Evidence map›Paper›PMID 36901438›Full record

ArticleInternational journal of environmental research and public health2023

Ecological Risk Assessment of Geological Disasters Based on Probability-Loss Framework: A Case Study of Fujian, China.

Leli Zong, Ming Zhang, Zi Chen, Xiaonan Niu, Guoguang Chen, Jie Zhang, Mo Zhou, Hongying Liu

Full text read
In one paragraph

Article in International journal of environmental research and public health, 2023. 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

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

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

8 authors.

Leli ZongNanjing Center, China Geological Survey, Nanjing 210016, China.ORCID 0000-0002-9460-941X
Ming ZhangNanjing Center, China Geological Survey, Nanjing 210016, China.
Zi ChenNanjing Center, China Geological Survey, Nanjing 210016, China.ORCID 0000-0003-1787-5447
Xiaonan NiuNanjing Center, China Geological Survey, Nanjing 210016, China.
Guoguang ChenNanjing Center, China Geological Survey, Nanjing 210016, China.
Jie ZhangNanjing Center, China Geological Survey, Nanjing 210016, China.
Mo ZhouNanjing Center, China Geological Survey, Nanjing 210016, China.
Hongying LiuNanjing Center, China Geological Survey, Nanjing 210016, China.

Funding

Geological Survey Projects of China DD20190301Geological Survey Projects of China DD20211390National Natural Science Foundation of China 41901310
6 · The paper itself

Abstract

Geological disaster could pose a great threat to human development and ecosystem health. An ecological risk assessment of geological disasters is critical for ecosystem management and prevention of risks. Herein, based on the "probability-loss" theory, a framework integrating the hazard, vulnerability, and potential damage for assessing the ecological risk of geological disasters was proposed and applied to Fujian Province. In the process, a random forest (RF) model was implemented for hazard assessment by integrating multiple factors, and landscape indices were adopted to analyze vulnerability. Meanwhile, ecosystem services and spatial population data were used to characterize the potential damage. Furthermore, the factors and mechanisms that impact the hazard and influence risk were analyzed. The results demonstrate that (1) the regions exhibiting high and very high levels of geological hazard cover an area of 10.72% and 4.59%, respectively, and are predominantly concentrated in the northeast and inland regions, often distributed along river valleys. Normalized difference vegetation index (NDVI), precipitation, elevation, and slope are the most important factors for the hazard. (2) The high ecological risk of the study area shows local clustering and global dispersion. Additionally, human activities have a significant influence on ecological risk. (3) The assessment results based on the RF model have high reliability with a better performance compared with the information quantity model, especially when identifying high-level hazard areas. Our study will improve research on the ecological risk posed by geological disasters and provide effective information for ecological planning and disaster mitigation.

Indexed as

DisastersEcosystemChinaHumansReproducibility of ResultsRisk AssessmentRiversecological risk assessmentFujiangeological disastershazardrandom forest

Identifiers

PMID36901438
PMCPMC10002115

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read20
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.