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Catastrophic seismic events off the coast of Chile and the tsunami caused by them on April 1, 2014 north of Iquique with a magnitude of 8.2 are analyzed. Possible causes of moderate tsunami strength at a sufficiently large earthquake magnitude have been investigated. Within the framework of the keyboard block model of the subduction zone, based on the data on the localization of the main shock and aftershocks, the structure of the seismic source was selected. It was found that the computation results for the tsunami run-up noticeably exceed the observational data, which may be associated with the complex dynamics of the source. Comparison with the data of computations of other authors is performed.

The detection of a new HLB epidemic in a planting often occurs when the disease has already reached high incidence.  This is problematic and once the epidemic has become established it is difficult to recover the economic productivity of the grove.  However, if new epidemics can be detected early enough then more can be done to control the disease.  Early detection requires that surveillance surveys be in place before the disease arrives; that is, a number of trees within a healthy grove should be inspected at regular intervals for symptoms of HLB.  Exactly how many trees should be surveyed and how frequently this should be done is a non-trivial problem and one that has not previously been addressed in plant pathology.  We present a theoretical method that relates the dynamics of an invading epidemic to the dynamics of a monitoring program.  The method determines exactly how an early detection survey should be designed in order to achieve a high probability of detecting an epidemic whilst it is at an early stage.  We compare the theoretical method to a complex simulation model which replicates the spatial and temporal dynamics of HLB in the field.  By running the model thousands of times we can make probabilistic predictions on early detection survey design that can be directly compared with the theoretical method.  We find striking similarities between the simple theoretical and more complicated simulation approach that enables us to make valuable new insights as well as deliver methods for transfer into practice.

We report on the small-scale (0.5 < r < 40 h-1 Mpc) clustering of 78 895 massive (M 1011.3M) galaxies at 0.2 < z< 0.4 from the first two years of data from the Baryon Oscillation Spectroscopic Survey (BOSS), to be released as part of Sloan Digital Sky Survey (SDSS) Data Release 9 (DR9). We describe the sample selection, basic properties of the galaxies and caveats for working with the data. We calculate the real- and redshift-space twopoint correlation functions of these galaxies, fit these measurements using halo occupation distribution (HOD) modelling within dark matter cosmological simulations, and estimate the errors using mock catalogues. These galaxies lie in massive haloes, with a mean halo mass of 5.2 1013 h-1M, a large-scale bias of ~2.0 and a satellite fraction of 12 ± 2 per cent. Thus, these galaxies occupy haloes with average masses in between those of the higher redshift BOSS CMASS sample and the original SDSS I/II luminous red galaxy sample © 2012 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society © doi:10.1093/mnras/sts314.

Different theoretical methodologies lead to order-of-magnitude variations in predicted galaxy-galaxy merger rates. We examine how this arises and quantify the dominant uncertainties. Modeling of dark matter and galaxy inspiral/merger times contribute factor of ∼2 uncertainties. Different estimates of the halo-halo merger rate, the subhalo "destruction" rate, and the halo merger rate with some dynamical friction time delay for galaxy-galaxy mergers, agree to within this factor of ∼2, provided proper care is taken to define mergers consistently. There are some caveats: if halo/subhalo masses are not appropriately defined the major-merger rate can be dramatically suppressed, and in models with "orphan" galaxies and under-resolved subhalos the merger timescale can be severely overestimated. The dominant differences in galaxy-galaxy merger rates between models owe to the treatment of the baryonic physics. Cosmological hydrodynamic simulations without strong feedback and some older semianalytic models (SAMs), with known discrepancies in mass functions, can be biased by large factors (∼5) in predicted merger rates. However, provided that models yield a reasonable match to the total galaxy mass function, the differences in properties of central galaxies are sufficiently small to alone contribute small (factor of ∼1.5) additional systematics to merger rate predictions. But variations in the baryonic physics of satellite galaxies in models can also have a dramatic effect on merger rates. The well-known problem of satellite "over-quenching" in most current SAMs-whereby SAM satellite populations are too efficiently stripped of their gas-could lead to order-of-magnitude under-estimates of merger rates for low-mass, gas-rich galaxies. Models in which the masses of satellites are fixed by observations (or SAMs adjusted to resolve this "over-quenching") tend to predict higher merger rates, but with factor of ∼2 uncertainties stemming from the uncertainty in those observations. The choice of mass used to define "major" and "minor" mergers also matters: stellar-stellar major mergers can be more or less abundant than halo-halo major mergers by an order of magnitude. At low masses, most true major mergers (mass ratio defined in terms of their baryonic or dynamical mass) will appear to be minor mergers in their stellar mass ratio-observations and models using just stellar criteria could underestimate major-merger rates by factors of ∼3-5. We discuss the uncertainties in relating any merger rate to spheroid formation (in observations or theory): in order to achieve better than factor of ∼3 accuracy, it is necessary to account for the distribution of merger orbital parameters, gas fractions, and the full efficiency of merger-induced effects as a function of mass ratio. © 2010. The American Astronomical Society. All rights reserved. Printed in the U.S.A.

Large-magnitude earthquakes in northern Chile and southern Peru occur every 108 years on average. It should be noted that over 143 years since the catastrophic earthquake of May 9, 1877, any similar events were completely absent. In 2007, a 7.7 Mw earthquake occurred near Tocopilla, and in 2014 a catastrophic M = 8.1 earthquake hit Pisagua. It is believed that only part of the energy accumulated over 143 years has been released during those events, while most of it is yet to be released. Thus, we can conclude that a serious tsunami hazard exists for all coastal cities of southern Peru and northern Chile. In this paper, on the basis of the available historical data and geodynamic studies, numerical simulation of the historical catastrophic earthquake and tsunami of May 9, 1877 is carried out assuming the blockwise earthquake source configurations. We implemented 23 simulation scenarios for different kinematic behavior patterns of such a source, sequentially updating the source fragmentation to reduce the misfit between the simulated and observed wave height data. Using the proposed methodology, for each scenario, the generation of a tsunami source is simulated and the computation of wave fields up to the 5-m isobath is carried out. The results obtained are compared with historical data. Analysis of the entire set of simulated earthquake scenarios makes it possible to choose a tsunamigenic earthquake scenario with the most adequate characteristics of tsunami waves in the coastal zone. [ABSTRACT FROM AUTHOR]