Biodegradation effects over different types of coastal rocks

Modern coastal areas have natural and transported rocks (armourstone) on which various types of organisms live. Burrowing, boring and feeding by these organisms can destroy or modify the coastal rocks and hence change the coastal morphology. Two rock types and three dominant types of organisms have been studied in Mersin Bay, Eastern Mediterranean of southern Turkey. In this study area, Plio-Quaternary conglomerates and variously aged limestone armourplates have been affected by Phoronida worms, bivalve Brachidontes pharaonis (Fischer P. 1870) and the limpet Patella sp. Phoronida colonies were found covering the hard substratum as a mat and form tubular endolithes of 35.0 mm depth and 1.5 mm diameter, whilst Brachidontes pharaonis (Fischer P. 1870) form 44 mm deep vase-shaped gastrochaenolites. The bioerosive activity of Limpet Patella sp., found intertidal and within the spray zone, cannot be significantly observed on the rocks over short time periods. The soft sandy matrix of the conglomerates present were found to disintegrate by bioerosional processes, with the released gravels being transported and deposited onto the beach. Within the armourstone limestone blocks, a maximum of 44.0 mm deep holes developed after 50–60 years. However, these biological activities do not threaten the stability of the blocks due to their hard and homogeneous internal structure. Furthermore, the organism colonies that cover these rocks as a strong mat (maximum 29.0 mm) act to protect their surfaces from further biological attack and wave action.     

Genetic algorithms for the classification and prediction of precipitation occurrence

Abstract

Using an approach similar to the biological processes of natural selection and evolution, the genetic algorithm (GA) is a nonconventional optimum search technique. Genetic algorithms have the ability to search large and complex decision spaces and handle nonconvexities. In this paper, the GA is applied for solving the optimum classification of rainy and non-rainy day occurrences based on vertical velocity, dewpoint depression, temperature and humidity data. The problem involves finding optimum classification based on known data, training the future prediction system and then making reliable predictions for rainfall occurrences which have significance in agricultural, transportation, water resources and tourism activities. Various statistical approaches require restrictive assumptions such as stationarity, homogeneity and normal probability distribution of the hydrological variables concerned. The GAs do not require any of these assumptions in their applications. The GA approach for the occurrence classifications and predictions is presented in steps and then the application of the methodology is shown for precipitation occurrence (non-occurrence) data. It has been shown that GAs give better results than classical approaches such as discriminant analysis. The application of the methodology is presented independently for the precipitation event occurrences and forecasting at the Lake Van station in eastern Turkey. Finally, the amounts of precipitation are predicted with a model similar to a third order Markov model whose parameters are estimated by the GA technique.     

Pyrite geochemistry in the Toarcian Posidonia Shale of south‐west Germany: Evidence for contrasting trace‐element patterns of diagenetic and syngenetic pyrites

Authigenic pyrite grains from a section of the Lower Toarcian Posidonia Shale were analysed for their trace‐element contents and sulphur‐isotope compositions. The resulting data are used to evaluate the relationship between depositional conditions and pyrite trace‐element composition. By using factor analysis, trace‐elements in pyrite may be assigned to four groups: (i) heavy metals (including Cu, Ni, Co, Pb, Bi and Tl); (ii) oxyanionic elements (As, Mo and Sb); (iii) elements partitioned in sub‐microscopic sphalerite inclusions (Zn and Cd); and (iv) elements related to organic or silicate impurities (Ga and V). Results indicate that trace‐element contents in pyrite depend on the site and mechanism of pyrite formation, with characteristic features being observed for diagenetic and syngenetic pyrites. Diagenetic pyrite formed within anoxic sediments generally has a high heavy metals content, and the degree of pyritization of these elements increases with increasing oxygen deficiency, similar to the degree of pyritization of reactive Fe. The highest gradient in the increase of the degree of trace element pyritization with bottom‐water oxygenation was found for the elements Ni < Cu < Mo = As < Tl. In contrast, syngenetic pyrite formed within a euxinic water column typically is enriched in As, Mo and Sb, but is low in heavy metals, and the geochemical variation reflects changes in sea water composition.     

Geochemistry of uranium and thorium and natural radioactivity levels of the western Anatolian plutons,Turkey

Mineralogy and Petrology - Seventy samples from major plutons (mainly granitic) of Western Anatolia (Turkey) have been analyzed by γ-ray spectrometry to determine the specific activities of...     

Modeling River Stage‐Discharge Relationships Using Different Neural Network Computing Techniques

One of the most important problems in hydrology is the establishment of rating curves. The statistical tools that are commonly used for river stage‐discharge relationships are regression and curve fitting. However, these techniques are not adequate in view of the complexity of the problems involved. Three different neural network techniques, i. e., multi‐layer perceptron neural network with Levenberg‐Marquardt and quasi‐Newton algorithms and radial basis neural networks, are used for the development of river stage‐discharge relationships by constructing nonlinear relationships between stage and discharge. Daily stage and flow data from three stations, Yamula, Tuzkoy and Sogutluhan, on the Kizilirmak River in Turkey were used. Regression techniques are also applied to the same data. Different input combinations including the previous stages and discharges are used. The models' results are compared using three criteria, i. e., root mean square errors, mean absolute error and the determination coefficient. The results of the comparison reveal that the neural network techniques are much more suitable for setting up stage‐discharge relationships than the regression techniques. Among the neural network methods, the radial basis neural network is found to be slightly better than the others.     

Disentangling intangible social–ecological systems

Contemporary environmental challenges call for new research approaches that include the human dimension when studying the natural environment. In spite of the recent development of several conceptual frameworks integrating human society with nature, there has been less methodological and theoretical progress on how to quantitatively study such social–ecological interdependencies. We propose a novel theoretical framework for addressing this gap that partly builds on the rapidly growing interdisciplinary research on complex networks. The framework makes it possible to unpack, define and formalize ways in which societies and nature are interdependent, and to empirically link this to specific governance challenges and opportunities using a range of theories from both the social and natural sciences in an integrated way. At the core of the framework is a set of basic building blocks (motifs) that each represents a simplified but non-trivial social–ecological systems (SES) consisting of two social actors and two ecological resources. The set represents all possible patterns of interdependency in a SES. Each unique motif is characterized in terms of social and ecological connectivity, resource sharing, and resource substitutability. By aligning theoretical insights related to the management of common-pool resources, metapopulation dynamics, and the problem of fit in SES with the set of motifs, we demonstrate the multi-theoretical ability of the framework in a case study of a rural agricultural landscape in southern Madagascar. Several mechanisms explaining the inhabitants’ demonstrated ability to preserve their scattered forest patches in spite of strong pressures on land and forest resources are presented.     

Marine vibrators: the new phase of seismic exploration

Marine seismic vibrators are generally considered to be less intrusive than airguns from an environmental perspective. This is because they emit their energy spread out in time, rather than in a single, high-intensity pulse. There are also significant geophysical benefits associated with marine vibrators, and they stem from the ability to specify in detail the output acoustic waveform. The phase can be specified independently at each frequency. Such detailed control cannot be achieved with conventional airgun sources, where the phase can only be modified using simple overall time delays. The vibrator phase can be employed in several different ways: it can be applied to the overall source phase in a sequence so that it varies from one source point to the next; it can be applied to the individual vibrators within the source array so the source directivity is changed; it can be applied to the overall source phase of each source in a simultaneous source acquisition. Carefully designed phase sequences can attenuate the residual source noise, and this in turn allows extra source points to be interleaved between the conventional ones. For these extra source points, the relative phase of the vibrators within the array can be chosen to create a transverse gradient source, which illuminates the earth predominantly in directions out of the plane of the sail line without left/right ambiguity. If seismic vibrator data are acquired using interleaved conventional and transverse gradient sweeps, more information is collected per kilometre of vessel travel than is the case in conventional acquisition. This richer data acquisition leads to the possibility of acquiring all the necessary seismic data in a shorter time. Three-dimensional reconstruction techniques are used to recover the same image quality that would have been obtained using the conventional, more time-consuming acquisition. For a marine vibrator to be suitable for these techniques it must, in general terms, have ‘high fidelity’. The precise device specifications are defined through realistic end-to-end simulations of the physical systems and the processing. The specifications are somewhat more onerous than for a conventional vibrator, but they are achievable. A prototype vibrator that satisfies these requirements has been built. In a simulated case study of a three-dimensional deep-water ocean bottom node survey, the seismic data could have been acquired using marine vibrators in one third of the time that it would have taken using airguns.     

Simulated climate conditions in Europe during the Marine Isotope Stage 3 stadial

Kjellström, E., Brandefelt, J., Näslund, J.‐O., Smith, B., Strandberg, G., Voelker, A. H. L. & Wohlfarth, B. 2010: Simulated climate conditions in Europe during the Marine Isotope Stage 3 stadial. Boreas, 10.1111/j.1502‐3885.2010.00143.x. ISSN 0300‐9483. State‐of‐the‐art climate models were used to simulate climate conditions in Europe during Greenland Stadial (GS) 12 at 44 ka BP. The models employed for these simulations were: (i) a fully coupled atmosphere–ocean global climate model (AOGCM), and (ii) a regional atmospheric climate model (RCM) to dynamically downscale results from the global model for a more detailed investigation of European climate conditions. The vegetation was simulated off‐line by a dynamic vegetation model forced by the climate from the RCM. The resulting vegetation was then compared with the a priori vegetation used in the first simulation. In a subsequent step, the RCM was rerun to yield a new climate more consistent with the simulated vegetation. Forcing conditions included orbital forcing, land–sea distribution, ice‐sheet configuration, and atmospheric greenhouse gas concentrations representative for 44 ka BP. The results show a cold climate on the global scale, with global annual mean surface temperatures 5 °C colder than the modern climate. This is still significantly warmer than temperatures derived from the same model system for the Last Glacial Maximum (LGM). Regional, northern European climate is much colder than today, but still significantly warmer than during the LGM. Comparisons between the simulated climate and proxy‐based sea‐surface temperature reconstructions show that the results are in broad agreement, albeit with a possible cold bias in parts of the North Atlantic in summer. Given a prescribed restricted Marine Isotope Stage 3 ice‐sheet configuration, with large ice‐free regions in Sweden and Finland, the AOGCM and RCM model simulations produce a cold and dry climate in line with the restricted ice‐sheet configuration during GS 12. The simulated temperature climate, with prescribed ice‐free conditions in south‐central Fennoscandia, is favourable for the development of permafrost, but does not allow local ice‐sheet formation as all snow melts during summer.