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Dryad

Ancient orogenic and monsoon-driven assembly of the world's richest temperate alpine flora

Cite this dataset

Ding, Wen-Na; Ree, Richard H.; Spicer, Robert A.; Xing, Yao-Wu (2020). Ancient orogenic and monsoon-driven assembly of the world's richest temperate alpine flora [Dataset]. Dryad. https://doi.org/10.5061/dryad.k6djh9w3s

Abstract

Understanding how alpine biotas formed in response to historical environmental change may improve our ability to predict and mitigate the threats to alpine species posed by global warming. In the world's richest temperate alpine flora, that of the Tibet-Himalaya-Hengduan region, phylogenetic reconstructions of biome and geographic range evolution show that extant lineages emerged by the early Oligocene and diversified first in the Hengduan Mountains. By the early to middle Miocene, accelerated diversification and colonization of adjacent regions were likely driven jointly by mountain building and intensification of the Asian monsoon. The alpine flora of the Hengduan Mountains has continuously existed far longer than any other alpine flora on Earth and illustrates how modern biotas have been shaped by past geological and climatic events.

Usage notes

This upload contains the input data (delimitations of geographical range and biome, time-calibrated phylogenies) and analyses scripts as mentioned in the paper. The scripts in the “data_and_scripts” file are numbered according to the order of execution and named according to their main analyses which can be directly run in each file where the python scripts placed. The R and python codes in the plots file are used for plotting the figures presented in the paper.

Funding

National Natural Science Foundation of China, Award: U1802242

Strategic Priority Research Program of Chinese Academy of Sciences, Award: XDB31000000

China Scholarship Council, Award: No. 201804910698

NERC-NSFC joint project and an Xishuangbanna Tropical Botanical Garden Fellowship for Visiting Scientists, Award: NE/P013805/1

Ministry of Science and Technology of the People's Republic of China, Award: 2017YFC0505200

Grainger Bioinformatics Center at the Field Museum

Strategic Priority Research Program of Chinese Academy of Sciences, Award: XDB31000000

Grainger Bioinformatics Center at the Field Museum