Soil organic carbon and root distribution in a temperate arable agroforestry system

Aim To determine, for arable land in a temperate area, the effect of tree establishment and intercropping treatments, on the distribution of roots and soil organic carbon to a depth of 1.5 m. Methods A poplar (Populus sp.) silvoarable agroforestry experiment including arable controls was established on arable land in lowland England in 1992. The trees were intercropped with an arable rotation or bare fallow for the first 11 years, thereafter grass was allowed to establish. Coarse and fine root distributions (to depths of up to 1.5 m and up to 5 m from the trees) were measured in 1996, 2003, and 2011. The amount and type of soil carbon to 1.5 m depth was also measured in 2011. Results The trees, initially surrounded by arable crops rather than fallow, had a deeper coarse root distribution with less lateral expansion. In 2011, the combined length of tree and understorey vegetation roots was greater in the agroforestry treatments than the control, at depths below 0.9 m. Between 0 and 1.5 m depth, the fine root carbon in the agroforestry treatment (2.56 t ha-1) was 79% greater than that in the control (1.43 t ha-1). Although the soil organic carbon in the top 0.6 m under the trees (161 t C ha-1) was greater than in the control (142 t C ha-1), a tendency for smaller soil carbon levels beneath the trees at lower depths, meant that there was no overall tree effect when a 1.5 m soil depth was considered. From a limited sample, there was no tree effect on the proportion of recalcitrant soil organic carbon. Conclusions The observed decline in soil carbon beneath the trees at soil depths greater than 60 cm, if observed elsewhere, has important implication for assessments of the role of afforestation and agroforestry in sequestering carbon

Product Attributes and Consumer Willingness to Pay for Environmental Management Systems in Agriculture: Using the Choice Modeling Technique

Consumer concerns in food purchasing contain a number of elements, including food safety, environment, animal welfare, and other social issues. The purpose of this study was to examine consumer perceptions of the potential benefits of products that are produced using an environmental management system (EMS) in agriculture, and to identify those factors that influence choice. The choice modeling technique uses consumer responses (preferences) to estimate Montrealers= willingness to pay (WTP) for production practices that decrease the impacts on the environment, as well as for other potential benefits of EMS production. Results indicate that consumers are willing to pay a price premium for these environmental benefits. This could provide a justification for government to provide incentives for environmental farm management practices and support to certification and labelling programs.Consumer/Household Economics,

Multi-object spectroscopy of the field surrounding PKS 2126-158: Discovery of a z=0.66 galaxy group

The high-redshift radio-loud quasar PKS 2126-158 is found to have a large number of red galaxies in close apparent proximity. We use the Gemini Multi-Object Spectrograph (GMOS) on Gemini South to obtain optical spectra for a large fraction of these sources. We show that there is a group of galaxies at $z\sim0.66$, coincident with a metal-line absorption system seen in the quasar's optical spectrum. The multiplexing capabilities of GMOS also allow us to measure redshifts of many foreground galaxies in the field surrounding the quasar. The galaxy group has five confirmed members, and a further four fainter galaxies are possibly associated. All confirmed members exhibit early-type galaxy spectra, a rare situation for a Mg II absorbing system. We discuss the relationship of this group to the absorbing gas, and the possibility of gravitational lensing of the quasar due to the intervening galaxies.Comment: Monthly Notices of the Royal Astronomical Society, in press. 10 pages, 8 figure

Individual Differences in the Experience of Cognitive Workload

This study investigated the roles of four psychosocial variables – anxiety, conscientiousness, emotional intelligence, and Protestant work ethic – on subjective ratings of cognitive workload as measured by the Task Load Index (TLX) and the further connections between the four variables and TLX ratings of task performance. The four variables represented aspects of an underlying construct of elasticity versus rigidity in response to workload. Participants were 141 undergraduates who performed a vigilance task under different speeded conditions while working on a jigsaw puzzle for 90 minutes. Regression analysis showed that anxiety and emotional intelligence were the two variables most proximally related to TLX ratings. TLX ratings contributed to the prediction of performance on the puzzle, but not the vigilance task. Severity error bias was evident in some of the ratings. Although working in pairs improved performance, it also resulted in higher ratings of temporal demand and perceived performance pressure

Learning about a Moving Target in Resource Management: Optimal Bayesian Disease Control

Resource managers must often make difficult choices in the face of imperfectly observed and dynamically changing systems (e.g., livestock, fisheries, water, and invasive species). A rich set of techniques exists for identifying optimal choices when that uncertainty is assumed to be understood and irreducible. Standard optimization approaches, however, cannot address situations in which reducible uncertainty applies to either system behavior or environmental states. The adaptive management literature overcomes this limitation with tools for optimal learning, but has been limited to highly simplified models with state and action spaces that are discrete and small. We overcome this problem by using a recently developed extension of the Partially Observable Markov Decision Process (POMDP) framework to allow for learning about a continuous state. We illustrate this methodology by exploring optimal control of bovine tuberculosis in New Zealand cattle. Disease testing—the control variable—serves to identify herds for treatment and provides information on prevalence, which is both imperfectly observed and subject to change due to controllable and uncontrollable factors. We find substantial efficiency losses from both ignoring learning (standard stochastic optimization) and from simplifying system dynamics (to facilitate a typical, simple learning model), though the latter effect dominates in our setting. We also find that under an adaptive management approach, simplifying dynamics can lead to a belief trap in which information gathering ceases, beliefs become increasingly inaccurate, and losses abound

Entropic Priors and Bayesian Model Selection

We demonstrate that the principle of maximum relative entropy (ME), used judiciously, can ease the specification of priors in model selection problems. The resulting effect is that models that make sharp predictions are disfavoured, weakening the usual Bayesian "Occam's Razor". This is illustrated with a simple example involving what Jaynes called a "sure thing" hypothesis. Jaynes' resolution of the situation involved introducing a large number of alternative "sure thing" hypotheses that were possible before we observed the data. However, in more complex situations, it may not be possible to explicitly enumerate large numbers of alternatives. The entropic priors formalism produces the desired result without modifying the hypothesis space or requiring explicit enumeration of alternatives; all that is required is a good model for the prior predictive distribution for the data. This idea is illustrated with a simple rigged-lottery example, and we outline how this idea may help to resolve a recent debate amongst cosmologists: is dark energy a cosmological constant, or has it evolved with time in some way? And how shall we decide, when the data are in?Comment: Presented at MaxEnt 2009, the 29th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (July 5-10, 2009, Oxford, Mississippi, USA

Microwave-mediated synthesis of N-methyliminodiacetic acid (MIDA) boronates

A library of over 20, mainly aryl or heteroaryl, N-methyliminodiacetic acid (MIDA) boronates have been synthesised. A rapid microwave-mediated (MW) method (5–10 min) has been developed using polyethylene glycol 300 (PEG 300) as solvent. However, acetonitrile (MeCN) and dimethylformamide (DMF) were found to be alternative solvents, the latter especially for 2-substituted aryl boronic acids