Iron Reduction Along an Inundation Gradient in a Tidal Sedge (<Emphasis Type="Italic">Cyperus malaccensis</Emphasis>) Marsh: the Rates,Pathways, and Contributions to Anaerobic Organic Matter Mineralization

Incubation experiments were adopted to characterize the rates and pathways of iron reduction and the contributions to anaerobic organic matter mineralization in the upper 0–5 cm of sediments along a landscape-scale inundation gradient in tidal marsh sediments in the Min River Estuary, Southeast China. Similar sediment characteristics, single-species vegetation, varied biomass and bioturbation, distinct porewater pH, redox potential, and electrical conductivity values have resulted in a unique ecogeochemical zonation along the inundation gradient. Decreases in solid-phase Fe(III) and increases in nonsulfidic Fe(II) and iron sulfide were observed in a seaward direction. Porewater Fe²⁺ was only detected in the upland area. High rates of iron reduction were observed in incubation jars, with significant accumulations of nonsulfidic Fe(II), moderate accumulations of iron sulfides, and negligible accumulations of porewater Fe²⁺. Most of the iron reduction was microbially mediated rather than coupled to reduced sulfides. Microbial iron reduction accounted for 20–89 % of the anaerobic organic matter mineralization along the inundation gradient. The rate and dominance of microbial iron reduction generally decreased in a seaward direction. The contributions of microbial iron reduction to anaerobic organic matter mineralization depended on the concentrations of bioavailable Fe(III), the spatial distribution of which was significantly related to tidal inundation. Our results clearly showed that microbial iron reduction in the upper sediments along the gradient is highly dependent on spatial scales controlled primarily by tidal inundation.     

Data-Driven Predictive Modeling of Mineral Prospectivity Using Random Forests: A Case Study in Catanduanes Island (Philippines)

The Random Forests (RF) algorithm is a machine learning method that has recently been demonstrated as a viable technique for data-driven predictive modeling of mineral prospectivity, and thus, it is instructive to further examine its usefulness in this particular field. A case study was carried out using data from Catanduanes Island (Philippines) to investigate further (a) if RF modeling can be used for data-driven modeling of mineral prospectivity in areas with few (i.e., <20) mineral occurrences and (b) if RF modeling can handle predictor variables with missing values. We found that RF modeling outperforms evidential belief (EB) modeling of prospectivity for hydrothermal Au–Cu deposits in Catanduanes Island, where 17 hydrothermal Au–Cu prospects are known to exist. Moreover, just like EB modeling, RF modeling allows analysis of the spatial relationships between known prospects and individual layers of predictor data. Furthermore, RF modeling can handle missing values in predictor data through an RF-based imputation technique whereas in EB modeling, missing values are simply represented by maximum uncertainty. Therefore, the RF algorithm is a potentially useful method for data-driven predictive modeling of mineral prospectivity in regions with few (i.e., <20) occurrences of mineral deposits of the type sought. However, further testing of the method in other regions with few mineral occurrences is warranted to fully determine its usefulness in data-driven predictive modeling of mineral prospectivity.     

Depth classification of underwater targets based on complex acoustic intensity of normal modes

In order to solve the problem of depth classification of the underwater target in a very low frequency acoustic field, the active component of cross spectra of particle pressure and horizontal velocity (ACCSPPHV) is adopted to distinguish the surface vessel and the underwater target. According to the effective depth of a Pekeris waveguide, the placing depth forecasting equations of passive vertical double vector hydrophones are proposed. Numerical examples show that when the sum of depths of two hydrophones is the effective depth, the sign distribution of ACCSPPHV has nothing to do with horizontal distance; in addition, the sum of the first critical surface and the second critical surface is equal to the effective depth. By setting the first critical surface less than the difference between the effective water depth and the actual water depth, that is, the second critical surface is greater than the actual depth, the three positive and negative regions of the whole ocean volume are equivalent to two positive and negative regions and therefore the depth classification of the underwater target is obtained. Besides, when the 20 m water depth is taken as the first critical surface in the simulation of underwater targets (40 Hz, 50 Hz, and 60 Hz respectively), the effectiveness of the algorithm and the correctness of relevant conclusions are verified, and the analysis of the corresponding forecasting performance is conducted.     

Tropical Atlantic climate response to different freshwater input in high latitudes with an ocean-only general circulation model

Tropical Atlantic climate change is relevant to the variation of Atlantic meridional overturning circulation (AMOC) through different physical processes. Previous coupled climate model simulation suggested a dipole-like SST structure cooling over the North Atlantic and warming over the South Tropical Atlantic in response to the slowdown of the AMOC. Using an ocean-only global ocean model here, an attempt was made to separate the total influence of various AMOC change scenarios into an oceanic-induced component and an atmospheric-induced component. In contrast with previous freshwater-hosing experiments with coupled climate models, the ocean-only modeling presented here shows a surface warming in the whole tropical Atlantic region and the oceanic-induced processes may play an important role in the SST change in the equatorial south Atlantic. Our result shows that the warming is partly governed by oceanic process through the mechanism of oceanic gateway change, which operates in the regime where freshwater forcing is strong, exceeding 0.3 Sv. Strong AMOC change is required for the gateway mechanism to work in our model because only when the AMOC is sufficiently weak, the North Brazil Undercurrent can flow equatorward, carrying warm and salty north Atlantic subtropical gyre water into the equatorial zone. This threshold is likely to be model-dependent. An improved understanding of these issues may have help with abrupt climate change prediction later.     

Mechanisms of partly flooded loose sand deposits

Partly flooded loose sand deposits are left back from lignite mining, particularly in east Germany. After flooding, gas inclusions in macropores enhance the pore pressure increase by total stress cycles without drainage, and this can cause the transition into a kind of suspension. Thus, natural and technical changes of surface loads triggered flow slides in chain reactions of sometimes catastrophic extent. Such collapsible deposits were and are stabilized by blast-induced liquefaction and densification. Successive collapse fronts in flooded grain skeletons are seismogeneous, and this appears as wavering in the near-field and leads to power-law spectra in the far-field. Apart from this evidence of mild fractality, the wild fractality of chain reactions eludes mathematical treatment. Therefore, uncommon methods of geotechnical design, operations and monitoring are required.     

Intrinsic groundwater vulnerability determination at the aquifer scale: a methodology coupling travel time estimation and rating methods

Groundwater vulnerability has been subject of much research due to the valuable information it provides concerning groundwater protection and exploitation potential. Up to now, most groundwater vulnerability studies adopt subjective systems of rating the various factors and subsequently, their results are often ambiguous and contradicting. Within the present study a methodology for the estimation of intrinsic groundwater vulnerability at the aquifer scale is presented. The methodology is based on travel time estimation from specified sources of pollution to the aquifer. Besides the deterministic calculation of travel times, the methodology provides a rating system for each pollution source, based on its relative severity and the estimated threat that it poses to the aquifer. Therefore, it can be regarded as a hybrid method that couples the advantages provided by the physically based methods with those of the subjective rating systems. The methodology is applied to the Neon Sidirochorion aquifer, Northeastern Greece, an overexploited aquifer where river waters, sea waters and lake waters interact, causing groundwater quality deterioration to the aquifer. The results indicated that the proposed groundwater vulnerability assessment methodology is well capturing pollution related to saltwater intrusion and agricultural activities, while it is concluded that the conceptual model is significantly affecting the vulnerability assessment results and therefore has to be previously developed.     

Estimation of air-overpressure produced by blasting operation through a neuro-genetic technique

Blasting operations usually produce significant environmental problems which may cause severe damage to the nearby areas. Air-overpressure (AOp) is one of the most important environmental impacts of blasting operations which needs to be predicted and subsequently controlled to minimize the potential risk of damage. In order to solve AOp problem in Hulu Langat granite quarry site, Malaysia, three non-linear methods namely empirical, artificial neural network (ANN) and a hybrid model of genetic algorithm (GA)–ANN were developed in this study. To do this, 76 blasting operations were investigated and relevant blasting parameters were measured in the site. The most influential parameters on AOp namely maximum charge per delay and the distance from the blast-face were considered as model inputs or predictors. Using the five randomly selected datasets and considering the modeling procedure of each method, 15 models were constructed for all predictive techniques. Several performance indices including coefficient of determination (R ²), root mean square error and variance account for were utilized to check the performance capacity of the predictive methods. Considering these performance indices and using simple ranking method, the best models for AOp prediction were selected. It was found that the GA–ANN technique can provide higher performance capacity in predicting AOp compared to other predictive methods. This is due to the fact that the GA–ANN model can optimize the weights and biases of the network connection for training by ANN. In this study, GA–ANN is introduced as superior model for solving AOp problem in Hulu Langat site.     

Do Macroalgal Mats Impact Microphytobenthos on Mudflats? Evidence from a Meta-Analysis,Comparative Survey,and Large-Scale Manipulation

Eutrophication and species introductions have resulted in increased macroalgal biomass in coastal ecosystems around the globe. Macroalgal mats may compete with microphytobenthos (MPB) for light and nutrients and, due to their position in the canopy, have a negative impact on MPB biomass. We tested this effect by conducting a meta-analysis of prior experiments, as well as a comparative survey, and a macroalgal-removal manipulation in the coastal lagoons of the Virginia Coastal Reserve (VCR) on the eastern shore of Virginia (USA). In all cases, MPB biomass was estimated using benthic chlorophyll as a proxy. While prior individual studies documented impacts of macroalgae, when effect sizes were averaged across studies, there was no consistent effect of macroalgal biomass on MPB biomass. In the VCR, a non-native red macroalga, Gracilaria vermiculophylla, dominates intertidal mats and attains high biomasses at some sites. Nevertheless, MPB biomass was unrelated to macroalgal mass based on a survey of mudflats. Further, when macroalgae were experimentally manipulated on a mudflat using a before and after impact design, there was no change in MPB. Based on the meta-analysis, survey, and manipulation we conducted, macroalgal mats do not have a generalizable effect on MPB, interactions seem context-dependent, and in the VCR, the effects on MPB appear neutral. This finding is important given the significance of MPB in supporting food webs and other estuarine ecosystem functions, as well as the increasing frequency and intensity of macroalgal blooms.     

Formation by silicate–fluoride + phosphate melt immiscibility of REE-rich globular segregations within aplite dikes

Aplite dikes intruding the Proterozoic 1.42(±?3) Ga Longs Peak-St. Vrain Silver Plume-type peraluminous granite near Jamestown, Colorado, contain F, P, and rare earth element (REE)-rich globular segregations, with 40–46% REE, 3.7–4.8 wt% P₂O₅, and 5–8 wt% F. A combination of textural features and geochemical data suggest that the aplite and REE-rich globular segregations co-existed as two co-genetic liquids prior to their crystallization, and we propose that they are formed by silicate–fluoride?+?phosphate (+?S?+?CO₂) melt immiscibility following ascent, cooling, and decompression of what was initially a single homogeneous magma that intruded the granite. The REE distribution coefficients between the silica-rich aplites and REE-rich segregations are in good agreement with experimentally determined distribution coefficients for immiscible silicate–fluoride?+?phosphate melts. Although monazite-(Ce) and uraninite U–Th–Pb microprobe ages for the segregations yield 1.420(±?25) and 1.442(±?8) Ga, respectively, thus suggesting a co-genetic relationship with their host granite, ε_Nd1.42Ga values for the granites and related granitic pegmatites range from ??3.3 to ??4.7 (average ??3.9), and differ from the values for both the aplites and REE-rich segregations, which range from ??1.0 to ??2.2 (average ??1.6). Furthermore, the granites and pegmatites have (La/Yb)_N <50 with significant negative Eu anomalies, which contrast with higher (La/Yb)_N >100 and absence of an Eu anomaly in both the aplites and segregations. These data are consistent with the aplite dikes and the REE-rich segregations they contain being co-genetic, but derived from a source different from that of the granite. The higher ε_Nd1.42Ga values for the aplites and REE-rich segregations suggest that the magma from which they separated had a more mafic and deeper, dryer and hotter source in the lower crust or upper mantle compared to the quartzo-feldspathic upper crustal source proposed for the Longs Peak-St. Vrain granite.