Juan Li

As a typical ecologically fragile area, the ecological security of the Loess Plateau has been seriously threatened. Ecological security patterns (ESP) have gradually become an effective method for protecting ecological security and supporting the management and sustainable development of ecosystems. Therefore, this study constructed a novel ESP based on ecological “function–structure”, utilizing minimum cumulative resistance (MCR) to identify ecological source areas and corridors. Additionally, time scales were introduced into the ESP, allowing for a comprehensive analysis of the spatiotemporal heterogeneity of ecological security in the Loess Plateau. The study revealed that the number of ecological sources decreased from southeast to northwest, with 27, 41, and 77 sources covering total areas of 4263.810 km², 18,566.034 km², and 113,209.595 km² from 2000 to 2020, respectively. Similarly, the number and complexity of ecological corridors increased over the same time period, with 64, 85, and 105 corridors totaling lengths of 4579.326 km, 6526.996 km, and 7015.174 km, respectively. The expansion of ecological security zones was mainly observed in the southeast part of the Loess Plateau. Overall, the ESP of the Loess Plateau saw an improvement, with the southeastern part showing better ecological security than the northwestern part. These findings hold great significance for regional ecological security evaluations and are crucial for promoting ecological management and healthy development in the Loess Plateau.

The Qinling Mountains represent the dividing line of the natural landscape of north-south in China. The prediction on vegetation coverage is important for protecting the ecological environment of the Qinling Mountains. In this paper, the data accuracy and reliability of three vegetation index data (GIMMS NDVI, SPOT NDVI, and MODIS NDVI) were compared at first. SPOT, NDVI, and MODIS NDVI were used for calculating the vegetation coverage in the Qinling Mountains. Based on the CA–Markov model, the vegetation coverage grades in 2008, 2010, and 2013 were used to simulate the vegetation coverage grade in 2025. The results show that the grades of vegetation coverage of the Qinling Mountains calculated by SPOT, NDVI, and MODIS NDVI are highly similar. According to the prediction results, the grade of vegetation coverage in the Qinling Mountains has a rising trend under the guidance of the policy, particularly in urban areas. Most of the vegetation coverage transit from low vegetation coverage to middle and low vegetation coverage. The grades of the vegetation coverage, which were predicted by the CA–Markov model using SPOT, NDVI, and MODI NDVI, are consistent in spatial distribution and temporal variation.