Evidence map›Paper›PMID 39379526›Full record

ArticleScientific reports2024

Spatiotemporal evolution and driving factors of ecosystem service value in the Upper Minjiang River of China.

Linsen Duan, Suhua Yang, Mingshun Xiang, Wenheng Li, Jianhua Li

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 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

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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

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.

Linsen DuanCollege of Geography and Planning, Chengdu University of Technology, Chengdu, 610059, China.
Suhua YangCollege of Geography and Planning, Chengdu University of Technology, Chengdu, 610059, China.
Mingshun XiangCollege of Geography and Planning, Chengdu University of Technology, Chengdu, 610059, China. xiangmingshun19@cdut.edu.cn.
Wenheng Li *College of Geography and Planning, Chengdu University of Technology, Chengdu, 610059, China.
Jianhua Li *College of Geography and Planning, Chengdu University of Technology, Chengdu, 610059, China.

Funding

National Natural Science Foundation of China 42071232Natural Science Foundation of Sichuan Province 2022NSFSC1096
6 · The paper itself

Abstract

The stability of ecosystems in high mountain canyon areas is poor, and the interaction between humans and the land is complex, making these ecosystems more vulnerable to destruction. Quantitatively assessing the ecosystem service value (ESV) in high mountain canyon areas and revealing its spatiotemporal evolution patterns and driving factors play a crucial role in the construction of regional ecological barriers and the assurance of ecological security. This study focuses on the Upper Minjiang River as the research area, using the InVEST model and the Equivalent Factor Method to estimate ESV. This combination aims to address the inadequacy of the Equivalent Factor Method in reflecting the variability of ESV across different regions, and the sensitivity of the InVEST model to data changes that results in insufficient accuracy of ESV assessments. By harnessing spatial au-tocorrelation and the geodetector method, we unravel the spatiotemporal evolution characteristics and driving factors of ESV. The results show that: (1) From 2000 to 2020, the ESVs estimated by the two estimations increased by 31.28% and 22.47%, respectively, both indicating that the eco-environment quality of the upper Minjiang River has been continuously improved. (2) When Moran's I was greater than 0.5 (p < 0.05), the spatial clustering of "High-High" and "Low-Low" ESV was obvious. It is clear that the ESV varies geographically. High values are primarily found in the study area's center and southern regions, as well as on both banks of the Minjiang River, whereas low values are more common in the region's northern region. (3) Slope and human activity intensity (HAI) are the principal contributors to the spatial differentiation of the ESV, more than 60% of the interaction types between the two factors were classified as dual-factor enhancement. The synergistic reinforcing effects of HAI, slope, elevation, and temperature collectively shape the shifts in ESV spatial distribution. This study offers a novel evaluative lens on the ESV of the Upper Minjiang River area, supplying a sturdy data support for crafting specific ecological preservation and rejuvenation strategies in the coming years.

Indexed as

Ecosystem Service ValueEquivalent factor methodGeodetectorInVEST Model

Identifiers

PMID39379526
PMCPMC11461897

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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.