Global hydrology modelling and uncertainty: running multiple ensembles with a campus grid.

Uncertainties associated with the representation of various physical processes in global climate models (GCMs) mean that, when projections from GCMs are used in climate change impact studies, the uncertainty propagates through to the impact estimates. A complete treatment of this ‘climate model structural uncertainty’ is necessary so that decision-makers are presented with an uncertainty range around the impact estimates. This uncertainty is often underexplored owing to the human and computer processing time required to perform the numerous simulations. Here, we present a 189-member ensemble of global river runoff and water resource stress simulations that adequately address this uncertainty. Following several adaptations and modifications, the ensemble creation time has been reduced from 750 h on a typical single-processor personal computer to 9 h of high-throughput computing on the University of Reading Campus Grid. Here, we outline the changes that had to be made to the hydrological impacts model and to the Campus Grid, and present the main results. We show that, although there is considerable uncertainty in both the magnitude and the sign of regional runoff changes across different GCMs with climate change, there is much less uncertainty in runoff changes for regions that experience large runoff increases (e.g. the high northern latitudes and Central Asia) and large runoff decreases (e.g. the Mediterranean). Furthermore, there is consensus that the percentage of the global population at risk to water resource stress will increase with climate change.

Epidemiological risk assessment using linked network and grid based modelling: Phytophthora ramorum and Phytophthora kernoviae in the UK

We developed a stochastic simulation model incorporating most processes likely to be important in the spread of Phytophthora ramorum and similar diseases across the British landscape (covering Rhododendron ponticum in woodland and nurseries, and Vaccinium myrtillus in heathland). The simulation allows for movements of diseased plants within a realistically modelled trade network and long-distance natural dispersal. A series of simulation experiments were run with the model, representing an experiment varying the epidemic pressure and linkage between natural vegetation and horticultural trade, with or without disease spread in commercial trade, and with or without inspections-with-eradication, to give a 2 x 2 x 2 x 2 factorial started at 10 arbitrary locations spread across England. Fifty replicate simulations were made at each set of parameter values. Individual epidemics varied dramatically in size due to stochastic effects throughout the model. Across a range of epidemic pressures, the size of the epidemic was 5-13 times larger when commercial movement of plants was included. A key unknown factor in the system is the area of susceptible habitat outside the nursery system. Inspections, with a probability of detection and efficiency of infected-plant removal of 80% and made at 90-day intervals, reduced the size of epidemics by about 60% across the three sectors with a density of 1% susceptible plants in broadleaf woodland and heathland. Reducing this density to 0.1% largely isolated the trade network, so that inspections reduced the final epidemic size by over 90%, and most epidemics ended without escape into nature. Even in this case, however, major wild epidemics developed in a few percent of cases. Provided the number of new introductions remains low, the current inspection policy will control most epidemics. However, as the rate of introduction increases, it can overwhelm any reasonable inspection regime, largely due to spread prior to detection. (C) 2009 Elsevier B.V. All rights reserved.

A middleware independent grid workflow builder for scientific applications

Grid workflow authoring tools are typically specific to particular workflow engines built into Grid middleware, or are application specific and are designed to interact with specific software implementations. g-Eclipse is a middleware independent Grid workbench that aims to provide a unified abstraction of the Grid and includes a Grid workflow builder to allow users to author and deploy workflows to the Grid. This paper describes the g-Eclipse Workflow Builder and its implementations for two Grid middlewares, gLite and GRIA, and a case study utilizing the Workflow Builder in a Grid user's scientific workflow deployment.

Building a biodiversity GRID

In the BiodiversityWorld project we are building a GRID to support scientific biodiversity-related research. The requirements associated with such a GRID are somewhat different from other GRIDs, and this has influenced the architecture that we have developed. In this paper we outline these requirements, most notably the need to interoperate over a diverse set of legacy databases and applications in an environment that supports effective resource discovery and use of these resources in complex workflows. Our architecture provides an invocation model that is usable over a wide range of resource types and underlying GRID middleware. However, there is a trade-off between the flexibility provided by our architecture and its performance. We discuss how this affects the inclusion of computationally intensive applications and applications that are highly interactive; we also consider the broader issue of interoperation with other GRIDs.

Methylene spacer-regulated structural variation in cobalt(II/III) complexes with bridging acetate and Salen- or Salpn-type Schiff-base ligands

Two linear, trinuclear mixed-valence complexes, [Co-II{(mu-L-1)(mu-OAc)Co-III (OAc)}(2)] (1) and [Co-II(mu-L-2) (mu-OAc)Co-III(OAc)}(2)] (2) and two mononuclear Con' complexes [Co-III{L-3)(OAc)] (3), and [Co-III {L-4}(OAc)] (4) were prepared and the molecular structures of 1, 2 and 4 elucidated on the basis of X-ray crystallography [OAc = Acetate ion, H2L1 = H(2)Salen 1,6-bis(2-hydroxyphenyl)-2,5-diazahexa-1,5-diene, H2L2 H2Me2-Salen = 2,7-bis(2-hydroxyphenyl)-2,6-diazaocta-2,6-diene, H2L3 = H(2)Salpn = 1,7-bis(2-hydroxyphenyl)-2,6-diazahepta1,6-diene, H2L4 = H(2)Me(2)Salpn = 2,8-bis(2-hydroxyphenyl)3,7-diazanona-2,7-dienel. In complexes I and 2, the acetate groups show both monodentate and bridging bidentate coordination modes, whereas chelating bidentate acetate is present in 4. The terminal (CoN2O4)-N-III centres in 1 and 2 exhibit uniform facial arrangements of both non-bridged N2O and bridging O-3 donor sets and the Co-II centre is coordinated to six (four phenoxo and two acetato) oxygen atoms of the bridging ligands. The effective magnetic moment at room temperature corresponds to the presence of high-spin Coll in both 1 and 2. The complexes 1 and 2 are thus Co-III(S = 0)Co-II(S = 3/2)-Co-II(S = 0) trimers. Complexes 3 and 4 are monomeric and diamagnetic containing low-spin Co-III(S = 0) with chelating tetradentate Schiff base and bidentate acetate. Calculations based on DFT rationalise the formation of trinuclear or monomiclear complexes. (C) Wiley-VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2008).

Variation in 16S-23S rRNA intergenic spacer regions in Photobacterium damselae: a mosaic-like structure

Phenotypically, Photobacterium damselae subsp. piscicida and P. damselae subsp. damselae are easily distinguished. However, their 16S rRNA gene sequences are identical, and attempts to discriminate these two subspecies by molecular tools are hampered by their high level of DNA-DNA similarity. The 16S-23S rRNA internal transcribed spacers (ITS) were sequenced in two strains of Photobacterium damselae subsp. piscicida and two strains of P. damselae subsp. damselae to determine the level of molecular diversity in this DNA region. A total of 17 different ITS variants, ranging from 803 to 296 bp were found, some of which were subspecies or strain specific. The largest ITS contained four tRNA genes (tDNAs) coding for tRNA(Glu(UUC)), tRNA(LyS(UUU)), tRNA(Val(UAC)), and tRNA(Ala(GGC)). Five amplicons contained tRNA(Glu(UUC)) combined with two additional tRNA genes, including tRNA(Lys(UUU)), tRNA(Val(UAC)), or tRNA(Ala(UGC)). Five amplicons contained tRNA(Ile(GAU)) and tRNA(Ala(UGC)). Two amplicons contained tRNA(Glu(UUC)) and tRNA(Val(UGC)). Two different isoacceptor tRNA(Ala) genes (GGC and UGC anticodons) were found. The five smallest amplicons contained no tRNA genes. The tRNA-gene combinations tRNA(Glu(UUC)) -tRNA(Val(UAC)) -tRNA(Ala(UGC)) and tRNA(Glu(UUC)) -tRNA(Ala(UGC)) have not been previously reported in bacterial ITS regions. The number of copies of the ribosomal operon (rrn) in the P. damselae chromosome ranged from at least 9 to 12. For ITS variants coexisting in two strains of different subspecies or in strains of the same subspecies, nucleotide substitution percentages ranged from 0 to 2%. The main source of variation between ITS variants was due to different combinations of DNA sequence blocks, constituting a mosaic-like structure.

Characterization of the 23S and 5S rRNA genes and 23S-5S intergenic spacer region (ITS-2) of Photobacterium damselae

The 23S ribosomal RNA (rRNA) gene has been sequenced in strains of the fish pathogens Photobacterium damselae subsp. damselae (ATCC 33539) and subsp. piscicida (ATCC 29690), showing that 3 nucleotide positions are clearly different between subspecies. In addition, the 5S rRNA gene plus the intergenic spacer region between the 23S and 5S rRNA genes (ITS-2) were amplified, cloned and sequenced for the 2 reference strains as well as the field isolates RG91 (subsp. damselae) and DI21 (subsp. piscicida). A 100% similarity was found for the consensus 5S rRNA gene sequence in the 2 subspecies, although some microheterogeneity was detected as inter-cistronic variability within the same chromosome. Sequence analysis of the spacer region between the 23S and 5S rRNA genes revealed 2 conserved and 3 variable nucleotide sequence blocks, and 4 different modular organizations were found. The ITS-2 spacer region exhibited both inter-subspecies and inter-cistronic polymorphism, with a mosaic-like structure. The EMBL accession numbers for the 23S, 5S and ITS-2 sequences are: P. damselae subsp. piscicida 5S gene (AJ274379), P. damselae subsp. damselae 23S gene (Y18520), subsp. piscicida 23S gene (Y17901), R damselae subsp. piscicida ITS-2 (AJ250695, AJ250696), P. damselae subsp. damselae ITS-2 (AJ250697, AJ250698).