The climatic challenge: which plants will people use in the next century?

More than 31,000 useful plant species have been documented to fulfil needs and services for humans or the animals and environment we depend on. Despite this diversity, humans currently satisfy most requirements with surprisingly few plant species; for example, just three crops – rice, wheat and maize – comprise more than 50% of plant derived calories. Here, we synthesize the projected impact of global climatic change on useful plants across the spectrum of plant domestication. We illustrate the demographic, spatial, ecophysiological, chemical, functional, evolutionary and cultural traits that are likely to characterise useful plants and their resilience in the next century. Using this framework, we consider a range of possible pathways for future human use of plants. These are centred on two trade-offs: i) diversification versus specialization in the range of species we utilize, and ii) substitutionof the species towards those better suited to future climate versus facilitating adaptation in our existing suite of dominant useful plants. In the coming century, major challenges to agriculture and biodiversity will be dominated by increased climatic variation, shifting species ranges, disruption to biotic interactions, nutrient limitation and emerging pests and pathogens. These challenges must be mitigated, whilst enhancing sustainable production to meet the needs of a growing population and a more resource intensive standard of living. With the continued erosion of biodiversity, our future ability to choose among these pathways and trade-offs is likely to be diminished

Large-Eddy Simulations of Magnetohydrodynamic Turbulence in Heliophysics and Astrophysics

We live in an age in which high-performance computing is transforming the way we do science. Previously intractable problems are now becoming accessible by means of increasingly realistic numerical simulations. One of the most enduring and most challenging of these problems is turbulence. Yet, despite these advances, the extreme parameter regimes encountered in space physics and astrophysics (as in atmospheric and oceanic physics) still preclude direct numerical simulation. Numerical models must take a Large Eddy Simulation (LES) approach, explicitly computing only a fraction of the active dynamical scales. The success of such an approach hinges on how well the model can represent the subgrid-scales (SGS) that are not explicitly resolved. In addition to the parameter regime, heliophysical and astrophysical applications must also face an equally daunting challenge: magnetism. The presence of magnetic fields in a turbulent, electrically conducting fluid flow can dramatically alter the coupling between large and small scales, with potentially profound implications for LES/SGS modeling. In this review article, we summarize the state of the art in LES modeling of turbulent magnetohydrodynamic (MHD) ows. After discussing the nature of MHD turbulence and the small-scale processes that give rise to energy dissipation, plasma heating, and magnetic reconnection, we consider how these processes may best be captured within an LES/SGS framework. We then consider several special applications in heliophysics and astrophysics, assessing triumphs, challenges,and future directions

State of the world’s plants and fungi 2020

Kew’s State of the World’s Plants and Fungi project provides assessments of our current knowledge of the diversity of plants and fungi on Earth, the global threats that they face, and the policies to safeguard them. Produced in conjunction with an international scientific symposium, Kew’s State of the World’s Plants and Fungi sets an important international standard from which we can annually track trends in the global status of plant and fungal diversity

Medicinal Mascarene Aloe s: An audit of their phytotherapeutic potential

A phytochemical and biological investigation of the endemic Mascarene Aloes (Aloe spp.), including A. tormentorii (Marais) L.E.Newton & G.D.Rowley, A. purpurea Lam, A. macra Haw., A. lomatophylloides Balf.f and A. vera (synonym A. barbadensis Mill.), which are used in the traditional folk medicine of the Mascarene Islands, was initiated. Methanolic extracts of the Aloes under study were analysed using high resolution LC-UV-MS/MS and compounds belonging to the class of anthraquinones, anthrones, chromones and flavone C-glycosides were detected. The Mascarene Aloes could be distinguished from A. vera by the absence of 2″-O-feruloylaloesin and 7-O-methylaloeresin. GC–MS analysis of monosaccharides revealed the presence of arabinose, fucose, xylose, mannose and galactose in all the Mascarene Aloes and in A. vera. The crude extracts of all Aloes analysed displayed antimicrobial activity against Bacillus cereus, Staphylococcus aureus, Escherichia coli and Pseudomonas aeruginosa. Only extracts of A. macra were active against P. aeruginosa and Klebsiella pneumoniae, while none of the Aloe extracts inhibited Propionibacterium acnes. A. macra displayed anti-tyrosinase activity, exhibiting 50% inhibition at 0.95 mg/mL, and extracts of A. purpurea (Mauritius) and A. vera displayed activity in a wound healing-scratch assay. In vitro cytotoxicity screening of crude methanolic extracts of the Aloes, using the MTT (3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide) showed that only A. purpurea (Réunion) elicited a modest toxic effect against HL60 cells, with a percentage toxicity of 8.2% (A. purpurea-Réunion) and none of the Aloe extracts elicited a toxic effect against MRC 5 fibroblast cells at a concentration of 0.1 mg/mL. Mascarene Aloe species possess noteworthy pharmacological attributes associated with their rich phytochemical profiles

Plasma Diagnostics of the Interstellar Medium with Radio Astronomy

Contains fulltext : 119335.pdf (preprint version ) (Open Access

Data mining using parallel multi-objective evolutionary algorithms on graphics processing units

An important and challenging data mining application in marketing is to learn models for predicting potential customers who contribute large profits to a company under resource constraints. In this chapter, we first formulate this learning problem as a constrained optimization problem and then convert it to an unconstrained multi-objective optimization problem (MOP), which can be handled by some multi-objective evolutionary algorithms (MOEAs). However, MOEAs may execute for a long time for theMOP, because several evaluations must be performed. A promising approach to overcome this limitation is to parallelize these algorithms. Thus we propose a parallel MOEA on consumer-level graphics processing units (GPU) to tackle the MOP. We perform experiments on a real-life direct marketing problem to compare the proposed method with the parallel hybrid genetic algorithm, the DMAX approach, and a sequential MOEA. It is observed that the proposed method is much more effective and efficient than the other approaches