Land use–land cover (LULC) alteration is primarily associated with land degradation, especially in recent decades, and has resulted in various harmful changes in the landscape. The normalized difference vegetation index (NDVI) has the prospective capacity to classify the vegetative characteristics of many ecological areas and has proven itself useful as a remote sensing (RS) tool in recording vegetative phenological aspects. Likewise, the normalized difference built-up index (NDBI) is used for quoting built-up areas. The current research objectives include identification of LULC, NDVI, and NDBI changes in Jhelum District, Punjab, Pakistan, during the last 30 years (1990–2020). This study targeted five major LULC classes: water channels, built-up area, barren land, forest, and cultivated land. Satellite imagery classification tools were used to identify LULC changes in Jhelum District, northern Punjab, Pakistan. The perception data about the environmental variations as conveyed by the 500 participants (mainly farmers) were also recorded and analyzed. The results depict that the majority of farmers (54%) believe in the appearance of more drastic changes such as less rainfall, drought, and decreased water availability for irrigation during 2020 compared to 30 years prior. Overall accuracy assessment of imagery classification was 83.2% and 88.8% for 1990, 88.1% and 85.7% for 2000, 86.5% and 86.7% for 2010, and 85.6% and 87.3% for 2020. The NDVI for Jhelum District was the highest in 1990 at +0.86 and the lowest in 2020 at +0.32; similarly, NDBI values were the highest in 2020 at +0.72 and the lowest in 1990 at −0.36. LULC change showed a clear association with temperature, NDBI, and NDVI in the study area. At the same time, variations in the land area of barren soil, vegetation, and built-up from 1990 to 2020 were quite prominent, possibly resulting in temperature increases, reduction in water for irrigation, and changing rainfall patterns. Farmers were found to be quite responsive to such climatic variations, diverting to framing possible mitigation approaches, but they need government assistance. The findings of this study, especially the causes and impacts of rapid LULC variations in the study area, need immediate attention from related government departments and policy makers.

Climbing plants have an important role in forest communities and ecosystems. Despite the significance of the climbers in ecosystems, most of the previous research work in Pakistan has been concentrated on trees, shrubs, and herbs, with little attention paid to climbing plants. The current study investigated the ecology of climbers and the influence of soil characteristics on diversity, richness, and indicator species distribution in the Changa Manga Forest Plantation, Punjab, Pakistan. Field surveys were carried out between 2020 and 2021, with the data gathered using a random sample approach for ordination and cluster analysis of each plant species and edaphic data from sample plots. We reported a total of 29 climber species belonging to 23 genera and 9 families from the area. The Convolvulaceae family was the most prevalent, followed by Apocynaceae and Cucurbitaceae. Herbaceous climbers were the typical life form (70% species) and species showed peak flowering during the months of August and September. The multivariate analysis and cluster analysis grouped the climbers into four distinct communities based on the indicator species, representing filtering of the species pool in the studied area. Canonical Correspondence Analysis (CCA) results showed that soil factors had a significant influence (p ≤ 0.002) on the climbers’ diversity and distribution pattern. Our research contributes to a deeper understanding of climbing plant ecology in response to soil variables, with immediate consequences for policy and practice in this Himalayan region, as well as research insights for neighboring Himalayan regions and elsewhere in the world.

The burgeoning human population exhibited a rapid amplification in demand for timber and fuelwood and as a result, the natural population of the native tree Tecomella undulata reduced rapidly due to its high economic and medicinal significance. The recognition of appropriate regions for threatened plants in the climate change scenario is a fundamental step for the restoration and conservation of biodiversity. The current study predicts the potentially suitable areas in Pakistan for T. undulata restoration. This research identifies the highly appropriate regions for vulnerable T. undulata through the maximum entropy model from MaxEnt software. The model’s Area Under Curve 0.968 suggested its accuracy. The mean temperature of the wettest quarter, precipitation of the warmest quarter, and mean temperature in the driest quarter significantly shaped the T. undulata distribution. Future suitable areas for T. undulata were made by using RCP (4.5 and 8.5) for the years 2050 and 2070 through 19 bioclimatic variables and 66 occurrence points. The current highly suitable area for T. undulata is approximately 135,749 km² (15.4%) while the unsuitable area identified is approximately 404,917 km² (45.91%). The highly suitable area for T. undulata increases by 3.6–7% under climate change regimes (RCP 4.5 and RCP 8.5). The Central Punjab (District Faisalabad, Nankana sahib, Jhang, Kasur, and Okara), Salt Range, Western Khayber Pakhtunkhwa (KPK), FATA area, Eastern Balochistan, and Thar and Tharparker in Sindh are the current appropriate habitats for T. undulata. Under all future climatic circumstances, the extremely appropriate area for T. undulata was anticipated to expand, whereas the unsuitable zones would all shrink. The research would be significant for the further development of T. undulata management and conservation techniques.