Evaluation of Ecological Sensitivity and Spatial Correlation Analysis of Landscape Patterns in Sanjiangyuan National Park

Author:

Liu Tianshu1,Peng Xiangbin2,Li Junjie2

Affiliation:

1. School of Forestry and Landscape Architecture, Anhui Agricultural University, Hefei 230036, China

2. College of Art and Design, Nanjing Forestry University, Nanjing 210037, China

Abstract

The Sanjiangyuan region, situated on the Qinghai–Tibetan Plateau, constitutes an exceptionally delicate ecological environment. Alterations in the region’s ecological landscape stem not only from natural factors but also from significant anthropogenic influences, exerting a notable impact on the sustainable economic and social development of the region’s middle and lower reaches. Consequently, investigating changes in the landscape pattern of Sanjiangyuan National Park holds paramount importance for comprehending the formation mechanism of spatial landscape distribution in the area. This study analyzes the ecological sensitivity and landscape pattern of Sanjiangyuan National Park in Qinghai Province, China, utilizing ArcGIS 10.8 and Fragstats 4.2. Employing the bivariate spatial autocorrelation analysis method, the research uncovers the spatial distribution characteristics between ecological sensitivity and landscape pattern, along with their aggregated change traits. The findings reveal that ecological sensitivity areas within the park encompass varying degrees, ranging from extremely sensitive to insensitive. The area of moderately sensitive zones in the Yellow River source region is 7279.67 km2 (39.17%), whereas the corresponding area in the Yangtze River source region is 32,572.34 km2 (36.30%). The eastern and northern parts of the Sanjiangyuan National Park exhibit significant landscape fragmentation. Ecological sensitivity varies markedly across different regions, with the southern and some northern areas showing higher sensitivity. In the Lancang River source park and the southern part of the Yellow River source park, the Largest Patch Index (LPI) and Ecological Sensitivity Index exhibit a high–high (HH) clustering pattern, indicating strong ecological connectivity in these areas. These regions also feature high Total Edge (TE), Number of Patches (NP), Patch Density (PD), and Edge Density (ED), indicating a complex landscape structure and abundant habitat edge areas. The study recommends restoring ecological connectivity in highly fragmented areas and implementing strict protection measures in sensitive regions to maintain ecosystem health and biodiversity. These findings provide a foundation for developing targeted ecological protection measures to enhance ecosystem health and biodiversity conservation in the area. This research aligns with several Sustainable Development Goals (SDGs), including Climate Action, Life on Land, and Clean Water and Sanitation, by promoting sustainable ecosystem management and biodiversity conservation.

Publisher

MDPI AG

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