Evidence map›Paper›PMID 36388591›Full record

ArticleFrontiers in plant science2022

Characterization and attribution of vegetation dynamics in the ecologically fragile South China Karst: Evidence from three decadal Landsat observations.

Jie Pei, Li Wang, Huabing Huang, Lei Wang, Wang Li, Xiaoyue Wang, Hui Yang, Jianhua Cao, Huajun Fang, Zheng Niu

Abstract read
In one paragraph

Article in Frontiers in plant science, 2022. 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

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

1 citing paper in PubMed.

  1. 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

10 authors.

Jie PeiSchool of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai, China.
Li WangState Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China.
Huabing HuangSchool of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai, China.
Lei WangInternational Research Center of Big Data for Sustainable Development Goals, Beijing, China.
Wang LiState Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China.
Xiaoyue WangThe Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
Hui YangInstitute of Karst Geology, Chinese Academy of Geological Sciences (CAGS), Karst Dynamics Laboratory, Ministry of Natural Resources (MNR) & Guangxi, Guilin, China.
Jianhua CaoInstitute of Karst Geology, Chinese Academy of Geological Sciences (CAGS), Karst Dynamics Laboratory, Ministry of Natural Resources (MNR) & Guangxi, Guilin, China.
Huajun FangKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
Zheng NiuState Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Plant growth and its changes over space and time are effective indicators for signifying ecosystem health. However, large uncertainties remain in characterizing and attributing vegetation changes in the ecologically fragile South China Karst region, since most existing studies were conducted at a coarse spatial resolution or covered limited time spans. Considering the highly fragmented landscapes in the region, this hinders their capability in detecting fine information of vegetation dynamics taking place at local scales and comprehending the influence of climate change usually over relatively long temporal ranges. Here, we explored the spatiotemporal variations in vegetation greenness for the entire South China Karst region (1.9 million km

Indexed as

afforestationclimate changeecological fragile areasspatial-temporal evolutionvegetation greenness

Identifiers

PMID36388591
PMCPMC9648820

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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.