An attempt has been made to list the trees and their uses mentioned in the Holy Bible (New English Version). There are 293 verses which speak about the trees, the different versatile uses and their effects. There is a proper mention of 22 trees species in the Bible.

A study in Sikkim’s Khangchendzonga landscape examined economic activities related to non-timber forest products (NTFPs), focusing on ten medicinal plants. It analyzed supply chains, traceability, and stakeholder roles. Due to a statewide ban on wild collection, collectors gathered small quantities and sold them to retail shops or local traders. These traders semi-processed the materials and passed them to wholesalers, who transported them with other crops to markets in Nepal or Siliguri, where they were mixed with other plant materials. The study found no linkage among stakeholders, making traceability to source impossible. To ensure sustainable harvesting, value addition, and better market access, coordinated participation of local communities, traders, herbal industries, and the forest department is essential.

­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.

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.

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.