Spatio-Temporal Assessment of Landscape Ecological Risk and Associated Drivers: A Case Study of the Yellow River Basin in Inner Mongolia

Abstract

The Yellow River Basin in Inner Mongolia (YRBIM) has witnessed major changes in land use/land cover (LULC), which have had an impact on the basin’s ecosystem, in the context of fast economic development and urbanization. This study set out to investigate the ecological risk and key driving forces in the basin as LULC evolves. In order to evaluate the ecological risk of the basin and use a geographic detector model to understand the causes of its spatial heterogeneity, we built a landscape ecological risk index (ERI) model based on changes in LULC from 1990 to 2020. The findings indicate that between 1990 and 2020, LULC modifications led to the transfer of several land types to a small number of land types, all of which have since changed into other land types. With high risk areas primarily located in the Hobq Desert, the Hetao irrigation area, and some portions of the Mu Us Sandy Land, the ecological risk level in the basin is gradually decreasing. Human activities are the main cause of the regional variation of ecological risk in the basin, with topography and climate coming in second and third. The Yellow River Basin’s ecological danger and environmental quality have only received a limited amount of analysis to date. This study is a crucial resource for the development of civilization and ecological restoration in the region.

Landscape Ecological Risk and Drivers of Land-Use Transition under the Perspective of Differences in Topographic Gradient

“…According to the connection between the landscape structure of the regional ecosystem and the ER, with reference to previous research results [48,49], this study selected the landscape disturbance index, landscape fragility index and landscape loss index to construct a LERA model (Table 4) and analyzed the size and change in the landscape ecological risk index (LERI) in the study area. To accurately evaluate the study area, the fishnet method was used to divide the study area into 20 km × 20 km fishnets, for a total of 1266 fishnets, after which the LERI in the center of each fishnet was calculated to represent the LER level of that fishnet.…”

Analysis of the Spatial and Temporal Evolution and Driving Factors of Landscape Ecological Risk in the Four Lakes Basin on the Jianghan Plain, China

“…Given the uncertainties concerning the scale, we will optimize the evaluation and selection cell of ERI. Eventually, there are several socioeconomic factors affecting LER [28], such as population growth, land use policies, economic activities, and urbanization rates. In subsequent research, we will consider these factors in our analysis to gain a greater awareness of the driving mechanisms.…”

“…Against such a backdrop, exploring implications between natural and anthropogenic factors affecting regional LER has received increased attention in recent years [28][29][30]. Conventional methods for studying driving mechanisms, such as correlation analysis and classical regression models, can only describe the effect of factors on the trend in LER, and it is difficult to quantify the extent to which a factor affects the spatial divergence in LER [31].…”

Study on Spatial and Temporal Changes in Landscape Ecological Risks and Indicator Weights: A Case Study of the Bailong River Basin

“…The current study uses the landscape index method as the primary evaluation method for LER. The scales of LER evaluation mainly include basins [13,14], landscape types [15,16], administrative regions [17], world-important heritage sites [10], and roads [18,19]. Different research scales reflect different perspectives on LER evaluation.…”