Effects of Season of Burning on the Microenvironment of Fescue Prairie in Central Saskatchewan

The microenvironmental effects of spring, summer and autumn burns were investigated for a small area of fescue prairie in Saskatchewan over two growing seasons. Maximum fire temperature in all burns exceeded 300°C at a height of 5-10 cm in the canopy. At a depth of 1 cm in the soil, temperature increased to 40°C during the summer burn, but was unaffected by burns at other seasons. Spring-burned grasses recovered to the same height as the unburned control plot by the end of the first summer. Grass height was similar in all plots by the end of the second growing season, but aboveground biomass in all burned plots was about half that of the control. Graminoid leaf area index at the end of the second growing season ranged from 0.65 in the control plot to 0.27 in the autumn burn. Surface albedos dropped to about 0.03 immediately after burning and took about 3 months to return to the pre-burn values near 0.20. By mid-June of the second year, albedos were similar in all plots. Soil temperatures at 50 cm depth in the burned plots were higher than in the control during the first summer and lower during the winter. The greatest winter snowpack (73 mm water equivalent) accumulated in the control, compared to 48, 35 and 25 mm in the spring, summer and autumn burned plots, respectively. In the first growing season the greatest demand for water occurred in the spring plot followed by the summer, control and autumn plots. In the second season water demand did not differ significantly among plots, reflecting the similarities in plant cover. The microenvironmental effects of a single burning episode in fescue prairie disappear rather quickly, so that there is little long-term impact on the vegetation

Spatially embedded random networks

Many real-world networks analyzed in modern network theory have a natural spatial element; e.g., the Internet, social networks, neural networks, etc. Yet, aside from a comparatively small number of somewhat specialized and domain-specific studies, the spatial element is mostly ignored and, in particular, its relation to network structure disregarded. In this paper we introduce a model framework to analyze the mediation of network structure by spatial embedding; specifically, we model connectivity as dependent on the distance between network nodes. Our spatially embedded random networks construction is not primarily intended as an accurate model of any specific class of real-world networks, but rather to gain intuition for the effects of spatial embedding on network structure; nevertheless we are able to demonstrate, in a quite general setting, some constraints of spatial embedding on connectivity such as the effects of spatial symmetry, conditions for scale free degree distributions and the existence of small-world spatial networks. We also derive some standard structural statistics for spatially embedded networks and illustrate the application of our model framework with concrete examples

Simulation of truncated normal variables

We provide in this paper simulation algorithms for one-sided and two-sided truncated normal distributions. These algorithms are then used to simulate multivariate normal variables with restricted parameter space for any covariance structure.Comment: This 1992 paper appeared in 1995 in Statistics and Computing and the gist of it is contained in Monte Carlo Statistical Methods (2004), but I receive weekly requests for reprints so here it is

Using Markov chain Monte Carlo methods for estimating parameters with gravitational radiation data

We present a Bayesian approach to the problem of determining parameters for coalescing binary systems observed with laser interferometric detectors. By applying a Markov Chain Monte Carlo (MCMC) algorithm, specifically the Gibbs sampler, we demonstrate the potential that MCMC techniques may hold for the computation of posterior distributions of parameters of the binary system that created the gravity radiation signal. We describe the use of the Gibbs sampler method, and present examples whereby signals are detected and analyzed from within noisy data.Comment: 21 pages, 10 figure

Markov basis and Groebner basis of Segre-Veronese configuration for testing independence in group-wise selections

We consider testing independence in group-wise selections with some restrictions on combinations of choices. We present models for frequency data of selections for which it is easy to perform conditional tests by Markov chain Monte Carlo (MCMC) methods. When the restrictions on the combinations can be described in terms of a Segre-Veronese configuration, an explicit form of a Gr\"obner basis consisting of moves of degree two is readily available for performing a Markov chain. We illustrate our setting with the National Center Test for university entrance examinations in Japan. We also apply our method to testing independence hypotheses involving genotypes at more than one locus or haplotypes of alleles on the same chromosome.Comment: 25 pages, 5 figure

Using Lean Quality Improvement Tools to Increase Delivery of Evidence-Based Tobacco Use Treatment in Hospitalized Neurosurgical Patients

Background Health care providers routinely undertreat tobacco dependence, indicating a need for innovative ways to increase delivery of evidence-based care. Lean, a set of quality improvement (QI) tools used increasingly in health care, can help streamline processes, create buy-in for use of evidence-based practices, and lead to the identification of solutions on the basis of a problem's root causes. To date, no published research has examined the use of Lean tools in tobacco dependence. A 12-month QI project using Lean tools was conducted to increase delivery of evidence-based tobacco use treatment (TUT) to hospitalized neurosurgical patients. Methods The study team developed a nicotine replacement therapy (NRT) and counseling protocol for neurosurgery inpatients who indicated current tobacco use and used Lean tools to increase protocol adherence. Rates of NRT prescription, referrals to counseling, and follow-up phone calls were compared pre- and postintervention. Secondary measures included patient satisfaction with intervention, quit rates, and reduction rates at 4 weeks postdischarge. Results Referrals to counseling doubled from 31.7% at baseline to 62.0% after implementation of the intervention, and rates of nicotine replacement therapy (NRT) prescriptions during hospitalization and at discharge increased from 15.3% to 28.5% and 9.0% to 19.3%, respectively. Follow-up phone call rates also dramatically increased. The majority of satisfaction survey respondents indicated that counseling had a positive or neutral impact on stress level and overall satisfaction. Conclusion Lean tools can dramatically increase use of evidence-based TUT in hospitalized patients. This project is easily replicable by professionals seeking to improve delivery of tobacco treatment. These findings may be particularly helpful to inpatient surgical departments that have traditionally been reticent to prescribe NRT

Anaerobic digestion of whole-crop winter wheat silage for renewable energy production

With biogas production expanding across Europe in response to renewable energy incentives, a wider variety of crops need to be considered as feedstock. Maize, the most commonly used crop at present, is not ideal in cooler, wetter regions, where higher energy yields per hectare might be achieved with other cereals. Winter wheat is a possible candidate because, under these conditions, it has a good biomass yield, can be ensiled, and can be used as a whole crop material. The results showed that, when harvested at the medium milk stage, the specific methane yield was 0.32 m3 CH4 kg–1 volatile solids added, equal to 73% of the measured calorific value. Using crop yield values for the north of England, a net energy yield of 146–155 GJ ha–1 year–1 could be achieved after taking into account both direct and indirect energy consumption in cultivation, processing through anaerobic digestion, and spreading digestate back to the land. The process showed some limitations, however: the relatively low density of the substrate made it difficult to mix the digester, and there was a buildup of soluble chemical oxygen demand, which represented a loss in methane potential and may also have led to biofoaming. The high nitrogen content of the wheat initially caused problems, but these could be overcome by acclimatization. A combination of these factors is likely to limit the loading that can be applied to the digester when using winter wheat as a substrat

Language and social/emotional problems identified at a universal developmental assessment at 30 months

Non peer reviewedPublisher PD