Ruling out thermal dark matter with a black hole induced spiky profile in the M87 galaxy
Applying a random encounter model to estimate lion density from camera traps in Serengeti National Park, Tanzania
Abstract:
The random encounter model (REM) is a novel method for estimating animal density from camera trap data without the need for individual recognition. It has never been used to estimate the density of large carnivore species, despite these being the focus of most camera trap studies worldwide. In this context, we applied the REM to estimate the density of female lions (Panthera leo) from camera traps implemented in Serengeti National Park, Tanzania, comparing estimates to reference values derived from pride census data. More specifically, we attempted to account for bias resulting from non-random camera placement at lion resting sites under isolated trees by comparing estimates derived from night versus day photographs, between dry and wet seasons, and between habitats that differ in their amount of tree cover. Overall, we recorded 169 and 163 independent photographic events of female lions from 7,608 and 12,137 camera trap days carried out in the dry season of 2010 and the wet season of 2011, respectively. Although all REM models considered over-estimated female lion density, models that considered only night-time events resulted in estimates that were much less biased relative to those based on all photographic events. We conclude that restricting REM estimation to periods and habitats in which animal movement is more likely to be random with respect to cameras can help reduce bias in estimates of density for female Serengeti lions. We highlight that accurate REM estimates will nonetheless be dependent on reliable measures of average speed of animal movement and camera detection zone dimensions.CFHTLenS: weak lensing calibrated scaling relations for low-mass clusters of galaxies
The morphology of the Anomalous Microwave Emission in the Planck 2015 data release
Galaxy merger histories and the role of merging in driving star formation at z > 1
Abstract:
We use Horizon-AGN, a hydrodynamical cosmological simulation, to explore the role of mergers in the evolution of massive (M* > 1010 M⊙) galaxies around the epoch of peak cosmic star formation (1 < z < 4). The fraction of massive galaxies in major mergers (mass ratio R < 4: 1) is around 3 per cent, a factor of ∼2.5 lower than minor mergers (4: 1 < R < 10: 1) at these epochs, with no trend with redshift. At z ∼ 1, around a third of massive galaxies have undergone a major merger, while all remaining systems have undergone a minor merger. While almost all major mergers at z > 3 are ‘blue’ (i.e. have significant associated star formation), the proportion of ‘red’ mergers increases rapidly at z < 2, with most merging systems at z ∼ 1.5 producing remnants that are red in rest-frame UV–optical colours. The star formation enhancement during major mergers is mild (∼20–40 per cent) which, together with the low incidence of such events, implies that this process is not a significant driver of early stellar mass growth. Mergers (R < 10: 1) host around a quarter of the total star formation budget in this redshift range, with major mergers hosting around two-thirds of this contribution. Notwithstanding their central importance to the standard Λ cold dark matter paradigm, mergers are minority players in driving star formation at the epochs where the bulk of today's stellar mass was formed.