Journal of Geography, Environment and Earth Science International

Fluids—The Basis for the Formation of Vein-type Mineral Complexes in Sedimentary Coal-bearing Strata

Nataliia Vergelska, Viktoriia Vergelska, Dina Holovchenko — Tue, 15 Sep 2026 00:00:00 +0000

The sedimentary strata of the lithosphere are constantly changing under the influence of tectonic deformations, lithogenic processes, and fluid movement. The study of secondary processes in the upper layers of the lithosphere is possible in natural outcrops or man-made engineering structures that expose the sedimentary strata: tunnels, quarries, adits, and mines. In most cases, fluid systems are recorded as fractures or discontinuities, forming a network of vertical, horizontal, or vertical-horizontal—predominantly carbonate—veins.

This study aims to identify the geological processes that contributed to the development of secondary fluid processes and the formation of calcite and quartz-calcite veins in the sedimentary strata of coal basins. Geological studies of calcite and quartz-calcite systems in sedimentary strata, including the possibility of their modern occurrence, were conducted and summarised. Spectral analysis was performed on coal and host rocks containing calcite veins and carbonate formations from mine workings after preparation for laboratory analysis.

The formation of vein-type mineral complexes indicates post-depositional processes involving fluid transport and fracture-filling mechanisms in sedimentary rocks characteristic of the coal-bearing massifs of the Krasnoarmiysk, Dovzhano-Rovenky, Central, and Donetsk-Makiivska coal industrial regions of the Donbas. Calcite inclusions and calcite veins that disrupt the integrity of the coal matrix were also identified in sections m₂, m₃, m₄², l₁^c, l₂, l₃, and l₄^a. Thus, directly or indirectly, the formation of mineral veins in the coal-bearing strata of the Donets Basin influences gas redistribution within the sedimentary strata they alter. Fluid migration continues within the newly formed voids—including those of anthropogenic origin—which are represented by both carbonate formations and gas reservoirs in the coal-bearing massifs. In the Earth’s lithosphere, during fluid migration and conservation, new carbonate mineral systems form that can still be studied today. Given their formation and genesis, tectono-magmatic or post-magmatic processes—including hydrothermal ones—play a leading role.

In situ Physicochemical Characterisation of Spring Waters in Crystalline Basement Environments: A Comparative Analysis with Surface Waters and Deep Groundwater in Daloa, Côte d’Ivoire

Fri, 14 Aug 2026 00:00:00 +0000

Maintaining the availability of groundwater, in terms of both quantity and quality, is essential to guarantee access to drinking water in many countries around the world, particularly in the bedrock regions of West Africa. In most crystalline bedrock areas of West Africa, due to the poor quality of surface water, people are increasingly turning to groundwater, particularly water from springs. In the municipality of Daloa (central-western Côte d’Ivoire), spring water is increasingly being used by all social groups to meet their drinking water needs. This study aims to understand the interactions between different water resources using physicochemical parameters in order to better guide policies for the management of springs in the localities of Daloa, which are under increasing pressure from the local population. This study is based on the statistical analysis of a dataset collected during a campaign to measure the physicochemical parameters of water in the Tétégbeu River catchment area in Daloa. Data collection was carried out according to a rigorous protocol, with quality control checks performed on each parameter measured. The physicochemical parameters, notably temperature, pH, electrical conductivity and redox potential, were measured in situ using a multi-parameter analyser. The results show that the spring waters generally exhibit physicochemical characteristics intermediate between those of surface water and deep aquifers. However, several parameters, notably temperature, pH, electrical conductivity and redox potential, indicate a closer resemblance to water from deep aquifers extracted via boreholes. This similarity suggests that deep aquifers contribute to the existence of the springs, with a limited but not negligible contribution from watercourses (rivers). Thus, the springs appear to be transitional waters that emerge from shallow aquifers with a contribution from deep aquifers, but which may be locally influenced by inflows from rivers. This dual influence gives the springs a distinctive physicochemical signature, reflecting both the dynamics of underground flow and interactions with the surface environment. These results contribute to a better understanding of the hydrogeological behaviour of spring waters in a crystalline basement context and provide an essential basis for guiding spring management policies, particularly in the face of increasing pressure from human activities.

Physiological and Multivariate Characterization of Chitosan-Indiced Drought Tolerance in Groundnut (Arachis hypogaea L.) Seedlings

Srijan Samanta, Sanjay Kumar Bordolui — Wed, 19 Aug 2026 00:00:00 +0000

Early-stage drought stress severely limits seedling establishment in groundnut (Arachis hypogaea L.), necessitating effective biostimulant-based approaches to enhance drought tolerance. This study aimed to identify the optimum foliar concentration of chitosan for improving seedling growth and physiological performance under contrasting moisture regimes using integrated multivariate analyses. A factorial completely randomised design with three replications was employed, comprising two moisture regimes (well-watered and water-stressed) and six chitosan concentrations (0, 100, 200, 300, 400, and 500 ppm). Chitosan was applied as a foliar spray at 15 days after sowing, and growth, biomass, relative leaf water content (RLWC), membrane stability index (MSI), and cellular metabolic activity were evaluated after 15 days. Chitosan significantly enhanced all measured traits under both moisture conditions, with responses increasing up to 300 ppm before declining at higher concentrations. The 300 ppm treatment produced the highest shoot length (27.01 cm), root length (19.55 cm), fresh biomass (3.32 g seedling⁻¹), RLWC (84.83%), MSI (83.00%), and cellular metabolic activity (2.14 A₄₈₅ g⁻¹ FW). Pearson's correlation analysis revealed strong positive associations among growth, biomass accumulation, water status, membrane stability, and cellular metabolic activity, while principal component analysis explained 87.2% of the total variation. The Composite Performance Index (CPI), integrated with quadratic regression, predicted optimum chitosan concentrations of approximately 322 ppm under water stress and 300 ppm under well-watered conditions. As both predicted optima closely corresponded to the tested 300 ppm treatment, this concentration was identified as the practical optimum. These findings demonstrate that foliar application of chitosan at 300 ppm effectively enhances seedling vigour and physiological resilience under both drought-stressed and well-watered conditions, providing a scientifically validated dose for future greenhouse and field evaluation.

Stakeholder Utilization of Weather Information from Mazimbu Weather Station in Morogoro Municipality, Tanzania

Idrisa Abuu Lema — Tue, 25 Aug 2026 00:00:00 +0000

Weather information is essential for weather-sensitive sectors such as agriculture, education, research, transportation, and environmental management. Despite its importance, evidence on stakeholder utilisation of localised weather information services in Tanzania remains limited. This study assessed stakeholder utilisation of weather information generated by the Mazimbu Weather Station in Morogoro Municipality, Tanzania, to identify primary users, examine utilisation patterns, and evaluate factors influencing weather service use.

A mixed-methods design was employed, using structured questionnaires administered to 60 respondents, key informant interviews with meteorological personnel, a review of the station visitor register, and field observations. Quantitative data were analysed using descriptive statistics and chi-square tests, while qualitative data were analysed thematically.

The findings revealed that university students, university staff, and secondary school students were the primary users of weather information, with most users originating from Morogoro Municipality. Accessibility, convenient location, and quality consultation services were identified as the station's main strengths, while learning, field practical training, and research were the principal reasons for utilisation. However, inadequate meteorological instruments, limited technological capacity, a shortage of technical staff, and conditions in the surrounding environment constrained effective service delivery and broader stakeholder utilisation.

The study concludes that the Mazimbu Weather Station provides valuable localised weather information, particularly for academic and educational purposes. Strengthening meteorological infrastructure, technological capacity, technical staffing, and stakeholder awareness would broaden utilisation beyond academia and support evidence-based decision-making across weather-sensitive sectors.

Climate Variability, Cocoa Production Decline and Livelihood Vulnerability among Smallholder Farmers in Mbam and Kim Division, Centre Region, Cameroon

Ngwang Brain Ngwang, Fombe Lawrence Fon, Tata Emmanuel Sunjo — Thu, 27 Aug 2026 00:00:00 +0000

Climate variability poses substantial challenges to cocoa-dependent smallholder livelihoods in Mbam and Kim Division, Centre Region of Cameroon. This study examined the effects of climate variability on cocoa production and household livelihoods in Mbam and Kim Division, Centre Region of Cameroon, using data from 1994 to 2024 for the Mbangassina and Yoko Sub-divisions. A mixed-methods design combined a survey of 303 cocoa-farming households, focus group discussions, key informant interviews, field observations, and 31 years of NASA POWER climate data. Over the study period, rainfall declined significantly in both Sub-divisions, while temperature increased by about 1.1 degrees Celsius. These changes disrupted the cocoa production system at every stage: most farmers reported increased black pod disease and mirid attacks, and 82 per cent reported declining cocoa yields, with a typical loss of about half of previous production. The production decline translated directly into household hardship. Most households reported declining cocoa income, most depended on cocoa for more than 60 per cent of their cash income, and more than half experienced food insecurity, while many struggled to meet school costs. All these effects were statistically significant, and none differed meaningfully between the two Sub-divisions, indicating a shared regional climate problem rather than an isolated local occurrence. The findings show that, because these households depend heavily on a single climate-sensitive crop, a shock to cocoa production rapidly affects income, food, schooling, health, and general wellbeing. The study recommends climate-smart cocoa practices, support for genuine income diversification, investment in rural roads, and stronger access to credit and social protection for cocoa-farming households.

Geospatial Engineering Geological Rock Mass Characterization and Classification using Multicriteria Analytical Hierarchy Decision Process (AHP-MCDA) in Ondo State, Southwestern Nigeria

O. O. Falowo, J. O. Owoseni, G. O. Oniyide, K. O. Olayiwola, G. K. Martins — Thu, 27 Aug 2026 00:00:00 +0000

This study provides quantitative and qualitative information on the strength/competency of rock masses in Ondo State, southwestern Nigeria, for slope, foundation, and tunnel applications. In addition, parameters influencing the general behaviour/characteristics of the rock masses, as well as the most suitable rock classification system(s), were duly identified. The study employed nine systems (RMR, Q-system, modified Q-system, RMN, RMI, GSI, SMR, RSR, and RQD), which were ranked using the AHP-MCDA method. All the parameters required were obtained through engineering geological mapping and laboratory analysis. The AHP-MCDA generated a strength map that categorised the area into five classes, comprising very weak (8 %), moderately weak (23 %), moderately strong (37 %), strong (18 %), and very strong (14 %), with areal extents of 384 km², 5399 km², 6524 km², 2232 km², and 461 km², respectively. The very strong rock masses usually have lower fracture frequency and are slightly weathered. These rocks are predominantly porphyritic granite, charnockite, granite gneiss, fine-grained granite, biotite granite, and gneisses. Among these rocks, the fine–medium and medium-coarse-grained granite (including aplites, dolerites, and some hypabyssal rocks occurring as dykes) showed the best geomechanical attributes and ranked very high by all the systems. The migmatite/migmatite gneiss, pegmatite, and some porphyritic granite constitute the moderately strong rocks. The quartz schist, mica – quartz schist, and the flaggy quartzite constitute the moderately weak rocks, while Dahomey Basin deposits make up the very weak rock units. Within the adopted AHP framework, the most suitable system is the RMR, with a weight of 31.752 %, followed by the modified Q-system (23.365 %), Q-system (16.769 %), RMN (8.588 %), RMI (6.243 %), RSR (4.815 %), GSI (3.645 %), SMR (2.994 %), and RQD (1.828 %), respectively. Overall, the AHP-MCDA map zonation highlights the importance of composite evaluation rather than relying on a single system of characterisation and classification.

Calibration and Validation of AquaCrop Model for Rice under Prayagraj Agro-Climatic Conditions

M. Daniel Rohith, Sharddha Rawat — Thu, 27 Aug 2026 00:00:00 +0000

Rice (Oryza sativa L.) is the principal food crop of the Indo-Gangetic plains, and its sustainable production is increasingly constrained by water scarcity and climatic variability. Crop simulation models offer a robust means of evaluating crop response to management practices without the cost and time demands of exhaustive field trials. This study calibrated and validated the FAO AquaCrop model for rice cultivar SARJU-52 grown under three transplanting dates (1, 11 and 21 July) and five irrigation regimes (rainfed, continuous flooding, alternate wetting and drying, irrigation at 3-day intervals, and irrigation at 7-day intervals) at the Field Nursery, College of Forestry, SHUATS, Prayagraj, during the 2019 and 2020 kharif seasons. Field-observed grain yield, above-ground biomass, harvest index and canopy cover (derived from Leaf Area Index using the Beer–Lambert relationship) from 2019 were used to calibrate the model, while the independent 2020 dataset was used for validation. Model performance was assessed using the root mean square error (RMSE), normalised RMSE (NRMSE), coefficient of determination (R²) and mean absolute error (MAE).

The calibrated model reproduced observed grain yield with R² values of 0.97 (sowing windows) and 0.94 (irrigation schedules) during calibration, and R² values of 0.92 and 0.93, respectively, during validation, with correspondingly low RMSE and NRMSE. Biomass simulations showed R² values of 0.88 or above in both phases, while canopy cover at 60 and 90 days after sowing was reproduced with NRMSE values generally below 5%. Among treatments, early transplanting (1 July) and moderate, well-timed irrigation (alternate wetting and drying and 7-day interval irrigation) produced the highest observed and simulated yields, whereas rainfed conditions and delayed transplanting reduced productivity. These results confirm that AquaCrop, after site-specific calibration, is a dependable decision-support tool for simulating rice growth, yield and water-use responses under the agro-climatic conditions of Prayagraj and provides a validated basis for subsequent irrigation-scheduling and climate-impact studies.

Food Security in Transition: A Subdivision-Level Study of Jangalmahal Using Multivariate Techniques

Nasim Aktar, Sanchari Majumdar — Tue, 01 Sep 2026 00:00:00 +0000

Background: Food security in Jangalmahal is characterised by substantial spatial disparities arising from differences in agricultural productivity, irrigation coverage, access to agricultural inputs, infrastructure, employment opportunities, and socio-economic conditions. Although the region is predominantly dependent on agriculture, subdivision-level variations in these factors may result in unequal food-security outcomes. A multidimensional assessment is therefore required to identify the spatial pattern of food security and the principal factors associated with these disparities.

Aims: To examine the level of food security in the Jangalmahal region and analyse the correlation between the food security index and the different variables affecting food security in the region.

Study Design: This study uses a Composite Z-score technique to examine food security at the subdivision level, considering a number of indicators affecting the region. Principal Component Analysis was subsequently used to highlight the most important variables.

Place of Study: The study was conducted in the Jangalmahal region, which includes Purulia, Bankura, Jhargram, and Paschim Medinipur. This region faces multiple socio-economic, infrastructural, and environmental constraints.

Methodology: The study analyses the correlation matrix to identify relationships between key indicators, such as calorie availability, agricultural productivity, infrastructure, and socio-economic factors. Principal Component Analysis (PCA) was applied to reduce dimensionality and identify the most important variables.

Results: About 30% of the subdivisions, namely Purulia Sadar (West), Purulia Sadar (East), and Raghunathpur, lying in the north-western part of the region, belong to the category of extreme food insecurity. Principal Component Analysis (PCA), which extracted four significant components explaining 67.04% of the total variance (KMO = 0.785; p < 0.001), was employed to reduce dimensionality and highlight the most important variables influencing food security. The results reveal substantial spatial disparities: southeastern subdivisions, such as Ghatal and Kharagpur, exhibit higher food security due to better irrigation coverage, greater access to agricultural inputs, higher road density, and higher employment rates. Conversely, central and western subdivisions, such as Bankura Sadar and Khatra, fall into medium or low food security categories due to limited irrigation facilities and reliance on rainfall.

Conclusion: This study emphasises the need for targeted interventions in irrigation expansion, infrastructure development, and socio-economic improvements to address food insecurity in this region effectively. Improving irrigation facilities, fertiliser availability, seed distribution, farmers’ literacy rates, and access to drinking water would contribute to enhanced food security.

Ecological Assessment of Riparian Vegetation Diversity and Phytosociological Structure Along the Arpa River, Central India

Alok Singh Bargah, Damini Sharma, Rajesh Kumar, Avinash Udikeri — Thu, 10 Sep 2026 00:00:00 +0000

The present study assessed the floristic composition, phytosociological structure, diversity and conservation status of riparian vegetation along the Arpa River in Bilaspur district, Chhattisgarh, India during 2024–25 and 2025–26. The study was conducted along the selected river stretch from Seepat Chowk, Bilaspur, to Arpa Bridge, Belgahna, covering a total research area of approximately 62 km. The river stretch was classified into three disturbance zones based on anthropogenic pressure: Zone I, Highly Disturbed Urban Area; Zone II, Moderately Disturbed Semi-urban/Rural Area; and Zone III, Least Disturbed Forest/Remote Area. Vegetation sampling was conducted using simple random sampling, with ten 10 m × 10 m quadrats established in each zone, giving a total of 30 quadrats and a sampled area of 3000 m². A total of 46 plant species, comprising 32 tree species, 9 shrub species, and 5 herbaceous species, were recorded from the sampled riparian vegetation. The recorded flora represented 25 families based on the complete species inventory. Fabaceae was the most species-rich family, contributing 10 species, whereas Asteraceae contributed the highest number of individuals. The phytosociological assessment revealed considerable variation in frequency, density, basal area and Importance Value Index among species. Parthenium incanum recorded the highest IVI (14.96), followed by Parthenium hysterophorus (14.30), Ruellia tuberosa/Ruellia spp. (11.84), Ipomoea carnea (11.52) and Solanum nigrum (10.61), while Terminalia tomentosa recorded the highest IVI among the tree species (10.21) in the principal phytosociological dataset. All were significant at p < 0.05. The results reveal a species-rich but invasion-prone riparian corridor whose structural integrity depends strongly on the near-channel zone, providing a quantitative baseline for riparian management, invasive species control and biodiversity conservation in Central Indian river systems.

Long-term Analysis of Rainfall Variability and Drought Characteristics for Climate-resilient Agricultural Planning in Ballari District, Karnataka, India

Umarfarooque Momin, Dinesh Kumar S. P., Kumara. B. H., Premkumara — Fri, 11 Sep 2026 00:00:00 +0000

Rainfall variability and drought occurrence are major challenges affecting agricultural productivity and water resource management in the semi-arid regions of India. The present study was undertaken to analyse long-term rainfall variability, rainfall anomalies, drought characteristics and rainfall trends in Ballari district of Karnataka and to assess their implications for agricultural sustainability. Daily rainfall data from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) dataset for the period 1981–2025 were used for the analysis. Annual rainfall variability was evaluated using descriptive statistical measures, while rainfall anomalies were assessed using the Rainfall Anomaly Index (RAI). Drought characteristics were examined using the Standardized Precipitation Index (SPI-12), and long-term rainfall trends were analysed using the Mann–Kendall test and Sen’s slope estimator. The results indicated that the long-term mean annual rainfall of Ballari district was 511.25 mm, with substantial interannual variability. The coefficient of variation was 24.07%, reflecting considerable year-to-year fluctuations in rainfall. Rainfall classification revealed that, out of 45 years analysed, 12 years were classified as deficit rainfall years, 21 years as normal rainfall years, and 12 years as excess rainfall years. RAI analysis demonstrated the recurrent occurrence of both wet and dry anomalies, highlighting the highly variable nature of rainfall in the district. SPI analysis further indicated the occurrence of recurring drought conditions, with several years experiencing moderate to severe moisture deficits. Trend analysis using the Mann–Kendall test and Sen’s slope estimator showed no statistically significant long-term trend in annual rainfall, suggesting that climatic risks in the district are primarily associated with rainfall variability and extreme events rather than systematic changes in mean rainfall. The study concludes that agriculture in Ballari district remains highly vulnerable to rainfall variability, drought recurrence and extreme rainfall events. Strengthening climate-resilient agricultural practices, improving soil and water conservation measures, promoting rainwater harvesting and enhancing weather-based agro-advisory services are essential for improving agricultural sustainability and resilience under changing climatic conditions.

Spatiotemporal Assessment of Evapotranspiration and Its Components in the Ahmedabad District, India: A Two-decadal Comparison Using Satellite Remote Sensing (2003-2023)

Rahul Kumar, K. C. Patel — Fri, 25 Sep 2026 00:00:00 +0000

Ahmedabad District, situated in the middle reaches of the semi-arid Sabarmati Basin, has undergone rapid urbanisation, groundwater over-abstraction, and changes in cropping intensity over the past two decades. Quantifying how these transformations have altered evapotranspiration (ET) and its partitioning among soil evaporation (E), interception (I), and canopy transpiration (T) is critical for district-scale water-resource planning. This study uses the operational SSEBop V6.1 monthly actual evapotranspiration product (1 km resolution), together with a sequential remote-sensing partitioning approach in which transpiration and interception are estimated from satellite-derived vegetation and rainfall inputs, while soil evaporation is derived as a residual. Spatial and temporal patterns of ET, E, I, and T are compared for Ahmedabad District between the water years 2003 and 2023. The results indicate that annual total ET remained nearly unchanged (729.99 mm in 2003 versus 721.88 mm in 2023, a decrease of approximately 1.1%); however, the internal composition of ET changed markedly. Soil evaporation increased by 5.8% (534.0 mm to 564.9 mm), interception increased by 32.8% (11.3 mm to 14.9 mm), and canopy transpiration decreased by 23.1% (184.8 mm to 142.0 mm). The E/ET ratio rose from 73.1% to 78.3%, while the T/ET ratio declined from 25.3% to 19.7%, indicating a shift towards direct, non-productive water loss. The monthly pattern also became less pronounced, with substantially higher winter values and lower monsoon peaks in 2023 than in 2003. These findings suggest a transition towards a more evaporation-dominated hydrological regime, although part of the transpiration signal may reflect known biases in the absolute ETₐ magnitudes reported for SSEBop and therefore warrants further validation. The study demonstrates the value of ET partitioning for diagnosing changes in water productivity in rapidly urbanising semi-arid districts.

Multidimensional Crisis of the Intermunicipal System of Drinking Water and Sewerage Services (SIAPA) in the Guadalajara Metropolitan Area: A Documentary Analysis of Water Security, Finance, Social Equity and Public Health

Sat, 26 Sep 2026 00:00:00 +0000

The Intermunicipal System of Drinking Water and Sewerage Services (SIAPA) in the Guadalajara Metropolitan Area (GMA) faces a multidimensional water-security challenge involving source availability and quality, infrastructure condition, operational efficiency, financial stress, unequal service impacts and public-health protection. This study undertook a structured documentary analysis of official information, regulatory standards, peer-reviewed literature and time-bounded public reporting, with the evidence updated to 29 August 2026, and developed qualitative policy scenarios for 2026–2035. Current CONAGUA data show negative average annual availability in five aquifers relevant to the metropolitan area, with a combined deficit of approximately 122.38 hm³/year. For Lake Chapala, published analysis of CONAGUA monitoring for 2012–2022 reported 26 of 35 sites in yellow or red categories. Public reporting on SIAPA's 2025 monitoring indicated that 278 of 1,180 monitored points (23.6%, publicly reported as 23%) were outside NOM-127-SSA1-2021 for at least one reported parameter; this is a surveillance signal, not an estimate of population exposure or disease incidence. Transparency-based reporting in August 2026 placed SIAPA's gross overdue portfolio at MXN 20.807 billion across 585,434 users, although recoverability requires account-level assessment. The synthesis identifies a reinforcing relationship among source stress, infrastructure deterioration, service failures, financial constraints and loss of trust. A recovery strategy is proposed around source protection, standardised water balances and loss reduction, asset renewal, treatment modernisation, financial restructuring, independent water-quality surveillance, water justice, reuse, energy efficiency and metropolitan governance. The proposed risk matrix, composite index and scenario trajectories are explicitly exploratory decision-support tools rather than validated forecasts.

Physical Soil Degradation and Geochemical Anomaly at an Artisanal Gold-mining Site in Zanikaha, Northern Côte d’Ivoire

Mon, 28 Sep 2026 00:00:00 +0000

Background: Artisanal gold mining can disrupt soil profiles, reduce soil fertility, and redistribute potentially toxic elements, but integrated site-specific information for Zanikaha remains limited.

Aim: This study aimed to assess the physical degradation, fertility status, and geochemical quality of soils affected by artisanal gold mining at Zanikaha in northern Côte d’Ivoire. It specifically sought to characterise mining-induced landscape disturbances, determine the main soil physicochemical properties, and identify potential anomalies in trace-element concentrations.

Methodology: Field investigations combined a morphopedological survey along a toposequence, the description of two soil profiles, and composite sampling of the 0-30 cm surface layer. Laboratory analyses included particle-size distribution, agronomic parameters, and multi-element geochemical measurements. The survey covered 37.2 ha and documented the major forms of land disturbance associated with artisanal mining activities.

Results: The study area showed severe physical degradation, characterised by topsoil stripping, excavations, waste-rock piles, washing sludge, and disrupted surface drainage. The soils were predominantly Ferralsols with plinthic properties and exhibited low organic fertility. Organic matter ranged from 2.41 to 8.62 g kg⁻¹, whereas total nitrogen ranged from 0.4 to 0.6 g kg⁻¹. Available phosphorus locally reached 71.7 mg kg⁻¹. Total arsenic concentrations at Zanikaha ranged from 207.989 to 267.735 mg kg⁻¹, compared with 8.669 mg kg⁻¹ at Gbini, indicating a marked arsenic anomaly. Lead concentrations remained low, while cadmium, mercury, and cyanide were below the reported limits of quantification.

Conclusion: The findings demonstrate severe physical soil degradation and a pronounced arsenic anomaly at the Zanikaha artisanal gold-mining site. However, the absence of a matched local reference site, the limited analytical dataset, and the lack of arsenic speciation and bioaccessibility data prevent exclusive attribution of the anomaly to mining activities and do not allow a direct human-health risk assessment. Integrated monitoring of soils, surface water, groundwater, mining residues, dust, and food crops is therefore recommended to clarify contaminant sources, transfer pathways, and potential environmental and health risks.

Biomass, Carbon Stock and Co₂-Equivalent Storage in Roadside Plantations of Naya Raipur, Chhattisgarh, India

Rajesh Kumar, Shalini Toppo — Wed, 30 Sep 2026 00:00:00 +0000

Roadside plantations constitute important linear green infrastructure in rapidly urbanising landscapes, but their contribution to biomass accumulation and carbon storage is often insufficiently quantified. This study estimated aboveground biomass (AGB), belowground biomass (BGB), total biomass, carbon stock and the corresponding CO₂ equivalent of roadside plantations in four zones of Naya Raipur, Chhattisgarh, India. Biomass was estimated through a non-destructive approach using diameter at breast height (DBH), tree height and wood density. BGB was estimated as 20% of AGB, while carbon stock was calculated using a biomass-to-carbon conversion factor of 0.47, and the CO₂ equivalent was calculated using a factor of 3.67. Across the study area, total biomass was 292.82 t ha⁻¹, including 244.04 t ha⁻¹ AGB and 48.81 t ha⁻¹ BGB. The West zone recorded the highest total biomass (161.33 t ha⁻¹) and carbon stock (75.83 t C ha⁻¹), whereas the South zone recorded the lowest values (25.10 t ha⁻¹ and 11.80 t C ha⁻¹, respectively). The aggregate carbon stock was 137.65 t C ha⁻¹, corresponding to 505.08 t CO₂-e ha⁻¹. Cassia siamea showed the highest species-wise total biomass (46.91 t ha⁻¹), while Acacia nilotica contributed the highest CO₂ equivalent in the zone-wise assessment (52.54 t CO₂-e ha⁻¹ in the West zone). The findings indicate substantial spatial and species-level variation in the carbon storage capacity of roadside plantations. Since the study used stock-conversion calculations rather than repeated temporal measurements, the reported CO₂ values should be interpreted as the CO₂ equivalent of stored carbon, not as an annual sequestration rate.

Geospatial Techniques for Identifying Land Degradation Driven by Climate Change-induced Multi-hazards in Tropical Regions: A Critical Narrative Review

H. M. B. S. Herath, K. D. P. P. Jayasinghe, I. T. H. Kokawalage — Tue, 15 Sep 2026 00:00:00 +0000

Tropical land systems are exposed to an unusually dense combination of hazards, including cyclones, extreme rainfall, riverine and coastal flooding, prolonged dry spells, wildfire, mass movement, salinisation and land subsidence. These hazards rarely act in isolation, and their combined imprint on soils, vegetation and hydrology is frequently interpreted as land degradation. Geospatial techniques based on satellite time series, active microwave sensing, cloud computing and machine learning now supply most of the evidence used to identify and report such degradation, yet the interpretive foundations of that evidence remain contested. This critical narrative review examines how geospatial methods identify land degradation attributable to climate change-induced multi-hazards in tropical settings, and evaluates the strength, consistency and limitations of the supporting literature published between January 2000 and 8 July 2026. Literature was identified through Crossref, the Directory of Open Access Journals, Semantic Scholar and Google Scholar, supplemented by citation chaining and searches of authoritative institutional sources. The synthesis identifies four persistent problems. First, definitional plurality means that measured quantities differ across studies that report the same nominal phenomenon, and global degradation hotspots diverge substantially according to the indicator selected. Second, the dominant trend-based and residual-trend methods have limited statistical power for gradual change, and are structurally poor at separating climate-driven variability from persistent capacity loss, which matters acutely where hazards recur. Third, persistent cloud cover in humid tropical regions displaces monitoring towards active microwave and fused data streams, whose degradation-relevant interpretation is less mature than that of optical vegetation indices. Fourth, multi-hazard and multi-risk frameworks and land degradation monitoring have developed largely in parallel, so the cumulative and cascading pathways through which sequential hazards deplete land capacity are seldom represented explicitly. Evidence is strongest for detecting abrupt, spatially extensive disturbance and weakest for attributing chronic degradation to specific hazard sequences. Priorities include hazard-conditioned baselines, sequence-aware detection, probability-based validation adequate to hazard footprints, and greater representation of small tropical states in the evidence base.

Climate Change: A Driver of Variability in Phytopathogens

Abhay Sharma, Archana Kushwaha, Aditi Dobhal, Riya, Preeti Massey — Wed, 16 Sep 2026 00:00:00 +0000

Climate change is altering the environmental conditions that regulate phytopathogen survival, reproduction, dispersal, infection and interactions with host plants and vectors. This review examines climate change as a driver of variability in phytopathogens, with emphasis on changes in population dynamics, geographical distribution, genetic and phenotypic characteristics, virulence or aggressiveness, host range, adaptation and epidemiological traits. Temperature, precipitation, humidity, atmospheric CO₂ and extreme climatic events can modify pathogen performance and inoculum availability, but responses are strongly pathogen-specific and depend on host susceptibility, environmental context and pathogen thermal or ecological tolerances. Climate-driven redistribution and selection may alter the relative fitness of existing pathogen genotypes and phenotypes, creating opportunities for population differentiation, local adaptation and establishment in new geographical or ecological settings. These changes can also shift epidemic timing and duration, disease incidence and severity, inoculum production, dispersal, co-infection outcomes and vector-mediated transmission. Consequently, the reliability of host resistance, chemical control schedules, forecasting models and early-warning systems may change under future climatic conditions. Effective management will require climate-informed surveillance, regular validation of forecasting tools, genomic monitoring, durable resistance and integrated disease management adapted to local pathogen characteristics. Multidisciplinary integration of plant pathology, climatology, epidemiology, genomics and crop science is therefore important for anticipating emerging disease risks and supporting more adaptive and sustainable plant disease management under changing climates.

Remote Sensing and GIS in Modern Drought Assessment: Bridging Conventional Methods and Emerging Technologies

Thu, 24 Sep 2026 00:00:00 +0000

Drought is a complex and recurring hydroclimatic hazard that affects agricultural production, water resources, ecosystems and socioeconomic development. Effective drought assessment requires approaches capable of capturing its spatial and temporal variability and its multiple dimensions. This review examines the evolution of drought assessment from conventional drought indices to integrated approaches based on remote sensing and Geographic Information Systems (GIS), with an emphasis on their applications, strengths, limitations and emerging developments. Conventional indices, including the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Palmer Drought Severity Index (PDSI), Reconnaissance Drought Index (RDI) and Percent of Normal Precipitation Index (PNPI), remain widely used because of their established methodologies and long-term applicability. However, their dependence on meteorological observations can limit spatial characterisation and the representation of vegetation, soil moisture and other land-surface responses. Remote sensing provides spatially extensive and repeated observations of vegetation condition, land surface temperature, soil moisture, evapotranspiration and water-related conditions, enabling the development of satellite-derived drought indicators and indices. GIS further facilitates the integration, spatial analysis, visualisation, and mapping of drought-related information from multiple sources. The review also discusses hybrid approaches that combine climate-based indices with satellite-derived indicators, as well as drought monitoring platforms and multi-source assessment frameworks. Despite substantial advances, challenges remain regarding cloud contamination, differences in spatial and temporal resolution, data continuity, ground-based validation and uncertainty associated with multi-source datasets. Emerging machine learning, deep learning and artificial intelligence approaches offer opportunities for integrating heterogeneous datasets and improving drought characterisation and early warning. Overall, the integration of conventional observations, remote sensing, GIS and advanced analytical approaches provides a promising framework for more comprehensive drought monitoring and risk assessment under increasing climate variability and change.

Spatial Estimation of Carbon Sequestration Using Remote Sensing and Its Application in Carbon-credit Assessment: A Comprehensive Review

Aishwarya Desai, Himalaya Ganachari, Sangita Shinde, Sachinkumar Nandgude — Fri, 25 Sep 2026 00:00:00 +0000

Carbon sequestration is fundamental to climate-change mitigation because terrestrial and aquatic ecosystems store carbon in vegetation, biomass, soils, and the Earth’s crust. Reliable estimation of carbon stocks and their temporal and spatial changes is essential for the formulation of climate policy, ecosystem management, carbon accounting, and carbon-credit assessment. Conventional field measurements provide detailed information but are constrained by sampling requirements, cost, labour, spatial heterogeneity, and limitations in continuous monitoring. Remote sensing provides a complementary approach by enabling spatially continuous observations of vegetation characteristics, land-cover change, biomass, and other carbon-related variables across different spatial and temporal scales. Advances in multispectral, hyperspectral, synthetic aperture radar, LiDAR, thermal, and high-resolution satellite observations have extended the capability for carbon estimation. Their integration with geographic information systems, field observations, statistical techniques, and machine-learning algorithms enables precise spatial assessment of above-ground biomass, below-ground biomass, soil organic carbon, forest carbon, agricultural carbon, mangrove carbon, and blue-carbon resources. However, uncertainties associated with sensor characteristics, field-data quality, model selection, spatial variability, temporal dynamics, and scaling remain acknowledged limitations. Converting spatial carbon estimates into carbon credits requires consideration of baseline conditions, additionality, permanence, leakage, uncertainty, verification, and measurement, reporting, and verification requirements. This review critically examines remote sensing technologies, carbon-estimation models, spatial mapping approaches, machine-learning techniques, carbon-accounting frameworks, and their integration into carbon-credit assessment. It places particular emphasis on multisource data fusion, emerging Earth-observation technologies, artificial intelligence, uncertainty assessment, and digital MRV systems. Major methodological, technological, and policy gaps are identified, along with opportunities for developing transparent, spatially explicit, scientifically robust, and scalable carbon-credit assessment frameworks.

Light Pollution in Aquatic Ecosystems: Impacts of Artificial Light at Night (ALAN) on Aquatic Organisms

Fri, 25 Sep 2026 00:00:00 +0000

Artificial light at night (ALAN) is an increasingly widespread component of light pollution that alters natural light–dark conditions in aquatic environments. This review synthesises current knowledge on the sources and underwater propagation of ALAN, the factors influencing its effects, and reported biological and ecological responses across aquatic systems. Available evidence indicates that artificial illumination can modify biological rhythms, movement, feeding, predator–prey interactions, migration, reproduction, and habitat use in a range of aquatic and coastal organisms. Reported responses include changes in zooplankton diel vertical migration, altered activity and physiological performance in aquatic invertebrates and fishes, disruption of sea-turtle orientation and dispersal, effects on coral physiology and reproductive synchrony, and attraction or disorientation of seabirds. Because aquatic organisms are connected through food webs and exchanges between aquatic and terrestrial habitats, organism-level responses may extend to community composition, energy transfer, and ecosystem functioning. The ecological consequences of ALAN are influenced by light intensity, spectral composition, timing and duration of exposure, water optical properties, habitat characteristics, weather, season, and species-specific sensitivity. Although the evidence base is increasing, responses remain unevenly understood across taxa, habitats, and levels of biological organisation. Mitigation therefore requires careful control of light intensity, direction, spectrum, and timing, together with ecological monitoring and the integration of light-pollution considerations into freshwater, coastal, and marine conservation planning.

Natural Regeneration of Forest Ecosystems through Seed Dispersal and Pollination Mediated by Faunal Diversity: A Review

Ramkaran Yadav, Yamini Baghel, Shivam Singh, Gitanjali Bharti — Sat, 26 Sep 2026 00:00:00 +0000

Natural regeneration is increasingly central to forest restoration because it can rebuild vegetation without the costs and ecological simplification associated with universal tree planting. Its success, however, depends on more than the presence of remnant vegetation or favourable soils. Animal-mediated pollination and seed dispersal determine whether reproductive propagules are produced, moved across landscapes and delivered to sites where recruitment can proceed. This critical narrative review examines how faunal diversity influences these sequential stages of forest regeneration, with emphasis on tropical and subtropical forests where biotic mutualisms are especially prominent. Literature published from 1990 to 19 July 2026 was selected through searches of multidisciplinary, ecological and agricultural scholarly sources and evaluated for methodological quality, ecological realism and evidence-claim alignment. The synthesis shows that species richness alone is an incomplete predictor of regenerative function. Functional traits, interaction complementarity, movement behaviour, body size, dietary specialisation and spatial connectivity often determine whether pollination and dispersal remain effective after disturbance. Birds and bats can move propagules across open or degraded habitats, large-bodied frugivores disproportionately contribute to the dispersal of large-seeded and late-successional plants, and rodents can either destroy or secondarily disperse seeds depending on context. Pollination is similarly sensitive to the loss of mobile or specialised taxa, yet network-level apparent robustness may mask deterioration in pollen quality, gene flow or reproductive success. Defaunation, fragmentation and hunting can therefore generate regeneration debt even where canopy cover is recovering. Recent chronosequence and network studies further indicate that vegetation structure can recover faster than the interaction networks and functional seed rain required for mature-forest composition. Restoration should consequently treat faunal communities and landscape connectivity as components of regenerative infrastructure, while recognising that perches, nuclei and corridor interventions are conditional tools rather than universal solutions. The strongest inference is that natural regeneration is most resilient when multiple, functionally distinct animal partners connect reproductive stages across space; confidence is weaker where studies stop at visitation, seed removal or short-term seed rain rather than following recruitment.