[Identification of Driving Mechanisms for the Evolution of Ecological Security Patterns and Multi-scenario Simulation Prediction in Xi'an].

Abstract

The ecological security pattern （ESP） is a crucial foundation for regional ecological protection and spatial planning. Existing research mostly focuses on the identification of driving factors of the ESP， emphasizing its evolution mechanism， but there is insufficient discussion on how key factors affect the future pattern evolution and their application value in spatial planning. The study proposes a research idea of shifting from "explaining the past" to "predicting the future." Based on a three-dimensional identification framework of "ecosystem service importance-ecological sensitivity-landscape connectivity，" the ESP of Xi'an from 2000 to 2020 are constructed. The key driving factors of the evolution of the ESP are identified by using a geographical detector model， ordinary least squares （OLS） regression， and geographically weighted regression （GWR） in a progressive "qualitative-quantitative-spatial" analytical sequence. These key driving factors were subsequently integrated into the FLUS model to simulate the future land use patterns and assessed the ecological security response characteristics under three scenarios： business as usual （BAU）， priority economic development （PED）， and priority ecological protection （PEP）. The results show that： ① The spatial pattern of ecological source areas in Xi'an were relatively stable， with fragmented distribution in the northern areas due to urbanization disturbance， while the remaining distribution was relatively concentrated in the southern mountainous regions. The number and length of ecological corridors both decreased， mainly distributed in the central plain and eastern mountainous areas. ② There were six influencing factors that significantly affected the formation of ecological sources， among which elevation， terrain roughness， and slope played a promoting role. Land use type， terrain roughness， and distance to residential areas were the three main driving factors of resistance surface formation， all exhibiting significant positive effects， with spatial effects mainly concentrated in the southern mountainous areas. ③ The scenario simulation results showed that there were significant differences in the land use pattern of Xi'an under different scenarios. Under the PEP scenario， the forest area increased； the landscape diversity， connectivity， and aggregation degree were optimal； the landscape disturbance risk was the lowest； and the ecological security response effect was the best. The study identified the key driving factors of the evolution of Xi'an's ESP and incorporated them into the FLUS model to enhance the scientific validity of the prediction results， providing more targeted decision-making support for ecological restoration and sustainable spatial governance in Xi'an.