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Arat S.,VA Technology | Arat S.,Virginia Polytechnic Institute and State University | Bullerjahn G.S.,Bowling Green State University | Laubenbacher R.,University of Connecticut Health Center | Laubenbacher R.,The Jackson Laboratory
PLoS ONE | Year: 2015

Pseudomonas aeruginosa is a metabolically flexible member of the Gammaproteobacteria. Under anaerobic conditions and the presence of nitrate, P. aeruginosa can perform (complete) denitrification, a respiratory process of dissimilatory nitrate reduction to nitrogen gas via nitrite (NO2), nitric oxide (NO) and nitrous oxide (N2O). This study focuses on understanding the influence of environmental conditions on bacterial denitrification performance, using a mathematical model of a metabolic network in P. aeruginosa. To our knowledge, this is the first mathematical model of denitrification for this bacterium. Analysis of the longterm behavior of the network under changing concentration levels of oxygen (O2), nitrate (NO3), and phosphate (PO4) suggests that PO4 concentration strongly affects denitrification performance. The model provides three predictions on denitrification activity of P. aeruginosa under various environmental conditions, and these predictions are either experimentally validated or supported by pertinent biological literature. One motivation for this study is to capture the effect of PO4 on a denitrification metabolic network of P. aeruginosa in order to shed light on mechanisms for greenhouse gas N2O accumulation during seasonal oxygen depletion in aquatic environments such as Lake Erie (Laurentian Great Lakes, USA). Simulating the microbial production of greenhouse gases in anaerobic aquatic systems such as Lake Erie allows a deeper understanding of the contributing environmental effects that will inform studies on, and remediation strategies for, other hypoxic sites worldwide. © 2015 Arat et al. Source


Tirpak J.M.,Fordham University | Giuliano W.M.,University of Florida | Bittner S.,Blairs Valley Road | Edwards J.W.,University | And 3 more authors.
Forest Ecology and Management | Year: 2010

Ruffed grouse (Bonasa umbellus; hereafter grouse) populations in the central and southern Appalachians (CSA) are declining due to widespread maturation of forest cover. Effective management of this species requires a sex- and age-specific understanding of habitat preferences at multiple temporal and spatial scales. We used multivariate logistic regression models to compare habitat within 1440 grouse home ranges and 1400 equally sized buffered random points across 7 CSA study areas. On most sites, grouse home ranges were positively associated with roads and young forest (<20 years old). Sex and age status affected habitat preference. In general, males used younger forest than females, likely because of differences in habitat use during reproductive periods. Juveniles had fewer vegetation types preferred by adult grouse and more of the avoided vegetation types within their home ranges, indicative of competitive exclusion. Adult females had the greatest specificity and selectivity of habitat conditions within their home ranges. Habitat selection varied among seasons and years on most sites. Winter habitat use reflected behavior that maximized energy conservation, with open vegetation types avoided in the winter on the northernmost study areas, and topography important on all areas. Summer habitat selection reflected vegetation types associated with reproductive activities. Scale influenced habitat preference as well. Although roads and forest age predominantly influenced grouse home range location within the landscape, mesic forest types were most important in determining core area use within the home range. This was likely a result of increased food availability and favorable microclimate. Habitat management efforts should attempt to maintain ∼3-4% of the landscape in young forest cover (<20 years old), evenly distributed across management areas. Roads into these areas should be seeded as appropriate to enhance brood habitat and provide travel corridors connecting suitable forest stands. © 2010 Elsevier B.V. Source


Bumgardner M.,U.S. Department of Agriculture | Buehlmann U.,VA Technology
Wood and Fiber Science | Year: 2015

Small firms are a critical component of the secondary woodworking industry and are important to hardwood lumber demand in the US. Understanding managers' perceptions of competitiveness in these firms is important to those working with the industry to help maintain a viable wood manufacturing base. One area of interest relative to the overall business environment involves attribution: to what do managers attribute their firms' success? In this study, attribution theory was applied to a sample of secondary woodworking manufacturers to test for a "self-serving" attribution effect (ie success is caused by internal factors, whereas a lack of success is caused by external factors), which has been shown in some other industries. Also of interest was determining if the effect was amplified for small firms. The presence of an overall attribution effect among secondary woodworking manufacturers was generally supported, but little evidence was found of an effect related specifically to small firms. The presence of an overall attribution effect is discussed in terms of the implications for research and outreach directed toward the secondary woodworking industry. © 2015 by the Society of Wood Science and Technology. Source


Jan M.,CEA Saclay Nuclear Research Center | Zaourar L.,CEA Saclay Nuclear Research Center | Legout V.,VA Technology | Pautet L.,Telecom ParisTech
Ada User Journal | Year: 2014

Mixed Criticality helps reducing the impact of pessimistic evaluation of Worst Case Execution Time for real-time systems. This is achieved by hosting lowcriticality tasks on a same hardware architecture in addition to the classical high-critical tasks, when considering two-criticality levels. The Time-Triggered paradigm (TT) is a classical approach within industry to develop high-criticality tasks. Extending TT systems in order to integrate the support of MC scheduling therefore requires the generation of two schedule tables, one for each criticality level. However, a switch between the schedule tables must not lead to an unschedulable situation for the high-criticality tasks. In this work, we show how a linear programming approach can be used to generate these schedule tables in a consistent way for dual-critical problems on multiprocessor architectures. Source


Morse J.L.,Cary Institute of Ecosystem Studies | Morse J.L.,Portland State University | Werner S.F.,Syracuse University | Gillin C.P.,VA Technology | And 5 more authors.
Journal of Geophysical Research G: Biogeosciences | Year: 2014

Understanding and predicting the extent, location, and function of biogeochemical hot spots at the watershed scale is a frontier in environmental science. We applied a hydropedologic approach to identify (1) biogeochemical differences among morphologically distinct hydropedologic settings and (2) hot spots of microbial carbon (C) and nitrogen (N) cycling activity in a northern hardwood forest in Hubbard Brook Experimental Forest, New Hampshire, USA. We assessed variables related to C and N cycling in spodic hydropedologic settings (typical podzols, bimodal podzols, and Bh podzols) and groundwater seeps during August 2010. We found that soil horizons (Oi/Oe, Oa/A, and B) differed significantly for most variables. B horizons (>10 cm) accounted for 71% (±11%) of C pools and 62% (±10%) ofmicrobial biomass C in the sampled soil profile, whereas the surface horizons (Oi/Oe and Oa/A; 0-10cm) were dominant zones for N-cycle-related variables. Watershed-wide estimates of C and N cycling were higher by 34 to 43% (±17-19%) when rates, horizon thickness, and areal extent of each hydropedologic setting were incorporated, versus conventionally calculated estimates for typical podzols that included only the top 10cm of mineral soil. Despite the variation in profile development in typical, bimodal, and Bh podzols, we did not detect significant differences in C and N cycling among them. Across all soil horizons and hydropedologic settings, we found strong links between biogeochemical cycling and soil C, suggesting that the accumulation of C in soils may be a robust indicator of microbial C and N cycling capacity in the landscape. ©2014. American Geophysical Union. All Rights Reserved. Source

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