Understanding macroalgal dispersal in a complex hydrodynamic environment: a combined population genetic and physical modelling approach

Gene flow in macroalgal populations can be strongly influenced by spore or gamete dispersal. This, in turn, is influenced by a convolution of the effects of current flow and specific plant reproductive strategies. Although several studies have demonstrated genetic variability in macroalgal populations over a wide range of spatial scales, the associated current data have generally been poorly resolved spatially and temporally. In this study, we used a combination of population genetic analyses and high-resolution hydrodynamic modelling to investigate potential connectivity between populations of the kelp Laminaria digitata in the Strangford Narrows, a narrow channel characterized by strong currents linking the large semi-enclosed sea lough, Strangford Lough, to the Irish Sea. Levels of genetic structuring based on six microsatellite markers were very low, indicating high levels of gene flow and a pattern of isolation-by-distance, where populations are more likely to exchange migrants with geographically proximal populations, but with occasional long-distance dispersal. This was confirmed by the particle tracking model, which showed that, while the majority of spores settle near the release site, there is potential for dispersal over several kilometres. This combined population genetic and modelling approach suggests that the complex hydrodynamic environment at the entrance to Strangford Lough can facilitate dispersal on a scale exceeding that proposed for L. digitata in particular, and the majority of macroalgae in general. The study demonstrates the potential of integrated physical–biological approaches for the prediction of ecological changes resulting from factors such as anthropogenically induced coastal zone changes.

Surveillance of Non melanoma Skin Cancer Incidence Rates in Kidney Transplant Recipients in Ireland

Background: The incidence of nonmelanomatous skin cancer (NMSC) is substantially higher among renal transplant recipients (RTRs) than in the general population. With a growing RTR population, a robust method for monitoring skin cancer rates in this population is required.
Methods: A modeling approach was used to estimate the trends in NMSC rates that adjusted for changes in the RTR population (sex and age), calendar time, the duration of posttransplant follow-up, and background population NMSC incidence rates. RTR databases in both Northern Ireland (NI) and the Republic of Ireland (ROI) were linked to their respective cancer registries for diagnosis of NMSC, mainly squamous cell carcinoma (SCC) and basal cell carcinoma (BCC).
Results: RTRs in the ROI had three times the incidence (P<0.001) of NMSC compared with NI. There was a decline (P<0.001) in NMSC 10-year cumulative incidence rate in RTRs over the period 1994–2009, which was driven by reductions in both SCC and BCC incidence rates. Nevertheless, there was an increase in the incidence of NMSC with time since transplantation. The observed graft survival was higher in ROI than NI (P<0.05) from 1994–2004. The overall patient survival of RTRs was similar in NI and ROI.
Conclusion: Appropriate modeling of incidence trends in NMSC among RTRs is a valuable surveillance exercise for assessing the impact of change in clinical practices over time on the incidence rates of skin cancer in RTRs. It can form the basis of further research into unexplained regional variations in NMSC incidence.

Forecasting Death Rates Using Exogenous Determinants

Mortality models used for forecasting are predominantly based on the statistical properties of time series and do not generally incorporate an understanding of the forces driving secular trends. This paper addresses three research questions: Can the factors found in stochastic mortality-forecasting models be associated with real-world trends in health-related variables? Does inclusion of health-related factors in models improve forecasts? Do resulting models give better forecasts than existing stochastic mortality models? We consider whether the space spanned by the latent factor structure in mortality data can be adequately described by developments in gross domestic product, health expenditure and lifestyle-related risk factors using statistical techniques developed in macroeconomics and finance. These covariates are then shown to improve forecasts when incorporated into a Bayesian hierarchical model. Results are comparable or better than benchmark stochastic mortality models.

On transition rates in surface hopping

Trajectory surface hopping (TSH) is one of the most widely used quantum-classical algorithms for nonadiabatic molecular dynamics. Despite its empirical effectiveness and popularity, a rigorous derivation of TSH as the classical limit of a combined quantum electron-nuclear dynamics is still missing. In this work, we aim to elucidate the theoretical basis for the widely used hopping rules. Naturally, we concentrate thereby on the formal aspects of the TSH. Using a Gaussian wave packet limit, we derive the transition rates governing the hopping process at a simple avoided level crossing. In this derivation, which gives insight into the physics underlying the hopping process, some essential features of the standard TSH algorithm are retrieved, namely (i) non-zero electronic transition rate ("hopping probability") at avoided crossings; (ii) rescaling of the nuclear velocities to conserve total energy; (iii) electronic transition rates linear in the nonadiabatic coupling vectors. The well-known Landau-Zener model is then used for illustration. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4770280]

The effect of helium accretion efficiency on rates of Type Ia supernovae: Double detonations in accreting binaries

he double-detonation explosion scenario of Type Ia supernovae (SNe Ia) has gained increased support from the SN Ia community as a viable progenitor model, making it a promising candidate alongside the well-known single degenerate and double degenerate scenarios. We present delay times of double-detonation SNe, in which a sub-Chandrasekhar mass carbon–oxygen white dwarf (WD) accretes non-dynamically from a helium-rich companion. One of the main uncertainties in quantifying SN rates from double detonations is the (assumed) retention efficiency of He-rich matter. Therefore, we implement a new prescription for the treatment of accretion/accumulation of He-rich matter on WDs. In addition, we test how the results change depending on which criteria are assumed to lead to a detonation in the helium shell. In comparing the results to our standard case (Ruiter et al.), we find that regardless of the adopted He accretion prescription, the SN rates are reduced by only ∼25 per cent if low-mass He shells (≲0.05 M⊙) are sufficient to trigger the detonations. If more massive (0.1 M⊙) shells are needed, the rates decrease by 85 per cent and the delay time distribution is significantly changed in the new accretion model – only SNe with prompt (<500 Myr) delay times are produced. Since theoretical arguments favour low-mass He shells for normal double-detonation SNe, we conclude that the rates from double detonations are likely to be high, and should not critically depend on the adopted prescription for accretion of He.

Seasonal differences in the effects of oscillatory and uni-directional flow on the growth and nitrate-uptake rates of juvenile Laminaria digitata (Phaeophyceae)

The influence of oscillatory versus unidirectional flow on the growth and nitrate-uptake rates of juvenile kelp, Laminaria digitata, was determined seasonally in experimental treatments that simulated as closely as possible natural environmental conditions. In winter, regardless of flow condition (oscillatory and unidirectional) or water velocity, no influence of water motion was observed on the growth rate of L. digitata. In summer, when ambient nitrate concentrations were low, increased water motion enhanced macroalgal growth, which is assumed to be related to an increase in the rate of supply of nutrients to the blade surface. Nitrate-uptake rates were significantly influenced by water motion and season. Lowest nitrate-uptake rates were observed for velocities <5 cm · s−1 and nitrate-uptake rates increased by 20%–50% under oscillatory motion compared to unidirectional flow at the same average speed. These data further suggested that the diffusion boundary layer played a significant role in influencing nitrate-uptake rates. However, while increased nitrate-uptake in oscillatory flow was clear, this was not reflected in growth rates and further work is required to understand the disconnection of nitrate-uptake and growth by L. digitata in oscillatory flow. The data obtained support those from related field-based studies, which suggest that in summer, when insufficient nitrogen is available in the water to saturate metabolic demand, the growth rate of kelps will be influenced by water motion restricting mass transfer of nitrogen.

Reducible Diffusions with Time-Varying Transformations with Application to Short-Term Interest Rates

Reducible diffusions (RDs) are nonlinear transformations of analytically solvable Basic Diffusions (BDs). Hence, by construction RDs are analytically tractable and flexible diffusion processes. Existing literature on RDs has mostly focused on time-homogeneous transformations, which to a significant extent fail to explore the full potential of RDs from both theoretical and practical points of view. In this paper, we propose flexible and economically justifiable time variations to the transformations of RDs. Concentrating on the Constant Elasticity Variance (CEV) RDs, we consider nonlinear dynamics for our time-varying transformations with both deterministic and stochastic designs. Such time variations can greatly enhance the flexibility of RDs while maintaining sufficient tractability of the resulting models. In the meantime, our modeling approach enjoys the benefits of classical inferential techniques such as the Maximum Likelihood (ML). Our application to the UK and the US short-term interest rates suggests that from an empirical point of view time-varying transformations are highly relevant and statistically significant. We expect that the proposed models can describe more truthfully the dynamic time-varying behavior of economic and financial variables and potentially improve out-of-sample forecasts significantly.

Historical data reveal power-law dispersal patterns of invasive aquatic species

Understanding how invasive species spread is of particular concern in the current era of globalisation and rapid environmental change. The occurrence of super-diffusive movements within the context of Lévy flights has been discussed with respect to particle physics, human movements, microzooplankton, disease spread in global epidemiology and animal foraging behaviour. Super-diffusive movements provide a theoretical explanation for the rapid spread of organisms and disease, but their applicability to empirical data on the historic spread of organisms has rarely been tested. This study focuses on the role of long-distance dispersal in the invasion dynamics of aquatic invasive species across three contrasting areas and spatial scales: open ocean (north-east Atlantic), enclosed sea (Mediterranean) and an island environment (Ireland). Study species included five freshwater plant species, Azolla filiculoides, Elodea canadensis, Lagarosiphon major, Elodea nuttallii and Lemna minuta; and ten species of marine algae, Asparagopsis armata, Antithamnionella elegans, Antithamnionella ternifolia, Codium fragile, Colpomenia peregrina, Caulerpa taxifolia, Dasysiphonia sp., Sargassum muticum, Undaria pinnatifida and Womersleyella setacea. A simulation model is constructed to show the validity of using historical data to reconstruct dispersal kernels. Lévy movement patterns similar to those previously observed in humans and wild animals are evident in the re-constructed dispersal pattern of invasive aquatic species. Such patterns may be widespread among invasive species and could be exacerbated by further development of trade networks, human travel and environmental change. These findings have implications for our ability to predict and manage future invasions, and improve our understanding of the potential for spread of organisms including infectious diseases, plant pests and genetically modified organisms.

Low rates of Pseudomonas aeruginosa misidentification in isolates from cystic fibrosis patients

Pseudomonas aeruginosa is an important cause of pulmonary infection in cystic fibrosis (CF). Its correct identification ensures effective patient management and infection control strategies. However, little is known about how often CF sputum isolates are falsely identified as P. aeruginosa. We used P. aeruginosa-specific duplex real-time PCR assays to determine if 2,267 P. aeruginosa sputum isolates from 561 CF patients were correctly identified by 17 Australian clinical microbiology laboratories. Misidentified isolates underwent further phenotypic tests, amplified rRNA gene restriction analysis, and partial 16S rRNA gene sequence analysis. Participating laboratories were surveyed on how they identified P. aeruginosa from CF sputum. Overall, 2,214 (97.7%) isolates from 531 (94.7%) CF patients were correctly identified as P. aeruginosa. Further testing with the API 20NE kit correctly identified only 34 (59%) of the misidentified isolates. Twelve (40%) patients had previously grown the misidentified species in their sputum. Achromobacter xylosoxidans (n = 21), Stenotrophomonas maltophilia (n = 15), and Inquilinus limosus (n = 4) were the species most commonly misidentified as P. aeruginosa. Overall, there were very low rates of P. aeruginosa misidentification among isolates from a broad cross section of Australian CF patients. Additional improvements are possible by undertaking a culture history review, noting colonial morphology, and performing stringent oxidase, DNase, and colistin susceptibility testing for all presumptive P. aeruginosa isolates. Isolates exhibiting atypical phenotypic features should be evaluated further by additional phenotypic or genotypic identification techniques.

Char oxidation of torrefied biomass at high temperatures and high heating rates

The char oxidation of a torrefied biomass and its parent material was carried out in an isothermal plug flow reactor (IPFR), which is able to rapidly heat the biomass particles to a maximum temperature of 1400 °C at a heating rate of 104 °C/s, similar to the real conditions found in power plant furnaces. During each char oxidation test, the residues of biomass particles were collected and analyzed to determine the weight loss based on the ash tracer method. According to the experimental results, it can be concluded that chars produced from a torrefied biomass are less reactive than the ones produced, under the same conditions, from its raw material. The apparent kinetics of the torrefied biomass and its parent material are determined by minimizing the difference between the modeled and the experimental results. The predicted weight loss during char oxidation, using the determined kinetics, agrees well with experimental results

Sediment accumulation rates in subarctic lakes: insights into age-depth modeling from 22 dated lake records from the Northwest Territories, Canada

Age-depth modeling using Bayesian statistics requires well-informed prior information about the behavior of sediment accumulation. Here we present average sediment accumulation rates (represented as deposition times, DT, in yr/cm) for lakes in an Arctic setting, and we examine the variability across space (intra- and inter-lake) and time (late Holocene). The dataset includes over 100 radiocarbon dates, primarily on bulk sediment, from 22 sediment cores obtained from 18 lakes spanning the boreal to tundra ecotone gradients in subarctic Canada. There are four to twenty-five radiocarbon dates per core, depending on the length and character of the sediment records. Deposition times were calculated at 100-year intervals from age-depth models constructed using the ‘classical’ age-depth modeling software Clam. Lakes in boreal settings have the most rapid accumulation (mean DT 20 ± 10 years), whereas lakes in tundra settings accumulate at moderate (mean DT 70 ± 10 years) to very slow rates, (>100 yr/cm). Many of the age-depth models demonstrate fluctuations in accumulation that coincide with lake evolution and post-glacial climate change. Ten of our sediment cores yielded sediments as old as c. 9,000 cal BP (BP = years before AD 1950). From between c. 9,000 cal BP and c. 6,000 cal BP, sediment accumulation was relatively rapid (DT of 20 to 60 yr/cm). Accumulation slowed between c. 5,500 and c. 4,000 cal BP as vegetation expanded northward in response to warming. A short period of rapid accumulation occurred near 1,200 cal BP at three lakes. Our research will help inform priors in Bayesian age modeling.