基于FLUS-Markov模型的多情景景观生态风险评价与预测——以南疆克州为例
收稿日期: 2021-06-03
修回日期: 2021-07-24
网络出版日期: 2021-11-29
基金资助
国家自然科学基金项目(31760151)
FLUS-Markov model-based multiscenario evaluation and prediction of the landscape ecological risk in Kezhou, South Xinjiang
Received date: 2021-06-03
Revised date: 2021-07-24
Online published: 2021-11-29
以新疆克孜勒苏柯尔克孜自治州（克州）为例,基于2005—2015年土地利用空间格局变化,利用FLUS-Markov复合模型预测2025年土地利用情况,采用Criteria Importance Though Intercrieria Correlation（CRITIC）权重法构建自然增长和生态保护情景下的景观生态风险指数,并采用自然断点法由低到高划分为5个等级（Risk Ⅰ、Risk Ⅱ、Risk Ⅲ、Risk Ⅳ和Risk Ⅴ）,以风险指数质心和标准差椭圆评价不同年份、多情景下景观生态风险时空格局和变化特征,探究影响其演化特征的驱动因素。结果表明：（1） 在自然增长情景下,耕地、水域、建设用地面积不断增加,林地、草地、荒漠和裸地面积逐渐减小;生态保护情景下,草地相比于自然增长情景增加了51 km2。（2） 2005—2025年,克州景观生态风险整体呈现减小的趋势,生态保护情景相比于自然增长情景下的Risk Ⅰ、Risk Ⅱ和Risk Ⅳ面积分别增加34 km2、1240 km2和66 km2,Risk Ⅲ和Risk Ⅴ面积分别减少695 km2和645 km2。（3） 2005—2025年,自然增长情景下克州Risk Ⅰ、Risk Ⅱ、Risk Ⅳ和Risk Ⅴ呈扩散分布状态,Risk Ⅲ呈现紧凑收缩状态。（4） 影响景观生态风险演化的主要因素是地形气候因子（解释力85%以上）,其次人口（解释力59%以上）也是重要的驱动因子,GDP对景观生态风险变化的贡献减小。
金梦婷,徐丽萍,徐权 . 基于FLUS-Markov模型的多情景景观生态风险评价与预测——以南疆克州为例[J]. 干旱区研究, 2021 , 38(6) : 1793 -1804 . DOI: 10.13866/j.azr.2021.06.31
In this study, the Kirgiz Autonomous Prefecture of Kizilsu in Xinjiang was set as an example to use an FLUS-Markov composite model based on changes in the land use spatial pattern from 2005 to 2015 for predicting the land use situation in 2025. The criteria importance though intercriteria correlation weight method was applied to construct the landscape ecological risk index under the two scenarios of natural growth and ecological protection. The natural risk index was also determined. The breakpoint method was divided into five levels (from low to high): risks I-V. Risk index centroid and standard deviation ellipse are used to evaluate the spatiotemporal pattern and changes in the characteristics of landscape ecological risk in different years and multiscenarios and to explore the driving factors affecting its evolution characteristics. Results show that (1) the area covered by cultivated land, water area, and construction land is increasing under a natural growth scenario, whereas the area spanning woodland, grassland, desert, and bare land is gradually decreasing. The grassland area under the ecological protection scenario increases by 51 km2 compared with that under the natural growth scenario. (2) From 2005 to 2025, the overall landscape ecological risk of Kezhou decreased. Compared with the natural growth scenario, the areas under risks I, II, and IV in the ecological protection scenario increased by 34 km2, 1240 km2, and 66 km2, respectively, and the areas under risks III and V decreased by 695 and 645 km2, respectively. (3) From 2005 to 2025, risks I, II, IV, and V in Kezhou would be in a diffused distribution state, and risk III would be in a compact contraction state. (4) The main factors affecting the evolution of landscape ecological risk are topographic and climatic factors (interpretation over 85%). Another important driving factor is population (interpretation over 59%). The contribution of GDP to the changes in the landscape ecological risk is reduced.
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