Distribution of calcareous nannoplankton in surface sediments along the northern KwaZulu-Natal Bight,South Africa

The coccolith assemblages from seafloor sediments over the inner shelf in the northern region of the KwaZulu- Natal Bight on the east coast of South Africa were identified and their distribution determined. In all, 29 Recent species and taxonomic groups, as well as 29 reworked species were recorded. The distribution of the Recent species appears to be governed by environmental features that have been documented in other studies: temperature, salinity, nutrient concentration and water circulation pattern, which reveals the long-term existence of a circulation cell in the sector between Durban Bay and the Thukela River. The outer edge of the cell consists of nutrient-enriched mixed layers and is characterised by an enhanced abundance of Gephyrocapsa oceanica, whereas the central region consists of a stratified nutrient-depleted water mass with elevated abundance of Umbilicosphaera sibogae, Florisphaera profunda, and a group of umbelliform species. The elevated levels of G. oceanica, coupled with the rarity of U. sibogae, F. profunda and the umbelliform species, confirm the presence of a permanent upwelling cell off Richards Bay. The maximum abundance of F. profunda found between Richards Bay and Lake Nhlabane indicates a region of nutrient-depleted (except for nitrite) conditions.     

Early Proterozoic,basaltic andesite tuff-breaccia: downslope,subaqueous mass transport of phreatomagmatically-generated tephra

At Bear Lake, in the Flin Flon-Snow Lake greenstone belt of Manitoba, 400⁺ m of thick-to very thick-bedded, generally ungraded, basaltic andesite tuff-breccia, breccia, and lapilli-tuff are intercalated with pillowed lava flows in the upper part of an early Proterozoic submarine basaltic andesite shield volcano. The fragmental rocks comprise angular, amygdaloidal blocks and lapilli, many with partial chilled selvages, in a matrix of blocky, non-amygdaloidal to highly amygdaloidal vitric basaltic andesite ash and small lapilli. Minor thin-to medium-bedded, commonly normally graded tuff occurs in the upper part of the sequence. Clasts in fragmental beds consistently have higher amygdule contents than intercalated lava flows. Although similar to pillow-fragment breccias, the Bear Lake fragmental rocks were produced by extended surtseyan-type, phreatomagmatic eruptions, with associated fire fountain activity, at a progressively subsiding, shallow water vent. Periodic tephra slumping generated debris flows that transported particles down the uppe, gentle slope of the volcano to a depositional site at a water depth of less than 1 km. Turbidity currents probably carried much fine tephra to deeper water; tuff was deposited in the preserved section only after explosive volcanism ceased.     

Structural features and mechanical behaviour of a pyroclastic weak rock

The results of an extensive programme of laboratory testing on intact and reconstituted samples of a pyroclastic weak rock from the volcanic complex of the Colli Albani (Central Italy) are presented. The deposit is known as Pozzolana Nera and may be assimilated to a bonded coarse grained material. The nature of bonds and the micro‐structural features were examined by means of diffractometry, optical and electron microscopy. As bonds are made of the same constituents of grains and aggregates of grains, bond deterioration and particles breakage upon loading are indistinguishable features of the mechanical behaviour. The testing programme consisted mainly of one‐dimensional and drained and undrained triaxial compression tests in a wide range of confining pressures up to 58 MPa. As confining stress increases, the mechanical behaviour of the material changes from brittle and dilatant to ductile and contractant; for both brittle and ductile behaviour failure is associated with the formation of shear surfaces separating the sample in several parts at the end of test. The experimental stress–dilatancy relationships are compared with the classical stress–dilatancy theories for a purely frictional material and for a material with friction and cohesion between particles. The analysis of the data indicates that peak strength results from the interplay between degradation of inter‐particle bonds, increasing friction between particles and increasing rate of dilation. Copyright © 2001 John Wiley & Son, Ltd.     

The XMM Cluster Survey: forecasting cosmological and cluster scaling-relation parameter constraints

We forecast the constraints on the values of  σ₈, Ω_m  and cluster scaling-relation parameters which we expect to obtain from the XMM Cluster Survey (XCS). We assume a flat Λ cold dark matter Universe and perform a Monte Carlo Markov Chain analysis of the evolution of the number density of galaxy clusters that takes into account a detailed simulated selection function. Comparing our current observed number of clusters shows good agreement with predictions. We determine the expected degradation of the constraints as a result of self-calibrating the luminosity–temperature relation (with scatter), including temperature measurement errors, and relying on photometric methods for the estimation of galaxy cluster redshifts. We examine the effects of systematic errors in scaling relation and measurement error assumptions. Using only  ( T , z )  self-calibration, we expect to measure Ω_m to ±0.03 (and  Ω_Λ  to the same accuracy assuming flatness), and σ₈ to ±0.05, also constraining the normalization and slope of the luminosity–temperature relation to ±6 and ±13 per cent (at 1σ), respectively, in the process. Self-calibration fails to jointly constrain the scatter and redshift evolution of the luminosity–temperature relation significantly. Additional archival and/or follow-up data will improve on this. We do not expect measurement errors or imperfect knowledge of their distribution to degrade constraints significantly. Scaling-relation systematics can easily lead to cosmological constraints 2σ or more away from the fiducial model. Our treatment is the first exact treatment to this level of detail, and introduces a new 'smoothed ML' (Maximum Likelihood) estimate of expected constraints.