Sodium fluoroacetate (1080) residues in longfin eels,Anguilla dieffenbachii,following exposure to contaminated water and food

Captive longfin eels (Anguilla dieffenbachii) were exposed to the vertebrate pesticide sodium fluoroacetate (1080) in the water column and through the ingestion of cereal pellet baits or possum muscle and gut tissue that contained 1080 residue. No mortality or unusual behaviour (in comparison with the controls) occurred in eels that were exposed to 1080. However, significantly greater weight loss occurred in eels exposed to 1080 compared with those eels that were not. No residue was detected in tissues of eels exposed to 1080 cereal baits through ingestion and direct (dermal and respiratory) absorption, or through direct absorption only. Low concentrations of 1080 were detected in muscle tissue of eels that consumed contaminated possum muscle (x = 0.0174 μg/g) or gut (x = 0.0306 μg/g) tissue. The primary factors affecting the concentration of 1080 detected in eel tissue included the dose of 1080 (mg/kg) that each eel" receiveddate="and number of days since the eel last fed on contaminated tissue. Based on the 1080 concentrations measured in eels in this study, the risk of acute poisoning to humans from eating contaminated eel flesh is considered extremely low. Even so, national and international perceptions and food safety standards have the potential to limit eel exports and/or close an eel fishery if 1080 residue was discovered in tissue.     

The genus Pseudo-nitzschia (Bacillariophyceae) in New Zealand: analysis of the last decade's monitoring data

The diatom genus Pseudo-nitzschia blooms throughout New Zealand's coastal waters. More than a decade of monitoring data were analysed in this study and seasonality was a significant factor in the appearance of Pseudo-nitzschia blooms. Austral spring and summer were the main bloom periods, although there were regional differences. Between January 2000 and August 2011, 8.4% of 29,000 seawater samples analysed for Pseudo-nitzschia exceeded the voluntary trigger level for biotoxin testing (10×10⁴ cells l^?1), and these were analysed by fluorescent in situ hybridisation (FISH) assays. Pseudo-nitzschia fraudulenta and P. pseudodelicatissima (low domoic acid [DA] producers) were the dominant bloom formers throughout New Zealand (each contributing 25%) followed by the highly toxic P. australis (10%). Shellfish flesh testing for DA was triggered on 8477 occasions between 2000 and 2011, but no samples exceeded the regulatory limit (20 mg/kg); the maximum concentration was 13 mg/kg (Marlborough Sounds, mid-winter 2010).     

Sea Levels and Coastal Inundation Due to Tropical Cyclones in Indian Coastal Regions of Andhra and Orissa

Coastal inundation associated with extreme sea levels is the main factor which leads to the loss of life and property whenever a severe tropical cyclonic storm hits the Indian coasts. The Andhra and Orissa coasts are most vulnerable for coastal inundation due to extreme rise in sea levels associated with tropical cyclones. Loss of life may be minimized if extreme sea levels and associated coastal flooding is predicted well in advance. Keeping this in view, location specific coastal inundation models are developed and applied for the Andhra and Orissa coasts of India. Several numerical experiments are carried out using the data of past severe cyclones that struck these regions. The simulated inland inundation distances are found to be in general agreement with the reported flooding.     

Impact of Satellite Altimetry on Simulations of Sea Level Variability by an Indian Ocean Model

This article describes the impact of satellite altimeter data on the simulations of sea level variability (SLV) by a nonlinear reduced gravity model of the entire Indian Ocean. The model has been forced by 6-hourly analyzed wind stress data containing SSM/I observations and has been able to produce realistic circulation features. However, SLV values observed by Topex/Poseidon altimeter do not fit these simulations because of imperfect initial data. Hence an attempt has been made to initialize the model using altimeter data. The initialized model-generated SLVvalues have been compared with SLV derived by altimeter for monsoon as well as nonmonsoon months of 1996. Experimental runs have been performed for 10 days, 20 days, and one month. It has been found that the initialized model results on the final day of these experiments are in very good agreement with altimeter data of the same day. It is thus possible, in principle, to hindcast and forecast sea level variations in the time scale of 10 days to one month with the availability of good quality wind data for forcing the model and altimeter observations of sea level for initializing it.     

Accuracy Assessment of the TOPEX/Poseidon Ionosphere Measurements

We conducted an assessment of the TOPEX dual-frequency nadir ionosphere observations in the TOPEX/Poseidon (T/P) GDR by comparing TOPEX with the Center for Orbit Determination in Europe (CODE) Global Ionosphere Map (GIM), the climatological model IRI2001, and the DORIS (onboard T/P) relative ionosphere delays. We investigated the TOPEX (TOPEX Side A and TOPEX Side B altimeters, TSA and TSB, respectively) ionosphere observations for the time period 1995–2001, covering periods of low, intermediate, and high solar activity. Here, we use absolute path delays (at Ku-band frequency of the TOPEX altimeter and with positive signs) rather than Total Electron Content (TEC). We found significant biases between GIM and TOPEX (GIM–TOPEX) nadir ionosphere path delays: ?8.1 ± 0.4 {mm} formal uncertainties and equivalent to 3.7 TECu) and ?9.0 ± 0.7 {mm} (4.1 TECu) for TSA and TSB, respectively, indicating that the TOPEX path delay is longer (or with higher TECu) than GIM. The estimated relative biases vary with latitude and with daytime or nighttime passes. The estimated biases in the path delays (DORIS–TOPEX) are: ?10.9 ± 0.4 {mm} (5.0 TECu) and ?14.8 ± 0.6 {mm} (6.7 TECu), for TSA and TSB, respectively. There is a distinct jump of the DORIS path delays (?3.9 ± 0.7 {mm}, TSA delays longer than TSB delays) at the TSB altimeter switch in February 1999, presumably due to inconsistent DORIS processing. The origin of the bias between GIM (GPS, L-band) and TOPEX (radar altimeter, Ku-band) is currently unknown and warrants further investigation. Finally, the estimated drift rates between GIM and TSA, DORIS and TSA ionosphere path delays for the 6-year study span are ?0.4 mm/yr and ?0.8 mm/yr, respectively, providing a possible error bound for the TOPEX/Poseidon sea level observations during periods of low and intermediate solar activity.     

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.     

Analysis of the Tsunami of December 26, 2004, on the Kerala Coast of India—Part I: Amplitudes

The Indian Ocean tsunami of December 26, 2004, not only affected the Bay of Bengal coast of India but also part of the Arabian Sea coast of India. In particular, the tsunami caused loss of life and heavy damage on some parts of the Kerala coast in southwest India. The tsunami traveled west, south of Sri Lanka, and some of the tsunami energy was diffracted around Sri Lanka and the southern tip of India and moved northward into the Arabian Sea. However, tsunami, being a long gravity wave with a wave length of a few hundred kilometers, has to take a wide turn. In that process, it missed the very southern part of the Kerala coast and did not achieve large amplitudes there. However, further north, the tsunami achieved amplitudes of upto 5 m and caused loss of life and significant damage. Here we identify the physical oceanographic processes that were responsible for selective amplification of the tsunami in certain locations.     

Identifying Rocky Seabed Using GIS-Modeled Predictor Variables

Mapping the seabed along the Norwegian coast is costly and time consuming. Hence, finding a modeling method to separate rocky seabed from other substrate types will provide digital maps that may be used to develop cost-effective sampling designs to predict species and habitat distribution. Our approach was to use geophysical data that were quantitative and objectively defined, generalized additive models (GAMs), and Akaike information criterion (AIC) to develop statistical models and select among them. We found that slope, terrain curvature, wave exposure, and depth predicted rocky seabed occurrence with a high degree of certainty.     

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.     

Contribution of Tides to Sea Level Variations Along Visakhapatnam,India

The sea level variations along Visakhapatnam coast are governed by astronomical tides and nontidal oscillations including atmospheric pressure, winds, coastal currents, Ekman Pumping, and river influx. Tidal and nontidal sea level oscillations are usually studied separately because of the vastly different ways in which they are forced. In this study the tidal oscillations along Visakhapatnam are analyzed using GOTIC2 tidal model. The correlation between monthly mean sea level and monthly mean tides is 47% (r = 0.68) and increases to 54% (r = 0.74) when applied for inverse-barometric effect. The major six partial tides are computed and presented. The tidal variations from Neap tide to Spring tide are studied.