Metal accumulation by plant species growing on a mine contaminated site in Mexico

The present work aims to assess the efficiency of heavy metal accumulation of native species growing in contaminated soils in the mining district of Taxco, Mexico. Soil and tailing sampling was conducted in three study sites: La Concha, El Fraile, and a control site. The study localities present diverse metal concentrations with significant differences in their proportion in the geochemical fractions. Results show that species Cupressus lindleyi and Juniperus deppeana accumulate Zn and Mn in anomalous concentrations at La Concha, where Zn is present in soluble fractions. Manganese, despite not being present mostly in the soluble fraction in soils and tailings, seems to have been increased in the soluble fraction after the plant growth. In contrast, samples of the same species taken at El Fraile and in the control site, where Zn and Mn are mainly contained in the residual fraction, do not show an anomalous enrichment. Other analyzed species growing under the same contamination conditions in La Concha (Jacaranda mimosifolia and Psidium guajava) do not show anomalous concentrations. These facts confirm the Zn and Mn accumulation capacity of C. lindleyi and Ju. deppeana, which depends on their accumulation ability and on the concentration of these elements in the soluble fraction.     

Role of rhizosphere and soil properties for the phytomanagement of a salt marsh polluted by mining wastes

The goal of this study was to evaluate the soil properties and their modifications within the rhizosphere of spontaneous vegetation as key factors to assess the phytomanagement of a salt marsh polluted by mining wastes. A field survey was performed based on a plot sampling design. The results provided by the analyses of rhizospheric soil (pH, electrical conductivity (EC), organic carbon, total nitrogen, etc.) and metal(loid)s’ phytoavailability (assessed by EDTA) were discussed and related to plant metal uptake. The averages of pH and EC values of the bulk soil and rhizospheric samples were in the range of neutral to slightly alkaline (pH 7–8) to saline (>2 dS m^?1), respectively. Heavy metal and As concentrations (e.g. ~600 mg kg^?1 As, ~50 mg kg^?1 Cd, ~11,000 mg kg^?1 Pb) were higher in the rhizosphere for both total and EDTA-extractable fraction. Phragmites australis uptaked the highest concentrations in roots (e.g. ~66 mg kg^?1 As, ~1,770 mg kg^?1 Zn) but not in shoots, for which most of plant species showed low values for Zn (<300 mg kg^?1) but not for Cd (>0.5 mg kg^?1) or Pb (~20–40 mg kg^?1). Vegetation distribution in the studied salt marsh looked to be more affected by salinity than by metal pollution. The free availability of water for plants and the incoming nutrient-enriched effluents which flow through the salt marsh may have hindered the metal(loid)s’ phytotoxicity. The phytomanagement of these polluted areas employing the spontaneous vegetation is a good option in order to improve the ecological indicators and to prevent the transport of pollutants to nearby areas.     

Ccd Photometry of Neglected Eclipsing Binaries – Kz Dra, Lr Cam and Im Vul

We present ephemerides and solutions of one Algol-type (KZ Dra) and two overcontact systems (LR Cam and IM Vul) based on V(RI)_C CCD observations obtained in the project Prosper (network of amateur observers).     

Microfacies and Depositional Environments of Miocene Isolated Carbonate Platforms from Central Luconia, Offshore Sarawak, Malaysia

The Luconia Province – offshore Sarawak – is a key geological unit for understanding the distribution of hydrocarbon resources in Malaysia. Nevertheless, little effort has been made to address the palaeoenvironmental characteristics of the Tertiary carbonates in the key sector of Central Luconia. We study the sedimentology and petrography of core samples from a well in Central Luconia, for which thirteen microfacies have been identified reflecting different depositional settings. This is the first microfacies scheme elaborated for Luconian carbonates. Lithofacies and microfacies distribution are compatible with deposition in a reef complex, originating around a framework reef, within the euphotic zone. Sediments were deposited in environments of backreef, reef crest, and forereef. The fair weather wave base is marked by the presence of coralline red algae, foraminifera, decreasing degree of bioclast fragmentation and other microfacies features. As a result, a depositional-environmental model is constructed, depicting a reef complex built around a framework reef developed on the margin of an isolated platform. In addition, an innovative, preliminary time series analysis of facies, microfacies and depositional environment data reveal the existence of seasonal cycles in the stacking patterns of facies and microfacies.     

Filter design for GOCE gravity gradients

The GOCE satellite observes gravity gradients with unprecedented accuracy and resolution. The GOCE observations are reliable within a well-defined measurement bandwidth. In this study, different finite and infinite impulse response filters have been designed to obtain the demanded pass. Exhaustive time and frequency domain investigations prove that the proposed infinite impulse response filter can be a real competitor of the existing solution of the filtering problem.     

An object-based approach for mapping forest structural types based on low-density LiDAR and multispectral imagery

Mapping forest structure variables provides important information for the estimation of forest biomass, carbon stocks, pasture suitability or for wildfire risk prevention and control. The optimization of the prediction models of these variables requires an adequate stratification of the forest landscape in order to create specific models for each structural type or strata. This paper aims to propose and validate the use of an object-oriented classification methodology based on low-density LiDAR data (0.5 m^?2) available at national level, WorldView-2 and Sentinel-2 multispectral imagery to categorize Mediterranean forests in generic structural types. After preprocessing the data sets, the area was segmented using a multiresolution algorithm, features describing 3D vertical structure were extracted from LiDAR data and spectral and texture features from satellite images. Objects were classified after feature selection in the following structural classes: grasslands, shrubs, forest (without shrubs), mixed forest (trees and shrubs) and dense young forest. Four classification algorithms (C4.5 decision trees, random forest, k-nearest neighbour and support vector machine) were evaluated using cross-validation techniques. The results show that the integration of low-density LiDAR and multispectral imagery provide a set of complementary features that improve the results (90.75% overall accuracy), and the object-oriented classification techniques are efficient for stratification of Mediterranean forest areas in structural- and fuel-related categories. Further work will be focused on the creation and validation of a different prediction model adapted to the various strata.