Oat Grain Variety Trial at Overton for 2000-2001 and Three Year Means

Last updated: 6/12/200

An Interactive Probability Plotting Program

An interactive FORTRAN program is presented which allows the user to produce probability plots (theoretical quantile-quantile plots) for an input data set based on several types of theoretical distributions. The program provides normal, two-parameter lognormal, three-parameter lognormal, right-tail half-normal, left-tail half-normal, exponential, two-parameter Weibull, and three-parameter Weibull plots. The present version of the program allows data entry and editing from the keyboard (not from stored files) and will accept up to 100 data values. This upper limit could easily be modified

Fish Cohort Dynamics: Application of Complementary Modeling Approaches

The recruitment to the adult stock of a fish population is a function of both environmental conditions and the dynamics of juvenile fish cohorts. These dynamics can be quite complicated and involve the size structure of the cohort. Two types of models, i-state distribution models (e.g., partial differential equations) and i-state configuration models (computer simulation models following many individuals simultaneously), have been developed to study this type of question. However, these two model types have not to our knowledge previously been compared in detail. Analytical solutions are obtained for three partial differential equation models of early life-history fish cohorts. Equivalent individual-by-individual computer simulation models are also used. These two approaches can produce similar results, which suggests that one may be able to use the approaches interchangeably under many circumstances. Simple uncorrected stochasticity in daily growth is added to the individual-by-individual models, and it is shown that this produces no significant difference from purely deterministic situations. However, when the stochasticity was temporally correlated such that a fish growing faster than the mean 1 d has a tendency to grow faster than the mean the next day, there can be great differences in the outcomes of the simulations.This research was sponsored in part by the Electric Power Research Institute under contract no. RP2932-2 (DOE no. ERD-87-672) with the U.S. Department of Energy under contract no. DE-AC05-84OR21400 with Martin Marietta Energy Systems, and in part by grant no. NAI6RG0492-01 from the Coastal Ocean Program of the National Oceanic and Atmospheric Administration (NOAA) to the University of North Carolina Sea Grant College Program

Probing substrate binding to Metallo-β-Lactamase L1 from Stenotrophomonas maltophilia by using site-directed mutagenesis

BACKGROUND: The metallo-β-lactamases are Zn(II)-containing enzymes that hydrolyze the β-lactam bond in penicillins, cephalosporins, and carbapenems and are involved in bacterial antibiotic resistance. There are at least 20 distinct organisms that produce a metallo-β-lactamase, and these enzymes have been extensively studied using X-ray crystallographic, computational, kinetic, and inhibition studies; however, much is still unknown about how substrates bind and the catalytic mechanism. In an effort to probe substrate binding to metallo-β-lactamase L1 from Stenotrophomonas maltophilia, nine site-directed mutants of L1 were prepared and characterized using metal analyses, CD spectroscopy, and pre-steady state and steady state kinetics. RESULTS: Site-directed mutations were generated of amino acids previously predicted to be important in substrate binding. Steady-state kinetic studies using the mutant enzymes and 9 different substrates demonstrated varying K(m) and k(cat) values for the different enzymes and substrates and that no direct correlation between K(m) and the effect of the mutation on substrate binding could be drawn. Stopped-flow fluorescence studies using nitrocefin as the substrate showed that only the S224D and Y228A mutants exhibited weaker nitrocefin binding. CONCLUSIONS: The data presented herein indicate that Ser224, Ile164, Phe158, Tyr228, and Asn233 are not essential for tight binding of substrate to metallo-β-lactamase L1. The results in this work also show that K(m) values are not reliable for showing substrate binding, and there is no correlation between substrate binding and the amount of reaction intermediate formed during the reaction. This work represents the first experimental testing of one of the computational models of the metallo-β-lactamases

Dynactin-dependent cortical dynein and spherical spindle shape correlate temporally with meiotic spindle rotation in Caenorhabditis elegans.

Oocyte meiotic spindles orient with one pole juxtaposed to the cortex to facilitate extrusion of chromosomes into polar bodies. In Caenorhabditis elegans, these acentriolar spindles initially orient parallel to the cortex and then rotate to the perpendicular orientation. To understand the mechanism of spindle rotation, we characterized events that correlated temporally with rotation, including shortening of the spindle in the pole-to pole axis, which resulted in a nearly spherical spindle at rotation. By analyzing large spindles of polyploid C. elegans and a related nematode species, we found that spindle rotation initiated at a defined spherical shape rather than at a defined spindle length. In addition, dynein accumulated on the cortex just before rotation, and microtubules grew from the spindle with plus ends outward during rotation. Dynactin depletion prevented accumulation of dynein on the cortex and prevented spindle rotation independently of effects on spindle shape. These results support a cortical pulling model in which spindle shape might facilitate rotation because a sphere can rotate without deforming the adjacent elastic cytoplasm. We also present evidence that activation of spindle rotation is promoted by dephosphorylation of the basic domain of p150 dynactin

Sensitivity and parameter-estimation precision for alternate LISA configurations

We describe a simple framework to assess the LISA scientific performance (more specifically, its sensitivity and expected parameter-estimation precision for prescribed gravitational-wave signals) under the assumption of failure of one or two inter-spacecraft laser measurements (links) and of one to four intra-spacecraft laser measurements. We apply the framework to the simple case of measuring the LISA sensitivity to monochromatic circular binaries, and the LISA parameter-estimation precision for the gravitational-wave polarization angle of these systems. Compared to the six-link baseline configuration, the five-link case is characterized by a small loss in signal-to-noise ratio (SNR) in the high-frequency section of the LISA band; the four-link case shows a reduction by a factor of sqrt(2) at low frequencies, and by up to ~2 at high frequencies. The uncertainty in the estimate of polarization, as computed in the Fisher-matrix formalism, also worsens when moving from six to five, and then to four links: this can be explained by the reduced SNR available in those configurations (except for observations shorter than three months, where five and six links do better than four even with the same SNR). In addition, we prove (for generic signals) that the SNR and Fisher matrix are invariant with respect to the choice of a basis of TDI observables; rather, they depend only on which inter-spacecraft and intra-spacecraft measurements are available.Comment: 17 pages, 4 EPS figures, IOP style, corrected CQG versio

LISA Data Analysis using MCMC methods

The Laser Interferometer Space Antenna (LISA) is expected to simultaneously detect many thousands of low frequency gravitational wave signals. This presents a data analysis challenge that is very different to the one encountered in ground based gravitational wave astronomy. LISA data analysis requires the identification of individual signals from a data stream containing an unknown number of overlapping signals. Because of the signal overlaps, a global fit to all the signals has to be performed in order to avoid biasing the solution. However, performing such a global fit requires the exploration of an enormous parameter space with a dimension upwards of 50,000. Markov Chain Monte Carlo (MCMC) methods offer a very promising solution to the LISA data analysis problem. MCMC algorithms are able to efficiently explore large parameter spaces, simultaneously providing parameter estimates, error analyses and even model selection. Here we present the first application of MCMC methods to simulated LISA data and demonstrate the great potential of the MCMC approach. Our implementation uses a generalized F-statistic to evaluate the likelihoods, and simulated annealing to speed convergence of the Markov chains. As a final step we super-cool the chains to extract maximum likelihood estimates, and estimates of the Bayes factors for competing models. We find that the MCMC approach is able to correctly identify the number of signals present, extract the source parameters, and return error estimates consistent with Fisher information matrix predictions.Comment: 14 pages, 7 figure

Characterizing Fishing Effort and Spatial Extent of Coastal Fisheries

Biodiverse coastal zones are often areas of intense fishing pressure due to the high relative density of fishing capacity in these nearshore regions. Although overcapacity is one of the central challenges to fisheries sustainability in coastal zones, accurate estimates of fishing pressure in coastal zones are limited, hampering the assessment of the direct and collateral impacts (e.g., habitat degradation, bycatch) of fishing. We compiled a comprehensive database of fishing effort metrics and the corresponding spatial limits of fisheries and used a spatial analysis program (FEET) to map fishing effort density (measured as boat-meters per km2) in the coastal zones of six ocean regions. We also considered the utility of a number of socioeconomic variables as indicators of fishing pressure at the national level; fishing density increased as a function of population size and decreased as a function of coastline length. Our mapping exercise points to intra and interregional ‘hotspots’ of coastal fishing pressure. The significant and intuitive relationships we found between fishing density and population size and coastline length may help with coarse regional characterizations of fishing pressure. However, spatially-delimited fishing effort data are needed to accurately map fishing hotspots, i.e., areas of intense fishing activity. We suggest that estimates of fishing effort, not just target catch or yield, serve as a necessary measure of fishing activity, which is a key link to evaluating sustainability and environmental impacts of coastal fisheries

Reaching consensus for conserving the global commons: The case of the Ross Sea, Antarctica

In October 2016, the international community made history by adopting the world's largest marine protected area in the Ross Sea, Antarctica&mdash;by consensus. Achieving this feat required trade‐offs and compromise among the 24‐Member States (plus the European Union) comprising the Commission for the Conservation of Antarctic Marine Living Resources. The process took 5 years of intense international negotiations and more than 10 years of scientific planning. Based on interviews with national delegations and other stakeholders, 5 years of participatory observation of Commission meetings (2012&ndash;2016), and analysis of hundreds of documents, we present unique insights that explain the conditions that stalled or facilitated the adoption of the Ross Sea MPA. These included economic interests, geopolitics, an erosion of trust, high‐level diplomacy, and the compromises that were ultimately necessary. We reflect on lessons learned as the world considers how to achieve future large‐scale conservation successes in the global commons.</p