Dynamic Ecological Risk Assessment and Management of Land Use in the Middle Reaches of the Heihe River Based on Landscape Patterns and Spatial Statistics

Abstract

Land use profoundly changes the terrestrial ecosystem and landscape patterns, and these changes reveal the extent and scope of the ecological influence of land use on the terrestrial ecosystem. The study area selected for this research was the middle reaches of the Heihe River. Based on land use data (1986, 2000, and 2014), we proposed an ecological risk index of land use by combining a landscape disturbance index with a landscape fragility index. An exponential model was selected to perform kriging interpolation, as well as spatial autocorrelations and semivariance analyses which could reveal the spatial aggregation patterns. The results indicated that the ecological risk of the middle reaches of the Heihe River was generally high, and higher in the northwest. The high values of the ecological risk index (ERI) tended to decrease, and the low ERI values tended to increase. Positive spatial autocorrelations and a prominent scale-dependence were observed among the ERI values. The main hot areas with High-High local autocorrelations were located in the north, and the cold areas with low-low local autocorrelations were primarily located in the middle corridor plain and Qilian Mountains. From 1986 to 2014, low and relatively low ecological risk areas decreased while relatively high risk areas expanded. A middle level of ecological risk was observed in Ganzhou and Minle counties. Shandan County presented a serious polarization, with high ecological risk areas observed in the north and low ecological risk areas observed in the southern Shandan horse farm. In order to lower the eco-risk and achieve the sustainability of land use, these results suggest policies to strictly control the oasis expansion and the occupation of farmland for urbanization. Some inefficient farmland should transform into grassland in appropriate cases.

Spatial–Temporal Evolution and Correlation Analysis of Ecosystem Service Value and Landscape Ecological Risk in Wuhu City

“…By using ArcGIS 10.2 software and considering relevant studies [24,25] and computing efficiency, a 5 km × 5 km grid was used to conduct grid resampling of Wuhu city's landscape types, and 304 evaluation units were formed. Based on the evaluation unit, the ecosystem service value and landscape ecological risk index were calculated and assigned to the centre point of the evaluation unit; then Kriging interpolation was carried out to analyze the spatial pattern distribution characteristics.…”

“…where ERI k is the ecological risk value of sampling plot k; A ki is the area of type i in sampling plot k, and A k is the area of sampling plot k; R i is the landscape loss index (measuring the ecosystem loss caused by external disturbance [25]); m is the number of landscape types in the sampling plot; S i is the landscape disturbance index; and F i is the landscape vulnerability index. The calculation formulas and ecological significance of each parameter are shown in Table 2.…”

A Quantitative Assessment of Comprehensive Ecological Risk for a Loess Erosion Gully: A Case Study of Dujiashi Gully, Northern Shaanxi Province, China

“…The Earth has entered a new geological time period, known as the "Anthropocene" [1]. During this time interval, changes in the Earth's surface system have been profoundly affected by human social-economic interactions [2]. Global landscape patterns and ecosystems have changed under the background of land use change, which has resulted in many ecological risks caused by natural hazards and human activities.…”

Assessment of Downscaling Planetary Boundaries to Semi-Arid Ecosystems with a Local Perception: A Case Study in the Middle Reaches of Heihe River

“…Two primary solutions had been proposed to mitigate the impact. The first was limiting water use through water policy since water was the main driver for land-system change [1,2,5,36]. This was achieved by allocating a reasonable water quota and introducing additional water costs to the farmers.…”