scholarly journals Tree-root control of shallow landslides

2017 ◽  
Vol 5 (3) ◽  
pp. 451-477 ◽  
Author(s):  
Denis Cohen ◽  
Massimiliano Schwarz
Keyword(s):  
Slope Stability ◽  
Traditional Approach ◽  
Shallow Landslide ◽  
Shallow Landslides ◽  
Tree Roots ◽  
Root Reinforcement ◽  
Apparent Cohesion ◽  
Root Strength ◽  
Weak Zones ◽  
Landslide Triggering

Abstract. Tree roots have long been recognized to increase slope stability by reinforcing the strength of soils. Slope stability models usually include the effects of roots by adding an apparent cohesion to the soil to simulate root strength. No model includes the combined effects of root distribution heterogeneity, stress-strain behavior of root reinforcement, or root strength in compression. Recent field observations, however, indicate that shallow landslide triggering mechanisms are characterized by differential deformation that indicates localized activation of zones in tension, compression, and shear in the soil. Here we describe a new model for slope stability that specifically considers these effects. The model is a strain-step discrete element model that reproduces the self-organized redistribution of forces on a slope during rainfall-triggered shallow landslides. We use a conceptual sigmoidal-shaped hillslope with a clearing in its center to explore the effects of tree size, spacing, weak zones, maximum root-size diameter, and different root strength configurations. Simulation results indicate that tree roots can stabilize slopes that would otherwise fail without them and, in general, higher root density with higher root reinforcement results in a more stable slope. The variation in root stiffness with diameter can, in some cases, invert this relationship. Root tension provides more resistance to failure than root compression but roots with both tension and compression offer the best resistance to failure. Lateral (slope-parallel) tension can be important in cases when the magnitude of this force is comparable to the slope-perpendicular tensile force. In this case, lateral forces can bring to failure tree-covered areas with high root reinforcement. Slope failure occurs when downslope soil compression reaches the soil maximum strength. When this occurs depends on the amount of root tension upslope in both the slope-perpendicular and slope-parallel directions. Roots in tension can prevent failure by reducing soil compressive forces downslope. When root reinforcement is limited, a crack parallel to the slope forms near the top of the hillslope. Simulations with roots that fail across this crack always resulted in a landslide. Slopes that did not form a crack could either fail or remain stable, depending on root reinforcement. Tree spacing is important for the location of weak zones but tree location on the slope (with respect to where a crack opens) is as important. Finally, for the specific cases tested here, intermediate-sized roots (5 to 20 mm in diameter) appear to contribute most to root reinforcement. Our results show more complex behaviors than can be obtained with the traditional slope-uniform, apparent-cohesion approach. A full understanding of the mechanisms of shallow landslide triggering requires a complete re-evaluation of this traditional approach that cannot predict where and how forces are mobilized and distributed in roots and soils, and how these control shallow landslides shape, size, location, and timing.

scholarly journals Tree-roots control of shallow landslides

2017 ◽  
Author(s):  
Denis Cohen ◽  
Massimiliano Schwarz
Keyword(s):  
Slope Stability ◽  
Shallow Landslide ◽  
Shallow Landslides ◽  
Tree Roots ◽  
Root Reinforcement ◽  
Apparent Cohesion ◽  
Root Strength ◽  
Tension And Compression ◽  
Weak Zones ◽  
Landslide Triggering

Abstract. Tree roots have long been recognized to increase slope stability by reinforcing the strength of soils. Slope stability models include the effects of roots by adding an apparent cohesion to the soil to simulate root strength. No model includes the combined effects of root distribution heterogeneity, stress-strain behavior of root reinforcement, or root strength in compression. Recent field observations, however, indicate that shallow landslide triggering mechanisms are characterized by differential deformation that indicates localized activation of zones in tension, compression, and shear in the soil. These observations contradict the common assumptions used in present models. Here we describe a new model for slope stability that specifically considers these effects. The model is a strain-step discrete element model that reproduces the self-organized redistribution of forces on a slope during rainfall-triggered shallow landslides. We use a conceptual sigmoidal-shaped hillslope with a clearing in its center to explore the effects of tree size, spacing, weak zones, maximum root-size diameter, and different root strength configurations. The model is driven by root data of Norway spruce obtained from laboratory and field measurements. Simulation results indicate that tree roots can stabilize slopes that would otherwise fail without them and, in general, higher root density with higher root reinforcement results in a more stable slope. Root tension provides more resistance to failure than root compression but roots with both tension and compression offer the best resistance to failure. Lateral (slope-parallel) tension can be important in cases when the magnitude of these forces is comparable to the slope-perpendicular tensile forces. In these cases, lateral forces can bring to failure tree-covered areas with high root reinforcement. Slope failure occurs when downslope soil compression reaches the soil maximum strength. When this occurs depends on the amount of root tension upslope in both the slope-perpendicular and slope-parallel directions. Roots in tension can prevent failure by reducing soil compressive forces downslope. When root reinforcement is limited, hillslopes form a crack parallel to the slope near its top. Simulations with roots that fail across this crack always resulted in a landslide. Slopes that did not form a crack could either fail or remain stable, depending on root reinforcement. Tree spacing is important for the location of weak zones but tree location on the slope (with respect to where a crack opens) is as important. Finally, for the specific cases tested here, large roots, greater than 20 mm, are too few too contribute significantly to root reinforcement. Omitting roots larger than 8 mm predicted a landslide when none should have occurred. Intermediate roots (5 to 20 mm) appear to contribute most to root reinforcement and should be included in calculations. To fully understand the mechanisms of shallow landslide triggering requires a complete re-evaluation of the traditional apparent-cohesion approach that does not reproduce the incremental loading of roots in tension or in compression. Our model shows that it is important to consider the forces held by roots in a way that is entirely different than done thus far. Our work quantifies the contribution of roots in tension and compression which now finally permits to analyze more realistically the role of root reinforcement during the triggering of shallow landslides.

Shallow landslides along the pyroclastic-mantled slopes of mount Partenio (Campania, Italy): the events of 16.12.1999 and 21.12.2019

2020 ◽  
Author(s):  
Emilia Damiano ◽  
Luca Comegna ◽  
Roberto Greco ◽  
Pasquale Marino ◽  
Lucio Olivares ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Shallow Landslide ◽  
Shallow Landslides ◽  
Monitoring Data ◽  
First Case ◽  
Failure Conditions ◽  
Fractured Limestone ◽  
Cover Thickness ◽  
The Town ◽  
Landslide Triggering

<p>As other mountainous areas of Campania (Italy), mount Partenio consists of carbonate rocks covered with layered air-fall deposits originated by eruptions of the two volcanic complexes of the area (Somma Vesuvius and Phlegrean Fields). The deposits are alternated layers of ashes (loamy sands) and pumices (sands with gravel), both materials characterized by negligible effective cohesion. The thickness of the deposit ranges between few centimeters along the steepest slopes (up to 50°) to some meters at the foot of the slopes, with gentle inclination. The equilibrium of the covers along the steepest slopes is guaranteed by the contribution of suction to soil shear strength. After intense and prolonged rain, this contribution is reduced by infiltrating water being stored within the cover, sometimes leading to shallow landslide triggering.</p><p>The two most recent landslide events in the area occurred on 16.12.1999 and 21.12.2019. In the first case, several landslides were triggered along slopes with inclination larger than 40°, in an area of about 10 km<sup>2</sup>, some of which evolved in the form of fast debris flows which caused damages to buildings and some victims in the town of Cervinara. In the second case, two major landslides were reported, one of which, along a slope with inclination between 42° and 45°, very close to two of the landslides of 1999, damaged roads and buildings in the town of San Martino Valle Caudina.</p><p>After the event of 1999, a hydro-meteorological monitoring station was installed near the scarp of the major landslide. Thanks to the monitoring data and laboratory investigation on the hydraulic properties of the involved soils, a mathematical model of the response of the slope to precipitation was developed (Greco et al., 2013). The model couples unsaturated flows in the pyroclastic cover with the groundwater system developing in the underlying fractured limestone bedrock, and it allows satisfactorily reproducing the seasonal trends of the terms of the hydrological balance of the slope (Greco et al., 2018).</p><p>In this study, the two events of 1999 and 2019 are compared, in terms of pre-event and event rainfall characteristics, as well as by simulating the response of the slopes by means of the mathematical model during the entire year until the day of the landslides. The obtained results show the importance of the interplay between predisposing conditions, related to the rainfall history during the months before the event, and the characteristics of the triggering event. The model simulations indicate that, while in 1999 failure conditions are predicted along slopes with inclination larger than 40°, regardless cover thickness, in 2019 landslide triggering is predicted only on slopes mantled by a cover thinner than 1.5 meters with inclination larger than 42°.</p><p>References</p><p>R. Greco, L. Comegna, E. Damiano, A. Guida, L. Olivares, L. Picarelli (2013). Hydrological modelling of a slope covered with shallow pyroclastic deposits from field monitoring data. Hydrology and Earth System Sciences, 17: 4001-4013.</p><p>R. Greco, P. Marino, G.F. Santonastaso, E. Damiano (2018). Interaction between perched epikarst aquifer and unsaturated soil cover in the initiation of shallow landslides in pyroclastic soils. Water, 10(7): 948.</p>

scholarly journals Site-specific to local-scale shallow landslides triggering zones assessment using TRIGRS

2015 ◽  
Vol 15 (5) ◽  
pp. 1025-1050 ◽  
Author(s):  
M. Bordoni ◽  
C. Meisina ◽  
R. Valentino ◽  
M. Bittelli ◽  
S. Chersich
Keyword(s):  
Input Data ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Regional Scale ◽  
Shallow Landslide ◽  
Local Scale ◽  
Shallow Landslides ◽  
Sensitivity Analyses ◽  
Site Specific ◽  
Landslide Triggering

Abstract. Rainfall-induced shallow landslides are common phenomena in many parts of the world, affecting cultivation and infrastructure and sometimes causing human losses. Assessing the triggering zones of shallow landslides is fundamental for land planning at different scales. This work defines a reliable methodology to extend a slope stability analysis from the site-specific to local scale by using a well-established physically based model (TRIGRS-unsaturated). The model is initially applied to a sample slope and then to the surrounding 13.4 km2 area in Oltrepò Pavese (northern Italy). To obtain more reliable input data for the model, long-term hydro-meteorological monitoring has been carried out at the sample slope, which has been assumed to be representative of the study area. Field measurements identified the triggering mechanism of shallow failures and were used to verify the reliability of the model to obtain pore water pressure trends consistent with those measured during the monitoring activity. In this way, more reliable trends have been modelled for past landslide events, such as the April 2009 event that was assumed as a benchmark. The assessment of shallow landslide triggering zones obtained using TRIGRS-unsaturated for the benchmark event appears good for both the monitored slope and the whole study area, with better results when a pedological instead of geological zoning is considered at the regional scale. The sensitivity analyses of the influence of the soil input data show that the mean values of the soil properties give the best results in terms of the ratio between the true positive and false positive rates. The scheme followed in this work allows us to obtain better results in the assessment of shallow landslide triggering areas in terms of the reduction in the overestimation of unstable zones with respect to other distributed models applied in the past.

scholarly journals Introducing SlideforMap; a probabilistic finite slope approach for modelling shallow landslide probability in forested situations

2021 ◽  
Author(s):  
Feiko Bernard van Zadelhoff ◽  
Adel Albaba ◽  
Denis Cohen ◽  
Chris Phillips ◽  
Bettina Schaefli ◽  
...  
Keyword(s):  
Soil Depth ◽  
Shallow Landslide ◽  
Shallow Landslides ◽  
Model Parameters ◽  
Topographic Wetness Index ◽  
Root Reinforcement ◽  
Wetness Index ◽  
Tree Detection ◽  
Single Tree ◽  
Soil Cohesion

Abstract. Worldwide, shallow landslides repeatedly pose a risk to infrastructure and residential areas. To analyse and predict the risk posed by shallow landslides, a wide range of scientific methods and tools to model shallow landslide probability exist for both local and regional scale However, most of these tools do not take the protective effect of vegetation into account. Therefore, we developed SlideforMap (SfM), which is a probabilistic model that allows for a regional assessment of shallow landslide probability while considering the effect of different scenarios of forest cover, forest management and rainfall intensity. SfM uses a probabilistic approach by distributing hypothetical landslides to uniformly randomized coordinates in a 2D space. The surface areas for these hypothetical landslides are derived from a distribution function calibrated from observed events. For each randomly generated landslide, SfM calculates a factor of safety using the limit equilibrium approach. Relevant soil parameters, i.e. angle of internal friction, soil cohesion and soil depth, are assigned to the generated landslides from normal distributions based on mean and standard deviation values representative for the study area. The computation of the degree of soil saturation is implemented using a stationary flow approach and the topographic wetness index. The root reinforcement is computed based on root proximity and root strength derived from single tree detection data. Ultimately, the fraction of unstable landslides to the number of generated landslides, per raster cell, is calculated and used as an index for landslide probability. Inputs for the model are a digital elevation model, a topographic wetness index and a file containing positions and dimensions of trees. We performed a calibration of SfM for three test areas in Switzerland with a reliable landslide inventory, by randomly generating 1000 combinations of model parameters and then maximising the Area Under the Curve (AUC) of the receiver operation curve (ROC). These test areas are located in mountainous areas ranging from 0.5–7.5 km2, with varying mean slope gradients (18–28°). The density of inventoried historical landslides varied from 5–59 slides/km2. AUC values between 0.67 and 0.92 indicated a good model performance. A qualitative sensitivity analysis indicated that the most relevant parameters for accurate modeling of shallow landslide probability are the soil depth, soil cohesion and the root reinforcement. Further, the use of single tree detection in the computation of root reinforcement significantly improved model accuracy compared to the assumption of a single constant value of root reinforcement within a forest stand. In conclusion, our study showed that the approach used in SfM can reproduce observed shallow landslide occurrence at a catchment scale.

Evaluation of the effect of hysteretic flow and root system on shallow landslide

Soil Research ◽  
2012 ◽  
Vol 50 (7) ◽  
pp. 616 ◽  
Author(s):  
Kuo-Chen Ma ◽  
Yong-Jun Lin ◽  
Shyh-Yuan Maa ◽  
Yih-Chi Tan
Keyword(s):  
Stability Analysis ◽  
Slope Stability ◽  
Root System ◽  
Soil Water ◽  
Economic Benefits ◽  
Shallow Landslide ◽  
Slope Stability Analysis ◽  
Tree Planting ◽  
Vegetation Types ◽  
Root Strength

This paper analyses the mechanics of slope stability with regard to the hysteretic flow of unsaturated soil and the root system of the covering vegetation. The hysteresis of the soil water retention curves and root strength are important factors in the evaluation of unsaturated shear strength. Engineers should consider how the transportation of the soil water content and the plant root strength influence evaluation of surficial slope stability analysis. The integrated slope stability analysis considering the hysteretic flow and root strength were calculated on variations of the safety factor (SF) and in accordance with different infiltration profiles and several species of vegetation. The results show that it is possible to predict shallow landslide on unsaturated slopes covered by different vegetation types. Tree planting, in combination with mechanical reinforcement, on the slope’s toe was found to improve stability, in addition to having economic benefits. This process allows for the selection and comparison of combinations and densities of vegetation types, in order to find the optimum location for increased SF. This will quickly improve shallow slope stability before it is destroyed. A better understanding of the process mechanics, as provided by the model, is critical for a reliable and appropriate design for slope stabilisation.

scholarly journals Root Reinforcement in Slope Stability Models: A Review

Geosciences ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 212
Author(s):  
Elena Benedetta Masi ◽  
Samuele Segoni ◽  
Veronica Tofani
Keyword(s):  
Soil Moisture ◽  
Slope Stability ◽  
Regional Scale ◽  
Moisture Gradient ◽  
Future Research ◽  
Spatial And Temporal Variability ◽  
Soil Behavior ◽  
Root Reinforcement ◽  
Soil Moisture Gradient ◽  
Root Strength

The influence of vegetation on mechanical and hydrological soil behavior represents a significant factor to be considered in shallow landslides modelling. Among the multiple effects exerted by vegetation, root reinforcement is widely recognized as one of the most relevant for slope stability. Lately, the literature has been greatly enriched by novel research on this phenomenon. To investigate which aspects have been most treated, which results have been obtained and which aspects require further attention, we reviewed papers published during the period of 2015–2020 dealing with root reinforcement. This paper—after introducing main effects of vegetation on slope stability, recalling studies of reference—provides a synthesis of the main contributions to the subtopics: (i) approaches for estimating root reinforcement distribution at a regional scale; (ii) new slope stability models, including root reinforcement and (iii) the influence of particular plant species, forest management, forest structure, wildfires and soil moisture gradient on root reinforcement. Including root reinforcement in slope stability analysis has resulted a topic receiving growing attention, particularly in Europe; in addition, research interests are also emerging in Asia. Despite recent advances, including root reinforcement into regional models still represents a research challenge, because of its high spatial and temporal variability: only a few applications are reported about areas of hundreds of square kilometers. The most promising and necessary future research directions include the study of soil moisture gradient and wildfire controls on the root strength, as these aspects have not been fully integrated into slope stability modelling.

scholarly journals Evaluation of shallow landslide-triggering scenarios through a physically based approach: an example of application in the southern Messina area (northeastern Sicily, Italy)

2015 ◽  
Vol 15 (9) ◽  
pp. 2091-2109 ◽  
Author(s):  
L. Schilirò ◽  
C. Esposito ◽  
G. Scarascia Mugnozza
Keyword(s):  
Back Analysis ◽  
Early Warning Systems ◽  
Shallow Landslide ◽  
Shallow Landslides ◽  
Landslide Event ◽  
Wide Range ◽  
Physically Based ◽  
Triggering Process ◽  
Landslide Triggering ◽  
Northeastern Sicily

Abstract. Rainfall-induced shallow landslides are a widespread phenomenon that frequently causes substantial damage to property, as well as numerous casualties. In recent~years a wide range of physically based models have been developed to analyze the triggering process of these events. Specifically, in this paper we propose an approach for the evaluation of different shallow landslide-triggering scenarios by means of the TRIGRS (transient rainfall infiltration and grid-based slope stability) numerical model. For the validation of the model, a back analysis of the landslide event that occurred in the study area (located SW of Messina, northeastern Sicily, Italy) on 1 October 2009 was performed, by using different methods and techniques for the definition of the input parameters. After evaluating the reliability of the model through comparison with the 2009 landslide inventory, different triggering scenarios were defined using rainfall values derived from the rainfall probability curves, reconstructed on the basis of daily and hourly historical rainfall data. The results emphasize how these phenomena are likely to occur in the area, given that even short-duration (1–3 h) rainfall events with a relatively low return period (e.g., 10–20~years) can trigger numerous slope failures. Furthermore, for the same rainfall amount, the daily simulations underestimate the instability conditions. The high susceptibility of this area to shallow landslides is testified by the high number of landslide/flood events that have occurred in the past and are summarized in this paper by means of archival research. Considering the main features of the proposed approach, the authors suggest that this methodology could be applied to different areas, even for the development of landslide early warning systems.

Factor of safety analysis with and without vegetation using the SOSlope model

2020 ◽  
Author(s):  
Massimiliano Schwarz ◽  
Ilenia Murgia ◽  
Filippo Giadrossich ◽  
Massimiliano Bordoni ◽  
Claudia Meisina ◽  
...  
Keyword(s):  
Slope Stability ◽  
Factor Of Safety ◽  
Survival Function ◽  
Shallow Landslide ◽  
Monitoring Station ◽  
Tree Roots ◽  
Complete Evaluation ◽  
Heterogeneous Distribution ◽  
Self Organized

<p>Until now, slope stability models include the effects of the vegetation by adding a fixed value of apparent root cohesion as an estimate of root strength. However, some studies have demonstrated that root reinforcement depends on poorly constrained factors such as the heterogeneous distribution of roots in the soil and their tensional and compressional strength behavior.</p><p>SOSlope (Self-Organized Slope) is a hydro-mechanical model that computes the factor of safety on a hillslope discretized into a two-dimensional array of blocks connected by bonds to simulate the interactions of root-soil systems (Cohen and Schwarz, 2017). SOSlope estimates slope stability considering the presence of vegetation as a function of parameters such as species, tree density and diameter at breast height. In particular, bonds between adjacent blocks represent mechanical forces acting across the blocks due to roots and soil, in tension or compression, depending on the relative position of blocks. It is a strain-step discrete element model that reproduces the self-organized redistribution of forces on a slope during a rainfall-triggered shallow landslide. The innovative aspect of this model is a complete evaluation of the effects of roots on slope stability calculated using the Root Bundle Model with Weibull survival function  (RBMw, Schwarz et al, 2013).</p><p>In this case study, SOSlope was used to reconstruct a critical shallow landslide triggering and to observe how the factor of safety changes depending on the presence, or not, of vegetation. The study area is located in the north-eastern part of the Oltrepò Pavese (Pavia, Italy), and is characterized by a high density of past landslides as reported in the database of Italian landslide inventories (IFFI). In the past, the common land use was vineyards, abandoned in the 1980s. Presently, the vegetation consists of grasses and shrubs moving to a thinned forest of young Robinia pseudoacacia L.    </p><p>On 27 and 28 April 2009 a shallow landslide triggered after an intense and prolonged rainfall event (160 mm accumulated in 62 h with a maximum intensity of 22.6 mm/h). A large number of shallow landslides occurred in the surrounding area with about 29 landslides per km<sup>2</sup> (1600 landslides in 240 km<sup>2</sup>). Five years later, on 28 February - 2 March 2014, 15 meters from a monitoring station and close to the previously affected area, another superficial landslide was triggered after 30 days of rain with a total precipitation of 105.5 mm (68.9 mm in 42 h recorded by the rain gauge of the monitoring station). In addition to the significance of this large landslide, this case study was scientifically important because it wasthe first documented case of a natural shallow landslide induced by rainfall since the 1950s (Bordoni et al, 2015).</p><p>The results of SOSlope simulations show good agreement with the real event of 28 February - 2 March 2014, and emphasize the important role of tree roots in the variation of the factor of safety. In this specific case, adding trees results in a reduction of about 39% of the dimensions of the unstable area.</p>

SlideforMap – a regional scale probabilistic model for shallow landslide onset analysis and protection forest management

2020 ◽  
Author(s):  
Feiko van Zadelhoff ◽  
Luuk Dorren ◽  
Massimiliano Schwarz
Keyword(s):  
Protective Effect ◽  
Probabilistic Model ◽  
Limit Equilibrium ◽  
Regional Scale ◽  
Shallow Landslide ◽  
Shallow Landslides ◽  
Soil Parameters ◽  
Root Reinforcement ◽  
Wetness Index ◽  
Wide Range

<p>In the Alps, shallow landslides repeatedly pose a risk to infrastructure and residential areas. For example, dozens of shallow landslides led to the destruction of several houses, killed one person and led to the evacuation of more than 50 houses, multiple road closure for several days in Austria in Nov. 2019. To analyse and predict the risk posed by shallow landslide, a wide range of scientific methods and tools for modelling disposition and runout exists, both for local and regional scale analyses. Most of these tools, however, do not take the protective effect, i.e. root reinforcement, of vegetation into account. Therefore, we developed SlideforMap (SfM), a probabilistic model that allows for a regional assessment of the disposition of shallow landslides while considering the effect of different scenarios of forest cover and management and of rainfall intensity.</p><p>SfM uses a probabilistic approach by attributing landslide surface areas, randomly selected from a gamma shaped distribution published by Malamud (2004), to random coordinates within a given study area. For each generated landslide, SfM calculates a factor of safety using the limit equilibrium infinite slope approach. Thereby, the relevant soil parameters, i.e. angle of internal friction, soil cohesion and soil depth, are defined by normal distributions based on mean and standard deviation values representative for the study area. Hydrology is implemented using a stationary flow approach and the topographical wetness index. Root reinforcement is computed based on root distribution and root strength derived from single tree detection data and the root bundle model of Schwarz et al. (2013). Finally, the fraction of unstable landslides to the number of generated slides per raster cells is calculated and used as an index for landslide onset susceptibility. Inputs for the model are a Digital Terrain Model, a topographical wetness index and a file containing positions and sizes of trees.</p><p>Validation of SfM has been done by calculating the AUC (Metz, 1978) for three test areas with a reliable landslide inventory in Switzerland. These test areas are in mountainous areas ranging 0.5 – 7.5 km<sup>2</sup> with varying mean slope gradients (18 - 28°). The density of inventoried historical landslides varied from 0.4 – 59 slides/km<sup>2</sup>. This resulted in AUC values between 0.64 and 0.86. Our study showed that the approach used in SfM can reproduce shallow landslide onset susceptibility on a regional scale observed in reality.</p><p>SfM was developed to quantify the stabilizing effect of vegetation at regional scale and localize potential areas where the protective effect of forests can be improved. A first version of the model will be released in 2020 by the ecorisQ association (www.ecorisq.org).</p>

Sign in / Sign up

Export Citation Format

Share Document