Prediction of sediment transport capacity based on slope gradients and flow discharge.

Sediment transport capacity (Tc) is an essential parameter in the establishment of the slope soil erosion model. Slope type is an important crucial factor affecting sediment transport capacity of overland flow, and vegetation can effectively inhibit soil loss. Two new formulae of sediment transport capacity (Tc) are proposed of brown soil slope and vegetation slope in this study and evaluate the influence of slope gradient (S) and flow discharge (Q) on sediment transport capacity of different slope types. Laboratory experiments conducted using four flow discharges (0.35, 0.45, 0.55, and 0.65 L s-1), four slope gradients (3, 6, 9, and 12°), and two kinds of underlying surface (Brown soil slope, Vegetation slope). The soil particle size range is 0.05-0.5mm. The vegetation stems were 2mm in diameter and randomly arranged. The results show that the sediment transport capacity was positively correlated with the flow discharge and slope gradient. The vegetation slope's average sediment transport capacity is 11.80% higher than the brown soil slope that same discharge and slope gradient conditions. The sensitivity of sediment transport capacity to flow discharge on brown soil slope is higher than that of slope gradient. The sensitivity of sediment transport capacity of vegetation slope to slope gradient is more heightened than flow discharge. The sediment transport capacity was well predicted by discharge and slope gradient on brown soil slope (R2 = 0.982) and vegetation slope (R2 = 0.993). This method is helpful to promote the study of the sediment transport process on overland flow.

Plant structural diversity alters sediment retention on and underneath herbaceous vegetation in a flume experiment.

Sediment retention is a key ecosystem function provided by floodplains to filter sediments and nutrients from the river water during floods. Floodplain vegetation is an important driver of fine sediment retention. We aim to understand which structural properties of the vegetation are most important for capturing sediments. In a hydraulic flume experiment, we investigated this by disentangling sedimentation on and underneath 96 vegetation patches (40 cm x 60 cm). We planted two grass and two herb species in each patch and conducted a full-factorial manipulation of 1) vegetation density, 2) vegetation height, 3) structural diversity (small-tall vs tall-tall species combinations) and 4) leaf pubescence (based on trait information). We inundated the vegetation patches for 21 h in a flume with silt- and clay-rich water and subsequently measured the amount of accumulated sediment on the vegetation and on a fleece as ground underneath it. We quantified the sediment by washing it off the biomass and off the fleece, drying the sediment and weighting it. Our results showed that all manipulated vegetation properties combined (vegetation density and height, and the interaction of structural diversity and leaf pubescence) explained sedimentation on the vegetation (total R2 = 0.34). The sedimentation underneath the vegetation was explained by the structural diversity and the leaf pubescence (total R2 = 0.11). We further found that vegetation biomass positively affected the sedimentation on and underneath the vegetation. These findings are crucial for floodplain management strategies with the aim to increase sediment retention. Based on our findings, we can identify management strategies and target plant communities that are able to maximize a floodplain's ability to capture sediments.

Assessing spatial variability of soil organic carbon and total nitrogen in eroded hilly region of subtropical China.

The hilly red soil region of southern China suffers from severe soil erosion that has led to soil degradation and loss of soil nutrients. Estimating the content and spatial variability of soil organic carbon (SOC) and soil total nitrogen (STN) and assessing the influence of topography and land-use type on SOC and STN after years of soil erosion control are important for vegetation restoration and ecological reconstruction. A total of 375 topsoil samples were collected from Changting County, and their SOC and STN distributions were studied by using descriptive statistics and geostatistical methods. Elevation, slope, aspect and land-use type were selected to investigate the impacts of natural and human factors on the spatial heterogeneity of SOC and STN. The mean SOC and STN concentrations were 15.85 and 0.98 g kg-1 with moderate spatial variations, respectively. SOC and STN exhibited relatively uniform distributions that decreased gradually from the outside parts to the center of the study area. The SOC and STN contents in the study area were still at moderate and low levels after years of erosion control, which suggests that soil nutrient improvement is a slow process. The lowest SOC and STN values were at lower elevations in the center of Changting County. The results indicated that the SOC and STN contents increased most significantly with elevation and slope due to the influence of topography on the regional natural environment and soil erosion in the eroded hilly region. No significant variations were observed among different slope directions and land-use types.

Micro-scale interactions between Arabidopsis root hairs and soil particles influence soil erosion.

Soil is essential for sustaining life on land. Plant roots play a crucial role in stabilising soil and minimising erosion, although these mechanisms are still not completely understood. Consequently, identifying and breeding for plant traits to enhance erosion resistance is challenging. Root hair mutants in Arabidopsis thaliana were studied using three different quantitative methods to isolate their effect on root-soil cohesion. We present compelling evidence that micro-scale interactions of root hairs with surrounding soil increase soil cohesion and reduce erosion. Arabidopsis seedlings with root hairs were more difficult to detach from soil, compost and sterile gel media than those with hairless roots, and it was 10-times harder to erode soil from roots with than without hairs. We also developed a model that can consistently predict the impact root hairs make to soil erosion resistance. Our study thus provides new insight into the mechanisms by which roots maintain soil stability.