Considérations sur la trompe fibro-cartilagineuse et la région pharyngo-tubaire

Worms G., Coulouma , Van Varseveld . Considérations sur la trompe fibro-cartilagineuse et la région pharyngo-tubaire. In: Bulletins et Mémoires de la Société d'anthropologie de Paris, VIII° Série. Tome 7, 1936. pp. 29-57

Importance of the spatial extent for using soil properties estimated by laboratory VNIR/SWIR spectroscopy : examples of the clay and calcium carbonate content

Visible, near-infrared and short-wave infrared (VNIR/SWIR, 400-2500 nm) laboratory soil spectrometry is now considered to provide accurate estimations of primary soil properties (clay, calcium carbonate, iron, soil organic carbon, etc.). The performances of primary soil property prediction models are evaluated in regard to figures of merit calculated over calibration and validation databases but not in regard to the spatial extent of predicted soil samples. The objective of this study was to analyze regional model performances for soil property prediction at regional and within-field extents within contrasted representative geopedological situations. This study used a database of 240 soil samples collected over eight vineyard fields located in the Languedoc Region (southern France) (between 20 and 36 soil samples per field) for which VNIR/SWIR laboratory spectra were acquired and two soil physico-chemical properties (clay and calcium carbonate) were measured. Soil property prediction models were built using the classical partial least square regression (PLSR) method, which links the VNIR/SWIR laboratory spectra and the physico-chemical soil property. Our results showed that both clay and calcium carbonate prediction models are accurate at the regional extent, whereas prediction model performances at the within-field extent depend on the model robustness. Therefore, primary soil properties predicted by VNIR/SWIR laboratory spectra must be used with care at different extents

Regional predictions of eight commonsoil properties and their spatial structures from hyperspectral Vis-NIR data

International audienceThe potential of the visible-near infrared (Vis-NIR; 400-2500 nm) laboratory spectroscopy for the estimation of soil properties has been previously demonstrated in the literature, and the Vis-NIR spatial spectroscopy is expected to provide direct estimates of these properties at the soil surface. The aim of this work was to examine whether Vis-NIR airborne spectroscopy could be used for mapping eight of the most common soil properties, including clay, sand, silt, calcium carbonate (CaCO3), free iron, cation-exchange capacity (CEC), organic carbon and pH, without mispredicting the local values of these properties and their spatial structures. Our study was based on 95 soil samples and a HyMap hyperspectral image available over 192 bare soil fields scattered within a 24.6 km(2) area. Predictions of soil properties from HyMap spectra were computed for the eight soil properties using partial least squares regression (PLSR). The results showed that 1) four out of the eight soil properties (CaCO3, iron, clay and CEC) were suitable for mapping using hyperspectral data, and both accurate local predictions and good representations of spatial structures were observed and 2) the application of prediction models using hyperspectral data over the study area provided statistical characterizations within soilscape variations and variograms that describe in details the short range soil variations. All results were consistent with the previous pedological knowledge of the studied region. This study opens up the possibility of more extensive use of hyperspectral data for digital soil mapping of these successfully predicted soil properties

Unexpected predominance of wine grower location over soil trafficability for vine management in southern France

On a regional scale, many management concerns, such as agricultural planning and water contamination management, require information regarding the diversity and location of agricultural practices. One means of obtaining this information is to search for spatially explicit indicators that correspond to factors that drive agricultural practices. The objective of our study was to assess the role of soil trafficability on the distribution of soil surface management practices in a Mediterranean vine-growing region characterised by water contamination by herbicides. Soil surface management relies on different combinations of technologies such as shallow tillage, chemical weeding, and grass cover. We hypothesised that soils characterised by low trafficability were associated with the use of chemical weeding or grass cover in alleys that tractors use while spraying pesticides. Here, data on practices were collected by survey at the plot resolution. Soil trafficability was evaluated based on an expert classification of the soil units of a 1:25,000 soil map. Using classification trees, we tested the ability of the following three explanatory variables to determine the choice of practice: (1) the trafficability of the plot, (2) the percentage of plots with low trafficability within the vineyard of the farm holding, and (3) the wine grower residence place. Our results show that the trafficability classifies 59% of plots. The percentage of plots with low trafficability classifies 76% of plots. The wine grower residence place classifies 84% of the plots. Although the choice of practice correlated with soil trafficability, the residence place of the wine grower unexpectedly over-determined the practice choice. As a consequence, our findings evidence a spatial variability of the role of soil in the distribution of soil surface management practices. In addition, soil trafficability cannot be used as major indicator of the practice spatial distribution

A characterization of oblivious message adversaries for which Consensus is solvable

International audienceA characterization of oblivious message adversaries..

Effects of redistribution processes on rock fragment variability within a vineyard topsoil in Mediterranean France

In Mediterranean vineyard landscapes, to understand soil cover evolution at the landscape scale via soil redistribution, one must take into account soil and land use specificities. Soils are characterised by large quantities of rock fragments, and affect hydrological and erosion processes that have widely been published in the literature. Vineyards require a persistent cultivation pattern, and soil tillage operations can often affect vertical and lateral rock fragment distribution. The aim of this study is to analyse rock fragment content and variability in the topsoil (0-15 cm) of a Mediterranean vineyard to determine whether rock fragment distribution (2-64mm) at a farm plot is influenced by soil type and/or linked to environmental parameters. Furthermore, relationships between observed rock fragment distribution, tillage and water erosion processes are discussed. The field survey was based on a stratified sampling strategy, taking into account soil type, cultivation patterns and farm plot topography. The results suggest that the effect of cultivation in the row/inter-row system is more pronounced than the previously inferred topographic effect The long-term vineyard cultivation pattern induces spatial segregation of redistribution processes, with cumulative effects over several years that are responsible for rock fragment spatial variability in topsoil

Contrasting soil property patterns between ditch bed and neighbouring field profiles evidence the need of specific approaches when assessing water and pesticide fate in farmed landscapes

Farm ditch networks, infrastructures designed to regulate excess water in cropped landscapes, constitute pesticide dispersal pathways or buffer zones, depending on their soil properties. Despite the key role that ditch soils play in the regulation of water and pesticide fate, their properties, especially in intermittently flooded ditches, remain poorly characterized. Therefore, our aim was to evaluate the specificity of ditch material properties to determine whether ditches require an approach that differs from that of field soils when studying water and pesticide fate in farmed landscapes. We thus analysed the variations in the pedological, herbicide sorption and flow properties of soil materials along a 2D cross-section of an intermittently flooded ditch in the Roujan catchment of southern France. We found that the upper part of the ditch bed soil profile is composed of 3 horizons that formed after the original creation of the ditch, most likely via the deposition of field-eroded particles and the accumulation of organic matter. These specific horizons have greater porosity, mostly due to their dense root systems, and contain up to 2 times more organic carbon than the neighbouring banks or field soils. Consequently, the hydraulic conductivity is greater, and the sorption of hydrophobic herbicides is up to 2 times greater in ditch bed materials than it is in soils located farther away from the ditch surface. Moreover, significant macroporal flow was evidenced in both profiles but with different contribution to the global flow. The contrasts in the hydrodynamic and sorption properties between both the ditch bed and banks materials likely results in significantly different water and pesticide infiltration patterns in ditches compared to crop fields. Given these differences, we recommend investigating the specific properties of ditch beds when studying and modelling water and pesticide fate in croplands

Combining Vis-NIR hyperspectral imagery and legacy measured soil profiles to map subsurface soil properties in a Mediterranean area (Cap-Bon, Tunisia)

International audiencePrevious studies have demonstrated that Visible Near InfraRed (Vis-NIR) hyperspectral imagery is a cost-efficient way to map soil properties at fine resolutions (similar to 5 m) over large areas. However, such mapping is only feasible for the soil surface because the effective penetration depths of optical sensors do not exceed several millimeters. This study aims to determine how Vis-NIR hyperspectral imagery can serve to map the subsurface properties at four depth intervals (15-30 cm, 30-60 cm, 60-100 cm and 30-100 cm) when used with legacy soil profiles and images of parameters derived from digital elevation model (DEM). Two types of surface-subsurface functions, namely linear models and random forests, that estimate subsurface property values from surface values and landscape covariates were first calibrated over the set of legacy measured profiles. These functions were then applied to map the soil properties using the hyperspectral-derived digital surface soil property maps and the images of landscape covariates as input. Error propagation was addressed using a Monte Carlo approach to estimate the mapping uncertainties. The study was conducted in a pedologically contrasted 300 km(2)-cultivated area located in the Cap Bon region (Northern Tunisia) and tested on three soil surface properties (clay and sand contents and cation exchange capacity). The main results were as follows: i) fairly satisfactory (cross-validation R-2 between 0.55 and 0.81) surface-subsurface functions were obtained for predicting the soil properties at 15-30 cm and 30-60 cm, whereas predictions at 60-100 cm were less accurate (R-2 between 0.38 and 0.43); ii) linear models outperformed random-forest models in developing surface-subsurface functions; iii) due to the error propagations, the final predicted maps of the subsurface soil properties captured from 1/3 to 2/3 of the total variance with a significantly decreasing performance with depth; and iv) these maps brought significant improvements over the existing soil maps of the region and showed soil patterns that largely agreed with the local pedological knowledge. This paper demonstrates the added value of combining modern remote sensing techniques with old legacy soil databases. (C) 2013 Elsevier B.V. All rights reserved