154 research outputs found

    Assessing movements of three buoy line types using DSTmilli Loggers: Implications for entanglements of bottlenose dolphins in the crab pot fishery

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    A study was conducted in October 2006 in the Charleston, South Carolina area to test the movements of three different buoy line types to determine which produced a preferred profile that could reduce the risk of dolphin entanglement. Tests on diamond-braided nylon commonly used in the crab pot fishery were compared with stiffened line of Esterpro and calf types in both shallow and deep water environments using DSTmilli data loggers. Loggers were placed at intervals along the lines to record depth, and thus movements, over a 24 hour period. Three observers viewed video animations and charts created for each of the six trial days from the collected logger data and provided their opinions on the most desirable line type that fit set criteria. A quantitative analysis (ANCOVA) of the data was conducted taking into consideration daily tidal fluctuations and logger movements. Loggers tracking the tides had an r2 value approaching 1.00 and produced little movement other than with the tides. Conversely, r2 values approaching 0.00 were less affected by tidal movement and influenced by currents that cause more erratic movement. Results from this study showed that stiffened line, in particular the medium lay Esterpro type, produced the more desirable profiles that could reduce risk of dolphin entanglement. Combining the observer’s results with the ANCOVA results, Esterpro was chosen nearly 60% of the time as opposed to the nylon line which was only chosen 10% of the time. ANCOVA results showed that the stiffened lines performed better in both the shallow and deep water environments, while the nylon line only performed better during one trial in a deep water set, most probably due to the increased current velocities experienced that day. (58pp.)(PDF contains 68 pages

    Where were they from? Modelling the source stock of dolphins stranded after the Deepwater Horizon oil spill using genetic and stable isotope data

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    Understanding the source stock of common bottlenose dolphins Tursiops truncatus that stranded in the northern Gulf of Mexico subsequent to the Deepwater Horizon oil spill was essential to accurately quantify injury and apportion individuals to the appropriate stock. The aim of this study, part of the Natural Resource Damage Assessment (NRDA), was to estimate the proportion of the 932 recorded strandings between May 2010 and June 2014 that came from coastal versus bay, sound and estuary (BSE) stocks. Four sources of relevant information were available on overlapping subsets totaling 336 (39%) of the strandings: genetic stock assignment, stable isotope ratios, photo-ID and individual genetic-ID. We developed a hierarchical Bayesian model for combining these sources that weighted each data source for each stranding according to a measure of estimated precision: the effective sample size (ESS). The photo- and genetic-ID data were limited and considered to potentially introduce biases, so these data sources were excluded from analyses used in the NRDA. Estimates were calculated separately in 3 regions: East (of the Mississippi outflow), West (of the Mississippi outflow through Vermilion Bay, Louisiana) and Western Louisiana (west of Vermilion Bay to the Texas-Louisiana border); the estimated proportions of coastal strandings were, respectively 0.215 (95% CI: 0.169-0.263), 0.016 (0.036-0.099) and 0.622 (0.487-0.803). This method represents a general approach for integrating multiple sources of information that have differing uncertainties.Publisher PDFPeer reviewe

    Survival, density, and abundance of common bottlenose dolphins in Barataria Bay (USA) following the Deepwater Horizon oil spill

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    To assess potential impacts of the Deepwater Horizon oil spill in April 2010, we conducted boat-based photo-identification surveys for common bottlenose dolphins Tursiops truncatus in Barataria Bay, Louisiana, USA (~230 km2, located 167 km WNW of the spill center). Crews logged 838 h of survey effort along pre-defined routes on 10 occasions between late June 2010 and early May 2014. We applied a previously unpublished spatial version of the robust design capture-recapture model to estimate survival and density. This model used photo locations to estimate density in the absence of study area boundaries and to separate mortality from permanent emigration. To estimate abundance, we applied density estimates to saltwater (salinity > ~8 ppt) areas of the bay where telemetry data suggested that dolphins reside. Annual dolphin survival varied between 0.80 and 0.85 (95% CIs varied from 0.77 to 0.90) over 3 yr following the Deepwater Horizon spill. In 2 non-oiled bays (in Florida and North Carolina), historic survival averages approximately 0.95. From June to November 2010, abundance increased from 1300 (95% CI ± ~130) to 3100 (95% CI ± ~400), then declined and remained between ~1600 and ~2400 individuals until spring 2013. In fall 2013 and spring 2014, abundance increased again to approximately 3100 individuals. Dolphin abundance prior to the spill was unknown, but we hypothesize that some dolphins moved out of the sampled area, probably northward into marshes, prior to initiation of our surveys in late June 2010, and later immigrated back into the sampled area.Publisher PDFPeer reviewe

    Bringing metabolic networks to life: convenience rate law and thermodynamic constraints

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    BACKGROUND: Translating a known metabolic network into a dynamic model requires rate laws for all chemical reactions. The mathematical expressions depend on the underlying enzymatic mechanism; they can become quite involved and may contain a large number of parameters. Rate laws and enzyme parameters are still unknown for most enzymes. RESULTS: We introduce a simple and general rate law called "convenience kinetics". It can be derived from a simple random-order enzyme mechanism. Thermodynamic laws can impose dependencies on the kinetic parameters. Hence, to facilitate model fitting and parameter optimisation for large networks, we introduce thermodynamically independent system parameters: their values can be varied independently, without violating thermodynamical constraints. We achieve this by expressing the equilibrium constants either by Gibbs free energies of formation or by a set of independent equilibrium constants. The remaining system parameters are mean turnover rates, generalised Michaelis-Menten constants, and constants for inhibition and activation. All parameters correspond to molecular energies, for instance, binding energies between reactants and enzyme. CONCLUSION: Convenience kinetics can be used to translate a biochemical network – manually or automatically - into a dynamical model with plausible biological properties. It implements enzyme saturation and regulation by activators and inhibitors, covers all possible reaction stoichiometries, and can be specified by a small number of parameters. Its mathematical form makes it especially suitable for parameter estimation and optimisation. Parameter estimates can be easily computed from a least-squares fit to Michaelis-Menten values, turnover rates, equilibrium constants, and other quantities that are routinely measured in enzyme assays and stored in kinetic databases

    Bartonella species detection in captive, stranded and free-ranging cetaceans

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    We present prevalence of Bartonella spp. for multiple cohorts of wild and captive cetaceans. One hundred and six cetaceans including 86 bottlenose dolphins (71 free-ranging, 14 captive in a facility with a dolphin experiencing debility of unknown origin, 1 stranded), 11 striped dolphins, 4 harbor porpoises, 3 Risso's dolphins, 1 dwarf sperm whale and 1 pygmy sperm whale (all stranded) were sampled. Whole blood (n = 95 live animals) and tissues (n = 15 freshly dead animals) were screened by PCR (n = 106 animals), PCR of enrichment cultures (n = 50 animals), and subcultures (n = 50 animals). Bartonella spp. were detected from 17 cetaceans, including 12 by direct extraction PCR of blood or tissues, 6 by PCR of enrichment cultures, and 4 by subculture isolation. Bartonella spp. were more commonly detected from the captive (6/14, 43%) than from free-ranging (2/71, 2.8%) bottlenose dolphins, and were commonly detected from the stranded animals (9/21, 43%; 3/11 striped dolphins, 3/4 harbor porpoises, 2/3 Risso's dolphins, 1/1 pygmy sperm whale, 0/1 dwarf sperm whale, 0/1 bottlenose dolphin). Sequencing identified a Bartonella spp. most similar to B. henselae San Antonio 2 in eight cases (4 bottlenose dolphins, 2 striped dolphins, 2 harbor porpoises), B. henselae Houston 1 in three cases (2 Risso's dolphins, 1 harbor porpoise), and untyped in six cases (4 bottlenose dolphins, 1 striped dolphin, 1 pygmy sperm whale). Although disease causation has not been established, Bartonella species were detected more commonly from cetaceans that were overtly debilitated or were cohabiting in captivity with a debilitated animal than from free-ranging animals. The detection of Bartonella spp. from cetaceans may be of pathophysiological concern

    iQuantitator: A tool for protein expression inference using iTRAQ

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    <p>Abstract</p> <p>Background</p> <p>Isobaric Tags for Relative and Absolute Quantitation (iTRAQ™) [Applied Biosystems] have seen increased application in differential protein expression analysis. To facilitate the growing need to analyze iTRAQ data, especially for cases involving multiple iTRAQ experiments, we have developed a modeling approach, statistical methods, and tools for estimating the relative changes in protein expression under various treatments and experimental conditions.</p> <p>Results</p> <p>This modeling approach provides a unified analysis of data from multiple iTRAQ experiments and links the observed quantity (reporter ion peak area) to the experiment design and the calculated quantity of interest (treatment-dependent protein and peptide fold change) through an additive model under log transformation. Others have demonstrated, through a case study, this modeling approach and noted the computational challenges of parameter inference in the unbalanced data set typical of multiple iTRAQ experiments. Here we present the development of an inference approach, based on hierarchical regression with batching of regression coefficients and Markov Chain Monte Carlo (MCMC) methods that overcomes some of these challenges. In addition to our discussion of the underlying method, we also present our implementation of the software, simulation results, experimental results, and sample output from the resulting analysis report.</p> <p>Conclusion</p> <p>iQuantitator's process-based modeling approach overcomes limitations in current methods and allows for application in a variety of experimental designs. Additionally, hypertext-linked documents produced by the tool aid in the interpretation and exploration of results.</p

    PhosPhAt: the Arabidopsis thaliana phosphorylation site database. An update

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    The PhosPhAt database of Arabidopsis phosphorylation sites was initially launched in August 2007. Since then, along with 10-fold increase in database entries, functionality of PhosPhAt (phosphat.mpimp-golm.mpg.de) has been considerably upgraded and re-designed. PhosPhAt is now more of a web application with the inclusion of advanced search functions allowing combinatorial searches by Boolean terms. The results output now includes interactive visualization of annotated fragmentation spectra and the ability to export spectra and peptide sequences as text files for use in other applications. We have also implemented dynamic links to other web resources thus augmenting PhosPhAt-specific information with external protein-related data. For experimental phosphorylation sites with information about dynamic behavior in response to external stimuli, we display simple time-resolved diagrams. We have included predictions for pT and pY sites and updated pS predictions. Access to prediction algorithm now allows ‘on-the-fly’ prediction of phosphorylation of any user-uploaded protein sequence. Protein Pfam domain structures are now mapped onto the protein sequence display next to experimental and predicted phosphorylation sites. Finally, we have implemented functional annotation of proteins using MAPMAN ontology. These new developments make the PhosPhAt resource a useful and powerful tool for the scientific community as a whole beyond the plant sciences
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