Effects of body size and lifestyle on evolution of mammal life histories

It has recently been proposed that life-history evolution is subject to a fundamental size-dependent constraint. This constraint limits the rate at which biomass can be produced so that production per unit of body mass is inevitably slower in larger organisms than in smaller ones. Here we derive predictions for how changes in body size and production rates evolve in different lifestyles subject to this constraint. Predictions are tested by using data on the mass of neonate tissue produced per adult per year in 637 placental mammal species and are generally supported. Compared with terrestrial insectivores with generalized primitive traits, mammals that have evolved more specialized lifestyles have divergent massspecific production rates: (i) increased in groups that specialize on abundant and reliable foods: grazing and browsing herbivores (artiodactyls, lagomorphs, perissoclactyls, and folivorous rodents) and flesh-eating marine mammals (pinnipeds, cetaceans); and (ii) decreased in groups that have lifestyles with reduced death rates: bats, primates, arboreal, fossorial, and desert rodents, bears, elephants, and rhinos. Convergent evolution of groups with similar lifestyles is common, so patterns of productivity across mammalian taxa reflect both ecology and phylogeny. The overall result is that groups with different lifestyles have parallel but offset relationships between production rate and body size. These results shed light on the evolution of the fast-slow life-history continuum, suggesting that variation occurs along two axes corresponding to body size and lifestyle.

Conservation and sustainable use of wild species as sources of new ornamentals

While only about 1-200 species are used intensively in commercial floriculture (e.g. carnations, chrysanthemums, gerbera, narcissus, orchids, tulips, lilies, roses, pansies and violas, saintpaulias, etc.) and 4-500 as house plants, several thousand species of herbs, shrubs and trees are traded commercially by nurseries and garden centres as ornamentals or amenity species. Most of these have been introduced from the wild with little selection or breeding. In Europe alone, 12 000 species are found in cultivation in general garden collections (i.e. excluding specialist collections and botanic gardens). In addition, specialist collections (often very large) of many other species and/or cultivars of groups such as orchids, bromeliads, cacti and succulents, primulas, rhododendrons, conifers and cycads are maintained in several centres such as botanic gardens and specialist nurseries, as are 'national collections' of cultivated species and cultivars in some countries. Specialist growers, both professional and amateur, also maintain collections of plants for cultivation, including, increasingly, native plants. The trade in ornamental and amenity horticulture cannot be fully estimated but runs into many billions of dollars annually and there is considerable potential for further development and the introduction of many new species into the trade. Despite this, most of the collections are ad hoc and no co-ordinated efforts have been made to ensure that adequate germplasm samples of these species are maintained for conservation purposes and few of them are represented at all adequately in seed banks. Few countries have paid much attention to germplasm needs of ornamentals and the Ornamental Plant Germplasm Center in conjunction with the USDA National Plant Germplasm System at The Ohio State University is an exception. Generally there is a serious gap in national and international germplasm strategies, which have tended to focus primarily on food plants and some forage and industrial crops. Adequate arrangements need to be put in place to ensure the long- and medium-term conservation of representative samples of the genetic diversity of ornamental species. The problems of achieving this will be discussed. In addition, a policy for the conservation of old cultivars or 'heritage' varieties of ornamentals needs to be formulated. The considerable potential for introduction of new ornamental species needs to be assessed. Consideration needs to be given to setting up a co-ordinating structure with overall responsibility for the conservation of germplasm of ornamental and amenity plants.

Recognition of sequence-information in synthetic copolymer chains by a conformationally-constrained tweezer molecule

A novel type of tweezer molecule containing electron-rich 2-pyrenyloxy arms has been designed to exploit intramolecular hydrogen bonding in stabilising a preferred conformation for supramolecular complexation to complementary sequences in aromatic copolyimides. This tweezer-conformation is demonstrated by single-crystal X-ray analyses of the tweezer molecule itself and of its complex with an aromatic diimide model-compound. In terms of its ability to bind selectively to polyimide chains, the new tweezer molecule shows very high sensitivity to sequence effects. Thus, even low concentrations of tweezer relative to diimide units (<2.5 mol%) are sufficient to produce dramatic, sequence-related splittings of the pyromellitimide proton NMR resonances. These induced resonance-shifts arise from ring-current shielding of pyromellitimide protons by the pyrenyloxy arms of the tweezer-molecule, and the magnitude of such shielding is a function of the tweezer-binding constant for any particular monomer sequence. Recognition of both short-range and long-range sequences is observed, the latter arising from cumulative ring-current shielding of diimide protons by tweezer molecules binding at multiple adjacent sites on the copolymer chain.

Functional petit-suisse cheese: measure of the prebiotic effect

Prebiotics and probiotics are increasingly being used to produce potentially synbiotic foods, particularly through dairy products as vehicles. It is well known that both ingredients may offer benefits to improve the host health. This research aimed to evaluate the prebiotic potential of novel petit-suisse cheeses using an in vitro fermentation model. Five petit-suisse cheese formulations combining candidate prebiotics (inulin. oligofructose. hone) and probiotics (Lactobacillus acidophilus, Bifidobacterium lactis) were tested in vitro using, sterile. stirred, batch culture fermentations with human faecal slurry. Measurement of prebiotic effect (MPE) values were generated comparing bacterial changes through determination of maximum growth rates of groups, rate of substrate assimilation and production of lactate and short chain fatty acids. Fastest fermentation and high lactic acid production, promoting increased growth rates of bifidobacteria and lactobacilli. were achieved with addition of prebiotics to a probiotic cheese (made using starter + probiotics). Addition of probiotic strains to control cheese (made using just a starter culture) also resulted in high lactic acid production. Highest MPE values were obtained with addition of prebiotics to a probiotic cheese, followed by addition of prebiotics and/or probiotics to a control cheese. Under the in vitro conditions used, cheese made with the combination of different prebiotics and probiotics resulted in the most promising functional petit-suisse cheese. The study allowed comparison of potentially functional petit-suisse cheeses and screening of preferred synbiotic potential for future market use. (c) 2007 Elsevier Ltd. All rights reserved.

The potential for community groups to promote sustainable living

In recent times there has been a growing recognition amongst policy-makers of the role for community-based action in contributing to the broader aims of energy policy and climate change. In this paper, we will examine the potential for existing community groups to use their influence and elements of internal cohesion to encourage more widespread understanding and adoption of sustainable lifestyle habits; both amongst their members and within the broader communities of which they are a part. Findings are presented from recent empirical work with a range of well-established community groups for whom environmental issues are not their main priority. A central aspect of the research was to explore both the current status and potential role of groups that may have the capacity to reach and influence a broader sphere of the public than energy/environment specific initiatives of recent times have been able to achieve. Representing a diversity of interests, age groups and functionality, the results suggest that the potential for more effective ‘bottom-up’ engagement on climate change and sustainable living might be given fresh impetus by these types of established community groups and their networks. An assessment of what motivates participation and membership in the groups highlights a series of factors common to all groups and a smaller number that are significant for particular groups individually. It is argued that an appreciation of motivating factors can be useful in understanding more clearly how such groups are able to survive and maintain cohesion over time. The findings also suggest that climate change action means different things for different groups, with the diversity of the groups bringing with it the challenge of making sustainable living relevant to a range of interests and different shared values.

The BioDICE Taverna plugin for clustering and visualization of biological data: a workflow for molecular compounds exploration

Background: In many experimental pipelines, clustering of multidimensional biological datasets is used to detect hidden structures in unlabelled input data. Taverna is a popular workflow management system that is used to design and execute scientific workflows and aid in silico experimentation. The availability of fast unsupervised methods for clustering and visualization in the Taverna platform is important to support a data-driven scientific discovery in complex and explorative bioinformatics applications. Results: This work presents a Taverna plugin, the Biological Data Interactive Clustering Explorer (BioDICE), that performs clustering of high-dimensional biological data and provides a nonlinear, topology preserving projection for the visualization of the input data and their similarities. The core algorithm in the BioDICE plugin is Fast Learning Self Organizing Map (FLSOM), which is an improved variant of the Self Organizing Map (SOM) algorithm. The plugin generates an interactive 2D map that allows the visual exploration of multidimensional data and the identification of groups of similar objects. The effectiveness of the plugin is demonstrated on a case study related to chemical compounds. Conclusions: The number and variety of available tools and its extensibility have made Taverna a popular choice for the development of scientific data workflows. This work presents a novel plugin, BioDICE, which adds a data-driven knowledge discovery component to Taverna. BioDICE provides an effective and powerful clustering tool, which can be adopted for the explorative analysis of biological datasets.

Tests of sunspot number sequences: 3. Effects of regression procedures on the calibration of historic sunspot data

We use sunspot group observations from the Royal Greenwich Observatory (RGO) to investigate the effects of intercalibrating data from observers with different visual acuities. The tests are made by counting the number of groups RB above a variable cut-off threshold of observed total whole-spot area (uncorrected for foreshortening) to simulate what a lower acuity observer would have seen. The synthesised annual means of RB are then re-scaled to the full observed RGO group number RA using a variety of regression techniques. It is found that a very high correlation between RA and RB (rAB > 0.98) does not prevent large errors in the intercalibration (for example sunspot maximum values can be over 30 % too large even for such levels of rAB). In generating the backbone sunspot number (RBB), Svalgaard and Schatten (2015, this issue) force regression fits to pass through the scatter plot origin which generates unreliable fits (the residuals do not form a normal distribution) and causes sunspot cycle amplitudes to be exaggerated in the intercalibrated data. It is demonstrated that the use of Quantile-Quantile (“Q  Q”) plots to test for a normal distribution is a useful indicator of erroneous and misleading regression fits. Ordinary least squares linear fits, not forced to pass through the origin, are sometimes reliable (although the optimum method used is shown to be different when matching peak and average sunspot group numbers). However, other fits are only reliable if non-linear regression is used. From these results it is entirely possible that the inflation of solar cycle amplitudes in the backbone group sunspot number as one goes back in time, relative to related solar-terrestrial parameters, is entirely caused by the use of inappropriate and non-robust regression techniques to calibrate the sunspot data.

Design for design: support for creative practice in computer-supported collaborative work (CSCW) in design

This paper describes a novel methodology for observing and analysing collaborative design by using the concepts of cognitive dimensions related to concept-based misfit analysis. The study aims at gaining an insight into support for creative practice of graphical communication in collaborative design processes of designers while sketching within a shared white board and audio conferencing environment. Empirical data on design processes have been obtained from observation of groups of student designers solving an interior space-planning problem of a lounge-diner in a shared virtual environment. The results of the study provide recommendations for the design and development of interactive systems to support such collaborative design activities.

Vibrations in the B-4 rhombic structure

A double minimum six-dimensional Potential energy surface (PES) is determined in symmetry coordinates for the most stable rhombic (D-2h) B-4 isomer in its (1)A(g) electronic ground state by fitting to energies calculated ab initio. The PES exhibits a barrier to the D-4h square structure of 255 cm(-1). The vibrational levels (J=0) are calculated variationally using an approach which involves the Watson kinetic energy operator expressed in normal coordinates. The pattern of about 65 vibrational levels up to 1600 cm-1 for all stable isotopomers is analyzed. Analogous to the inversion in ammonia-like molecules, the rhombus rearrangements lead to splittings of the vibrational levels. In B-4 it is the B-1g (D-4h mode which distorts the square molecule to its planar rhombic form. The anharmonic fundamental vibrational transitions of B-11(4) are calculated to be (splittings in parentheses): G(O) = 2352(22) cm(-1), v(1)(A(1g)) - 1136(24) cm(-1,) v(2)(B-1g)=209(144) cm(-1) v(3)(B-2g)=1198(19)cm(-1), v(4)(B-2u) = 271(24) cm(-1), and v(5) (E-u) = 1030( 166) cm(-1) (D-4h notation). Their variations in all stable isotoporners were investigated. Due to the presence of strong anharmonic resonances between the B-1g in-plane distortion and the B-2u, out-of-plane bending modes. the hiaher overtones and combination levels are difficult to assign unequivocally. (C) 2005 American Institute of Physics.

Reducing defects through organizational learning within a Housing Association environment

Housing Associations (HAs) contribute circa 20% of the UK’s housing supply. HAs are however under increasing pressure as a result of funding cuts and rent reductions. Due to the increased pressure, a number of processes are currently being reviewed by HAs, especially how they manage and learn from defects. Learning from defects is considered a useful approach to achieving defect reduction within the UK housebuilding industry. This paper contributes to our understanding of how HAs learn from defects by undertaking an initial round table discussion with key HA stakeholders as part of an ongoing collaborative research project with the National House Building Council (NHBC) to better understand how house builders and HAs learn from defects to reduce their prevalence. The initial discussion shows that defect information runs through a number of groups, both internal and external of a HA during both the defects management process and organizational learning (OL) process. Furthermore, HAs are reliant on capturing and recording defect data as the foundation for the OL process. During the OL process defect data analysis is the primary enabler to recognizing a need for a change to organizational routines. When a need for change has been recognized, new options are typically pursued to design out defects via updates to a HAs Employer’s Requirements. Proposed solutions are selected by a review board and committed to organizational routine. After implementing a change, both structured and unstructured feedback is sought to establish the change’s success. The findings from the HA discussion demonstrates that OL can achieve defect reduction within the house building sector in the UK. The paper concludes by outlining a potential ‘learning from defects model’ for the housebuilding industry as well as describing future work.