磴口县生态网络多情景模拟研究

复杂生态网络是近年来区域生态环境可持续研究的热点。以2016年磴口县的遥感影像数据、DEM数据等为研究素材,提出生态库伦力的概念并基于力导向算法构建生态网络多情景模拟模型,结合最小累积阻力面模型设置多个情景模式对磴口县现状生态网络的演化进行研究。研究结果表明:随着(1.0,0)模式到(0,1.0)模式的转换,生态源地斑块栅格逐渐消失,骨架廊道逐渐出现断裂;在(0,1.0)模式下生态网络遭到极大破坏,现状条件下若进行大规模土地经济开发会对生态网络造成极大的破坏;但在(0.9,0.1)模式下,虽沙漠边缘处出现破坏,但是在样圆内部生态网络却出现扩张,在现有自然资源的约束下,磴口县仍有发展经济的空间,但空间不大。本研究所提出的多情景模拟模型适用于生态网络的演化分析。

Multi-scenario Simulation of Ecological Networks in Dengkou County

Complex ecological network is a hotspot in the study of regional eco-environmental sustainability in recent years. The remote sensing image in 2016, DEM data and so on in Dengkou County were used as research material. The concept of ecological Coulomb force was proposed and based on the force-directed algorithm, a multi-scenario simulation model of ecological network was constructed. Furthermore, combining the minimum cumulative resistance surface model, totally 11 scenarios were set up to study the evolution of the present ecological network. The results were shown as follows: based on the current situation of ecological protection mode, the cumulative ecological resistance surface showed that the wolf mountain piedmont and the northeastern margin of the Ulan Buh Desert had great ecological resistance. In contrast, there were significantly more areas with large cumulative ecological resistance values under the economic development model. With (1.0, 0) to (0, 1.0) model conversion, ecological source grid patches gradually disappeared, the skeleton corridor was gradually broken. In the (0, 1.0) mode, the ecological network had been greatly destroyed. Under the present condition, large-scale land economic development would cause great damage to the ecological network. However, in the (0.9, 0.1) mode, although the destruction occurred on the edge of the desert, the ecological network inside the sample circle was expanded. Under the existing natural resources, there was still room for economic development in Dengkou County, but the space was limited. The multi-scenario simulation model proposed was suitable for the evolution analysis of ecological networks.