Evidence map›Paper›PMID 41345391›Full record

ArticleScientific data2025

A global hourly gross primary production dataset from 2001 to 2020.

Yong Wang, Zehuang He, Wei Zhao, Gaofei Yin, Xiaobin Guan, Xinyao Xie

Abstract read
In one paragraph

Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Yong WangInstitute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610299, China.
Zehuang HeInstitute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610299, China.
Wei ZhaoInstitute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610299, China.ORCID http://orcid.org/0000-0002-4839-6791
Gaofei YinFaculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu, 610031, China.
Xiaobin GuanSchool of Resource and Environmental Sciences, Wuhan University, Wuhan, 430079, China.ORCID http://orcid.org/0000-0002-3812-7141
Xinyao XieInstitute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610299, China. xinyaoxie@imde.ac.cn.ORCID http://orcid.org/0000-0002-4901-0854

Funding

National Natural Science Foundation of China (National Science Foundation of China) 42222109National Natural Science Foundation of China (National Science Foundation of China) 42471429;42201418
6 · The paper itself

Abstract

Fine-resolution estimation of gross primary production (GPP) is essential for advancing our knowledge of ecosystem carbon cycling. However, most existing global GPP products are constrained by coarse temporal resolutions (typically ≥ 8 days), limiting their capacity to capture short-term variations in ecosystem productivity. This paper presents a global new GPP dataset for 2001-2020, based on a modified radiation scalar two-leaf LUE (RTL-LUE) model. The RTL-LUE GPP dataset is generated at an hourly temporal resolution and a spatial resolution of 0.1°, driven by the hourly climate data from ERA5-land, GLASS leaf area index, MODIS land cover, and NOAA atmospheric CO

Identifiers

PMID41345391
PMCPMC12816656

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.