Paleoenvironmental and Human Behavioral Implications of the Boegoeberg 1 Late Pleistocene Hyena Den, Northern Cape Province, South Africa

Boegoeberg 1 (BOG1) is located on the Atlantic coast of South Africa, 850 km north of Cape Town. The site is a shallow rock shelter in the side of a sand-choked gully that was emptied by diamond miners. Abundant coprolites, chewed bones, and partially digested bones implicate hyenas as the bone accumulators. The location of the site, quantity of bones, and composition of the fauna imply it was a brown hyena nursery den. The abundance of Cape fur seal bones shows that the hyenas had ready access to the coast. Radiocarbon dates place the site before 37,000 ¹⁴C yr ago, while the large average size of the black-backed jackals and the presence of extralimital ungulates imply cool, moist conditions, probably during the early part of the last glaciation (isotope stage 4 or stage 3 before 37,000 ¹⁴C yr ago) or perhaps during one of the cooler phases (isotope substages 5d or 5b) within the last interglaciation. Comparisons of the BOG1 seal bones to those from regional Middle Stone Age (MSA) and Later Stone Age (LSA) archeological sites suggest (1) that hyena and human seal accumulations can be distinguished by a tendency for vertebrae to be much more common in a hyena accumulation and (2) that hyena and LSA accumulations can be distinguished by a tendency for hyena-accumulated seals to represent a much wider range of individual seal ages. Differences in the way hyenas and people dismember, transport, and consume seal carcasses probably explain the contrast in skeletal part representation, while differences in season of occupation explain the contrast in seal age representation. Like modern brown hyenas, the BOG1 hyenas probably occupied the coast year-round, while the LSA people focused their coastal visits on the August–October interval when nine-to-eleven-month-old seals were abundant. The MSA sample from Klasies River Mouth Cave 1 resembles BOG1 in seal age composition, suggesting that unlike LSA people, MSA people obtained seals more or less throughout the year.     

The cosmic ray energy spectrum between 10 and 10 eV

The energy spectrum of cosmic rays with primary energies between 10¹⁴ eV and 10¹⁶ eV has been studied with the CASA-MIA air shower array. The measured differential energy spectrum is a power law (dj/dE ∝ E^−y) with spectral indices γ of 2.66±0.02 below approximately 10¹⁵ eV and 3.00±0.05 above. A new method is used for measuring primary energy derived from ground-based data in a compositionally insensitive way. In contrast with some previous reports, the “knee” of the energy spectrum does not appear sharp, but rather a smooth transition over energies from 10¹⁵ eV to 3.0 × 10¹⁵ eV.     

On the existence of cosmological evolutionary effects

Parameters of the distant galaxy clusters of 3C295 (z=0.46) and Cl 0024+1654 (z=0.39) are compared with the predictions made using galaxies of the local clusters Coma (z=0.023) and DC 0329–52 (z=0.057) taking theK-effect into account. The distributions of colour and morphological type, and the amplitudesF ⁺/F^– of the ₀ 4000 discontinuity are examined and no evidence for evolution of the galaxies and the clusters can be seen.     

Strain analysis and stratigraphic status of Nongkhya,Sumer and Mawmaram conglomerates of Shillong basin,Meghalaya, India

Shillong basin, one of the Purana basins of the Indian peninsula is situated in the central and eastern parts of the Shillong plateau of NE India. Metasedimentary and metavolcanic rocks of the basin are of Mesoproterozoic age and lithostratigraphically belong to Shillong Group (erstwhile Shillong series) comprising Lower Metapelitic Formation (LMF) and Upper Quartzitic Formation (UQF). A long, persistent, faulted and tectonically attenuated conglomerate known as Nongkhya-Sumer-Mawmaram-conglomerate separates these two formations. In the present work, quantitative strain analyses of the pebbles of Sumer, Nongkhya and Mawmaram conglomerates of Ri-Bhoi and West Khasi Hills districts of Meghalaya are carried out using manual and computerized programmes. Eight different techniques for intrapebble, interpebble and bulk rock strain estimation are applied and results are compared systematically. Sumer and Mawmaram conglomerates bear the testimony of broadly flattening type of deformation (0 < k < 1) while Nongkhya conglomerate shows constriction type (1 < k < α). The change in strain ellipsoid shape from Nongkhya to Mawmaram area is accompanied by a change of fabric from S < L to L < S tectonites. Affinity of rotational strain is more in Nongkhya conglomerate as compared to Sumer and Mawmaram conglomerates. The compactness of pebbles is high in case of Nongkhya conglomerate and low to moderate in Sumer and Mawmaram conglomerates indicating high strain in Nongkhya conglomerate (northeastern part of Shillong basin) relative to Sumer and Mawmaram conglomerates (southwestern part of Shillong basin). Thus strain magnitude increases from SW to NE direction of the Shillong basin.     

Physico-chemical seasonal variability of a tropical estuary: major and minor elements in water and air

The lower reaches of the Coatzacoalcos River in southeast Mexico is an area of intense industrial development. The physico-chemical characteristics of the area have exhibited differences over the years. Apparently from the associated outcroppings of limestone in the Uxpanapa River Basin, the major elements that are dissolved show higher concentrations of Ca, Mg and HCO₃^– in the waters supplied by this river. The water in the Calzadas River contains high concentrations of Ca, SO₄ and HCO₃^– that are associated with the saline domes crossed by this river. Due to industrial discharges, the sulfate concentration is very high in the water and air during April. Nitrate concentration diminishes with salinity. Higher nitrate as well as nitrite and ammonia levels are present during flood season. Phosphate concentration, associated with high oxygen levels, is higher in January. Zn, Cu and Cr are higher during the dry season (April) when dilution is minimal and low levels of TOC are present. The smaller concentrations of Zn and Cu observed in January are associated with high TOC values in water. The lower levels of Cr present in August are associated with high amounts of suspended matter. Pajaritos Lagoon and Teapa-L, with large industrial discharges, have the highest nutrient and dissolved metal concentrations in the area. Air particles smaller than 2.5 m contain Fe, V, Ti, Cu, Zn, and high amounts of S. These anomalous concentrations of sulfates and metals are attributed to anthropogenic sources.     

Magnetotelluric sounding results in eastern Tibetan Plateau

The results of Zayü-Qingshuihe MT sounding profile carried out in eastern Tibetan Plateau are presented in this paper. Using 2-D RRI method, the resistivity distribution with depth is obtained along the profile. It is featured by the resistivity zones in the horizontal direction and layers in the vertical direction. The Bangong-Nujiang suture zone and Jinshajiang suture zone are both important electrical conductivity-separating zones in the plateau, and the former is a zone with relatively low resistivity while the latter is an electrical conductivity gradient zone. The highly electrical conductive bodies in the mid and lower crust of northern Qiangtang and Bayan Har Terrain might be caused by regional melting due to shear heating during the process of subduction in tectonic evolution.     

Sources of uncertainty in exploring rangeland phenology: A case study in an alpine meadow on the central Tibetan Plateau

Global climate change has been found to substantially influence the phenology of rangeland, especially on the Tibetan Plateau. However, there is considerable controversy about the trends and causes of rangeland phenology owing to different phenological exploration methods and lack of ground validation. Little is known about the uncertainty in the exploration accuracy of vegetation phenology. Therefore, in this study, we selected a typical alpine rangeland near Damxung national meteorological station as a case study on central Tibetan Plateau, and identified several important sources influencing phenology to better understand their effects on phenological exploration. We found man-made land use was not easily distinguished from natural rangelands, and therefore this may confound phenological response to climate change in the rangeland. Change trends of phenology explored by four methods were similar, but ratio threshold method (RTM) was more suitable for exploring vegetation phenology in terms of the beginning of growing season (BGS) and end of growing season (EGS). However, some adjustments are needed when RTM is used in extreme drought years. MODIS NDVI/EVI dataset was most suitable for exploring vegetation phenology of BGS and EGS. The discrimination capacities of vegetation phenology declined with decreasing resolution of remote sensing images from MODIS to GIMMS AVHRR datasets. Additionally, distinct trends of phenological change rates were indicated in different terrain conditions, with advance of growing season in high altitudes but delay of season in lower altitudes. Therefore, it was necessary to eliminate interference of complex terrain and man-made land use to ensure the representativeness of natural vegetation. Moreover, selecting the appropriate method to explore rangelands and fully considering the impact of topography are important to accurately analyze the effects of climate change on vegetation phenology.     

Analysis of the Seasonal Variation of CO<Subscript>2</Subscript> Concentration in China Based on GOSAT Satellite Data

Carbon dioxide (CO₂) is one of the major gases that contribute to the global warming. Therefore, studying the distribution of CO₂ can help people understand the carbon cycle. Based on the GOSAT retrieved CO₂ products, the temporal and spatial distribution and seasonal variation of CO₂ concentration were analyzed from 2011 to 2015. CO₂ concentration has obvious seasonal variation. It was low in summer, and was high in spring, and the annual increase was about 2 ppm. Nevertheless, the annual growth rate of CO₂ concentration in summer was higher than that in spring, it was 0.5425% in summer and was 0.46% in spring. CO₂ concentration was low in the northwest and was high in the southeast. The growth rate of CO₂ was 2.8 ppm in the northwest and was 3.42 ppm in the southeast. More human’s activities made CO₂ concentration higher in the southeast than that in other regions.