Impact of small-scale vegetation structure on tephra layer preservation.

The factors that influence tephra layer taphonomy are poorly understood, but vegetation cover is likely to play a role in the preservation of terrestrial tephra deposits. The impact of vegetation on tephra layer preservation is important because: 1) the morphology of tephra layers could record key characteristics of past land surfaces and 2) vegetation-driven variability in tephra thickness could affect attempts to infer eruption and dispersion parameters. We investigated small- (metre-) scale interactions between vegetation and a thin (<10 cm), recent tephra layer. We conducted surveys of vegetation structure and tephra thickness at two locations which received a similar tephra deposit, but had contrasting vegetation cover (moss vs shrub). The tephra layer was thicker and less variable under shrub cover. Vegetation structure and layer thickness were correlated on the moss site but not under shrub cover, where the canopy reduced the influence of understory vegetation on layer morphology. Our results show that vegetation structure can influence tephra layer thickness on both small and medium (site) scales. These findings suggest that some tephra layers may carry a signal of past vegetation cover. They also have implications for the sampling effort required to reliably estimate the parameters of initial deposits

Emergence of the subtropical sea urchin Centrostephanus rodgersii as a threat to kelp forest ecosystems in northern New Zealand

Marine protected areas have long been proposed as a key tool to restore lost food web interactions and increase the resilience of ecosystems to climate change impacts. However, a changing climate can result in the arrival of new species or differentially affect native species, which can alter ecosystem dynamics and make it difficult to predict how ecosystems will respond to protection. The long-spined sea urchin Centrostephanus rodgersii is a well-known range extender with large impacts on kelp forest ecosystems, yet its response to warming and long-term marine protection has not been examined within its native range. We examine long-term trends in C. rodgersii and the endemic sea urchin Evechinus chloroticus following no-take protection within the Poor Knights Islands Marine Reserve, in northeastern Aotearoa New Zealand, from 1999-2022, and compare with population trends at an unprotected island group. Within the marine reserve, E. chloroticus decreased in density, became more cryptic, and urchin barrens associated with this species largely disappeared, whereas in fished areas, populations and extent of barrens remained stable. This differing response between the reserve and fished location is consistent with a top-down effect and greater abundance of predatory fish in the reserve. In contrast, the subtropical sea urchin C. rodgersii increased in abundance by 9.3 times in the Poor Knights Island Marine Reserve and 4.3 times at the fished location, with areas of urchin barrens associated with this species developing at both locations. This increase coincides with substantial warming over the monitoring period (0.25°C decade-1) and low numbers of key predators (rock lobster) at both reserve and fished locations. This highlights the emerging threat of C. rodgersii to rocky reefs in the region and how marine protection alone may not increase resilience to this threat. This suggests multifaceted management approaches are needed to mitigate the impacts of emerging pest species and increase the resilience of temperate reef ecosystems in a warming climate

The Algorithm Steering and Trigger Decision mechanism of the ATLAS High Level Trigger

Given the extremely high output rate foreseen at LHC and the general-purpose nature of ATLAS experiment, an efficient and flexible way to select events in the High Level Trigger is needed. An extremely flexible solution is proposed that allows for early rejection of unwanted events and an easily configurable way to choose algorithms and to specify the criteria for trigger decisions. It is implemented in the standard ATLAS object-oriented software framework, Athena. The early rejection is achieved by breaking the decision process down into sequential steps. The configuration of each step defines sequences of algorithms which should be used to process the data, and 'trigger menus' that define which physics signatures must be satisfied to continue on to the next step, and ultimately to accept the event. A navigation system has been built on top of the standard Athena transient store (StoreGate) to link the event data together in a tree-like structure. This is fundamental to the seeding mechanism, by which data from one step is presented to the next. The design makes it straightforward to utilize existing off-line reconstruction data classes and algorithms when they are suitableComment: Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 8 pages, PDF, PSN TUGT00

Exploiting lung adaptation and phage steering to clear pan-resistant Pseudomonas aeruginosa infections in vivo

Pseudomonas aeruginosa is a major nosocomial pathogen that causes severe disease including sepsis. Carbapenem-resistant P. aeruginosa is recognised by the World Health Organisation as a priority 1 pathogen, with urgent need for new therapeutics. As such, there is renewed interest in using bacteriophages as a therapeutic. However, the dynamics of treating pan-resistant P. aeruginosa with phage in vivo are poorly understood. Using a pan-resistant P. aeruginosa in vivo infection model, phage therapy displays strong therapeutic potential, clearing infection from the blood, kidneys, and spleen. Remaining bacteria in the lungs and liver displays phage resistance due to limiting phage adsorption. Yet, resistance to phage results in re-sensitisation to a wide range of antibiotics. In this work, we use phage steering in vivo, pre-exposing a pan resistant P. aeruginosa infection with a phage cocktail to re-sensitise bacteria to antibiotics, clearing the infection from all organs

Polarimetry and the Long Awaited Superoutburst of BZ UMa

BZ UMa is a cataclysmic variable star whose specific classification has eluded researchers since its discovery in 1968. It has outburst and spectral properties consistent with both U Gem class dwarf novae and intermediate polars. We present new photometric and polarimetric measurements of recent outbursts, including the first detected superoutburst of the system. Statistical analysis of these and archival data from outbursts over the past 40 years present a case for BZ UMa as a non-magnetic, U Gem class, SU-UMa subclass dwarf novae.Comment: Accepted by PASP for the November, 2009 issu

Precision luminosity measurements at LHCb

Measuring cross-sections at the LHC requires the luminosity to be determined accurately at each centre-of-mass energy √s. In this paper results are reported from the luminosity calibrations carried out at the LHC interaction point 8 with the LHCb detector for √s = 2.76, 7 and 8 TeV (proton-proton collisions) and for √sNN = 5 TeV (proton-lead collisions). Both the "van der Meer scan" and "beam-gas imaging" luminosity calibration methods were employed. It is observed that the beam density profile cannot always be described by a function that is factorizable in the two transverse coordinates. The introduction of a two-dimensional description of the beams improves significantly the consistency of the results. For proton-proton interactions at √s = 8 TeV a relative precision of the luminosity calibration of 1.47% is obtained using van der Meer scans and 1.43% using beam-gas imaging, resulting in a combined precision of 1.12%. Applying the calibration to the full data set determines the luminosity with a precision of 1.16%. This represents the most precise luminosity measurement achieved so far at a bunched-beam hadron collider

Performance of the LHCb vertex locator

The Vertex Locator (VELO) is a silicon microstrip detector that surrounds the proton-proton interaction region in the LHCb experiment. The performance of the detector during the first years of its physics operation is reviewed. The system is operated in vacuum, uses a bi-phase CO2 cooling system, and the sensors are moved to 7 mm from the LHC beam for physics data taking. The performance and stability of these characteristic features of the detector are described, and details of the material budget are given. The calibration of the timing and the data processing algorithms that are implemented in FPGAs are described. The system performance is fully characterised. The sensors have a signal to noise ratio of approximately 20 and a best hit resolution of 4 μm is achieved at the optimal track angle. The typical detector occupancy for minimum bias events in standard operating conditions in 2011 is around 0.5%, and the detector has less than 1% of faulty strips. The proximity of the detector to the beam means that the inner regions of the n+-on-n sensors have undergone space-charge sign inversion due to radiation damage. The VELO performance parameters that drive the experiment's physics sensitivity are also given. The track finding efficiency of the VELO is typically above 98% and the modules have been aligned to a precision of 1 μm for translations in the plane transverse to the beam. A primary vertex resolution of 13 μm in the transverse plane and 71 μm along the beam axis is achieved for vertices with 25 tracks. An impact parameter resolution of less than 35 μm is achieved for particles with transverse momentum greater than 1 GeV/c