Landscape Ecological Risk Assessment under Multiple Indicators

Li, Xupu; Li, Shuangshuang; Zhang, Yufeng; O’Connor, Patrick J.; Zhang, Liwei; Jun-ping, Yan

doi:10.3390/land10070739

Cited by 37 publications

(20 citation statements)

References 49 publications

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“…The geographical detector method is a set of statistical methods that detect spatial differentiation, while also revealing driving forces behind it [47]. The factor detection method can be used to analyze the magnitude of the explanatory power of each driver on the spatial and temporal variations in ecological risk of the landscape [48] and is calculated using the following formula:…”

Section: Geographical Detector Methodsmentioning

confidence: 99%

Landscape Pattern and Ecological Risk Assessment in Guangxi Based on Land Use Change

Yang

Chen

Lan

et al. 2022

IJERPH

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Due to ecological environmental fragility and soil erosion in Guangxi, studies of landscape patterns and associated ecological risks are needed to guide sustainable land development and ecologically sensitive land management. This study assesses dynamic spatial and temporal change patterns in land use and ecological risks based on 30 m land-use data, analyzes spatial correlations with ecological risks, and explores natural and socio-economic factor impacts on ecological risks. The results reveal: (1) A rapid and sizeable construction land increase in Guangxi from 2000 to 2018 associated mainly with loss of woodland and grassland. (2) Guangxi had the highest number of arable land patches from 2000 to 2018, and the distribution tended to be fragmented; moreover, the construction land gradually expanded outward from concentrated areas to form larger aggregates with increasing internal stability each year. (3) Guangxi ecological risk levels were low, low–medium, and medium, with significantly different spatial distributions observed for areas possessing different ecological risk levels. Regional ecological risk gradually decreased from the middle Guangxi regions to the surrounding areas and was positively correlated with spatial distribution. (4) Socio-economic factor impacts on ecological risk exceeded natural factor impacts. These results provide guidance toward achieving ecologically sensitive regional land-use management and ecological risk reduction and control, it can also provide a reference for ecological risk research in other similar regions in the world.

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Section: Geographical Detector Methodsmentioning

confidence: 99%

Landscape Pattern and Ecological Risk Assessment in Guangxi Based on Land Use Change

Yang

Chen

Lan

et al. 2022

IJERPH

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“…In general, a more diversified landscape pattern could display increased ability to deal with external interference. Therefore, it was assumed that the higher the SHEI, the lower the ecological risk [23,29]. Overall, a combined assessment with the CONTAG and SHEI indices could reflect the complicated relationships between landscape patterns and the ecological risk to a certain extent.…”

Section: Construction Of Landscape Ecological Risk Assessment Index Systemmentioning

confidence: 99%

“…Zhang et al [22] constructed an index system from three aspects, nature, society and landscape pattern, to assess the landscape ecological risk in a watershed area. Li et al [23] constructed a "Potential-connectedness-resilience" framework and assessed the landscape ecological risk based on the analytic hierarchy process (AHP) method. The involvement of new aspects and factors has extended the dimension of landscape ecological risk, yet few studies have focused on neighborhood factors when evaluating landscape ecological risk.…”

Section: Introductionmentioning

confidence: 99%

The Construction of Ecological Security Patterns in Coastal Areas Based on Landscape Ecological Risk Assessment—A Case Study of Jiaodong Peninsula, China

Yan

Zhang

et al. 2021

IJERPH

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Increasing land utilization, population aggregation and strong land–sea interaction make coastal areas an ecologically fragile environment. The construction of an ecological security pattern is important for maintaining the function of the coastal ecosystem. This paper takes Jiaodong Peninsula in China, a hilly coastal area, as an example for evaluating landscape ecological risk within a comprehensive framework of “nature–neighborhood–landscape”, based on spatial principal component analysis, and it constructs the ecological security pattern based on the minimum cumulative resistance model (MCR). The results showed that the overall level of ecological risk in the study area was medium. The connectivity between the areas of low landscape ecological risk was relatively low, and the high risk areas were concentrated in the north of the Peninsula. A total of 11 key ecological corridors of three types (water, green space and road corridors) and 105 potential corridors were constructed. According to the ecological network pattern, landscape ecological optimization suggestions were proposed: key corridors in the north and south of Jiaodong Peninsula should be connected; urban development should consider current ecological sources and corridors to prevent landscape fragmentation; and the ecological roles of potential corridors should be strengthened. This paper can provide a theoretical and practical basis for ecological planning and urban master planning in coastal areas in the future.

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“…The management of regional eco-environmental risks is the key to promoting regional economic sustainability from the macro level. Therefore, accurate evaluation of the evolutionary trends of regional ecological risk in the future is of high importance [1]. The Chengdu-Chongqing Economic Zone (the C-C E Zone) is the economic core of Southwest China, playing an important role in both economic development and ecological protection [2].…”

Section: Introductionmentioning

confidence: 99%

Impact of Future Development Scenario Selection on Landscape Ecological Risk in the Chengdu-Chongqing Economic Zone

Zhu

Zhang

et al. 2022

Land

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The management of regional eco-environmental risks is the key to promoting regional economic sustainability from the macro level, and accurate evaluation of the evolutionary trends of regional ecological risk in the future is of high importance. In order to clearly identify the possible impact of future development scenario selection for the Chengdu-Chongqing Economic Zone (C-C E Zone) on the evolution of landscape ecological risk (LER), we introduced the Patch-generating Land Use Simulation (PLUS) model to simulate land use data for the C-C E Zone from 2030 to 2050 for two scenarios: natural development (ND) and ecological protection (EP). Based on the ecological grid and landscape ecological risk index (LERI) model, the landscape ecological risk (LER) evolutionary trends seen in the C-C E Zone from 2000 to 2050 were analyzed and identified. The results showed that: (1) The PLUS model can obtain high-precision simulation results in the C-C E Zone. In the future, the currently increasing rate of land being used for construction will be reduced, the declining rates of forest and cultivated land area will also be reduced, and the amount of land being used for various purposes will remain stable going into the future. (2) This study found that the optimal size of the ecological grid in the LERI calculation of the mountainous area was 4 × 4 km. Additionally, the mean values of the LERI in 2030, 2040, and 2050 were 0.1612, 0.1628, and 0.1636 for ND and 0.1612, 0.1618, and 0.1620 for EP. (3) The hot spot analysis results showed that an area of about 49,700 km2 in the C-C E Zone from 2000 to 2050 belongs to high agglomeration of LER. (4) Since 2010, the proportions of high and extremely high risk levels have continued to increase, but under the EP scenario, the high and extremely high risk levels in 2040 and 2050 decreased from 14.36% and 6.66% to 14.33% and 6.43%. Regional analysis showed that the high and extremely high risk levels in most regions increased over 2010–2050. (5) Under the ND scenario, the proportions of grids with decreased, unchanged, and increased risk levels were 15.13%, 81.48%, and 3.39% for 2000–2010 and 0.54%, 94.75%, and 4.71% for 2040–2050. These trends indicated that the proportion of grids with changed risk levels gradually decreased going into the future. This study analyzed the evolutionary trends of LER at the C-C E Zone for the ND and EP scenario. On the whole, the LER for the C-C E Zone showed an upward trend, and the EP scenario was conducive to reducing the risk. These research results can serve as a valuable data reference set for regional landscape optimization and risk prevention and control.

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Landscape Ecological Risk Assessment under Multiple Indicators

Cited by 37 publications

References 49 publications

Landscape Pattern and Ecological Risk Assessment in Guangxi Based on Land Use Change

Landscape Pattern and Ecological Risk Assessment in Guangxi Based on Land Use Change

The Construction of Ecological Security Patterns in Coastal Areas Based on Landscape Ecological Risk Assessment—A Case Study of Jiaodong Peninsula, China

Impact of Future Development Scenario Selection on Landscape Ecological Risk in the Chengdu-Chongqing Economic Zone

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