Plant species and functional group effects on abiotic and microbial soil properties and plant-soil feedback responses in two grasslands

1 Plant species differ in their capacity to influence soil organic matter, soil nutrient availability and the composition of soil microbial communities. Their influences on soil properties result in net positive or negative feedback effects, which influence plant performance and plant community composition. 2 For two grassland systems, one on a sandy soil in the Netherlands and one on a chalk soil in the United Kingdom, we investigated how individual plant species grown in monocultures changed abiotic and biotic soil conditions. Then, we determined feedback effects of these soils to plants of the same or different species. Feedback effects were analysed at the level of plant species and plant taxonomic groups (grasses vs. forbs). 3 In the sandy soils, plant species differed in their effects on soil chemical properties, in particular potassium levels, but PLFA (phospholipid fatty acid) signatures of the soil microbial community did not differ between plant species. The effects of soil chemical properties were even greater when grasses and forbs were compared, especially because potassium levels were lower in grass monocultures. 4 In the chalk soil, there were no effects of plant species on soil chemical properties, but PLFA profiles differed significantly between soils from different monocultures. PLFA profiles differed between species, rather than between grasses and forbs. 5 In the feedback experiment, all plant species in sandy soils grew less vigorously in soils conditioned by grasses than in soils conditioned by forbs. These effects correlated significantly with soil chemical properties. None of the seven plant species showed significant differences between performance in soil conditioned by the same vs. other plant species. 6 In the chalk soil, Sanguisorba minor and in particular Briza media performed best in soil collected from conspecifics, while Bromus erectus performed best in soil from heterospecifics. There was no distinctive pattern between soils collected from forb and grass monocultures, and plant performance could not be related to soil chemical properties or PLFA signatures. 7 Our study shows that mechanisms of plant-soil feedback can depend on plant species, plant taxonomic (or functional) groups and site-specific differences in abiotic and biotic soil properties. Understanding how plant species can influence their rhizosphere, and how other plant species respond to these changes, will greatly enhance our understanding of the functioning and stability of ecosystems.

The influence of age and gender on food choice: a focus group exploration

With 25% of the UK population predicted to be obese by 2010, the costs to individuals and society are set to rise. Due to the extra economic and social pressures obesity causes, there is an increasing need to understand what motivates and prevents consumers from eating a healthy diet so as to be able to tailor policy interventions to specific groups in society. In so doing, it is important to explore potential variations in attitudes, motivation and behaviour as a function of age and gender. Both demographic factors are easily distinguished within society and a future intervention study which targets either, or both, of these would likely be both feasible and cost-effective for policy makers. As part of a preliminary study, six focus groups (total n = 43) were conducted at the University of Reading in November 2006, with groups segmented on the basis of age and gender. In order to gather more sensitive information, participants were also asked to fill out a short anonymous questionnaire before each focus group began, relating to healthy eating, alcohol consumption and body dissatisfaction. Making use of thematic content analysis, results suggested that most participants were aware of the type of foods that contribute to a healthy diet and the importance of achieving a healthy balance within a diet. However, they believed that healthy eating messages were often conflicting, and were uncertain about where to find information on the topic. Participants believed that the family has an important role in educating children about eating habits. Despite these similarities, there were a number of key differences among the groups in terms of their reasons for making food choices. Older participants (60+ years old) were more likely to make food choices based on health considerations. Participants between the ages of 18–30 were less concerned with this link, and instead focused on issues of food preparation and knowledge, prices and time. Younger female participants said they had more energy when they ate healthier diets; however, very often their food choices related to concern with their appearance. Older female participants also expressed this concern within the questionnaire, rather than in the group discussions. Overall, these results suggest that consumer motivations for healthy eating are diverse and that this must be considered by government, retailers and food producers.

An adaptive approach to implementing bivariate group sequential clinical trial designs

In clinical trials, situations often arise where more than one response from each patient is of interest; and it is required that any decision to stop the study be based upon some or all of these measures simultaneously. Theory for the design of sequential experiments with simultaneous bivariate responses is described by Jennison and Turnbull (Jennison, C., Turnbull, B. W. (1993). Group sequential tests for bivariate response: interim analyses of clinical trials with both efficacy and safety endpoints. Biometrics 49:741-752) and Cook and Farewell (Cook, R. J., Farewell, V. T. (1994). Guidelines for monitoring efficacy and toxicity responses in clinical trials. Biometrics 50:1146-1152) in the context of one efficacy and one safety response. These expositions are in terms of normally distributed data with known covariance. The methods proposed require specification of the correlation, ρ between test statistics monitored as part of the sequential test. It can be difficult to quantify ρ and previous authors have suggested simply taking the lowest plausible value, as this will guarantee power. This paper begins with an illustration of the effect that inappropriate specification of ρ can have on the preservation of trial error rates. It is shown that both the type I error and the power can be adversely affected. As a possible solution to this problem, formulas are provided for the calculation of correlation from data collected as part of the trial. An adaptive approach is proposed and evaluated that makes use of these formulas and an example is provided to illustrate the method. Attention is restricted to the bivariate case for ease of computation, although the formulas derived are applicable in the general multivariate case.

An adaptive group sequential design for phase II/III clinical trials that select a single treatment from several

There is increasing interest in combining Phases II and III of clinical development into a single trial in which one of a small number of competing experimental treatments is ultimately selected and where a valid comparison is made between this treatment and the control treatment. Such a trial usually proceeds in stages, with the least promising experimental treatments dropped as soon as possible. In this paper we present a highly flexible design that uses adaptive group sequential methodology to monitor an order statistic. By using this approach, it is possible to design a trial which can have any number of stages, begins with any number of experimental treatments, and permits any number of these to continue at any stage. The test statistic used is based upon efficient scores, so the method can be easily applied to binary, ordinal, failure time, or normally distributed outcomes. The method is illustrated with an example, and simulations are conducted to investigate its type I error rate and power under a range of scenarios.