Evidence map›Paper›PMID 38112828›Full record

ArticleCarbon balance and management2023

Growing-season carbon budget of alpine meadow ecosystem in the Qinghai Lake Basin: a continued carbon sink through this century according to the Biome-BGC model.

Meng-Ya Zhang, Yu-Jun Ma, Peng Chen, Fang-Zhong Shi, Jun-Qi Wei

Open access · goldAbstract read
In one paragraph

Article in Carbon balance and management, 2023. 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
1.1field-weighted citation impact, top 23% of its field
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, 7 citations in OpenAlex.

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

5 authors at 2 institutions in 1 country.

Meng-Ya ZhangSchool of Geography and Planning, Sun Yat-Sen University, Guangzhou, 510275, China.
Yu-Jun MaSchool of Geography and Planning, Sun Yat-Sen University, Guangzhou, 510275, China. mayujun3@mail.sysu.edu.cn.
Peng ChenSchool of Geography and Planning, Sun Yat-Sen University, Guangzhou, 510275, China.
Fang-Zhong ShiSchool of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.
Jun-Qi WeiSchool of Natural Resources, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.
Sun Yat-sen University · CNBeijing Normal University · CN

Funding

National Natural Science Foundation of China 41730854
6 · The paper itself

Abstract

backgroundThe alpine meadow is one of the most important ecosystems in the Qinghai-Tibet Plateau (QTP), and critically sensitive to climate change and human activities. Thus, it is crucial to precisely reveal the current state and predict future trends in the carbon budget of the alpine meadow ecosystem. The objective of this study was to explore the applicability of the Biome-BGC model (BBGC) in the Qinghai Lake Basin (QLB), identify the key parameters affecting the variation of net ecosystem exchange (NEE), and further predict the future trends in carbon budget in the QLB.

resultsThe alpine meadow mainly acted as carbon sink during the growing season. For the eco-physiological factors, the YEL (Yearday to end litterfall), YSNG (Yearday to start new growth), CLEC (Canopy light extinction coefficient), FRC:LC (New fine root C: new leaf C), SLA (Canopy average specific leaf area), C:N

conclusionOverall, the alpine meadow ecosystem in the QLB generally performs as a carbon sink at present and in the future. It is of great significance for the achievement of the goal of carbon neutrality and the management of alpine ecosystems.

Indexed as

Biome-BGCCarbon budgetClimate changeQinghai Lake BasinSensitivity analysis

Identifiers

PMID38112828
PMCPMC10729358
OpenAlexW4389951339

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LicenceCC BY
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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.