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  1. Abstract

    Landslides influence the global carbon (C) cycle by facilitating transfer of terrestrial C in biomass and soils to offshore depocenters and redistributing C within the landscape, affecting the terrestrial C reservoir itself. How landslides affect terrestrial C stocks is rarely quantified, so we derive a model that couples stochastic landslides with terrestrial C dynamics, calibrated to temperate rainforests in southeast Alaska, United States. Modeled landslides episodically transfer C from scars to deposits and destroy living biomass. After a landslide, total C stocks on the scar recover, while those on the deposit either increase (in the case of living biomass) or decrease while remaining higher than if no landslide had occurred (in the case of dead biomass and soil C). Specifically, modeling landslides in a 29.9 km2watershed at the observed rate of 0.004 landslides km−2 yr−1decreases average living biomass C density by 0.9 tC ha−1(a relative amount of 0.4%), increases dead biomass C by 0.3 tC ha−1(0.6%), and increases soil C by 3.4 tC ha−1(0.8%) relative to a base case with no landslides. The net effect is a small increase in total terrestrial C stocks of 2.8 tC ha−1(0.4%). The size of this boost increases with landslide frequency, reaching 6.5% at a frequency of 0.1 landslides km−2 yr−1. If similar dynamics occur in other landslide‐prone regions of the globe, landslides should be a net C sink and a natural buffer against increasing atmospheric CO2levels, which are forecast to increase landslide‐triggering precipitation events.

     
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  2. Free, publicly-accessible full text available June 1, 2024
  3. Abstract The Pandora Software Development Kit and algorithm libraries provide pattern-recognition logic essential to the reconstruction of particle interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at ProtoDUNE-SP, a prototype for the Deep Underground Neutrino Experiment far detector. ProtoDUNE-SP, located at CERN, is exposed to a charged-particle test beam. This paper gives an overview of the Pandora reconstruction algorithms and how they have been tailored for use at ProtoDUNE-SP. In complex events with numerous cosmic-ray and beam background particles, the simulated reconstruction and identification efficiency for triggered test-beam particles is above 80% for the majority of particle type and beam momentum combinations. Specifically, simulated 1 GeV/ c charged pions and protons are correctly reconstructed and identified with efficiencies of 86.1 $$\pm 0.6$$ ± 0.6 % and 84.1 $$\pm 0.6$$ ± 0.6 %, respectively. The efficiencies measured for test-beam data are shown to be within 5% of those predicted by the simulation. 
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    Free, publicly-accessible full text available July 1, 2024
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  5. Free, publicly-accessible full text available May 1, 2024