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Abstract. Erosion is a relevant soil degradation factor in mountain agrosilvopastoral ecosystems that can be enhanced by the abandonment of agricultural land and pastures left to natural evolution. The on-site and off-site consequences of soil erosion at the catchment and landscape scale are particularly relevant and may affect settlements at the interface with mountain ecosystems. RUSLE (Revised Universal Soil Loss Equation) estimates of soil erosion consider, among others, the soil erodibility factor (K), which depends on properties involved in structure and aggregation. A relationship between soil erodibility and aggregation should therefore be expected. However, erosion may limit the development of soil structure; hence aggregates should not only be related to erodibility but also partially mirror soil erosion rates. The aim of the research was to evaluate the agreement between aggregate stability and erosion-related variables and to discuss the possible reasons for discrepancies in the two kinds of land use considered (forest and pasture). Topsoil horizons were sampled in a mountain catchment under two vegetation covers (pasture vs. forest) and analyzed for total organic carbon, total extractable carbon, pH, and texture. Soil erodibility was computed, RUSLE erosion rate was estimated, and aggregate stability was determined by wet sieving. Aggregation and RUSLE-related parameters for the two vegetation covers were investigated through statistical tests such as ANOVA, correlation, and regression. Soil erodibility was in agreement with the aggregate stability parameters; i.e., the most erodible soils in terms of K values also displayed weaker aggregation. Despite this general observation, when estimating K from aggregate losses the ANOVA conducted on the regression residuals showed land-use-dependent trends (negative average residuals for forest soils, positive for pastures). Therefore, soil aggregation seemed to mirror the actual topsoil conditions better than soil erodibility. Several hypotheses for this behavior were discussed. A relevant effect of the physical protection of the organic matter by the aggregates that cannot be considered in $K$ computation was finally hypothesized in the case of pastures, while in forests soil erodibility seemed to keep trace of past erosion and depletion of finer particles. A good relationship between RUSLE soil erosion rates and aggregate stability occurred in pastures, while no relationship was visible in forests. Therefore, soil aggregation seemed to capture aspects of actual vulnerability that are not visible through the erodibility estimate. Considering the relevance and extension of agrosilvopastoral ecosystems partly left to natural colonization, further studies on litter and humus protective action might improve the understanding of the relationship among erosion, erodibility, and structure.

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In highly weathered soils, such as tropical soils, organic phosphorus (P) may decline together with total P and could be represented by a relatively lower amount of inositol phosphates compared with temperate soils. The aim of this work was to understand the abiotic processes leading to inositol phosphate retention in highly weathered soils. Sorption of myo-inositol hexakisphosphate and inorganic phosphate (Pi) on two clay fractions (A and B) extracted from Brazilian oxisols was studied, examining both the extent of P retention and surface property modifications induced by anion sorption. The two clays were characterized by a high amount of crystalline iron oxides and kaolinite. In clay A, gibbsite was also present, plus a higher amount of organic matter. The two clays presented a similar specific surface area, but clay A had a lower microporosity. The amount of Pi sorbed on the two clays was similar, reaching a plateau at about 1.35 2mol m j2 , whereas the amount of myo-inositol hexakisphosphate was higher on clay A, 0.67 2mol m j2 , than clay B, 0.49 2mol m j2 . The retention of both P forms on the two clays was linked to the large presence of crystalline Fe and Al oxides. Whereas Pi adsorbed on the external surfaces and diffused into micropores, myo-inositol hexakisphosphate likely adsorbed only on the external surfaces. The precipitation of Al and Fe myo-inositol hexakisphosphate was also limited because of the small amounts of soluble Al and Fe forms. All these phenomena may contribute to justify the relatively low accumulation of these organic P compounds found in some highly weathered soils. (Soil Science 2008;173:694-706)

Spatially explicit knowledge of recent and past soil organic carbon (SOC) stocks in forests will improve our understanding of the effect of human- and non-human-induced changes on forest C fluxes. For SOC accounting, a minimum detectable difference must be defined in order to adequately determine temporal changes and spatial differences in SOC. This requires sufficiently detailed data to predict SOC stocks at appropriate scales within the required accuracy so that only significant changes are accounted for. When designing sampling campaigns, taking into account factors influencing SOC spatial and temporal distribution (such as soil type, topography, climate and vegetation) are needed to optimise sampling depths and numbers of samples, thereby ensuring that samples accurately reflect the distribution of SOC at a site. Furthermore, the appropriate scales related to the research question need to be defined: profile, plot, forests, catchment, national or wider. Scaling up SOC stocks from point sample to landscape unit is challenging, and thus requires reliable baseline data. Knowledge of the associated uncertainties related to SOC measures at each particular scale and how to reduce them is crucial for assessing SOC stocks with the highest possible accuracy at each scale. This review identifies where potential sources of errors and uncertainties related to forest SOC stock estimation occur at five different scales-sample, profile, plot, landscape/regional and European. Recommendations are also provided on how to reduce forest SOC uncertainties and increase efficiency of SOC assessment at each scale.