Evidence map›Paper›PMID 41617722›Full record

ArticleScientific data2026

Spatial Distribution Dataset of All Constructive Grass Species in Tibetan Grasslands under 2024 and 2060.

Guoyong Tang, Qingwan Li, Shunbin Wang, Jinkai Gu, Qinglin Li, Shengjian Xiang, Wanchi Li

Abstract readDataset
In one paragraph

Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Guoyong Tang *Chuxiong Normal University, Chuxiong, China. tangguoyong1980@caf.ac.cn.
Qingwan Li *Chuxiong Normal University, Chuxiong, China.
Shunbin WangInstitute of Highland Forest Science, Chinese Academy of Forestry Sciences, Kunming, China.
Jinkai GuInstitute of Highland Forest Science, Chinese Academy of Forestry Sciences, Kunming, China.
Qinglin LiInstitute of International Rivers and Eco-security, Yunnan University, Kunming, China.
Shengjian XiangInstitute of Highland Forest Science, Chinese Academy of Forestry Sciences, Kunming, China.
Wanchi LiInstitute of Highland Forest Science, Chinese Academy of Forestry Sciences, Kunming, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Tibetan grassland is the principal ecosystem in a high-altitude, ecologically fragile region, providing vital services for biodiversity and local livelihoods. Constructive grass species play a pivotal role in maintaining the structure and function of grassland ecosystems. In this study, we constructed a comprehensive dataset of the spatial distribution of all constructive grass species (44) in Tibetan grasslands under current (2024) and four future (2060) climate scenarios by leveraging species distribution models and high-resolution ecological data. Our dataset encompasses each individual constructive grass species habitat distribution, including expansion, contraction, and stability. This dataset will be applied to climate-change impact assessment on individual species, grassland-type shift projection, and multi-stressor ecosystem-dynamics evaluation. It is essential for supporting grassland management, biodiversity conservation, and livestock production in high-altitude grassland ecosystems.

Indexed as

GrasslandPoaceaeBiodiversityClimate ChangeConservation of Natural ResourcesEcosystemTibet

Identifiers

PMID41617722
PMCPMC12859009

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.