Search

Comments in our September 7 eNewsletter spurred a slew of thoughts about the responsibilities engineers have over their designs and their future uses. Read on to hear what other engineers [...]

In northern peatlands, near‐saturated surface conditions promote valuable ecosystem services such as carbon storage and drinking water provision. Peat saturated hydraulic conductivity (Ksat) plays an important role in maintaining wet surface conditions by moderating drainage and evapotranspiration. Peat Ksatcan exhibit intense spatial variability in three dimensions and can change rapidly in response to disturbance. The development of skillful predictive equations for peat Ksatand other hydraulic properties, akin to mineral soil pedotransfer functions, remains a subject of ongoing research. We report a meta‐analysis of 2,507 northern peat samples, from which we developed linear models that predict peat Ksatfrom other variables, including depth, dry bulk density, von Post score (degree of humification), and categorical information such as surface microform type and peatland trophic type (e.g., bog and fen). Peat Ksatdecreases strongly with increasing depth, dry bulk density, and humification; and increases along the trophic gradient from bog to fen peat. Dry bulk density and humification are particularly important predictors and increase model skill greatly; our best model, which includes these variables, has a cross‐validated r2of 0.75 and little bias. A second model that includes humification but omits dry bulk density, intended for rapid field estimations of Ksat, also performs well (cross‐validated r2= 0.64). Two additional models that omit several predictors perform less well (cross‐validated r2∼ 0.5), and exhibit greater bias, but allow Ksatto be estimated from less comprehensive data. Our models allow improved estimation of peat Ksatfrom simpler, cheaper measurements. We report skillful statistical models to estimate saturated hydraulic conductivity in northern peats from simpler measurementsPeat dry bulk density and humification (von Post score) are particularly powerful predictorsOur models represent an improvement over existing pedotransfer functions for peat saturated hydraulic conductivity We report skillful statistical models to estimate saturated hydraulic conductivity in northern peats from simpler measurements Peat dry bulk density and humification (von Post score) are particularly powerful predictors Our models represent an improvement over existing pedotransfer functions for peat saturated hydraulic conductivity

A validation study of the Larocque Obesity Questionnaire designed for use in obesity treatment was performed. Unlike other measures of obesity, this questionnaire includes scales measuring general emotional state as well as eating behavior. Subscales measured uncontrolled eating, physical stress responses, depression, and perfectionism. Subjects were 458 women and 79 men in treatment for obesity by general practitioners. The subscales showed acceptable internal consistency and related in predictable ways to measures of eating behavior, depression, self-criticism, stress, physical complaints and weight-control motivation. Subjects in the heaviest weight category (Body Mass Index ≥ 40) showed higher scores on Stress Response and Depression subscales. There were no significant sex differences, after controlling for weight. All four subscales showed significant improvement after 5 wk., which indicates their sensitivity to changes during treatment.

The production of bareroot seedlings in tree nurseries requires large amounts of inorganic fertilizers. The fertilizer type and application schedule can have an effect on seedling growth and on NO3losses to the environment. The objective of this study was to determine if a model simulating N dynamics in agricultural field soils could be used to estimate soil inorganic N levels in forest tree nursery soils. The model selected was AGRIFLUX, a mechanistic and stochastic model. The study was carried out from 1993 to 1995 in a Canada forest tree nursery located in Quebec. In 1994, four different treatments of N fertilization (186 kg N ha−1) were applied: nine applications of ammonium sulfate (AS: 21‐0‐0) every 2 wk compared with two and three seasonal applications of sulfur‐coated urea (SCU: 38‐0‐0). Soil inorganic N concentrations were measured at depths of 0 to 20 and 20 to 40 cm. Temporal trends of inorganic N were generally well simulated by the model for both soil depths, considering the high variability of the field measurements. Results show that the AS treatment was better simulated than the SCU treatments. Sensitivity analysis revealed that most of the parameters used in AGRIFLUX have a relatively limited influence on the model results. This study shows that a model such as AGRIFLUX can be a useful tool for the estimation of inorganic N levels in forest tree nursery soils.

The identification of representative parameter values is an important aspect of N modeling because many parameters are unavailable or difficult to evaluate. Reversed modeling was performed using a conceptual simulation model, AgriFlux, and NO3−concentrations from a field near Quebec City, Canada, to identify N cycle parameters. A sensitivity analysis of the model with regard to the unavailable N cycle parameters identified three parameters related to the organic N transformations that largely control soil N dynamics (efficiency of the internal synthesis of the microbial biomass, litter humification fraction, and humus mineralization rate). The available parameters and those of lesser influence were kept constant while various combinations of the three influential parameters were used for the simulations. An optimal parameter set was identified using the root mean square error procedure, and its uniqueness was confirmed by the isocontouring technique. For the site studied, low values of humus mineralization combined with low values for the efficiency of the microbial biomass and small transfers from the litter pool to the humus pool generated the NO3−concentrations that compared the most favorably with the measured values. However, a fitting difference was observed between simulated and measured concentrations that can be imputed to nonoptimized parameters or processes not differentiated in the model.

Most NO−3leaching models require the quantification of many parameters. Because the majority of these parameters are difficult to estimate, it is important to know the impact of parameter imprecision to make proper use of a model. A study was performed to identify the relative influence of the parameters in a deterministic NO−3leaching model (SOILN) used with inorganic fertilization in nordic climates. A sensitivity analysis of the model was performed using parameters related to the N cycle with two reference systems for the parameters corresponding to field sites located in Quebec and in southern Sweden. Results from both sites showed that atmospheric deposits had little influence on NO−3leaching in agricultural areas in Quebec and Sweden; the variation of parameters related to nitrification also had little impact on NO−3leaching at the sites studied; parameters used for mineralization, plant uptake, and denitrification had a significant impact on NO−3leaching in the simulated conditions; parameters related to abiotic factors had a variable influence, depending mostly on soil water contents.