Ecological Sensitivity Assessment of the Southeastern Qinghai-Tibet Plateau using GIS and AHP—A Case Study of the Nyingchi Region

Wang, Yongxiang; Jiaxuan, Wei; Zhou, Juan; Jiajia, Yang; Xu, Yuanyuan; Chen, Yuxin; Jiangcheng, Hao; Cheng, Wuxue

doi:10.5814/j.issn.1674-764x.2023.01.015

Cited by 3 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Classifying Nyingchi based on thermal levels, drywet types, and geomorphic distinctions yields categories such as mountainous tropical, subtropical humid canyon agroforestry climate region; plateau temperate humid, semihumid, semi-arid river valley basin agroforestry climate region; eastern temperate, subfrigid humid high-altitude forest climate region; and central sub-frigid, frigid semi-humid, humid high-altitude meadow desert climate region. This classification results in five primary climate regions and four sub-regions [34].…”

Section: Overview Of the Study Areamentioning

confidence: 99%

Temporal and Spatial Dynamics in Carbon Utilization Efficiency and Driving Mechanisms in Southeast Tibet from 2012 to 2022

Shi,

Lu,

et al. 2024

Forests

View full text Add to dashboard Cite

Carbon utilization efficiency (CUE) in terrestrial ecosystems stands as a pivotal metric for assessing ecosystem functionality. Investigating the spatiotemporal dynamics of regional CUE within the context of global climate change not only provides a theoretical foundation for understanding terrestrial carbon cycling but also furnishes essential data support for formulating sustainable management strategies at a regional scale. This study focuses on the southeastern region of Tibet. Utilizing monthly and yearly MOD17A2HGF as primary sources, we employ Thiel–Sen estimation and Mann–Kendall trend analysis to scrutinize the spatiotemporal dynamics of CUE. Systematic analysis of the stability of CUE spatiotemporal changes in the Southeast Tibet region is conducted using the coefficient of variation analysis. The Hurst model is then applied to prognosticate future CUE changes in Southeast Tibet. Additionally, a comprehensive analysis of CUE is undertaken by integrating meteorological data and land-use data. The findings reveal the following: (1) At the monthly scale, regional CUE exhibits discernible variations synchronized with the growth season, with different vegetation types displaying diverse fluctuation patterns. The high-altitude forest area manifests the least annual CUE fluctuations, while evergreen needleleaf forests and evergreen broadleaf forests demonstrate larger variations. At the yearly scale, CUE reveals a non-significant upward trend overall, but there is an augmented fluctuation observed from 2019 to 2022. (2) CUE in Southeast Tibet demonstrates sensitivity to temperature and precipitation variations, with temperature exhibiting a more pronounced and strongly correlated impact, especially in Gongjo County and Qamdo Town. Temperature and precipitation exert opposing influences on CUE changes in the Southeast Tibet region. In the southern (below 28° N) and northern (above 31° N) regions of Southeast Tibet, the response of CUE to temperature and precipitation variations differs. Moreover, over 62.3% of the areas show no sustained trend of change. (3) Vegetation type emerges as a principal factor determining the scope and features of vegetation CUE changes. Grassland and sparse grassland areas exhibit markedly higher CUE values than evergreen broadleaf forests, deciduous broadleaf forests, evergreen needleleaf forests, and deciduous needleleaf forests. Notably, the CUE fluctuation in shrublands and areas with embedded farmland vegetation surpasses that of other vegetation types.

show abstract

Section: Overview Of the Study Areamentioning

confidence: 99%

Temporal and Spatial Dynamics in Carbon Utilization Efficiency and Driving Mechanisms in Southeast Tibet from 2012 to 2022

Shi,

Lu,

et al. 2024

Forests

View full text Add to dashboard Cite

show abstract

“…The area is rich in water vapor, and the rainy season begins in June and lasts until September, with abundant precipitation during summer. Precipitation in Nyingchi is mostly irregular and evenly continuous, with the majority of areas receiving annual rainfall between 500 and 1000 mm [24]. However, due to the influence of topography, there are notable differences between regions, such as in the western Yarlung Zangbo River, where annual precipitation is less than 500 mm, while in Motuo County, situated on the southern foothills of the Himalayas, the annual precipitation can exceed 2000 mm.…”

Section: Study Areamentioning

confidence: 99%

Spatio-Temporal Dynamic Characteristics of Carbon Use Efficiency in a Virgin Forest Area of Southeast Tibet

Yang

et al. 2023

Remote Sensing

View full text Add to dashboard Cite

The sequestration of carbon in forests plays a crucial role in mitigating global climate change and achieving carbon neutrality goals. Carbon use efficiency (CUE) is an essential metric used to evaluate the carbon sequestration capacity and efficiency of Vegetation. Previous studies have emphasized the importance of assessing CUE at specific regions and times to better understand its spatiotemporal variations. The southeastern region of Tibet in the Qinghai-Tibet Plateau is recognized as one of the most biodiverse areas in China and globally, characterized by diverse vegetation types ranging from subtropical to temperate. In this study, we focused on Nyingchi, which is the largest virgin forest area in southeast Tibet, to explore the spatial-temporal dynamic characteristics of regional CUE based on MODIS remote sensing products. The following results were obtained: (1) On a monthly scale, regional CUE exhibits significant seasonal variations, with varying patterns among different vegetation types. Specifically, the fluctuation of CUE is the lowest in high-altitude forest areas and the greatest in grasslands and barrens. On an annual scale, forests exhibit higher fluctuations than areas with sparse vegetation and the overall volatility of CUE increased over the past 11 years. (2) There are regional differences in the trend of CUE changes, with a substantial downward trend in the Himalayan region and a significant upward trend in the residual branches of the Gangdise Mountains. More than 75% of the regions exhibit no persistent trend in CUE changes. (3) Vegetation type is the main determinant of the range and characteristics of vegetation CUE changes, while the geographical location and climatic conditions affect the variation pattern. CUE in the southern and northern regions of Nyingchi at 28.5°N exhibits different responses to temperature and precipitation changes, with temperature having a more significant impact on CUE.

show abstract

Research on Ecological Sensitivity in Northwestern Sichuan

Sun,

Hu,

Yang

et al. 2024

Environmental Science and Engineering

View full text Add to dashboard Cite

Ecological Sensitivity Assessment of the Southeastern Qinghai-Tibet Plateau using GIS and AHP—A Case Study of the Nyingchi Region

Cited by 3 publications

References 9 publications

Temporal and Spatial Dynamics in Carbon Utilization Efficiency and Driving Mechanisms in Southeast Tibet from 2012 to 2022

Temporal and Spatial Dynamics in Carbon Utilization Efficiency and Driving Mechanisms in Southeast Tibet from 2012 to 2022

Spatio-Temporal Dynamic Characteristics of Carbon Use Efficiency in a Virgin Forest Area of Southeast Tibet

Research on Ecological Sensitivity in Northwestern Sichuan

Contact Info

Product

Resources

About