Spatiotemporal Variations of Ecosystem Service Indicators and the Driving Factors Under Climate Change in the Qinghai–Tibet Highway Corridor

Abstract

In recent decades, the influence of climate change and human activities on the ecosystem services (ES) in the Qinghai–Tibet Plateau (QTP) has been extensively investigated. However, few studies focus on linear traffic corridor area, which is heavily affected by human activities. Taking the Golmud–Lhasa national highway corridor as a case, this study investigated the land-use and land-cover change (LUCC) and spatiotemporal variations of ES indicators using ecosystem indices of fractional vegetation cover (FVC), leaf area index (LAI), evapotranspiration (ET), and net primary productivity (NPP) from 2000 to 2020. The results indicated that LUCC was faster in the last decade, mostly characterized by the conversion from grassland to unused land. In buffer within 3000 m, the proportions of productive areas represented the increased trends with distance. In terms of ES variations, the improved areas outweighed the degraded areas in terms of FVC, LAI, and NPP from 2000 to 2020, mostly positioned in the Qinghai Province. In addition, FVC, LAI, and NPP peaked at approximately 6000 m over time. With regard to influencing factors, precipitation (20.54%) and temperature (14.19%) both positively influenced the spatiotemporal variation of FVC. Nearly 60% of the area exhibited an increased NPP over time, especially in the Qinghai Province, which could be attributed to the temperature increase over the last two decades. In addition, the distance effects of climatic factors on ES indicators exhibited that the coincident effects almost showed an opposite trend, while the reverse effects showed a similar trend. The findings of this study could provide a reference for the ecological recovery of traffic corridors in alpine fragile areas.

Assessment of eco‐environmental changes along roads in the Qinghai‐Tibetan Plateau based on remote sensing data: A case study of the Sino‐Nepalese Transport Corridor

“…Spatial statistical methods are used to calculate the values of RSEI within each buffer zone. Compared to previous studies which typically subjectively set an impact distance or area (Ma et al, 2021;Miao et al, 2021;Yang et al, 2022), this study, based on establishing the RSEI change curve for each kilometer buffer zone, divides different regions by identifying significant turning points in the curve for subsequent analysis (Huang et al, 2015). Regions are named according to their proximity to the road, labeled as Region (I), Region (II), …, Region (n).…”

“…Luo et al (2018), Song et al (2018), and Ma et al (2021) assessed the impact of the Qinghai‐Tibetan Railway and Highway on vegetation along roads using remote sensing data. Yang et al (2022) used fractional vegetation cover (FVC) and net primary productivity to investigate spatiotemporal changes in ecosystem services along the transport corridor of the Qinghai‐Tibetan Highway. Previous research has mainly concentrated on changes in single elements such as vegetation or soil.…”

“…Current research generally assumes that the impact of transportation infrastructure is limited to 0.1–3 km (Yang et al, 2022; Zhou et al, 2023). However, overlooked is the additional and more profound impact of the mutual promotion between transportation infrastructure and regional socioeconomic development on the eco‐environment of transport corridors.…”