Search

The practice of using plants in traditional remedies, drawing from age-old knowledge to treat various illnesses, falls under the scope of ethnobotany. The current research aimed to report traditional medicinal herbs that locals used to treat various diseases in Ahmedpur East, Pakistan. GPS data was used to capture the whole survey area. All plant specimens were preserved in the herbarium. The collected data was in demographic form. The native names of the plants, their purposes, parts used and techniques for preparing medicines as well as other pertinent information were gathered. The current study involved interviewing 300 informants (25 females, 275 males). The study identified wild medicinal plants from 15 families with Amaranthaceae and Brassicaceae being the most prevalent. The study revealed that leaves were the primary plant part used medicinally, accounting for 65% of remedies. Informant Consensus Factor (ICF) scores ranged from 0.52 to 0.96, while Fidelity Level (FL) was observed between 66% to 96%, indicating the community's agreement on the plants' medicinal efficacy. Notably, species like Aerva javanica, Melilotus indicus, and Cannabis sativa achieved the highest Use Value (UV) of 0.93. Comparative analysis using the Jaccard Index showed varying plant use patterns across different regions, emphasizing the unique ethnobotanical landscape of each area. The findings highlight local populations' rich traditional plant knowledge, suggesting potential avenues for phytotherapeutic chemical discovery and new treatments. [ABSTRACT FROM AUTHOR]

Groundwater contamination poses a severe public health risk in Lahore, Pakistan's second-largest city, where over-exploited aquifers are the primary municipal and domestic water supply source. This study presents the first comprehensive district-wide assessment of groundwater quality across Lahore using an innovative integrated approach combining geographic information systems (GIS), multi-criteria decision analysis (MCDA), and water quality indexing techniques. The core objectives were to map the spatial distributions of critical pollutants like arsenic, model their impacts on overall potability, and evaluate targeted remediation scenarios. The analytic hierarchy process (AHP) methodology was applied to derive weights for the relative importance of diverse water quality parameters based on expert judgments. Arsenic received the highest priority weight (0.28), followed by total dissolved solids (0.22) and hardness (0.15), reflecting their significance as health hazards. Weighted overlay analysis in GIS delineated localized quality hotspots, unveiling severely degraded areas with very poor index values (>150) in urban industrial zones like Lahore Cantt, Model Town, and parts of Lahore City. This corroborates reports of unregulated industrial effluent discharges contributing to aquifer pollution. Prospective improvement scenarios projected that reducing heavy metals like arsenic by 30% could enhance quality indices by up to 20.71% in critically degraded localities like Shalimar. Simulating advanced multi-barrier water treatment processes showcased an over 95% potential reduction in arsenic levels, indicating the requirement for deploying advanced oxidation and filtration infrastructure aligned with local contaminant profiles. The integrated decision support tool enables the visualization of complex contamination patterns, evaluation of remediation options, and prioritizing risk-mitigation investments based on the spatial distribution of hazard exposures. This framework equips urban planners and utilities with critical insights for developing targeted groundwater quality restoration policies through strategic interventions encompassing treatment facilities, drainage infrastructure improvements, and pollutant discharge regulations. Its replicability across other regions allows for tackling widespread groundwater contamination challenges through robust data synthesis and quantitative scenario modeling capabilities. [ABSTRACT FROM AUTHOR]

Salinity stress represents a major threat to crop production by inhibiting seed germination, growth of seedlings, and final yield and, therefore, to the social and economic prosperity of developing countries. Recently, plant growth‐promoting substances have been widely used as a chemical strategy for improving plant resilience towards abiotic stresses. This study aimed to determine whether melatonin (MT) and glycine betaine (GB) alone or in combination could alleviate the salinity‐induced impacts on seed germination and growth of maize seedlings. Increasing NaCl concentration from 100 to 200 mM declined seed germination rate (4.6–37.7%), germination potential (24.5–46.7%), radical length (7.7–40.0%), plumule length (2.2–35.6%), seedling fresh (1.7–41.3%) and dry weight (23.0–56.1%) compared to control (CN) plants. However, MT and GB treatments lessened the adverse effects of 100 and 150 mM NaCl and enhanced germination comparable to control plants. In addition, results from the pot experiments show that 200 mM NaCl stress disrupted the osmotic balance and persuaded oxidative stress, presented by higher electrolyte leakage, hydrogen peroxide, superoxide radicals, and malondialdehyde compared to control plants. However, compared to the NaCl treatment, NaCl+MT+GB treatment decreased the accumulation of malondialdehyde (24.2–42.1%), hydrogen peroxide (36.2–44.0%), and superoxide radicals (20.1–50.9%) by up‐regulating the activity of superoxide dismutase (28.4–51.2%), catalase (82.2–111.5%), ascorbate peroxidase (40.3–59.2%), and peroxidase (62.2–117.9%), and by enhancing osmolytes accumulation, thereby reducing NaCl‐induced oxidative damages. Based on these findings, the application of MT+GB is an efficient chemical strategy for improving seed germination and growth of seedlings by improving the physiological and biochemical attributes of maize under 200 mM NaCl stress. [ABSTRACT FROM AUTHOR]

The Atlas pistachio tree is a typically Mediterranean species, which represents an important forest heritage in the arid and semi-arid regions of Algeria. It is deeply rooted in the local population's culture, making it essential to better understand this species for its conservation and valorization. Through our work on 7 provenances of Pistacia atlantica distributed across different bioclimates in Algeria and based on 28 quantitative and qualitative leaf, trichome, and stomatal traits, it was revealed that the Atlas pistachio tree exhibits significant ecotypic variability linked to its habitat and a high adaptability to extreme conditions in its environments (aridity and altitude). Indeed, statistical analyses indicate a substantial heterogeneity in the studied characteristics among different ecotypes of P. atlantica. Genetic factors undoubtedly play a primary role in this variability, but environmental factors also exert a remarkable impact on this heterogeneity. Gender also plays a crucial role in this variability. Microphotographs of leaf samples taken under scanning electron microscopy (SEM), such as the density and type of trichomes, and form and position of stomates in the epidermis, can provide an important taxonomic tool for identifying Pistacia species and valuable insights into their adaptation to xeric conditions, thus enabling their use in desertification control projects and the rehabilitation of highly degraded forest environments such as those found in the "Green Dam" initiative. [ABSTRACT FROM AUTHOR]

This research used the Revised Universal Soil Loss Equation (RUSLE) with Sediment Delivery Ratio (SDR) model. The analytic hierarchy process (AHP) method, while also incorporating the use of a geographic information system (GIS) and remote sensing (RS) to predict the annual soil loss rate and spatialise the processes of water erosion at the scale of the Loukkos Watershed, Morocco. The RUSLE model and AHP parameters were estimated using RS data, and the erosion vulnerability zones were determined using GIS. We used five parameters, including precipitation erosivity, soil erodibility, slope length and steepness, vegetation cover, and soil erosion control practices in the RUSLE. For the AHP technique, we used seven geo‐environmental factors, including annual average precipitation, drainage density, lineament density, slope, soil texture, land use/land cover and landform maps. The results of RUSLE indicated that the average annual soil loss varied from 0 to 2388.27 t·ha−1·year−1. The total estimated annual potential soil loss was approximately 40 790 220.11 t·ha−1·year−1, and a sediment yield estimated by RUSLE‐SDR was 8 647 526.66 t·ha−1·year−1, equivalent to 6.65 Mm3. This value is very close to the measured value of 6.81 Mm3, for a difference of 0.16 Mm3. Furthermore, the results of the AHP indicate that the soil erosion potential index varies from 0 to 0.205315 t·ha−1·year−1. Overall, nearly 13.7% of the area suffered from severe soil erosion exceeding 50 t·ha−1·year−1. Approximately 80% of the Loukkos Watershed area experienced only slight erosion, while the remaining 6% incurred moderate erosion. Integrating GIS and RS into the RUSLE model and AHP helped us robustly estimate the extent and degree of erosion risk. Territorial decision‐makers should adopt our results to develop soil conservation strategies, water management plans and other necessary soil and water conservation measures for this region. [ABSTRACT FROM AUTHOR]

Anthropogenic activities like overgrazing, deforestation and mismanaged land use accelerate soil erosion (SE), causing nutritional and organic matter loss. In this study, we predicted the annual rate of soil loss in the Salt Range, extending south from the Pothohar plateau, Pakistan, using the Revised Universal Soil Loss Equation (RUSLE). The RUSLE model parameters and erosion probability zones were estimated using remote sensing and Geo‐Spatial methods. The annual average soil loss rates were calculated by considering five geo‐environmental factors, that is, slope length and steepness (LS), rainfall erosivity (R), cover management (C), soil erodibility (K), and conservation practice (P) range from 0–559 527, 1404–4431, 0–1, −0.14 to 1.64, and 0.2–122 t.ha−1.year−1$$ \left(t.{ha}^{-1}.{year}^{-1}\right) $$ respectively. This research determined that the yearly average rate of SE in the Salt Range varies from over 50 to above 350 t.ha−1.year−1$$ \mathrm{t}.{\mathrm{ha}}^{-1}.{\mathrm{year}}^{-1} $$. The distribution of land area across different SE probability zones reveals that a small portion (2.11%) is classified as High, a moderate portion (7.13%) falls under the category of Moderate, while the majority (90.7%) is classified as Low in terms of proneness towards erosion. The land devoid of vegetation and characterized by steep slopes is especially prone to SE. The Salt Range is highly vulnerable to SE risk due to climatic variations and improper land use practices. The result provides a spatial distribution of SE across the salt range, utilized for management planning processes and conservation at the policy level among decision‐makers and land‐use planners. [ABSTRACT FROM AUTHOR]

Multi-temporal unmanned aerial vehicle (UAV) imagery and topographic data were used to characterize and evaluate the geomorphic changes of two active landslides (Nara and Nokot) in Pakistan. Ortho-mosaic images and field-based investigations were utilized to assess the geomorphological changes, including the Topographic Wetness Index, slope, and displacement. Volumetric changes in specific areas of the landslides were measured using the Geomorphic Change Detection (GCD) tool. The depletion zone of the Nara landslide was characterized by failures of the main scarps, resulting in landslides causing erosional displacements exceeding 201.6 m. In contrast, for the Nokot landslide, the erosional displacement ranged from −201.05 m to −64.98 m. The transition zone of the slide experienced many slow earth flows that re-mobilized displaced material from the middle portion of the landslide, ultimately reaching the accumulation zone. Volumetric analysis of the Nara landslide indicated overall erosion of landslide material with a volume of approximately 4,565,274.96 m3, while the accumulated and surface-raising material volume was approximately 185,544.53 m3. Similarly, for the Nokot landslide, the overall erosion of landslide material was estimated to be 6,486,121.30 m3, with an accumulated volume and surface-raising material of 117.98 m3. This study has demonstrated the efficacy of the GCD tool as a robust and repeatable method for mapping and monitoring landslide dynamics with UAVs over a relatively long time series. [ABSTRACT FROM AUTHOR]