Spatial and temporal patterns of vegetation carbon sources/sinks and driving factors in southeastern Xizang from 2000 to 2020.

Jiahua Han, Xiyue Meng, Li Lin, Jie Lu

Abstract read

In one paragraph

Article in PeerJ, 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

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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.

Spatiotemporal evolution and drivers of carbon stock in arid oases: Multi-source assessment and scenario prediction in Wei-Ku oasis, China.iScience · 2026
Article

4 · The record

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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

4 authors.

Jiahua HanSchool of Ecology and Environment, Xizang University, Lhasa, China.

Xiyue MengInstitute of Xizang Plateau Ecology, Xizang Agricultural and Animal Husbandry University, Nyingchi, China.

Li LinSchool of Ecology and Environment, Xizang University, Lhasa, China.

Jie LuInstitute of Xizang Plateau Ecology, Xizang Agricultural and Animal Husbandry University, Nyingchi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Net ecosystem productivity (NEP) is a crucial measurement for understanding ecosystem function and carbon cycling. On the basis of Moderate Resolution Imaging Spectroradiometer (MODIS) data, meteorological data, and topographic data, combined with the enhanced Carnegie Ames Stanford Approach (CASA) model, we analyzed the spatiotemporal trends and changes in the vegetation NEP in southeastern Xizang from 2000 to 2020. Additionally, we employed the GeoDetector model to identify the driving factors influencing the vegetation NEP. The results indicated that: (1) from 2000 to 2020, the annual vegetation NEP in southeastern Xizang exhibited a fluctuating increasing trend. The multiyear average vegetation NEP was 519.06 gC m

Indexed as

CarbonCarbon CycleCarbon SequestrationEcosystemPlantsChinaSpatio-Temporal AnalysisCarbonCASA modelDriving factorsGeoDetectorNet ecosystem productivitySoutheast Xizang (Tibet)

Identifiers

PMID41527572

DOI10.7717/peerj.20572

PMCPMC12790777

What OpenQuestion holds

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LicenceCC BY

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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.