Retrospective and prospective model simulations of sea level rise impacts on Gulf of Mexico coastal marshes and forests in Waccasassa Bay, Florida

The State of Florida (USA) is especially threatened by sea level rise due to extensive low elevation coastal habitats (approximately 8,000?km²?<?1?m above sea level) where the majority of the human population resides. We used the Sea Level Affecting Marshes Model (SLAMM) simulation to improve understanding of the magnitude and location of these changes for 58,000?ha of the Waccasassa Bay region of Florida??s central Gulf of Mexico coast. To assess how well SLAMM portrays changes in coastal wetland systems resulting from sea level rise, we conducted a hindcast in which we compared model results to 30?years of field plot data. Overall, the model showed the same pattern of coastal forest loss as observed. Prospective runs of SLAMM using 0.64?m, 1?m and 2?m sea level rise scenarios predict substantial changes over this century in the area covered by coastal wetland systems including net losses of coastal forests (69%, 83%, and 99%, respectively) and inland forests (33%, 50%, and 88%), but net gains of tidal flats (17%, 142%, and 3,837%). One implication of these findings at the site level is that undeveloped, unprotected lands inland from the coastal forest should be protected to accommodate upslope migration of this natural community in response to rising seas. At a broader scale, our results suggest that coastal wetland systems will be unevenly affected across the Gulf of Mexico as sea level rises. Species vulnerable to these anticipated changes will experience a net loss or even elimination.     

Pathogenic fungi: an unacknowledged risk at coastal resorts? New insights on microbiological sand quality in Portugal

Whilst the potential impact on beach users from microorganisms in water has received considerable attention, there has been relatively little investigation into microbial contaminants in sand. Thirty three beaches across Portugal were analyzed during a five year period (2006-2010) to determine the presence of yeasts, pathogenic fungi, dermatophytes, total coliforms, Escherichia coli and intestinal enterococci in sand.Our results showed that 60.4% of the samples were positive for fungi and that 25.2% were positive for the bacterial parameters. The most frequent fungal species found were Candida sp. and Aspergillus sp., whereas intestinal enterococci were the most frequently isolated bacteria. Positive associations were detected among analyzed parameters and country-regions but none among those parameters and sampling period.Regarding threshold values, we propose 15 cfu/g for yeasts, 17 cfu/g for potential pathogenic fungi, 8 cfu/g for dermatophytes. Eighty four cfu/g for coliforms, 250 cfu/g for E. coli, and 100 cfu/g for intestinal enterococci.     

Representing Grounding Line Dynamics in Numerical Ice Sheet Models: Recent Advances and Outlook

Recent satellite observations of the Antarctic and Greenland ice sheets show accelerated ice flow and associated ice sheet thinning along coastal outlet glaciers in contact with the ocean. Both processes are the result of grounding line retreat due to melting at the grounding line (the grounding line is the contact of the ice sheet with the ocean, where it starts to float and forms an ice shelf or ice tongue). Such rapid ice loss is not yet included in large-scale ice sheet models used for IPCC projections, as most of the complex processes are poorly understood. Here we report on the state-of-the art of grounding line migration in marine ice sheets and address different ways in which grounding line migration can be attributed and represented in ice sheet models. Using one-dimensional ice flow models of the ice sheet/ice shelf system we carried out a number of sensitivity experiments with different spatial resolutions and stress approximations. These are verified with semi-analytical steady state solutions. Results show that, in large-scale finite-difference models, grounding line migration is dependent on the numerical treatment (e.g. staggered/non-staggered grid) and the level of physics involved (e.g. shallow-ice/shallow-shelf approximation).     

Phosphate defects and apatite inclusions in coral skeletal aragonite revealed by solid-state NMR spectroscopy

Recent development of paleo-nutrient proxies based on the phosphorus/calcium (P/Ca) ratio in tropical- and deep-water corals (also known as cold-water corals) require an understanding of the processes by which P is incorporated into the coral skeletal aragonite. Here, we apply single- and double-resonance solid-state nuclear magnetic resonance (NMR) spectroscopy to determine the speciation of P in coral aragonite. The results show that the majority of P occurs as phosphate defects in the aragonite structure, but in many samples a significant fraction of the P occurs also in crystalline hydroxylapatite inclusions. Quantification of the amount of hydroxylapatite indicates that its presence is not related simply to external environmental factors and that it can occur at varying abundances in different parts of the same corallite. Since there is currently no model available to describe the relationship between dissolved inorganic phosphate and its incorporation as apatite inclusions into carbonates, careful screening of samples which contain only phosphate in the aragonite structure or selective microsampling could improve proxy development.     

The dynamics of the snow avalanche affected areas in Piatra Mica mountains (Romania)

This article is intended to explain the snow avalanche occurrence, as a natural phenomenon directly influenced by the local natural conditions, for the well-delimited area represented by the Piatra Mica massif, belonging to the Piatra Craiului mountain range (southern Carpathians). In this respect, depending on the factors that may trigger or encourage the avalanches, some vulnerable areas with avalanche occurring conditions have been identified, based on the analysis of the relationships among the factors controlling the avalanche vulnerability in the study area. These factors are mainly represented by the slope aspect, which induces from the very beginning some specific features for each type of slope (north-, east-, south and west-facing slopes), the geological structure, slope gradient and topography. At the same time, the general climatic and biological features have been taken into account, from the point of view of their importance for avalanche occurrence and distribution. Depending on the microrelief exhibited by the avalanche chutes, one can establish distinct dynamical features for each of the four major slopes of the massif. It is worth mentioning that for this study area, this is the first paper dealing with avalanche phenomenon, vulnerable space, control factors and landscape dynamics. In accomplishing this demarche, we used detailed mappings in the field in several stages, the processing of satellite images, analytical (declivities, the exposure of slopes, etc.) and synthetic maps from which the dynamic of sectors with avalanches resulted. The findings of this investigation may further be employed for solving the problems raised by avalanche-prone areas, as well as for devising a better strategy for the effective management of the mountain realm.     

Spatial and temporal variability of deep-water algal assemblages in the Northwestern Mediterranean: The effects of an exceptional storm

There are deep-water populations of the endemic and threatened Mediterranean brown alga Cystoseira zosteroides in the Medes Islands Marine Reserve (NW Mediterranean). Here, the distribution, population structure, individual growth, mortality and recruitment rates of this species over two years are described in relation to the effects of an exceptional storm. We found a high spatial variability in the structure and dynamics of C. zosteroides populations at small geographical scales, suggesting that environmental factors acting at the population level display a key role in population size structure, mortality and recruitment. The elevated mortality rates recorded at some locations (almost 80%) is amongst the highest recorded for perennial algae as a consequence of a single storm, emphasizing the importance of episodic catastrophic events in the maintenance of these deep-water, slow-growing populations. These findings are of particular importance not only to fully understand the ecology of C. zosteroides, but also for its conservation.     

Effect of the dilution process on the attenuation of contaminants in aquifers

This paper discusses the effects of the dilution process on levels of aquifer contamination attenuation, developing analytical equations for application in theoretical and practical cases. The key finding is that, in aquifers, the dilution process causes a reduction of the contaminant concentration. Analytical equations for the assessment of the contaminant attenuation capacity, by means of the dilution process in an aquifer, are put forward. In particular, the attenuation of the contaminant concentration in an aquifer, and thus the dilution, is described by the volumetric flow rate per unit width perpendicular to the flow direction (q _u). Moreover, a classification of q _u was developed, considering six classes of attenuation capacity due to dilution. For the equations validation, nitrate contamination attenuation due to dilution was analysed in two sample areas in Piedmont (North-West Italy). The results confirmed the hypothesis, evidencing high nitrate concentrations in areas with low q _u values, connected to low dilution rate of the contaminant in the groundwater; vice versa, low nitrate concentrations were evidenced in areas with high q _u values, due to a high nitrate dilution rate.     

Inversion of time-dependent nuclear well-logging data using neural networks

The purpose of this work was to investigate a new and fast inversion methodology for the prediction of subsurface formation properties such as porosity, salinity and oil saturation, using time‐dependent nuclear well logging data. Although the ultimate aim is to apply the technique to real‐field data, an initial investigation as described in this paper, was first required; this has been carried out using simulation results from the time‐dependent radiation transport problem within a borehole. Simulated neutron and γ‐ray fluxes at two sodium iodide (NaI) detectors, one near and one far from a pulsed neutron source emitting at ～14 MeV, were used for the investigation. A total of 67 energy groups from the BUGLE96 cross section library together with 567 property combinations were employed for the original flux response generation, achieved by solving numerically the time‐dependent Boltzmann radiation transport equation in its even parity form. Material property combinations (scenarios) and their correspondent teaching outputs (flux response at detectors) are used to train the Artificial Neural Networks (ANNs) and test data is used to assess the accuracy of the ANNs. The trained networks are then used to produce a surrogate model of the expensive, in terms of computational time and resources, forward model with which a simple inversion method is applied to calculate material properties from the time evolution of flux responses at the two detectors. The inversion technique uses a fast surrogate model comprising 8026 artificial neural networks, which consist of an input layer with three input units (neurons) for porosity, salinity and oil saturation; and two hidden layers and one output neuron representing the scalar photon or neutron flux prediction at the detector. This is the first time this technique has been applied to invert pulsed neutron logging tool information and the results produced are very promising. The next step in the procedure is to apply the methodology to real data.