294 resultados para PHYTOPLANKTON PATCHINESS


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Phytoplankton regulate internal pigment concentrations in response to light and nutrient availability. Chlorophyll to carbon ratios (Chl:Cphyto) are commonly reported as a function of growth irradiance (Eg) for evaluating the photoacclimation response of phytoplankton. In contrast to most culture experiments, natural phytoplankton communities experience fluctuating environmental conditions making it difficult to compare field and lab observations. Observing and understanding photoacclimation in nature is important for deciphering changes in Chl:Cphyto resulting from environmental forcings and for accurately estimating net primary production (NPP) in models which rely on a parameterized description of photoacclimation. Here we employ direct analytical measurements of Cphyto and parallel high-resolution biomass estimates from particulate backscattering (bbp) and flow cytometry to investigate Chl:Cphyto in natural phytoplankton communities. Chl:Cphyto observed over a wide range of Eg in the field was consistent with photoacclimation responses inferred from satellite observations. Field-based photoacclimation observations for a mixed natural community contrast with laboratory results for single species grown in continuous light and nutrient replete conditions. Applying a carbon-based net primary production (NPP) model to our field data for a north-south transect in the Atlantic Ocean results in estimates that closely match 14C depth-integrated NPP for the same cruise and with historical records for the distinct biogeographic regions of the Atlantic Ocean. Our results are consistent with previous satellite and model observations of cells growing in natural or fluctuating light and showcase how direct measurements of Cphyto can be applied to explore phytoplankton photophysiology, growth rates, and production at high spatial resolution in-situ.

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This study presents the first in-situ measurements of the chlorophyll a oxidation product, hydroxychlorophyll a as well as the chlorophyll a precursor, chlorophyll aP276 conducted over an annual cycle. Chlorophyll a oxidation products, such as hydroxychlorophyll a may be associated with the decline of algal populations and can act as an initial step in the degradation of chlorophyll a into products which can be found in the geochemical record, important for studying past climate change events. Here, hydroxychlorophyll a and chlorophyll aP276 were measured at the long-term monitoring station L4, Western Channel Observatory (UK, www.westernchannelobservatory.org) over an annual cycle (2012). Weekly measurements of phytoplankton species composition and abundance enabled detailed analysis of possible sources of hydroxychlorophyll a. Dinoflagellates, 2 diatom species, the prymnesiophyte Phaeocystis spp. and the coccolithophorid Emiliania huxleyi were all associated with hydroxychlorophyll a occurrence. However, during alternate peaks in abundance of the diatoms, no association with hydroxychlorophyll a occurred, indicating that the oxidation of chlorophyll a was dependant not only on species but also on additional factors such as the mode of mortality, growth limiting factor (i.e. nutrient concentration) or phenotypic plasticity. Surface sediment samples contained 10 times more hydroxychlorophyll a (relative to chlorophyll a) than pelagic particulate samples, indicating that more chlorophyll a oxidation occurred during sedimentation or at the sediment–water interface, than in the pelagic environment. In addition, chlorophyll aP276 correlated with chl-a concentration, thus supporting its assignment as a chl-a precursor.

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The Baltic Sea is a unique environment as the largest body of brackish water in the world. Acidification of the surface oceans due to absorption of anthropogenic CO2 emissions is an additional stressor facing the pelagic community of the already challenging Baltic Sea. To investigate its impact on trace gas biogeochemistry, a large-scale mesocosm experiment was performed off Tvärminne Research Station, Finland in summer 2012. During the second half of the experiment, dimethylsulphide (DMS) concentrations in the highest fCO2 mesocosms (1075–1333 μatm) were 34 % lower than at ambient CO2 (350 μatm). However the net production (as measured by concentration change) of seven halocarbons analysed was not significantly affected by even the highest CO2 levels after 5 weeks exposure. Methyl iodide (CH3I) and diiodomethane (CH2I2) showed 15 % and 57 % increases in mean mesocosm concentration (3.8 ± 0.6 pmol L−1 increasing to 4.3 ± 0.4 pmol L−1 and 87.4 ± 14.9 pmol L−1 increasing to 134.4 ± 24.1 pmol L−1 respectively) during Phase II of the experiment, which were unrelated to CO2 and corresponded to 30 % lower Chl-ɑ concentrations compared to Phase I. No other iodocarbons increased or showed a peak, with mean chloroiodomethane (CH2ClI) concentrations measured at 5.3 (± 0.9) pmol L−1 and iodoethane (C2H5I) at 0.5 (± 0.1) pmol L−1. Of the concentrations of bromoform (CHBr3; mean 88.1 ± 13.2 pmol L−1), dibromomethane (CH2Br2; mean 5.3 ± 0.8 pmol L−1) and dibromochloromethane (CHBr2Cl, mean 3.0 ± 0.5 pmol L−1), only CH2Br2 showed a decrease of 17 % between Phases I and II, with CHBr3 and CHBr2Cl showing similar mean concentrations in both Phases. Outside the mesocosms, an upwelling event was responsible for bringing colder, high CO2, low pH water to the surface starting on day t16 of the experiment; this variable CO2 system with frequent upwelling events implies the community of the Baltic Sea is acclimated to regular significant declines in pH caused by up to 800 μatm fCO2. After this upwelling, DMS concentrations declined, but halocarbon concentrations remained similar or increased compared to measurements prior to the change in conditions. Based on our findings, with future acidification of Baltic Sea waters, biogenic halocarbon emissions are likely to remain at similar values to today, however emissions of biogenic sulphur could significantly decrease from this region.

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We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll-a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed-layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite-derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low-productivity seasons as well as in sea ice-covered/deep-water regions. Depth-resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption-based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll-a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic-relevant parameters.

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1.There are tens of thousands of species of phytoplankton found throughout the tree of life. Despite this diversity, phytoplankton are often aggregated into a few functional groups according to metabolic traits or biogeochemical role. We investigate the extent to which phytoplankton species dynamics are neutral within functional groups. 2.Seasonal dynamics in many regions of the ocean are known to affect phytoplankton at the functional group level leading to largely predictable patterns of seasonal succession. It is much more difficult to make general statements about the dynamics of individual species. 3.We use a 7 year time-series at station L4 in the Western English Channel with 57 diatom and 17 dinoflagellate species enumerated weekly to test if the abundance of diatom and dinoflagellate species vary randomly within their functional group envelope or if each species is driven uniquely by external factors. 4.We show that the total biomass of the diatom and dinoflagellate functional groups is well predicted by irradiance and temperature and quantify trait values governing the growth rate of both functional groups. The biomass dynamics of the functional groups are not neutral and each has their own distinct responses to environmental forcing. Compared to dinoflagellates, diatoms have faster growth rates, and grow faster under lower irradiance, cooler temperatures, and higher nutrient conditions. 5.The biomass of most species vary randomly within their functional group biomass envelope, most of the time. As a consequence, modelers will find it difficult to predict the biomass of most individual species. Our analysis supports the approach of using a single set of traits for a functional group and suggests that it should be possible to determine these traits from natural communities.

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In 2012, the Western English Channel experienced an unusually large and long-lived phytoplankton spring bloom. When compared with data from the past 20 years, average phytoplankton biomass at Station L4 (part of the Western Channel Observatory) was approximately 3× greater and lasted 50% longer than any previous year. Regular (mostly weekly) box core samples were collected from this site before, during and after the bloom to determine its impact on macrofaunal abundance, diversity, biomass, community structure and function. The spring bloom of 2012 was shown to support a large and rapid response in the majority of benthic taxa and functional groups. However, key differences in the precise nature of this response, as well as in its timing, was observed between different macrofauna feeding groups. Deposit feeders responded almost instantly at the start of the bloom, primarily thorough an increase in abundance. Suspension feeders and opportunistic/predatory/carnivorous taxa responded slightly more slowly and primarily with an increase in biomass. At the end of the bloom a rapid decline in macrobenthic abundance, diversity and biomass closely followed the decline in phytoplankton biomass. With suspension feeders showing evidence of this decline a few weeks before deposit feeders, it was concluded that this collapse in benthic communities was driven primarily by food availability and competition. However, it is possible that environmental hypoxia and the presence of toxic benthic cyanobacteria could also have contributed to this decline. This study shows evidence for strong benthic–pelagic coupling at L4; a shallow (50 m), coastal, fine-sand habitat. It also demonstrates that in such habitats, it is not just planktonic organisms that demonstrate clear community phenology. Different functional groups within the benthic assemblage will respond to the spring bloom in specific manner, with implications for key ecosystem functions and processes, such as secondary production and bioturbation. Only by taking integrated benthic and pelagic observations over such fine temporal scales (weekly) was the current study able to identify the intimate structure of the benthic response. Similar studies from other habitats and under different bloom conditions are urgently needed to fully appreciate the strength of benthic–pelagic coupling in shallow coastal environments.

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Global ocean biogeochemistry models currently employed in climate change projections use highly simplified representations of pelagic food webs. These food webs do not necessarily include critical pathways by which ecosystems interact with ocean biogeochemistry and climate. Here we present a global biogeochemical model which incorporates ecosystem dynamics based on the representation of ten plankton functional types (PFTs); six types of phytoplankton, three types of zooplankton, and heterotrophic bacteria. We improved the representation of zooplankton dynamics in our model through (a) the explicit inclusion of large, slow-growing zooplankton, and (b) the introduction of trophic cascades among the three zooplankton types. We use the model to quantitatively assess the relative roles of iron vs. grazing in determining phytoplankton biomass in the Southern Ocean High Nutrient Low Chlorophyll (HNLC) region during summer. When model simulations do not represent crustacean macrozooplankton grazing, they systematically overestimate Southern Ocean chlorophyll biomass during the summer, even when there was no iron deposition from dust. When model simulations included the developments of the zooplankton component, the simulation of phytoplankton biomass improved and the high chlorophyll summer bias in the Southern Ocean HNLC region largely disappeared. Our model results suggest that the observed low phytoplankton biomass in the Southern Ocean during summer is primarily explained by the dynamics of the Southern Ocean zooplankton community rather than iron limitation. This result has implications for the representation of global biogeochemical cycles in models as zooplankton faecal pellets sink rapidly and partly control the carbon export to the intermediate and deep ocean.

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We examine a model of the rate of phytoplankton production in the ocean and its dependence on depth. The model is analysed as a function of photosynthesis parameters and it is shown that: (i) production profiles with depth are determined uniquely by the parameter values; (ii) daily water column production is not uniquely determined by the parameter values; (iii) a unique combination of parameters exists for which the model best fits a measured production profile. An inverse procedure is developed to recover photosynthesis parameters from measured profiles of primary production, and its performance tested by application to profiles of primary production collected at the Hawaii Ocean Time Series. For each profile tested, the method is successful in recovery of the photosynthesis parameters. The method can be applied to the estimation of photosynthesis parameters from data on in situ production profiles, which have been collected globally for more than half a century, thereby augmenting the world archive of these parameters for application in ecosystem modelling and estimation of primary production from remotely sensed data.