Agriculture is greatly impacted by climate change, which can lead to situations of food security or insecurity at both regional and global levels. Pakistan is predicted to experience an area reduction and geographical shifting of major crops in the near future. In the present study, we assessed the potential future distribution of wheat and maize in Pakistan. Based on current locations of these crops, we ran a Maxent species distribution model to predict future changes in crop distributions. We used 58 presence records for wheat and 48 presence records for maize. The model simulated current and future climate change scenarios (RCP 4.5 and RCP 8.5) based on the CMIP5 model, MPI-ESM-LR. Results from our model showed a decline in production area, with a 30-35% reduction in wheat and a 23-36% reduction in maize in the year 2070, depending upon which climate change scenario was modelled (i.e. RCP 4.5 or RCP 8.5). The model predictions were highly accurate, with test AUC values of 0.88 for wheat and 0.89 for maize. A jackknife test for variable importance indicated that irrigation, precipitation seasonality and precipitation of the warmest quarter are the most important environmental variables determining the potential geographic distribution of the crops. Due to the varying severity and nature of climate impacts, adaptation strategies are needed. This study can aid policy makers in devising policies that can help reduce the threat of future food insecurity in the region.

The impacts of climate change are projected to become more intense and frequent. One of the indirect impacts of climate change is food insecurity. Agriculture in Pakistan, measured fourth best in the world, is already experiencing visible adverse impacts of climate change. Among many other food sources, potato crop remains one of the food security crops for developing nations. Potatoes are widely cultivated in Pakistan. To assess the impact of climate change on potato crop in Pakistan, it is imperative to analyze its distribution under future climate change scenarios using Species Distribution Models (SDMs). Maximum Entropy Model is used in this study to predict the spatial distribution of Potato in 2070 using two CMIP5 models for two climate change scenarios (RCP 4.5 and RCP 8.5). 19 Bioclimatic variables are incorporated along with other contributing variables like soil type, elevation and irrigation. The results indicate slight decrease in the suitable area for potato growth in RCP 4.5 and drastic decrease in suitable area in RCP 8.5 for both models. The performance evaluation of the model is based on AUC. AUC value of 0.85 suggests the fitness of the model and thus, it is applicable to predict the suitable climate for potato production in Pakistan. Sustainable potato cultivation is needed to increase productivity in developing countries while promoting better resource management and optimization.

Increasing atmospheric carbon dioxide concentration [CO₂] caused by anthropogenic activities has triggered a requirement to predict the future impact of [CO₂] on forests. The Hindu Kush Himalayan (HKH) region comprises a vast territory including forests, grasslands, farmlands and wetland ecosystems. In this study, the impacts of climate change and land-use change on forest carbon fluxes and vegetation productivity are assessed for HKH using the Lund–Potsdam–Jena General Ecosystem Simulator (LPJ-GUESS). LPJ-GUESS simulations were driven by an ensemble of three climate models participating in the CMIP5 (Coupled Model Intercomparison Project phase 5) database. The modelled estimates of vegetation carbon (VegC) and terrestrial primary productivity were compared with observation-based estimates. Furthermore, we also explored the net biome productivity (NBP) and its components over HKH for the period 1851–2100 under the future climate scenarios RCP2.6 and RCP8.5. A reduced modelled NBP (reduced C sink) is observed from 1986–2015 primarily due to land-use change. However, an increase in NBP is predicted under RCP2.6 and RCP8.5. The findings of the study have important implications for the management of the HKH region, in addition to informing strategic decision making and land-use planning, and clarifying policy concerns.

Urea is a crucial nutrient for plant growth, but because of its substantial losses due to nitrification, ammonification, and subsurface leaching, there is currently a push to reduce these losses. Urea is frequently uploaded and trapped in gelatin. In this research, the improvement of urea uploading and encapsulation efficiency is investigated using wood ash made from plant biomass (Pinus roxburghii). The 8 g w/v of gelatin was mixed with various concentrations of wood ash (from 4 to 16 g w/w), urea (from 4 to 24 g w/w), and glutaraldehyde (from 0.5 to 3 mL g⁻¹) to prepare various formulations of slow-release fertilizer (SRF). According to this study, adding wood ash to gelatin increases its ability to upload and encapsulate urea. The urea on its surface and the metal in wood ash both considerably contribute to the compositional alterations in gelatin in SRFs, which were demonstrated by IR spectroscopy. Visualization from photographs revealed that the homogenous dispersion of wood ash improved structural compatibility. The water content of the SRF formulation showed that wood ash can reduce water absorption by changing how hydrophobic gelatin is. Wood ash improves the gelatin’s ability to reduce the rapid release of urea over time, according to testing of cumulative urea release from SRF. The optimal combinations for achieving the maximum 53.43% of urea uploading were 2.44 g of urea, 2.47 mL of glutaraldehyde, and 1.50 g of wood ash, according to the Box–Behnken model. The gelatin-based SRF that had been amended with wood ash was applied to the Mentha spicata plant, and the plant’s healthy development and higher chlorophyll content revealed its agronomic potential. This study has a significant contribution to the development of an affordable and more effective wood ash-modified gelatin-based SRF.

The rise of methicillin-resistant Staphylococcus epidermidis (MRSE) makes it difficult to treat infections that increase morbidity and mortality rates in various parts of the world. The study’s objectives include identifying the clinical prevalence, antibiogram profile, and Gompertz growth kinetics of MRSE treated with synthetically created nanoparticles of rosin obtained from Pinus roxburghii. A total of 64 of 200 clinical isolates of S. epidermidis (32% of the total) displayed sensitivity (40.62%) and resistance (59.37%) to seven different antibiotic classes. The most sensitive patterns of antibiotic resistance were seen in 20 (78.95%) and 24 (94.74%) isolates of MRSE against piperacillin/tazobactam and cephradine, respectively. Fosfomycine was found to be the most effective antibiotic against MRSE in 34 (89.47%) isolates, followed by amoxicillin. Successfully produced, described, and used against MRSE were rosin maleic anhydride nanoparticles with a size range of 250 nm to 350 nm. Five different concentrations of 25, 50, 75, 100, and 150 mg mL⁻¹ rosin maleic anhydride nanoparticles were investigated to treat MRSE resistance. According to Gompertz growth kinetics, the maximal growth response was 32.54% higher and the lag phase was also 10.26% longer compared to the control when the amount of rosin maleic anhydride nanoparticles was increased in the MRSE. Following the application of rosin maleic anhydride nanoparticles, the growth period is extended from 6 to 8 h. A potential mechanism for cell disintegration and distortion is put forth. This investigation came to the conclusion that rosin maleic anhydride nanoparticles better interfere with the surface of MRSE and demonstrated a preferred bacteriostatic action.