964 resultados para Marine plankton


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57 bacterial strains isolated from marine plankton and mud from the inshore waters of Cochin, are described. The flora of the plankton was dominated by chromogens while mud sample and failed to produce chromogens. The different strains are divided into five arbitrary groups for the convenience of description. The flora is similar to that of Mandapam (east coast) while it differed from the flora of Calicut (west coast) in the paucity of Bacillus and other spore formers.

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Understanding how climate change will affect the planet is a key issue worldwide. Questions concerning the pace and impacts of climate change are thus central to many ecological and biogeochemical studies, and addressing the consequences of climate change is now high on the list of priorities for funding agencies. Here, we review the interactions between climate change and plankton communities, focusing on systematic changes in plankton community structure, abundance, distribution and phenology over recent decades. We examine the potential socioeconomic impacts of these plankton changes, such as the effects of bottom-up forcing on commercially exploited fish stocks (i.e. plankton as food for fish). We also consider the crucial roles that plankton might have in dictating the future pace of climate change via feedback mechanisms responding to elevated atmospheric CO sub(2) levels. An important message emerges from this review: ongoing plankton monitoring programmes worldwide will act as sentinels to identify future changes in marine ecosystems.

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Over the last few decades, global warming has accelerated both the rate and magnitude of changes observed in many functional units of the Earth System. In this context, plankton are sentinel organisms because they are sensitive to subtle levels of changes in temperature and might help in identifying the current effects of climate change on pelagic ecosystems. In this paper, we performed a comparative approach in two regions of the North Atlantic (i.e. the Northeast Atlantic and the North Sea) to explore the relationships between changes in marine plankton, the regional physico-chemical environment and large-scale hydro-climatic forcing using four key indices: the North Atlantic Oscillation (NAO), the Atlantic Multidecadal Oscillation (AMO), the East Atlantic (EA) pattern and Northern Hemisphere Temperature (NHT) anomalies. Our analyses suggest that long-term changes in the states of the two ecosystems were synchronous and correlated to the same large-scale hydro-climatic variables: NHT anomalies, the AMO and to a lesser extent the EA pattern. No significant correlation was found between long-term ecosystem modifications and the state of the NAO. Our results suggest that the effect of climate on these ecosystems has mainly occurred in both regions through the modulation of the thermal regime.

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The number of variables involved in the monitoring of an ecosystem can be high and often one of the first stages in the analysis is to reduce the number of variables. We describe a method developed for geological purposes, using the information theory, that enables selection of the most relevant variables. This technique also allows the examination of the asymmetrical relationships between variables. Applied to a set of physical and biological variables (plankton assemblages in four areas of the North Sea), the method shows that biological variables are more informative than physical variables although the controlling factors are mainly physical (sea surface temperature in winter and spring). Among biological variables, diversity measures and warm-water species assemblages are informative for the state of the North Sea pelagic ecosystems while among physical variables sea surface temperature in late winter and early spring are highly informative. Although often used in bioclimatology, the utilisation of the North Atlantic Oscillation (NAO) index does not seem to provide a lot of information. The method reveals that only the extreme states of this index has an influence on North Sea pelagic ecosystems. The substantial and persistent changes that were detected in the dynamic regime of the North Sea ecosystems and called regime shift are detected by the method and corresponds to the timing of other shifts described in the literature for some European Systems such as the Baltic and the Mediterranean Sea when both physical and biological variables are considered.

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Increasing availability and extent of biological ocean time series (from both in situ and satellite data) have helped reveal significant phenological variability of marine plankton. The extent to which the range of this variability is modified as a result of climate change is of obvious importance. Here we summarize recent research results on phenology of both phytoplankton and zooplankton. We suggest directions to better quantify and monitor future plankton phenology shifts, including (i) examining the main mode of expected future changes (ecological shifts in timing and spatial distribution to accommodate fixed environmental niches vs. evolutionary adaptation of timing controls to maintain fixed biogeography and seasonality), (ii) broader understanding of phenology at the species and community level (e.g. for zooplankton beyond Calanus and for phytoplankton beyond chlorophyll), (iii) improving and diversifying statistical metrics for indexing timing and trophic synchrony and (iv) improved consideration of spatio-temporal scales and the Lagrangian nature of plankton assemblages to separate time from space changes.

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We examined how marine plankton interaction networks, as inferred by multivariate autoregressive (MAR) analysis of time-series, differ based on data collected at a fixed sampling location (L4 station in the Western English Channel) and four similar time-series prepared by averaging Continuous Plankton Recorder (CPR) datapoints in the region surrounding the fixed station. None of the plankton community structures suggested by the MAR models generated from the CPR datasets were well correlated with the MAR model for L4, but of the four CPR models, the one most closely resembling the L4 model was that for the CPR region nearest to L4. We infer that observation error and spatial variation in plankton community dynamics influenced the model performance for the CPR datasets. A modified MAR framework in which observation error and spatial variation are explicitly incorporated could allow the analysis to better handle the diverse time-series data collected in marine environments.

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Programa de doctorado en Oceanografía. La fecha de publicación es la fecha de lectura