The Sargasso Sea has long been considered as the only spawning area for Atlantic eels, despite the absence of direct observations. The present study raises a novel scenario, deviating from Schmidt’s dogma, begins with a review of historical and recent observations that were combined to build up a global theory on spawning ecology and migration behavior of Atlantic eels. From this, it is argued that a favorable spawning area could be located eastward of Sargasso Sea at the intersection between the Mid-Atlantic Ridge and the oceanic fronts. Ocean circulation models combined with 3D particle-tracking method confirmed that spawning at this specific area would result in larval distribution fitting the field observation. This study explores the hypothesis that leptocephali are able to swim and orientate to reach their specific growth areas. It proposes a novel framework about spawning ecology, based on orientation, navigation and meeting cues of silver eels to the spawning area. Together this framework may serve as a stepping-stone for solving the long-lasting mystery of eel reproduction which first came out 2,400 years ago and promotes the understanding of oceanic migration and reproduction of marine organisms.

European eel is thought to be a symbol of the effects of global change on aquatic biodiversity. The species has persisted for millions of years and faced drastic environmental fluctuations thanks to its phenotypic plasticity. However, the species has recently declined to historically low levels under synergistic human pressures. Sublethal chemical contamination has been shown to alter reproductive capacity, but the impacts and required actions are not fully addressed by conservation plans. This paper proposes a modelling approach to quantify the effects of sublethal contamination by anthropogenic pollutants on the expression of life history traits and related fitness of the critically endangered European eel. Material and Methods: We sampled female silver eels from eight different catchments across Europe previously shown to be representative of the spectrum of environmental variability and contamination. We measured 11 fitness-related life history traits within four main categories: fecundity, adaptability and plasticity, migratory readiness, and spawning potential. We used machine learning in models to explore the phenotypic reaction (expression of these life history traits) according to geographical parameters, parasite burdens (the introduced nematode Anguillicoloides crassus) and anthropogenic contaminants (persistent organic pollutants (POPs) in muscular tissue and trace elements (TEs) in gonads, livers and muscles). Finally, we simulated, the effects of two management scenarios—contamination reduction and contamination increase—on the fecundity and recruitment. Results: Contamination in our sampling was shown to have a stronger control on life history traits than do geographic and environmental factors that are currently described in the literature. We modelled different contamination scenarios to assess the benefit of mitigation: these scenarios suggest that reducing pollutants concentrations to the lowest values that occurred in our sampling design would double the fecundity of eels compared to the current situation. Discussion: Remediation of contamination could represent a viable management option for increasing the resilience of eel populations, with much more effects than solely reducing fishing mortality. More broadly, our work provides an innovative way for quantitative assessment of the reaction norms of species’ biological traits and related fecundity to contamination by organic and inorganic pollutions thus opening new management and conservation pathways to revert the erosion of biodiversity.

To identify key nonspecific organisational characteristics of the mid-trophic pelagic communities, which remain a challenge, we work with sound scattering layers (SSLs). Application was tested in the three African Atlantic Large Marine Ecosystems (AALMEs) to assess the utility of adapting and developing new acoustic variables. Our methodology allowed comparison between Large Marine Ecosystems (LMEs) based on 14 morphological, spatial and acoustic variables to characterize SSLs over time. These original variables were effective in monitoring and comparing the LMEs, and even allowed us to discriminate different organisations inside the Canary Current LME. Common traits identified for all AALMEs included the importance of the shallowest SSL. However, we identified an unexpected night-time pattern in SSL distributions in the Benguela Current LME which reflect a major difference in diel vertical migration mechanisms relative to other AALMEs. We also highlighted the predominance of elementary sampling unit (ESUs) with a single SSL and an unoccupied tiny layer close to the bottom, even if some ESUs presented up to six SSLs. Inter-annual changes in SSL organisation are highlighted by adaptation of original variables as the proportion of the water column occupied by SSLs and the relative importance of the shallowest SSL. SSL variables have been used mostly in deep water; here, we applied them on the continental shelf. SSL variables can be used to standardize the monitoring of marine ecosystems and capture change in spatial structure and function of mid-trophic pelagic marine ecosystems worldwide, even in data-poor areas where species identification of lower-trophic pelagic organism remains a challenge.