South Punjab experiences recurrent pre-monsoon droughts that place severe stress on its environment and pose a serious challenge to crop production. This study examines the spatial and temporal variability of drought across South Punjab from 2000 to 2025, characterizing the region's pre-monsoon drought dynamics using six MODIS-derived indicators: land surface temperature (LST), the Temperature Condition Index (TCI), the Vegetation Condition Index (VCI), the Vegetation Health Index (VHI), the Normalized Difference Vegetation Index (NDVI), and the Normalized Difference Water Index (NDWI). Image processing was performed on the Google Earth Engine platform, and the resulting time series were analyzed using box plots, standard deviations, and Mann-Kendall trend tests. The results reveal pronounced intra-regional heterogeneity, with frequent outliers across districts. Mean VHI was lowest in 2005, recovered through 2010-2015, declined again in 2020, and reached its highest value in 2025, while LST was lowest and vegetation health greatest in 2025. NDWI nonetheless indicated severe surface-moisture deficits in both 2020 and 2025, exposing a disconnect between vegetation greenness and underlying water availability that points to the region's growing reliance on artificial irrigation to sustain pre-monsoon cropping amid escalating hydrological deficits. These findings suggest that, even as remote sensing and GIS provide an increasingly capable toolkit for drought monitoring, intensifying anthropogenic pressures mean that agro-meteorological crises in South Punjab are becoming socio-natural rather than purely geophysical hazards.
Climate change is increasing the vulnerability of cities, and it is therefore important to evaluate vegetation comprehensively for sustainability and resilience. This research utilizes advanced machine learning and remote sensing methods to examine urban vegetation dynamics in Karachi. Utilizing Google Earth Engine (GEE) for large-scale geospatial analysis, mean monthly NDVI values were obtained from Landsat 8 data from the years 2013 to 2022. Seasonal ARIMA (SARIMA) models were utilized to detect trends and seasonal variations in the NDVI time series. The results were utilized to forecast future NDVI trends, which were subsequently incorporated into conservation and urban planning initiatives following the model's verification of accuracy. The SARIMA (0,1,2)x(0,1,2,12) model was the most appropriate for the description of trend and seasonal behavior. The model provided the best overall fit among the tested configurations. Model diagnostics indicated a strong performance, with good values across standard statistical criteria such as log likelihood, AIC, BIC, and HQIC. Residual analysis further confirmed that the model adequately captured the underlying patterns. Predictions indicated a mean NDVI value of 0.196, with a 95% confidence interval of 0.146 to 0.246. Strong fluctuations in NDVI values over time included the highest values in September 2023 (0.232) and October 2024 (0.253), with lower values in the summer months, indicating clear seasonal fluctuations. This interdisciplinary effort offers a holistic assessment of urban vegetation dynamics with global applicability. By focusing on the importance of green spaces in the mitigation of urban heat island and climate adaptation, the research calls for their incorporation in urban planning. The findings provide practical recommendations toward sustainable development, urban planning, and environmental protection, demonstrating the capacity of sophisticated modeling methods to inform resilient urban ecosystems.
This study examines how livelihood pressures, environmental variability, and changes in land use/land cover (LULC) affect ecosystem dynamics and biodiversity in Lal Sohanra National Park (LSNP) in Pakistan. Remote sensing (RS) and geographic information system (GIS) methods were used to process multi-temporal Landsat images spanning from 1990 to 2023. The normalized difference vegetation index (NDVI), the normalized difference water index (NDWI), and the bare soil index (BSI) were used to assess the dynamics of vegetation, water, and bare soil, respectively. The photos covered a wide range of years, from 1990 to 2023. Local reliance on park resources was assessed using household survey data from 100 respondents. At the same time, climatic variability was examined using the Mann-Kendall trend test, Sen's slope estimator, and Pettitt's change-point analysis. Over the course of the research period, the results reveal significant changes in land cover. Barren land and shrubland varied widely, alternating between stages of degradation and vegetation regeneration, whereas forest cover declined at times but recovered partially in later years. While BSI indicates that soil remains exposed in critical zones, NDVI shows that vegetation is improving in some areas. Despite non-significant or fluctuating trends in precipitation and temperature, climate research reveals a notable rise in soil moisture and a notable fall in wind speed. In the late 90s and early 2000s, when land use changed and environmental stress was at its worst, change-point analysis primarily found structural shifts. According to socioeconomic data, local communities rely heavily on park resources, including fuelwood, grazing, and livelihood assistance, which strains habitat quality and vegetation. The study found that land-cover change, climate variability, and human resource use all play a role in shaping ecosystem dynamics in the Lal Sohanra Biosphere Reserve. To manage biodiversity sustainably, it is advised to implement integrated conservation planning, regulate resource use, and provide community-based livelihood options.
The Sehb El Masjoune basin, located in the Oum Er-Rbia watershed (Morocco), is classified as both a Site of Biological and Ecological Interest (SBEI) and a Key Biodiversity Area (KBA). This study presents a phytoecological assessment based on 18 vegetation surveys conducted before and during the site's flooding (November 2020 – June 2021). A total of 70 vascular plant species, representing 29 families, were recorded. Annual therophytes dominate the flora (68%), indicating arid environmental conditions and strong anthropogenic pressures, particularly overgrazing. The chorological analysis of the recorded taxa showed that most of the recorded species belonged to mediterranean (72.8%). The presence of seven endemic and two threatened species highlights the site’s ecological value. The analysis of the principal component analysis (PCA) revealed the differentiation of five major plant associations, each reflecting distinct ecological conditions related to substrate type and salinity. The results demonstrate the ecological significance of the basin and emphasize the urgent need for a dedicated conservation and management plan. This study provides a baseline for future biodiversity monitoring and sustainable management efforts in this nationally and internationally important site.
Microplastics are of environmental concern because they are ubiquitous, persistent, and readily ingested by aquatic organisms. This study investigated the occurrence and characteristics of microplastics in the water column and in stomachs of juvenile European perch (Perca fluviatilis) in the Włocławek Reservoir, a large dam reservoir in Central Europe. Samples were collected in June 2024 from the nearshore zone in the central part of the reservoir. Water samples were filtered through 11 µm filters, and the retained material was digested with 30% hydrogen peroxide to remove organic matter. The samples were then re-filtered and examined under a stereomicroscope. Fish digestive tracts were dissected and analysed stereomicroscopically. For each identified microplastic particle, shape (fibres, ovals, flakes), colour, number, and size range were recorded. Ivlev's electivity index was used to assess selective ingestion of microplastics by fish. Microplastics were detected in reservoir water (188.7 particles per litre), in 25% (13 of 52) of the examined perch, and in the procedural blank (distilled water processed in the same way as reservoir water), where 24 particles per litre were found. Among fish containing microplastics, the mean number of particles per stomach was 2.08. Fibres dominated in the water column and were mostly blue, whereas only fibres were found in biological samples, where red fibres predominated. The results indicate a substantial microplastic contamination of the Włocławek Reservoir and demonstrate the presence of microplastics in the fish. However, the observed selectivity of microplastic uptake by fish from the water column remains unclear. The predominance of red fibres in stomach contents may indicate selective ingestion and/or differential retention of fibres in the digestive tract.
