The unchecked and unplanned expansion of urban areas has led to the conversion of millions of green areas to gray areas. The recent urban growth patterns of Pakistan’s metropolitan twin cities, Islamabad and Rawalpindi, is a matter of concern for the surrounding green areas. The present study aimed to categorize and quantify the land-use and land-cover change (LULCC) patterns and the corresponding impacts on the forest carbon dynamics around Islamabad and Rawalpindi. Multispectral satellite images for the year 1990 (Landsat 5 TM) and 2020 (Landsat 8 OLI) were used to determine, quantify, and compare the LULCC inside and around the twin metropolitan cities. Field inventory surveys in the reserved forests of Rawalpindi and Islamabad were also conducted to determine the amount of stored carbon in these forests. Our results showed an accelerated annual urban expansion (i.e., an increase in the built-up area) of 16.49% and 26.72% in Rawalpindi and Islamabad, respectively, during the study period. Similarly, the amount of barren land and agricultural land was reduced at an annual rate of 2.08% and 2.18%, respectively, in Rawalpindi and 0.25% and 1.04% in Islamabad. A reduction in the area of barren mountains also occurred at an annual of 2.26% in Islamabad, while it increased by 4.16% in Rawalpindi. The amount of carbon stored in the reserved forests of Islamabad stood at 139.17 ± 12.15 Mg C/ha while that of Rawalpindi was 110.4 ± 13.79 Mg C/ha. In addition, total stored forest carbon was found to have decreased from 544.70 Gg C to 218.05 Gg C in Rawalpindi, while in Islamabad it increased from 2779.64 Gg C to 3548.16 Gg C. Investment in ecological urban planning, sustainable cities, and appropriate land-use planning is recommended to curb the degradation and conversion of the surrounding green areas of Rawalpindi and Islamabad.

The sub-tropical broadleaved forests in Pakistan are the main constituents of the ecosystem services playing a vital role in the global carbon cycle. Monotheca buxifolia (Falc.) A. DC. is an important constituent of these forests, encompassing a variety of ecological and commercial uses. To our best knowledge, no quantitative studies have been conducted in these forests across the landscape to establish a baseline for future monitoring. We investigated the forest structural attributes, growing stock characteristics and total biomass carbon stock and established relationships among them in the phytocoenosis of Monotheca forests along an altitudinal gradient in Pakistan to expand an eco-systemic model for assessment of the originally-implemented conservation strategies. A floristic survey recorded 4986 individuals of 27 species in overstory and 59 species in the understory stratum. Species richness (ANOVA; F = 3.239; p = 0.045) and Simpson’s diversity (ANOVA; F = 2.802; p = 0.043) differed significantly in three altitudinal zones, with a maximum value for lower elevations, followed by middle and higher elevations. Based on the importance values, Acacia modesta and Olea ferruginea are strong companions of M. buxifolia at lower and higher altitudes, whereas forests at mid elevation represent pure crop of M. buxifolia (IVI = ≥85.85%). A similar pattern in stem density, volume and Basal area were also recorded. The carbon stock in trees stratum (51.81 T ha⁻¹) and understory vegetation (0.148 T ha⁻¹) contributes high values in the lower elevation forests. In contrast, soil carbon had maximum values at higher elevation (36.21 T ha⁻¹) and minimum at lower elevation (16.69 T ha⁻¹) zones. Aboveground biomass carbon stock (AGB BMC) of woody trees, understory vegetation and soil organic carbon (SOC) were estimated higher (77.72 T ha⁻¹) at higher and lower (68.65 T ha⁻¹) elevations. Likewise, the AGB BMC exhibited a significant (p < 0.05) negative correlation with elevation and positive correlation with soil carbon. We concluded that lower elevation forests are more diverse and floristically rich in comparison to higher altitudinal forests. Similarly, the biomass carbon of Monotheca forests were recorded maximum at low altitudes followed by high and middle ranges, respectively.

Liupan Mountains are an important region in China in the context of forest cover and vegetation due to huge afforestation and plantation practices, which brought changes in soil physio-chemical properties, soil stocks, and soil stoichiometries are rarely been understood. The study aims to explore the distribution of soil nutrients at 1-m soil depth in the plantation forest region. The soil samples at five depth increments (0-20, 20-40, 40-60, 60-80, and 80-100 cm) were collected and analyzed for different soil physio-chemical characteristics. The results showed a significant variation in soil bulk density (BD), soil porosity, pH, cation exchange capacity (CEC), and electric conductivity (EC) values. More soil BD (1.41 g cm^-3) and pH (6.97) were noticed in the deep soil layer (80-100 cm), while the highest values of porosity (60.6%), EC (0.09 mS cm^-1), and CEC (32.9 c mol kg^-1) were reflected in the uppermost soil layer (0-20 cm). Similarly, the highest contents of soil organic carbon (SOC), total phosphorus (TP), available phosphorus (AP), total nitrogen (TN), and available potassium (AK) were calculated in the surface soil layer (0-20 cm). With increasing soil depth increment a decreasing trend in the SOC and other nutrient concentration were found, whereas the soil total potassium (TK) produced a negative correlation with soil layer depth. The entire results produced the distribution of SOCs and TNs (stocks) at various soil depths in forestland patterns were 0→20cm > 20→40cm > 40→60cm ≥ 60→80cm ≥ 80→100 cm. Furthermore, the stoichiometric ratios of C, N, and P, the C/P, and N/P ratios showed maximum values (66.49 and 5.46) in 0-20 cm and lowest values (23.78 and 1.91) in 80-100 cm soil layer depth. Though the C/N ratio was statistically similar across the whole soil profile (0-100 cm). These results highlighted that the soil depth increments might largely be attributed to fluctuations in soil physio-chemical properties, soil stocks, and soil stoichiometries. Further study is needed to draw more conclusions on nutrient dynamics, soil stocks, and soil stoichiometry in these forests.

Rapid urbanization attributed to population growth is affecting the built environment's thermal and landscape dynamics. Using Landsat satellite datasets, this study investigated the complex interplay between urban Land Cover (LC) modification, fluctuation in Land Surface Temperature (LST) and severity of Urban Heat Island (UHI) from 1990 to 2020 in Peshawar City, Pakistan. Thermal bands were used to calculate LST and severity of UHI using the Urban Thermal Field Variance Index (UTFVI). Furthermore, through Cellular Automata (CA), Logistic Regression (LR), and Artificial Neural Network (ANN), future predictions on thermal characteristics associated with land use changes were made. The results showed that the urban areas expanded by ∼25 % from 1990 to 2020, while a ∼10 % decrease occurred in urban vegetation. The city is projected to expand by ∼45 % and ∼56 % in 2035 and 2050, respectively. Notably, the results also demonstrated that urban hotspots were found the warmest with the strongest UHI severity (∼34 °C), followed by the barren land (∼32 °C), and vegetation. The results further predicted an increase of LST (∼55 % and ∼82 %) and UTFVI (∼62 % and ∼83 %) in 2035 and 2050, respectively. These findings provide useful insights for policymakers and city planners to mitigate heat stress and create a sustainable urban environment through the development of effective urban land use policies and urban greening.

The utilization of remote sensing (RS) techniques plays a crucial role in the efficient planning and monitoring of afforestation projects within constrained timeframes. This study evaluates the progress of the Billion Trees Afforestation Project (BTAP) in Dera Ismail Khan (DIK), Khyber Pakhtunkhwa, Pakistan, using RS technology. Geographical positioning systems were employed to delineate the boundaries of the plantation areas, and two temporal Sentinel-2 images from 2016 (the commencement of the plantation) and 2018 were analyzed to calculate the normalized difference vegetation index (NDVI). The results revealed that the survival rate of plantations varied between 37.39% and 85.15%, while the area of unstocked regions ranged from 14.84% to 62.60%. Overall, in 2016, the survival rate was determined to be 61.28%, with 38.72% of the area remaining unstocked. The NDVI values in 2016 ranged from -1 to -0.43, whereas in 2018, they spanned from -0.43 to 0.80, indicating significant progress in plantation growth and a substantial reduction in unstocked areas. The RS-based assessment proved to be highly effective, suggesting its adoption for the rapid detection and evaluation of plantation efforts. It is recommended to use high-resolution satellite images and drone technology to enhance accuracy further. Additionally, measures such as the establishment of closures, pit sowing, appropriate site and species selection, and effective soil and water conservation techniques are essential to maximizing the survival rate of plantations.