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吉林省西部湿地土地利用格局变化的多情景模拟
引用本文:刘雁,刘吉平,盛连喜.吉林省西部湿地土地利用格局变化的多情景模拟[J].吉林大学学报(地球科学版),2016,46(3):865-875.
作者姓名:刘雁  刘吉平  盛连喜
作者单位:1. 吉林师范大学旅游与地理科学学院, 吉林 四平 136000; 2. 东北师范大学国家环境保护湿地生态与植被恢复重点实验室, 长春 130117
基金项目:吉林省科技发展计划项目(20100425
摘    要:吉林省西部属于生态脆弱区,湿地作为重要的生态单元,其发展变化对区域生态环境产生重要影响。近年来,由于受到较多的人为干扰,该区域湿地变化极为显著。为了充分发挥湿地生态环境功能,促进区域生态环境改善,以吉林省西部2000-2010年湿地变化数据为基础,基于情景分析法设置了自然变化(情景1)、规划优先(情景2)和生态优先(情景3)三种情景,利用CLUE-S模型对2020年湿地空间格局进行模拟,并从湿地空间分布变化特征和景观抗干扰能力两个方面对不同情景下的湿地格局进行分析评价,旨在了解不同情景下湿地格局的差异性,寻求合理的湿地空间分布格局。结果表明:CLUE-S模型的土地利用预测正确率为84.54%,κ指数为0.83,能够较好地模拟2020年湿地格局变化,特别是对沼泽湿地、水域和建设用地模拟效果较好;不同情景下湿地空间格局特征具有明显的差异性,三种情景下的沼泽湿地的质心均偏向西南,水域的质心均偏向东南,而水田的质心在情景1中偏向东北,在情景2和情景3中偏南,沼泽湿地和水田在情景3比情景1中具有更强的聚集性,而水域恰相反,情景1比情景3中具有更强的聚集性;不同情景下的湿地景观抗干扰能力不同,2010-2020年,情景1中的所有湿地类型的景观干扰指数都逐渐增加,而情景2和情景3中沼泽湿地和水域的景观干扰指数逐渐降低,尤以生态优先情景的下降幅度最大。表明在实施科学的生态建设时,湿地景观具有较强的抗干扰能力。

关 键 词:湿地格局  情景模拟  CLUE-S模型  吉林省西部  
收稿时间:2015-09-23

Scenario Simulation on Changing Pattern of Land Use for Wetland in the West of Jilin Province
Liu Yan,Liu Jiping,Sheng Lianxi.Scenario Simulation on Changing Pattern of Land Use for Wetland in the West of Jilin Province[J].Journal of Jilin Unviersity:Earth Science Edition,2016,46(3):865-875.
Authors:Liu Yan  Liu Jiping  Sheng Lianxi
Institution:1. College of Tourist and Geoscience, Jilin Normal University, Siping 136000, Jilin, China;
2. State Environmental Protection Key Laboratory of Wetland Ecology and Vegetation Restoration, Northeast Normal University, Changchun 130117, China
Abstract:Wetlands have important eco-environmental functions in the west of Jilin Province that located in ecologically fragile zone. In recent years wetlands changed significantly in the west of Jilin Province because of more anthropogenic interference. In order to strengthen wetland functions and improve regional eco-environment, this paper simulated wetland spatial pattern in 2020 by using CLUE-S model, and set up three scenarios of wetland change, including 1) natural development scenario, 2) planning priority scenario and 3) ecological construction priority scenario based on the analysis on wetland change in the west of Jilin Province from 2000 to 2010. This paper also analyzed the characteristics of wetland spatial distribution and evaluated landscape anti-interference abilities in three different scenarios, and made clear the differences among three wetland patterns and explored reasonable wetland patterns. The results showed that average correct rate of predication on all types of land in the study area was 84.54%, with κ index of 0.83, which indicated that CLUE-S model can well simulate land-use changes in 2020, especially for marshes, waters, and residential land. Wetland patterns in three scenarios have obvious differences. The centroids of marshes and waters respectively tended to move to southwest and southeast in three scenarios, while the centroid of paddy fields of scenario 1 moved to northeast and that of scenario 2 and 3 moved to south. Marshes and paddy fields of scenario 3 have a stronger assemblage than those of scenario 1, while waters of scenario 1 have a stronger assemblage than those of scenario 3. From 2010 to 2020, in scenario 1, the landscape interference indexes of all types of wetlands all increased gradually, while in scenario 2 and scenario 3, the landscape interference indexes of marshes and waters all show a drop trend, especially the decrement in scenario 3 is the maximum, which indicated that wetland landscape has a stronger anti-interference ability when ecological construction priority scenario is implemented.
Keywords:wetland pattern  scenario simulation  CLUE-S model  west Jilin Province
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