Assessment of dissolved nutrients dispersal derived from offshore fish-farm using nitrogen stable isotope ratios (δ15N) in macroalgal bioassays

In this study, the dispersal of wastes from offshore fish farms was evaluated by analyzing nitrogen stable isotope ratios (δ¹⁵N) in macroalgae incubated in the water column at sites located at an increasing distance from the fish cages. Bioassays were performed at three fish farms situated in separate localities with different nutritional conditions (Canary Islands, Murcia and Catalonia) and varying in size, species of fish reared and annual production. Macroalgal bioassays were carried out in two different directions (DI and DII) and they were replicated at each distance in order to evaluate the effect of small-scale variability on the spatial extent of fish farm wastes. The results obtained with δ¹⁵N contribute to a better understanding of the application of nitrogen stable isotopes ratios in macroalgae as an effective bioindicator for tracing the dispersion of offshore fish farm wastes, and demonstrate that fish farm wastes can be traced even over distances of some km from the pollution source. In the Canary Islands, the maximum distance obtained for detection of fish farm wastes was between 450 and 700 m. Of the three installations studied, Murcia presented the greatest distance for detection of fish farm waste influence, ranging from between 1550 and 2450 m, whilst in Catalonia this distance was less than 120 m. In Catalonia, the results were masked by the influence of other sources of nitrogen, and thus fish farm wastes were detected at more reduced distances than expected. These results confirm that fish farm wastes can be traced using the nitrogen stable isotope ratios of macroalgae and that this method can also be useful for identifying areas of potential risk to some sensitive ecosystems, and as an early signal that changes in the community structure might occur.     

A gridded sea surface salinity data set for the tropical Pacific with sample applications (1950–2008)

We present a gridded data set of Sea Surface Salinity (SSS) for the tropical Pacific (120°E–70°W; 30°N–30°S), with a grid resolution of 1° longitude, 1° latitude and 1 month, from 1950 to 2008. The product, together with its associated error field, is derived from an objective analysis of about 10 million validated SSS records, with most of the data originating from Voluntary Observing Ships, TAO/TRITON moorings and Argo profilers (during the most recent period). We expect this product to benefit studies in oceanography, meteorology and paleoceanography. As examples of applications, we analyse: (a) the seasonal and ENSO (El Niño Southern Oscillation) modes of observed SSS variability, (b) the ability of 23 coupled models used in the Intergovernmental Panel for Climate Change 4th Assessment Report (IPCC AR4) to simulate the mean SSS and these two time varying modes, and (c) the usefulness of the SSS product and of its associated error field in calibrating and validating the paleo-salinity time series. We anticipate improvements and regular updates to our product, as more SSS data become available from in situ networks and from the ongoing and near-future satellite-derived observations by SMOS (Soil Moisture and Ocean Salinity) and Aquarius.     

Integrating Uncertainty Theories with GIS for Modeling Coastal Hazards of Climate Change

Prediction of coastal hazards due to climate change is fraught with uncertainty that stems from complexity of coastal systems, estimation of sea level rise, and limitation of available data. In-depth research on coastal modeling is hampered by lack of techniques for handling uncertainty, and the available commercial geographical information systems (GIS) packages have only limited capability of handling uncertain information. Therefore, integrating uncertainty theory with GIS is of practical and theoretical significance. This article presents a GIS-based model that integrates an existing predictive model using a differential approach, random simulation, and fuzzy set theory for predicting geomorphic hazards subject to uncertainty. Coastal hazard is modeled as the combined effects of sea-level induced recession and storm erosion, using grid modeling techniques. The method is described with a case study of Fingal Bay Beach, SE Australia, for which predicted responses to an IPCC standard sea-level rise of 0.86 m and superimposed storm erosion averaged 12 m and 90 m, respectively, with analysis of uncertainty yielding maximum of 52 m and 120 m, respectively. Paradoxically, output uncertainty reduces slightly with simulated increase in random error in the digital elevation model (DEM). This trend implies that the magnitude of modeled uncertainty is not necessarily increased with the uncertainties in the input parameters. Built as a generic tool, the model can be used not only to predict different scenarios of coastal hazard under uncertainties for coastal management, but is also applicable to other fields that involve predictive modeling under uncertainty.     

Impact of Ocean Mean Dynamic Topography on Satellite Data Assimilation

The response of an eddy-permitting ocean model to changes imposed by the use of different mean dynamic topographies (MDT) is analyzed in a multivariate assimilation context, allowing the evaluation of this impact, not only on the surface circulation, but also on the interior ocean representation. The assimilation scheme is a reduced-order sequential Kalman filter (SEEK). In a first set of experiments, high resolution sea surface temperature, along-track sea surface height and sea surface salinity from climatology are assimilated into a 1/3° resolution North and Tropical Atlantic version of the HYCOM model. In a second experiment, in situ profile data are assimilated in addition to the surface measurements.

The first set of experiments illustrates that important differences in the representation of the horizontal model circulation pattern are related to differences in the MDT used. The objective of assimilation is to improve the representation of the 3D ocean state. However, the imperfect representation of the mean dynamic topography appears to be an important limiting factor with regard to the degree of realism obtained in the simulated flow.

Vertical temperature and salinity profiles are key observations to drive a general circulation ocean model toward a more realistic state. The second set of experiments shows that assimilating them in addition to sea surface measurements is a far from trivial exercise. A specific difficulty is due to inconsistencies between the dynamic topography diagnosed from in situ observations and that diagnosed from sea surface height. These two fields obtained from different data sources do not contain exactly the same information. In order to overcome this difficulty, a strategy is proposed and validated.     

Evidence That Sea State Bias is Different for Ascending and Descending Tracks

Jason-1 and TOPEX/Poseidon (T/P) measured sea-surface heights (SSHs) are compared for five regions during the verification tandem phase. The five regions are of similar latitude and spatial extent and include the Gulf of Mexico, Arabian Sea, Bay of Bengal, and locations in the Pacific and Atlantic Oceans away from land. In all five regions, a bias, defined as Jason SSH—TOPEX-B SSH, exists that is different for ascending and descending tracks. For example, in the Gulf of Mexico the bias for ascending tracks was ?0.13 cm and the bias for descending tracks was 2.19 cm. In the Arabian Sea the bias for ascending tracks was ?2.45 cm and the bias for descending tracks was ?1.31 cm. The bias was found to depend on track orientation and significant wave height (SWH), indicating an error in the sea state bias (SSB) model for one or both altimeters. The bias in all five regions can be significantly reduced by calculating separate corrections for ascending and descending tracks in each region as a function of SWH. The correction is calculated by fitting a second-order polynomial to the bias as a function of SWH separately for ascending and descending tracks. An additional constraint is required to properly apply the correction, and we chose to minimize the sum of the TOPEX-B and Jason-1 root-mean-square (rms) crossover differences to be consistent with present SSB models. Application of this constraint shows that the correction, though consistent within each region, is different for each region and that each satellite contributes to the bias. One potential source that may account for a portion of the difference in bias is the leakage in the wave forms in TOPEX-B due to differing altitude rates for ascending and descending tracks. Global SSB models could be improved by separating the tracks into ascenders and descenders and calculating a separate SSB model for each track.     

Vulnerability Assessment at Village Level Due to Tides,Surges and Wave Setup

An assessment of cyclone risk and vulnerability at the village level has evolved, which is an important component of the information system for local level development action plans for preparedness and mitigation. Here, a case study for the Nellore district along the east coast of India is considered. Using maximum probable surges along the coast, total water level (TWL) due to the combined effect of surge, tide, and wind wave is computed for the most vulnerable coastal villages of the Nellore district due to any tropical cyclones. The computations suggest that the TWL along the Nellore coast varies from 2 m in the south to 4 m in the north.     

Quantification of Spatial and Thematic Uncertainty in the Application of Underwater Video for Benthic Habitat Mapping

This study presents an analysis of the application of underwater video data collected for training and validating benthic habitat distribution models. Specifically, we quantify the two major sources of error pertaining to collection of this type of reference data. A theoretical spatial error budget is developed for a positioning system used to co-register video frames to their corresponding locations at the seafloor. Second, we compare interpretation variability among trained operators assessing the same video frames between times over three hierarchical levels of a benthic classification scheme. Propagated error in the positioning system described was found to be highly correlated with depth of operation and varies from 1.5m near the surface to 5.7m in 100m of water. In order of decreasing classification hierarchy, mean overall observer agreement was found to be 98% (range 6%), 82% (range 12%) and 75% (range 17%) for the 2, 4, and 6 class levels of the scheme, respectively. Patterns in between-observer variation are related to the level of detail imposed by each hierarchical level of the classification scheme, the feature of interest, and to the amount of observer experience.     

Implementation of Tidal Constituent Interpolation Method for the Israeli Coastline

Many ship-borne geodetic surveys at sea, such as Global Navigation Satellite System (GNSS)-based sea surface height (SSH) observation, acoustic profiling of the bottom, and others, deal with a dynamic topography which undergoes several changes during the survey campaign (e.g., changes in tide, salinity and currents). Those changes affect the measurements and may causes for some variations in the results. There are several methods for tidal variations correction, being the most dominant phenomena, such as tidal zoning, tidal constituent interpolation or ocean tidal models. In this study, we have implemented the tidal constituent interpolation method for the Israeli coastline in order to assess its quality and determine whether it is suitable for use in this particular region. This paper depicts the interpolation method, discusses some difficulties in the implementation for the Israeli coast and presents results from exemplary processing. In addition, we compare the results to those obtained using global and regional tidal models.     

Environmental Impact Assessment of the Proposed Titanium Mining Project in Kwale District,Kenya

This article addresses both environmental and socioeconomic issues concerned with the development or operation of the envisaged titanium mining project in Kwale District of Kenya. TIOMIN Resources Inc., of Canada, through its wholly owned Kenyan subsidiary, Kenya Titanium Minerals Ltd., is proposing to develop a titanium sands mine and mineral processing plants which will produce high grades of heavy minerals including rutile, ilmenite, and zircon. In addition, TIOMIN has proposed to develop a ship loading facility at Shimoni, a significant marine habitat in Kenya. When properly designed and implemented, an Environmental Impact Assessment (EIA) is a powerful tool for ensuring that environmental issues are given due consideration during project design, allowing the benefits of the project to be maximized, while reducing the environmental and social costs of development. In Kenya, the EIA has to be conducted according to the requirements of the Kenya Environmental Management and Co-ordination Act (2000) and in compliance with World Bank standards. An EIA document submitted to the enforcement authority, National Environmental Management Authority (NEMA), enables the issuing of an Environmental Impact Assessment License and a Mining License. A number of exploration studies have been undertaken and several sites have been identified for the extraction of titanium minerals and zircon. Many have expressed concern that environmental matters should be considered before a decision about titanium mining is undertaken. Toxic chemicals used in heavy mineral separation processes and disturbance or redistribution of sediment could spell a disaster for the coastal waters. The Wasini channel is home to world class coral reefs, humpback and spotted dolphins, and marine turtles. Another contentious issue is that of radioactivity associated with the minerals zircon and monazite. The coastal zone is a crucial part of the economy, as it supplies a living for a large number of people along the coast. It is envisaged that involuntary resettlement without adequate compensation and viable alternative sites may result in serious socioeconomic consequences.     

In Memoriam

Abstract

The engineering properties of deep continental margin sediments were determined on a worldwide basis. Deep Sea Drilling Project (DSDP) core data and material were utilized from over 900 cores obtained from 89 sites, primarily on the continental margins. Cores were recovered from penetrations to 200 m in water depths averaging 3000 m. Supplementary laboratory testing on selected cores was directed toward determining index properties and shear strength properties of the sediments. The study included a literature review of deep‐sea soil properties, the results of which are to be used by DSDP to evaluate foundation conditions for reentry cones with long casing strings. The results will also be used for a feasibility study of an ultradeepwater marine riser and well‐control system. The marine sediments examined can be divided into three main types: clay, calcareous ooze, and siliceous ooze. Sediment distribution consisted of 48% calcareous ooze, 43% clay, 6% siliceous ooze, and 3% volcanic ash. Because of the sample disturbance inherent in the deepwater coring operation, emphasis was placed on analyzing sediment properties not significantly affected by changes in in situ stresses and structure caused by sampling. Averages and ranges in values of water content and unit weight are presented for the three main sediment types. Plasticity and strength characteristics are discussed in detail and the elastic and compression properties are outlined. The geotechnical properties of deep continental margin soils are summarized.