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Abstract Global biodiversity gradients are generally expected to reflect greater species replacement closer to the equator. However, empirical validation of global biodiversity gradients largely relies on vertebrates, plants, and other less diverse taxa. Here we assess the temporal and spatial dynamics of global arthropod biodiversity dynamics using a beta-diversity framework. Sampling includes 129 sampling sites whereby malaise traps are deployed to monitor temporal changes in arthropod communities. Overall, we encountered more than 150,000 unique barcode index numbers (BINs) (i.e. species proxies). We assess between site differences in community diversity using beta-diversity and the partitioned components of species replacement and richness difference. Global total beta-diversity (dissimilarity) increases with decreasing latitude, greater spatial distance and greater temporal distance. Species replacement and richness difference patterns vary across biogeographic regions. Our findings support long-standing, general expectations of global biodiversity patterns. However, we also show that the underlying processes driving patterns may be regionally linked.

Abstract Background Traditional ecological knowledge (TEK) helps tribal communities adapt to socio-ecological changes, improving the long-term sustainability of their livelihood strategies and fostering social–ecological resilience. TEK provides thorough understanding of ecosystem dynamics, as well as how they relate to societal norms, practices, and resource use patterns. The integrity of TEK is often in jeopardy due to changes in belief systems, regional languages, traditional ways of subsistence, and disruption of traditional social–ecological systems. Landscape restoration has the ability to promote self-determination while safeguarding the livelihoods, beliefs, cultural, and biodiversity of indigenous peoples. However, there is a substantial knowledge gap on how TEK might aid ecosystem restoration, particularly in elephant corridors. Methods The current study focused on gathering traditional ecological knowledge on the woody tree species from the Dering-Dibru Saikhowa Elephant Corridor using semi-structured interviews, group discussions, and direct observations. The acquired data were applied to heat map cluster analysis and ordination techniques using R software version 4.0.0. Results Traditional usage information of 31 tree species utilized for food, fodder, timber, fuelwood, medicinal, and livelihood by local people was gathered. Most of the species utilized locally belonged to the families Combretaceae and Fabaceae. The species were classified into single, double, or multi-uses based on the extent of utilization. Azadirachta indica, Phyllanthus emblica, and Syzygium cumini (six each) had the highest utilization, while Mesua ferrea had the lowest. Chionanthus ramiflorus, Artocarpus heterophyllus, and Dillenia indica were among the plants valuable to wildlife, providing both forage and habitat for a wide variety of birds and animals. Artocarpus heterophyllus, Averrhoa carambola, Mangifera indica, P. emblica, Psidium guajava, and S. cumini were among the plants important for the livelihoods of the local community. Our findings demonstrated that local people were knowledgeable about the plant species to use as pioneer species, such as Bombax ceiba, Albizia lebbeck, D. indica, S. cumini, P. emblica, Lagerstroemia speciosa, and Alstonia scholaris, for habitat restoration in a diverse habitat. We classified the habitat of the enlisted species into different categories, and two clusters (clusters 1 and 2) were identified based on the similarity of woody species in different habitats. We prioritized multiple tree species for eco-restoration using the information collected through TEK. We planted 95,582 saplings on 150 hectares in the Dering-Dibru Saikhowa Elephant Corridors’ degraded habitat patches, which will serve as future reference site for landscape rehabilitation. Out of total saplings planted, 56% of the species were linked to native communities through ethnobotanical uses, as well as providing connectivity and habitat for elephant movement, 16% of all woody species are pioneer species to colonize a degraded habitat, 15% of all woody species are preferred food and foraging by wildlife, and 13% of the species as a source of livelihood for local people, incorporating social, economic, cultural, and biodiversity benefits into the restoration framework. Conclusion The current study also provides insights how the TEK can assist with aspects of ecological restoration, from reference ecosystem reconstruction and adaptive management through species selection for restoration, monitoring, and evaluation of restoration effectiveness.

Designing of molecules for drugs is important topic from many decades. The search of new drugs is very hard, and it is expensive process. Computer assisted framework can provide the fastest way to design and screen drug-like compounds. In present work, a multidimensional approach is introduced for the designing and screening of antioxidant compounds. Antioxidants play a crucial role in ensuring that the body's oxidizing and reducing species are kept in the proper balance, minimizing oxidative stress. Machine learning models are used to predict antioxidant activity. Three hydroxycinnamates are selected as standard antioxidants. Similar compounds are searched from ChEMBL database using chemical structural similarity method. The libraries of new compounds are generated using evolutionary method. New compounds are also designed using automatic decomposition and construction building blocks. The antioxidant activity of all designed and searched compounds is predicted using machine learning models. The chemical space of searched and generated compounds is envisioned using t-distributed stochastic neighbor embedding (t-SNE) method. Best compounds are shortlisted, and their synthetic accessibility is predicted to further facilitate the experimental chemists. The chemical similarity between standard and selected compounds is also studied using fingerprints and heatmap.

Although insects dominate the terrestrial fauna, sampling constraints and the poor taxonomic knowledge of many groups have limited assessments of their diversity. Passive sampling techniques and DNA-based species assignments now make it possible to overcome these barriers. For example, Malaise traps collect specimens with minimal intervention while the Barcode Index Number (BIN) system automates taxonomic assignments. The present study employs Malaise traps and DNA barcoding to extend understanding of insect diversity in one of the least known zoogeographic regions, the Saharo-Arabian. Insects were collected at four sites in three countries (Egypt, Pakistan, Saudi Arabia) by deploying Malaise traps. The collected specimens were analyzed by sequencing 658 bp of cytochrome oxidase I (DNA barcode) and assigning BINs on the Barcode of Life Data Systems. The year-long deployment of a Malaise trap in Pakistan and briefer placements at two Egyptian sites and at one in Saudi Arabia collected 53,092 specimens. They belonged to 17 insect orders with Diptera and Hymenoptera dominating the catch. Barcode sequences were recovered from 44,432 (84%) of the specimens, revealing the occurrence of 3,682 BINs belonging to 254 families. Many of these taxa were uncommon as 25% of the families and 50% of the BINs from Pakistan were only present in one sample. Family and BIN counts varied significantly through the year, but diversity indices did not. Although more than 10,000 specimens were analyzed from each nation, just 2% of BINs were shared by Pakistan and Saudi Arabia, 4% by Egypt and Pakistan, and 7% by Egypt and Saudi Arabia. The present study demonstrates how the BIN system can circumvent the barriers imposed by limited access to taxonomic specialists and by the fact that many insect species in the Saharo-Arabian region are undescribed.