136 research outputs found

    Dominance of photo over chromatic acclimation strategies by habitat-forming mesophotic red algae

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    Funding was provided by a Leverhulme Trust Research Project grant no. (RPG-2018-113) to H.L.B., G.A.T. and I.D.W.S., an Engineering and Physical Sciences Research Council grant (EP/L017008/1) to G.A.T. and I.D.W.S., and a São Paulo Research Foundation (FAPESP) individual grant (#2016/14017-0) to G.H.P.-F.Red coralline algae are the deepest living macroalgae, capable of creating spatially complex reefs from the intertidal to 100+ m depth with global ecological and biogeochemical significance. How these algae maintain photosynthetic function under increasingly limiting light intensity and spectral availability is key to explaining their large depth distribution. Here, we investigated the photo- and chromatic acclimation and morphological change of free-living red coralline algae towards mesophotic depths in the Fernando do Noronha archipelago, Brazil. From 13 to 86 m depth, thalli tended to become smaller and less complex. We observed a dominance of the photo-acclimatory response, characterized by an increase in photosynthetic efficiency and a decrease in maximum electron transport rate. Chromatic acclimation was generally stable across the euphotic-mesophotic transition with no clear depth trend. Taxonomic comparisons suggest these photosynthetic strategies are conserved to at least the Order level. Light saturation necessitated the use of photoprotection to 65 m depth, while optimal light levels were met at 86 m. Changes to the light environment (e.g. reduced water clarity) due to human activities therefore places these mesophotic algae at risk of light limitation, necessitating the importance of maintaining good water quality for the conservation and protection of mesophotic habitats.Publisher PDFPeer reviewe

    Ecosystem engineer morphological traits and taxon identity shape biodiversity across the euphotic-mesophotic transition

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    Funding was provided by a Leverhulme Trust Research Project grant (no. RPG-2018-113) to H.L.B., G.A.T. and I.D.W.S., an Engineering and Physical Sciences Research Council grant (no. EP/L017008/1) to G.A.T. and I.D.W.S., and a São Paulo Research Foundation (FAPESP) individual grant (no. 2016/14017-0) to G.H.P.F.The euphotic-mesophotic transition is characterized by dramatic changes in environmental conditions, which can significantly alter the functioning of ecosystem engineers and the structure of their associated communities. However, the drivers of biodiversity change across the euphotic-mesophotic transition remain unclear. Here, we investigated the mechanisms affecting the biodiversity-supporting potential of free-living red coralline algae-globally important habitat creators-towards mesophotic depths. Across a 73 m depth gradient, we observed a general decline in macrofaunal biodiversity (fauna abundance, taxon richness and alpha diversity), but an increase in beta-diversity (i.e. variation between assemblages) at the deepest site (86 m depth, where light levels were less than 1% surface irradiance). We identified a gradient in abundance decline rather than distinct ecological shifts, driven by a complex interaction between declining light availability, declining size of the coralline algal host individuals and a changing host taxonomy. However, despite abundance declines, high between-assemblage variability at deeper depths allowed biodiversity-supporting potential to be maintained, highlighting their importance as coastal refugia.PostprintPeer reviewe

    A search for ultra-high-energy photons at the Pierre Auger Observatory exploiting air-shower universality

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    The Pierre Auger Observatory is the most sensitive detector to primary photons with energies above ∼0.2 EeV. It measures extensive air showers using a hybrid technique that combines a fluorescence detector (FD) with a ground array of particle detectors (SD). The signatures of a photon-induced air shower are a larger atmospheric depth at the shower maximum (Xmax_{max}) and a steeper lateral distribution function, along with a lower number of muons with respect to the bulk of hadron-induced background. Using observables measured by the FD and SD, three photon searches in different energy bands are performed. In particular, between threshold energies of 1-10 EeV, a new analysis technique has been developed by combining the FD-based measurement of Xmax_{max} with the SD signal through a parameter related to its muon content, derived from the universality of the air showers. This technique has led to a better photon/hadron separation and, consequently, to a higher search sensitivity, resulting in a tighter upper limit than before. The outcome of this new analysis is presented here, along with previous results in the energy ranges below 1 EeV and above 10 EeV. From the data collected by the Pierre Auger Observatory in about 15 years of operation, the most stringent constraints on the fraction of photons in the cosmic flux are set over almost three decades in energy

    Study on multi-ELVES in the Pierre Auger Observatory

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    Since 2013, the four sites of the Fluorescence Detector (FD) of the Pierre Auger Observatory record ELVES with a dedicated trigger. These UV light emissions are correlated to distant lightning strikes. The length of recorded traces has been increased from 100 μs (2013), to 300 μs (2014-16), to 900 μs (2017-present), to progressively extend the observation of the light emission towards the vertical of the causative lightning and beyond. A large fraction of the observed events shows double ELVES within the time window, and, in some cases, even more complex structures are observed. The nature of the multi-ELVES is not completely understood but may be related to the different types of lightning in which they are originated. For example, it is known that Narrow Bipolar Events can produce double ELVES, and Energetic In-cloud Pulses, occurring between the main negative and upper positive charge layer of clouds, can induce double and even quadruple ELVES in the ionosphere. This report shows the seasonal and daily dependence of the time gap, amplitude ratio, and correlation between the pulse widths of the peaks in a sample of 1000+ multi-ELVES events recorded during the period 2014-20. The events have been compared with data from other satellite and ground-based sensing devices to study the correlation of their properties with lightning observables such as altitude and polarity

    First results from the AugerPrime Radio Detector

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    Update of the Offline Framework for AugerPrime

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    Outreach activities at the Pierre Auger Observatory

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    The ultra-high-energy cosmic-ray sky above 32 EeV viewed from the Pierre Auger Observatory

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    Extraction of the Muon Signals Recorded with the Surface Detector of the Pierre Auger Observatory Using Recurrent Neural Networks

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    We present a method based on the use of Recurrent Neural Networks to extract the muon component from the time traces registered with water-Cherenkov detector (WCD) stations of the Surface Detector of the Pierre Auger Observatory. The design of the WCDs does not allow to separate the contribution of muons to the time traces obtained from the WCDs from those of photons, electrons and positrons for all events. Separating the muon and electromagnetic components is crucial for the determination of the nature of the primary cosmic rays and properties of the hadronic interactions at ultra-high energies. We trained a neural network to extract the muon and the electromagnetic components from the WCD traces using a large set of simulated air showers, with around 450 000 simulated events. For training and evaluating the performance of the neural network, simulated events with energies between 1018.5, eV and 1020 eV and zenith angles below 60 degrees were used. We also study the performance of this method on experimental data of the Pierre Auger Observatory and show that our predicted muon lateral distributions agree with the parameterizations obtained by the AGASA collaboration

    Event-by-event reconstruction of the shower maximum XmaxX_{\mathrm{max}} with the Surface Detector of the Pierre Auger Observatory using deep learning

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