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International audience; Le changement d’usage des terres et l’impact de l’anthropisation sur les milieux forestiers tropicaux sont en progression constante sous les tropiques et en Guyane française. Ces changements sont souvent accompagnés de défriches mécanisées qui favorisent la compaction du sol. Notre objectif était de suivre l’évolution de la compaction du sol d’une parcelle de forêt naturelle exploitée (7 ha) soumise à une défriche mécanisée alternative (itinéraire « chop and mulch », couvert herbacé de Stylosanthes guianensis), puis replantée de quatre espèces forestières commerciales. Sur cet espace présentant finalement diverses couvertures de sol (sol nu, mulch, couvert herbacé), nous avons mesuré la densité apparente jusqu’à 30 cm de profondeur et effectué le test d’infiltration simplifié de Beerkan lors de trois campagnes : avant, juste après et neuf mois après la défriche. Avant la défriche, les sols avaient une très bonne capacité d’infiltration (111 cm/h), étaient peu denses à 0-5 cm de profondeur (0,88) et denses à 5-30 cm (1,19 à 1,40). Juste après la défriche, les sols avaient une capacité d’infiltration très réduite (2 cm/h) et leur couche de surface avait été fortement compactée (1,28) contrairement aux couches plus profondes (1,41 à 1,49). Neuf mois après la défriche, les sols avaient retrouvé une très bonne capacité d’infiltration (149 cm/h), particulièrement sous le couvert herbacé de S. guianensis, et leur couche de surface avait retrouvé une densité proche de l’état initial (1,01), contrairement aux couches plus profondes (1,46 à 1,58). De futures recherches sont nécessaires pour expliquer le retour rapide à l’état initial de la couche de surface et estimer la contribution relative de la macrofaune du sol, des racines et de la fissuration.

International audience; Zinc (Zn) occurs naturally in soils, but spreading Zn-rich livestock manure on agricultural soils may lead to hazardous Zn levels. Interactions between exogenous Zn (from animal manure) and the soil matrix must be assessed to predict its behavior. We conducted soil density fractionation using sodium polytungstate solutions (LST) to isolate and identify the soil constituents and investigated their associations with Zn within five density fractions by characterizing the total organic carbon (TOC), mineralogy and Zn speciation. We analyzed a clayey Hapludox soil from a field experiment that had received pig slurry applications over an 11-year period, causing a 2-fold increase in the Zn concentration within the 0-5 cm layer relative to the control soil. Two density fractions with contrasting compositions were found: (i) a light fraction (

Assessing soil organic carbon (SOC) stocks is a methodological issue for SOC monitoring at regional scale but crucial for global agendas of SOC sequestration to mitigate climate change and reduce food insecurity. The ‘4 per mille Initiative: Soils for Food Security and Climate’, highlighted agricultural soil as a major lever for climate action and the need to assess SOC stock at different spatial and temporal scale. Infrared spectroscopy appeared as a promising tool to address this methodological issue. This work aimed to evaluate the potential of visible-near-infrared (VNIR) and mid-infrared (MIR) spectroscopic measurement methods to predict SOC stock and its variables (SOC content and bulk density) in tropical volcanic soils of ‘La Reunion’ island. The diversity of agricultural soils of ‘La Reunion’ was captured in the sample set (n = 95) with soil orders such as Andosols, Cambisols and Ferralsols. Partial least squares regressions (PLSR) with leave-one-out cross validation were used to build prediction models. With RPD higher than 2, the present study showed good prediction accuracy of models by MIR and VNIR spectroscopy of SOC content, bulk density and SOC stock for measurements in the laboratory or in the field. Accurate and direct SOC stock predictions were achieved on dried and sieved soil samples with MIR spectroscopy (RPD = 2.25; R2cv = 0.80; RMSEcv = 0.69 KgC m−2) and VNIR spectroscopy (RPD = 2.74; R2cv = 0.87; RMSEcv = 0.61 KgC m−2) but also directly on cores in the field with VNIR spectroscopy (RPD = 3.29; R2cv = 0.91; RMSEcv = 0.51 KgC m−2). This unexpected ability to predict directly SOC stocks by infrared spectroscopy can be partly explained by the high SOC content coupled with the large variation of SOC content and bulk density, providing a large range for those variables, and then a higher predictability. Yet these results questioned the underlying drivers of the bulk density and SOC stock, both being largely physical parameters supposed to be hardly predictable by infrared spectroscopy. Analyses of mean spectra and regression coefficients, combined with amorphous product (Alo, Feo, Sio, Alp, Fep) prediction models, demonstrated that these were detected in the spectra and were the drivers of SOC stock accurate predictions by infrared spectroscopy. Short-range ordered minerals, especially allophanes, appeared as proxy of the bulk density, and amorphous products such as Alp and Fep indicated the presence of organo-mineral complexes involved in SOC storage. Such promising results for SOC stock predictions from near- and mid-infrared volcanic soil spectra, confirmed that VNIR and MIR diffuse reflectance spectroscopy are an appropriate tool, rapid, low cost and non-destructive, to study SOC stocks in tropical volcanic soils. Upscaling of SOC stocks across the agricultural soils of the island is now just a step ahead, following external validation with additional data to validate the robustness of the prediction models.

Though soil bulk density (BD) is important for crop growth and land management, information about BD is often missing in soil database due to the fact that the determination of BD is time consuming and labor intensive. In order to fill this gap, pedotransfer functions (PTFs) have been developed for predicting bulk density during last decades. To avoid non-valid extrapolation, the validity domain of PTFs should be investigated. In this study, a PTFs for bulk density was built using GBM model on data from Region Centre and we tested its validity on data from mainland France except Region Centre. Standardized Euclidean distance was applied to distinguish dissimilar soil samples from Region Centre data and other regions data. The established PTFs were not suitable for predicting these dissimilar samples. In order to make a balance between prediction accuracy and the number of samples can be predicted with our PTFs, different cutoff limits of Standardized Euclidean distance was compared. When optimized distance cutoff limit was at 97%, compared to result without excluding dissimilar samples, RMSPE value on test data decreased from 0.179 to 0.163 g cm − 3 . An additional sampling strategy based on these dissimilar samples can improve the predictive ability of PTFs. We also suggest that the purposive sampling strategy or the systematic and dense sampling strategy will do large contribution in robust modelling of PTFs.

International audience; Soil aggregate stability is a key factor in soil resistance to water erosion, which is a threat to soils in a large part of northern Tunisia. The analysis of the spatial variability of soil aggregate stability provides both agronomic and environmentally useful information. However, extensive measurements of soil aggregate stability remain tedious and expensive. This study explores two different approaches as alternative to measurements of soil aggregate stability. One approach estimated aggregate stability via laboratory measurements of soil elementary properties using multiple linear regressions known as pedotransfer functions. The second approach, which is methodologically innovating, was based on the geological pattern as a proxy for aggregate stability using regression-kriging analysis. A set of 113 soil samples from an 800 km² agricultural region that included the Lebna watershed (Cap Bon, Tunisia) were collected from the soil surface layer (0-10 cm depth). Samples were analyzed for elementary properties (i.e., soil texture, total carbon and nitrogen, iron, CaCO3, salinity, CEC and pH) and for soil aggregate stability according to the normalized method (ISO/DIS 10930, 2012), which considers three indexes (MWD) calculated for three contrasted wetting conditions and disruptive energies. Most soils in the study area were non-salted with an alkaline pH and relatively low organic carbon content. Of the soils, 35% were clay soils, and 55% had a balanced soil texture. The average of the three soil aggregate stability indexes (MWDmean) ranged from 0.38 to 2.80 mm, and this property showed large variability from instable soils to very stable ones. Analysis of pedotransfer functions determined that the best predictor variables for soil aggregate stability were silt, organic matter and iron. Geostatistical analyses at the regional scale showed spatially structured soil aggregate stability (variograms with sills reaching a 5 km distance). Using geological information as ancillary data, the prediction of soil aggregate stability with regression-kriging was similar to that of pedotransfer functions. A regression-kriged map of soil aggregate stability associated with a map of prediction uncertainties was developed. The resulting maps and methods of this study can be useful in the development of management options that minimize water erosion risks in the studied area.

International audience; Increasingly mechanized timber harvesting and the repeated use of skid trail networks may affect ground vegetation differently at subsequent stages in the forest rotation. At a fine scale, no studies have yet compared the influence of micro-environmental factors and the effects of skid trail disturbance on ground flora diversity. We investigated understory diversity patterns on skid trails in 30-, 50- and 63-year-old oak forests in the northern half of France. Subplots were placed on skid trail center, wheel track, skid trail edge plus an off-trail control. At each subplot, we measured soil moisture, soil compaction (penetration resistance and bulk density) and photosynthetic active radiation and recorded the abundance of all vascular plants. The richness and abundance of ground flora were calculated based on the classification of their life form, seed bank persistence, light preference and moisture requirements. For each ecological group, we found out its best diversity indicator from subplot location, micro-environmental factors (soil moisture and compaction, light) and stand attributes (stand type, basal area), then assessed the magnitude and negligibility of the effect of the best indicator. (1) Higher soil compaction compared to controls was detected on the tracks of skid trails in the 50- and 63-year-old stands. Neither soil moisture nor light varied with subplot location whatever the stand type. (2) The best diversity indicator that showed non-negligible effects included subplot location, and soil moisture or soil compaction. Compared to controls, skid trails in the 50- and 63-year-old stands were richer in tree and short-term seed bank species, while skid trails in the 30-year-old plots had no effect on ground flora. The abundance of tree and shade-tolerant species was also higher on skid trails. Soil moisture was positively correlated with the richness of low- and high-humidity species, shade-tolerant species and transient seed bank species as well as with the abundance of short-term seed bank species. Bulk density positively affected heliophilous species richness, while penetration resistance was positively related to shrub abundance. Skid trails and soil compaction in our research area had either no impact or a positive impact on ground flora diversity. Longer-term studies of skid trail effects are needed to validate these main findings.

La profondeur de sol est une propriété importante à prendre en compte pour un grand nombre d’applications. La mesure directe par des méthodes destructives est ponctuelle et coûteuse. Les méthodes géophysiques sont citées comme alternative. Ce travail compare l’analyse des ondes de surface, la tomographie de résistivité électrique en conditions sèches et en diachronique pour estimer la profondeur de sol dans des contextes géo-pédologiques variés en milieu viticole méditerranéen. Les résultats montrent qu’aucune de ces méthodes n’est utilisable avec succès dans tous les contextes., Bedrock depth is an important property for a lot of environmental and agricultural applications. Direct estimates of bedrock depth from destructive soil observations are too costly for being extended to large areas. Geophysical methods are often cited as possible alternatives. This study examine the ability of the Spectral Analysis of Surface Waves (SASW) method combined with classical high resolution Electrical Resistivity Tomography (ERT) one to predict soil and rooting depths of vineyard soils in French Mediterranean area. Results showed that none of the two tested geophysical methods was able to predict soil depths in all pedological situations.

International audience; Pedotransfer functions (PTFs) are used to estimate certain soil properties that are difficult and costly to measure front others more easily available. Bulk density is one important soil property. Although nor requiring complex analysis, its measurement remains time consuming and is lacking in many soil surveys. For several decades, PTFs have been developed for predicting soil bulk density. Most of these PTFs are suited only for specific agro-pedo-climatic conditions, however, and can be applied only within a limited geographic area. In this study, we derived and experimented with two new PTFs based on a multiple additive regression trees (MART) method, and assessed their performance compared with existing PTFs when applied to a country-level soil database, the Reseau de Mesures de la Qualite des Sols (RMQS) survey network. This database was designed to include the major soil types and land uses in France. The first proposed PTF (Model m) involves only three predictors typically found in the existing PTFs for bulk density (C content and texture) and the second one (Model M) includes eight easily accessible quantitative and qualitative predictors (e.g., soil taxon). Both models significantly outperformed existing PTFs. Without arbitrarily partitioning the data set before fitting the model, the m and M MART models yielded R-2 values of 0.83 and 0.94, respectively. The predictive quality on independent data, assessed using cross-validation, was also improved compared with published PTFs, with R-2 reaching 0.62 and 0.66 and root mean square prediction errors of 0.123 and 0.117 Mg m(-3) for the two MAPT models.

International audience