No abstract

Cross-flows (winds or currents) affect animal movements [1-3]. Animals can temporarily be carried off course or permanently carried away from their preferred habitat by drift depending on their own traveling speed in relation to that of the flow [1]. Animals able to only weakly fly or swim will be the most impacted (e.g., [4]). To circumvent this problem, animals must be able to detect the effects of flow on their movements and respond to it [1, 2]. Here, we show that a weakly swimming organism, the jellyfish Rhizostoma octopus, can orientate its movements with respect to currents and that this behavior is key to the maintenance of blooms and essential to reduce the probability of stranding. We combined in situ observations with first-time deployment of accelerometers on free-ranging jellyfish and simulated the behavior observed in wild jellyfish within a high-resolution hydrodynamic model. Our results show that jellyfish can actively swim countercurrent in response to current drift, leading to significant life-history benefits, i.e., increased chance of survival and facilitated bloom formation. Current-oriented swimming may be achieved by jellyfish either directly detecting current shear across their body surface [5] or indirectly assessing drift direction using other cues (e.g., magnetic, infrasound). Our coupled behavioral-hydrodynamic model provides new evidence that current-oriented swimming contributes to jellyfish being able to form aggregations of hundreds to millions of individuals for up to several months, which may have substantial ecosystem and socioeconomic consequences [6, 7]. It also contributes to improve predictions of jellyfish blooms' magnitude and movements in coastal waters.

Detection and attribution of human influence on sea level rise are important topics that have not yet been explored in depth. We question whether the sea level changes (SLC) over the past century were natural in origin. SLC exhibit power law long-term correlations. By estimating Hurst exponent through Detrended Fluctuation Analysis and by applying statistics of Lennartz and Bunde [2009], we search the lower bounds of statistically significant external sea level trends in longest tidal records worldwide. We provide statistical evidences that the observed SLC, at global and regional scales, is beyond its natural internal variability. The minimum anthropogenic sea level trend (MASLT) contributes to the observed sea level rise more than 50% in New York, Baltimore, San Diego, Marseille, and Mumbai. A MASLT is about 1 mm/yr in global sea level reconstructions that is more than half of the total observed sea level trend during the XXth century.