Diagnosing ecological quality dynamics in a karst restoration belt: Trajectory instability, response breakpoints, and adaptive restoration implications
5 affiliations
- 1Faculty of Geography, Yunnan Normal University, Kunming, Yunnan 650500, China; GIS Technology Engineering Research Centre for West-China Resources and Environment of Educational Ministry, Yunnan Normal University, Kunming, Yunnan 650500, China
- 2Faculty of Geography, Yunnan Normal University, Kunming, Yunnan 650500, China; GIS Technology Engineering Research Centre for West-China Resources and Environment of Educational Ministry, Yunnan Normal University, Kunming, Yunnan 650500, China; Corresponding authors at: Faculty of Geography, Yunnan Normal University, Kunming, Yunnan 650500, China.
- 3School of Ecology and Environment, Yunnan University, Kunming, Yunnan 650500, China
- 4Faculty of Geography, Yunnan Normal University, Kunming, Yunnan 650500, China
- 5Faculty of Geography, Yunnan Normal University, Kunming, Yunnan 650500, China; Yunnan International Joint Laboratory of Resource and Security in the Indian Ocean Region, Yunnan Normal University, Kunming, Yunnan 650500, China
Abstract
Conventional global attribution models tend to smooth over spatially conflicting ecological signals, thereby limiting the identification of trajectory-dependent association patterns, nonlinear responses, and latent instability in heterogeneous fragile landscapes. To address this limitation, this study developed a diagnostic adaptive assessment framework (DAAF) and applied it to the rocky desertification restoration belt of eastern and southeastern Yunnan, China. Using annual remote sensing ecological index (RSEI) data from 2000 to 2022 as the operational indicator of ecological environmental quality (EEQ), Sen's slope, the Mann–Kendall test, and the Hurst exponent were jointly employed to diagnose EEQ trends, characterize Hurst-based persistence tendencies and potential trajectory instability, and delineate eight dynamic trajectory types. Spatially stratified XGBoost–SHAP analysis, breakpoint detection, and network-assisted mediation analysis were then conducted to identify trajectory-specific environmental associations, response breakpoints, and indirect association patterns. The results showed that 88.29% of the study area exhibited improving EEQ, whereas 34.52% fell within trajectory-instability zones, indicating widespread improvement alongside anti-persistent or fluctuation-prone trajectories. Improving trajectories showed stronger associations with reduced external human pressure, whereas degrading trajectories were associated with weaker vegetation-cover conditions, hydroclimatic stress, and cumulative disturbance patterns. The fitted association between land-use intensity (LUCI) and annual RSEI showed an approximate response breakpoint around 2.09. In addition, FVC and precipitation exhibited separate approximate model-based response breakpoints around 0.63 and 970 mm, respectively, within localized degradation trajectories. Their co-occurring nonlinear patterns were consistent with a process-informed karst rainfall-paradox hypothesis under weakened vegetation protection. Mediation-assisted analysis further identified indirect association patterns linking land-use intensity, cumulative human pressure, and annual RSEI, whereas steep slopes showed terrain-related buffering associations with disturbance patterns. By linking trend diagnosis, stratified attribution, and breakpoint identification, the proposed framework provides a diagnostic workflow for EEQ assessment and spatially differentiated restoration management in fragile landscapes.
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BibTeX
@article{lin2026diagnosing,
title = {{Diagnosing ecological quality dynamics in a karst restoration belt: Trajectory instability, response breakpoints, and adaptive restoration implications}},
author = {Zhiqiang Lin and Juexian Dong and Shuangyun Peng and Jiaying Zhu and Shuangfu Shi and Kang Hu and Xiaoliang Ma and Ziyi Zhu and Fucheng Cai and Wenguang Xiang and Xianchun Pan and Weihang Wang and Fapeng Cai},
journal = {Ecological Indicators},
year = {2026},
month = oct,
doi = {10.1016/j.ecolind.2026.115526},
url = {https://doi.org/10.1016/j.ecolind.2026.115526},
note = {CC BY},
}
RIS
TY - JOUR
TI - Diagnosing ecological quality dynamics in a karst restoration belt: Trajectory instability, response breakpoints, and adaptive restoration implications
AU - Zhiqiang Lin
AU - Juexian Dong
AU - Shuangyun Peng
AU - Jiaying Zhu
AU - Shuangfu Shi
AU - Kang Hu
AU - Xiaoliang Ma
AU - Ziyi Zhu
AU - Fucheng Cai
AU - Wenguang Xiang
AU - Xianchun Pan
AU - Weihang Wang
AU - Fapeng Cai
PY - 2026
DA - 2026/10/23
JO - Ecological Indicators
DO - 10.1016/j.ecolind.2026.115526
UR - https://doi.org/10.1016/j.ecolind.2026.115526
AB - Conventional global attribution models tend to smooth over spatially conflicting ecological signals, thereby limiting the identification of trajectory-dependent association patterns, nonlinear responses, and latent instability in heterogeneous fragile landscapes. To address this limitation, this study developed a diagnostic adaptive assessment framework (DAAF) and applied it to the rocky desertification restoration belt of eastern and southeastern Yunnan, China. Using annual remote sensing ecological index (RSEI) data from 2000 to 2022 as the operational indicator of ecological environmental quality (EEQ), Sen's slope, the Mann–Kendall test, and the Hurst exponent were jointly employed to diagnose EEQ trends, characterize Hurst-based persistence tendencies and potential trajectory instability, and delineate eight dynamic trajectory types. Spatially stratified XGBoost–SHAP analysis, breakpoint detection, and network-assisted mediation analysis were then conducted to identify trajectory-specific environmental associations, response breakpoints, and indirect association patterns. The results showed that 88.29% of the study area exhibited improving EEQ, whereas 34.52% fell within trajectory-instability zones, indicating widespread improvement alongside anti-persistent or fluctuation-prone trajectories. Improving trajectories showed stronger associations with reduced external human pressure, whereas degrading trajectories were associated with weaker vegetation-cover conditions, hydroclimatic stress, and cumulative disturbance patterns. The fitted association between land-use intensity (LUCI) and annual RSEI showed an approximate response breakpoint around 2.09. In addition, FVC and precipitation exhibited separate approximate model-based response breakpoints around 0.63 and 970 mm, respectively, within localized degradation trajectories. Their co-occurring nonlinear patterns were consistent with a process-informed karst rainfall-paradox hypothesis under weakened vegetation protection. Mediation-assisted analysis further identified indirect association patterns linking land-use intensity, cumulative human pressure, and annual RSEI, whereas steep slopes showed terrain-related buffering associations with disturbance patterns. By linking trend diagnosis, stratified attribution, and breakpoint identification, the proposed framework provides a diagnostic workflow for EEQ assessment and spatially differentiated restoration management in fragile landscapes.
SN - 1470-160X
SN - 1872-7034
ER -