5 resultados para diffuse uterine myohypertrophy

em Plymouth Marine Science Electronic Archive (PlyMSEA)


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The vent mussel Bathymodiolus puteoserpentis, a large vesicomyid clam and a smaller thyasirid were collected from an area of sediment subject to diffuse hydrothermal flow. The mussels live on the surface, the vesicomyids are partly buried and the thyasirids burrow in the sediment. The fine structure of the gills differs in the three bivalves. Bathymodiolus puteoserpentis hosts two types of bacterial symbiont, one methanotrophic, and another probably thiotrophic. The other two bivalves have single types of symbiont of different shapes. Stable isotope ratios of carbon and nitrogen indicate thiotrophy in the vesicomyid and thyasirid, but a predominance of methanotrophy in the mussel. This is the first time that such an assemblage has been found at a hydrothermal site on the Mid-Atlantic Ridge (MAR), with the different faunistic elements exploiting different energy resources

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Satellite-derived remote-sensing reflectance (Rrs) can be used for mapping biogeochemically relevant variables, such as the chlorophyll concentration and the Inherent Optical Properties (IOPs) of the water, at global scale for use in climate-change studies. Prior to generating such products, suitable algorithms have to be selected that are appropriate for the purpose. Algorithm selection needs to account for both qualitative and quantitative requirements. In this paper we develop an objective methodology designed to rank the quantitative performance of a suite of bio-optical models. The objective classification is applied using the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Using in situRrs as input to the models, the performance of eleven semi-analytical models, as well as five empirical chlorophyll algorithms and an empirical diffuse attenuation coefficient algorithm, is ranked for spectrally-resolved IOPs, chlorophyll concentration and the diffuse attenuation coefficient at 489 nm. The sensitivity of the objective classification and the uncertainty in the ranking are tested using a Monte-Carlo approach (bootstrapping). Results indicate that the performance of the semi-analytical models varies depending on the product and wavelength of interest. For chlorophyll retrieval, empirical algorithms perform better than semi-analytical models, in general. The performance of these empirical models reflects either their immunity to scale errors or instrument noise in Rrs data, or simply that the data used for model parameterisation were not independent of NOMAD. Nonetheless, uncertainty in the classification suggests that the performance of some semi-analytical algorithms at retrieving chlorophyll is comparable with the empirical algorithms. For phytoplankton absorption at 443 nm, some semi-analytical models also perform with similar accuracy to an empirical model. We discuss the potential biases, limitations and uncertainty in the approach, as well as additional qualitative considerations for algorithm selection for climate-change studies. Our classification has the potential to be routinely implemented, such that the performance of emerging algorithms can be compared with existing algorithms as they become available. In the long-term, such an approach will further aid algorithm development for ocean-colour studies.

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Socio-economic development in Europe has exerted increasing pressure on the marine environment. Eutrophication, caused by nutrient enrichment, is evident in regions of all European seas. Its severity varies but has, in places, adversely impacted socio-economic activities. This paper aims to evaluate the effectiveness of recently adopted policies to reduce anthropogenic nutrient inputs to European seas. Nitrogen and phosphorus budgets were constructed for three different periods (prior to severe eutrophication, during severe eutrophication and contemporary) to capture changes in the relative importance of different nutrient sources in four European seas suffering from eutrophication (Baltic Proper, coastal North Sea, Northern Adriatic and North-Western Black Sea Shelf). Policy success is evident for point sources, notably for P in the Baltic and North Seas, but reduction of diffuse sources has been more problematic.

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In this paper we evaluate whether the assimilation of remotely-sensed optical data into a marine ecosystem model improves the simulation of biogeochemistry in a shelf sea. A localized Ensemble Kalman filter was used to assimilate weekly diffuse light attenuation coefficient data, Kd(443) from SeaWiFs, into an ecosystem model of the western English Channel. The spatial distributions of (unassimilated) surface chlorophyll from satellite, and a multivariate time series of eighteen biogeochemical and optical variables measured in situ at one long-term monitoring site were used to evaluate the system performance for the year 2006. Assimilation reduced the root mean square error and improved the correlation with the assimilated Kd(443) observations, for both the analysis and, to a lesser extent, the forecast estimates, when compared to the reference model simulation. Improvements in the simulation of (unassimilated) ocean colour chlorophyll were less evident, and in some parts of the Channel the simulation of this data deteriorated. The estimation errors for the (unassimilated) in situ data were reduced for most variables with some exceptions, e.g. dissolved nitrogen. Importantly, the assimilation adjusted the balance of ecosystem processes by shifting the simulated food web towards the microbial loop, thus improving the estimation of some properties, e.g. total particulate carbon. Assimilation of Kd(443) outperformed a comparative chlorophyll assimilation experiment, in both the estimation of ocean colour data and in the simulation of independent in situ data. These results are related to relatively low error in Kd(443) data, and because it is a bulk optical property of marine ecosystems. Assimilation of remotely-sensed optical properties is a promising approach to improve the simulation of biogeochemical and optical variables that are relevant for ecosystem functioning and climate change studies.