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[Display omitted] Structural information of grassland changes on the Tibetan Plateau is essential for understanding alterations in critical ecosystem functioning and their underlying drivers that may reflect environmental changes. However, such information at the regional scale is still lacking due to methodological limitations. Beyond remote sensing indicators only recognizing vegetation productivity, we utilized multivariate data fusion and deep learning to characterize formation-based plant community structure in alpine grasslands at the regional scale of the Tibetan Plateau for the first time and compared it with the earlier version of Vegetation Map of China for historical changes. Over the past 40 years, we revealed that (1) the proportion of alpine meadows in alpine grasslands increased from 50% to 69%, well-reflecting the warming and wetting trend; (2) dominances of Kobresia pygmaea and Stipa purpurea formations in alpine meadows and steppes were strengthened to 76% and 92%, respectively; (3) the climate factor mainly drove the distribution of Stipa purpurea formation, but not the recent distribution of Kobresia pygmaea formation that was likely shaped by human activities. Therefore, the underlying mechanisms of grassland changes over the past 40 years were considered to be formation dependent. Overall, the first exploration for structural information of plant community changes in this study not only provides a new perspective to understand drivers of grassland changes and their spatial heterogeneity at the regional scale of the Tibetan Plateau, but also innovates large-scale vegetation study paradigm. [ABSTRACT FROM AUTHOR]

Extensive global glacial retreats are threatening cryosphere ecosystem functioning and the associated biota in glacier-fed water systems. Understanding multi-group biodiversity distributions and compositional variation across diverse but hydrologically linked habitats under varying glacial influences will help explain the mechanisms underlying glacial community organization and ecosystem processes. However, such data are generally lacking due to the difficulty of obtaining biodiversity information across wide taxonomic ranges. Here, we used a multi-marker environmental DNA metabarcoding approach to simultaneously investigate the spatial patterns of community compositions and assembly mechanisms of four taxonomic groups (cyanobacteria, diatoms, invertebrates, and vertebrates) along the flowpaths of a tributary of Lake Nam Co on the Tibetan Plateau—from its glacier headwaters, through its downstream river and wetlands, to its estuary. We detected 869 operational taxonomic units: 119 cyanobacterial, 395 diatom, 269 invertebrate, and 86 vertebrate. Taxonomic richnesses consistently increased from upstream to downstream, and although all groups showed community similarity distance decay patterns, the trend for vertebrates was the weakest. Cyanobacteria, diatom, and invertebrate community compositions were significantly correlated with several environmental factors, while the vertebrate community was only correlated with waterway width. Variation partitioning analysis indicated that varying extents of environmental conditions and spatial factors affected community organizations for different groups. Furthermore, stochastic processes contributed prominently to the microorganisms' community assembly (Sloan's neutral model R 2 = 0.77 for cyanobacteria and 0.73 for diatoms) but were less important for macroorganisms (R 2 = 0.21 for invertebrates and 0.15 for vertebrates). That trend was further substantiated by modified stochasticity ratio analyses. This study provides the first holistic picture of the diverse biotic communities residing in a series of hydrologically connected glacier-influenced habitats. Our results both uncovered the distinct mechanisms that underlie the metacommunity organizations of different glacial organisms and helped comprehensively predict the ecological impacts of the world's melting glaciers. [Display omitted] • Environmental DNA captured diverse biota along a glacial pathway. • Different organism groups showed variable biodiversity distribution patterns. • Smaller organisms' communities were more correlated with environmental factors. • Stochastic and deterministic processes differentially impacted community assembly. • Multi-group biomonitoring can comprehensively assess ecosystem responses. [ABSTRACT FROM AUTHOR]