Movements of bluefin tuna (<Emphasis Type="Italic">Thunnus thynnus</Emphasis>) in the northwestern Atlantic Ocean recorded by pop-up satellite archival tags

Pop-up satellite archival tags were implanted into 68 Atlantic bluefin tuna (Thunnus thynnus Linnaeus), ranging in size from 91 to 295 kg, in the southern Gulf of Maine (n=67) and off the coast of North Carolina (n=1) between July 2002 and January 2003. Individuals tagged in the Gulf of Maine left that area in late fall and overwintered in northern shelf waters, off the coasts of Virginia and North Carolina, or in offshore waters of the northwestern Atlantic Ocean. In spring, the fish moved either northwards towards the Gulf of Maine or offshore. None of the fish crossed the 45°W management line (separating eastern and western management units) and none traveled towards the Gulf of Mexico or the Straits of Florida (known western Atlantic spawning grounds). The greatest depth recorded was 672 m and the fish experienced temperatures ranging from 3.4 to 28.7°C. Swimming depth was significantly correlated with location, season, size class, time of day, and moon phase. There was also evidence of synchronous vertical behavior and changes in depth distribution in relation to oceanographic features.Communicated by J.P. Grassle, New Brunswick     

Multi-lag cluster designs for estimating the semivariogram for sediments affected by effluent discharges offshore in San Diego

Maps are useful tools for understanding, managing, and protecting the marine environment, yet few useful and statistically defensible maps of environmental quality and aquatic resources have been developed in near-coastal regions. Current environmental management efforts, such as ocean monitoring by sewage dischargers, routinely sample areas of potential impact using sparse sampling grids. Heterogeneous oceanic conditions often make extrapolation from these grids to non-sampled locations questionable. Although rarely applied in coastal monitoring, kriging offers a more rigorous statistical approach to mapping and allows confidence intervals to be calculated for predictions. Its usefulness relies on accurate models of the spatial variability through estimating the semivariogram. Many optimal designs for estimating the semivariogram have been proposed, but these designs are often difficult to implement in practice. In this paper, we present simple design strategies for augmenting existing monitoring designs with the goal of estimating the semivariogram. In particular, we investigate a multi-lag cluster design strategy, where clusters of sites, spaced at various lag distances, are placed around fixed stations on an existing sampling grid. We find that these multi-lag cluster designs provide improved accuracy in estimating the parameters of the semivariogram. Based on simulation study findings, we apply a multi-lag cluster enhancement to the monitoring grid for the City of San Diego’s Point Loma Wastewater Treatment Plant as part of a special study to map chemical contaminants in sediments around its sewage outfall.     

An estimate of predation rate and relative preference for algal versus crustacean prey by a spongiose skeletal radiolarian

Solitary radiolarians (Spongodrymus sp.) in laboratory cultures consumed ¹⁴C-labeled Amphidinium carteri and Coccolithus huxleyi more than Isochrysis galbana or Thalassiosira fluviatilis. The ratio of A. carteri protein consumed per unit time to the amount of Artemia sp. nauplius protein consumed (P/Z) was 6.7×10^-2 indicating that these omnivorous radiolarians tend to consume more zooplankton protein than phytoplankton protein.