下辽河平原景观格局脆弱性及空间关联格局

以东北三省开发强度最大的辽河中下游地区——下辽河平原为研究对象,根据景观格局脆弱性的概念及内涵,通过景观敏感度指数和景观适应度指数构建景观格局脆弱度指数,并借助地统计学和空间自相关模型分析的理论方法,对下辽河平原景观格局脆弱度的空间分布特征、变异规律以及空间关联格局进行探讨,结果表明:①1989—2010年下辽河平原景观格局脆弱度总体上呈递减趋势;②1989—2010年研究区景观格局脆弱度Moran's I表现为一定程度的正相关,且相关程度略微呈下降趋势;③1989—2010年研究区景观格局脆弱度局部空间自相关和显著性水平均发生了明显的变化;④研究区各时期景观格局脆弱度的空间相关性是受结构性因素和非结构性因素共同影响,C0所占的比例在3a期间有逐步上升趋势,表明非结构性因素对景观格局脆弱度演变的影响程度不断加深,但是结构性因素(地形地貌、水文、土壤植被类型等)仍然对本区景观格局脆弱度的空间分布起决定性作用。

Evaluation of the landscape patterns vulnerability and analysis of spatial correlation patterns in the lower reaches of Liaohe River Plain

Landscape patterns embody both landscape heterogeneity and the accumulation of all kinds of ecological process in different scales. Landscape patterns determine the distribution of resources and the environment, which has a profound impact on anti-interference ability, recoverability, system stability and biodiversity. However, since the 21st century, soil desertification, biodiversity decrease and other issues have appeared in many countries and regions in the world, economic losses has been increased gradually.Located in the middle and lower reaches of Liaohe River Basin-the lower reaches of Liaohe River Plain, it is one of the strongest areas of human development in northeastern part of China. It has an enormous population and a long history of land development, and the region is one of the important commodity grain bases in Liaoning province and northeast. In recent years, with the rapid development of regional social economy, the landscape patterns have been dramatically changed in the lower reaches of Liaohe River Plain, even the unreasonable development has leaded to accelerate soil erosion. Therefore, for reasonable development and landscape patterns optimization management, the research of landscape patterns vulnerability becomes important and urgent in the lower reaches of Liaohe River Plain.In this study, on the basis of understanding the concept and connotation of landscape patterns vulnerability, our study first attempts to construct landscape vulnerability index through landscape sensitivity index and landscape adaptability index. And at last our study explores the influential factors of the variation of the landscape vulnerability by using geo-statistical method combined with Moran's I index. The results of our study show that: (1) The landscape vulnerability degree gradually declined in the study tine, the area ratio and space structure in the classification areas changed significantly. (2) Moran' s I shows positive spatial autocorrelation, and the correlation drops slightly. (3)The spatial autocorrelation analysis we have done reveals that the landscape vulnerability has a high degree spatial correlation, and both the local spatial autocorrelation and significance level obviously changed during the period of 3 years. (4) Through the analysis of theoretical model, the percentage of nugget gradually increased in 1989, 2001 and 2010, and then it indicates that the non-structural factors deeply impact on the evolution of the vulnerability, however, structural factors (the landform, hydrology, soil, vegetation type, etc.) in this area still play a decisive role. Range indicates that landscape vulnerability of the study area has a high degree spatial correlation in 2.5 km sampling spacing.