Using Clustered Heat Maps in Mineral Exploration to Visualize Volcanic-Hosted Massive Sulfide Alteration and Mineralization

Natural Resources Research - This study proposes an extension of a visualization approach common in biochemistry (the clustered heat maps—CHMs) to geochemical data with the main objective of...     

Long‐term temporal and spatial patterns in bioeroding sponge distribution at the Abrolhos Bank,Brazil, Southwestern Atlantic

Bioeroding sponges belong to the most dominant bioeroders, significantly contributing to the erosion of coral reefs. Some species are tolerant or even benefit from environmental conditions such as ocean warming, acidification, and eutrophication. In consequence, increases in sponge bioerosion have been observed on some coral reefs over the last decades. The Abrolhos Bank is the largest coral reef system in the South Atlantic. It has been affected by sedimentation, eutrophication, overfishing, and climate change, mainly affecting coastal reefs, and at lesser intensity outer ones as well. This study aimed to describe spatial and temporal patterns in bioeroding sponge distribution in carbonate substrates in the Abrolhos Bank. Photo‐quadrats were used to compare bioeroding sponge abundance between two shallow reefs: a coastal, Pedra de Leste (PL), and an outer reef, Parcel dos Abrolhos (PAB). Each individual was delimitated over the substrate by determining the sponge surface through a line connecting the outermost papillae. The study was conducted over 6 years in 2008–2009 and 2013–2016. Four species of bioeroding sponges were identified: Cliona carteri Ridley, 1881, C. delitrix Pang, 1973, C. cf. schmidtii Ridley, 1881, and Siphonodictyon coralliphagum Rützler, 1971. The distribution and abundance of species varied between the inner and outer reefs and across the years, and displayed certain selectivity for the calcareous substrates recorded. Crustose coralline algae (CCA) were the main substrate excavated by the most abundant bioeroding species, C. carteri, and represented 70% of the substrate types occupied by this sponge (CCA, coral overgrown by CCA and plain coral). The highest abundance of bioeroding sponges observed in photo‐quadrats was 21.3 individuals/m² at the outer reefs (PAB) in 2014. The abundances or areal extents of bioeroding sponges were up to 10 times greater on the outer reefs than on the coastal ones, where sedimentation is higher and more strongly influenced by siliciclastic material. Moreover, a higher herbivorous fish biomass has been reported on outer reefs which could also influence the higher abundance of bioeroding sponges in outer reefs. During the study period of 6 years, an increase in bioeroding sponge abundance was observed at the outer reefs (PAB), with the sea surface temperature increase. As CCA have an important role in reefal cementation and carbonate production in the Abrolhos reefs, a bioerosion impact might be expected, in particular, on the outer reefs.     

Fractional Flow Speed-Up from Porous Windbreaks for Enhanced Wind-Turbine Power

The potential for porous windbreaks to enhance wind-turbine power production is studied using linearized theory and wind-tunnel experiments. Results suggest that windbreaks have the potential to substantially increase power production, while lowering mean shear, and leading to negligible changes in turbulence intensity. The fractional increase in turbine power output is found to vary roughly linearly with windbreak height, where a windbreak 10% the height of the turbine hub increases power by around 10%. Wind-tunnel experiments with a windbreak imposed beneath a turbulent boundary layer show the linearized predictions to be in good agreement with particle-image-velocimetry data. Power measurements from a model turbine further corroborate predictions in power increase. Moreover, the wake of the windbreak showed a significant interaction with the turbine wake, which may inform windbreak use in large wind farms. Power measurements from a second turbine downwind of the first with its own windbreak show that the net effect for multiple turbines is dependent on windbreak height.     

Efficacy of Coagulants and Ballast Compounds in Removal of Cyanobacteria (<Emphasis Type="Italic">Microcystis</Emphasis>) from Water of the Tropical Lagoon Jacarepaguá (Rio de Janeiro,Brazil)

Eutrophication is considered the most important water quality problem in freshwaters and coastal waters worldwide promoting frequent occurrence of blooms of potentially toxic cyanobacteria. Removal of cyanobacteria from the water column using a combination of coagulant and ballast is a promising technique for mitigation and an alternative to the use of algaecides. In laboratory, we tested experimentally the efficiency of two coagulants, polyaluminium chloride (PAC) and chitosan (made of shrimp shells), alone and combined with two ballasts: red soil (RS) and the own lagoon sediment, to remove natural populations of cyanobacteria, from an urban brackish coastal lagoon. PAC was a very effective coagulant when applied at low doses (≤8 mg Al L^?1) and settled the cyanobacteria, while at high doses (≥16 mg Al L^?1) large flocks aggregated in the top of test tubes. In contrast, chitosan was not able to form flocks, even in high doses (>16 mg L^?1) and did not efficiently settle down cyanobacteria when combined with ballast. The RS itself removed 33–47 % of the cyanobacteria. This removal was strongly enhanced when combined with PAC in a dose-dependent matter; 8 mg Al L^?1 was considered the best dose to be applied. The lagoon sediment alone did not promote any settling of cyanobacteria but removal was high when combined with PAC. Combined coagulant and ballast seems a very efficient, cheap, fast and safe curative measure to lessen the harmful cyanobacteria bloom nuisance in periods when particularly needed, such as around the 2016 Olympics in Jacarepaguá Lagoon.     

Exploiting historical rainfall and landslide data in a spatial database for the derivation of critical rainfall thresholds

Critical rainfall thresholds for landslides are powerful tools for preventing landslide hazard. The thresholds are commonly estimated empirically starting from rainfall events that triggered landslides in the past. The creation of the appropriate rainfall–landslide database is one of the main efforts in this approach. In fact, an accurate agreement between the landslide and rainfall information, in terms of location and timing, is essential in order to correctly estimate the rainfall–landslide relationships. A further issue is taking into account the average moisture conditions prior the triggering event, which reasonably may be crucial in determining the sufficient amount of precipitation. In this context, the aim of this paper is exploiting historical landslide and rainfall data in a spatial database for the derivation of critical rainfall thresholds for landslide occurrence in Sicily, southern Italy. The hourly rainfall events that caused landslides occurred in the twentieth century were specifically identified and reconstructed. A procedure was proposed to automatically convert rain guages charts recorded on paper tape into digital format and then to provide the cumulative rainfall hyetograph in digital format. This procedure is based on a segmentation followed by signal recognition techniques which allow to digitalize and to recognize the hyetograph automatically. The role of rainfall prior to the landslide events was taken into account by including in the analysis the rainfall occurred 5, 15 and 30 days before each landslide. Finally, cumulated rainfall duration thresholds for different exceedance probability levels were determined. The obtained thresholds resulted in agreement with the regional curves proposed by other authors for the same area; antecedent rainfall turned out to be particularly important in triggering landslides.     

Regularized sparse‐grid geometric sampling for uncertainty analysis in non‐linear inverse problems

This paper introduces an efficiency improvement to the sparse‐grid geometric sampling methodology for assessing uncertainty in non‐linear geophysical inverse problems. Traditional sparse‐grid geometric sampling works by sampling in a reduced‐dimension parameter space bounded by a feasible polytope, e.g., a generalization of a polygon to dimension above two. The feasible polytope is approximated by a hypercube. When the polytope is very irregular, the hypercube can be a poor approximation leading to computational inefficiency in sampling. We show how the polytope can be regularized using a rotation and scaling based on principal component analysis. This simple regularization helps to increase the efficiency of the sampling and by extension the computational complexity of the uncertainty solution. We demonstrate this on two synthetic 1D examples related to controlled‐source electromagnetic and amplitude versus offset inversion. The results show an improvement of about 50% in the performance of the proposed methodology when compared with the traditional one. However, as the amplitude versus offset example shows, the differences in the efficiency of the proposed methodology are very likely to be dependent on the shape and complexity of the original polytope. However, it is necessary to pursue further investigations on the regularization of the original polytope in order to fully understand when a simple regularization step based on rotation and scaling is enough.     

Denudation and retreat of the Serra do Mar escarpment in southern Brazil derived from in situ‐produced 10Be concentration in river sediment

The Serra do Mar escarpment, located along the southeastern coast of Brazil, is a high‐elevation passive margin escarpment. This escarpment evolved from the denudation of granites, migmatites and gneisses. The granites outcrop in the form of a ridge along the escarpment crest, due to its differential erosion (‘sugarloaf’ hills) from the surrounding lithologies. Several studies suggest that the passive margin escarpments are actively retreating toward the interior of the continent. However, no prior study has calculated the long‐term denudation rates of Serra do Mar to test this hypothesis. In this study, we measured the in situ‐produced ¹⁰Be concentration in fluvial sediments to quantify the catchment‐wide long‐term denudation rates of the Serra do Mar escarpment in southern Brazil. We sampled the fluvial sediments from ten watersheds that drain both sides of the escarpment. The average long‐term denudation rate of the oceanic side is between 2.1‐ and 2.6‐fold higher than the rate of the continental side: 26.04 ± 1.88 mm ka^‐1 (integrating over between 15.8 ka^‐1 and 46.6 ka^‐1) and 11.10 ± 0.37 mm ka^‐1 (integrating over between 52.9 ka^‐1 and 85.4 ka^‐1), respectively. These rates indicate that the coastal base level is controlling the escarpment retreat toward the continental high lands, which is consistent with observations made at other high‐elevation passive margins around the globe. The results also demonstrate the differential erosion along the Serra do Mar escarpment in southern Brazil during the Quaternary, where drainages over granites had lower average denudation rates in comparison with those over migmatites and gneisses. Moreover, the results demonstrate that the ocean‐facing catchments have been eroded more intensely than those facing the continent. The results also reveal that drainage over the granites decreases the average denudation rates of the ocean‐facing catchments and the ‘sugarloaf’ hills therefore are natural barriers that slowly retreat once they are exhumed. Copyright © 2013 John Wiley & Sons, Ltd.     

Forest Fire Alert System: a Geo Web GIS prioritization model considering land susceptibility and hotspots – a case study in the Carajás National Forest,Brazilian Amazon

To increase the monitoring potential of forest fires, an alert classification methodology using satellite-mapped hotspots has been established to help forest managers in the prioritization of which hotspot to be verified in the field, thus potentially improving the distribution of fire-fighting resources. A computer application was developed based on web-distributed geographical information technology whose main function is to interact automatically generated satellite hotspots and risk areas indicated in fire-susceptibility maps and classify them into five alert levels. The location of the hotspots is available continuously every 4 h, and a susceptibility map is produced daily through map algebra algorithm, which uses static (topography, vegetation and land use) and dynamic (weather) variables. Every process runs through automated geoprocessing routines. The methodology was tested during the dry period of 2007 in the Carajás National Forest, in the Brazilian Amazon, within an area of 400,000 ha. It is a critical area constantly threatened by fires caused by invasions and deforestation owing to intense agribusiness advances and mining activities in its surroundings. This situation results in observations of many hotspots inside the study area for the same day and almost the same time period, in places of extreme opposites, demanding complex rapid analysis and hindering the decision of the displacement of fire-fighting teams. Further, a major mining company operates within the National Forest area, maintaining actions of protection as part of its environmental mining license. Results are presented under three aspects: (i) the credibility of the daily susceptibility map (algorithm), which showed strong correlation between areas of greatest risks and the confirmed forest fires; (ii) the reliability of hotspots (alert levels), confirming 71% of fires; (iii) accuracy in the decision of which hotspot to be checked, which revealed the same number of verifications at different alert levels, 82% confirmed alert 5 hotspots (maximum) and only 50% from alert 1 (minimum), resulting in faster fire-fighting actions, minimizing burned areas and, in some cases, allowing fire control before its spreading. Therefore, the methodology demonstrated that GIS routines are able to determine the relationship between a reality-based, interpreted susceptibility map of the area and satellite-generated hotspots, highlighting the ones of highest hazard level through the alert classification, becoming an important tool to help decisions from the fire-control center, especially for high-risk regions. The methodology may be extrapolated to other forested areas.     

Experimental investigation on the seismic performance of masonry buildings using shaking table testing

Masonry buildings worldwide exhibited severe damage and collapse in recent strong earthquake events. It is known that their brittle behavior, which is mainly due to the combination of low tensile strength, large mass and insufficient connection between structural elements, is the main limitation for their structural implementation in residential buildings. A new construction system for masonry buildings using concrete blocks units and trussed reinforcement is presented here and its seismic behavior is validated through shaking table tests. Dynamic tests of two geometrically identical two-story reduced scale (1:2) models have been carried out, considering artificial accelerograms compatible with the elastic response spectrum defined by the Eurocode 8. The first model was reinforced with the new proposed system while the second model was built with unreinforced masonry. The experimental analysis encompasses local and global parameters such as cracking patterns, failure mechanisms, and in-plane and out-of-plane behavior in terms of displacements and lateral drifts from where the global dynamic behavior of the two buildings is analyzed comparatively. Finally, behavior factors for the design recommendations in case of unreinforced masonry are also evaluated.     

Numerical relationships between magnetic parameters measured in Quaternary sediments and global paleoclimatic proxies

The complexity of most geological and geophysical problems prompts sometimes the use of non linear mathematical methods to handle them. An adaptive neuro fuzzy inference system (ANFIS) that combines fuzzy logic with neural networks, is applied here to study a paleoclimate section from the Quaternary sedimentary fill of the Lake Mucubají (western Venezuela). The purpose of this work is to find a set of numerical relationships that could predict the possible connections between oxygen isotope (δ¹⁸O) values from two different locations in the northern hemisphere (Ammersee in southern Germany and an ice core from the Greenland Ice Core Project — GRIP) and rock-magnetic parameters measured in Mucubají samples (i.e. mass-specific magnetic susceptibility — χ, magnetic remanence S-ratio, mass-specific saturation isothermal remanent magnetization — SIRM and anhysteretic remanent magnetization — ARM). The best inferences in terms of coefficient of determionation R² and the Root Mean-Square Error (RMSE) are obtained using those magnetic data as input that include information about magnetite grain size distributions, e.g., SIRM and ARM in FIS structures [1χ, 4ARM] and [4ARM, 1SIRM]. A comparison between Ammersee and GRIP actual data, as well as their corresponding inferences for the FIS structure [4ARM, 1SIRM], reveals a reasonable good inference of global trends for both records, overlooking the regional and/or local paleoclimate forcings that might have affected Ammersee. A better correlation between global isotope paleoclimate records and magnetic proxies, is perhaps prevented by the role played by local and regional paleoclimate and tectonism in Mucubají. We also argue that the ratio of ARM over SIRM appears to be related in a complex way to the onset and to the end of the Younger Dryas. Our novel approach to the assessment of a specific paleoclimate case study shows the potential of the ANFIS technique in solving problems where traditional univariate and multivariate linear regression methods could prove inadequate.