Evidence map›Paper›PMID 39523422›Full record

ArticleScientific reports2024

Evaluating the influence of human disturbance on the ecosystem service scarcity value: an insightful exploration in Guangxi region.

Lanhui Zhou, Changsu Song, Chang You, Longqing Liu

Abstract read
In one paragraph

Article in Scientific reports, 2024. 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

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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

4 authors.

Lanhui Zhou *College of Life and Environmental Sciences, Minzu University of China, Beijing, 100081, China.
Changsu Song *Department of Social & Ecological Studies, Chinese Academy of Governance, Beijing, 100091, China. songcs@ccps.gov.cn.
Chang YouSchool of Ethnology and Sociology, Minzu University of China, Beijing, 100081, China.
Longqing LiuCollege of Life and Environmental Sciences, Minzu University of China, Beijing, 100081, China.

Funding

National Key Research and Development Program of China 2022YFF1303001
6 · The paper itself

Abstract

Investigating how human disturbance affects the ecosystem service scarcity value (ESSV) is crucial for maintaining ecosystem stability and achieving sustainable development goals (SDGs). This study separately assessed ESSV and human disturbance in Guangxi from 1990 to 2020, revealing their spatiotemporal distribution differences over time. The environmental Kuznets curve (EKC) is used to analyze the interrelationship between the two, with the purpose of filling the gap in current research. The main results are as follows: (1) From 1990 to 2020, ESSV in Guangxi increased significantly and reached its highest value in 2020. Under the four scenarios, ESSV increased significantly in Scenarios 2 and 4. Spatially, high ESSV was mainly distributed in some cities in central, southern, western and northeastern Guangxi. (2) The index of human disturbance in Guangxi continued to increase during the study period, with a high level of human disturbance in the central urban area and a low level of human disturbance in the peripheral areas, which were distributed in a radial pattern. (3) According to the EKC, the relationship between ESSV and human disturbance in Guangxi followed an inverted N-shaped curve. In addition, after 2010, the coupling and coordination level was dominated by "slightly balanced development", and the area of "ESSV significantly lagged" gradually increased. This study provides a new perspective for understanding ESSV and its relationship with human disturbances, and provides an important reference for the sustainable management of ecosystems and the formulation of ecological conservation policies.

Indexed as

Conservation of Natural ResourcesEcosystemSustainable DevelopmentChinaHuman ActivitiesHumansCoupling coordination degree (CCD)Ecosystem service scarcity value (ESSV)Environmental Kuznets curveHuman disturbance

Identifiers

PMID39523422
PMCPMC11551210

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LicenceCC BY-NC-ND
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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.