Evidence map›Paper›PMID 40051850›Full record

ArticleHeliyon2025

Social vulnerability: A driving force in amplifying the overall vulnerability of protected areas to natural hazards.

Saied Pirasteh, Davood Mafi-Gholami, Huxiong Li, Tao Wang, Eric K Zenner, Akram Nouri-Kamari, Tim G Frazier, Saman Ghaffarian

Abstract read
In one paragraph

Article in Heliyon, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Saied PirastehInstitute of Artificial Intelligence, Shaoxing University, 508 West Huancheng Road, Yuecheng District, Shaoxing,Zhejiang Province, 312000, China.
Davood Mafi-GholamiDepartment of Forest Sciences, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord, 8818634141, Iran.
Huxiong LiInstitute of Artificial Intelligence, Shaoxing University, 508 West Huancheng Road, Yuecheng District, Shaoxing,Zhejiang Province, 312000, China.
Tao WangInstitute of Artificial Intelligence, Shaoxing University, 508 West Huancheng Road, Yuecheng District, Shaoxing,Zhejiang Province, 312000, China.
Eric K ZennerDepartment of Ecosystem Science and Management, The Pennsylvania State University, Forest Resources Building, University Park, PA, 16802, USA.
Akram Nouri-KamariDepartment of Geography Education, Farhangian University, Tehran, Iran.
Tim G FrazierEmergency and Disaster Management Program, School of Continuing Studies (SCS), Georgetown University, Washington, DC, USA.
Saman GhaffarianInstitute for Risk and Disaster Reduction, University College London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Incorporating social vulnerability (SoV) into vulnerability assessments for protected areas provides critical insights for enhancing the resilience and adaptability of these regions to environmental hazards. This study aimed to develop and apply an integrated social-ecological vulnerability assessment framework for a forest-protected area, focusing on scales relevant to management decisions. We collected data from 70 villages within the protected area through structured surveys, interviews, and reviews of secondary socio-economic and environmental datasets. A total of 24 socio-economic and environmental indicators were selected, based on expert consultation and literature review, to quantify the indices of exposure, sensitivity, adaptive capacity, and SoV. These indicators were weighted using the Fuzzy Analytical Hierarchy Process (FAHP) to ensure objective and expert-driven prioritization. Subsequently, the SoV index, derived from socio-economic metrics, was incorporated as a key variable in the exposure assessment. This integration involved 18 additional ecological indicators measured across a spatial grid, enabling a fine-scale analysis of the protected area's exposure, sensitivity, adaptive capacity, and overall vulnerability. Integrating social and ecological dimensions allowed for a spatially explicit evaluation of vulnerability at the grid-cell level, providing granular insights for localized management interventions. The results revealed that SoV significantly influenced the levels of exposure and overall vulnerability across the study area. High SoV values corresponded to areas with elevated overall vulnerability, emphasizing the interplay between social conditions and ecological risks. To enhance resilience in the medium and long term, the study recommends shifting investments toward active community engagement in conservation planning, increasing environmental awareness through education programs, and improving the socio-economic well-being of local communities to mitigate social vulnerability. This approach highlights the importance of integrating social dimensions into ecological assessments to inform more equitable and effective management strategies.

Indexed as

Environmental hazard resilienceFAHPIntegrated social-ecological framework and vulnerability assessmentProtected area managementSpatial pattern

Identifiers

PMID40051850
PMCPMC11883368

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.