Suchergebnisse

The Eastern Mediterranean Transient (EMT) occurred in the Aegean Sea from 1988 to 1995 and is the most significant intermediate-to-deep Mediterranean overturning perturbation reported by instrumental records. The EMT was likely caused by accumulation of high salinity waters in the Levantine and enhanced heat loss in the Aegean Sea, coupled with surface water freshening in the Sicily Channel. It is still unknown whether similar transients occurred in the past and, if so, what their forcing processes were. In this study, sediments from the Sicily Channel document surface water freshening (SCFR) at 1910 ± 12, 1812 ± 18, 1725 ± 25 and 1580 ± 30 CE. A regional ocean hindcast links SCFR to enhanced deep-water production and in turn to strengthened Mediterranean thermohaline circulation. Independent evidence collected in the Aegean Sea supports this reconstruction, showing that enhanced bottom water ventilation in the Eastern Mediterranean was associated with each SCFR event. Comparison between the records and multi-decadal atmospheric circulation patterns and climatic external forcings indicates that Mediterranean circulation destabilisation occurs during positive North Atlantic Oscillation (NAO) and negative Atlantic Multidecadal Oscillation (AMO) phases, reduced solar activity and strong tropical volcanic eruptions. They may have recurrently produced favourable deep-water formation conditions, both increasing salinity and reducing temperature on multi-decadal time scales. ; Funding for this work was provided by the European Union's Seventh Framework programme, FP7 under grant agreement no 265103 (MedSeA Project) and no 243908 (Past4FutureProject), Red CONSOLIDER GRACCIE CTM2014-59111-RED and the Past Global Changes (PAGES) project, which in turn received support from the US and Swiss National Science Foundations. G.J. thanks a postdoctoral grant (PD-036-2013) from the Comunitat Autonoma de les Illes Balears and the European Social Fund and a Ramón y Cajal contract (RYC-2013-14714). We acknowledge the support of the Generalitat de Catalunya to MERS (2014 SGR–1356) and Applied Geography (2014 SGR–1090). ; Peer Reviewed

The Common Fisheries Policy of the European Union aims to exploit fish stocks at a level of Maximum Sustainable Yield by 2020 at the latest. At the Mediterranean level, the General Fisheries Commission for the Mediterranean (GFCM) has highlighted the importance of reversing the observed declining trend of fish stocks. In this complex context, it is important to obtain reliable biomass estimates to support scientifically sound advice for sustainable management of marine resources. This paper presents a machine learning methodology for the classification of pelagic species schools from acoustic and environmental data. In particular, the methodology was tuned for the recognition of anchovy, sardine and horse mackerel. These species have a central role in the fishing industry of Mediterranean countries and they are also of considerable importance in the trophic web because they occupy the so-called middle trophic level. The proposed methodology consists of a classifier based on an optimized two layer feed-forward neural network. Morphological, bathymetric, energetic and positional features, extracted from acoustic data, are used as input, together with other environmental data features. The classifier uses an optimal number of neurons in the hidden layer, and a feature selection strategy based on a genetic algorithm. Working on a dataset of 2565 fish schools, the proposed methodology permitted us to identify the these three fish species with an accuracy of around 95%.