2020
DOI: 10.3390/ijerph17249292
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Early-Warning Measures for Ecological Security in the Qinghai Alpine Agricultural Area

Abstract: The study area of this paper is the Qinghai alpine agricultural mountain area. An ecological security early-warning model is used to identify the early warning signs of ecosystem destruction, environmental pollution and resource depletion in districts and counties from 2011 to 2018. A combination of qualitative and quantitative early-warning models is used to predict the existence of hidden or sudden advance warnings. The grey (1, 1) model (GM) is used to predict the evolution trend of ecological security warn… Show more

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Cited by 13 publications
(6 citation statements)
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“…It has certain advantages in the expression of ecological processes and spatial visualization of influencing factors. This study mainly uses raster data based on the minimum cumulative resistance model method to evaluate ecological security, extract ecological corridors, and construct an ecological network framework for Tianzhu (Guo et al, 2020). Overall, the research results are more in line with the actual situation of the county.…”
Section: Discussionmentioning
confidence: 77%
“…It has certain advantages in the expression of ecological processes and spatial visualization of influencing factors. This study mainly uses raster data based on the minimum cumulative resistance model method to evaluate ecological security, extract ecological corridors, and construct an ecological network framework for Tianzhu (Guo et al, 2020). Overall, the research results are more in line with the actual situation of the county.…”
Section: Discussionmentioning
confidence: 77%
“…However, frequently studies directly determined the thresholds without adequate explanation. For example, Guo et al (2020) subdivided a province into different counties and then used the maximum and minimum values of factors, such as population density and forest coverage, in each county as the thresholds to normalize the attribute values of other counties. Similarly, Xu et al (2014) selected the maximum values in different years of their study period as the criteria and the normalized values of other years as the proportions of the maximum values.…”
Section: Scoring Factorsmentioning
confidence: 99%
“…This sensitivity leads to greater variability and uncertainty in predicting future climate impacts [30]. What is more, urban areas account for only 0.22% of the province's total land area and are mainly concentrated in river valleys and basins, where multi-level problems such as gully erosion hazards and geological hazards prevail [31]. Precipitation and intensity in Qinghai are unevenly distributed, gradually decreasing from east to west and from south to north [32], exacerbating the region's vulnerability to droughts and floods due to anomalous climatic conditions, resulting in concentrated disaster events.…”
Section: Introductionmentioning
confidence: 99%