A Coupled Vegetation–Crust Model for Patchy Landscapes

Kinast, Shai; Ashkenazy, Yosef; Meron, Ehud

doi:10.1007/s00024-014-0959-8

Cited by 11 publications

(9 citation statements)

References 30 publications

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“…This process depends on the ability of the clonal species to protect the centre of the ring from the erosive action of wind, and on the ring size. More elaborated models can take this aeolian–soil feedback into account and treat the parameter f as a dynamic variable (e.g., Kinast, Ashkenazy, & Meron, ). The effect heterogeneity of soil characteristics has on ring formation and their pattern can be taken into account by inducing spatial disorder in the model parameters (Yizhaq et al, , ; Yizhaq & Bel, ).…”

Section: Discussionmentioning

confidence: 99%

“…More elaborated models can take this aeolian-soil feedback into account and treat the parameter f as a dynamic variable (e.g., Kinast, Ashkenazy, & Meron, 2016). The effect heterogeneity of soil characteristics has on ring formation and their pattern can be taken into account by inducing spatial disorder in the model parameters Yizhaq & Bel, 2016).…”

Section: Discussionmentioning

confidence: 99%

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Vegetation ring formation by water overland flow in water‐limited environments: Field measurements and mathematical modelling

et al. 2019

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Vegetation rings are a unique vegetation pattern found in drylands. Most examples are found in clonal plants growing in sandy soils with confined root zones. Using field measurements and numerical simulations, we found that water overland flow is a predominant mechanism that drives ring formation in the clonal species Asphodelus ramosus. In these rings, an infiltration contrast develops due to aeolian feedback between vegetation and wind‐induced particle transport. Fine particles settle at the patch's centre, reducing water infiltrability compared with that of its perimeter. In turn, this encourages the development of biological soil crust in the ring's centre, further decreasing water infiltration in this micro‐environment. These processes cause the development of surface run‐off source–sink relations between the ring's centre and perimeter. The outcome of this process is the formation of three different micro‐environments: the centre of the patch, characterized by low soil‐water content; its perimeter, characterized by higher soil‐water content; and the matrix, also characterized by higher soil‐water content. Competition for the water resource between the ramets at the perimeter and the ones at the centre leads to dieback, resulting in ring formation. Measurements of soil‐water content in rings of A. ramosus in the semiarid Negev of Israel throughout 5 years showed that the soil‐water content in the ring's centre is lower than that at its perimeter and matrix. These results are in accord with numerical simulations of a mathematical model for plant species with confined roots grown under highly seasonal rainfalls in water‐limited environments.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Vegetation ring formation by water overland flow in water‐limited environments: Field measurements and mathematical modelling

et al. 2019

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“…Banded vegetation has been reported in Central America, Africa, and Australia, where annual rainfall is low (50–750 mm) [ 5 , 6 , 7 , 8 , 9 ], and spotted vegetation has been described in Africa, America, and Asia [ 10 , 11 , 12 , 13 ], which does not appear to be specific to particular soils, parent materials, or plant species [ 3 ]. There is an ongoing debate on the formation mechanisms of vegetation patch patterns [ 14 , 15 , 16 , 17 , 18 , 19 ]. In general, it is acknowledged that water reallocation is a key to the establishment of patches.…”

Section: Introductionmentioning

confidence: 99%

Comparison of CBERS-04, GF-1, and GF-2 Satellite Panchromatic Images for Mapping Quasi-Circular Vegetation Patches in the Yellow River Delta, China

Liu

Huang

Liu

et al. 2018

Sensors

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Vegetation in arid and semi-arid regions frequently exists in patches, which can be effectively mapped by remote sensing. However, not all satellite images are suitable to detect the decametric-scale vegetation patches because of low spatial resolution. This study compared the capability of the first Gaofen Satellite (GF-1), the second Gaofen Satellite (GF-2), and China-Brazil Earth Resource Satellite 4 (CBERS-04) panchromatic images for mapping quasi-circular vegetation patches (QVPs) with K-Means (KM) and object-based example-based feature extraction with support vector machine classification (OEFE) in the Yellow River Delta, China. Both approaches provide relatively high classification accuracy with GF-2. For all five images, the root mean square errors (RMSEs) for area, perimeter, and perimeter/area ratio were smaller using the KM than the OEFE, indicating that the results from the KM are more similar to ground truth. Although the mapped results of the QVPs from finer-spatial resolution images appeared more accurate, accuracy improvement in terms of QVP area, perimeter, and perimeter/area ratio was limited, and most of the QVPs detected only by finer-spatial resolution imagery had a more than 40% difference with the actual QVPs in these three parameters. Compared with the KM approach, the OEFE approach performed better for vegetation patch shape description. Coupling the CBERS-04 with the OEFE approach could suitably map the QVPs (overall accuracy 75.3%). This is important for ecological protection managers concerned about cost-effectiveness between image spatial resolution and mapping the QVPs.

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“…It is worth mentioning that the current model also assumed that fracture network parameters are independent of landscape parameters. However, the tectonism that is related to the formation of superimposed fracture sets can also have a profound effect on landscape evolution (Lifton and Chase 1992;Kinast et al 2016). A high fractal dimension of landscape is usually found in the region under a very low uplift rate, which allows fully downcut by erosive streamflows, while a low fractal dimension of vegetation often occurs in the tectonic system with a high uplift rate due to the limited degradation time of landscapes (Lifton and Chase 1992).…”

Section: Discussionmentioning

confidence: 99%

Influence of Landscape Coverage on Measuring Spatial and Length Properties of Rock Fracture Networks: Insights from Numerical Simulation

Cao

Lei

2018

Pure Appl. Geophys.

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Abstract-Natural fractures are ubiquitous in the Earth's crust and often deeply buried in the subsurface. Due to the difficulty in accessing to their three-dimensional structures, the study of fracture network geometry is usually achieved by sampling two-dimensional (2D) exposures at the Earth's surface through outcrop mapping or aerial photograph techniques. However, the measurement results can be considerably affected by the coverage of forests and other plant species over the exposed fracture patterns. We quantitatively study such effects using numerical simulation. We consider the scenario of nominally isotropic natural fracture systems and represent them using 2D discrete fracture network models governed by fractal and length scaling parameters. The groundcover is modelled as random patches superimposing onto the 2D fracture patterns. The effects of localisation and total coverage of landscape patches are further investigated. The fractal dimension and length exponent of the covered fracture networks are measured and compared with those of the original non-covered patterns. The results show that the measured length exponent increases with the reduced localisation and increased coverage of landscape patches, which is more evident for networks dominated by very large fractures (i.e. small underlying length exponent). However, the landscape coverage seems to have a minor impact on the fractal dimension measurement. The research findings of this paper have important implications for field survey and statistical analysis of geological systems.

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A Coupled Vegetation–Crust Model for Patchy Landscapes

Cited by 11 publications

References 30 publications

Vegetation ring formation by water overland flow in water‐limited environments: Field measurements and mathematical modelling

Vegetation ring formation by water overland flow in water‐limited environments: Field measurements and mathematical modelling

Comparison of CBERS-04, GF-1, and GF-2 Satellite Panchromatic Images for Mapping Quasi-Circular Vegetation Patches in the Yellow River Delta, China

Influence of Landscape Coverage on Measuring Spatial and Length Properties of Rock Fracture Networks: Insights from Numerical Simulation

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