Abstract ID: 3.8112 | Pending | Poster | TBA | TBA

Tree line vegetation serves as a key indicator of climate change, shaped by diverse topographic and climatic conditions. While forest structure along environmental gradients has been studied, most research has focused on single species, leaving the variation in forest structure across tree line ecoregions and their response to environmental factors largely unexplored in Nepal. This study aims to address this gap by assessing forest composition and structure along the tree line ecotone of the Annapurna mountains using terrestrial mobile laser scanning. We analyzed 90 plots (25m diameter), with an equal number of plots (45) distributed on the windward (wet) side and on the leeward (dry) side, where annual average precipitation varies from 4000 mm to 200 mm. Species diversity and the 15 forest structural variables were derived by assessing point cloud data using LIDAR 360 software to compare the two sides of the mountain. Similarly, 19 bio-climatic variables from CHELSA climatic data and three topographic variables elevation, aspect, and slope were used to study the effects of environmental variables on forest variables. Generalized additive models (GAM) revealed a significant decline in all forest variables with increasing elevation, more pronounced in dry regions. Wet-region forests were denser and more diverse but exhibited lower structural complexity, suggesting intense competition and ecological interactions. In contrast, dry-region forests were sparse but have higher structural complexity highlighting spatial adaptability to arid conditions. Random forest models identified elevation, maximum summer temperature, annual precipitation, isothermality, aspect, and slope as key environmental drivers of tree line vegetation. Our findings emphasize the importance of understanding tree line composition and structure for effective conservation and biodiversity management. These insights could guide future research on the impact of global warming on mountain forest ecosystems and inform strategies for sustainable resource management.