Fruit production, migrant bird visitation, and seed dispersal of Guarea glabra in Panama

The relationship between bird visitation and the size of the available fruit crop was studied at an understory tree ( Guarea glabra Vahl, Meliaceae) in the tropical wet forest of Barro Colorado Island, Panama Canal Zone. Twelve resident species and seven North American migrant species fed on the Bright orange arilloids (seeds with arils), which were not depleted during the normal fruiting period. The number of individual visitors, the number of visiting species, and the number of seeds removed increased linearly with the size of the available fruit crop. The proportion of seeds removed did not increase with the size of the available fruit crop, indicating that dispersal is a function of the number of fruit available and not a disproportionate function of large fruit displays. Four species of North American migrants ( Myiarchus crinitus, Catharus ustulatus, Vireo olivaceus , and Vermivora peregrina ) accounted for 70% of the visits and 60% of the seeds removed from the trees. No resident species visited Guarea as frequently as any one of these migrants. There was no indication that any single visitor was dependent on this tree for nutrition, nor that the tree was dependent upon any single species for dispersal. We hypothesize that the fruiting season of G. glabra is adaptively synchronized with northward migration of opportunistically frugivorous North American birds.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47724/1/442_2004_Article_BF00348067.pd

The ATLAS trigger system for LHC Run 3 and trigger performance in 2022

The ATLAS trigger system is a crucial component of the ATLAS experiment at the LHC. It is responsible for selecting events in line with the ATLAS physics programme. This paper presents an overview of the changes to the trigger and data acquisition system during the second long shutdown of the LHC, and shows the performance of the trigger system and its components in the proton-proton collisions during the 2022 commissioning period as well as its expected performance in proton-proton and heavy-ion collisions for the remainder of the third LHC data-taking period (2022–2025)

Electron and photon energy calibration with the ATLAS detector using LHC Run 2 data

This paper presents the electron and photon energy calibration obtained with the ATLAS detector using 140 fb-1 of LHC proton-proton collision data recorded at √(s) = 13 TeV between 2015 and 2018. Methods for the measurement of electron and photon energies are outlined, along with the current knowledge of the passive material in front of the ATLAS electromagnetic calorimeter. The energy calibration steps are discussed in detail, with emphasis on the improvements introduced in this paper. The absolute energy scale is set using a large sample of Z-boson decays into electron-positron pairs, and its residual dependence on the electron energy is used for the first time to further constrain systematic uncertainties. The achieved calibration uncertainties are typically 0.05% for electrons from resonant Z-boson decays, 0.4% at ET ∼ 10 GeV, and 0.3% at ET ∼ 1 TeV; for photons at ET ∼ 60 GeV, they are 0.2% on average. This is more than twice as precise as the previous calibration. The new energy calibration is validated using J/ψ → ee and radiative Z-boson decays

Performance and calibration of quark/gluon-jet taggers using 140 fb−1 of pp collisions at √s = 13 TeV with the ATLAS detector

The identification of jets originating from quarks and gluons, often referred to as quark/gluon tagging, plays an important role in various analyses performed at the Large Hadron Collider, as Standard Model measurements and searches for new particles decaying to quarks often rely on suppressing a large gluon-induced background. This paper describes the measurement of the efficiencies of quark/gluon taggers developed within the ATLAS Collaboration, using √s = 13 TeV proton–proton collision data with an integrated luminosity of 140 fb-1 collected by the ATLAS experiment. Two taggers with high performances in rejecting jets from gluon over jets from quarks are studied: one tagger is based on requirements on the number of inner-detector tracks associated with the jet, and the other combines several jet substructure observables using a boosted decision tree. A method is established to determine the quark/gluon fraction in data, by using quark/gluon-enriched subsamples defined by the jet pseudorapidity. Differences in tagging efficiency between data and simulation are provided for jets with transverse momentum between 500 GeV and 2 TeV and for multiple tagger working points