Towards improving ambient noise tomography using simultaneously curvelet denoising filters and SEM simulations of seismic ambient noise

The aim of this article is to investigate a possible way to improve ambient noise tomography by expanding the data base of useful cross-correlation measurements. We show that the curvelet transform makes it possible to compute synthetic noise correlations by simulating directly seismic ambient noise using the spectral element method. These synthetic correlations can in turn be used to identify surface waves and overtones even on correlations having a signal to noise ratio much lower than one. We hope that the possibility to compute SEM synthetic correlations and to extract more information from correlations will be useful to improve ambient noise tomography and monitoring.     

Coral reef productivity and diversity—Contributions from enhanced photosynthesis via demand for carbohydrate from the host

Coral reefs’ high productivity has been attributed mainly to photosymbioses between the coral animal and algae of the family Symbiodiniaceae, with recognition that the host can increase algal photosynthesis by concentrating nutrients and enhancing the efficiency of light absorption. Here, we propose that an additional effect, consumption of carbohydrate by the host, may also enhance algal photosynthesis. We examine evidence from symbiosis between terrestrial plants and root fungi that indicates a link between carbohydrate consumption by the symbiotic partner and photosynthetic upregulation in the plant system. In addition, we review evidence from free-living algae manipulated to exude carbohydrate into the external medium, which was associated with strong upregulation of photosynthetic capacity. We offer suggestions on how host-induced carbohydrate release may increase photosynthesis rates in the symbionts in the intact photosymbiosis and how this relationship evolved.     

Shifts in an epibenthic trophic web across a marine frontal area in the Southwestern Atlantic (Argentina)

Marine benthic trophic relationships and food web structures may be influenced by benthic–pelagic coupling processes, which could also be intensified by the physical dynamics of marine fronts. In this work, we employed stable isotope (δ¹³C and δ¹⁵N) analysis to investigate the influence of the Southwest (SW) Atlantic shelf-break front (SBF; 38–39°S, 55–56°W; Argentina) on an epibenthic trophic web. Epibenthic organisms were sampled, at depths of ~ 100 m, with a non-selective dredge from a sandy bottom community located in frontal (F) and marginal (M) areas. The SBF position and the chlorophyll-a (chl-a) concentrations were inferred using satellite data of the sea surface temperature (SST) and satellite chl-a concentration, respectively. The most noticeable shifts in stable isotopes between the sampled areas were those of the Patagonian scallop, Zygochlamys patagonica (δ¹³C), and those of the sea urchin, Sterechinus agassizi (δ¹⁵N). Diet analyses inferred from stable isotopes and mixing models demonstrated that the dominant component of this community, Z. patagonica, had variable contributions to higher trophic levels between areas. More importantly, the epibenthic assemblage in F areas showed δ¹³C-enriched and δ¹⁵N-depleted isotopic signatures with respect to the M areas. Collectively, this evidence suggests that frontal dynamics promotes the accumulation of δ¹³C-enriched phytoplankton in the seabed in F areas, while in M areas the more degraded organic matter becomes more important in the trophic web, decreasing the δ¹⁵N isotopic signature of the assemblage. Therefore, the trophic web was sustained by fresher food in F areas than in M areas, demonstrating the role of frontal dynamics in the shaping of these communities.     

EAF implementation in Southern Africa: Lessons learnt

The practical implementation of an ecosystem approach to fisheries (EAF) management has proved difficult to achieve. Without simple and structured guidelines for implementing an EAF, managers are grappling with the complexity of implementation and the need to prioritise resources and management actions. Ecological risk assessment has been put forward as a structured procedure. There is a need to review regularly whether progress is being made in addressing the issues and priorities identified through ecological risk assessment. Such reviews require a framework providing clear objectives for the respective fishery and delineating the steps required towards their achievement. This paper proposes a generic framework for reviewing ecological risk assessments through stakeholder workshops. This framework is aided by a fuzzy logic tool to track EAF implementation and informs the development of proactive work plans which incorporate EAF objectives. The advantages and disadvantages of a generic and participatory approach are discussed and compared with other related methods for evaluating progress in implementing an EAF.     

Incorporating subjective and stochastic uncertainty in an interactive multi-objective groundwater calibration framework

The interactive multi-objective genetic algorithm (IMOGA) combines traditional optimization with an interactive framework that considers the subjective knowledge of hydro-geological experts in addition to quantitative calibration measures such as calibration errors and regularization to solve the groundwater inverse problem. The IMOGA is inherently a deterministic framework and identifies multiple large-scale parameter fields (typically head and transmissivity data are used to identify transmissivity fields). These large-scale parameter fields represent the optimal trade-offs between the different criteria (quantitative and qualitative) used in the IMOGA. This paper further extends the IMOGA to incorporate uncertainty both in the large-scale trends as well as the small-scale variability (which can not be resolved using the field data) in the parameter fields. The different parameter fields identified by the IMOGA represent the uncertainty in large-scale trends, and this uncertainty is modeled using a Bayesian approach where calibration error, regularization, and the expert’s subjective preference are combined to compute a likelihood metric for each parameter field. Small-scale (stochastic) variability is modeled using a geostatistical approach and added onto the large-scale trends identified by the IMOGA. This approach is applied to the Waste Isolation Pilot Plant (WIPP) case-study. Results, with and without expert interaction, are analyzed and the impact that expert judgment has on predictive uncertainty at the WIPP site is discussed. It is shown that for this case, expert interaction leads to more conservative solutions as the expert compensates for some of the lack of data and modeling approximations introduced in the formulation of the problem.     

Statistical dependence in input data of national greenhouse gas inventories: effects on the overall inventory uncertainty

An uncertainty assessment of the Austrian greenhouse gas inventory provided the basis for this analysis. We isolated the factors that were responsible for the uncertainty observed, and compared our results with those of other countries. Uncertainties of input parameters were used to derive the uncertainty of the emission estimate. Resulting uncertainty using a Monte Carlo approach was 5.2% for the emission levels of 2005 and 2.4 percentage points for the 1990–2005 emission trend. Systematic uncertainty was not assessed. This result is in the range expected from previous experience in Austria and other countries. The determining factor for the emission level uncertainty (not the trend uncertainty) is the uncertainty associated with soil nitrous oxide N₂O emissions. Uncertainty of the soil N₂O release rate is huge, and there is no agreement even on the magnitude of the uncertainty when country comparisons are made. In other words, reporting and use of N₂O release uncertainty are also different between countries; this is important, as this single factor fully determines a country’s national greenhouse gas inventory uncertainty. Inter-country comparisons of emission uncertainty are thus unable to reveal much about a country’s inventory quality. For Austria, we also compared the results of the Monte Carlo approach to those obtained from a simpler error propagation approach, and find the latter to systematically provide lower uncertainty. The difference can be explained by the ability of the Monte Carlo approach to account for statistical dependency of input parameters, again regarding soil N₂O emissions. This is in contrast to the results of other countries, which focus less on statistical dependency when performing Monte Carlo analysis. In addition, the error propagation results depend on treatment of skewed probability distributions, which need to be translated into normal distributions. The result indicates that more attention needs to be given to identifying statistically dependent input data in uncertainty assessment.     

The effects of spatially distributed ionisation sources on the temperature structure of H <Emphasis Type="SmallCaps">ii</Emphasis> regions

Spatially resolved studies of star-forming regions show that the assumption of spherical geometry is not realistic in most cases, with a major complication posed by the gas being ionised by multiple non-centrally located stars or star clusters. Geometrical effects including the spatial configuration of ionising sources affect the temperature and ionisation structure of these regions. We try to isolate the effects of multiple non-centrally located stars, via the construction of 3D photoionisation models using the 3D Monte Carlo photoionisation code mocassin with very simple gas density distributions, but various spatial configurations for the ionisation sources.Emission-line spectra from H?ii regions are often used to study the metallicity of star-forming regions, as well as for providing a constraint on temperatures and luminosities of the ionising sources. Empirical metallicity diagnostics must often be calibrated with the aid of photoionisation models. However, most studies so far have been carried out by assuming spherical or plane-parallel geometries, with major limitations on the allowed gas and dust density distributions and with the spatial distribution of multiple, non-centrally located ionising sources not being accounted for. We compare integrated emission-line spectra from our models and quantify any systematic errors caused by the simplifying assumption of a single, central location for all ionising sources. We find that the dependence of the metallicity indicators on the ionisation parameter causes a clear bias, due to the fact that models with a fully distributed configuration of stars always display lower ionisation parameters than their fully concentrated counterparts. The errors found imply that the geometrical distribution of ionisation sources may partly account for the large scatter in metallicities derived using model-calibrated empirical methods.