The quantification of post-disturbance root reinforcement (RR) recovery dynamics is of paramount importance for the optimisation of forest ecosystem services and natural hazards risk management in mountain regions. In this work we analyse the long-term root reinforcement dynamic of spruce forests combining data of the Swiss National Forest Inventory with data on root distribution and root mechanical properties. The results show that root reinforcement recovery depends primarily on stand altitude and slope inclination. The maximum root reinforcement recovery rate is reached at circa 100 years. RR increases continuously with different rates for stand ages over 200 years. These results shows that RR in spruce stands varies considerably depending on the local conditions and that its recovery after disturbances requires decades. The new method applied in this study allowed for the first time to quantify the long term dynamics of RR in spruce stands supporting new quantitative approaches for the analysis of shallow landslides disposition in different disturbance regimes of forests.

Populus nigra ita. is an important tree species for preventing rainfall-triggered shallow landslides and hydraulic bank erosion in New Zealand. However, the quantification of its spatial root distribution and reinforcement remains challenging. The objective of this study is to calibrate and validate models for the spatial upscaling of root distribution and root reinforcement. The data were collected in a 26-year-old “Tasman” poplar stand at Ballantrae Hill Country Research Station in New Zealand. We assessed root distribution at different distances from the stem of four poplar trees and from eleven soil pits along a transect located in a sparse to densely planting poplar stand. 124 laboratory tensile tests and 66 field pullout tests on roots with diameters up to 0.04 m were carried out to estimate root mechanical properties. The results show that the spatial distribution of roots can be well predicted in trenches of individual tree root systems (R2 = 0.78), whereas it tends to overestimate root distribution when planting density was higher than 200 stems per hectare. The root reinforcement is underestimated within single tree root systems (R2 = 0.64), but it performs better for the data along the transect. In conclusion, our study provided a unique and detailed database for quantifying root distribution and reinforcement of poplars on a hillslope. The implementation of these models for the simulation of shallow landslides and hydraulic bank erosion is crucial for identifying hazardous zones and for the prioritization of bio-engineering measures in New Zealand catchments. Results from this study are useful in formulating a general guideline for the planning of bio-engineering measures considering the temporal dynamics of poplar’s growth and their effectiveness in sediment and erosion control.

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<p>Poplar (<em>Populus</em> sp.) is an important species for preventing shallow, rainfall-triggered landslides and hydraulic bank erosion in New Zealand. However, quantifying the spatial root distribution pattern and reinforcement remains challenging. This study aimed to find the Root Bundle Model with the Weibull survival function (RBMw), a root distribution model (RDM), and a root reinforcement model for the implementation in models such as BankforMAP and SlideforMAP. Our study was conducted within a 26-year-old “Tasman” poplar stand at Ballantrae Hill Country Research Station in the North Island of NZ. We measured root distribution at distances of 1.5, 2.5, 3.5, and 4.5 m from the stem of four poplar trees whose diameters ranged from 0.41 to 0.56 m and from eleven soil profiles along a transect located in a sparse to a densely planted poplar stand. This created a unique database of root distribution. 124 laboratory tensile tests and 66 field pullout tests on roots with diameters up to 0.04 m were carried out. The root distribution model well predicted spatial root partition in trenches of single tree root systems with R<sup>2 </sup>= 0.78 and in the transect with R<sup>2</sup> = 0.85. The model tends to overestimate root distribution when planting density was higher than 200 stems per hectare. The maximum lateral root reinforcement model tends to underestimate forces in single tree root systems with R<sup>2</sup> = 0.64, but it well performs along the transect within the stand with different planting densities. The basal root reinforcement model performed well in predicting its vertical distribution as a function of soil depth. In conclusion, our study provided a detailed dataset for the quantification of root distribution and reinforcement of poplars on a hillslope for the purpose of increasing slope stability and mitigating hydraulic bank erosion. The implementation of these data in models for the simulation of shallow landslides and hydraulic bank erosion is fundamental for the identification of hazardous zones and the prioritization of bio-engineering measures in NZ catchments. Moreover, the results are used to formulate a general guideline for the planning of bio-engineering measures considering the temporal dynamics of poplar’s growth and their effectiveness in sediment and erosion control.</p><p><img src="https://contentmanager.copernicus.org/fileStorageProxy.php?f=gepj.df9c06814db362647433761/sdaolpUECMynit/32UGE&app=m&a=0&c=12967dc2610d8c55cfd4666ed81ae438&ct=x&pn=gepj.elif&d=1" alt=""></p>

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