@article {5844,
	title = {Functional traits unravel temporal changes in fish biomass production on artificial reefs},
	journal = {Marine Environmental Research},
	volume = {145},
	year = {2019},
	pages = {137-146},
	abstract = {<p>Artificial reefs (ARs) are deployed worldwide as they are expected to support fisheries management. While the underlying mechanisms remain widely debated, production was recently determined as the most probable cause of increases in fish biomass. Changes in fish biomass in a temperate AR system were investigated from December 2008 to November 2015 by considering seven distinct functional groups, and isotopic functional indices were used to identify how these changes may have affected organic matter (OM) fluxes. Contrasting patterns of change were observed between functional trophic groups, highlighting that combining the biomass of all species present in a community is inappropriate for assessing AR-induced effects. Benthic sedentary species predominated (\&gt;75\% of the total biomass) through massive production, with a 68-fold increase in mean biomass over the study period. Mobile species tended to vary seasonally, suggesting only a slight influence of AR. Zooplanktivores biomass decreased over the 6-year period, as a possible result of changes in environmental conditions. Isotopic indices helped to reveal both the community maturation and the importance of local OM sources not only in supporting fish biomass production but also in attracting pelagic species. Our results corroborate that production and attraction are two extremes of a range of contrasting patterns and highlight the importance of considering the specific responses of functional components of fish communities to accurately describe changes in AR functioning. Functional attributes such as trophic traits, habitat use and dispersal abilities must not be overlooked as they modulate fish species responses to the deployment of man-made rocky substrates.</p>
},
	keywords = {Artificial reefs, Fish biomass production, Isotopic functional indices, Mediterranean sea},
	issn = {0141-1136},
	doi = {https://doi.org/10.1016/j.marenvres.2019.02.018},
	url = {http://www.sciencedirect.com/science/article/pii/S0141113618307979},
	author = {Cresson, Pierre and Le Direach, Laurence and Rouanet, Elodie and Goberville, Eric and Astruch, Patrick and Ourgaud, M{\'e}lanie and Mireille Harmelin-Vivien}
}
@article {Meddeb201967,
	title = {A new type of plankton food web functioning in coastal waters revealed by coupling Monte Carlo Markov chain linear inverse method and ecological network analysis},
	journal = {Ecological Indicators},
	volume = {104},
	year = {2019},
	note = {cited By 0},
	pages = {67-85},
	publisher = {Elsevier B.V.},
	abstract = {Plankton food webs (PFW) typology is based on different categories of functioning, according to the dominant processes and the role played by heterotrophic bacteria, small vs large phytoplankton, and small vs large zooplankton. Investigating the structure and the function of planktonic food webs in two SW Mediterranean waters (inshore and marine sites) at four seasons, using inverse (LIM-MCMC) and ecological network (ENA) analyses, we identified a new type of food web, called the {\textquotedblleft}bacterial multivorous food web{\textquotedblright}. This food web adds to the conventional trophic continuum as previously reported. The {\textquotedblleft}bacterial multivorous food web{\textquotedblright} present in winter showed the lowest primary production among seasons, but highest bacterial production. Several food web ratios characterized this new typology e.g. picophytoplankton net primary production to total primary production varied from 0.20 to 0.28; bacterial to primary production ratio is higher than values reported in global scale (≅1); bacterial net production to the potential protozoan prey net production was high (\&gt;0.2). In this special food web, carbon was mostly recycled, with a moderate fraction channeled to deep waters, which lead to a higher retention of carbon inside the ecosystem. This winter PFW also seemed to be the most organized, specialized, stable and mature, as related to common interpretations of ENA. The spring was characterized by herbivorous food web, with highest activity coinciding with low stability. Although less usual, the herbivorous pathway was also observed during summer, in inshore waters. The autumn food webs, which functioned as multivorous or microbial food webs, appeared to be stable and mature. Finally, our study demonstrates the usefulness of food web models derived ratios combined with ecological network analysis indices to conduct evaluation of the structure and functioning of ecosystems and potentially to support management decisions in marine environment. {\textcopyright} 2019},
	keywords = {Bacteria (microorganisms), bacterium, Carbon, Chemical contamination, coastal water, Coastal waters, ecological modeling, Ecology, ecosystem function, Ecosystems, Electric network analysis, Food microbiology, food web, Food web model, Food webs, inverse analysis, Inverse problems, Markov chain, Markov processes, Mediterranean sea, Monte Carlo analysis, Monte Carlo methods, net primary production, network analysis, Phytoplankton, picoplankton, Plankton, Protozoa, protozoan, Seasonal variation, trophic status, Trophic structure},
	issn = {1470160X},
	doi = {10.1016/j.ecolind.2019.04.077},
	url = {https://www.sciencedirect.com/science/article/abs/pii/S1470160X19303243},
	author = {Meddeb, M. and Nathalie Niquil and Grami, B. and Mejri, K. and Haraldsson, M. and Chaalali, A. and Pringault, O. and Hlaili, A.S.}
}
@article {Meddeb201866,
	title = {Plankton food-web functioning in anthropogenically impacted coastal waters (SW Mediterranean Sea): An ecological network analysis},
	journal = {Progress in Oceanography},
	volume = {162},
	year = {2018},
	note = {cited By 4},
	pages = {66-82},
	publisher = {Elsevier Ltd},
	abstract = {The study is the first attempt to (i) model spring food webs in three SW Mediterranean ecosystems which are under different anthropogenic pressures and (ii) to project the consequence of this stress on their function. Linear inverse models were built using the Monte Carlo method coupled with Markov Chains to characterize the food-web status of the Lagoon, the Channel (inshore waters under high eutrophication and chemical contamination) and the Bay of Bizerte (offshore waters under less anthropogenic pressure). Ecological network analysis was used for the description of structural and functional properties of each food web and for inter-ecosystem comparisons. Our results showed that more carbon was produced by phytoplankton in the inshore waters (966{\textendash}1234 mg C m-2 d-1) compared to the Bay (727 mg C m-2 d-1). The total ecosystem carbon inputs into the three food webs was supported by high primary production, which was mainly due to \&gt;10 {\textmu}m algae. However, the three carbon pathways were characterized by low detritivory and a high herbivory which was mainly assigned to protozooplankton. This latter was efficient in channelling biogenic carbon. In the Lagoon and the Channel, foods webs acted almost as a multivorous structure with a tendency towards herbivorous one, whereas in the Bay the herbivorous pathway was more dominant. Ecological indices revealed that the Lagoon and the Channel food webs/systems had high total system throughput and thus were more active than the Bay. The Bay food web, which had a high relative ascendency value, was more organized and specialized. This inter{\textendash}ecosystem difference could be due to the varying levels of anthropogenic impact among sites. Indeed, the low value of Finn{\textquoteright}s cycling index indicated that the three systems are disturbed, but the Lagoon and the Channel, with low average path lengths, appeared to be more stressed, as both sites have undergone higher chemical pollution and nutrient loading. This study shows that ecosystem models combined with ecological indices provide a powerful approach to detect change in environmental status and anthropogenic impacts. {\textcopyright} 2018},
	keywords = {Algae, anthropogenic effect, Anthropogenic impacts, Anthropogenic pressures, Bizerte, Bizerte Bay, Chemical analysis, Chemical contamination, coastal water, community structure, Ecological network analysis, Ecology, ecosystem function, ecosystem modeling, Ecosystems, eutrophication, food web, Food webs, Functional properties, Inverse problems, Lakes, Linear inverse models, Markov processes, Mediterranean coastal waters, Mediterranean ecosystem, Mediterranean sea, Monte Carlo methods, network analysis, Phytoplankton, Plankton, primary production, Tunisia, Zooplankton},
	issn = {00796611},
	doi = {10.1016/j.pocean.2018.02.013},
	url = {https://www.sciencedirect.com/science/article/abs/pii/S0079661117300782},
	author = {Meddeb, M. and Grami, B. and Chaalali, A. and Haraldsson, M. and Nathalie Niquil and Pringault, O. and Sakka Hlaili, A.}
}
@article {6667,
	title = {Dynamics of particulate organic matter composition in coastal systems: A spatio-temporal study at multi-systems scale},
	journal = {Progress in Oceanography},
	volume = {156},
	year = {2017},
	pages = {221-239},
	abstract = {In coastal systems, the multiplicity of sources fueling the pool of particulate organic matter (POM) leads to divergent estimations of POM composition. Eleven systems (two littoral systems, eight embayments and semi-enclosed systems and one estuary) distributed along the three maritime fa{\c c}ades of France were studied for two to eight years in order to quantify the relative contribution of organic matter sources to the surface-water POM pool in coastal systems. This study was based on carbon and nitrogen elemental and isotopic ratios, used for running mixing models. The POM of the estuary is dominated by terrestrial material (93\% on average), whereas the POM of the other systems is dominated by phytoplankton (84\% on average). Nevertheless, for the latter systems, the POM composition varies in space, with (1) systems where POM is highly composed of phytoplankton (>=93\%), (2) systems characterized by a non-negligible contribution of benthic (8{\textendash}19\%) and/or river (7{\textendash}19\%) POM sources, and (3) the Mediterranean systems characterized by the contribution of diazotroph organisms (ca. 14\%). A continent-to-ocean gradient of river and/or benthic POM contribution is observed. Finally, time series reveal (1) seasonal variations of POM composition, (2) differences in seasonality between systems, and (3) an inshore-offshore gradient of seasonality within each system that were sampled at several stations. Spatial and seasonal patterns of POM composition are mainly due to local to regional processes such as hydrodynamics and sedimentary hydrodynamic (e.g. resuspension processes, changes in river flows, wind patterns influencing along-shore currents) but also due to the geomorphology of the systems (depth of the water column, distance to the shore). Future studies investigating the link between these forcings and POM composition would help to better understand the dynamics of POM composition in coastal systems. {\textcopyright} 2017 Elsevier Ltd},
	keywords = {bacterium, benthos, biogeochemistry, Biological materials, C and n stable isotopes, C:N ratio, Carbon, carbon isotope, Coastal systems, coastal zone, Fluid dynamics, France, geomorphology, Hydrodynamics, Isotopes, isotopic ratio, Mediterranean sea, Meta analysis, meta-analysis, Mixing, Mixing models, nitrogen isotope, Organic compounds, particulate organic matter, Particulate organic matters, Phytoplankton, prokaryote, Rivers, seasonality, spatiotemporal analysis, stable isotope, Surface water, Surface waters, terrestrial deposit, Time series},
	issn = {00796611},
	doi = {10.1016/j.pocean.2017.03.001},
	url = {https://www.sciencedirect.com/science/article/abs/pii/S0079661116301914},
	author = {Li{\'e}nart, Camilla and Savoye, Nicolas and Bozec, Yann and Elsa Breton and Conan, Pascal and David, Val{\'e}rie and Eric Feunteun and Karine Granger{\'e} and Kerherv{\'e}, P. and Lebreton, B. and S{\'e}bastien Lefebvre and St{\'e}phane L{\textquoteright}Helguen and Mousseau, Laure and Raimbault, P and Richard, P. and Riera, P. and Sauriau, P.-G. and Gauthier Schaal and Aubert, F. and Aubin, S. and Bichon, S. and Boinet, C. and Bourasseau, L. and Br{\'e}ret, M. and Caparros, J. and Cariou, T. and Charlier, K. and Claquin, P. and Vincent Cornille and Corre, A.-M. and Costes, L. and Crispi, O. and Muriel Crouvoisier and Czamanski, M. and Del Amo, Y. and Derriennic, H. and Dindinaud, F. and Durozier, M. and Hanquiez, V. and Antoine Nowaczyk and Devesa, J. and Ferreira, S. and Fornier, M. and Garcia, F. and Garcia, N. and Geslin, S. and Emilie Grossteffan and Gueux, A. and Guillaudeau, J. and Guillou, G. and Joly, O. and Lachauss{\'e}e, N. and Lafont, M. and Lamoureux, J. and Lecuyer, E. and Lehodey, J.-P. and Lemeille, D. and Leroux, C. and Mac{\'e}, E. and Maria, E. and Pineau, P. and Petit, F. and Pujo-Pay, M. and Rimelin-Maury, P. and Sultan, E.}
}
