Seasonal patterns of tidepool macroalgal assemblages in the North of Portugal. Consistence between species and functional group approaches

Macroalgae are useful organisms to monitor the environmental quality and to detect impacts due to anthropogenic activities. However, it is very important to identify the scales of variation in natural assemblages, particularly for the detection of environmental impacts. Otherwise, changes due to anthropogenic impacts may be confused with differences due to natural temporal variability. Another important task is to determine the appropriate level of taxonomical effort needed to detect changes in the assemblage structure. Many taxonomical surrogates, at higher taxonomic levels than that of species, have been proposed but, the consistence in space and time of the results produced by surrogates with those obtained at specific level should be tested. The objectives of this study are to identify the seasonal patterns of tidepool macroalgal communities using objective procedures and to test the consistence between the patterns obtained considering data at the species level and functional groups. Results showed that the seasonal pattern obtained using functional groups and species was consistent. Tidepool macroalgal assemblages showed a seasonal pattern with significant differences between spring–summer and autumn–winter. This pattern can be explained by changes in environmental variables and the seasonal development of the dominating species. Ulva spp. and the non-indigenous species Grateloupia turuturu were the species responsible for this pattern due to their high seasonality in terms of biomass. Finally, the abundance and species diversity within the corticated functional group was proposed as indicator of environmental impacts due to its relatively constant abundance and its sensitivity to environmental impacts.     

Accurate seabed modeling using finite difference methods

Finite difference is the most widely used method for seismic wavefield modeling. However, most finite-difference implementations discretize the Earth model over a fixed grid interval. This can lead to irregular model geometries being represented by ‘staircase’ discretization, and potentially causes mispositioning of interfaces within the media. This misrepresentation is a major disadvantage to finite difference methods, especially if there exist strong and sharp contrasts in the physical properties along an interface. The discretization of undulated seabed bathymetry is a common example of such misrepresentation of the physical properties in finite-difference grids, as the seabed is often a particularly sharp interface owing to the rapid and considerable change in material properties between fluid seawater and solid rock. There are two issues typically involved with seabed modeling using finite difference methods: firstly, the travel times of reflections from the seabed are inaccurate as a consequence of its spatial mispositioning; secondly, artificial diffractions are generated by the staircase representation of dipping seabed bathymetry. In this paper, we propose a new method that provides a solution to these two issues by positioning sharp interfaces at fractional grid locations. To achieve this, the velocity model is first sampled in a model grid that allows the center of the seabed to be positioned at grid points, before being interpolated vertically onto a regular modeling grid using the windowed sinc function. This procedure allows undulated seabed bathymetry to be represented with improved accuracy during modeling. Numerical tests demonstrate that this method generates reflections with accurate travel times and effectively suppresses artificial diffractions.     

A Multistep Methodology for Building a Stochastic Model of Gold Grades in the Disseminated and Complex Deposit of Casas Novas in Alentejo,Southern Portugal

This paper proposes a multistep approach for creating a 3D stochastic model of gold grades in a complex disseminated auriferous deposit located in the Alentejo region, southern Portugal. The approach involves the following steps: (i) the creation of a 3D low‐resolution vector object model of two geological domains that better discriminate gold grades; (ii) the definition of three intervals for gold grades (low, intermediate, and high values); (iii) the estimation of the probability of each grid block belonging to each interval constrained by the geological domains; (iv) the calculation of local conditional cumulative distribution functions (CCDFs) of gold grades, for each block, taking into account the geological domains and the borehole data; and finally (v) the simulation of images of gold grades. The results demonstrate the usefulness and accuracy of the proposed procedure, as they are in compliance with the conceptual model, the distribution laws are conditioned by the geological domains, and the transition of grades between domains is continuous.     

El Niño influence on streamflow forecasting

Stochastic models are often fitted to historical data in order to produce streamflow scenarios. These scenarios are used as input data for simulation/optimization models that support operational decisions for water resource systems. The streamflow scenarios are sampled from probability distributions conditioned on the available information, such as recent streamflow data. In this paper we introduce a procedure for further conditioning the probability distributions by considering the recent measurements of climatic variables, such as sea temperatures, that are used to describe the occurrence of El Ni?o. We adopt an auto-regressive model and use the “El Ni?o information” to refine the parameter estimation process for each time step. The corresponding methodology is tested for the monthly energy time series, “inflowing” to the power plants of Colombia. This is a linear combination of streamflow values for the 18 most important rivers of the country.     

Limits to Mercury's magnesium exosphere from MESSENGER second flyby observations

The discovery measurements of Mercury's exospheric magnesium, obtained by the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) probe during its second Mercury flyby, are modeled to constrain the source and loss processes for this neutral species. Fits to a Chamberlain exosphere reveal that at least two source temperatures are required to reconcile the distribution of magnesium measured far from and near the planet: a hot ejection process at the equivalent temperature of several tens of thousands of degrees K, and a competing, cooler source at temperatures as low as 400 K. For the energetic component, our models indicate that the column abundance that can be attributed to sputtering under constant southward interplanetary magnetic field conditions is at least a factor of five less than the rate dictated by the measurements. Although highly uncertain, this result suggests that another energetic process, such as the rapid dissociation of exospheric MgO, may be the main source of the distant neutral component. If meteoroid and micrometeoroid impacts eject mainly molecules, the total amount of magnesium at altitudes exceeding ∼100 km is found to be consistent with predictions by impact vaporization models for molecule lifetimes of no more than two minutes. Though a sharp increase in emission observed near the dawn terminator region can be reproduced if a single meteoroid enhanced the impact vapor at equatorial dawn, it is much more likely that observations in this region, which probe heights increasingly near the surface, indicate a reservoir of volatile Mg being acted upon by lower-energy source processes.     

A methodology for quantifying the value of spatial information for dynamic Earth problems

We develop a methodology for assessing the value of information (VOI) from spatial data for groundwater decisions. Two sources of uncertainty are the focus of this VOI methodology: the spatial heterogeneity (how it influences the hydrogeologic response of interest) and the reliability of geophysical data (how they provide information about the spatial heterogeneity). An existing groundwater situation motivates and in turn determines the scope of this research. The objectives of this work are to (1) represent the uncertainty of the dynamic hydrogeologic response due to spatial heterogeneity, (2) provide a quantitative measure for how well a particular information reveals this heterogeneity (the uncertainty of the information) and (3) use both of these to propose a VOI workflow for spatial decisions and spatial data. The uncertainty of the hydraulic response is calculated using many Earth models that are consistent with the a priori geologic information. The information uncertainty is achieved quantitatively through Monte Carlo integration and geostatistical simulation. Two VOI results are calculated which demonstrate that a higher VOI occurs when the geophysical attribute (the data) better discriminates between geological indicators. Although geophysical data can only indirectly measure static properties that may influence the dynamic response, this transferable methodology provides a framework to estimate the value of spatial data given a particular decision scenario.     

The Colorado East River Community Observatory Data Collection

The U.S. Department of Energy's (DOE) Colorado East River Community Observatory (ER) in the Upper Colorado River Basin was established in 2015 as a representative mountainous, snow-dominated watershed to study hydrobiogeochemical responses to hydrological perturbations in headwater systems. The ER is characterized by steep elevation, geologic, hydrologic and vegetation gradients along floodplain, montane, subalpine, and alpine life zones, which makes it an ideal location for researchers to understand how different mountain subsystems contribute to overall watershed behaviour. The ER has both long-term and spatially-extensive observations and experimental campaigns carried out by the Watershed Function Scientific Focus Area (SFA), led by Lawrence Berkeley National Laboratory, and researchers from over 30 organizations who conduct cross-disciplinary process-based investigations and modelling of watershed behaviour. The heterogeneous data generated at the ER include hydrological, genomic, biogeochemical, climate, vegetation, geological, and remote sensing data, which combined with model inputs and outputs comprise a collection of datasets and value-added products within a mountainous watershed that span multiple spatiotemporal scales, compartments, and life zones. Within 5 years of collection, these datasets have revealed insights into numerous aspects of watershed function such as factors influencing snow accumulation and melt timing, water balance partitioning, and impacts of floodplain biogeochemistry and hillslope ecohydrology on riverine geochemical exports. Data generated by the SFA are managed and curated through its Data Management Framework. The SFA has an open data policy, and over 70 ER datasets are publicly available through relevant data repositories. A public interactive map of data collection sites run by the SFA is available to inform the broader community about SFA field activities. Here, we describe the ER and the SFA measurement network, present the public data collection generated by the SFA and partner institutions, and highlight the value of collecting multidisciplinary multiscale measurements in representative catchment observatories.     

Using a genetic algorithm for 3-D inversion of gravity data in Fuerteventura (Canary Islands)

The use of genetic algorithms in geophysical inverse problems is a relatively recent development and offers many advantages in dealing with the non-linearity inherent in such applications. We have implemented a genetic algorithm to efficiently invert a set of gravity data. Employing several fixed density contrasts, this algorithm determines the geometry of the sources of the anomaly gravity field in a 3-D context. The genetic algorithms, based on Darwins theory of evolution, seek the optimum solution from an initial population of models, working with a set of parameters by means of modifications in successive iterations or generations. This searching method traditionally consists of three operators (selection, crossover and mutation) acting on each generation, but we have added a further one, which smoothes the obtained models. In this way, we have designed an efficient inversion gravity method, confirmed by both a synthetic example and a real data set from the island of Fuerteventura. In the latter case, we identify crustal structures related to the origin and evolution of the island. The results show a clear correlation between the sources of gravity field in the model and the three volcanic complexes recognized in Fuerteventura by other geological studies.