Spatiotemporal variation in the vegetation cover of Peshawar Basin in response to climate change.

Climate factors like temperature, precipitation, humidity, and sunshine time exert a profound influence on vegetation. The intricate interplay between the two is crucial to understand in the face of changing climate to develop mitigation strategies. In the current exploration, we delve how climate variability (CV) has impacted the vegetation in the Peshawar Basin (PB) using remote sensing data tools. The trend of climatic variability was investigated using the modified Mann-Kendall test and Sen's slope statistics. The changing climatic parameters were regressed on the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI). The NDVI was further analyzed for spatiotemporal variability under land surface temperature (LST) influence. Results revealed that among the climate factors, average annual temperature and solar radiation have a significant (p < 0.05) negative impact on vegetation while precipitation and relative humidity significantly (p < 0.05) influence NDVI positively. The overall positive trend shows that vegetation improved between 2001 and 2020 with time, however some years (2010, 2012, 2014, 2016, and 2017) with low NDVI. NDVI varied in space considerably due to climatic extremes brought on by CV and the urbanization of agricultural land. NDVI regressed on LST showed that there was no or very little vegetation in the grids with high LST. The study concluded that the region is significantly impacted by both CV-related extreme weather events and anthropogenic activities. The vegetation is improving, but it is in danger of being destroyed by deforestation due to CV and human activities that exacerbate the risk of future calamities. To protect vegetation and avoid disasters, there is an immense need for adaptation and mitigation measures to deal with the region's fast-changing environment. The study urges local authorities to create climate-resilient governmental policies and supports regional sustainable development and vegetation restoration.

Multivariate analysis of the summer herbaceous vegetation and environmental factors of the sub-tropical region.

Understanding the distribution of the plant species of an unexplored area is the utmost need of the present-day. In order to collect vegetation data, Quadrat method was used having size of 1 m2. The composite soil samples from each site were tested for various edaphic properties. PC-ORD v.5 was used for the classification of the vegetation while CANOCO v.5.1 was used for ordination of the data and to find out the complex relationship between plants and environment. Survey was conducted during summer season and a total of 216 herbaceous species were recorded from forty different sites of District Kohat, Pakistan. Cluster Analysis (CA) and Two-Way Cluster Analysis (TWCA) classified the vegetation of forty sites into six major plant groups i.e., 1. Paspalum paspalodes, Alternanthera sessilis, Typha domingensis, 2. Cynodon dactylon, Parthenium hysterophorus, Brachiaria ramosa, 3. Cynodon dactylon, Eragrostis minor, Cymbopogon jwarancusa, 4. Cymbopogon jwarancusa, Aristida adscensionis, Boerhavia procumbens, 5. Cymbopogon jwarancusa, Aristida adscensionis, Pennisetum orientale and 6. Heteropogon contortus, Bothriochloa ischaemum, Chrysopogon serrulatus. They were named after the dominant species based on their Importance Value (IV). The detrended correspondence analysis (DCA) analysis further confirmed the vegetation classification. Canonical correspondence analysis (CCA) indicated that the species distribution in the area was strongly affected by various environmental factors including status, soil characteristics, topography and altitude.