Evidence map›Paper›PMID 37208404›Full record

ArticleScientific data2023

Vegetation photosynthetic phenology dataset in northern terrestrial ecosystems.

Jing Fang, Xing Li, Jingfeng Xiao, Xiaodong Yan, Bolun Li, Feng Liu

Abstract readDataset
In one paragraph

Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. 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.

Jing FangCAS Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, China.
Xing LiResearch Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea.
Jingfeng XiaoEarth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, USA.ORCID 0000-0002-0622-6903
Xiaodong YanState Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China.
Bolun LiResearch Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea.
Feng LiuCAS Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, China. liufeng@wbgcas.cn.

Funding

National Natural Science Foundation of China (National Science Foundation of China) 32101349
6 · The paper itself

Abstract

Vegetation phenology can profoundly modulate the climate-biosphere interactions and thus plays a crucial role in regulating the terrestrial carbon cycle and the climate. However, most previous phenology studies rely on traditional vegetation indices, which are inadequate to characterize the seasonal activity of photosynthesis. Here, we generated an annual vegetation photosynthetic phenology dataset with a spatial resolution of 0.05 degrees from 2001 to 2020, using the latest gross primary productivity product based on solar-induced chlorophyll fluorescence (GOSIF-GPP). We combined smoothing splines with multiple change-point detection to retrieve the phenology metrics: start of the growing season (SOS), end of the growing season (EOS), and length of growing season (LOS) for terrestrial ecosystems above 30° N latitude (Northern Biomes). Our phenology product can be used to validate and develop phenology or carbon cycle models and monitor the climate change impacts on terrestrial ecosystems.

Indexed as

EcosystemPhotosynthesisCarbon CycleClimate ChangeSeasons

Identifiers

PMID37208404
PMCPMC10198999

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.