Preserving Madagascar's Natural Heritage: The Importance of Keeping the Island's Vertebrate Fossils in the Public Domain

No Abstrac

Writhe in the Stretch-Twist-Fold Dynamo

This is an Author's Original Manuscript of an article whose final and definitive form, the Version of Record, has been published in Geophysical and Astrophysical Fluid Dynamics (2008) Copyright © 2008 Taylor & Francis, available online at: http://www.tandfonline.com/10.1080/03091920802531791This article looks at the influence of writhe in the stretch-twist-fold dynamo. We consider a thin flux tube distorted by simple stretch, twist, and fold motions and calculate the helicity and energy spectra. The writhe number assists in the calculations, as it tells us how much the internal twist changes as the tube is distorted. In addition it provides a valuable diagnostic for the degree of distortion. Non mirror-symmetric dynamos typically generate magnetic helicity of one sign on large-scales and the opposite sign on small scales. The calculations presented here confirm the hypothesis that the large-scale helicity corresponds to writhe and the small scale corresponds to twist. In addition, the writhe helicity spectrum exhibits an interesting oscillatory behavior. The technique of calculating Fourier spectra for the writhe helicity may be useful in other areas of research, for example, the study of highly coiled molecules

Human Computation and Convergence

Humans are the most effective integrators and producers of information, directly and through the use of information-processing inventions. As these inventions become increasingly sophisticated, the substantive role of humans in processing information will tend toward capabilities that derive from our most complex cognitive processes, e.g., abstraction, creativity, and applied world knowledge. Through the advancement of human computation - methods that leverage the respective strengths of humans and machines in distributed information-processing systems - formerly discrete processes will combine synergistically into increasingly integrated and complex information processing systems. These new, collective systems will exhibit an unprecedented degree of predictive accuracy in modeling physical and techno-social processes, and may ultimately coalesce into a single unified predictive organism, with the capacity to address societies most wicked problems and achieve planetary homeostasis.Comment: Pre-publication draft of chapter. 24 pages, 3 figures; added references to page 1 and 3, and corrected typ

Robot life: simulation and participation in the study of evolution and social behavior.

This paper explores the case of using robots to simulate evolution, in particular the case of Hamilton's Law. The uses of robots raises several questions that this paper seeks to address. The first concerns the role of the robots in biological research: do they simulate something (life, evolution, sociality) or do they participate in something? The second question concerns the physicality of the robots: what difference does embodiment make to the role of the robot in these experiments. Thirdly, how do life, embodiment and social behavior relate in contemporary biology and why is it possible for robots to illuminate this relation? These questions are provoked by a strange similarity that has not been noted before: between the problem of simulation in philosophy of science, and Deleuze's reading of Plato on the relationship of ideas, copies and simulacra

Elevation gradients of lemur abundance emphasise the importance of Madagascar’s lowland rainforest for the conservation of endemic taxa

1. Elevation gradients correlate with changes in several environmental conditions and are known to be related to animal abundance. Animals in regions with a naturally limited extent of lowland rainforest are expected to have evolved adaptations to intermediate elevations that provided a stable environment during their evolution. 2. Since the lowland rainforest of Madagascar has a limited extent and suffers from increasing anthropogenic pressure, it is essential to understand how well species tolerate intermediate and high elevations. In this study, we aim to quantify the relationship between lemur abundance and elevation in the eastern rainforest of Madagascar. 3. We correlated abundance data on 26 lemur species (10 genera), including 492 records from 26 studies, with elevation. We analysed the consistency of correlations across species with a meta‐analytical approach. We controlled for species’ body mass, elevational range and median elevation. We then ran generalised linear mixed models to determine whether lemur abundance was related to elevation, body mass, plant productivity and anthropogenic disturbance. 4. Overall, the abundance of lemur species in Malagasy rainforests was negatively correlated with elevation, and species occupying broader elevational ranges showed stronger correlations. Body mass was not related to species’ tolerance of high elevations. Even though several lemur species are able to occupy the entire elevation gradient, the few remaining patches of lowland rainforests host lemur species at greater abundances than other sites. Abundance across species was negatively related to body mass, elevation and seasonality in plant productivity and positively related to plant productivity. 5. Despite the ecological flexibility of many lemur species, the remnant patches of lowland rainforests host the highest levels of lemur abundance and are key to lemur conservation. It is crucial to preserve this priority habitat both for biodiversity conservation and for our understanding of lemur adaptations

On the magnetic fields generated by experimental dynamos

We review the results obtained by three successful fluid dynamo experiments and discuss what has been learnt from them about the effect of turbulence on the dynamo threshold and saturation. We then discuss several questions that are still open and propose experiments that could be performed to answer some of them.Comment: 40 pages, 13 figure

Classification of behaviour in housed dairy cows using an accelerometer-based activity monitoring system

Background Advances in bio-telemetry technology have made it possible to automatically monitor and classify behavioural activities in many animals, including domesticated species such as dairy cows. Automated behavioural classification has the potential to improve health and welfare monitoring processes as part of a Precision Livestock Farming approach. Recent studies have used accelerometers and pedometers to classify behavioural activities in dairy cows, but such approaches often cannot discriminate accurately between biologically important behaviours such as feeding, lying and standing or transition events between lying and standing. In this study we develop a decision-tree algorithm that uses tri-axial accelerometer data from a neck-mounted sensor to both classify biologically important behaviour in dairy cows and to detect transition events between lying and standing. Results Data were collected from six dairy cows that were monitored continuously for 36 h. Direct visual observations of each cow were used to validate the algorithm. Results show that the decision-tree algorithm is able to accurately classify three types of biologically relevant behaviours: lying (77.42 % sensitivity, 98.63 % precision), standing (88.00 % sensitivity, 55.00 % precision), and feeding (98.78 % sensitivity, 93.10 % precision). Transitions between standing and lying were also detected accurately with an average sensitivity of 96.45 % and an average precision of 87.50 %. The sensitivity and precision of the decision-tree algorithm matches the performance of more computationally intensive algorithms such as hidden Markov models and support vector machines. Conclusions Biologically important behavioural activities in housed dairy cows can be classified accurately using a simple decision-tree algorithm applied to data collected from a neck-mounted tri-axial accelerometer. The algorithm could form part of a real-time behavioural monitoring system in order to automatically detect dairy cow health and welfare status

Massive migration from the steppe is a source for Indo-European languages in Europe

We generated genome-wide data from 69 Europeans who lived between 8,000-3,000 years ago by enriching ancient DNA libraries for a target set of almost four hundred thousand polymorphisms. Enrichment of these positions decreases the sequencing required for genome-wide ancient DNA analysis by a median of around 250-fold, allowing us to study an order of magnitude more individuals than previous studies and to obtain new insights about the past. We show that the populations of western and far eastern Europe followed opposite trajectories between 8,000-5,000 years ago. At the beginning of the Neolithic period in Europe, ~8,000-7,000 years ago, closely related groups of early farmers appeared in Germany, Hungary, and Spain, different from indigenous hunter-gatherers, whereas Russia was inhabited by a distinctive population of hunter-gatherers with high affinity to a ~24,000 year old Siberian6 . By ~6,000-5,000 years ago, a resurgence of hunter-gatherer ancestry had occurred throughout much of Europe, but in Russia, the Yamnaya steppe herders of this time were descended not only from the preceding eastern European hunter-gatherers, but from a population of Near Eastern ancestry. Western and Eastern Europe came into contact ~4,500 years ago, as the Late Neolithic Corded Ware people from Germany traced ~3/4 of their ancestry to the Yamnaya, documenting a massive migration into the heartland of Europe from its eastern periphery. This steppe ancestry persisted in all sampled central Europeans until at least ~3,000 years ago, and is ubiquitous in present-day Europeans. These results provide support for the theory of a steppe origin of at least some of the Indo-European languages of Europe

The origin of dust in galaxies revisited: the mechanism determining dust content

The origin of cosmic dust is a fundamental issue in planetary science. This paper revisits the origin of dust in galaxies, in particular, in the Milky Way, by using a chemical evolution model of a galaxy composed of stars, interstellar medium, metals (elements heavier than helium), and dust. We start from a review of time-evolutionary equations of the four components, and then, we present simple recipes for the stellar remnant mass and yields of metal and dust based on models of stellar nucleosynthesis and dust formation. After calibrating some model parameters with the data from the solar neighborhood, we have confirmed a shortage of the stellar dust production rate relative to the dust destruction rate by supernovae if the destruction efficiency suggested by theoretical works is correct. If the dust mass growth by material accretion in molecular clouds is active, the observed dust amount in the solar neighborhood is reproduced. We present a clear analytic explanation of the mechanism for determining dust content in galaxies after the activation of accretion growth: a balance between accretion growth and supernova destruction. Thus, the dust content is independent of the uncertainty of the stellar dust yield after the growth activation. The timing of the activation is determined by a critical metal mass fraction which depends on the growth and destruction efficiencies. The solar system formation seems to have occurred well after the activation and plenty of dust would have existed in the proto-solar nebula.Comment: 12 pages, 11 figure

Defining the functional traits that drive bacterial decomposer community productivity

Microbial communities are essential to a wide range of ecologically and industrially important processes. To control or predict how these communities function, we require a better understanding of the factors which influence microbial community productivity. Here, we combine functional resource use assays with a biodiversity–ecosystem functioning (BEF) experiment to determine whether the functional traits of constituent species can be used to predict community productivity. We quantified the abilities of 12 bacterial species to metabolise components of lignocellulose and then assembled these species into communities of varying diversity and composition to measure their productivity growing on lignocellulose, a complex natural substrate. A positive relationship between diversity and community productivity was caused by a selection effect whereby more diverse communities were more likely to contain two species that significantly improved community productivity. Analysis of functional traits revealed that the observed selection effect was primarily driven by the abilities of these species to degrade β-glucan. Our results indicate that by identifying the key functional traits underlying microbial community productivity we could improve industrial bioprocessing of complex natural substrates