↓ Skip to main content

Leaf unfolding of Tibetan alpine meadows captures the arrival of monsoon rainfall

Overview of attention for article published in Scientific Reports, February 2016
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

news
7 news outlets
twitter
2 X users
facebook
1 Facebook page
googleplus
1 Google+ user

Citations

dimensions_citation
47 Dimensions

Readers on

mendeley
27 Mendeley
Title
Leaf unfolding of Tibetan alpine meadows captures the arrival of monsoon rainfall
Published in
Scientific Reports, February 2016
DOI 10.1038/srep20985
Pubmed ID
Authors

Ruicheng Li, Tianxiang Luo, Thomas Mölg, Jingxue Zhao, Xiang Li, Xiaoyong Cui, Mingyuan Du, Yanhong Tang

Abstract

The alpine meadow on the Tibetan Plateau is the highest and largest pasture in the world, and its formation and distribution are mainly controlled by Indian summer monsoon effects. However, little is known about how monsoon-related cues may trigger spring phenology of the vast alpine vegetation. Based on the 7-year observations with fenced and transplanted experiments across lower to upper limits of Kobresia meadows in the central plateau (4400-5200 m), we found that leaf unfolding dates of dominant sedge and grass species synchronized with monsoon onset, regardless of air temperature. We also found similar patterns in a 22-year data set from the northeast plateau. In the monsoon-related cues for leaf unfolding, the arrival of monsoon rainfall is crucial, while seasonal air temperatures are already continuously above 0 °C. In contrast, the early-emerging cushion species generally leafed out earlier in warmer years regardless of precipitation. Our data provide evidence that leaf unfolding of dominant species in the alpine meadows senses the arrival of monsoon-season rainfall. These findings also provide a basis for interpreting the spatially variable greening responses to warming detected in the world's highest pasture, and suggest a phenological strategy for avoiding damages of pre-monsoon drought and frost to alpine plants.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 4%
Unknown 26 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 22%
Student > Ph. D. Student 5 19%
Student > Master 3 11%
Student > Doctoral Student 1 4%
Librarian 1 4%
Other 2 7%
Unknown 9 33%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 22%
Environmental Science 5 19%
Earth and Planetary Sciences 3 11%
Social Sciences 1 4%
Unknown 12 44%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 64. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 March 2016.
All research outputs
#568,422
of 22,851,489 outputs
Outputs from Scientific Reports
#6,357
of 123,393 outputs
Outputs of similar age
#11,897
of 400,377 outputs
Outputs of similar age from Scientific Reports
#228
of 3,314 outputs
Altmetric has tracked 22,851,489 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 123,393 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.2. This one has done particularly well, scoring higher than 94% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 400,377 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 3,314 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.