in improving decision-making in sugarcane farming by providing timely and relevant seasonal guidance. However, challenges during the monsoon period limit their full effectiveness. The study highlights the need to strengthen real-time communication systems and improve farmer preparedness to maximize the benefits of agrometeorological services.

Spatio-temporal Assessment of Meteorological Drought Dynamics and Precipitation Variability in Pauri Garhwal District, Uttarakhand, India

Kusum Rawat — 2026-05-30

Meteorological drought is one of the major climatic hazards in the Himalayan region, impacting the agricultural production, water resource availability, and environmental sustainability. In the present study, the spatio-temporal variability of meteorological dryness and precipitation patterns in the study area Pauri Garhwal has been evaluated with the help of long-term rainfall data (1994-2024). Rainfall Anomaly Index (RAI) was applied to the district's fifteen administrative blocks for determining drought severity, temporal variability and wet/dry variability of the rainfall. The investigation revealed that there is significant temporal and regional variability in the distribution of rainfall in the District. The mean annual rainfall was determined to be approximately 1146 mm and variation between blocks was also assessed. The southwest monsoon contributed to almost 80% of the annual precipitation indicating high dependence on monsoonal rainfall. Persistent negative rainfall anomalies were used to identify a number of severe drought years, including 1997, 2000, 2002, 2006, 2009, 2012, 2019, 2023, and 2024. With a RAI score of −8.1, Khirsu block had the worst drought severity in 1997. The results also revealed that the area was becoming more vulnerable to drought conditions, as negative rainfall anomalies were becoming more frequent. Lots of blocks in the district also experienced extended dry spells that correlated with an increased vulnerability to forest fires and dry vegetation. The study emphasizes how crucial sustainable watershed management and scientific drought monitoring are to climate adaption and environmental preservation in Himalayan regions.

Assessment of Knowledge about Climate Change among Dairy Farmers’ of Jharkhand

Kumari Shweta — 2026-05-30

Climate change has emerged as a global problem affecting each and every living organism. Dairy animals particularly the cattle and buffalo are suffering from direct impact like reduced feed intake causing reduction in milk production, infertility, delayed estrous, occurrence of diseases, and indirect impact like unavailability of green fodder round the year. Ultimately profitability for dairy farmers is negatively affected. Adequate knowledge of dairy farmers about the changing climate enables them to adopt mitigation strategies like using fans or sprinklers in the shed, providing fresh and cool drinking water, and changing the feeding time. In this context, the present study was carried out to know the knowledge level of dairy farmers about climate change among 240 dairy farmers from all the three agro-climatic regions (80 from each) of Jharkhand. Personal interview method using structured interview schedule was followed to collect the primary data.

The results indicated that maximum farmers had medium knowledge level about the climate change (60.83%) and its impact (66.67%). Most of the farmers had heard or read about climate change (67.50), thought that climate is really changing (71.25%), were sure that climate is changing (70.83), knew that climate change affects agriculture and animal husbandry (57.08%) and knew that indigenous breeds are better adapted to adverse climatic conditions (82.08%). The knowledge level of farmers was found to be significantly correlated with age, farming experience, annual income, SES and extension participation at 1% and with land holding at 5% level of significance. Education, gender and caste were also found to have significant effect on farmer’s level of knowledge about climate change. The findings underscore the urgent need for attention and action from relevant departments and organizations to support farmers in adapting to evolving environmental conditions.

Flora of Amahar Reservoir Wetland in Korea District, Chhattisgarh, India

Varun Kumar Kushwaha — 2026-05-30

Background: Wetlands are highly valuable ecosystems that purify water, support rich biodiversity, regulate wildlife populations, and provide essential ecological services crucial for sustaining life and environmental balance. The study focuses on floristic composition and ecosystem characteristics of Amahar reservoir wetland located at Amahar and Khairi village of Patna tahsil of Korea district of Chhattisgarh state of India. This medium sized manmade reservoir covers approximately 68.6 hectare area. The survey carried out between December 2025 to January 2026.

Objective: The study aim was documenting the floristic diversity of the wetland ecosystem and understanding the ecological interactions among flora, fauna, and abiotic environmental factors. Another objective was to recommend strategies for conservation of wetland for sustainable socio economic and ecological benefits.

Methodology: The study was carried out as an exploratory and observational field based ecological study. The survey was adopted a qualitative research approach with assessing floristic composition, ecological interaction and ecological health. accessible areas of the wetland included marshy shallow water areas, shoreline vegetation zones, submerged aquatic habitats and swampy margins and mudflats.

Results: This wetland have more marshy area which support more emergent, submerged and floating vegetation. We found a rich biodiversity of flora and fauna. Many local and migratory bird species also observed which is indicating availability of rich vegetation. Most dominant producers of wetland are Hydrilla, Chara, Spirogyra, Nymphaea, Nelumbo nucifera and Marsilea species. Butomopsis latifolia also observed growing abundantly near shore area of wetland. Many plant species of cyperaceae and convonvulaceae family is forming bushes and hedges including spike rush, Ipomaeaa near shore area. Clean water, high plant and avifaunal diversity indicate healthy wetland ecosystem. Absence of industries and urban settlements in catchment area of wetland is good for wetland health. Some rural settlement with hunting activity are identified. The wetland also supports local livelihood through irrigation and fishing activity. Ecological importance of wetland is very high for this area. Some protection strategies including monitoring of human activity, community awareness is essential for sustaining biodiversity and ensuring long term ecological and socio economic benefits. Deepen shore may be important to reduce human activities.

Conclusion: The observed rich plant diversity and ecosystem health indicate that Amahar Reservoir is relatively undisturbed and functioning efficiently as a natural system. The interaction between flora, fauna, and abiotic factors such as water availability and climate demonstrates a well-balanced ecosystem with human. The presence of dense avifaunal diversity in diverse ecological niches from submerged zones to marshy edges enhances species richness and ecological resilience.

Analysis of Temperature and Rainfall Trends from 1994 to 2024 in Kiminini Sub-County, Trans Nzoia County, Kenya

Beverly Mukoma Aura — 2026-06-01

Climate variability and climate change have increasingly affected agricultural productivity and rural livelihoods in Kenya, particularly in areas dependent on rain-fed agriculture. This study analyzed temperature and rainfall trends from 1994 to 2024 in Kiminini Sub-County, Trans Nzoia County. The study aimed to examine long-term changes in annual temperature and rainfall patterns and determine their implications for agricultural activities within the study area. A descriptive research design employing quantitative trend analysis methods was adopted. Secondary climatic data on annual rainfall totals and average annual temperatures were obtained from meteorological records, county agricultural reports, and climate databases. Data were analysed using descriptive statistics, linear regression analysis, graphical trend analysis, and the Mann–Kendall trend test. The findings revealed that average annual temperatures in Kiminini Sub-County increased steadily over the thirty-year study period at an estimated rate of approximately 0.05°C per year, indicating a significant warming trend. Rainfall patterns exhibited high interannual variability characterized by fluctuating annual totals, delayed onset of rainfall seasons, prolonged dry spells, and occasional extreme rainfall events. The Mann–Kendall test results showed a statistically significant increasing trend in annual temperature (Z = 2.84, p < 0.05), leading to rejection of the null hypothesis that no temperature trend existed between 1994 and 2024. Conversely, rainfall trends showed a weak declining and statistically insignificant pattern (Z = -1.21, p > 0.05), indicating that annual rainfall variability was high but lacked a strong monotonic trend over the study period. The study further established that increasing temperatures and irregular rainfall patterns negatively affected agricultural productivity through reduced soil moisture availability, increased crop stress, declining maize and wheat yields, and disruption of planting calendars among farmers. The study concluded that climate variability has intensified in Kiminini Sub-County and continues to threaten sustainable agricultural production and food security. The study recommends adoption of climate-smart agricultural practices, improved dissemination of climate information services, investment in irrigation and water conservation technologies, and strengthening of local climate adaptation strategies. The findings provide useful information for policymakers, researchers, agricultural extension officers, and farmers in developing effective climate resilience interventions within the study area.

Comparative Study of Forest Resource Management Initiatives in the Nchumuru and Adele Communities of the Oti Region, Ghana

Makpobi Kwasi Lapah — 2026-06-02

Background: Community-Based Forest Resource Management (CBFRM) has become an increasingly recognised approach for combining ecological stewardship with local empowerment, especially in rural settings where forests underpin food security, energy access, and cultural livelihoods. The Nchumuru and Adele communities, in particular, remain underrepresented in the literature, creating a contextual gap in understanding how local governance structures, cultural practices, and livelihood pressures shape community-based forest management outcomes.

Aim: This study comparatively assesses the effectiveness of community-based forest resource management (CBFRM) initiatives in the Nchumuru and Adele communities of the Oti Region in Ghana. It examines differences in participation, benefits derived from forest resources, and perceived performance of existing governance arrangements.

Methods: A quantitative cross-sectional research design was employed. A structured questionnaire survey was administered to 344 systematically selected respondents, 174 from Nchumuru and 170 from Adele. Data were analysed using descriptive statistics, cross-tabulation, and Chi-square tests in SPSS (Version 23) to determine the level of effectiveness and the extent of variation between the two communities.

Result: The results show that CBFRM initiatives are operational in both communities but vary in effectiveness. Nchumuru recorded higher participation in forest management activities, whereas Adele demonstrated stronger enforcement mechanisms through community by-laws. Respondents from both sites acknowledged ecological and livelihood benefits of forest management, though these were more pronounced in Nchumuru. Perceptions of effectiveness were generally moderate, with limited institutional support and weak monitoring practices identified as constraints.

Conclusion: The study highlights the need to strengthen enforcement, monitoring, and institutional support systems to enhance CBFRM outcomes, particularly in communities with weaker participation structures. Improved CBFRM effectiveness has the potential to enhance community cohesion, promote environmental stewardship, and sustain forest-dependent livelihoods, thereby contributing to rural socio-economic resilience. This study contributes empirical evidence on how different community governance structures influence the effectiveness of CBFRM initiatives. It advances comparative understanding of forest governance systems and supports context-sensitive policymaking for sustainable natural resource management.

Assessment of Climate Change, Rainfall Variability, and Displacement: Insights from Assam, India

Angita Gogoi — 2026-06-03

Assam, a flood-prone state in Northeast India, is increasingly experiencing erratic monsoon patterns and extreme rainfall events intensified by climate change. This study examines the relationship between rainfall variability and climate-induced displacement in Assam using secondary data from the Indian Meteorological Department (IMD), Assam State Disaster Management Authority (ASDMA), Disaster Reporting and Information Management System (DRIMS), and existing literature. The findings reveal that altered monsoon patterns, intense rainfall, floods, erosion, and landslides are contributing to infrastructural damage, livelihood insecurity, and recurring displacement across the state. Marginalized communities residing in char areas, riverbanks, and ecologically vulnerable regions are disproportionately affected by these environmental changes. The study further highlights how climate-induced disasters place severe pressure on local infrastructure, relief systems, and human security. By situating Assam within the broader discourse on climate vulnerability and internal displacement, the article argues that climate-induced displacement is not merely an environmental issue but also a developmental, governance, and human-rights challenge. It therefore emphasizes the need for long-term climate-resilient rehabilitation policies and integrated disaster governance frameworks to address growing displacement risks in vulnerable regions.

Soil Properties and Wheat Yield under STCR-Based Nutrient Application in an Inceptisol

Brijesh Kumar — 2026-05-30

Soil Test Crop Response-based nutrient application is an important strategy for improving soil fertility, nutrient use efficiency, and sustainable wheat production in Agronomy. Inceptisols, widely cultivated for wheat, often face nutrient imbalances that limit productivity and soil health. A field experiment was conducted for two consecutive years during the Rabi seasons of 2020-21 and 2021-22, at Sam Higginbottom University of Agriculture, Technology & Sciences, Prayagraj, District of Uttar Pradesh. The central objective of this experimentation was to evaluate the implications of employing a Soil Test Crop Response (STCR) strategy for fertilizer application and its chaser impact on soil attributes and yield within the background of Inceptisol soil order, with a focused attention on wheat (Triticum aestivum L.) cultivate within the Prayagraj region. Sandy loam in soil texture, belongs to soil order Inceptisol and neutral in soil reaction. Soil samples were taken from two depth viz.0-15 cm and 15-30 cm and analyzed for their physico-chemical properties (BD, PD, Soil pH, and OC). The experiment was carried out in Randomized Block Design and replicated thrice with 9 treatments. The best treatment combination was (T₉) STB (100:75:50 NPK kg/ha + FYM 15 t/ha), which displayed grain yield of 6.50 t /ha on a pooled basis respectively. It is concluded that the advantageous use of NPK fertilizers with FYM- based organic fertilizer on STCR standpoint not only grant best wheat yield but also increased soil status and environment approachable.