Premium
Modelling biome‐scale root reinforcement and slope stability
Author(s) -
Hales Tristram C.
Publication year - 2018
Publication title -
earth surface processes and landforms
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.294
H-Index - 127
eISSN - 1096-9837
pISSN - 0197-9337
DOI - 10.1002/esp.4381
Subject(s) - biome , environmental science , soil science , monte carlo method , landslide , cohesion (chemistry) , slope stability , grassland , soil water , shrubland , geology , mathematics , geotechnical engineering , statistics , ecology , ecosystem , biology , chemistry , organic chemistry
Abstract Rapid changes in the composition of hillslope vegetation due to a combination of changing climate and land use make estimating slope stability a significant challenge. The dynamics of root growth on any individual hillslope result in a wide range of root distributions and strengths that are reflected as up to an order of magnitude variability in root cohesion. Hence the challenge of predicting the magnitude of root reinforcement for hillslopes requires both an understanding of the magnitude and variability of root distributions and material properties (e.g. tensile strength, elasticity). Here I develop a model for estimating the reinforcement provided by plant roots based on the distribution of biomass measured at the biome level and a compilation of root tensile strength measurements measured across a range of vegetation types. The model modifies the Wu/Waldron method of calculating root cohesion to calculate the average lateral root cohesion and its variability with depth using the Monte Carlo method. The model was validated in two ways, the first against the predicted depth‐reinforcement characteristics of Appalachian soils and the second using a global dataset of landslides. Model results suggest that the order of magnitude difference in root cohesions measured on individual hillslopes can be captured by the Monte Carlo approach and provide a simple tool to estimate root reinforcement for data‐poor areas. The model also suggests that future hotspots of slope instability will occur in areas where land use and climate convert forest to grassland, rather than changes between different forest structures or forest and shrubland. Copyright © 2018 John Wiley & Sons, Ltd.