Geochemistry and δ11 B evolution of tourmaline from tourmalinite as a record of oceanic crust in the Tonian Ibaré ophiolite, southern Brasiliano Orogen.

The isotopic and geochemical evolution of tourmaline constrain the processes of paleo-oceanic lithosphere in ophiolites. The Brasiliano Orogen is a major structure of South America and requires characterization for the understanding of Gondwana supercontinent evolution. We made a pioneering investigation of tourmaline from a tourmalinite in the Ibaré ophiolite by integrating field work with chemical analyses of tourmaline by electron microprobe (EPMA) and δ11B determinations via laser ablation inductively coupled plasma mass spectrometer (LA-ICP-MS). Remarkably massive tourmalinite (>90 vol.% tourmaline, some chlorite) enclosed in serpentinite has homogeneous dravite in chemical and isotopic composition (δ11B = +3.5 to +5.2‰). These results indicate a geotectonic environment in the altered oceanic crust for the origin of the tourmalinite. This first δ11B characterization of tourmaline from tourmalinite sets limits to the evolution of the Neoproterozoic to Cambrian Brasiliano Orogen and Gondwana evolution.

Modelling Highly Biodiverse Areas in Brazil.

Traditional conservation techniques for mapping highly biodiverse areas assume there to be satisfactory knowledge about the geographic distribution of biodiversity. There are, however, large gaps in biological sampling and hence knowledge shortfalls. This problem is even more pronounced in the tropics. Indeed, the use of only a few taxonomic groups or environmental surrogates for modelling biodiversity is not viable in mega-diverse countries, such as Brazil. To overcome these limitations, we developed a comprehensive spatial model that includes phylogenetic information and other several biodiversity dimensions aimed at mapping areas with high relevance for biodiversity conservation. Our model applies a genetic algorithm tool for identifying the smallest possible region within a unique biota that contains the most number of species and phylogenetic diversity, as well as the highest endemicity and phylogenetic endemism. The model successfully pinpoints small highly biodiverse areas alongside regions with knowledge shortfalls where further sampling should be conducted. Our results suggest that conservation strategies should consider several taxonomic groups, the multiple dimensions of biodiversity, and associated sampling uncertainties.