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A field study of sediment movement through vegetative barriers was carried out to assess the sediment-trapping effectiveness of vegetative barrier types typically used in forest forest plantation management in south-east Queensland, Australia, and to develop a simple methodology for predicting sediment movement through these barriers. For sites at the centre of Queensland's 110 000 ha Pinus plantation and 45 000 ha Araucaria plantation program, small field flumes (plots) were established on a range of vegetation types and slope gradients, and sediment-laden flows passed through them. Sediment trapping in the plots was assessed by comparing paired samples taken from the inlet and outlet of the plots at pre-determined sampling times. Measurements included total sediment and equivalent size distributions of sediment particles (the latter measurements being based on settling velocities). For plots that did not erode, the degree of sediment trapping, if based on total sediment only, was quite variable. However, if rates of transport were considered in terms of the various size fractions, results were very consistent. A simple conceptual approach equating the vegetated area to a sedimentation pond allowed deposition to be calculated on the basis of settling velocity, flow depth, and residence time within the vegetated area. Estimated transport rates of sediment through the vegetated areas were in close agreement with measured transport rates, confirming the eciency of this approach. The results highlight a number of issues for management of sediment movement from forest estates.

The study evaluates and compares two procedures for selecting soil quality indicators (used for the construction of soil quality indices, SQI) by using diverse chemical, physical, and biological properties, and evaluates the role of soil microbiological properties in the construction of SQI. Different soil environments were selected from an extensive agricultural production site in the rolling pampa, Buenos Aires, Argentina. The plots included an undisturbed soil, a grassland soil, and continuous tilled soils with four different surface horizon depths (25, 23, 19, and 14 cm). Various properties were measured, and a minimum dataset was chosen by principal component analysis (PCA) considering all measured soil properties together (procedure A), or the PCA was performed separately according to classification as physical, chemical, or biological soil properties (procedure B). The measured soil properties involved physical, chemical, and biochemical properties determined by standard protocols used in routine laboratory analysis (simple SQI, SSQI) or more laborious protocols to determine microbial community structure and function by phospholipid fatty acid (PLFA) and catabolic response profile (CRP), respectively (complex SQI, CSQI). The selected properties were linearly normalised and integrated by the weight additive method to calculate SSQI A, SSQI B, CSQI A, and CSQI B indices. Two microbiological SQI (MSQI) were also calculated; MSQI 1 considered only biological properties according to the procedure used for calculating SQI; MSQI 2 was calculated by considering three selected microbiological parameters representing the size (microbial biomass carbon), activity (soil basal respiration), and functional diversity (evenness, determined by CRP) of the microbial communities. All of the constructed indices show the same differences among the study sites. The inclusion of CRP and PLFA data in the indices slightly increased, or did not increase, the index sensitivity. Microbiological indices had the same sensitivity as the indices integrated by physical, chemical, and biological properties. An evaluation of the SQI constructed by both procedures found no difference in sensitivity. However, SQI constructed by procedure B allowed evaluation of the effects of management practices on physical, chemical, and biological soil properties.