The oxygen isotopic ratio of the sulphate remaining in the bacterial sulphate reduction has been found to be dependent on the oxygen isotopic ratio of the water in which the sulphate was reduced by bacteria. This finding is interpreted by a mechanism , in which the sulphate exchanges oxygen isotopes with the water through the inter mediates in the bacterial reduction of sulphate into sulphide .

Soil organic matter was extracted by a mixture of O * I M Na4P20,: O'IM NaOH from a chronosequence of weakly weathered soils developed on aeolian sand, and fractionated into humin (non-extractable), humic acid, and fulvic acid. The mass of total organic carbon in the profiles, the 14C content and the 13C/12C ratios were also determined.The weight of total carbon increased rapidly at first and then gradually without attaining a steady state. This trend was also shown by the humin and fulvic acid fractions, but the humic acid fraction appeared to have reached a maximum after about 3000 years. The order of total weights of the organic fractions was humin > fulvic acid > humic acid.The evidence suggests that the proportions of the humic fractions formed by decomposition are related to soil differences but not to vegetation. The greater part of the plant material found in the soils appears in the humin and fulvic acid fractions.

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Model evaluation is an important tool to help rate confidence in climate model simulations. This can add to the overall confidence assessment for future projections of the Australian climate. Additionally it can highlight significant model deficiencies that may affect the selection of a subset of models for use in impact assessment.Here we present results from an extensive model evaluation undertaken as part of the Natural Resource Management (NRM) Project in order to inform the newest set of climate change projections for Australia.The assessment covers mean climate skill over Australia as well as variability measures and teleconnections from up to 47 CMIP5 models and 23 CMIP3 models (for comparison where appropriate). Additionally, the skill in representing important climate features such as MJO, SAM, blocking and cut-off lows are also reviewed. Selected extremes are evaluated as well as simulations of two different types of downscaling simulations used within the NRM project. Finally, an attempt is made to synthesise this information in order to highlight a small group of CMIP5 models which show consistent deficiencies in representing the Australian climate and its features.