Fertilization trajectory of the root crop Raphanus sativus across atmospheric pCO2 estimates of the next 300 years

Plant biomass is known to increase in response to elevated atmospheric CO₂ concentration (pCO₂); however, no experiments have quantified the trajectory of crop fertilization across the full range of pCO₂ levels estimated for the next 300 years. Here we quantify the above- and below-ground biomass response of Raphanus sativus (common radish) across eight pCO₂ levels ranging from 348 to 1791 ppmv. We observed a large net biomass increase of 58% above ground and 279% below ground. A large part of the net increase (38% of the above-ground and 53% of the below-ground) represented biomass fertilization at the high levels of pCO₂ (700–1791 ppmv) predicted if fossil fuel emissions continue unabated. The trajectory of below-ground fertilization in R. sativus greatly exceeded a trajectory based on extrapolation of previous experiments for plants grown at pCO₂ < 800 ppmv. Based on the experimental parameters used to grow these plants, we hypothesize that these experiments represent the maximum CO₂ fertilization that can be achieved for this plant growing under low light levels. If the below-ground biomass enhancement that we have quantified for R. sativus represents a generalized root-crop response that can be extrapolated to agricultural systems, below-ground fertilization under very high pCO₂ levels could dramatically augment crop production in some of the poorest nations of the world, provided that water resources are sufficient and sustainable.     

An information–motivation–behavioral skills assessment of curbside recycling behavior

Despite annual increases in the amount of material solid waste (MSW) that is recycled in the United States, the overall amount of MSW generated continues to increase. In an effort to identify and test specific predictors of curbside recycling behavior, the current study adapted the empirically validated Information–Motivation–Behavioral Skills model (IMB), traditionally used to predict personal health behavior, to explain curbside recycling behavior. Using structured computer assisted telephone surveys with two random community samples; structural equation models indicated that the IMB model significantly predicted curbside recycling. Data from the current study provides specific information about critical psychosocial determinants of curbside recycling behavior and public policy implications.     

New Zealand drivers study: developing a methodology for conducting a follow-up study of newly licensed drivers

PROBLEM: In recent years, there has been a significant reduction in traffic crash injury among young people, but they continue to be overrepresented in the traffic crash statistics. To improve this situation, sound scientific evidence is needed to develop effective policies and programs. METHOD: The aim of the proposed study is to provide this evidence by examining early driving and driving-related experiences of newly licensed drivers as they progress through the learner-, restricted-, and full-license stages of the graduated licensing system and to determine the impact of these experiences on subsequent negative traffic-related outcomes (risky driving behavior, injury traffic crashes, noninjury traffic crashes, infringements, convictions). Given the size and complexity of the proposed study, a comprehensive pilot study was undertaken to determine the feasibility of conducting a New Zealand-wide cohort study of newly licensed drivers. RESULTS: This article describes the pilot study process and the methodology that has been developed for the New Zealand-wide study.     

ESTIMATING REFERENCE EVAPORATION IN THE CENTRAL VALLEY OF CALIFORNIA USING THE LINACRE MODEL1

ABSTRACT: The Linacre (1988) model for calculating evaporation from open water or well-watered surfaces only requires inputs of air temperature, latitude and elevation, and windspeed if it is available. The model was developed using data collected at a large number of sites in different climatic regions of the world, while independent tests of the model have shown it to be suitable for estimating evaporation in a variety of locations. This study was intended to contribute to the broad goal of evaluating temperature-based evaporation models for use in California by testing the Linacre model in the agriculturally intensive Central Valley. Observed monthly mean reference evaporation (E_o) and meteorological data for periods ranging up to 72 months were obtained from 25 California Irrigation and Management Information System (CIMIS) stations distributed throughout the Central Valley. Uncalibrated and calibrated Linacre models were used to estimate monthly mean reference evaporation, and the performance of each model was evaluated using indices that quantified the random and systematic errors and overall model performance. The accuracy of the radiation and ventilation components of the model were evaluated separately. The uncalibrated model was found to systematically overestimate E_o with most of the model error being attributed to the ventilation component. Calibration of the radiation and ventilation components removed most of the systematic model errors, and the root mean square error for monthly mean E_o was 0.676 mm day^?1 (16.8 percent of the mean observed value). (KEY TERMS: reference evaporation; Linacre model; irrigation scheduling.)     

Assessing Water Quality Improvement Schemes: The Multi-Attribute Technique of the UK's Environment Agency

The Environment Agency for England and Wales is required to take account of likely costs and benefits in carrying out its duties. Given the complex nature of environmental problems, this task requires sensitivity to issues such as uncertainty, multiple objectives and conflicting value systems. This paper describes a multi-attribute methodology used to carry out this duty in one area of the Agency's work, the regulation of the water industry. The method includes nine attributes measuring the benefits from water quality improvement schemes, and one attribute measuring scheme costs. It is a workable method that clearly satisfies the requirements for the Environment Agency to take account of the costs and benefits of its actions. Refinements are suggested to improve the individual attribute scores, the weights used in prioritisation and the incorporation of costs. This revised version was published online in July 2006 with corrections to the Cover Date.     

PRIESTLEY‐TAYLOR ALPHA COEFFICIENT: VARIABILITY AND RELATIONSHIP TO NDVI IN ARCTIC TUNDRA LANDSCAPES1

ABSTRACT: Average daily values of the Priestley‐Taylor coefficient (a) were calculated for two eddy covariance (flux) tower sites with contrasting vegetation, soil moisture, and temperature characteristics on the North Slope of Alaska over the 1994 and 1995 growing seasons. Because variations in a have been shown to be associated with changes in vegetation, soil moisture, and meteorological conditions in Arctic ecosystems, we hypothesized that a values would be significantly different between sites. Since variations in the normalized difference vegetation index (NDVI) follow patterns of vegetation community composition and state that are largely controlled by moisture and temperature gradients on the North Slope of Alaska, we hypothesized that temporal variations in a respond to these same conditions and thus co‐vary with NDVI. Significant differences in a values were found between the two sites in 1994 under average precipitation conditions. However, in 1995, when precipitation conditions were above average, no significant difference was found. Overall, the variations in a over the two growing seasons showed little relationship to the seasonal progression of the regional NDVI. The only significant relationship was found at the drier, upland study site.