Landscape fragmentation associated with the Qingzang Highway and its influencing factors—A comparison study on road sections and buffers

• Published in: Geography and Sustainability
• Main Authors: Yi Miao, Teqi Dai, Xingdou Yang, Jinping Song
• Format: Article in Journal/Newspaper
• Language: English
• Published: Elsevier 2021
• Subjects: Qingzang Highway; Landscape fragmentation; Road section; Buffer; Geodetector; Geography (General); G1-922; Environmental sciences; GE1-350; permafrost
• Online Access: https://doi.org/10.1016/j.geosus.2021.03.001; https://doaj.org/article/fcfb4bc623194dc4a0096eddc1058da3

Many studies have examined the effect of roads on landscape fragmentation. Yet they rarely considered local characteristics of the road and road buffer widths. Therefore, this study that took place in the Qingzang Highway (QH) examined the variations in road buffers and road sections of landscape fragmentation. The QH was divided into 32 sections with 23 buffer areas. Based on the indicators of landscape fragmentation from 1980 to 2018, we found significant spatial heterogeneity between sections and buffers. Generally, landscape fragmentation decreased with increasing buffer distance to the QH. For different sections, the coefficients of variation between buffers were rather high and significantly different. Therefore, fixed-width buffers may overestimate or underestimate the spatial scope and influence intensity of a road. The impacts of road sections around provincial capitals, prefecture-level cities and main counties on landscape fragmentation were relatively extensive and formed clusters of highly fragmented areas. Geodetector results indicated that natural and anthropogenic factors, such as altitude, climate, distance to major settlements and socioeconomic conditions, could well explain the spatiotemporal characteristics of landscape fragmentation. Altitude, precipitation and the distance to major settlements had higher explanatory power for landscape fragmentation in permafrost regions, whereas slope and socioeconomic condition had higher explanatory power for non-permafrost regions in Xizang Autonomous Region.