Engineering ecological protection against landslides in diverse mountain forests: Choosing cohesion models
2012
Abstract Vegetation is increasingly used to protect artificial and natural slopes against shallow landslides. Mechanically, plant roots reinforce soil along a slope by providing cohesion (c r ). c r is usually estimated using either of two models: a Wu and Waldron's Model (WWM) or a Fiber Bundle Model (FBM). The WWM assumes that all fine and medium roots break simultaneously during shearing, whereas the FBM assumes progressive breakage of these roots. Both models are based on measurements of root density (RD), root tensile strength (T r ) and root orientation (R f ). RD is highly variable and influences c r significantly more than the other variables. We investigated RD in a mixed forest stand dominated by Fagus sylvatica and Abies alba growing at an altitude of 1400 m and a mixed stand of Abies alba and Picea abies located at 1700 m. We assumed that our sites were composed of different plant functional groups, i.e. (1) only trees and shrubs were present and (2) trees, shrubs and herbaceous plants coexisted within the same site. Results showed that RD was significantly influenced by soil depth, tree spatial density and species composition. c r was then estimated by the WWM and three different FBMs; each FBM differed in the manner that load was apportioned to the roots (as a function of root cross-sectional area (CSA), root diameter or number of intact roots). Results showed that c r values differed significantly depending on the model used: c r (FBM, root number) r (FBM, root diameter) r (FBM, root CSA) r (WWM). Through a meta-analysis of literature data relating to changes in T r with root diameter, we found that compared with other factors, plant functional group had a limited effect on the estimation of c r . The use of a generic equation for T r is therefore justified when studying the stability of temperate forested slopes with mixed species.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
68
References
97
Citations
NaN
KQI