Cometary science at the launch of Rosetta

The launch of ESA's Rosetta mission, to orbit and land on a comet, has been postponed and the target of the mission may have to change. Uncertainty over the mission provoked extra interest at the RAS discussion meeting in December 2002, as Geraint Jones and Simeon Barber report.     

The electrical structure of the Slave craton

The Slave craton in northwestern Canada, a relatively small Archean craton (600×400 km), is ideal as a natural laboratory for investigating the formation and evolution of Mesoarchean and Neoarchean sub-continental lithospheric mantle (SCLM). Excellent outcrop and the discovery of economic diamondiferous kimberlite pipes in the centre of the craton during the early 1990s have led to an unparalleled amount of geoscientific information becoming available.

Over the last 5 years deep-probing electromagnetic surveys were conducted on the Slave, using the natural-source magnetotelluric (MT) technique, as part of a variety of programs to study the craton and determine its regional-scale electrical structure. Two of the four types of surveys involved novel MT data acquisition; one through frozen lakes along ice roads during winter, and the second using ocean-bottom MT instrumentation deployed from float planes.

The primary initial objective of the MT surveys was to determine the geometry of the topography of the lithosphere–asthenosphere boundary (LAB) across the Slave craton. However, the MT responses revealed, completely serendipitously, a remarkable anomaly in electrical conductivity in the SCLM of the central Slave craton. This Central Slave Mantle Conductor (CSMC) anomaly is modelled as a localized region of low resistivity (10–15 Ω m) beginning at depths of 80–120 km and striking NE–SW. Where precisely located, it is spatially coincident with the Eocene-aged kimberlite field in the central part of the craton (the so-called “Corridor of Hope”), and also with a geochemically defined ultra-depleted harzburgitic layer interpreted as oceanic or arc-related lithosphere emplaced during early tectonism. The CSMC lies wholly within the NE–SW striking central zone defined by Grütter et al. [Grütter, H.S., Apter, D.B., Kong, J., 1999. Crust–mantle coupling; evidence from mantle-derived xenocrystic garnets. Contributed paper at: The 7th International Kimberlite Conference Proceeding, J.B. Dawson Volume, 1, 307–313] on the basis of garnet geochemistry (G10 vs. G9) populations.

Deep-probing MT data from the lake bottom instruments infer that the conductor has a total depth-integrated conductivity (conductance) of the order of 2000 Siemens, which, given an internal resistivity of 10–15 Ω m, implies a thickness of 20–30 km. Below the CSMC the electrical resistivity of the lithosphere increases by a factor of 3–5 to values of around 50 Ω m. This change occurs at depths consistent with the graphite–diamond transition, which is taken as consistent with a carbon interpretation for the CSMC.

Preliminary three-dimensional MT modelling supports the NE–SW striking geometry for the conductor, and also suggests a NW dip. This geometry is taken as implying that the tectonic processes that emplaced this geophysical–geochemical body are likely related to the subduction of a craton of unknown provenance from the SE (present-day coordinates) during 2630–2620 Ma. It suggests that the lithospheric stacking model of Helmstaedt and Schulze [Helmstaedt, H.H., Schulze, D.J., 1989. Southern African kimberlites and their mantle sample: implications for Archean tectonics and lithosphere evolution. In Ross, J. (Ed.), Kimberlites and Related Rocks, Vol. 1: Their Composition, Occurrence, Origin, and Emplacement. Geological Society of Australia Special Publication, vol. 14, 358–368] is likely correct for the formation of the Slave's current SCLM.     

Vanadium in peridotites as a proxy for paleo-fO2 during partial melting : prospects, limitations, and implications

The compatibility of vanadium (V) during mantle melting is a function of oxygen fugacity (fO₂): at high fO₂’s, V becomes more incompatible. The prospects and limitations of using the V content of peridotites as a proxy for paleo-fO₂ at the time of melt extraction were investigated here by assessing the uncertainties in V measurements and the sensitivity of V as a function of degree of melt extracted and fO₂. V-MgO and V-Al₂O₃ systematics were found to be sensitive to fO₂ variations, but consideration of the uncertainties in measurements and model parameters indicates that V is sensitive only to relative fO₂ differences greater than ∼2 log units. Post-Archean oceanic mantle peridotites, as represented by abyssal peridotites and obducted massif peridotites, have V-MgO and -Al₂O₃ systematics that can be modeled by 1.5 GPa melting between FMQ − 3 and FMQ − 1. This is consistent with fO₂’s of the mantle source for mid-ocean ridge basalts (MORBs) as determined by the Fe³⁺ activity of peridotitic minerals and basaltic glasses. Some arc-related peridotites have slightly lower V for a given degree of melting than oceanic mantle peridotites, and can be modeled by 1.5 GPa melting at fO₂’s as high as FMQ. However, the majority of arc-related peridotites have V-MgO systematics overlapping that of oceanic mantle peridotites, suggesting that although some arc mantle may melt under slightly oxidizing conditions, most arc mantle does not. The fact that thermobarometrically determined fO₂’s in arc peridotites and lavas can be significantly higher than that inferred from V systematics, suggests that V retains a record of the fO₂ during partial melting, whereas the activity of Fe³⁺ in arc peridotitic minerals and lavas reflect subsequent metasomatic overprints and magmatic differentiation/emplacement processes, respectively.Peridotites associated with middle to late Archean cratonic mantle are characterized by highly variable V-MgO systematics. Tanzanian cratonic peridotites have V systematics indistinguishable from post-Archean oceanic mantle and can be modeled by 3 GPa partial melting at ∼FMQ − 3. In contrast, many South African and Siberian cratonic peridotites have much lower V contents for a given degree of melting, suggesting at first glance that partial melting occurred at high fO₂’s. More likely, however, their unusually low V contents for a given degree of melting may be artifacts of excess orthopyroxene, a feature that pervades many South African and Siberian peridotites but not the Tanzanian peridotites. This is indicated by the fact that the V contents of South African and Siberian peridotites are correlated with increases in SiO₂ content, generating data arrays that cannot be modeled by partial melting but can instead be generated by the addition of orthopyroxene through processes unrelated to primary melt depletion. Correction for orthopyroxene addition suggests that the South African and Siberian peridotites have V-MgO systematics similar to those of Tanzanian peridotites. Thus, if the Tanzanian peridotites represent the original partial melting residues, and if the South African and Siberian peridotites have been modified by orthopyroxene addition, then there is no indication that Archean cratonic mantle formed under fO₂’s significantly greater than that of modern oceanic mantle. Instead, the fO₂’s inferred from the V systematics in these three cratonic peridotite suites are within range of modern oceanic mantle. This also suggests that the transition from a highly reducing mantle in equilibrium with a metallic core to the present oxidized state must have occurred by late Archean times.     

Computational study of tetrahedral Al–Si and octahedral Al–Mg ordering in phengite

 As part of a wider study of the nature and origins of cation order–disorder in micas, a variety of computational techniques have been used to investigate the nature of tetrahedral and octahedral ordering in phengite, K₂ ^[6](Al₃Mg)^[4](Si₇Al)O₂₀(OH)₄. Values of the atomic exchange interaction parameters J _n used to model the energies of order–disorder were calculated. Both tetrahedral Al–Si and octahedral Al–Mg ordering were studied and hence three types of interaction parameter were necessary: for T–T, O–O and T–O interactions (where T denotes tetrahedral sites and O denotes octahedral sites). Values for the T–T and O–O interactions were taken from results on other systems, whilst we calculated new values for the T–O interactions. We have demonstrated that modelling the octahedral and tetrahedral sheets alone and independently produces different results from modelling a whole T–O–T layer, hence justifying the inclusion of the T–O interactions. Simulations of a whole T–O–T layer of phengite indicated the presence of short-range order, but no long-range order was observed. Received: 8 August 2002 / Accepted: 14 February 2003 Acknowledgements The authors are grateful to EPSRC (EJP) and the Royal Society (CIS) for financial support. Monte Carlo simulations were performed on the Mineral Physics Group's Beowulf cluster and the University of Cambridge's High Performance Computing Facility.     

Determination and application of the weights for landslide susceptibility mapping using an artificial neural network

The purpose of this study is the development, application, and assessment of probability and artificial neural network methods for assessing landslide susceptibility in a chosen study area. As the basic analysis tool, a Geographic Information System (GIS) was used for spatial data management and manipulation. Landslide locations and landslide-related factors such as slope, curvature, soil texture, soil drainage, effective thickness, wood type, and wood diameter were used for analyzing landslide susceptibility. A probability method was used for calculating the rating of the relative importance of each factor class to landslide occurrence. For calculating the weight of the relative importance of each factor to landslide occurrence, an artificial neural network method was developed. Using these methods, the landslide susceptibility index (LSI) was calculated using the rating and weight, and a landslide susceptibility map was produced using the index. The results of the landslide susceptibility analysis, with and without weights, were confirmed from comparison with the landslide location data. The comparison result with weighting was better than the results without weighting. The calculated weight and rating can be used to landslide susceptibility mapping.