Evidence map›Paper›PMID 35551521›Full record

ArticleEnvironmental monitoring and assessment2022

Analysis of the spatial distribution and influencing factors of China national forest villages.

Guofang Gong, Zhen Wei, Fengtai Zhang, Yuzhen Li, Youzhi An, Qing Yang, Jianfeng Wu, Lu Wang, Pengzhen Yu

Abstract read
PubMed Publisher
In one paragraph

Article in Environmental monitoring and assessment, 2022. 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. China's environmental solutions.Applied microbiology and biotechnology · 2023
    Review
  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

9 authors.

Guofang GongSchool of Management, Chongqing University of Technology, Chongqing, 400054, China.
Zhen WeiSchool of Management, Chongqing University of Technology, Chongqing, 400054, China.
Fengtai ZhangSchool of Management, Chongqing University of Technology, Chongqing, 400054, China. zhfthero45@cqut.edu.cn.ORCID http://orcid.org/0000-0002-5981-5381
Yuzhen LiSchool of Management, Chongqing University of Technology, Chongqing, 400054, China.
Youzhi AnSchool of Management, Chongqing University of Technology, Chongqing, 400054, China.
Qing YangSchool of Management, Chongqing University of Technology, Chongqing, 400054, China.
Jianfeng WuSchool of Geography and Resources, Guizhou Education University, Guiyang, 550018, China.
Lu WangSchool of Foreign Studies, Hefei University of Technology, Hefei, 230009, China.
Pengzhen YuSchool of Management, Chongqing University of Technology, Chongqing, 400054, China.

Funding

Chongqing Social Science Planning Project No.2019YBGL075Humanities and Social Science Research Project of The Ministry of Education of China No.20XJCZH001Humanities and Social Sciences Research Program of Chongqing Municipal Education Commission No.19SKGH132Science and Technology Research Program of Chongqing Municipal Education Commission No.KJQN201901129
6 · The paper itself

Abstract

China national forest villages are the agents to promote rural greening and beautification, as well as further implementation of the rural revitalization strategy. It is of great significance to study their spatial distribution characteristics and influencing factors. Therefore, taking 7586 China national forest villages as examples, the methods of nearest neighbor index, Tyson polygon, cold and hot spot analysis, and nuclear density index are used to study the spatial distribution characteristics of China national forest villages and their influencing factors. The results show that (1) since the nearest neighbor index is less than 1, and the Tyson polygon area variation coefficient is much greater than 64%, it is comprehensively determined that the distribution of China national forest villages belongs to agglomerated distribution. (2) The spatial clustering is characterized by "hot in the south and cold in the north." The hot spots are dominated by southern regions such as Sichuan, Hubei, and Jiangsu, and the cold spots are dominated by northern regions such as Heilongjiang, Jilin and Xinjiang. (3) The distribution characteristics of nuclear density have a strong correlation with the distribution characteristics of forest vegetation and urban agglomerations. Most high-density areas are located within the forest vegetation coverage. The first batch forms the Yangtze River Delta and Central Plains urban agglomerations high-density areas, and the second batch forms the Yangtze River Delta and Central Plains high-density areas. (4) Elevation, aspect, river, forest resources endowment, traffic, economic development level, and population size are important factors affecting the distribution of China national forest villages, and their distribution presents the characteristics of "low altitude, positive direction, near water, rich forest resources, convenient transportation, developed economy, and dense population." The research can provide reference for the evaluation and construction of China national forest villages and the implementation of village beautification and rural revitalization strategies in the future.

Indexed as

Environmental MonitoringForestsChinaEconomic DevelopmentRiversSpatial AnalysisCorrelation analysisForest resourcesGISLandscape patternRural revitalization

Identifiers

What OpenQuestion holds

Textmetadata
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.