Quantifying the influence of individual trees on slope stability at landscape scale

Silvopastoralism in New Zealand's highly erodible hill country is an important form of erosion and sediment control. Yet, there has been little quantitative work to establish the effectiveness of space-planted trees in reducing shallow landslide erosion. We propose a method to provide high-resolution spatially explicit individual tree influence models at landscape scale for the dominant species in pastoral hill country. The combined hydrological and mechanical influence of trees on slopes is inferred through the spatial relationship between trees and landslide erosion. First, we delineate individual tree crowns and classify these into four dominant species classes found in New Zealand's pastoral hill country. This is the first species classification of individual trees at landscape scale in New Zealand using freely accessible data, achieving an overall accuracy of 92.6%. Second, we develop tree influence models for each species class by means of inductive inference. The inferred empirical 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. 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. The tree influence models presented in this study can be integrated into landslide susceptibility modelling in silvopastoral landscapes to both quantify the reduction in landslide susceptibility achieved and support targeted erosion and sediment mitigation plans.