Evidence map›Paper›PMID 32770004›Full record

ArticleScientific reports2020

Understanding the spatial-temporal variation of human footprint in Jiangsu Province, China, its anthropogenic and natural drivers and potential implications.

Feixue Shen, Lin Yang, Xianglin He, Chenghu Zhou, Jonathan M Adams

Abstract read
In one paragraph

Article in Scientific reports, 2020. 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

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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

2 citing papers in PubMed.

  1. Article
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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

5 authors.

Feixue ShenSchool of Geography and Ocean Science, Nanjing University, Nanjing, 210023, China.
Lin YangSchool of Geography and Ocean Science, Nanjing University, Nanjing, 210023, China. yanglin@nju.edu.cn.
Xianglin HeSchool of Geography and Ocean Science, Nanjing University, Nanjing, 210023, China.
Chenghu ZhouSchool of Geography and Ocean Science, Nanjing University, Nanjing, 210023, China.
Jonathan M AdamsSchool of Geography and Ocean Science, Nanjing University, Nanjing, 210023, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the spatial and temporal patterns of human pressures provides a foundation for understanding interactions between human and environment and managing human activities for a sustainable development. This study is the first attempt focused within China at calculating the spatial-temporal human footprint and its driving forces in a highly urbanized area with intensive human activities. Population, land use, night-time lights, and road impacts were used to generate human footprint maps of Jiangsu Province for 2000, 2010 and 2015 with a resolution of 1 km * 1 km. Five natural drivers and four anthropogenic drivers were employed to construct generalized additive models for explaining the spatial variation of human footprint and its change. It shows that a large difference is between the human footprint in northern and southern Jiangsu, and the pattern of human pressures conforms to the "Matthew effect", with spatial aggregation of high human footprint areas accelerating. Slope, industrialization level are significant in explaining the spatial variation of human footprint in 2000, 2010 and 2015. The effect of natural drivers decreases for explaining the human footprint over time. Furthermore, annual precipitation, mean annual temperature and urban per capita disposable income are also significant drivers for human footprint in 2010 and 2015. And the increasing of human footprint slows with increasing of industrialization level. The difference of industrialization level and urban income between northern and southern Jiangsu mainly caused different driving pattern for human footprint and its change. Our study has generated new insights on the interaction pattern between human and nature in highly developed regions based on the human footprint concept, and can provide references for managing human activities in similar regions rapid socioeconomic development.

Indexed as

EcosystemHuman ActivitiesSustainable DevelopmentUrbanizationHumans

Identifiers

PMID32770004
PMCPMC7414874

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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.