Timescales of Quartz Crystallization and the Longevity of the Bishop Giant Magma Body

Supereruptions violently transfer huge amounts (100 s–1000 s km3) of magma to the surface in a matter of days and testify to the existence of giant pools of magma at depth. The longevity of these giant magma bodies is of significant scientific and societal interest. Radiometric data on whole rocks, glasses, feldspar and zircon crystals have been used to suggest that the Bishop Tuff giant magma body, which erupted ∼760,000 years ago and created the Long Valley caldera (California), was long-lived (>100,000 years) and evolved rather slowly. In this work, we present four lines of evidence to constrain the timescales of crystallization of the Bishop magma body: (1) quartz residence times based on diffusional relaxation of Ti profiles, (2) quartz residence times based on the kinetics of faceting of melt inclusions, (3) quartz and feldspar crystallization times derived using quartz+feldspar crystal size distributions, and (4) timescales of cooling and crystallization based on thermodynamic and heat flow modeling. All of our estimates suggest quartz crystallization on timescales of <10,000 years, more typically within 500–3,000 years before eruption. We conclude that large-volume, crystal-poor magma bodies are ephemeral features that, once established, evolve on millennial timescales. We also suggest that zircon crystals, rather than recording the timescales of crystallization of a large pool of crystal-poor magma, record the extended periods of time necessary for maturation of the crust and establishment of these giant magma bodies

Effects of structural and functional habitat gaps on breeding woodland birds: working harder for less

The effects of habitat gaps on breeding success and parental daily energy expenditure (DEE) were investigated in great tits (Parus major) and blue tits (Cyanistes caeruleus) in urban parkland (Cardiff, UK) compared with birds in deciduous woodland (eastern England, UK). Tree canopy height, the percentage of gap in the canopy and the percentage of oak (in the wood only) within a 30 m radius of nest boxes were obtained from airborne remote-sensed data. Breeding success was monitored and parental DEE (great tits: both habitats; blue tits: park only) was measured using doubly labelled water in birds feeding young. In the park, mean (± SD) tree height (7.5 ± 4.7 m) was less than in the wood (10.6 ± 4.5 m), but the incidence of gaps (32.7 ± 22.6%) was greater (9.2 ± 14.7%). Great tits and blue tits both reared fewer young in the park and chick body mass was also reduced in park-reared great tits. Park great tits had a higher DEE (86.3 ± 12.3 kJ day-1) than those in the wood (78.0 ± 11.7 kJ day-1) and, because of smaller brood sizes, worked about 64% harder for each chick reared. Tits in the park with more than about 35% gap around their boxes had higher DEEs than the average for the habitat. In the wood, great tits with less oak around their boxes worked harder than average. Thus structural gaps, and functional gaps generated by variation in the quality of foraging habitat, increased the costs of rearing young

Patient-specific computational modeling of cortical spreading depression via diffusion tensor imaging

Cortical spreading depression, a depolarization wave originating in the visual cortex and traveling towards the frontal lobe, is commonly accepted as a correlate of migraine visual aura. As of today, little is known about the mechanisms that can trigger or stop such phenomenon. However, the complex and highly individual characteristics of the brain cortex suggest that the geometry might have a significant impact in supporting or contrasting the propagation of cortical spreading depression. Accurate patient-specific computational models are fundamental to cope with the high variability in cortical geometries among individuals, but also with the conduction anisotropy induced in a given cortex by the complex neuronal organisation in the grey matter. In this paper, we integrate a distributed model for extracellular potassium concentration with patient-specific diffusivity tensors derived locally from diffusion tensor imaging data

Introduction and summary

Due to copyright restrictions, the access to the full text of this article is only available via subscription.Control and optimization of dynamical systems in the presence of stochastic uncertainty is a mature field with a large range of applications. A comprehensive treatment of such problems can be found in excellent books and other resources including [7, 16, 29, 68, 84, 95, 104], and [6]. To date, there exist a nearly complete theory regarding the existence and structure of optimal solutions under various formulations as well as computational methods to obtain such optimal solutions for problems with finite state and control spaces. However, there still exist substantial computational challenges involving problems with large state and action spaces, such as standard Borel spaces. For such state and action spaces, obtaining optimal policies is in general computationally infeasible