The storage of red snapper (Lutjanus spp.) in ice, chilled sea water and chilled fresh water

The results are given of trials conducted to determine the effect on quality of holding fish (Lutjanus species) in chilled freshwater and also to compare the quality loss of fish stored in chilled seawater and chilled freshwater and in ice. No adverse effects were observed when storing in chilled freshwater apart from loss of external appearance after 6 days storage; taste panel tests showed acceptable conditions up to 15 days. Chilled seawater is unsuitable for storage as it spoils the intake of salt from the medium, making the flesh unpalatable.

Fluorescence Characterization of Dissolved Organic Matter in the East China Sea after Diatom Red Tide Dispersion

Fluorescence excitation-emission spectroscopy (EEMS) was employed to analyze the 3-dimensional fluorescence of dissolved organic matter in the East China Sea after diatom red tide dispersion. The relationships between fluorescence peak intensity, and salinity and chlorophyll-a were discussed. The centers of protein-like fluorescence peaks dispersed at Ex(max)/Em(max) = 270-280/290-315 nm (Peak B), 220-230/290-305 nm (Peak D), 230-240/335-350 nm(Peak S)and 280/320 nm(Peak T). Two humic-like peaks appeared at 255-270/435-480 nm (Peak A) and 330-350/420-480 nm(Peak C). High tyrosine-like intensity was observed in diatom red tide dispersion area, and tryptophan-like fluorescence was also found which was lower. High FIB/FIS showed that diatom red tide produced much tyrosine-like matter during dispersion. Peaks S, A and C had positive correlation with one another, and their distributions were similar, which decreased with distance increasing away from the shore. Good negative correlations between peaks S, A and C and salinity suggested that Jiangsu-Zhejiang coastal water was the same source of then-L Correlations between fluorescence peak intensity and chlorophyll-a were not remarkable enough to clear the relationship between fluorescence and living algal matter. It was supposed that the living algal matter contributed little to the fluorescence intensity of algal dispersion seawater.

A multidisciplinary approach for puzzling over fish connectivity in the Mediterranean Sea: The role of early life history stages of red mullet (Mullus barbatus)

Integrating connectivity patterns into marine ecosystem management is a fundamental step, specially for stock subjected to the combined impacts of human activities (overfishing, habitat degradation, etc.) and climate changes. Thus, management of marine resources must incorporates the spatial scales over which the populations are connected. Notwithstanding, studying these dynamics remains a crucial and hard task and the predictions of the temporal and spatial patterns of these mechanisms are still particularly challenging. This thesis aims to puzzle over the red mullet Mullus barbatus population connectivity in the Western Mediterranean Sea, by implementing a multidisciplinary approach. Otolith sclerochronology, larval dispersal modelling and genetic techniques were gathered in this study. More particularly, this research project focused on early life history stages of red mullet and their role in the characterization of connectivity dynamics. The results show that M. barbatus larval dispersal distances can reach a range of 200 km. The differences in early life traits (i.e. PLD, spawning and settlement dates) observed between various areas of the Western Mediterranean Sea suggest a certain level of larval patchiness, likely due to the occurrence of different spawning pulses during the reproductive period. The dispersal of individuals across distant areas, even not significant in demographic terms, is accountable for the maintenance of the genetic flow among different demes. Fluctuations in the level of exchange among different areas, due to the variability of the source-sink dynamics, could have major implications in the population connectivity patterns. These findings highlight the reliability of combining several approaches and represent a benchmark for the definition of a proper resource management, with considerable engagements in effectively assuring the beneficial effects of the existent and future conservation strategies.

Extended optimal estimation techniques for sea surface temperature from the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI)

Sea surface temperature (SST) can be estimated from day and night observations of the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) by optimal estimation (OE). We show that exploiting the 8.7 μm channel, in addition to the “traditional” wavelengths of 10.8 and 12.0 μm, improves OE SST retrieval statistics in validation. However, the main benefit is an improvement in the sensitivity of the SST estimate to variability in true SST. In a fair, single-pixel comparison, the 3-channel OE gives better results than the SST estimation technique presently operational within the Ocean and Sea Ice Satellite Application Facility. This operational technique is to use SST retrieval coefficients, followed by a bias-correction step informed by radiative transfer simulation. However, the operational technique has an additional “atmospheric correction smoothing”, which improves its noise performance, and hitherto had no analogue within the OE framework. Here, we propose an analogue to atmospheric correction smoothing, based on the expectation that atmospheric total column water vapour has a longer spatial correlation length scale than SST features. The approach extends the observations input to the OE to include the averaged brightness temperatures (BTs) of nearby clear-sky pixels, in addition to the BTs of the pixel for which SST is being retrieved. The retrieved quantities are then the single-pixel SST and the clear-sky total column water vapour averaged over the vicinity of the pixel. This reduces the noise in the retrieved SST significantly. The robust standard deviation of the new OE SST compared to matched drifting buoys becomes 0.39 K for all data. The smoothed OE gives SST sensitivity of 98% on average. This means that diurnal temperature variability and ocean frontal gradients are more faithfully estimated, and that the influence of the prior SST used is minimal (2%). This benefit is not available using traditional atmospheric correction smoothing.

Estimation of sea surface temperature from the Spinning Enhanced Visible and Infra Red Imager, improved using numerical weather prediction

Most of the operational Sea Surface Temperature (SST) products derived from satellite infrared radiometry use multi-spectral algorithms. They show, in general, reasonable performances with root mean square (RMS) residuals around 0.5 K when validated against buoy measurements, but have limitations, particularly a component of the retrieval error that relates to such algorithms' limited ability to cope with the full variability of atmospheric absorption and emission. We propose to use forecast atmospheric profiles and a radiative transfer model to simulate the algorithmic errors of multi-spectral algorithms. In the practical case of SST derived from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG), we demonstrate that simulated algorithmic errors do explain a significant component of the actual errors observed for the non linear (NL) split window algorithm in operational use at the Centre de Météorologie Spatiale (CMS). The simulated errors, used as correction terms, reduce significantly the regional biases of the NL algorithm as well as the standard deviation of the differences with drifting buoy measurements. The availability of atmospheric profiles associated with observed satellite-buoy differences allows us to analyze the origins of the main algorithmic errors observed in the SEVIRI field of view: a negative bias in the inter-tropical zone, and a mid-latitude positive bias. We demonstrate how these errors are explained by the sensitivity of observed brightness temperatures to the vertical distribution of water vapour, propagated through the SST retrieval algorithm.

Probabilistic physically-based cloud screening of satellite infra-red imagery for operational sea surface temperature retrieval

We propose and demonstrate a fully probabilistic (Bayesian) approach to the detection of cloudy pixels in thermal infrared (TIR) imagery observed from satellite over oceans. Using this approach, we show how to exploit the prior information and the fast forward modelling capability that are typically available in the operational context to obtain improved cloud detection. The probability of clear sky for each pixel is estimated by applying Bayes' theorem, and we describe how to apply Bayes' theorem to this problem in general terms. Joint probability density functions (PDFs) of the observations in the TIR channels are needed; the PDFs for clear conditions are calculable from forward modelling and those for cloudy conditions have been obtained empirically. Using analysis fields from numerical weather prediction as prior information, we apply the approach to imagery representative of imagers on polar-orbiting platforms. In comparison with the established cloud-screening scheme, the new technique decreases both the rate of failure to detect cloud contamination and the false-alarm rate by one quarter. The rate of occurrence of cloud-screening-related errors of >1 K in area-averaged SSTs is reduced by 83%. Copyright © 2005 Royal Meteorological Society.

DNA, Red Tide and the Sea: a new exhibit at Mystic Aquarium & IFE

DNA, Red Tide and the Sea is a new exhibit at Mystic Aquarium & IFE. It was developed by UConn Marine Sciences Professor Senjie Lin, and Mystic Aquarium. Children can extract DNA from fruit and learn about genetic codes and red tides in the ocean.