Elevational distribution patterns of bryophytes in Eastern China - A comprehensive species-trait dataset

Yi Ran Wang; Xue Yao; Peng Zheng; Rui Ping Shi; Min Li; Zun Dai; Xing Chen; Shu Wen Tu; Yu Ting Yang; En Dao Wang; Kun Song; Zhong Sheng He; Zhao Chen Zhang; Qi Wu; Hong Yu Zhang; Yu Ling Xiong; En Qi Lou; You Fang Wang; Jian Zhang; Jian Wang

doi:10.1038/s41597-025-06247-3

Elevational distribution patterns of bryophytes in Eastern China - A comprehensive species-trait dataset

Yi Ran Wang
, Xue Yao
, Peng Zheng
, Rui Ping Shi
, Min Li
, Zun Dai
, Xing Chen
, Shu Wen Tu
, Yu Ting Yang
, En Dao Wang
, Kun Song
, Zhong Sheng He
, Zhao Chen Zhang
, Qi Wu
, Hong Yu Zhang
, Yu Ling Xiong
, En Qi Lou
, You Fang Wang
, Jian Zhang^*
, Jian Wang^*

^*Corresponding author for this work

School of Ecology and Environmental Sciences

Research output: Contribution to journal › Article › peer-review

Abstract

Climate change significantly affects the dynamics of mountain ecosystems, impacting not only species distributions but also their phenological characteristics. Nevertheless, our comprehension of the effects of climate change on biodiversity is still limited, primarily due to insufficient historical data. The dramatic temperature variations over short distances make permanent monitoring plots along elevational gradients an ideal natural laboratory for investigating species’ responses to climate change. Drawing on field survey information gathered from 2018 to 2022, we have developed a bryophyte species-trait dataset that encompasses 16,920 trait measurements across four categories: taxonomy, distribution, resistance traits, and reproductive traits, derived from 549 species in Eastern China. The compilation of this bryophyte species-trait dataset offers valuable opportunities to deepen our understanding of the factors, constraints, and effects associated with biodiversity variability, while also providing richer insights into predicting species distributions and implementing targeted in-situ conservation strategies.

Original language	English
Article number	2001
Journal	Scientific Data
Volume	12
Issue number	1
DOIs	https://doi.org/10.1038/s41597-025-06247-3
State	Published - Dec 2025

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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Wang, Y. R., Yao, X., Zheng, P., Shi, R. P., Li, M., Dai, Z., Chen, X., Tu, S. W., Yang, Y. T., Wang, E. D., Song, K., He, Z. S., Zhang, Z. C., Wu, Q., Zhang, H. Y., Xiong, Y. L., Lou, E. Q., Wang, Y. F., Zhang, J., & Wang, J. (2025). Elevational distribution patterns of bryophytes in Eastern China - A comprehensive species-trait dataset. Scientific Data, 12(1), Article 2001. https://doi.org/10.1038/s41597-025-06247-3

@article{319b5c2d80a641fabc01485faef9b721,

title = "Elevational distribution patterns of bryophytes in Eastern China - A comprehensive species-trait dataset",

abstract = "Climate change significantly affects the dynamics of mountain ecosystems, impacting not only species distributions but also their phenological characteristics. Nevertheless, our comprehension of the effects of climate change on biodiversity is still limited, primarily due to insufficient historical data. The dramatic temperature variations over short distances make permanent monitoring plots along elevational gradients an ideal natural laboratory for investigating species{\textquoteright} responses to climate change. Drawing on field survey information gathered from 2018 to 2022, we have developed a bryophyte species-trait dataset that encompasses 16,920 trait measurements across four categories: taxonomy, distribution, resistance traits, and reproductive traits, derived from 549 species in Eastern China. The compilation of this bryophyte species-trait dataset offers valuable opportunities to deepen our understanding of the factors, constraints, and effects associated with biodiversity variability, while also providing richer insights into predicting species distributions and implementing targeted in-situ conservation strategies.",

author = "Wang, \{Yi Ran\} and Xue Yao and Peng Zheng and Shi, \{Rui Ping\} and Min Li and Zun Dai and Xing Chen and Tu, \{Shu Wen\} and Yang, \{Yu Ting\} and Wang, \{En Dao\} and Kun Song and He, \{Zhong Sheng\} and Zhang, \{Zhao Chen\} and Qi Wu and Zhang, \{Hong Yu\} and Xiong, \{Yu Ling\} and Lou, \{En Qi\} and Wang, \{You Fang\} and Jian Zhang and Jian Wang",

note = "Publisher Copyright: {\textcopyright} The Author(s) 2025.",

year = "2025",

month = dec,

doi = "10.1038/s41597-025-06247-3",

language = "英语",

volume = "12",

journal = "Scientific Data",

issn = "2052-4463",

publisher = "Nature Research",

number = "1",

}

Wang, YR, Yao, X, Zheng, P, Shi, RP, Li, M, Dai, Z, Chen, X, Tu, SW, Yang, YT, Wang, ED, Song, K, He, ZS, Zhang, ZC, Wu, Q, Zhang, HY, Xiong, YL, Lou, EQ, Wang, YF, Zhang, J & Wang, J 2025, 'Elevational distribution patterns of bryophytes in Eastern China - A comprehensive species-trait dataset', Scientific Data, vol. 12, no. 1, 2001. https://doi.org/10.1038/s41597-025-06247-3

TY - JOUR

T1 - Elevational distribution patterns of bryophytes in Eastern China - A comprehensive species-trait dataset

AU - Wang, Yi Ran

AU - Yao, Xue

AU - Zheng, Peng

AU - Shi, Rui Ping

AU - Li, Min

AU - Dai, Zun

AU - Chen, Xing

AU - Tu, Shu Wen

AU - Yang, Yu Ting

AU - Wang, En Dao

AU - Song, Kun

AU - He, Zhong Sheng

AU - Zhang, Zhao Chen

AU - Wu, Qi

AU - Zhang, Hong Yu

AU - Xiong, Yu Ling

AU - Lou, En Qi

AU - Wang, You Fang

AU - Zhang, Jian

AU - Wang, Jian

PY - 2025/12

Y1 - 2025/12

N2 - Climate change significantly affects the dynamics of mountain ecosystems, impacting not only species distributions but also their phenological characteristics. Nevertheless, our comprehension of the effects of climate change on biodiversity is still limited, primarily due to insufficient historical data. The dramatic temperature variations over short distances make permanent monitoring plots along elevational gradients an ideal natural laboratory for investigating species’ responses to climate change. Drawing on field survey information gathered from 2018 to 2022, we have developed a bryophyte species-trait dataset that encompasses 16,920 trait measurements across four categories: taxonomy, distribution, resistance traits, and reproductive traits, derived from 549 species in Eastern China. The compilation of this bryophyte species-trait dataset offers valuable opportunities to deepen our understanding of the factors, constraints, and effects associated with biodiversity variability, while also providing richer insights into predicting species distributions and implementing targeted in-situ conservation strategies.

AB - Climate change significantly affects the dynamics of mountain ecosystems, impacting not only species distributions but also their phenological characteristics. Nevertheless, our comprehension of the effects of climate change on biodiversity is still limited, primarily due to insufficient historical data. The dramatic temperature variations over short distances make permanent monitoring plots along elevational gradients an ideal natural laboratory for investigating species’ responses to climate change. Drawing on field survey information gathered from 2018 to 2022, we have developed a bryophyte species-trait dataset that encompasses 16,920 trait measurements across four categories: taxonomy, distribution, resistance traits, and reproductive traits, derived from 549 species in Eastern China. The compilation of this bryophyte species-trait dataset offers valuable opportunities to deepen our understanding of the factors, constraints, and effects associated with biodiversity variability, while also providing richer insights into predicting species distributions and implementing targeted in-situ conservation strategies.

UR - https://www.scopus.com/pages/publications/105025776272

U2 - 10.1038/s41597-025-06247-3

DO - 10.1038/s41597-025-06247-3

M3 - 文章

C2 - 41402323

AN - SCOPUS:105025776272

SN - 2052-4463

VL - 12

JO - Scientific Data

JF - Scientific Data

IS - 1

M1 - 2001

ER -

Elevational distribution patterns of bryophytes in Eastern China - A comprehensive species-trait dataset

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