Relationship between waterfowl and the seagrassRuppia maritima in a Southwestern Atlantic coastal lagoon

We evaluated the distribution of waterfowl in relation to a seagrass (Ruppia maritima) patch, to infauna, and on its relationship with substrate characteristics. An experiment performed in the Mar Chiquita coastal lagoon (37°46′S, 57°27′W; Argentina) was used to evaluate the effect of herbivory on widgeon grass,R. maritima. Control plots of equal size, located between bird exclosures, were exposed to herbivory. The experiment ran for 31 d, starting on December 1, 1994. Censuses showed that black-necked swan ( $\bar x = 50$ birds ha^?1, SD = 37, n = 10) and coots ( $\bar x = 42$ birds ha^?1, SD = 28, n = 10) were the most important (always present) of the waterfowl seen feeding onR. maritima. The results of the experiment showed greater leaf lengths, lower belowground (rhizomes and roots) biomass, greater aboveground (leaves and shoots) biomass, and greater abundance of the polychaeteHeteromastus similis in exclosure plots. There were no exclosure effects on total biomass (belowground plus aboveground), reproductive parts (fruits and pre- and postpollination flowers), or abundance of most benthic infauna. Topographic surveys showed that sediment surface was higher within theR. maritima patches, but there were no significant differences in granulometric composition. Surveys also showed that bird distribution was strongly associated with the presence ofR. maritima.     

A flow-based pattern recognition algorithm for rapid quantification of geologic uncertainty

Geologic uncertainties and limited well data often render recovery forecasting a difficult undertaking in typical appraisal and early development settings. Recent advances in geologic modeling algorithms permit automation of the model generation process via macros and geostatistical tools. This allows rapid construction of multiple alternative geologic realizations. Despite the advances in geologic modeling, computation of the reservoir dynamic response via full-physics reservoir simulation remains a computationally expensive task. Therefore, only a few of the many probable realizations are simulated in practice. Experimental design techniques typically focus on a few discrete geologic realizations as they are inherently more suitable for continuous engineering parameters and can only crudely approximate the impact of geology. A flow-based pattern recognition algorithm (FPRA) has been developed for quantifying the forecast uncertainty as an alternative. The proposed algorithm relies on the rapid characterization of the geologic uncertainty space represented by an ensemble of sufficiently diverse static model realizations. FPRA characterizes the geologic uncertainty space by calculating connectivity distances, which quantify how different each individual realization is from all others in terms of recovery response. Fast streamline simulations are employed in evaluating these distances. By applying pattern recognition techniques to connectivity distances, a few representative realizations are identified within the model ensemble for full-physics simulation. In turn, the recovery factor probability distribution is derived from these intelligently selected simulation runs. Here, FPRA is tested on an example case where the objective is to accurately compute the recovery factor statistics as a function of geologic uncertainty in a channelized turbidite reservoir. Recovery factor cumulative distribution functions computed by FPRA compare well to the one computed via exhaustive full-physics simulations.     

Lithological and geochemical record of mining-induced changes in sediments from Macquarie Harbour,southwest Tasmania,Australia

Macquarie Harbour in southwest Tasmania, Australia, has been affected severely by the establishment of mines in nearby Queenstown in the 1890s. As well as heavy metal-laden acid rock drainage from the Mount Lyell mine area, over 100 Mt of mine tailings and slag were discharged into the Queen and Ring Rivers, with an estimated 10 Mt of mine tailings building a delta of ca. 2.5 km² and ca. 10 Mt of fine tailings in the harbour beyond the delta. Coring of sediments throughout Macquarie Harbour indicated that mine tailings accreted most rapidly close to the King River delta source with a significant reduction in thickness of tailings and heavy metal contamination with increasing distance from the King River source. Close to the King River delta the mine tailings are readily discriminated from the background estuarine sediments on the basis of visual logging of the core (laminations, colour), sediment grain size, sediment magnetic susceptibility and elemental geochemistry, especially concentrations of the heavy metals Cu, Zn and Pb. The high heavy metal concentrations are demonstrated by the very high contamination factors (CF > 6) for Cu and Zn, with CF values mostly >50 for Cu for the mine-impacted sediments. Although the addition of mine waste into the King River catchment has ceased, the catchment continues to be a source of these heavy metals due to acid rock drainage and remobilisation of mine waste in storage in the river banks, river bed and delta. The addition of heavy metals to the harbour sourced from the Mount Lyell mines preceded the advent of direct tailings disposal into the Queen River in 1915 with the metals probably provided by acid rock drainage from the Mount Lyell mining area.     

Are assemblages of the fireworm Hermodice carunculata enhanced in sediments beneath offshore fish cages?

Abundances of the fireworm Hermodice carunculata were counted through a monitoring assessment study of fish cages in Barranco Hondo（NE Tenerife）. Seven campaigns were conducted from November 2007 to June 2010 and temporal variations were found, as well as differences among sampling stations. The polychaete H. carunculata obtained its highest abundance in sediments beneath fish cages throughout the study period. Thus, the assemblages of this omnivorous species were favoured by the presence of fish cages.     

Impact of improved assimilation of temperature and salinity for coupled model seasonal forecasts

We assess the impact of improved ocean initial conditions for predicting El Niño-Southern Oscillation (ENSO) and Indian Ocean dipole (IOD) using the Bureau of Meteorology’s Predictive Ocean Atmosphere Model for Australia (POAMA) coupled seasonal prediction model for the period 1982–2006. The new ocean initial conditions are provided by an ensemble-based analysis system that assimilates subsurface temperatures and salinity and which is a clear improvement over the previous optimal interpolation system which used static error covariances and was univariate (temperature only). Hindcasts using the new ocean initial conditions have better skill at predicting sea surface temperature (SST) variations associated with ENSO than do the hindcasts initialized with the old ocean analyses. The improvement derives from better prediction of subsurface temperatures and the largest improvements come during ENSO–IOD neutral years. We show that improved prediction of the Niño3.4 SST index derives from improved initial depiction of the thermocline and halocline in the equatorial Pacific but as lead time increases the improved depiction of the initial salinity field in the western Pacific become more important. Improved ocean initial conditions do not translate into improved skill for predicting the IOD but we do see an improvement in the prediction of subsurface temperatures in the Indian Ocean (IO). This result reflects that the coupling between subsurface and surface temperature variations is weaker in the IO than in the Pacific, but coupled model errors may also be limiting predictive skill in the IO.     

ENSO,the IOD and the intraseasonal prediction of heat extremes across Australia using POAMA-2

The simulation and prediction of extreme heat over Australia on intraseasonal timescales in association with the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) is assessed using the Bureau of Meteorology’s Predictive Ocean Atmosphere Model for Australia (POAMA). The analysis is based on hindcasts over 1981–2010 and focuses on weeks 2 and 3 of the forecasts, i.e. beyond a typical weather forecast. POAMA simulates the observed increased probabilities of extreme heat during El Niño events, focussed over south eastern and southern Australia in SON and over northern Australia in DJF, and the decreased probabilities of extreme heat during La Niña events, although the magnitude of these relationships is smaller than observed. POAMA also captures the signal of increased probabilities of extreme heat during positive phases of the IOD across southern Australia in SON and over Western Australia in JJA, but again underestimates the strength of the relationship. Shortcomings in the simulation of extreme heat in association with ENSO and the IOD over southern Australia may be linked to deficiencies in the teleconnection with Indian Ocean SSTs. Forecast skill for intraseasonal episodes of extreme heat is assessed using the Symmetric Extremal Dependence Index. Skill is highest over northern Australia in MAM and JJA and over south-eastern and eastern Australia in JJA and SON, whereas skill is generally poor over south-west Western Australia. Results show there are windows of forecast opportunity related to the state of ENSO and the IOD, where the skill in predicting extreme temperatures over certain regions is increased.     

Diversity and Habitat Distribution of Birds in Coastal Marshes and Comparisons with Surrounding Upland Habitats in Southeastern South America

We studied variation in bird assemblages with plant associations for three different coastal marshes from Southeastern South America (SESA) and assessed how marsh bird assemblages related to nearby upland bird assemblages. We surveyed bird species and plant structure along the tidal gradient of each locality from the low tide level to the upper habitats bordering coastal marshes. Twenty species frequently used coastal marshes, including relatively few migratory species. We found that birds occurring in SESA coastal marshes do not have distributions constrained to coastal marshes. Nonetheless, four bird assemblages were recognized in association with vegetation types and/or sites. Among the recorded coastal marsh species, the bay-capped wren-spinetail (Spartonoica maluroides) is both the most frequent and the most habitat constrained. Bird richness increases steadily along the tidal gradient associated with the increase in vegetation structure, suggesting that bird richness is directly explained by vegetation and indirectly by the physical conditions influencing vegetation structure. Results highlight the importance of SESA middle marshes as habitat for conservation of some threatened SESA grassland birds.     

Scales and causes of heterogeneity in bars in a large multi‐channel river: Río Paraná, Argentina

To date, published studies of alluvial bar architecture in large rivers have been restricted mostly to case studies of individual bars and single locations. Relatively little is known about how the depositional processes and sedimentary architecture of kilometre‐scale bars vary within a multi‐kilometre reach or over several hundreds of kilometres downstream. This study presents Ground Penetrating Radar and core data from 11, kilometre‐scale bars from the Río Paraná, Argentina. The investigated bars are located between 30 km upstream and 540 km downstream of the Río Paraná – Río Paraguay confluence, where a significant volume of fine‐grained suspended sediment is introduced into the network. Bar‐scale cross‐stratified sets, with lengths and widths up to 600 m and thicknesses up to 12 m, enable the distinction of large river deposits from stacked deposits of smaller rivers, but are only present in half the surface area of the bars. Up to 90% of bar‐scale sets are found on top of finer‐grained ripple‐laminated bar‐trough deposits. Bar‐scale sets make up as much as 58% of the volume of the deposits in small, incipient mid‐channel bars, but this proportion decreases significantly with increasing age and size of the bars. Contrary to what might be expected, a significant proportion of the sedimentary structures found in the Río Paraná is similar in scale to those found in much smaller rivers. In other words, large river deposits are not always characterized by big structures that allow a simple interpretation of river scale. However, the large scale of the depositional units in big rivers causes small‐scale structures, such as ripple sets, to be grouped into thicker cosets, which indicate river scale even when no obvious large‐scale sets are present. The results also show that the composition of bars differs between the studied reaches upstream and downstream of the confluence with the Río Paraguay. Relative to other controls on downstream fining, the tributary input of fine‐grained suspended material from the Río Paraguay causes a marked change in the composition of the bar deposits. Compared to the upstream reaches, the sedimentary architecture of the downstream reaches in the top ca 5 m of mid‐channel bars shows: (i) an increase in the abundance and thickness (up to metre‐scale) of laterally extensive (hundreds of metres) fine‐grained layers; (ii) an increase in the percentage of deposits comprised of ripple sets (to >40% in the upper bar deposits); and (iii) an increase in bar‐trough deposits and a corresponding decrease in bar‐scale cross‐strata (<10%). The thalweg deposits of the Río Paraná are composed of dune sets, even directly downstream from the Río Paraguay where the upper channel deposits are dominantly fine‐grained. Thus, the change in sedimentary facies due to a tributary point‐source of fine‐grained sediment is primarily expressed in the composition of the upper bar deposits.