EGU21-756, updated on 18 Dec 2023
https://doi.org/10.5194/egusphere-egu21-756
EGU General Assembly 2021
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Inferring the effect of individual trees on slope stability in New Zealand’s pastoral hill country

Raphael Spiekermann1,2, Sam McColl2, Ian Fuller2, John Dymond1, Lucy Burkitt2, and Hugh Smith1
Raphael Spiekermann et al.
  • 1Manaaki Whenua - Landcare Research, Palmerston North, New Zealand (spiekermannr@landcareresearch.co.nz)
  • 2School of Agriculture and Environment, Massey University, Palmerston North, New Zealand

Silvopastoralism in New Zealand’s highly erodible hill country is an important form of erosion and sediment control. Despite a long history in improving sustainable land management and soil conservation since the enactment of the Soil Conservation and Rivers Control Act 1941, there has been little quantitative work to establish the effectiveness of space-planted trees in reducing shallow landslide erosion at farm to landscape scales. This is largely due to the lack of spatially explicit data on individual trees and their influence on slope stability. Therefore, it is difficult to determine the extent to which plantings have targeted slopes susceptible to landslide erosion. Furthermore, root data collection for multiple species and age classes is very time-consuming and costly, which limits the development of root reinforcement models for different species and partly explains the paucity of quantitative data on the effectiveness of space-planted trees.

We present an empirical approach that aims to fill the gap in scale between 1) physical models that integrated root reinforcement data of individual trees into slope stability models and 2) landslide susceptibility modelling at regional scale using land cover data. First, we delineate individual tree crowns (ITCs) at landscape scale and classify into dominant species classes found in New Zealand’s pastoral hill country. The resulting rural tree species classification achieved an overall accuracy of 92.6% based on 9,200 samples that were collected from two farms within the study area. We then present a spatially explicit tree influence model for each species class developed by means of inductive inference. The tree influence models represent the combined hydrological and mechanical influence of trees on slopes, which is inferred through the spatial relationship between individual trees and landslide erosion. The resulting tree influence models largely agree with the shape and distribution of existing physical root reinforcement models.

Of exotic species that were planted for erosion and sediment control, poplars (Populus spp.) and willows (Salix spp.) make up 51% (109,000 trees) in pastoral hill country at a mean density of 3.2 trees/ha. This large number of poplars and willows reflects the efforts made by landowners and soil conservators over several decades to mitigate erosion processes and adopt more sustainable land management practices. In line with previous studies, poplars and willows have the greatest contribution to slope stability with an average maximum effective distance of 20 m. Yet, native kānuka (Kunzea spp.) is the most abundant woody vegetation species in pastoral hill country within the study area, with an average of 24.1 stems per ha (sph), providing an important soil conservation function. A large proportion (56% or 212.5 km2) of pastoral hill-country in the study area remains untreated, i.e. has no added soil shear strength due to the presence of trees. The tree influence models presented in this study can be integrated into landslide susceptibility modelling in silvopastoral/agroforestry landscapes to both quantify the reduction in landslide susceptibility achieved and support targeted erosion and sediment mitigation plans.

How to cite: Spiekermann, R., McColl, S., Fuller, I., Dymond, J., Burkitt, L., and Smith, H.: Inferring the effect of individual trees on slope stability in New Zealand’s pastoral hill country, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-756, https://doi.org/10.5194/egusphere-egu21-756, 2021.