Quantifying bioirrigation using ecological parameters: a stochastic approach†

Irrigation by benthic macrofauna has a major influence on the biogeochemistry and microbial community structure of sediments. Existing quantitative models of bioirrigation rely primarily on chemical, rather than ecological, information and the depth-dependence of bioirrigation intensity is either imposed or constrained through a data fitting procedure. In this study, stochastic simulations of 3D burrow networks are used to calculate mean densities, volumes and wall surface areas of burrows, as well as their variabilities, as a function of sediment depth. Burrow networks of the following model organisms are considered: the polychaete worms Nereis diversicolor and Schizocardium sp., the shrimp Callianassa subterranea, the echiuran worm Maxmuelleria lankesteri, the fiddler crabs Uca minax, U. pugnax and U. pugilator, and the mud crabs Sesarma reticulatum and Eurytium limosum. Consortia of these model organisms are then used to predict burrow networks in a shallow water carbonate sediment at Dry Tortugas, FL, and in two intertidal saltmarsh sites at Sapelo Island, GA. Solute-specific nonlocal bioirrigation coefficients are calculated from the depth-dependent burrow surface areas and the radial diffusive length scale around the burrows. Bioirrigation coefficients for sulfate obtained from network simulations, with the diffusive length scales constrained by sulfate reduction rate profiles, agree with independent estimates of bioirrigation coefficients based on pore water chemistry. Bioirrigation coefficients for O₂ derived from the stochastic model, with the diffusion length scales constrained by O₂ microprofiles measured at the sediment/water interface, are larger than irrigation coefficients based on vertical pore water chemical profiles. This reflects, in part, the rapid attenuation with depth of the O₂ concentration within the burrows, which reduces the driving force for chemical transfer across the burrow walls. Correction for the depletion of O₂ in the burrows results in closer agreement between stochastically-derived and chemically-derived irrigation coefficient profiles.     

Modelling the Effect of Tree Foliage on Sprayer Airflow in Orchards

The effect of tree foliage on sprayer airflow through pear trees in a fruit orchard was studied and modelled in detail. A new three-dimensional (3-D) computational fluid dynamics model that integrates the 3-D canopy architecture with a local closure model to simulate the effect of the stem and branches and leaves of trees separately on airflow was developed. The model was validated with field observations made in an experimental orchard (pcfruit, Sint-Truiden, Belgium) in spring and summer 2008 and was used to investigate the airflow from three air-assisted orchard sprayers (Condor V, Duoprop and AirJet quatt). Velocity magnitudes were measured before and behind leafless and fully-leafed pear canopies across the row while the operating sprayers are passing along the row, and were compared with the simulations. The simulation results predicted the measured values well with all the local relative errors within 20%. The effect of foliar density on airflow from the three air assisted sprayers was manifested by changing the magnitude and direction of the sprayers’ air velocity behind the canopy, especially at the denser regions of the canopy and by changing the pattern of velocity decay horizontally along the jet. The developed methodology will also allow a thorough investigation of atmospheric airflow in canopy structures.     

Depletion-induced seismicity in NW-Germany: lessons from comprehensive investigations

Acta Geotechnica - Evaluating various investigations for north-German gas fields, we discuss past and actual evolutions of the rock fabric in the light of dilatant driven and spontaneous...     

‘Observations and Modelling of Cold-air Advection over Arctic Sea Ice’

Aircraft observations of the atmospheric boundary layer (ABL) over Arctic sea ice were made during non-stationary conditions of cold-air advection with a cloud edge retreating through the study region. The sea-ice concentration, roughness, and ABL stratification varied in space. In the ABL heat budget, 80% of the Eulerian change in time was explained by cold-air advection and 20% by diabatic heating. With the cloud cover and inflow potential temperature profile prescribed as a function of time, the air temperature and near-surface fluxes of heat and momentum were well simulated by the applied two-dimensional mesoscale model. Model sensitivity tests demonstrated that several factors can be active in generating unstable stratification in the ABL over the Arctic sea ice in March. In this case, the upward sensible heat flux resulted from the combined effect of clouds, leads, and cold-air advection. These three factors interacted non-linearly with each other. From the point of view of ABL temperatures, the lead effect was far less important than the cloud effect, which influenced the temperature profiles via cloud-top radiative cooling and radiative heating of the snow surface. The steady-state simulations demonstrated that under overcast skies the evolution towards a deep, well-mixed ABL may take place through the merging of two mixed layers one related to mostly shear-driven surface mixing and the other to buoyancy-driven top-down mixing due to cloud-top radiative cooling.     

Orthit in den Gesteinen der Sonnblickgruppe (Hohe Tauern)

Summary Some types of Allanite (Orthite) are here described. They are found as assessory minerals in the rocks of the Hohe Tauern (penninic zone of the Eastern Alps) and in the hercynian foreland (Bohemian Massif). We distinguish Allanite I, II and III.The Allanite I (Hohe Tauern) is not isotropisized, but currently idiomorphic, with a xenomorphic rim of Clinozoisite. Where Allanite I is bordering Quartz or Potassium feldspar there is generally no rim of Clinozoisite. In the tectonites one observes granulated Allanite I and transformation of Allanite I to finegranied aggregates of Clinozoisite.Allanite II (Hohe Tauern) is found in intensely radioactive rocks. It is currently isotropisized, xenomorphic and surrounded by xenomorphic rims of Pistacite.Allanite III (Bohemian Massif) may be the oldest one and it is mostly isotropisized.The problems of the genesis and the age of crystallisation of Allanite during the history of our polymetamorphic rocks are shortly touched.

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Mit 11 Textabbildungen

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Herrn Prof. Dr.H. Leitmeier zum 80. Geburtstag gewidmet.     

Experimental determination of Ni diffusion coefficients in olivine and their dependence on temperature, composition, oxygen fugacity, and crystallographic orientation

Diffusion couple experiments were carried out with San Carlos olivine (Fo₉₀) and NiFe alloys (Ni₁₀₀, Ni₉₇Fe₃, Ni₉₀Fe₁₀) or other olivine compositions (Fo₁₀₀, Fo₂₅) in order to determine the dependence on temperature, oxygen fugacity, composition and crystallographic orientation of Ni diffusion coefficient (D_Ni) in olivine. Experiments at 1 atmosphere total pressure cover a temperature range of 900-1445°C with run durations from 48 to 2155 h at different oxygen fugacities. In an Arrhenius plot the best fit for all data for Fo₉₀ yields an activation energy (E_D) of 220 ± 14 kJ/mol and an fO₂ dependence of (1/4.25)·Δ log fO₂ = Δ log D_Ni. The relationship between diffusion coefficients along different crystallographic axes at 1200°C is given by D_[001] ≈ 6·D_[100] ≈ 6·D_[010]. D_Ni depends strongly on the major element (i.e. Fe/Mg) composition of olivine and decreases by about 1 order of magnitude as the olivine composition changes from Fo₃₅ to Fo₉₀. Thus, experimental investigations in Fe-free systems cannot be applied to natural samples. For calculation of residence times or cooling rates the present Ni data yield shorter timescales compared to those obtained using diffusion data published until now.In addition to Ni diffusion coefficients, Fe-Mg, Mn and Ca diffusion data were obtained from some of the same diffusion couples (Fo₉₀-Fo₁₀₀). It is found that the activation energies, E_D[Ni] ≅ E_D[Fe-Mg] ≅ E_D[Mn] ≤ E_D[Ca]. All diffusion coefficients are strongly dependent on the major element composition of olivine.