268 research outputs found
\u3ci\u3eCarcinonemertes conanobrieni\u3c/i\u3e - A Nemertean Parasite Infecting the Caribbean Spiny Lobster, \u3ci\u3ePanulirus argus\u3c/i\u3e. Species Description, Host-Use, and Effect on Host Reproductive Health
Marine ecosystems are one of the world’s most heavily used and valuable natural systems. However, over the past decades, they have seen changes in the oceans’ pH, temperature, salinity, and other abiotic factors - all of which appear to have impacted the health of these systems, and there seems to be a global trend indicating that diseases in marine environments are emerging at an increased rate. Infection by a disease can result in a variety of negative effects on the health of a host, all of which are especially relevant in instances where commercially important hosts are infected. Disease can lead to changes in growth, longevity, reproduction, embryo survival, and marketability of a host. One ecologically and commercially important species that appears to have been impacted by this trend of increased disease emergence is the Caribbean spiny lobster, Panulirus argus. Panulirus argus plays host to a number of previously described and newly emergent pathogens. However, here, a new species of nemertean worm belonging to the genus Carcinonemertes is described from egg masses of P. argus from the Florida Keys, Florida, USA. Though P. argus ranges throughout the Caribbean, this worm has thus far only been observed infecting gravid female lobsters in the Florida Keys. This is the first species of Carcinonemertes reported to infect P. argus or any other lobster species in the greater Caribbean and western Atlantic Ocean. To determine the host use, infection prevalence, and infection intensity of this new parasite on P. argus, male, non-gravid female, and gravid female lobsters were captured along the Florida Key reef tract from and examined for infection. Furthermore, infected gravid females were also used in estimating the impact that infection by this nemertean had on three levels of reproductive performance (reproductive output, fecundity, and brood mortality)
Passive Retention/Expulsion Methods for Subcritical Storage of Cryogens
Development of passive retention/expulsion system for subcritical storage of cryogenic material during low gravity situation
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Measurement of Black Carbon and Particle Number Emission Factors from Individual Heavy-Duty Trucks
Emission factors for black carbon (BC) and particle number (PN) were measured from 226 individual heavy-duty (HD) diesel-fueled trucks driving through a 1 km-long California highway tunnel in August 2006. Emission factors were based on concurrent increases in BC, PN, and CO{sub 2}B concentrations (measured at 1 Hz) that corresponded to the passage of individual HD trucks. The distributions of BC and PN emission factors from individual HD trucks are skewed, meaning that a large fraction of pollution comes from a small fraction of the in-use vehicle fleet. The highest-emitting 10% of trucks were responsible for {approx} 40% of total BC and PN emissions from all HD trucks. BC emissions were log-normally distributed with a mean emission factor of 1.7 g kg {sup -1} and maximum values of {approx} 10 g kg{sup -1}. Corresponding values for PN emission factors were 4.7 x 10{sup 15} and 4 x 10{sup 16} kg{sup -1}. There was minimal overlap among high-emitters of these two pollutants: only 1 of the 226 HD trucks measured was found to be among the highest 10% for both BC and PN. Monte Carlo resampling of the distribution of BC emission factors observed in this study revealed that uncertainties (1{sigma}) in extrapolating from a random sample of n HD trucks to a population mean emission factor ranged from {+-} 43% for n = 10 to {+-} 8% for n = 300, illustrating the importance of sufficiently large vehicle sample sizes in emissions studies. Studies with low sample sizes are also more easily biased due to misrepresentation of high-emitters. As vehicles become cleaner on average in future years, skewness of the emissions distributions will increase, and thus sample sizes needed to extrapolate reliably from a subset of vehicles to the entire in-use vehicle fleet are expected to become more of a challenge
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