Francisco Pinheiro Lima-Filho

The detection of subsurface stromatolites remains challenging due to their complex morphology and heterogeneous composition. This study assesses the combined application of Electrical Resistivity Tomography (ERT) and Ground Penetrating Radar (GPR) for identifying microbialites in two contrasting geological and climatic settings: the Neoproterozoic Salitre Formation in Brazil and the Mesozoic microbialite-bearing limestones in northern Spain. High-resolution ERT profiles processed with raster-based blob detection algorithms revealed subcircular high-resistivity anomalies consistent with the studied microbialite morphologies, with strong resistivity contrasts observed between microbialites and host matrices despite variations in absolute values linked to lithology and soil moisture. In parallel, GPR surveys analyzed with a peak detection algorithm delineated domal reflectors and clusters of high-amplitude reflections that directly captured the internal architecture of stromatolitic buildups. With decimetric vertical resolution, GPR offered unrivaled insights into internal morphology, complementing the broader-scale imaging capacity of ERT. The complementary strengths of both methods are clear: ERT excels at mapping distribution and stratigraphic context, while GPR provides unparalleled resolution of internal structures. Crucially, this work advances previous efforts by explicitly demonstrating that integrated ERT-GPR approaches, when combined with algorithm-based interpretation, can resolve microbialite morphology, distribution and internal architecture with a level of objectivity not previously achieved. Beyond methodological refinement, these findings open new avenues for reconstructing microbialite development and preservation in ancient carbonate systems and hold strong potential for application in other geological contexts where complex carbonate structures challenge traditional geophysical imaging.

Pterosaur dental biology remains poorly understood despite its importance for comprehending feeding strategies and flight adaptations. Here, we present the first comprehensive histological analysis of an ornithocheiriform pterosaur tooth from the Lower Cretaceous Crato Formation (Santana Group, Northeast Brazil). Specimen LPP‐UFRN 3002 exhibits thin prismless enamel (61 μm thickness), orthodentine with dense tubule networks, and 82 von Ebner lines indicating rapid tooth formation. Quantitative comparison across major clades of extinct reptiles reveals that pterosaurs demonstrate the most accelerated tooth development among archosauriforms, with formation times of 54–82 lines compared to 185–933 lines in non‐avialan dinosaurs, 50–283 lines in crocodyliforms, and 342–426 lines in mosasaurs. The rapid tooth development and thin enamel documented in ornithocheiriform pterosaurs could enable the maintenance of lightweight skulls, essential for powered flight, while ensuring continuous replacement for effective prey capture. The specimen preserves microstructural detail despite diagenetic calcite permineralization and partial focalized substitution, a characteristic of the Crato Formation carbonate environment. These findings demonstrate that ornithocheiriform pterosaurs evolved a unique dental strategy, prioritizing replacement efficiency over individual tooth durability, which contrasts with the extended formation times characteristic of large‐bodied mosasaurs and herbivorous dinosaurs. This research establishes dental histology as critical for understanding pterosaur paleobiology and provides quantitative data for reconstructing ecosystem dynamics throughout the Mesozoic.

This study investigates groundwater salinization in a section of a coastal aquifer in Rio Grande do Norte, Brazil, using frequency-domain electromagnetic (FDEM) measurements. With the global expansion of shrimp farming in ecologically sensitive coastal regions, there is an urgent need to assess associated risks and promote sustainable management practices. A key concern is the prolonged flooding of shrimp ponds, which accelerates saltwater infiltration into surrounding areas. To better delineate salinization plumes, we analyzed direct groundwater salinity measurements from 14 wells combined with 315 subsurface apparent conductivity measurements obtained using the FDEM method. Correlating these datasets improved the accuracy of salinity mapping, as evidenced by reduced variance in kriging interpolation. By integrating hydrogeological, hydrogeochemical, and geophysical approaches, this study provides a comprehensive characterization of groundwater salinity in the study area. Hydrogeological investigations delineated aquifer properties and flow dynamics; hydrogeochemical analyses identified salinity levels and water quality indicators; and geophysical surveys provided spatially extensive conductivity measurements essential for detecting and mapping saline intrusions. The combined insights from these methodologies enable a more precise assessment of salinity sources and support the development of more effective groundwater management strategies. Our findings demonstrate the effectiveness of integrating geophysical surveys with hydrogeological and hydrogeochemical data, confirming that shrimp farm ponds are a significant source of groundwater contamination. This combined methodology offers a low-impact, cost-effective approach that can be applied to other coastal regions facing similar environmental challenges.

This article explores the application of ground penetrating radar (GPR) as a novel, cost-effective tool for rock mass classification in geotechnical engineering. Traditional rock mass classification systems, such as the rock quality index (RQD), the rock mass rating (RMR), the q-system (Q), and the geological strength index (GSI), primarily rely on geological mapping and drilling investigations, which, while effective, have limitations including high costs, invasiveness, and one-dimensional subsurface information. GPR offers a non-destructive alternative, providing high-resolution, two-dimensional subsurface imaging. This study demonstrates the efficacy of ground-penetrating radar (GPR) in identifying subsurface discontinuities, comparing its findings with UAV imagery. We also outline the potential for GPR-based insights to complement geomechanical classifications (RQD, RMR, Q, and GSI), highlighting how GPR can enhance the interpretation of rock mass characterization. Utilizing data from a GPR survey conducted on a jointed rock mass slope outcrop at the downstream side of the Castanhão Dam spillway in the state of Ceará, Brazil, the research highlights GPR's potential in accurately characterizing rock mass discontinuity conditions. Incorporating GPR as a complementary tool alongside traditional methodologies for jointed rock mass characterization, this research demonstrates the method's potential in refining and augmenting the identification of discontinuities. Such a synergistic approach could significantly enhance the accuracy of rock mass classification, potentially contributing to improved safety and efficiency in rock engineering practices.

The increasing installation of shrimp farms in vulnerable coastal areas around the world generates an environmental impact and makes it urgent to develop methodologies and studies for assessing and scaling the potential risks and sustainability of these activities. One of the main hazards of these activities is that the prolonged inundation of excavated ponds for shrimp farming allows the percolation of saltwater in the surroundings, resulting in increasing groundwater salinity. Saltwater intrusion in coastal aquifers, accompanied by salinization of soils, causes a decrease in available freshwater resources, a decline in crop productivity and the deterioration of the natural ecosystem. The coastal aquifer of Rio Grande do Norte State (Brazil) where, for years, several shrimp farm factories have been operating, reported some issues related to aquifer and soil salinization. The present study aims to assess the origin of and delineate groundwater salinization in a sector of this coastal aquifer using a low-budget procedure. The integration of hydrogeological and hydrogeochemical characterization by drilling shallow piezometers, measuring the hydrostatic level and analyzing the major ion concentrations of the groundwater has made it possible to establish that the origin of groundwater pollution in the studied area is caused by saltwater percolation from shrimp farms. The joint use of both characterization techniques has been shown to have an efficient cost–benefit ratio and less-intrusive methodology, which can be applied in other areas with similar environmental concerns.

Caracterização preliminar geotécnica do subsolo do Campo Experimental de Geotecnia e de Fundações da Universidade Federal do Ceará (CEGEF – UFC) / Preliminary geotechnical characterization of the subsoil of the Geotechnical and Foundation Experimental Field of the Federal University of Ceará (CEGEF - UFC)

The rock mass deformation modulus, Erm, is an input parameter for most numerical modeling to verify the deformation behavior of rocks due to rock engineering activities within/on it. Among the most common methodologies used for estimating this parameter, empirical correlations based on rock mass classification schemes (e.g., RQD, RMR, GSI, and Q) stand out the most, principally because of their low cost when compared to the other methods. Herein, the main correlations used in practice are evaluated and comparted for 48 different rock quality scenarios, previously characterized and classified according to rock mass classification systems. The results obtained by each of the empirical correlations demonstrated that normalized correlations, that is, based on the ratio of the rock mass and intact rock modulus, Erm/Ei, underestimate the Erm values when compared to those results obtained from not-normalized correlations in the scenarios of better quality rock masses. For poor quality rock mass scenarios, both non-normalized and normalized correlation presented similar results. The correlations proposed by Hoek and Diederichs (2006) and Galera et al. (2007) estimated more central Erm values when compared to the other correlations, for all quality scenarios, while the Mitri et al. (1994) and Sonmez et al. (2006) methods estimated most high and low values of Erm, respectively.