18 resultados para Foliar C:N:P Stoichiometry

em Plymouth Marine Science Electronic Archive (PlyMSEA)


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The combined consequences of the multi-stressors of pH and nutrient availability upon the growth of a marine diatom were investigated. Thalassiosira weissflogii was grown in N- or P-limited batch culture in sealed systems, with pH commencing at 8.2 (extant conditions) or 7.6 (ocean acidification [OA] conditions), and then pH was allowed to either drift with growth, or was held fixed. Results indicated that within the pH range tested, the stability of environmental pH rather than its value (i.e., OA vs. extant) fundamentally influenced biomass accumul-ation and C:N:P stoichiometry. Despite large changes in total alkalinity in the fixed pH systems, final biomass production was consistently greater in these systems than that in drifting pH systems. In drift systems, pH increased to exceed pH 9.5, a level of alkalinity that was inhibitory to growth. No statis-tically significant differences between pH treatments were measured for N:C, P:C or N:P ratios during nutrient-replete growth, although the diatom expre-ssed greater plasticity in P:C and N:P ratios than in N:C during this growth phase. During nutrient-deplete conditions, the capacity for uncoupled carbon fixa-tion at fixed pH was considerably greater than that measured in drift pH systems, leading to strong contrasts in C:N:P stoichiometry between these treatments. Whether environmental pH was stable or drifted directly influenced the extent of physiological stress. In contrast, few distinctions could be drawn between extant versus OA conditions for cell physiology.

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Light (20-450 μmol photons m-2 s-1), temperature (3-11°C) and inorganic nutrient composition (nutrient replete and N, P and Si limitation) were manipulated to study their combined influence on growth, stoichiometry (C:N:P:Chl a) and primary production of the cold water diatom Chaetoceros wighamii. During exponential growth, the maximum growth rate (~0.8 d-1) was observed at high temperture and light; at 3°C the growth rate was ~30% lower under similar light conditions. The interaction effect of light and temperature were clearly visible from growth and cellular stoichiometry. The average C:N:P molar ratio was 80:13:1 during exponential growth, but the range, due to different light acclimation, was widest at the lowest temperature, reaching very low C:P (~50) and N:P ratios (~8) at low light and temperature. The C:Chl a ratio had also a wider range at the lowest temperature during exponential growth, ranging 16-48 (weight ratio) at 3°C compared with 17-33 at 11°C. During exponential growth, there was no clear trend in the Chl a normalized, initial slope (α*) of the photosynthesis-irradiance (PE) curve, but the maximum photosynthetic production (Pm) was highest for cultures acclimated to the highest light and temperature. During the stationary growth phase, the stoichiometric relationship depended on the limiting nutrient, but with generally increasing C:N:P ratio. The average photosynthetic quotient (PQ) during exponential growth was 1.26 but decreased to <1 under nutrient and light limitation, probably due to photorespiration. The results clearly demonstrate that there are interaction effects between light, temperature and nutrient limitation, and the data suggests greater variability of key parameters at low temperature. Understanding these dynamics will be important for improving models of aquatic primary production and biogeochemical cycles in a warming climate.

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The controls on the 'Redfield' N:P stoichiometry of marine phytoplankton and hence the N:P ratio of the deep ocean remain incompletely understood. Here, we use a model for phytoplankton ecophysiology and growth, based on functional traits and resource-allocation trade-offs, to show how environmental filtering, biotic interactions, and element cycling in a global ecosystem model determine phytoplankton biogeography, growth strategies and macromolecular composition. Emergent growth strategies capture major observed patterns in marine biomes. Using a new synthesis of experimental RNA and protein measurements to constrain per-ribosome translation rates, we determine a spatially variable lower limit on adaptive rRNA:protein allocation and hence on the relationship between the largest cellular P and N pools. Comparison with the lowest observed phytoplankton N:P ratios and N:P export fluxes in the Southern Ocean suggests that additional contributions from phospholipid and phosphorus storage compounds play a fundamental role in determining the marine biogeochemical cycling of these elements.

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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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The vertical distribution of decapod larvae off the northwest Portuguese coast was analysed in relation to associated environmental conditions from sampling during a 69 h period around a current meter mooring located on the shelf, approximately 21 km off the coast. Plankton samples were collected every 2 h at the surface with a neuston net and through the water column with a Longhurst Hardy Plankton Recorder (Pro-LHPR), allowing a very detailed resolution of larval vertical distribution. Environmental data (temperature, salinity, and chlorophyll a) were obtained every hour. To investigate the horizontal distribution of decapod larvae in relation to the coast, a plankton-sampling grid was carried out before the 69 h fixed station. Larvae of shelf decapod species were widely distributed over the shelf, while those of inshore species were found much closer to the coast. Decapod larvae (zoeae and megalopae) showed clear diel vertical migrations, only appearing in the upper 20 m at night, a migration that did not appear to be affected by physical conditions in the water column. Larval densities were highly variable, 0.01 to 215 ind. m super(-3) for zoeae and 0 to 93 ind. m super(-3) for megalopae, the zoeae being generally more abundant. The results indicated that during the day larvae accumulate very close to the bottom. The diel vertical migration behaviour is discussed as one of the contributing mechanisms for larval retention over the shelf, even with offshore transport conditions promoted by coastal upwelling, and is hence of major relevance for the recruitment success of decapod species that inhabit inshore and shelf zones of coastal upwelling systems.

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Exploring climate and anthropogenic impacts on marine ecosystems requires an understanding of how trophic components interact. However, integrative end-to-end ecosystem studies (experimental and/or modelling) are rare. Experimental investigations often concentrate on a particular group or individual species within a trophic level, while tropho-dynamic field studies typically employ either a bottom-up approach concentrating on the phytoplankton community or a top-down approach concentrating on the fish community. Likewise the emphasis within modelling studies is usually placed upon phytoplankton-dominated biogeochemistry or on aspects of fisheries regulation. In consequence the roles of zooplankton communities (protists and metazoans) linking phytoplankton and fish communities are typically under-represented if not (especially in fisheries models) ignored. Where represented in ecosystem models, zooplankton are usually incorporated in an extremely simplistic fashion, using empirical descriptions merging various interacting physiological functions governing zooplankton growth and development, and thence ignoring physiological feedback mechanisms. Here we demonstrate, within a modelled plankton food-web system, how trophic dynamics are sensitive to small changes in parameter values describing zooplankton vital rates and thus the importance of using appropriate zooplankton descriptors. Through a comprehensive review, we reveal the mismatch between empirical understanding and modelling activities identifying important issues that warrant further experimental and modelling investigation. These include: food selectivity, kinetics of prey consumption and interactions with assimilation and growth, form of voided material, mortality rates at different age-stages relative to prior nutrient history. In particular there is a need for dynamic data series in which predator and prey of known nutrient history are studied interacting under varied pH and temperature regimes.

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The seeding of an expanse of surface waters in the equatorial Pacific Ocean with low concentrations of dissolved iron triggered a massive phytoplankton bloom which consumed large quantities of carbon dioxide and nitrate that these microscopic plants cannot fully utilize under natural conditions. These and other observations provide unequivocal support for the hypothesis that phytoplankton growth in this oceanic region is limited by iron bioavailability.

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There is ongoing debate as to whether the oligotrophic ocean is predominantly net autotrophic and acts as a CO2 sink, or net heterotrophic and therefore acts as a CO2 source to the atmosphere. This quantification is challenging, both spatially and temporally, due to the sparseness of measurements. There has been a concerted effort to derive accurate estimates of phytoplankton photosynthesis and primary production from satellite data to fill these gaps; however there have been few satellite estimates of net community production (NCP). In this paper, we compare a number of empirical approaches to estimate NCP from satellite data with in vitro measurements of changes in dissolved O2 concentration at 295 stations in the N and S Atlantic Ocean (including the Antarctic), Greenland and Mediterranean Seas. Algorithms based on power laws between NCP and particulate organic carbon production (POC) derived from 14C uptake tend to overestimate NCP at negative values and underestimate at positive values. An algorithm that includes sea surface temperature (SST) in the power function of NCP and 14C POC has the lowest bias and root-mean square error compared with in vitro measured NCP and is the most accurate algorithm for the Atlantic Ocean. Nearly a 13 year time series of NCP was generated using this algorithm with SeaWiFS data to assess changes over time in different regions and in relation to climate variability. The North Atlantic subtropical and tropical Gyres (NATL) were predominantly net autotrophic from 1998 to 2010 except for boreal autumn/winter, suggesting that the northern hemisphere has remained a net sink for CO2 during this period. The South Atlantic subtropical Gyre (SATL) fluctuated from being net autotrophic in austral spring-summer, to net heterotrophic in austral autumn–winter. Recent decadal trends suggest that the SATL is becoming more of a CO2 source. Over the Atlantic basin, the percentage of satellite pixels with negative NCP was 27%, with the largest contributions from the NATL and SATL during boreal and austral autumn–winter, respectively. Variations in NCP in the northern and southern hemispheres were correlated with climate indices. Negative correlations between NCP and the multivariate ENSO index (MEI) occurred in the SATL, which explained up to 60% of the variability in NCP. Similarly there was a negative correlation between NCP and the North Atlantic Oscillation (NAO) in the Southern Sub-Tropical Convergence Zone (SSTC),which explained 90% of the variability. There were also positive correlations with NAO in the Canary Current Coastal Upwelling (CNRY) and Western Tropical Atlantic (WTRA)which explained 80% and 60% of the variability in each province, respectively. MEI and NAO seem to play a role in modifying phases of net autotrophy and heterotrophy in the Atlantic Ocean.