Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Spatio‐Temporal Evolution Characteristics and Driving Mechanisms of Habitat Quality on the Qinghai‐Tibet Plateau

A Multi‐Source Data Approach

Bibliographic Data

ID21648121
AuthorsGao Jie (School of Life Sciences Yan'an University Yan'an China), Shan Wenfei (School of Petroleum and Environmental Engineering Yan'an University Yan'an China), Sun Yongxiu (School of Petroleum and Environmental Engineering Yan'an University Yan'an China, corresponding author), Shiliang Liu (0000-0001-5830-5171, State Key Laboratory of Water Environment Simulation, School of Environment Beijing Normal University Beijing China), Xu Xiaoling (School of Petroleum and Environmental Engineering Yan'an University Yan'an China), XU Xiao-ling (Yan'an University), Niu Zhirui (School of Petroleum and Environmental Engineering Yan'an University Yan'an China), Teng Yanmin (College of Life Science Hebei University Baoding China), Cheng Fangyan (State Key Laboratory of Subtropical Silviculture Zhejiang A & F University Hangzhou China)
Year2026
Volume37
Issue3
Pages1027-1040
Publication date2026-02-15
Open AccessYes
TypeARTICLE
VenueLand Degradation and Development (JOURNAL)
Journal identifiersISSN: 1085-3278 • E-ISSN: 1099-145X
PublisherWiley (PUBLISHER • GB)
DOI10.1002/ldr.70158
OpenAlexW4413738522
LanguageEN
References cited39

The Qinghai‐Tibetan Plateau (QTP), serving as a crucial ecological security barrier in China, exhibits habitat quality patterns that profoundly influence regional ecological stability and human welfare. Although previous studies have examined this relationship, comprehensive investigations on habitat quality dynamics and their underlying mechanisms remain limited. This study presents a multi‐dimensional assessment framework that integrates ecosystem services values, vegetation characteristics, and external threat factors to evaluate spatiotemporal variations in habitat quality. Using a methodological approach combining structural equation modeling (SEM) and geographically weighted regression (GWR), we systematically analyzed the driving factors and their spatial heterogeneity effects. Key findings include: (1) temporal analysis revealed relative stability in overall habitat quality during 1990–2015, followed by a marked decline during 2015–2020, (2) spatially, habitat quality demonstrated a distinct northwest‐to‐southeast increasing gradient, with > 50% of the northern regions maintaining a low‐quality status. Degradation hotspots during 1990–2020 clustered in the central, western, and northern zones, while 38% of the southeastern areas showed improvement, (3) multivariate analysis identified interactive climate‐topography‐anthropogenic effects, with standardized total impact coefficients of 0.76 (climate), 0.28 (topography), and 0.14 (human activities), establishing climate as the predominant driver, and (4) GWR results revealed significant spatial non‐stationarity in factor influences. This study advances methodological integration for ecosystem assessment and provides actionable insights for managing fragile alpine environments

Biology · Geography · Habitat · Physical geography · Physics · Ecology, Conservation, and Geographical Studies · Environmental Science · Land Use and Ecosystem Services · Mathematics · Rangeland Management and Livestock Ecology · Ecology

  • Model development for the assessment of terrestrial and aquatic habitat quality in conservation planning

    Open Access•Marta Terrado, Sergi Sabater et al.•The Science of The Total…•2016

  • From Balance of Nature to Hierarchical Patch Dynamics

    Jianguo Wu, Orie L Loucks•The Quarterly Review of Biology•1995

  • Resilience and Stability of Ecological Systems

    C S Holling•Annual Review of Ecology and…•1973

  • Spatial Non-Stationarity of Influencing Factors of China’s County Economic Development Base on a Multiscale Geographically Weighted Regression Model

    Open Access•Ziwei Huang, Shaoying Li et al.•ISPRS International Journal of…•2023

Highly citedNo

Tools

Open DOI
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae