Climate change hotspots over South America: from CMIP3 to CMIP5 multi-model datasets

This study identifies possible hotspots of climate change in South America through an examination of the spatial pattern of the Regional Climate Change Index (RCCI) over the region by the end of the twenty-first century. The RCCI is a qualitative index that can synthesize a large number of climate model projections, and it is suitable for identifying those regions where climate change could be more pronounced in a warmer climate. The reliability and uncertainties of the results are evaluated by using numerous state-of-the-art general circulation models (GCMs) and forcing scenarios from the Coupled Model Intercomparison Project phases 3 and 5. The results show that southern Amazonia and the central-western region and western portion of Minas Gerais state in Brazil are persistent climate change hotspots through different forcing scenarios and GCM datasets. In general, as the scenarios vary from low- to high-level forcing, the area of high values of RCCI increase and the magnitude intensify from central-western and southeast Brazil to northwest South America. In general, the climatic hotspots identified in this study are characterized by an increase of mean surface air temperature, mainly in the austral winter; by an increase of interannual temperature variability, predominantly in the austral summer; and by a change in the mean and interannual variability of precipitation during the austral winter.     

Civil nuclear power at risk of tsunamis

Tsunamis have caused severe destruction to vulnerable populations through the ages. Commonly generated from oceanic subduction zones, they still remain difficult to predict. Recent instrumental record on risk of occurrence can be enhanced when complemented by historical, archeological, and geological studies. We assessed the coast at risk and overlaid civilian nuclear sites active, in expansion and under construction. The worldwide distribution of threatened nuclear sites revealed a clustering in South and South-East Asia. We identified four areas for urgent policy attention, including the need for funding to translate scientific risks assessment into effective policy.     

Amphipoda assemblages in a disturbed area (Alicante,Spain, Western Mediterranean)

The distribution and composition of Amphipoda assemblages were analysed off the coasts of Alicante (Spain, Western Mediterranean), a disturbed area affected by several co‐occurring anthropogenic impacts. Although differences among sampled stations were mainly related to natural parameters, anthropogenic activities were linked with changes in amphipod assemblages. Expansion of the Port of Alicante, a sewage outfall and a high salinity brine discharge could be causing the disappearance of amphipods at stations closer to these disturbances. However, the completion of port enlargement works and mitigatory dilution of the brine discharge has led to the recovery of the amphipod assemblage. Among the natural parameters, depth determines the distribution of some of the species. While Siphonoecetes sabatieri was abundant at shallow stations, Ampelisca spp., Photis longipes, Pseudolirius kroyeri, Apherusa chiereghinii and Phtisica marina were more abundant at deeper stations. Grain size and percentage of organic matter also influenced amphipod distribution, resulting in changes in species composition and in the relative percentages of different trophic groups. Species such as Ampelisca brevicornis, Perioculodes longimanus, Urothoe hesperiae and Urothoe elegans were more abundant at stations with a high content of fine sand. Carnivorous species, mainly of the Oedicerotidae family, were more abundant at those stations with a low organic matter content, while detritivorous species were more abundant at stations with a higher mud content. Among 62 identified species, three were reported for the first time from the Spanish Mediterranean coast, two species were recorded for the second time and a new species of Siphonoecetes was found, Siphonoecetes (Centraloecetes) bulborostrum. These results confirm the need for further data on amphipods from the Mediterranean Spanish coast.     

Heavy metal accumulation in the surficial sediments along southwest coast of India

Concentration and distribution of heavy metals (Cd, Cr, Cu, Hg, Ni, Pb and Zn) in surface sediments collected from five stations located along the southwest coast of India were investigated seasonally to assess whether there is insidious buildup of heavy metals. Spatial variation was in accordance with textural characteristics and organic matter content. The concentration of the metals in sediments of the study area followed the order: Zn > Cr > Ni > Cu > Pb > Cd > Hg. The use of geochemical tools and sediment quality guidelines to account for the magnitude of heavy metal contamination revealed high contamination in monsoon and impoverishment during post-monsoon. Estimated total metal concentrations in the present investigation were comparable with other studies; however, concentrations of Ni and Zn were higher than that of other coastal regions. Concentrations of metals in sediment largely exceed NOAA effects range:low (e.g., Cu, Cr, Hg) or effects range:median (e.g., Ni) values. This means that adverse effects for benthic organisms are highly probable.     

Validation and evaluation of two multivariate statistical models for predictive shallow landslide susceptibility mapping of the Eastern Pyrenees (Spain)

This paper deals with the quality of two multivariate statistical models based on the Geographical Information System for shallow landslide susceptibility assessment in a test area at La Pobla de Lillet (Eastern Pyrenees, Spain). The quality, which was guaranteed by a rigorous methodology based on a suitable diagnosis, validation, and evaluation of the models, ensured a reliable contrast of the final susceptibility maps. This enables us to transfer the best results to the end user. Landslide susceptibility models were carried out by logistic regression and discriminant analysis of the significant conditioning factors related to the characteristics of the slope and the upslope contributing area captured from the digital elevation model and landslide distribution. The explanatory variables were tested (KS test, principal components and one-way and T-test) to select the most statistically significant ones before being introduced into the logistic and discriminant analyses. Accuracy statistics and the receiver operating characteristic curve used for diagnosis and validation showed similar prediction skills and a good fit to the data with more than 85% of unfailed cells properly classified for the two models. The evaluation of the study area and the correlation function (R ² = 0.83) between the models revealed that the discriminant model overestimated the susceptibility of the most stable zones with respect to the logistic model. Different methods of producing susceptibility maps showed marked differences in matching the models. Substantial spatial agreement (Kappa = 0.741) between binary maps produced by the standard cut-off value descended moderately (Kappa = 0.540) as a result of superimposing maps with five susceptibility levels defined by landslide percentage. Despite the fact that the two statistical models are similar in assessing susceptibility in the study area, the implications for hazard and risk management can be different because of the conservative nature of the discriminant model.