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A comprehensive study was conducted to investigate the factors contributing to the proliferation of dengue in the Faisalabad district of Pakistan. The research focused on analyzing demographic parameters through an examination of dengue hotspot areas and assessing the impact of climatic factors on the spread of dengue infection. To establish the relationship between dengue infection and climatic factors, various data extraction approaches, statistical analyses, and GIS mapping techniques were employed. The study covered the epidemic period from 2013 to 2019. Pearson correlation coefficients for temperature, relative humidity, and precipitation were calculated to understand the correlation between climatic factors and dengue cases. The analysis revealed that the highest number of dengue cases occurred in Tehsil Faisalabad city during the post-monsoon season, specifically from September to November, with the peak in October reaching 63 cases. This finding indicated a direct correlation between dengue-infected cases and population density. The correlation coefficients between dengue-infected cases and climatic factors (temperature, rainfall, and relative humidity) in district Faisalabad from 2014 to 2019 were 0.58, -0.421, and -0.364, respectively. These values demonstrated a 58% positive correlation between dengue cases and temperature, a negative 43% correlation between rainfall and dengue cases, and a 36% negative correlation between relative humidity and the number of dengue cases. The relationship between climatic variables and dengue cases was found to be complex. While an increase in temperature was associated with higher dengue transmission, the other two variables (rainfall and relative humidity) showed a decrease in dengue transmission potential. This complexity explains the inconsistent statistical correlation between climate and dengue. This research provides valuable insights and future projections for analyzing the climatic influence and conducting epidemiological analyses of dengue infection in the region. [ABSTRACT FROM AUTHOR]

Shisham (Dalbergia sissoo) dieback disease has been a subject of great economic importance for the last few decades in South Asian countries. This disease prevails across the shisham growing geographical regions in these countries. Shisham dieback disease has been highlighted as a national forest problem in Pakistan. In this investigation, major shisham plantations of Pakistan were targeted for disease surveillance and monitoring. The extent of shisham dieback disease at different age classes of shisham plantations was also quantified. Surveillance data revealed, that shisham dieback disease is present in all surveyed shisham growing areas, including in areas where mild to no shisham dieback had been reported previously. A significant correlation was observed between different environmental variables (temperature (T), rain fall (RF), and relative humidity (RH) and disease development at (P < 0.01). T has negative correlation with RF (r= -0.793) and RH (r= -0.867). Infection prevails in different ecological zones depicted that environment has a minor role in disease development. Shisham dieback disease symptoms gain a seasonal peak from mid-February to end-March and mid-August to mid-October. Plants belonging to different age classes were exhibited different levels of disease incidence (20.95-28-2%). These findings will guide policy making and breeding programs with the goal of successful management of the shisham dieback disease and sustainable production of shisham in Pakistan. [ABSTRACT FROM AUTHOR]

Understanding the intricate relationship between climate variables and the Normalized Difference Vegetation Index (NDVI) is essential for effective ecosystem management. This study focuses on the spatiotemporal dynamics of NDVI and its interaction with climate variables in the ecologically diverse Khyber Pakhtunkhwa (KPK) Province, Pakistan, from 2000 to 2022. The research methodology involves analyzing satellite images and meteorological datasets to examine NDVI and surface latent heat flux (SHF), total precipitation (TPP), temperature (T), soil temperature (ST), and total pressure (TP). KPK Province's ecological significance and complex climate-vegetation interactions drive the selection of this study area. The study uses multiple linear regression analysis to investigate how T, TPP, SHF, and TP influence NDVI. The Mann-Kendall test detects trends, with Sen's slope estimator quantifying trend magnitudes. Additionally, correlation coefficients provide insights into long-term changes and association strengths. The findings highlight a consistent upward trend in mean NDVI over the 23 years, revealing an overall increase in NDVI, particularly in vegetation-dense areas where it rose from 0.27 to 0.32. The research showed an annual growth rate of 0.84% in the entire area, with specific vegetated zones exhibiting a slightly lower rate of 0.80%. However, the average yearly increase in NDVI is higher in vegetation-specific zones (0.00237) compared to the whole area (0.00151). This increase in NDVI occurs alongside a statistically significant decrease in SHF and PPT, suggesting a complex adaptation of vegetation to changing climate conditions in the KPK Province. In contrast, SHF exhibits a statistically significant negative slope of −5.952e-06 (p < 0.05), indicating a pronounced downward trend. Similarly, Sen's slope estimate for precipitation demonstrates a significant negative trend of −0.0001 (p < 0.05), showing diminishing precipitation. The study uncovers intricate linkages between climate variables and vegetation dynamics within KPK Province. These insights have far-reaching implications, guiding decision-making in land management, conservation efforts, and global climate resilience strategies. Ultimately, the research underscores the critical role of data-driven approaches in shaping a greener and more sustainable future. • Upward NDVI trend shows dense area growth over 23 years. • Zones show 0.80% annual growth, revealing nuanced vegetation dynamics in Province. • Clear SHF decrease & diminishing precipitation show complex vegetation adaptation. • Complex climate-NDVI dynamics revealed, highlighting changing conditions' impact. • Data insights guide global land, conservation, and climate strategies. [ABSTRACT FROM AUTHOR]

Dieback of forest trees is considered as serious problem in most parts of the world. Shisham an important multipurpose tree of the Indian subcontinent is suffering from dieback. Changing climate in most parts of the world is considered an important factor of ecosystem disturbance. Impact of environmental variables, tree age and water table on the dieback of shisham was examined in different regions of Punjab, Pakistan. Significant correlation was observed between environmental variables and dieback in minimum, moderate and maximum infected trees among three age classes. Water table and rainfall expressed non- significant correlation. A multiple regression model was developed to determine the relationship between environmental variables and dieback. Coefficient of determination value (R² = 0.89) depicts that model is statistically good. Model indicated that most of the predictor variables has minor role in disease development except age and time span. With one unit increase in age and time span disease will increase 4.15 and 5.25 units respectively. Values of partial R-square indicated that age class (0.5253), time span (0.2943) and relative humidity (0.0552) are major contributors in disease development. It was concluded form the study that age and time span are significant predictor of dieback. [ABSTRACT FROM AUTHOR]