Polychaete fauna from the intertidal zone of the Kneiss Islands  (central Mediterranean Sea)

The spatial and temporal distribution, abundance and assemblage structure of polychaete communities in the Kneiss Islands (central Mediterranean Sea) was studied at 42 stations selected among seagrass Zostera (Zosterella) noltei Hornemann meadows and unvegetated habitats sampled from April 2014 to January 2015. The Kneiss Islands represent a site of international interest in terms of their ornithological diversity (Important Bird Area, Ramsar Site and SPAMI). A total of 18,026 individuals and 92 species of polychaetes belonging to 25 families were identified. Analysis of the trophic structure reveals that the majority of stations are strongly dominated by deposit feeders (51.2%), followed by carnivores (34.8%) and suspension feeders (14%). Polychaete diversity and abundance were higher on the vegetated stations. Four polychaete assemblages are identified using MDS analysis. The distribution of polychaete assemblages are influenced by edaphic factors, particularly sediment structure and organic matter content. Seasonal variations of the polychaete community patterns at 20 stations show a maximum abundance and diversity during spring and summer and a minimum during winter. Seasonal fluctuations follow the seasonal variations of the environmental factors such as temperature and salinity, and correspond also to the lifestyle of the dominant species.

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Swordfish monitoring by a GIS-based spatial and temporal distribution analysis on harpoon fishery data: A case of study in the central Mediterranean Sea

Fisheries Research ◽

10.1016/j.fishres.2016.07.006 ◽

2016 ◽

Vol 183 ◽

pp. 424-434 ◽

Cited By ~ 6

Author(s):

Patrizia Perzia ◽

Pietro Battaglia ◽

Pierpaolo Consoli ◽

Franco Andaloro ◽

Teresa Romeo

Keyword(s):

Mediterranean Sea ◽

Temporal Distribution ◽

Distribution Analysis ◽

Spatial And Temporal Distribution ◽

Central Mediterranean ◽

Central Mediterranean Sea ◽

Fishery Data

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Predictive distribution models of European hake in the south-central Mediterranean Sea

Hydrobiologia ◽

10.1007/s10750-017-3338-5 ◽

2017 ◽

Vol 821 (1) ◽

pp. 153-172 ◽

Cited By ~ 3

Author(s):

G. Garofalo ◽

S. Fezzani ◽

F. Gargano ◽

G. Milisenda ◽

O. Ben Abdallah ◽

...

Keyword(s):

Mediterranean Sea ◽

Predictive Distribution ◽

The South ◽

Distribution Models ◽

Central Mediterranean ◽

South Central ◽

Central Mediterranean Sea ◽

European Hake

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Ecological status assessment and non-indigenous species in industrial and fishing harbours of the Gulf of Gabès (central Mediterranean Sea)

Environmental Science and Pollution Research ◽

10.1007/s11356-021-14729-1 ◽

2021 ◽

Author(s):

Nawfel Mosbahi ◽

Jean-Philippe Pezy ◽

Lassad Neifar ◽

Jean-Claude Dauvin

Keyword(s):

Mediterranean Sea ◽

Ecological Status ◽

Indigenous Species ◽

Central Mediterranean ◽

Gulf Of Gabes ◽

Gulf Of Gabès ◽

Central Mediterranean Sea ◽

Ecological Status Assessment ◽

Status Assessment ◽

Non Indigenous Species

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Correction to: Assessment of cetacean–fishery interactions in the marine food web of the Gulf of Taranto (Northern Ionian Sea, Central Mediterranean Sea)

Reviews in Fish Biology and Fisheries ◽

10.1007/s11160-020-09630-y ◽

2021 ◽

Author(s):

Roberto Carlucci ◽

Francesca Capezzuto ◽

Giulia Cipriano ◽

Gianfranco D’Onghia ◽

Carmelo Fanizza ◽

...

Keyword(s):

Food Web ◽

Mediterranean Sea ◽

Ionian Sea ◽

Central Mediterranean ◽

Marine Food Web ◽

Central Mediterranean Sea ◽

Marine Food ◽

Fishery Interactions

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Air–Sea Interaction in the Central Mediterranean Sea: Assessment of Reanalysis and Satellite Observations

Remote Sensing ◽

10.3390/rs13112188 ◽

2021 ◽

Vol 13 (11) ◽

pp. 2188

Author(s):

Salvatore Marullo ◽

Jaime Pitarch ◽

Marco Bellacicco ◽

Alcide Giorgio di Sarra ◽

Daniela Meloni ◽

...

Keyword(s):

Heat Flux ◽

Mediterranean Sea ◽

Seasonal Cycle ◽

Heat Fluxes ◽

Meteorological Variables ◽

Central Mediterranean ◽

High Quality ◽

Central Mediterranean Sea ◽

In Situ Observations

Air–sea heat fluxes are essential climate variables, required for understanding air–sea interactions, local, regional and global climate, the hydrological cycle and atmospheric and oceanic circulation. In situ measurements of fluxes over the ocean are sparse and model reanalysis and satellite data can provide estimates at different scales. The accuracy of such estimates is therefore essential to obtain a reliable description of the occurring phenomena and changes. In this work, air–sea radiative fluxes derived from the SEVIRI sensor onboard the MSG satellite and from ERA5 reanalysis have been compared to direct high quality measurements performed over a complete annual cycle at the ENEA oceanographic observatory, near the island of Lampedusa in the Central Mediterranean Sea. Our analysis reveals that satellite derived products overestimate in situ direct observations of the downwelling short-wave (bias of 6.1 W/m2) and longwave (bias of 6.6 W/m2) irradiances. ERA5 reanalysis data show a negligible positive bias (+1.0 W/m2) for the shortwave irradiance and a large negative bias (−17 W/m2) for the longwave irradiance with respect to in situ observations. ERA5 meteorological variables, which are needed to calculate the air–sea heat flux using bulk formulae, have been compared with in situ measurements made at the oceanographic observatory. The two meteorological datasets show a very good agreement, with some underestimate of the wind speed by ERA5 for high wind conditions. We investigated the impact of different determinations of heat fluxes on the near surface sea temperature (1 m depth), as determined by calculations with a one-dimensional numerical model, the General Ocean Turbulence Model (GOTM). The sensitivity of the model to the different forcing was measured in terms of differences with respect to in situ temperature measurements made during the period under investigation. All simulations reproduced the true seasonal cycle and all high frequency variabilities. The best results on the overall seasonal cycle were obtained when using meteorological variables in the bulk formulae formulations used by the model itself. The derived overall annual net heat flux values were between +1.6 and 40.4 W/m2, depending on the used dataset. The large variability obtained with different datasets suggests that current determinations of the heat flux components and, in particular, of the longwave irradiance, need to be improved. The ENEA oceanographic observatory provides a complete, long-term, high resolution time series of high quality in situ observations. In the future, more similar sites worldwide will be needed for model and satellite validations and to improve the determination of the air–sea exchange and the understanding of related processes.

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