The cold desert biome of Spiti Valley, located in the north-western Trans-Himalayas of Himachal Pradesh, is a biodiversity-rich region supporting a wide range of medicinal and aromatic plants (MAPs) within its unique ecosystems. These temperate and alpine species serve as important raw materials for traditional herbal medicines used in the Amchi healthcare system practiced in Spiti Valley. This indigenous system, derived from Tibetan medicine and linked to the broader Chinese medical tradition, represents a valuable cultural heritage. Experienced Amchis prepare herbal remedies using traditional formulations by combining various plant species to treat local tribal communities. However, the survival of these medicinal plants and the continuity of the Amchi tradition are increasingly threatened by rapid developmental activities in the fragile Trans-Himalayan region. Depletion of plant resources from easily accessible areas has further weakened the profession and created serious concerns for the future of this traditional knowledge system. The present manuscript highlights plant species at risk from development pressures and notes the changing social trend of abandoning traditional medicine. Sustainable resource management, environmental awareness, and participatory assessment before development projects are essential to conserve both medicinal flora and this cultural heritage.

Present study endeavours to propagate Oroxylum indicum using vegetative propagation techniques. Stem cuttings and root cuttings are used as propagules. The cuttings were subjected to optimal environmental condition, well-draining rooting medium and treated with variable concentration of rooting hormones (IBA and NAA) for better root development. Data was documented on root development and overall growth. Vegetative propagation techniques yielded promising results, with plantlets developed from root cuttings displaying superior survival rates (55%) and rooting response compared to those from stem cuttings. These findings offer valuable insights for optimum propagation of O. indicum. Therefore, it is recommended that root cuttings be used as the preferred propagule for large-scale propagation and conservation efforts aimed at preserving this vital species.

The Sherdukpen tribe, a major ethnic group of West Kameng district in Arunachal Pradesh, possesses rich ethnobotanical knowledge and relies extensively on plant resources. This study aimed to document and evaluate culturally important tree species used by the community. Data were collected from 105 informants across seven villages through questionnaires and personal interviews. A total of 30 tree species, representing 23 genera and 18 families, were recorded and classified into eleven use categories, with Rosaceae as the dominant family. Food category accounted for the highest proportion (25%), while manure category was minimal (2.9%). Gender-based knowledge variation was observed, with women more familiar with food-related species and men with species used for construction, tools, and poison. Pinus wallichiana, Quercus griffithii, and Rhododendron arboreum showed the highest cultural importance. The study highlights diverse utilization patterns and cultural significance of tree resources.

This study presents ethnomedicinal research conducted in the Bhaba Valley of Kinnaur district, Himachal Pradesh, offering valuable insights into phytomedicinal practices among the local indigenous community. The primary objective was to document the therapeutic uses of plants and to develop a comprehensive ethnobotanical inventory of the region’s biodiversity. Data were collected during 2023–2024 through semi-structured questionnaires and group discussions. Quantitative indices, including Informant Consensus Factor (ICF), Relative Frequency of Citation (RFC), Use Value (UV), Use Reports (UR), and Family Importance Value (FIV), were applied to analyze the medicinal plant data. A total of 42 informants (22 males and 20 females) provided information on 34 plant species belonging to 22 families. The highest representation was recorded in the Pinaceae family (4 species), followed by Berberidaceae (3) and Apiaceae (2). Herbs (41%) and trees (32%) were the most commonly used life forms. Most plants were utilized for gastrointestinal ailments, followed by dermatological and respiratory conditions. The findings emphasize the continued reliance on traditional plant-based remedies and highlight the need for systematic documentation and conservation.

­Wildfires have caused long-term economic, ecological, and biological damage, highlighting the need for accurate prediction systems to protect forest wildlife and valuable non-timber resources such as medicinal plants, aromatic products, food, fodder, and fuelwood. This study proposes wildfire prediction models using frequency-domain analytics and Bayesian Optimization (BSO) in designing Convolutional Neural Network (CNN)-based deep learning models, including LeNet-5, AlexNet, and VGG16, applied to the DeepFire dataset. The models are trained and tested on both RGB images and Fast Fourier Transform (FFT)-based frequency-domain representations of fire and non-fire images. BSO, integrated with the Tree-structured Parzen Estimator (TPE), optimizes model parameters to effectively extract fire-related features. Model performance is evaluated using Accuracy and AUC-ROC metrics. Results indicate that BSO-based frequency-aware modified LeNet-5 and AlexNet achieve accuracies of 97% and 96%, respectively. Additionally, RGB-based BSO enhances performance, with modified LeNet-5 and baseline VGG16 reaching up to 98% accuracy. Overall, findings demonstrate that frequency-domain features combined with BSO significantly improve wildfire prediction, supporting ecological and biological conservation efforts.