Pore, live root and necromass quantification in complex heterogeneous wetland soils using X-ray computed tomography

Chirol, Clémentine; Carr, Simon; Spencer, Kate L.; Moeller, Iris

doi:10.1016/j.geoderma.2020.114898

Cited by 15 publications

(5 citation statements)

References 68 publications

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“…Compared with previous studies, the development of a novel segmentation technique combining local adaptive thresholding and tubular shape detection gives us greater confidence in our capacity to capture the complexity of a saltmarsh subsurface environment: ground referencing tests confirmed that the μCT data accurately capture regions of dense roots as well as the position and structures of macropores (Chirol et al, 2021). Using μCT morphological data under various types of ground cover and under different sediment types allows us to explore the potential role of subsurface structure on shear strength with an unprecedented perspective on the 3D structure and interplay of pores and roots.…”

Section: Discussionmentioning

confidence: 89%

“…The scanned volumes were cropped to an 8.75 × 8.75 cm square base to reduce edge effects and remove any disturbance from sampling. All 24 scanned volumes were processed following the method detailed in Chirol et al (2021) to segment the μCT data into three phases: pore space, organic matter elements (including roots and degraded organic matter) and finally the bulk inorganic mineral phase. All elements larger than 5000 voxels (1.22 mm 3 ) were removed as noise, and the minimal thickness of elements at any point is twice the resolution, so 125 μm.…”

Section: Methodsmentioning

confidence: 99%

“…Episodes of storm surges, colonization by burrowing organisms, or colonization and die‐off of plants may be recorded as sedimentary features, and therefore subsurface features may be critical to interpreting surface information and marsh response. Recent studies have developed new approaches for root analysis (Chirol et al, 2021), which allow us to capture the complexity of heterogeneous saltmarsh substrates with unprecedented precision.…”

Section: Introductionmentioning

confidence: 99%

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Effect of vegetation cover and sediment type on 3D subsurface structure and shear strength in saltmarshes

Chirol

Spencer

Carr

et al. 2021

Earth Surf Processes Landf

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The vulnerability of saltmarshes to lateral erosion at their margin depends on the local biogeomorphological properties of the substrate. In particular, the 3D architecture of pore and root systems is expected to influence shear strength, with repercussions for the wider-scale stability of saltmarshes. We apply X-ray computed microtomography (μCT) to visualize and quantify subsurface structures in two UK saltmarshes at Tillingham Farm, Essex (silt/clay rich substrate) and Warton Sands (sand-rich substrate), with four types of ground cover: bare ground, Spartina spp, Salicornia spp and Puccinellia spp. We extracted μCT structural parameters that characterize pore and root morphologies at each station, and compared them with field measurements of shear strength using a principal component analysis and correlation tests. The 3D volumes show that species-dependent variations in root structures, plant colonization events and bioturbation activity control the morphology of macropores, while sediment cohesivity determines the structural stability and persistence of these pore structures over time, even after the vegetation has died. Areas of high porosity and high mean pore thickness were correlated to lower values of shear strength, especially at Tillingham Farm, where wellconnected vertical systems of macropores were associated with current or previous colonization by Spartina spp. However, while well-connected systems of macropores may lower the local deformation threshold of the sediment, they also encourage drainage, promote vegetation growth and reduce the marsh vulnerability to hydrodynamic forces. The highest values of shear strength at both sites were found under Puccinellia spp, and were associated with a high density of mesh-like root structures that bind the sediment and resist deformation. Future studies of marsh stability should ideally consider time series of vegetation cover, especially in silt/clay-dominated saltmarshes, in order to consider the potential effect of preserved buried networks of macropores on water circulation, marsh functioning and cliff-face erosion.

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Section: Discussionmentioning

confidence: 89%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Effect of vegetation cover and sediment type on 3D subsurface structure and shear strength in saltmarshes

Chirol

Spencer

Carr

et al. 2021

Earth Surf Processes Landf

Self Cite

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“…Medicinal computed tomography image analysis facilitates studying the 3D root morphology of vegetation in undisturbed tidal marsh soils (Davey et al, 2011;Blum and Davey, 2013;Hanson et al, 2016;Wigand et al, 2016). CT-scanning enables the distinction of air-spaces, organic structures and mineral particulates by means of a standardized X-ray response (Hounsfield units HU;Hounsfield, 1979), which allows the 3D root-system structures (root-tissue and root-aerenchyma) to be reconstructed in-silico using segmentation and skeleton analysis methods (Gao et al, 2019;Chirol et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Subsurface aeration of tidal wetland soils: Root-system structure and aerenchyma connectivity in Spartina (Poaceae)

Granse

Titschack

Aïnouche

et al. 2022

Science of The Total Environment

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“…[6,7], are limited in their application and development due to their heavy workload, destructive sampling approach and unachievable repeated measurements [8]. With the innovation and development of technology, some in situ non-destructive observation methods have become the hotspots of plant root parameter estimation and distribution modeling research [9], such as minirhizotrons [10], X-ray Computed Tomography (CT) [11], magnetic resonance imaging (MRI) [12], ground-penetrating radar (GPR) method [13][14][15][16], etc. Among them, GPR is a non-intrusive geophysical technology that uses high-frequency electromagnetic waves to locate underground targets [17].…”

Section: Introductionmentioning

confidence: 99%

Theoretical Development of Plant Root Diameter Estimation Based on GprMax Data and Neural Network Modelling

Liang

Fan

et al. 2021

Forests

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The in situ non-destructive quantitative observation of plant roots is difficult. Traditional detection methods are not only time-consuming and labor-intensive, but also destroy the root environment. Ground penetrating radar (GPR), as a non-destructive detection method, has great potential in the estimation of root parameters. In this paper, we use GprMax software to perform forward modeling of plant roots under different soil dielectric constants, and analyze the situation of plant roots with different dielectric constants and different root diameters under 1.5 GHz frequency antenna detection. Firstly, root systems with increasing diameter under different values of root and soil dielectric constant were scanned. Secondly, from the scanning results, two time points T1 and T2 of radar wave entering and penetrating the root system were defined, and the correlation between root diameter D and time interval ∆T between T1 and T2 was analyzed. Finally, the least square regression model and back propagation (BP) neural network model for root diameter parameter estimation were established, and the estimation effects of the two models were compared and evaluated. The research results show that the root diameter (12–48 mm) is highly correlated with the time interval. Given the dielectric constants of the root and soil, the prediction results of the two models are accurate, but the prediction result of the neural network model is more stable, and the residual between the predicted value and the actual value is mainly concentrated in the [−1.5 mm, 1.5 mm] range, as well as the average of prediction error percentage being 3.62%. When the dielectric constants of the root and soil are unknown, the accuracy of the prediction results of the two models is decreased, but the stability of the neural network model is still superior to the least squares model, and the residual error is mainly concentrated in the range of [−5.3 mm, 5.0 mm], the average of prediction error percentage is 10.19%. This study uses GprMax to simulate root system detection and reveals the theoretical potential of GPR technology for non-destructive estimation of root diameter parameters. It is also pointed out that in the field exploration process, if the dielectric constants of the root and soil in the experimental site are sampled and measured first, the prediction accuracy of the model for root diameter would be effectively improved. This research is based on simulation experiments, so further simulation followed by laboratory and field testing is warranted using non-uniform roots and soil.

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Pore, live root and necromass quantification in complex heterogeneous wetland soils using X-ray computed tomography

Cited by 15 publications

References 68 publications

Effect of vegetation cover and sediment type on 3D subsurface structure and shear strength in saltmarshes

Effect of vegetation cover and sediment type on 3D subsurface structure and shear strength in saltmarshes

Subsurface aeration of tidal wetland soils: Root-system structure and aerenchyma connectivity in Spartina (Poaceae)

Theoretical Development of Plant Root Diameter Estimation Based on GprMax Data and Neural Network Modelling

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