Chemical composition of ocean manganese nodules from the Pacific Ocean using different techniques

Mineralogical and chemical analyses performed on 67 ferromanganese nodules from widely varying locations and depths within the marine environment of the Pacific Ocean indicate that the minor element composition is controlled by the mineralogy and that the formation of the mineral phases is depth dependent. The pressure effect upon the thermodynamics or kinetics of mineral formation is suggested as the governing agent in the depth dependence of the mineralogy. The minor elements, Pb and Co, appear concentrated in the dMnO2 phase, whereas Cu and Ni are more or less excluded from this phase. In the manganites, Pb and Co are relatively low in concentration, whereas Cu and Ni are spread over a wide range of values. The oxidation of Pb and Co from divalent forms in sea water to higher states can explain their concentration in the dMnO2 phase.

Call recognition and individual identification of fish vocalizations based on automatic speech recognition: An example with the Lusitanian toadfish

The study of acoustic communication in animals often requires not only the recognition of species specific acoustic signals but also the identification of individual subjects, all in a complex acoustic background. Moreover, when very long recordings are to be analyzed, automatic recognition and identification processes are invaluable tools to extract the relevant biological information. A pattern recognition methodology based on hidden Markov models is presented inspired by successful results obtained in the most widely known and complex acoustical communication signal: human speech. This methodology was applied here for the first time to the detection and recognition of fish acoustic signals, specifically in a stream of round-the-clock recordings of Lusitanian toadfish (Halobatrachus didactylus) in their natural estuarine habitat. The results show that this methodology is able not only to detect the mating sounds (boatwhistles) but also to identify individual male toadfish, reaching an identification rate of ca. 95%. Moreover this method also proved to be a powerful tool to assess signal durations in large data sets. However, the system failed in recognizing other sound types.