Phytoplankton biomass and size fractions in surface waters of the Australian sector of the southern ocean

We collected surface water along the 142nd E meridian from Tasmania to Antarctica in December 1999. We measured temperature, salinity and total chlorophyll a; additionally, we collected suspended particle size fractions and used fluorometric analysis to determine the quantity of chlorophyll a in each of four cell size classes: picoplankton (<3 μm), two nanoplankton fractions (3–10 μm and 10–20 μm) and microplankton (> 20 μm). Changes in temperature and salinity show that we crossed 6 water masses separated by 5 fronts. We found low abundance (<0.2 mg m⁻³) of chlorophyll in all size classes, with the exception of higher values near the continent (0.2 to 0.4 mg m⁻³). Lowest chlorophyll values (<0.1 mg m⁻³) were found in the Polar Frontal Zone (51° to 54°S). Microplankton made up the largest portion of total chlorophyll throughout most of the region. We conclude that biomass of all phytoplankton fractions, especially pico-and nanoplankton, was constrained by limiting factors, most probably iron, throughout the region and that ecosystem dynamics within a zone are not circumpolar but are regionalized within sectors.     

Microbial Diversity in Nankai Trough Sediments at a Depth of 3,843 m

Dense populations of bivalves, primarily Calyptogena sp., were observed at cold seeps of the Nankai Trough. Bacterial input to the sediment was estimated through determination of phospholipid ester-linked fatty acid (PLFA) and DNA profiles. Results indicated a bacterial biomass of 10⁹ cells (g dry wt)^-1 while individual fatty acid profiles revealed a predominance of monounsaturated fatty acids, mainly 18:1 isomers. The presence of these fatty acids can be interpreted to reflect a response to low temperature and a predominance of psychrophilic bacteria. DNA fragments encoding bacterial ribosomal RNA small-subunit sequences (16S rDNA) were amplified by the polymerase chain reaction method using DNA extracted directly from the sediment samples. From the sequencing results, at least 19 kinds of bacterial 16S rDNAs related to mostly the Proteobacteria and a few gram-positive bacteria were identified. These results suggest that the bacterial community in the Nankai Trough sediments consists of mainly bacteria belonging to the Proteobacteria , , and subdivisions. Bacteria belonging to the and subdivisions, which are known to include epibiont and sulfate reducing bacteria, respectively, were mostly detected in the sediment obtained from inside the area of the Calyptogena community, and the -Proteobacteria may function to supply reduced sulfur to bacterial endosymbionts of Calyptogena.     

Evidence for microbiological manganese oxidation in the river Tamar Estuary, South West England

Water samples from the Tamar Estuary oxidized manganese when supplemented with Mn²⁺ (2 mgl⁻¹). The rates of oxidation were depressed in the presence of various metabolic inhibitors. The effect of Mn²⁺ and temperature on the rate of manganese oxidation suggested that a biological process was largely responsible for converting Mn²⁺ to Mn⁴⁺. Rates of manganese oxidation were much higher in freshwater (3·32 μgl⁻¹ h⁻¹ in water containing 30 mgl⁻¹ of suspended matter) than in saline water (0·7 μgl⁻¹ h⁻¹ in water of salinity 32‰) containing the same amount of particulate matter. The rate of manganese oxidation was proportional to the particulate load (up to 100 mgl⁻¹ particulates).     

PM10 Source Apportionment in Ahvaz,Iran, Using Positive Matrix Factorization

Source apportionment of particulate matter <10 µm in diameter (PM₁₀), having considerable impacts on human health and the environment, is of high priority in air quality management. The present study, therefore, aimed at identifying the potential sources of PM₁₀ in an arid area of Ahvaz located in southwest of Iran. For this purpose, we collected 24‐h PM₁₀ samples by a high volume air sampler. The samples were then analyzed for their elemental (Al, As, B, Ba, Be, Ca, Cd, Co, Cr, Cu, Fe, Hg, K, Mg, Mn, Na, Ni, Pb, Se, Si, Sn, Sr, Li, Ti, V, Zn, Mo, and Sb) and ionic (NH, Cl^?, NO, and SO) components using inductively coupled plasma optical emission spectrometry and ion chromatography instruments, respectively. Eight factors were identified by positive matrix factorization: crustal dust (41.5%), road dust (5.5%), motor vehicles (11.5%), marine aerosol (8.0%), secondary aerosol (9.5%), metallurgical plants (6.0%), petrochemical industries and fossil fuel combustion (13.0%), and vegetative burning (5.0%). Result of this study suggested that the natural sources contribute most to PM₁₀ particles in the area, followed closely by the anthropogenic sources.     

Gravel‐bed rivers: from particles to patterns

The papers in this special issue reflect several of the major themes and topics from the 7^th International Workshop on Gravel‐Bed Rivers. The papers focus primarily on aspects of bed material transport in gravel‐bed rivers and larger scale morpho‐dynamics. Research in gravel‐bed rivers is increasingly integrating processes over a wide range of temporal and spatial scales by combining field observation, lab experimentation, numerical modeling and theory testing in a range of river types, aided by new technological developments in particle tracking, computational modeling and high resolution spatial data. This is leading to greater understanding of the processes leading to distinctive morpho‐dynamics of river types and a more reliable basis for river management. Copyright © 2012 John Wiley & Sons, Ltd.     

Surveying Upstate NY Well Water for Pesticide Contamination: Cayuga and Orange Counties

Private wells in Cayuga and Orange counties in New York were sampled to determine the occurrence of pesticide contamination of groundwater in areas where significant pesticide use coincides with shallow or otherwise vulnerable groundwater. Well selection was based on local groundwater knowledge, risk modeling, aerial photo assessments, and pesticide application database mapping. Single timepoint samples from 40 wells in each county were subjected to 93‐compound chromatographic scans. All samples were nondetects (reporting limits ≤1 μg/L), thus no wells from either county exceeded any of 15 state groundwater standards or guidance values. More sensitive enzyme‐linked immunosorbent assays (ELISA) found two wells with quantifiable atrazine in each county (0.1–0.3 μg/L), one well with quantifiable diazinon (0.1 μg/L) in Orange County, and one well with quantifiable alachlor (0.2 μg/L) in Cayuga County. Trace detections (<0.1 μg/L) in Cayuga County included atrazine (five wells), metolachlor (six wells), and alachlor (one well), including three wells with multiple detections. All 12 Cayuga County wells with ELISA detections had either corn/grain or corn/forage rotations as primary surrounding land uses (although 20 other wells with the same land uses had no detections) and all quantified detections and most trace detections occurred in wells up to 9‐m deep. Orange County trace (<0.1 μg/L) ELISA detections (atrazine three wells, diazinon one well, and metolachlor five wells) and quantified detections were only generally associated with agricultural land uses. Finding acceptable drinking water quality in areas of vulnerable groundwater suggests that water quality in less vulnerable areas will also be good.     

Relevance of Deterministic Structures for Modeling of Transport: The Lauswiesen Case Study

Knowledge of site‐specific contaminant transport processes is an essential requirement for performing various tasks concerning the protection and management of groundwater resources. However, prediction of their behavior is often difficult, especially in heterogeneous aquifers because of the lack of information about flow‐ and transport‐governing subsurface structures and parameters. Hence, stochastic approaches have been developed and frequently used. However, extensive modeling studies on sedimentary structures have shown that consideration of hydrogeological subunits and their distribution can be essential for transport modeling. A case study from the intensely investigated Lauswiesen site is used to demonstrate that more accurate predictions are possible with improved knowledge of deterministic structures. Results of this case study using direct‐push injection logging (DPIL) provide a more reliable characterization of hydraulic conductivity than sieve and flow meter data.     

Building and Testing an <Emphasis Type="Italic">a priori</Emphasis> Geophysical Model for Western Eurasia and North Africa

We construct and evaluate a new three-dimensional model of crust and upper mantle structure in Western Eurasia and North Africa (WENA) extending to 700 km depth and having 1° parameterization. The model is compiled in an a priori fashion entirely from existing geophysical literature, specifically, combining two regionalized crustal models with a high-resolution global sediment model and a global upper mantle model. The resulting WENA1.0 model consists of 24 layers: water, three sediment layers, upper, middle, and lower crust, uppermost mantle, and 16 additional upper mantle layers. Each of the layers is specified by its depth, compressional and shear velocity, density, and attenuation (quality factors, Q _P and Q _S ). The model is tested by comparing the model predictions with geophysical observations including: crustal thickness, surface wave group and phase velocities, upper mantle _n velocities, receiver functions, P-wave travel times, waveform characteristics, regional 1-D velocities, and Bouguer gravity. We find generally good agreement between WENA1.0 model predictions and empirical observations for a wide variety of independent data sets. We believe this model is representative of our current knowledge of crust and upper mantle structure in the WENA region and can successfully be used to model the propagation characteristics of regional seismic waveform data. The WENA1.0 model will continue to evolve as new data are incorporated into future validations and any new deficiencies in the model are identified. Eventually this a priori model will serve as the initial starting model for a multiple data set tomographic inversion for structure of the Eurasian continent.