Evidence map›Paper›PMID 40144763›Full record

ArticleFrontiers in plant science2025

Adaptive management for alpine grassland of the Tibetan Plateau based on a multi-criteria assessment.

Tianyu Zhan, Shurong Zhang, Wenwu Zhao

Abstract read
In one paragraph

Article in Frontiers in plant science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Tianyu ZhanState Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing, China.
Shurong ZhangState Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing, China.
Wenwu ZhaoState Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the increasing threats of global climate change and human activities to terrestrial ecosystems, understanding the quality of alpine grassland ecosystems and their influencing factors is fundamental for effective ecosystem management and improving human well-being. However, current adaptive management plans for alpine grasslands based on multi-criteria assessment are limited. This study utilized field investigations at 77 sampling points, drone remote sensing, and satellite remote sensing data to construct an alpine grassland quality index based on vegetation and soil indicators, and assess the ecosystem's resilience and pressure. The assessment revealed that the alpine grasslands of the Tibetan Plateau were classified into five zones, indicating significant differences in quality and pressure levels. Key findings showed that the High-Quality Pressure Zone comprise 41.88% of the area of alpine meadow and 31.89% of alpine steppe, while the Quality Improvement-Limitation Zone account for 21.14% and 35.8% of the respective areas. The study recommends graded protection and recovery strategies for alpine grasslands based on quality levels: prioritizing high-quality grasslands, implementing dynamic monitoring and enhancement for moderate-quality grasslands, and applying artificial interventions and suitable species for low-quality grasslands. This research underscores the importance of zoning-based adaptive strategies for sustainable ecosystem management and provides valuable insights for effective management and protection of alpine grasslands in the Tibetan Plateau.

Indexed as

adaptive managementalpine grasslandmulti-criteriaTibetan Plateauzone

Identifiers

PMID40144763
PMCPMC11937058

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Registered trials

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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.