Depth profiles of bacterioplankton assemblages and their activities in the Ross Sea

The identification of bacterial community structure has led, since the beginning of the 1990s, to the idea that bacterioplankton populations are stratified in the water column and that diverse lineages with mostly unknown phenotypes dominate marine microbial communities. The diversity of depth-related assemblages is also reflected in their patterns of activities, as bacteria affiliated to different groups can express different activities in a given ecosystem. We analysed bacterial assemblages (DGGE fingerprinting) and their activities (prokaryotic carbon production, protease, phosphatase, chitinase, beta-glucosidase and lipase activities) in two areas in the Ross Sea, differing mainly in their productivity regime: two stations are located in the Terra Nova Bay polynya area (highly productive during summer) and two close to Cape Adare (low phytoplankton biomass and activity). At every station a pronounced stratification of bacterial assemblages was identified, highlighting epipelagic communities differing substantially from the mesopelagic and the bathypelagic communities. Multivariate analysis suggested that pressure and indirectly light-affected variables (i.e. oxygen and fluorescence) had a great effect on the bacterial communities outcompeting the possible influences of temperature and dissolved organic carbon concentration. Generally activities decreased with depth even though a signal of the Circumpolar Deep Water (CDW) at one of the northern stations corresponded to an increase in some of the degradative activities, generating some ‘hot spots’ in the profile. We also found that similar assemblages express similar metabolic requirements reflected in analogous patterns of activity (similar degradative potential and leucine uptake rate). Furthermore, the presence of eukaryotic chloroplasts’ 16S rDNA in deep samples highlighted how in some cases the dense surface-water formation (in this case High Salinity Shelf Water—HSSW) and downwelling can affect, at least for some phylotypes, the bacterial (16S rDNA based) community structure of the dark ocean.     

Distrubution of Dissolved and Particulate Iron, copper and Manganese in the Shelf waters of the Ross sea (Antarctica)

Abstract. During the austral summer 1997–98, within the framework of the activities of the Climatic Long-term Interaction for the Massbalance in Antarctica (CLIMA) Project of the Italian National Program for Antarctic Research (PNRA) in the Ross Sea, measurements were conducted to focus on the role of dissolved iron, copper and manganese as micronutrients, and on their distribution in suspended particulate matter in different water masses. Sampling was carried out in two selected shelf areas, both important for formation and mixing processes of the water bodies.
Metal data were evaluated together with physical measurements and classical chemical parameters such as oxygen and nutrients.
In both the studied areas, the distribution of dissolved metals along the waste column confirmed their micronutrient behaviour, showing depletion where phytoplanktonic activities occurred.
The trend of particulate metals underlined the scavenging phenomena along the water column and presented an interesting correlation at intermediate depths with the amount and origin of suspended matter.     

Impacts of land use on the hydrological response of tropical Andean catchments

Changes in land use and land cover are major drivers of hydrological alteration in the tropical Andes. However, quantifying their impacts is fraught with difficulties because of the extreme diversity in meteorological boundary conditions, which contrasts strongly with the lack of knowledge about local hydrological processes. Although local studies have reduced data scarcity in certain regions, the complexity of the tropical Andes poses a big challenge to regional hydrological prediction. This study analyses data generated from a participatory monitoring network of 25 headwater catchments covering three of the major Andean biomes (páramo, jalca and puna) and links their hydrological responses to main types of human interventions (cultivation, afforestation and grazing). A paired catchment setup was implemented to evaluate the impacts of change using a ‘trading space‐for‐time’ approach. Catchments were selected based on regional representativeness and contrasting land use types. Precipitation and discharge have been monitored and analysed at high temporal resolution for a time period between 1 and 5 years. The observed catchment responses clearly reflect the extraordinarily wide spectrum of hydrological processes of the tropical Andes. They range from perennially humid páramos in Ecuador and northern Peru with extremely large specific discharge and baseflows, to highly seasonal, flashy catchments in the drier punas of southern Peru and Bolivia. The impacts of land use are similarly diverse and their magnitudes are a function of catchment properties, original and replacement vegetation and management type. Cultivation and afforestation consistently affect the entire range of discharges, particularly low flows. The impacts of grazing are more variable but have the largest effect on the catchment hydrological regulation. Overall, anthropogenic interventions result in increased streamflow variability and significant reductions in catchment regulation capacity and water yield, irrespective of the hydrological properties of the original biome. Copyright © 2016 The Authors. Hydrological Processes. Published by John Wiley & Sons Ltd.     

Diagnosis of physical and biological controls on phytoplankton distribution in the Sargasso Sea

The linkage between physical and biological processes is studied by applying a one-dimensional physical-biological coupled model to the Sargasso Sea. The physical model is the Princeton Ocean Model and the biological model is a five-component system including phytoplankton, zooplankton, nitrate, ammonium, and detritus. The coupling between the physical and biological model is accomplished through vertical mixing which is parameterized by the level 2.5 Mellor and Yamada turbulence closure scheme. The coupled model investigates the annual cycle of ecosystem production and the response to external forcing, such as heat flux, wind stress, and surface salinity, and the relative importance of physical processes in affecting the ecosystem. Sensitivity experiments are also carried out, which provide information on how the model bio-chemical parameters affect the biological system. The computed seasonal cycles compare reasonably well with the observations of the Bermuda Atlantic Time-series Study (BATS). The spring bloom of phytoplankton occurs in March and April, right after the weakening of the winter mixing and before the establishment of the summer stratification. The bloom of zooplankton occurs about two weeks after the bloom of phytoplankton. The sensitivity experiments show that zooplankton is more sensitive to the variations of biochemical parameters than phytoplankton.     

The use of the slope–area function to analyse process domains in complex badland landscapes

This paper explores the effectiveness of the widely-used functional relationship between drainage area (A in m²) and slope (S in m/m) to identify local process domains and aid interpretation of process interactions in a complex badland landscape. In order to perform this investigation, a series of sub-basins tributary to the Formone River in the Orcia catchment (central Italy) were selected as a suitable study area within which to explore our questions, given these basins' general representativeness of local terrain, the availability of a high resolution digital terrain model and previous extensive geomorphological research. Eroding basins containing both calanchi and landslides are common in the sub-humid badland landscape of central Italy, where field observation identifies a complex pattern of erosive processes associated with a history of uplift, despite which parts of the local landscape appear disconnected. Results reveal that the shape of all S–A curves (plotted using S data binned on log A) is comparable with that described in the literature, although sub-basins containing calanchi generally plot with higher S values than non-calanchi ones, except in the ‘fluvial’ section of the plots. Second, when viewed on total data (non-binned) S–A plots, landslide source area domains and calanchi domains are entirely coincident in all basins, supporting a cause–effect relationship. Additional plotting of the frequency characteristics of the raw data in a new way supports the interpretation that calanchi frequently initiate in landslide scars. In general though, although the S–A plots can contribute to the disentanglement of geomorphological behaviour in some complex erosional landscapes, it became apparent that in this landscape, process domains do not separate out with clarity along the A axis as suggested by theory. Despite this, an alternative, broader-scale morphoevolutive model can be proposed for the development of within-landslide calanchi, driven by changes to basin connectivity to the base channel. © 2018 John Wiley & Sons, Ltd.     

Bias and precision of percentiles of bulk grain size distributions

Percentiles such as D₅₀ and D₈₄, calculated from weights retained on different sieves, are widely used to characterize grain size distributions (GSDs) of bulk samples of sedimentary deposits or sediment fluxes. The sampling variability of such percentiles is not well known, and few sampling guidelines exist for reliable characterization of GSDs. We report results from computer sampling experiments on the variability of sample percentiles in different-sized samples from populations with a log-normal GSD by weight and different sorting coefficients. Sample sizes are scaled by the volume of a median-sized grain so that results can be applied to any log-normal GSD. Sampling is random for the GSD by number that is equivalent to a specified GSD by weight. Results show important differences from standard sampling theory applicable to pebble-count GSDs. In small bulk samples all percentiles, including the median, are underestimated (more so for smaller samples, coarser percentiles and poorer sorting), and precision does not improve with the square root of sample size until fairly large sample sizes are exceeded. Non-dimensional equations fitted by eye to the results give good approximations to expected bias and precision in any percentile from 50 to 95 for any given sample size and population sorting coefficient. They are inverted to estimate the sample size required to avoid significant bias, or achieve specified precision, in any percentile of interest given estimates of the population D₅₀ and sorting coefficient. Target sample sizes are sometimes considerably smaller, but in other circumstances larger, than suggested by previous guidelines relating to estimation of the entire grain size distribution. Bias is likely in small samples of river bedload and good precision requires very large samples of poorly sorted gravel deposits. © 1997 John Wiley & Sons, Ltd.     

Using Lightning Data to Better Understand and Predict Flash Floods in the Mediterranean

One of the costliest natural hazards around the globe is flash floods, resulting from localized intense convective precipitation over short periods of time. Since intense convective rainfall (especially over the continents) is well correlated with lightning activity in these storms, a European Union FP6 FLASH project was realized from 2006 to 2010, focusing on using lightning observations to better understand and predict convective storms that result in flash floods. As part of the project, 23 case studies of flash floods in the Mediterranean region were examined. For the analysis of these storms, lightning data were used together with rainfall estimates in order to understand the storms?? development and electrification processes. In addition, these case studies were simulated using mesoscale meteorological models to better understand the local and synoptic conditions leading to such intense and damaging storms. As part of this project, tools for short-term predictions (nowcasts) of intense convection across the Mediterranean and Europe, and long-term forecasts (a few days) of the likelihood of intense convection, were developed and employed. The project also focused on educational outreach through a special Web site http://flashproject.org supplying real-time lightning observations, real-time experimental nowcasts, medium-range weather forecasts and educational materials. While flash floods and intense thunderstorms cannot be prevented, long-range regional lightning networks can supply valuable data, in real time, for warning the public, end-users and stakeholders of imminent intense rainfall and possible flash floods.     

Magnesiochloritoid: Compressibility and high pressure structure refinement

The response of magnesiochloritoid to pressure has been studied by single crystal X-ray diffraction in a diamond anvil cell, using crystals with composition Mg_1.3Fe_0.7Al₄Si₂O₁₀(OH)₄. The unit cell parameters decrease from a = 9.434 (3), b = 5.452 (2), c = 18.136 (5) Å, β = 101.42° (2) (1 bar pressure) to a = 9.370 (7), b = 5.419 (5), c = 17.88 (1) Å, β = 101.5° (1) (42 kbar pressure), following a slightly anisotropic compression pattern (linear compressibilities parallel to unit cell edges: β _a = 1.85, β _b = 1.74, β_c = 3.05 × 10^?4 kbar^?1) with a bulk modulus of 1480 kbar. Perpendicular to c, the most compressible direction, the crystal structure (space group C2/c) consists of two kinds of alternating octahedral layers connected via isolated SiO₄ tetrahedra. With increasing pressure the slightly wavy layer [Mg_1.3Fe_0.7AlO₂(OH)₄] tends to flatten. Furthermore, the octahedra in this layer, with all cations underbonded, are more compressible than the octahedra in the (A1₃O₈) layer with slightly overbonded aluminum. Comparison between high-pressure and high-temperature data yields the following equations: $$\begin{gathered} a_{P,T} = 9.434{\text{ }}{\AA} - 174 \cdot 10^{ - 5} {\text{ }}{\AA}{\text{kb}}^{{\text{ - 1}}} \cdot P \hfill \\ {\text{ }} + 9 \cdot 10^{ - 5} {\text{ }}{\AA}^\circ C^{ - 1} \cdot (T - 25^\circ C) \hfill \\ b_{P,T} = 5.452{\text{ }}{\AA} - 95 \cdot 10^{ - 5} {\text{ }}{\AA}{\text{kb}}^{{\text{ - 1}}} \cdot P \hfill \\ {\text{ }} + 5 \cdot 65 \cdot 10^{ - 5} {\text{ }}{\AA}^\circ C^{ - 1} \cdot (T - 25^\circ C) \hfill \\ c_{P,T} = 18.136{\text{ }}{\AA} - 549 \cdot 10^{ - 5} {\text{ }}{\AA}{\text{kb}}^{{\text{ - 1}}} \cdot P \hfill \\ {\text{ }} + 16 \cdot 2^{ - 5} {\text{ }}{\AA}^\circ C^{ - 1} \cdot (T - 25^\circ C) \hfill \\ \end{gathered} $$ with P in kbar and T in °C. These equations indicate that the unit cell and bond geometry of magnesiochloritoid at formation conditions do not differ greatly from those at the outcrop conditions, e.g. the calculated unitcell volume is 917.3 ų at P = 16 kbar and T=500 °C, whereas the observed volume at room conditions is 914.4 ų. In addition, they show that the specific gravity increases from formation at depth to outcrop at surface conditions.     

Storm surges in the Singapore Strait due to winds in the South China Sea

Among the semi-enclosed basins of the world ocean, the South China Sea (SCS) is unique in its configuration as it lies under the main southwest-northeast pathway of the seasonal monsoons. The northeast (NE) monsoon (November–February) and southwest (SW) monsoon (June–August) dominate the large-scale sea level dynamics of the SCS. Sunda Shelf at the southwest part of SCS tends to amplify Sea Level Anomalies (SLAs) generated by winds over the sea. The entire region, bounded by Gulf of Thailand on the north, Karimata Strait on the south, east cost of Peninsular Malaysia on the west, and break of Sunda Shelf on the east, could experience positive or negative SLAs depending on the wind direction and speed. Strong sea level surges during NE monsoon, if coincide with spring tide, usually lead to coastal floods in the region. To understand the phenomena, we analyzed the wind-driven sea level anomalies focusing on Singapore Strait (SS), laying at the most southwest point of the region. An analysis of Tanjong Pagar tide gauge data in the SS, as well as satellite altimetry and reanalyzed wind in the region, reveals that the wind over central part of SCS is arguably the most important factor determining the observed variability of SLAs at hourly to monthly scales. Climatological SLAs in SS are found to be positive, and of the order of 30 cm during NE monsoon, but negative, and of the order of 20 cm during SW monsoon. The largest anomalies are associated with intensified winds during NE monsoon, with historical highs exceeding 50 cm. At the hourly and daily time-scales, SLA magnitude is correlated with the NE wind speed over central part of SCS with an average time lag of 36–42 h. An exact solution is derived by approximating the elongated SCS shape with one-dimensional two-step channel. The solution is utilized to derive simple model connecting SLAs in SS with the wind speeds over central part of SCS. Due to delay of sea level anomaly in SS with respect to the remote source at SCS, the simplified solutions could be used for storm surge forecast, with a lead time exceeding 1 day.