Shell growth and oxygen isotopes in the topshell Osilinus turbinatus: resolving past inshore sea surface temperatures

Shells of the rocky shore intertidal gastropod Osilinus turbinatus (von Born), often abundant in archaeological deposits in the Mediterranean region, are a potential source of data on palaeotemperature, palaeoseasonality and archaeological seasonality. To evaluate this species as a climate archive, investigations of annual patterns of shell growth and of monthly variations in oxygen isotopes in shell carbonates were made on different populations in NW Sicily. Mark-recapture experiments at San Vito lo Capo and Mazzaforno show that O. turbinatus grows almost continuously throughout the year but at different rates in different seasons. Around 75% of the yearly shell growth occurs in the autumn and winter. On average, larger/older shells produce narrower annual growth increments than smaller/younger ones. Conspicuous growth lines in larger/older shells show that growth stops during the hottest part of the summer. Oxygen isotope analyses on monthly collected shells of O. turbinatus from three shores (Cala Grande, Monte Cofano and Mazzaforno) show that the isotope values record temperature variations through the year. In all the datasets, surface seawater temperatures (SSTs) calculated from δ¹⁸O_SHELL mostly underestimate measured SSTs, offsets being generally greater in summer. Minimum annual offsets range from 0.0°C to 0.7°C and maximum annual offsets from 3.1°C to 8.7°C. δ¹⁸O_SHELL values fail to record temperatures higher than 25°C. Careful selection of shells to be analysed can reduce offsets between δ¹⁸O_SHELL temperature estimates and measured SSTs for many parts of the year, except the hottest. Allowing for this, shells of O. turbinatus offer good potential as climate archives and for archaeological studies of seasonal patterns of human foraging for shellfish.     

Organic matter in deepwater sediments of the Northern Gulf of Mexico and its relationship to the distribution of benthic organisms

Sediment samples were selected from 28 sites across the deep (212–3527 m) northern Gulf of Mexico (GOM) as part of the Deep Gulf of Mexico Benthos (DGoMB) program, and analyzed for geochemical parameters related to organic carbon (OC) distribution and characteristics. The results of this study indicate that the OC content of sediments in the deep northern GOM is controlled by several factors; including water depth, overlying water productivity, sediment carbonate content, sediment oxygen exposure time, OC sources, and regional influences. The best correlation between sediment OC content, on a CaCO₃-free basis, and other parameters examined was an inverse correlation of OC with water depth. The OC/SA ratio had a wide range of values and, along with variable sources of sedimentary OC, indicated that the organism-available concentration of metabolizable organic matter may not be simply related to sedimentary OC content. This was perhaps reflected in the observation that benthic macrofaunal and meiofaunal biomass abundances were well correlated with sedimentary OC, but the abundance of bacteria in sediments was not.     

Boosting for Mineral Prospectivity Modeling: A New GIS Toolbox

With an increasing demand for raw materials, predictive models that support successful mineral exploration targeting are of great importance. We evaluated different machine learning techniques with an emphasis on boosting algorithms and implemented them in an ArcGIS toolbox. Performance was tested on an exploration dataset from the Iberian Pyrite Belt (IPB) with respect to accuracy, performance, stability, and robustness. Boosting algorithms are ensemble methods used in supervised learning for regression and classification. They combine weak classifiers, i.e., classifiers that perform slightly better than random guessing to obtain robust classifiers. Each time a weak learner is added; the learning set is reweighted to give more importance to misclassified samples. Our test area, the IPB, is one of the oldest mining districts in the world and hosts giant volcanic-hosted massive sulfide (VMS) deposits. The spatial density of ore deposits, as well as the size and tonnage, makes the area unique, and due to the high data availability and number of known deposits, well-suited for testing machine learning algorithms. We combined several geophysical datasets, as well as layers derived from geological maps as predictors of the presence or absence of VMS deposits. Boosting algorithms such as BrownBoost and Adaboost were tested and compared to Logistic Regression (LR), Random Forests (RF) and Support Vector machines (SVM) in several experiments. We found performance results relatively similar, especially to BrownBoost, which slightly outperformed LR and SVM with respective accuracies of 0.96 compared to 0.89 and 0.93. Data augmentation by perturbing deposit location led to a 7% improvement in results. Variations in the split ratio of training and test data led to a reduction in the accuracy of the prediction result with relative stability occurring at a critical point at around 26 training samples out of 130 total samples. When lower numbers of training data were introduced accuracy dropped significantly. In comparison with other machine learning methods, Adaboost is user-friendly due to relatively short training and prediction times, the low likelihood of overfitting and the reduced number of hyperparameters for optimization. Boosting algorithms gave high predictive accuracies, making them a potential data-driven alternative for regional scale and/or brownfields mineral exploration.

     

Accumulation of Cu and Zn in discarded antifouling paint particles by the marine gastropod, Littorina littorea

The short-term (5 day) accumulation of Cu and Zn in different tissues of the marine gastropod, Littorina littorea, has been studied in the presence of 10 mg l⁻¹ of antifouling paint particles and pre- or simultaneously contaminated algal food (Ulva lactuca). Accumulation of Cu was observed in the head–foot, digestive gland–gonad complex and gills to extents dependent on how and when food was contaminated and administered. However, retention of Zn was only observed in the gills and only when L. littorea and U. lactuca were simultaneously exposed to paint particles. Relative to the alga, faecal material was highly enriched in Zn, suggesting that the animal is able to rapidly eliminate this metal, most likely through the formation and egestion of insoluble phosphate granules. Thus, L. littorea is a useful biomonitor of marine contamination by antifouling applications in respect of Cu but not Zn.     

Specific-lon electrode determinations of sulfide preconcentrated from San Francisco Bay waters

Measurements of low-level dissolved-sulfide concentrations in estuarine water from San Francisco Bay have been made using the sulfide-specific electrode after preservation, separation, and preconcentration of the sulfide species. The separation and preconcentration were acheived by coprecipitation of ZnS with Zn(OH)₂ followed by collection and dissolution of the precipitate, giving concentration factors up to 160-fold Preconcentration provided sulfide solutions that were adequately measurable within the practical working range of the specific-ion electrode The sulfide detection limit with the preconcentration step is 0 02 μg/l Spike recoveries in the range of 81 to 10 1% have been achieved for laboratory-prepared samples having S²⁻ concentrations as low as 0 6 μg/l and 84 to 100% for an estuarine sample spiked in the field with 2 μg/l (S(−II) Positive correlations have been found between dissolved S(−II) concentrations and concentrations of dissolved Cd, Cu, and Ni, negative correlations have been found between bisulfide (HS⁻) activity and activities of Cd²⁺, Cu²⁺, and Ag⁺ species     

Reconstructing spatio-temporal patterns of debris-flow activity using dendrogeomorphological methods

Debris flows are a major threat in many parts of the Alps, where they repeatedly cause severe damage to infrastructure and transportation corridors or even loss of life. Nonetheless, the spatial behavior of past debris-flow activity and the analysis of areas affected during particular events have been widely neglected in reconstructions so far. It was therefore the purpose of this study to reconstruct spatio-temporal patterns of past debris flows on a forested cone in the Swiss Alps (Bruchji torrent, Blatten, Valais). The analysis of past events was based on a detailed geomorphic map (1:1000) of all forms related to debris flows as well as on tree-ring series from 401 heavily affected trees (Larix decidua Mill. and Picea abies (L.) Karst.) growing in or next to deposits. The samples were analyzed and growth disturbances related to debris-flow activity assessed, such as tangential rows of traumatic resin ducts, the onset of reaction wood or abrupt growth suppression or release.In total, 960 growth disturbances were identified in the samples, belonging to 40 different event years between A.D. 1867 and 2005. In addition, the coupling of tree-ring data with the geomorphic map allowed reconstruction of eleven formerly active channels and spatial representation of individual events. Based on our results we believe that before 1935, debris flows preferentially used those channels located in the western part of the cone, whereas the eastern part of the cone remained widely unaffected. The spatial representation of the 40 events also allowed identification of five different spatial patterns for debris flows at the study site.     

The effects of organic removal treatment on the integrity of δ<Superscript>18</Superscript>O measurements from biogenic silica

Prior to oxygen isotope analysis of biogenic silica by fluorination techniques, sediments must be cleaned of all organic compounds. Despite the expanding volume of research utilising oxygen isotope ratios in biogenic silica in palaeoclimatology, very little is known about the effects of different standard preparation methods for the removal of organic matter on the isotope values. Here we compare a number of methods for the removal of organic matter in order to assess their effectiveness and influence on subsequent isotope measurements. Not all the methods described here effectively removed organic matter, the best treatments were H₂O₂ and ignition in air at 550°C. Ignition in air at 950°C, and heating in vacuum at 250 and 450°C results in marked alteration of isotope values, whereas use of hydrogen peroxide (H₂O₂), nitric acid (HNO₃) and plasma ashing have little or no effect, within the bounds of analytical error. Ignition in air at 550°C was the most effective technique, and induced no alteration of δ¹⁸O_silica, but practical constraints may limit the application of this method routinely. Our findings indicate that considerable caution is required when preparing sediment for isotope analysis of biogenic silica.