Christien Thiart

Preferential distribution along transcontinental corridors of kimberlites and related rocks of Southern Africa

Regional and local structural controls on the emplacement of 1326 Southern African kimberlites and related rocks (kimberlites sensu lato, 11% of which are dated) are analysed using a framework of lineaments defined by combining geology, aeromagnetics, gravity and geomorphological data. Spatial analysis of occurrences within clusters of kimberlites less than 100km across resolves variable trends, depending on the age and position of the cluster; but on a regional scale the distribution of these clusters is statistically controlled by four lineament trends: 040°, 096°, 134° and 165°. Similar regional trends are observed as aspect lineaments that can be followed over large distances from modelling the variation in dip direction of the Southern African topography. These observations suggest that different geological parameters exert a control on the distribution of kimberlites. Local structures may include en-echelon fault arrays, Riedel, R’-, P- or T-structures within trans-continental lithosphere structures (cryptic continental corridors). Many cryptic continental corridors are collinear with fracture zones along the Atlantic and Indian continental margins of Southern Africa, and may have found their origin in events resulting from plate reorganization during the break-up of the supercontinent Gondwana. Fault resistance may have rapidly changed the stress state of the African continent causing the deep lithospheric faults to be the loci of episodic extension, allowing kimberlite fluids to ascend through the faults and cluster within near-surface structures. A progressive age variation of kimberlite magmatism in Southern Africa may be attributed to stress propagation along deep lithospheric fractures.

Scent of a supercontinent: Gondwana's ores as chemical tracers—tin, tungsten and the Neoproterozoic Laurentia-Gondwana connection

Abstract The birth of Gondwana is inextricably linked to the break-up of the earlier Neoproterozoic supercontinent Rodinia. In detail, the Neoproterozoic reconstructions of Rodinia are unsolved and without them a detailed kinematic history of the birth of Gondwana cannot be constructed. This paper shows that Gondwanas ore deposits provide chemical “scents” that can be effectively used to trace the tectonic history of Gondwana; and the heterogenous distribution of Gondwanas ore deposits are used to evaluate Late Neoproterozoic reconstructions, which place Laurentia against West Gondwana along a common belt of Grenville age rocks. West Gondwana (including its Grenville-like rocks) is anomalously enriched in Sn and W relative to the rest of Gondwana. The Grenville Province of Laurentia and its immediate hinterland are devoid of Sn-W deposits and even occurrences of any significance. Therefore, Rodinia reconstructions which juxtapose East Laurentia against the west coast of South America result in juxtaposition of distinctly different metalliferous crustal blocks. These reconstructions may not be correct, and other models should be (re-)explored.

Predicting air pollution using fuzzy membership grade Kriging

Abstract A practical situation often facing us is that fuzzy spatial data are recorded as crisp real-valued numbers, e.g., a PM 10 record is 15.1, but we do know that it is an imprecise and vague observation. A new spatial analysis technique – fuzzy membership grade Kriging with semi-statistical membership, proposed by Guo has been developed to address fuzzy spatial data recorded as crisp numbers. In this paper, we will explain fuzzy membership grade Kriging, its root, its theory and its implementations. As an illustration, we will use PM 10 data of California, USA. Three sample membership functions are extracted from the data itself: linear, quadratic and hyperbolic tangent and applied to the PM 10 data. The predicted membership grades are also transformed back into PM 10 concentrations by using inverse functions in order to identify areas being dangerous to human health. Finally, we implement our new fuzzy membership grade Kriging in GIS.

Linking Spatial Statistics to GIS: exploring potential gold and tin models of Africa

The goal of this paper is a first attempt to link the geology and mineral deposits of the Gondwana GIS, called GO-GEOID, to spatial statistics and map modelling. Such integration allows, for example, meaningful identification of the mineral potential of unexplored regions relative to those around them that are known to host major ore deposits. We use gold and tin deposits of Africa to derive prescriptive and predictive potential mineral maps. In the case of the prescriptive output, techniques such as Boolean algebra or multicriteria analysis are explored together with the expert knowledge of the geologist (knowledge-driven models). In the case of the predictive output/models, map layers are combined using a Bayesian probabilistic framework; these models become data-driven and are more objective. Confidence in our predictive model for gold mineralisation is provided through validation against recently discovered gold deposits in Tanzania.

The Coupling of Regression Model and Differential Equation Model in GM (1, 1) Modeling and Extended GM (1, 1) Models

The GM (1,1) model is a small-sample based coupled data-assimilation approach with the advantages of highly predictive power and easy computations. However, in the standard GM (1,1) model building exercises we often face a statistical-grey inconsistency problem. Therefore, in this paper we examine the GM(1,1) model from its component-level and try to reveal an interactive coupling nature of differential equation model and corresponding regression model constituting of a GM(1,1) model. Based our analysis, we state a coupling principle for establishing an extended GM(1,1) model and further explore certain families of extended GM(1,1) models with statistical-grey consistency.

Identification of sources of environmental lead in South Africa from surface soil geochemical maps

The bioavailability of lead in soil is of considerable importance to human and animal health. Although selective extraction has been explored as a more appropriate technique than total heavy metal analysis in environmental pollution assessments, such studies remain scarce globally and are almost non-existent in developing countries. Results for a large-scale study of extractable lead levels in undisturbed soil samples in South Africa identify several geographic areas of concern. Lead levels are considerably elevated relative to background levels in the Johannesburg urban and industrial area. Areas of active lead mining also exhibit higher surface soil values. Interestingly, areas of active and intensive coal mining activity display relatively low soil Pb values, possibly attributable to the relatively low heavy metal content of South African coal. In all instances, distribution of cadmium, a carcinogenic element, correlates with that of lead. The results demonstrate the usefulness of the quick and easy Mehlich-3 single extractant technique, an established technique in micronutrient studies, to simultaneously provide valuable environmental data for toxic metals such as Pb and Cd.

Metallogenic fingerprints of Archaean cratons

Abstract Archaean cratons are fragments of old continents that are more richly endowed with mineral deposits than younger terrains. The mineral deposits of different cratons are also diversely enriched with useful (to humankind) chemical elements. Cratons are therefore mineral-diversity hotspots that represent regional geochemical heterogeneities in the early Earth, evidence for which remains encoded on each craton as unique metallogenic ‘fingerprints’. Some of the younger cratons (<3.0 Ga, e.g. Superior Province, Yilgarn and Zimbabwe) have strong Au, Cu, Pb and Zn imprints. Older (>3.0 Ga) cratons, however, are remarkably enriched in siderophile elements such as Ni, Cr, PGE, in both their crustal and mantle sections (e.g. Pilbara and Kaapvaal Cratons). Still other Archaean cratons are relatively enriched in Sn, W, U and Th (e.g. Amazonian, Leo-Man, Ntem and South China Cratons). How most of these fragments of old continents inherited their rich and diverse metallogenic characteristics is unresolved. Their dominant metallogenic inventories were formed near the time of their separation from the mantle; thereafter the inherited metals were frequently remobilized and redistributed during subsequent tectono-metamorphic, magmatic and erosion-deposition processes (e.g. tin in South America; platinum and gold in Southern Africa). Because different cratons are likely to represent only small remnants of once much larger and probably varied Archaean continents, part of the total metal inventories of Archaean continents must have been recycled back into the mantle. Using six selected element groups from our extensive in-house GIS database of Gondwana mineral deposits, we derive the metallogenic fingerprints of 11 Archaean cratons of the southern hemisphere, and compare these against metallogenic fingerprints of the same elements in younger crust of three continents (Africa, Australia and South America). We confirm that the mineral deposit density and diversity of Earth’s continental lithosphere has decreased with time. We conclude that metallogenic elements were transferred more efficiently from the mantle to the continental lithosphere in the Archaean and/or that subsequently (<2.5 Ga) recycling of these elements (mineral deposits) back into the mantle became more effective.

Imprecise Uncertainty Modelling of Air Pollutant PM10

Particulate matter (PM) refers to solid particles and liquid droplets found in air. Many manmade and natural sources produce PM directly, or produce pollutants that react in the atmosphere to form PM. The resultant solid and liquid particles come in a wide range of sizes, and particles that are 10 micrometers or less in diameter (PM

DEMR embedded models in density saddlepoint approximations

In this paper we review the small asymptotic theory, particularly, the saddlepoint approximation to the density of sample mean and M-estimator. Furthermore, we merge the univariate differential equation motivated regression model, abbreviated as DEMR model, into small sample asymptotic theory, which is called saddlepoint approximation with embedded DEMR model. Two cases are briefly considered: DEMR embedded as a mean, and DEMR embedded as an M-estimator, with or without the knowledge of underlying distribution function from which the observation data sampled.

Climate Change Impact on Quiver Trees in Arid Namibia and South Africa

The climate fluctuates and changes naturally, and adding the common problems of land transformation and deforestation, its impact can be very harsh on the natural environment, and cause a decline in the biodiversity of plants and animals. Aloe dichotoma, common name Quiver tree, is an important part of the arid regions, such as Namaqualand and Bushmanland in South Africa, and in arid parts of southern Namibia. This succulent tree species occurs in rocky areas, and it can grow quite rapidly under the right conditions. Succulents are able to survive long periods of drought conditions, due to the fact succulent plants has special water-storing tissue which makes part of the plant fleshy, and the Quiver tree has succulent leaf and stem (Van Wyk and Smith, 1996). The Quiver tree has a 200 year life span, and can grow up to 9 meters tall, and it occurs in summer and winter rainfall regions, and can live under a variety of climatic conditions (Fig. 1). The Quiver tree is important to the ecosystem due to the fact that it is as a source of moisture for a wide variety of mammals, birds, and insects. Foden’s detailed study of the demographic data of the Quiver trees show that negligible recruitment has occurred in certain populations for 50 years, and the effects of non-climatic variables, such as herbivory, competition, seed availability, fungal pathogens, plant collection... are very small (Foden, 2002). Today, the Quiver trees are threatened by agricultural expansion, overgrazing, and mining, as well as droughts and other climate changes (Foden, 2002). Climate changes is one of the major factors affecting the existence of Quiver trees, while the Quiver tree will unlikely to be affected by small climatic fluctuations, but will be affected larger or long term climatic changes. The Quiver tree can potentially provide a good indication of long term climate changes in the arid regions (Foden, 2002). Previous onsite observations show that Quiver trees are very sensitive to temperature changes, and does not do well under extreme hot and dry conditions. Observations has also shown that the Quiver trees might be responding to higher temperatures by shifting its distribution range towards higher and higher altitudes, showing a preference for slightly cooler regions (Midgley et al., 2009).