Beneath the surface: Characteristics of oceanic ecosystems under weak mixing conditions – A theoretical investigation

This study considers an important biome in aquatic environments, the subsurface ecosystem that evolves under low mixing conditions, from a theoretical point of view. Employing a conceptual model that involves phytoplankton, a limiting nutrient and sinking detritus, we use a set of key characteristics (thickness, depth, biomass amplitude/productivity) to qualitatively and quantitatively describe subsurface biomass maximum layers (SBMLs) of phytoplankton. These SBMLs are defined by the existence of two community compensation depths in the water column, which confine the layer of net community production; their depth coincides with the upper nutricline. Analysing the results of a large ensemble of simulations with a one-dimensional numerical model, we explore the parameter dependencies to obtain fundamental steady-state relationships that connect primary production, mortality and grazing, remineralization, vertical diffusion and detrital sinking. As a main result, we find that we can distinguish between factors that determine the vertically integrated primary production and others that affect only depth and shape (thickness and biomass amplitude) of this subsurface production layer. A simple relationship is derived analytically, which can be used to estimate the steady-state primary productivity in the subsurface oligotrophic ocean. The fundamental nature of the results provides further insight into the dynamics of these “hidden” ecosystems and their role in marine nutrient cycling.     

Comparison of Supercontinent Cycles in the Metallogeny of Rare Earth Elements

The distribution of integrated resources of large and superlarge deposits (LSLDs) of rare earth elements (REEs) is compared to the current model of supercontinent cyclicity during Earth’s evolution. It is found that REE LSLDs are related predominantly to igneous complexes (carbonatite, nepheline syenites, syenite-alkaline granites, subalkaline granites), which are often additionally enriched in the hypergenic zone. A certain part of the resources is concentrated in independent hypergenic formations represented by placers and ion-adsorbed clays. Each supercontinent cycle—Kenoran, Columbian, Rodinian, Pangean, and Amasian—is expressed in the REE metallogeny in particular way: we revealed significant intercycle variations in the amount of REE LSLDs, the variety of their types, total accumulated resources, and some other characteristics.     

A level-set corrector to an adaptive multiscale permeability prediction

We consider the inverse problem of permeability estimation for two-phase porous-media flow. The novel approach is based on regularization by zonation, where the geometry and size of the regions are chosen adaptively during the optimization procedure. To achieve this, we have utilized level-set functions to represent the permeability. The available data are sparsely distributed in space; hence, it is reasonable to confine the estimation to coarse-scale structures. The level-set approach is able to alter the boundaries between regions of different permeability without strict restrictions on their shape; however, when the data are sparse, a reasonable initial guess for the permeability is required. For this task, we use adaptive multiscale permeability estimation, which has the potential of identifying main permeability variations. These are described by a piecewise constant function, where the constant values are attained on rectangular zones. In the current work, we develop a level-set corrector strategy, assuming adaptive multiscale permeability estimation as a predictor.     

Projected climate change impact on Baltic Sea cyanobacteria

Compared to other phytoplankton groups, nitrogen-fixing cyanobacteria generally prefer high water temperatures for growth and are therefore expected to benefit from global warming. We use a coupled biological-physical model with an advanced cyanobacteria life cycle model to compare the abundance of cyanobacteria in the Baltic Sea during two different time periods (1969–1998; 2069–2098). For the latter, we find prolonged growth and a more than twofold increase in the climatologically (30 years) averaged cyanobacteria biomass and nitrogen fixation. Additional sensitivity experiments indicate that the biological-physical feedback mechanism through light absorption becomes more important with global warming. In general, we find a nonlinear response of cyanobacteria to changes in the atmospheric forcing fields as a result of life-cycle related feedback mechanisms. Overall, the sensitivity of the cyanobacteria-driven system suggests that biological-physical and life-cycle related feedback mechanisms are important and must therefore be included in future projection studies.     

Investigating Bermuda's pollution history through stable isotope analyses of modern and museum-held gorgonian corals

For centuries, Bermuda has been challenged with wastewater management for the protection of human and environmental health. By quantifying the δ¹⁵N of the common sea fan Gorgonia ventalina sampled from 30 sites throughout Bermuda we show that sewage-derived nitrogen is detectable on nearshore coral reefs and declines across the lagoon to the outer rim. We also sampled gorgonians from two museum collections representing a 50y time-series (1958–2008). These samples revealed an increase in δ¹⁵N of > 4.0‰ until the mid-1970s, after which δ¹⁵N values slowly declined by ~ 2.0‰. A δ¹⁵N chronology from a gorgonian skeleton exhibited a similar decline over the last 30–40 years of approximately 0.6‰. We conclude that policies have been effective in reducing sewage impacts to Bermudian reefs. However, significant sources of sewage pollution persist and are likely have a strong impact on harbor and nearshore coral communities and human health.     

Formation of Pt-bearing Western Pana pluton on the Kola Peninsula: Fluid regime as deduced from helium and argon isotopic compositions

The distribution of He and Ar isotopes has been studied in 41 rock samples and seven monomineralic fractions from ore-bearing layered units and poorly differentiated host gabbronorite of the Western Pana mafic–ultramafic pluton on the Kola Peninsula. The gases assigned for mass-spectrometric analysis were released by means of whole-rock sample melting and by comminution mainly from fluid microinclusions. The data show that the present-day isotopic composition of noble gases in rocks from the pluton is caused by many factors: the degree of melt degassing, various concentrations and retention of the trapped isotopes, the contents of radioactive elements, and the generation and loss of radiogenic gases. The hypabyssal conditions of pluton formation facilitate the loss of primary mantle-derived volatile components and the dilution of magmatic fluid with near-surface paleometeoric waters containing air dissolved therein. The correlation of noble gas isotopes and ore-forming chemical elements does not suggest derivation of the latter from crustal material and evidences their mantle origin. Variations in the geochemical indices of the gas corroborate previously established or proposed multistage formation of the pluton, mainly, the autometamorphic character of postmagmatic processes and the participation of fluids in ore formation.     

Lagrangian analysis by clustering

We propose a new method for obtaining average velocities and eddy diffusivities from Lagrangian data. Rather than grouping the drifter-derived velocities in geographical bins, we group them by nearest-neighbor distance using a clustering algorithm. This yields sets with approximately the same number of observations, covering unequal areas. A major advantage is that, because the number of observations is the same for the clusters, the statistical accuracy is more uniform than with geographical bins. We illustrate the technique using synthetic data from a stochastic model, employing a realistic mean flow. The latter represents the surface currents in the Nordic Seas and is strongly inhomogeneous in space. We use the clustering algorithm to extract the mean velocities and diffusivities and compare the results with the corresponding quantities from the stochastic model. We perform a similar comparison with the means and diffusivities obtained with geographical bins. Clustering is more successful at capturing the mean flow and improves convergence in the eddy diffusivity estimates. We discuss both the advantages and shortcomings of the new method.