The potential effects of climate change on malaria transmission in Africa using bias-corrected regionalised climate projections and a simple malaria seasonality model

Climatic conditions such as relatively cold temperatures and dryness are able to limit malaria transmission. Climate change is therefore expected to alter malaria spread. A previous assessment of the potential impacts of climate change on the seasonality of malaria in Africa is revisited. Bias-corrected regional climate projections with a horizontal resolution of 0.5° are used from the Regional Model (REMO), which include land use and land cover changes. The malaria model employed is the climate-driven seasonality model (MSM) from the Mapping Malaria Risk in Africa project for which a comparison with data from the Malaria Atlas Project (MAP) and the Liverpool Malaria Model (LMM), and a novel validation procedure lends more credence to results. For climate scenarios A1B and B1 and for 2001–2050, REMO projects an overall drying and warming trend in the African malaria belt, that is largely imposed by the man-made degradation of vegetation. As a result, the malaria projections of the MSM show a decreased length of the malaria season in West Africa. The northern Sahel is no more longer suitable for malaria in the projections and shorter malaria seasons are expected for various areas farther south. In East Africa, higher temperatures and nearly unchanged precipitation patterns lead to longer transmission seasons and an increase in highland malaria. Assuming constant population numbers, an overall increase in person-months of exposure of up to 6 % is found. The results of this simple seasonality model are similar to previous projections from the more complex LMM. However, a different response to the warming of highlands is found for the two models. It is concluded that the MSM is an efficient tool to assess the climate-driven malaria seasonality and that an uncertainty analysis of future malaria spread would benefit from a multi-model approach.     

Spatio‐temporal variability of zooplankton biomass and environmental control in the Northern Benguela Upwelling System: field investigations and model simulation

Spatial and temporal distribution patterns of zooplankton are highly variable in the Northern Benguela Upwelling System. We studied the distribution of zooplankton (size class ≥ 0.33 mm) and used field data from four cruises that took place between March 2008 and February 2011, as well as simulation results of a regional ecosystem model. Remotely sensed sea surface temperatures (SST) and surface chlorophyll concentrations were analysed to investigate environmental influences on zooplankton biomass. The Intense Benguela Upwelling Index showed a distinct seasonal signal throughout the years and the highest upwelling peaks in August/September. Even though surface chlorophyll concentrations were very variable throughout the year, the highest concentrations were always detected in September, following the upwelling of nutrient‐rich water. In field catches, zooplankton biomass concentration in the upper 200 m was highest above the outer shelf and shelf‐break in December 2010 and February 2011, i.e. 6 months after the upwelling peaks. In contrast, zooplankton biomass simulated by the model in the surface water was highest in September. In March/April, biomass maxima were typically measured in the field at intermediate water depths, but the vertical distribution was also affected by extensive oxygen minimum zones. The ecosystem model reproduced this vertical pattern. Although general trends were similar, simulation data of zooplankton standing stocks overestimated the field data by a factor of 3. In upwelling systems, food webs are generally considered to be short and dominated by large cells. However, our field data indicate more small‐sized zooplankton organisms above the shelf than offshore.     

Indirect Tracking of Drop Bears Using GNSS Technology

Animal tagging and tracking has been a fundamental tool in the quest to increase our knowledge and understanding of biogeography and ecology for about 50 years. Monitoring animal populations is also necessary for conservation purposes and to limit negative effects on the human population, particularly in an era of human expansion into traditional animal habitats. The use of Global Navigation Satellite System (GNSS) technology has been responsible for significant advances in this field by providing the ability to obtain accurate, regular and frequent estimates of the changing distributions of many rare animal species. Employing conventional GNSS-based animal tracking methods to study drop bears is extremely difficult due to their habitat. The dense tree canopy regularly causes extended periods of complete GNSS signal loss, and sensors are often damaged during attacks on prey. This paper proposes an indirect, GNSS-based method for tracking drop bears. This involves tracking the prey rather than the predator in order to map the population of drop bears in a particular area. The method can be used to effectively estimate the number of drop bears in the study area. Analysis of the collected data provides valuable insights into the hunting behaviour of drop bears and has implications for a better understanding of the geographical distribution of other rare species, including hoop snakes and bunyips.     

Tropical cyclone hazard assessment using model-based track simulation

A method is introduced for assessing the probabilities and intensities of tropical cyclones at landfall and applied to data from the North Atlantic. First, a recently developed model for the basin-wide Monte-Carlo simulation of tropical cyclone tracks is enhanced and transferred to the North Atlantic basin. Subsequently, a large number of synthetic tracks is generated by means of an implementation of this model. This synthetic data is far more comprehensive than the available historical data, while exhibiting the same basic characteristics. It, thus, creates a more sound basis for assessing landfall probabilities than previously available, especially in areas with a low historical landfall frequency.     

On the computation of area probabilities based on a spatial stochastic model for precipitation cells and precipitation amounts

A main task of weather services is the issuing of warnings for potentially harmful weather events. Automated warning guidances can be derived, e.g., from statistical post-processing of numerical weather prediction using meteorological observations. These statistical methods commonly estimate the probability of an event (e.g. precipitation) occurring at a fixed location (a point probability). However, there are no operationally applicable techniques for estimating the probability of precipitation occurring anywhere in a geographical region (an area probability). We present an approach to the estimation of area probabilities for the occurrence of precipitation exceeding given thresholds. This approach is based on a spatial stochastic model for precipitation cells and precipitation amounts. The basic modeling component is a non-stationary germ-grain model with circular grains for the representation of precipitation cells. Then, we assign a randomly scaled response function to each precipitation cell and sum these functions up to obtain precipitation amounts. We derive formulas for expectations and variances of point precipitation amounts and use these formulas to compute further model characteristics based on available sequences of point probabilities. Area probabilities for arbitrary areas and thresholds can be estimated by repeated Monte Carlo simulation of the fitted precipitation model. Finally, we verify the proposed model by comparing the generated area probabilities with independent rain gauge adjusted radar data. The novelty of the presented approach is that, for the first time, a widely applicable estimation of area probabilities is possible, which is based solely on predicted point probabilities (i.e., neither precipitation observations nor further input of the forecaster are necessary). Therefore, this method can be applied for operational weather predictions.     

On the crystal structure and compressional behavior of talc: a mineral of interest in petrology and material science

The crystal structure of a natural triclinic talc (1Tc polytype) [with composition: (Mg_2.93Fe_0.06)_Σ2.99(Al_0.02Si_3.97)_Σ3.99O₁₀(OH)_2.10] has been investigated by single-crystal X-ray diffraction at 223 and 170 K and by single-crystal neutron diffraction at 20 K. Both the anisotropic X-ray refinements (i.e. at 223 and 170 K) show that the two independent tetrahedra are only slightly distorted. For the two independent Mg-octahedra, the bond distances between cation-hydroxyl groups are significantly shorter than the others. The ditrigonal rotation angle of the six-membered ring of tetrahedra is modest (α ~ 4°). The neutron structure refinement shows that the hydrogen-bonding scheme in talc consists of one donor site and three acceptors (i.e. trifurcated configuration), all the bonds having O···O ≤ 3.38 Å, H···O ~ 2.8 Å, and O–H···O ~ 111–116°. The three acceptors belong to the six-membered ring of tetrahedra juxtaposed to the octahedral sheet. The vibrational regime of the proton site appears being only slightly anisotropic. The elastic behavior of talc was investigated by means of in situ synchrotron single-crystal diffraction up to 16 GPa (at room temperature) using a diamond anvil cell. No evidence of phase transition has been observed within the pressure range investigated. P–V data fit, with an isothermal third-order Birch-Murnaghan equation of state, results as follows: V ₀ = 454.7(10) Å³, K _T0 = 56(3) GPa, and K′ = 5.4(7). The “Eulerian finite strain” versus “normalized stress” plot yields: Fe(0) = 56(2) GPa and K′ = 5.3(5). The compressional behavior of talc is strongly anisotropic, as reflected by the axial compressibilities (i.e. β(a):β(b):β(c) = 1.03:1:3.15) as well as by the magnitude and orientation of the unit-strain ellipsoid (with ε ₁:ε ₂:ε ₃ = 1:1.37:3.21). A comparison between the elastic parameters of talc obtained in this study with those previously reported is carried out.     

Einige geoelektrische Untersuchungen auf österreichischen Gletschern

Summary Experiments to determine the thickness of glaciers by high frequency prospecting were carried out on the Austrian glacier Hintereisferner in 1938. After the war electrohydrographical measurements on glacier rivulets were carried out in the Kaprun Valley. The resistance of the glacier water fluctuates according to the time of season. It depends on the respective composition of these waters (Fig. 2). Therefore the geologic and mineralogic properties of the glacier-water may be deducted from the electric resistance. Especially the amount of surface water may be deducted (Fig. 3). An example is shown in Fig. 4.