752 resultados para Microzooplankton


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Oceanic dimethyl sulfide (DMS) is the enzymatic cleavage product of the algal metabolite dimethylsulfoniopropionate (DMSP) and is the most abundant form of sulfur released into the atmosphere. To investigate the effects of two emerging environmental threats (ocean acidification and warming) on marine DMS production, we performed a large-scale perturbation experiment in a coastal environment. At both ambient temperature and 2 °C warmer, an increase in partial pressure of carbon dioxide (pCO2) in seawater (160-830 ppmv pCO2) favored the growth of large diatoms, which outcompeted other phytoplankton species in a natural phytoplankton assemblage and reduced the growth rate of smaller, DMSP-rich phototrophic dinoflagellates. This decreased the grazing rate of heterotrophic dinoflagellates (ubiquitous micrograzers), resulting in reduced DMS production via grazing activity. Both the magnitude and sign of the effect of pCO2 on possible future oceanic DMS production were strongly linked to pCO2-induced alterations to the phytoplankton community and the cellular DMSP content of the dominant species and its association with micrograzers.

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The Deep Convection cruise repeatedly sampled two locations in the North Atlantic, sited in the Iceland and Norwegian Basins, onboard the RV Meteor (19 March - 2 May 2012). Samples were collected from multiple casts of a conductivity-temperature-depth (CTD) - Niskin rosette at each station. Water samples for primary production rates, community structure, chlorophyll a [Chl a], calcite [PIC], particulate organic carbon [POC] and biogenic silicic acid [BSi] were collected from predawn casts from six light depths (55%, 20%, 14%, 7%, 5% and 1% of incident PAR). Additional samples for community structure and ancillary parameters were collected from a second cast. Carbon fixation rates were determined using the 13C stable isotope method. Water samples for diatom and micro zooplankton counts, collected from the predawn casts, were preserved with acidic Lugol's solution (2% final solution) and counted using an inverted light microscope. Water samples for coccolithophore counts were collected onto cellulose nitrate filters and counted using polarising light microscopy. Water samples for Chl a analysis were filtered onto MF300 and polycarbonate filters and extracted in 90% acetone. PIC and BSi samples were filtered onto polycarbonate filters and analysed using an inductively coupled plasma emission optical spectrometer and a SEAL QuAAtro autoanalyser respectively.

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Global warming and ocean acidification are among the most important stressors for aquatic ecosystems in the future. To investigate their direct and indirect effects on a near-natural plankton community, a multiple-stressor approach is needed. Hence, we set up mesocosms in a full-factorial design to study the effects of both warming and high CO2 on a Baltic Sea autumn plankton community, concentrating on the impacts on microzooplankton (MZP). MZP abundance, biomass, and species composition were analysed over the course of the experiment. We observed that warming led to a reduced time-lag between the phytoplankton bloom and an MZP biomass maximum. MZP showed a significantly higher growth rate and an earlier biomass peak in the warm treatments while the biomass maximum was not affected. Increased pCO2 did not result in any significant effects on MZP biomass, growth rate, or species composition irrespective of the temperature, nor did we observe any significant interactions between CO2 and temperature. We attribute this to the high tolerance of this estuarine plankton community to fluctuations in pCO2, often resulting in CO2 concentrations higher than the predicted end-of-century concentration for open oceans. In contrast, warming can be expected to directly affect MZP and strengthen its coupling with phytoplankton by enhancing its grazing pressure.

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In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2015) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation is 2016-10-12.