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Indicating landslide hazard from tree rings – Ecosystem service provided by an alder forest in the hengduan Mts, Sichuan, China.

Authors :
Wistuba, Małgorzata
Malik, Ireneusz
Tie, Yongbo
Gorczyca, Elżbieta
Zhang, Xianzheng
Wang, Jiazhu
Lu, Tuo
Source :
Ecosystem Services; Jun2024, Vol. 67, pN.PAG-N.PAG, 1p
Publication Year :
2024

Abstract

• Tree rings have recently become a widely used tool in landslide studies. • We explore the potential of trees in providing a new ecosystem service of landslide monitoring. • We present results obtained for 48 Nepalese alders sampled on a landslide in the Moxi basin, Sichuan, China. • Dendrochronology can provide data for landslide hazard assessment, monitoring and prediction. Landslides are destructive geomorphological processes that cause economic and social losses. This stimulates the development of new tools related to landslide hazard. Recently, trees, their growth rings and dendrochronology have become widely used in landslide studies. Thus, this study aims to explore the potential of trees in providing landslide-monitoring ecosystem services through dendrochronology. In our opinion, establishing such an idea would help promote empirical evidence on the efficiency of tree-ring-based tools to decision-makers. We use the example of a landslide in the Moxi basin, Sichuan, China and present results of dendrochronological analysis of growth eccentricity in 48 Nepalese alder (Alnus nepalensis) trees. This analysis provided data on event timing and magnitudes, average frequency and recurrence interval for reactivation of the study landslide, as well as spatial variability of landslide active. Based on dendrochronological data we were also able to determine the current slope balance and general hazard of landslide reactivation on the study slope. Our study shows that trees and dendrochronology can provide data on the activity of landslides that can complement and improve the results of standard engineering methods. Moreover, dendrochronology itself can provide the full information needed for landslide hazard assessment, monitoring and prediction. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22120416
Volume :
67
Database :
Supplemental Index
Journal :
Ecosystem Services
Publication Type :
Academic Journal
Accession number :
177373370
Full Text :
https://doi.org/10.1016/j.ecoser.2024.101619