6 resultados para Continuous Variable Systems

em Plymouth Marine Science Electronic Archive (PlyMSEA)


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A simple unit for filtration prior to continuous autoanalysis of highly turbid waters is described. Seawater can be supplied at a rate of 10 ml min−1, after filtration through a 0.45 μm pore-sized membrane filter (47 mm diameter), for at least 45 min from sea water containing 1000 parts/106 of suspended solids.

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Studies relating biodiversity to ecosystem processes typically do not take into account changes in biodiversity through time. Marine systems are highly dynamic, with biodiversity changing at diel, seasonal and inter-decadal timescales. We examined the dynamics of biodiversity in the Gulf of Maine pelagic zooplankton community. Taxonomic data came from the Gulf of Maine continuous plankton recorder (CPR) transect, spanning the years 1961–2006. The CPR transect also contains coincident information on temperature and phytoplankton biomass (measured by the phytoplankton color index). Taxonomic richness varied at all timescales considered. The relationships between temperature and richness, and between phytoplankton and richness, also depended on temporal scale. The temperature–richness relationship was monotonic at the multi-decadal scale, and tended to be hump-shaped at finer scales; the productivity–richness relationship was hump-shaped at the multi-decadal scale, and tended to be monotonic at finer scales. Seasonal biodiversity dynamics were linked to temperature; inter-decadal biodiversity dynamics were linked to phytoplankton.

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A comparison between monthly mean ContinuousPlanktonRecorder (CPR) data and zooplankton data caught during winter and early spring with different sampling devices in the North Sea is presented to estimate the relative error in abundance of CPR measurements. CPR underestimates the abundance of zooplankton by a factor 25 during winter and early spring and by a factor 18 if Oithona spp. is not considered. This has serious implications for estimation of biomass as well as for modelling ecosystem dynamics.

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Diatoms exist in almost every aquatic regime; they are responsible for 20% of global carbon fixation and 25% of global primary production, and are regarded as a key food for copepods, which are subsequently consumed by larger predators such as fish and marine mammals. A decreasing abundance and a vulnerability to climatic change in the North Atlantic Ocean have been reported in the literature. In the present work, a data matrix composed of concurrent satellite remote sensing and Continuous Plankton Recorder (CPR) in situ measurements was collated for the same spatial and temporal coverage in the Northeast Atlantic. Artificial neural networks (ANNs) were applied to recognize and learn the complex non-monotonic and non-linear relationships between diatom abundance and spatiotemporal environmental factors. Because of their ability to mimic non-linear systems, ANNs proved far more effective in modelling the diatom distribution in the marine ecosystem. The results of this study reveal that diatoms have a regular seasonal cycle, with their abundance most strongly influenced by sea surface temperature (SST) and light intensity. The models indicate that extreme positive SSTs decrease diatom abundances regardless of other climatic conditions. These results provide information on the ecology of diatoms that may advance our understanding of the potential response of diatoms to climatic change.