Podzolization processes were studied under heather (Calluna vulgaris L. Hull) and Crowberry (Empetrum nigrum L.) and sitka spruce [Picea sitchensis (Bong.) Carr] planted on former heathland at Hjelm Hede, Jutland, Denmark. The aim was to compare changes in soil‐water chemistry with changes in the solid‐state chemistry after vegetation change. Fourteen profiles under heather and five profiles under spruce were examined and soil water was collected in lysimeter wells from the bottom of individual soil horizons A, E, Bh, and Bs from four representative profiles. The investigated area has been heathland for more than 2000 yr and part of it was planted with sitka spruce in 1933. The sitka spruce litter provided a more acidic soil environment, and the taller canopy increased the deposition of seasalts. The acidifying effects were increased by increased evapotranspiration from the plantation compared with the heathland. The investigation indicates disturbance of the podzolization process under spruce. Soil‐water chemistry showed a lack of Al immobilization in the B horizon under spruce, contrary to the heather system. Analyses of the spruce soil reveal a depletion of pyrophosphate (PYR) extractable Al and Fe. The charge balance in soil water showed a high deficit of anions under spruce compared with the dissolved organic C (DOC) concentration. Therefore, the deficit cannot be exclusively ascribed to negative charge on DOC. Sources of anion deficit might include (i) dissociated organic acids (R‐COO−), (ii) reduction in positive charge because of the existence of organo‐metal complexes [R‐(COO)2Al+], and (iii) reduction in positive charge because of an inorganic pH‐dependent species distribution of Al [Al(OH)2+, Al(OH)+2
[1] Performing realistic simulations is crucial for developing, testing, and subsequently analyzing results of experiments sent to the surface of Mars. A wind tunnel has been constructed, in which the atmospheric conditions of pressure and wind speed are controlled to match those observed by the Pathfinder mission to Mars. Injection into the wind tunnel of an analogue dust from Salten Skov in Denmark allows simulation of the Martian aerosol. Here experiments can be tested in preparation for a planned mission to the planet (Mars Exploration Rovers to be launched in 2003). Observations of adhesion and cohesion effects have been made in the wind tunnel, which are relevant to particle transport and of significance for validating the performance of specific experiments on Mars. Preliminary studies have been made, at Mars atmospheric pressure, of dust capture on magnet arrays similar to those flown on the Mars Pathfinder mission.
Simple evapotranspiration models with few data requirements and Penman reference evapotranspiration for grass (Eref) limiting the actual evapotranspiration are often used to estimate chemical fluxes in ecosystems. The aim of this paper is to show how much the interception loss might exceed Eref in a wind-exposed Danish Sitka spruce stand and to demonstrate the importance of the evaluation of model performance, here represented by throughfall measurements and chemical fluxes. Precipitation, throughfall, soil moisture and soil water chemistry were measured monthly for 1.5 years. Model input was daily precipitation, Eref, leaf area index, root distribution and plant available water. The model interception loss was calculated using an empirical relationship between precipitation and interception loss that was calibrated against the measured interception loss. Interception loss was found to be unusually high, on average 58% of precipitation, which was supported by measurements from two other years with interception losses from 62–68% of precipitation. Transpiration and evaporation from soil were constrained by Eref. The modelled percolation was compared to percolation calculated by a chloride mass balance based on measured values. The percolation was only about 20% of precipitation due to the exceptionally high interception loss, which exceeded Eref by almost 50%. Therefore, in wind-exposed forest stands the interception loss should be modelled separately, as done here, and be calibrated on measured values.
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