Implications of hornbeam and beech root systems on slope stability: from field and laboratory measurements to modelling methods

Deljouei, Azade; Cislaghi, Alessio; Abdi, Ehsan; Borz, Stelian Alexandru; Majnounian, Baris; Hales, Tristram C.

doi:10.1007/s11104-022-05764-z

Cited by 16 publications

(16 citation statements)

References 106 publications

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“…Our study found that three species are distributed in the slopes of the mountainous regions in the Caspian Sea, and Iraniano-Turanian regions, particularly in well-drained soils 31 . Slope percentage plays a vital role in regulating the spatial arrangement of soil nutrients, soil stability 61 , 62 , water availability, heat, and sunlight 63 . It creates diverse microclimates with unique soil properties, especially in mountainous regions like Iran 24 , 64 , 65 .…”

Section: Discussionmentioning

confidence: 99%

“…The adverse effects of climate change include changes in precipitation and temperature patterns, water resources, sea levels and coastal zones, agriculture and food production, forestry, drought frequency and intensity, and human health 74 . Climate change has also affected the distribution of various species, although the effects vary depending on the species 41 , 62 . Mountainous plant communities around the world have been found to be diverse 75 , 76 .…”

Section: Discussionmentioning

confidence: 99%

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Habitat potential modelling and the effect of climate change on the current and future distribution of three Thymus species in Iran using MaxEnt

Hosseini,

Ghorbanpour,

Mostafavi

2024

Sci Rep

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Over the course of a few decades, climate change has caused a rapid and alarming reshaping of species habitats, resulting in mass extinction, particularly among sensitive species. In order to investigate the effects of climate change on species distribution and assess habitat suitability, researchers have developed species distribution models (SDMs) that estimate present and future species distribution. In West Asia, thyme species such as T. fedtschenkoi, T. pubescens, and T. transcaucasicus are rich in thymol and carvacrol, and are commonly used as herbal tea, spice, flavoring agents, and medicinal plants. This study aims to model the distribution of these Thymus species in Iran using the MaxEnt model under two representative concentration pathways (RCP 4.5 and RCP 8.5) for the years 2050 and 2070. The objective is to identify the crucial bioclimatic (n = 5), edaphic (n = 1), and topographic (n = 3) variables that influence their distribution and predict how their distribution might change under various climate scenarios. The findings reveal that the most significant variable affecting T. fedtschenkoi and T. pubescens is altitude, while soil organic carbon content is the primary factor influencing the distribution of T. transcaucasicus. The MaxEnt modeling demonstrates excellent performance, as indicated by all the area under the curve (AUC) values exceeding 0.9. Based on the projections, it is expected that these three thyme species will experience negative area changes in the coming years. These results can serve as a valuable tool for developing adaptive management strategies aimed at enhancing protection and sustainable utilization in the context of global climate change. Special attention should be given to conserving T. fedtschenkoi, T. pubescens, and T. transcaucasicus due to their significant habitat loss in the future.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Habitat potential modelling and the effect of climate change on the current and future distribution of three Thymus species in Iran using MaxEnt

Hosseini,

Ghorbanpour,

Mostafavi

2024

Sci Rep

View full text Add to dashboard Cite

show abstract

“…However, uncertainties in model predictions are inevitable, so the validity of predictions and model functionality assessment is critical. In the current study, standard deviation (STDEV), root-mean-square error (RMSE), Nash-Sutcliffe efficiency (NSE), RMSE-observations standard deviation ratio (RSR), correlation coefficient (COR), R-squared (R 2 ), Kling-Gupta efficiency (KGE), and percentage of bias (PBIAS) [89,91,92] are provided in five packages of the R platform for the functionality and precision of the models.…”

Section: Ls Susceptibility Modeling and Validation Mapmentioning

confidence: 99%

Land Subsidence Susceptibility Mapping Using Interferometric Synthetic Aperture Radar (InSAR) and Machine Learning Models in a Semiarid Region of Iran

Gharechaee

Samani

Sigaroodi

et al. 2023

Land

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Most published studies identify groundwater extraction as the leading cause of land subsidence (LS). However, the causes of LS are not only attributable to groundwater extraction. Other land-use practices can also affect the occurrence of LS. In this study, radar interferometric techniques and machine learning (ML) models were used for the prediction, susceptibility zoning, and prioritization of influential variables in the occurrence of LS in the Bakhtegan basin. The LS rate was characterized by applying an interferometric synthetic aperture radar (InSAR). The recursive feature elimination (RFE) method was used to detect and select the dominant combination of indicators to prepare an LS susceptibility map. Three ML models, including random forest (RF), k-nearest neighbors (KNN), and classification and regression trees (CART), were used to develop predictive models. All three models had acceptable performance. Among the ML models, the RF model performed the best (i.e., Nash–Sutcliffe efficiency, Kling–Gupta efficiency, correlation coefficient, and percent bias metrics of 0.76, 0.78, 0.88, and 0.70 for validating phase, respectively). The analysis conducted on all three ML model outputs showed that high and very high LS susceptibility classes were located on or near irrigated agricultural land. The results indicate that the leading cause of land LS in the study region is not due to groundwater withdrawals. Instead, the distance from dams and the proximity to anticlines, faults, and mines are the most important identifiers of LS susceptibility. Additionally, the highest probability of LS susceptibility was found at distances less than 18 km from synclines, 6 to 13 km from anticlines, 23 km from dams, and distances less than 20 to more than 144 km from mines. The validated methods presented in this study are reproducible, transferrable, and recommended for mapping LS susceptibility in semiarid and arid climate zones with similar environmental conditions.

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“…Xiao et al [11] comprehensively considered root length and root diameter of the vetiver plant, further improved the original formula for calculating root tensile strength, and obtained the relevant calculation model parameters for vetiver plant roots. Deljouei's research [12] shows that the main factor affecting the change in fine root tension is the DBH of tree species and sampling trees, In the follow-up study of Deljouei [13] it was found that the increase in RAR in different species also had an impact on the enhancement of root reinforcement. In addition, after considering the effect of DBH the elevation significantly affected the root reinforcement of C. betulus.…”

Section: Introductionmentioning

confidence: 99%

Influence of Vetiver Root Morphology on Soil–Water Characteristics of Plant-Covered Slope Soil in South Central China

Wang

Chen

et al. 2023

Sustainability

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The soil–water characteristic curve is an important tool to evaluate the water-holding capacity of unsaturated soil. Plant roots can affect the matric suction of soil and the water-holding capacity and permeability of the soil. Therefore, the morphological characteristics of plant roots will lead to the difference in soil–water characteristics between soil slope and plant-covered slope. This study aims to investigate the effect of Vetiver root morphology on soil–water characteristic curves of plant-covered slope soil. The hydrological effect of the root distribution on the root–soil system was also discussed. The results showed that: (1) The root surface area index (RAI) and root volume ratio (Rv) of each soil section of the vetiver root system varied with depth in accordance with the Gaussian function distribution; (2) In the process of natural drying, the matric suction generated within the root system is significantly higher than that generated by evaporation of bare soil in the same soil layer. The ability of vegetation soil to enhance soil matrix suction increases with the increase of soil root surface area index; and (3) The α and n values of the SWCC model decreased with the increase of Rv (root volume ratio of soil), while the air entry value increased. Under the same water content, the matric suction corresponding to vegetation soil is significantly greater than bare soil. In addition, the soil–water characteristic curve can be effectively predicted by combining the Rv of vegetated soils.

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Implications of hornbeam and beech root systems on slope stability: from field and laboratory measurements to modelling methods

Cited by 16 publications

References 106 publications

Habitat potential modelling and the effect of climate change on the current and future distribution of three Thymus species in Iran using MaxEnt

Habitat potential modelling and the effect of climate change on the current and future distribution of three Thymus species in Iran using MaxEnt

Land Subsidence Susceptibility Mapping Using Interferometric Synthetic Aperture Radar (InSAR) and Machine Learning Models in a Semiarid Region of Iran

Influence of Vetiver Root Morphology on Soil–Water Characteristics of Plant-Covered Slope Soil in South Central China

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