Terrestrial vertabrates of Scotts Bluff National Monument, Nebraska

A survey of terrestrial vertebrates was conducted at the Scotts Bluff National Monument (SBNM), Nebraska, to determine species composition, relative abundance, and distribution by habitat of the existing amphibians, reptiles, birds, and mammals. Various sampling methods were used to detect animal species richness and to estimate population densities. The seven major habitat types at SBNM contained 4 species of amphibians, 8 reptiles, 96 birds, and 28 mammals. The only endangered or threatened species observed was a dead bald eagle ( Haliaeetus leucocephalus ). The racer ( Coluber constrictor ) and prairie rattlesnake ( Crotalus viridis ) were the two most abundant snakes. The prairie falcon ( Falco mexicanus ) was a common raptor that nested in Scotts Bluff. Sympatric populations of mule deer ( Odocoileus hemionus ) and white-tailed deer ( Odocoileus virginianus ) appeared to be hybridizing. The riverine woodland contained the greatest number of fauna species with only 4% surface area of SBNM. Sharp-tailed grouse ( Tympanuchus phasianellus ) and pronghorn antelope ( Antilocapra americana ), absent from the Monument, are two potential native species for reintroduction.     

Volatility forecasting with double Markov switching GARCH models

This paper investigates inference and volatility forecasting using a Markov switching heteroscedastic model with a fat‐tailed error distribution to analyze asymmetric effects on both the conditional mean and conditional volatility of financial time series. The motivation for extending the Markov switching GARCH model, previously developed to capture mean asymmetry, is that the switching variable, assumed to be a first‐order Markov process, is unobserved. The proposed model extends this work to incorporate Markov switching in the mean and variance simultaneously. Parameter estimation and inference are performed in a Bayesian framework via a Markov chain Monte Carlo scheme. We compare competing models using Bayesian forecasting in a comparative value‐at‐risk study. The proposed methods are illustrated using both simulations and eight international stock market return series. The results generally favor the proposed double Markov switching GARCH model with an exogenous variable. Copyright © 2008 John Wiley & Sons, Ltd.     

The decline and fate of an iron-induced subarctic phytoplankton bloom

Iron supply has a key role in stimulating phytoplankton blooms in high-nitrate low-chlorophyll oceanic waters. However, the fate of the carbon fixed by these blooms, and how efficiently it is exported into the ocean's interior, remains largely unknown. Here we report on the decline and fate of an iron-stimulated diatom bloom in the Gulf of Alaska. The bloom terminated on day 18, following the depletion of iron and then silicic acid, after which mixed-layer particulate organic carbon (POC) concentrations declined over six days. Increased particulate silica export via sinking diatoms was recorded in sediment traps at depths between 50 and 125 m from day 21, yet increased POC export was not evident until day 24. Only a small proportion of the mixed-layer POC was intercepted by the traps, with more than half of the mixed-layer POC deficit attributable to bacterial remineralization and mesozooplankton grazing. The depletion of silicic acid and the inefficient transfer of iron-increased POC below the permanent thermocline have major implications both for the biogeochemical interpretation of times of greater iron supply in the geological past, and also for proposed geo-engineering schemes to increase oceanic carbon sequestration.     

C. elegans ORFeome version 1.1: experimental verification of the genome annotation and resource for proteome-scale protein expression

To verify the genome annotation and to create a resource to functionally characterize the proteome, we attempted to Gateway-clone all predicted protein-encoding open reading frames (ORFs), or the 'ORFeome,' of Caenorhabditis elegans. We successfully cloned approximately 12,000 ORFs (ORFeome 1.1), of which roughly 4,000 correspond to genes that are untouched by any cDNA or expressed-sequence tag (EST). More than 50% of predicted genes needed corrections in their intron-exon structures. Notably, approximately 11,000 C. elegans proteins can now be expressed under many conditions and characterized using various high-throughput strategies, including large-scale interactome mapping. We suggest that similar ORFeome projects will be valuable for other organisms, including humans.     

Type II supernovae as a significant source of interstellar dust

Large amounts of dust (>10(8)M(o)) have recently been discovered in high-redshift quasars and galaxies corresponding to a time when the Universe was less than one-tenth of its present age. The stellar winds produced by stars in the late stages of their evolution (on the asymptotic giant branch of the Hertzsprung-Russell diagram) are thought to be the main source of dust in galaxies, but they cannot produce that dust on a short enough timescale (&<1 Gyr) to explain the results in the high-redshift galaxies. Supernova explosions of massive stars (type II) are also a potential source, with models predicting 0.2-4M(o) of dust. As massive stars evolve rapidly, on timescales of a few Myr, these supernovae could be responsible for the high-redshift dust. Observations of supernova remnants in the Milky Way, however, have hitherto revealed only 10(-7)-10(-3)M(o) each, which is insufficient to explain the high-redshift data. Here we report the detection of approximately 2-4M(o) of cold dust in the youngest known Galactic supernova remnant, Cassiopeia A. This observation implies that supernovae are at least as important as stellar winds in producing dust in our Galaxy and would have been the dominant source of dust at high redshifts.     

Defects in whirlin,a PDZ domain molecule involved in stereocilia elongation,cause deafness in the whirler mouse and families with DFNB31

The whirler mouse mutant (wi) does not respond to sound stimuli, and detailed ultrastructural analysis of sensory hair cells in the organ of Corti of the inner ear indicates that the whirler gene encodes a protein involved in the elongation and maintenance of stereocilia in both inner hair cells (IHCs) and outer hair cells (OHCs). BAC-mediated transgene correction of the mouse phenotype and mutation analysis identified the causative gene as encoding a novel PDZ protein called whirlin. The gene encoding whirlin also underlies the human autosomal recessive deafness locus DFNB31. In the mouse cochlea, whirlin is expressed in the sensory IHC and OHC stereocilia. Our findings suggest that this novel PDZ domain-containing molecule acts as an organizer of submembranous molecular complexes that control the coordinated actin polymerization and membrane growth of stereocilia.     

From genomics to proteomics

Proteomics is the study of the function of all expressed proteins. Tremendous progress has been made in the past few years in generating large-scale data sets for protein-protein interactions, organelle composition, protein activity patterns and protein profiles in cancer patients. But further technological improvements, organization of international proteomics projects and open access to results are needed for proteomics to fulfil its potential.     

Insect communication: 'no entry' signal in ant foraging

Forager ants lay attractive trail pheromones to guide nestmates to food, but the effectiveness of foraging networks might be improved if pheromones could also be used to repel foragers from unrewarding routes. Here we present empirical evidence for such a negative trail pheromone, deployed by Pharaoh's ants (Monomorium pharaonis) as a 'no entry' signal to mark an unrewarding foraging path. This finding constitutes another example of the sophisticated control mechanisms used in self-organized ant colonies.     

Statistical analyses of freeway traffic flows

This paper concerns the exploration of statistical models for the analysis of observational freeway flow data, and the development of empirical models to capture and predict short‐term changes in traffic flow characteristics on sequences of links in a partially detectorized freeway network. A first set of analyses explores regression models for minute‐by‐minute traffic flows, taking into account time of day, day of the week, and recent upstream detector‐based flows. Day‐ and link‐specific random effects are used in a hierarchical statistical modelling framework. A second set of analyses captures day‐specific idiosyncrasies in traffic patterns by including parameters that may vary throughout the day. Model fit and short‐term predictions of flows are thus improved significantly. A third set of analyses includes recent downstream flows as additional predictors. These further improvements, though marginal in most cases, can be quite radically useful in cases of very marked breakdown of freeway flows on some links. These three modelling stages are described and developed in analyses of observational flow data from a set of links on Interstate Highway 5 (I‐5) near Seattle. Copyright © 2002 John Wiley & Sons, Ltd.