76 research outputs found

    Flexible C : N ratio enhances metabolism of large phytoplankton when resource supply is intermittent

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    Abstract. Phytoplankton cell size influences particle sinking rate, food web interactions and biogeographical distributions. We present a model in which the uptake, storage and assimilation of nitrogen and carbon are explicitly resolved in different-sized phytoplankton cells. In the model, metabolism and cellular C : N ratio are influenced by the accumulation of carbon polymers such as carbohydrate and lipid, which is greatest when cells are nutrient starved, or exposed to high light. Allometric relations and empirical data sets are used to constrain the range of possible C : N, and indicate that larger cells can accumulate significantly more carbon storage compounds than smaller cells. When forced with extended periods of darkness combined with brief exposure to saturating irradiance, the model predicts organisms large enough to accumulate significant carbon reserves may on average synthesize protein and other functional apparatus up to five times faster than smaller organisms. The advantage of storage in terms of average daily protein synthesis rate is greatest when modeled organisms were previously nutrient starved, and carbon storage reservoirs saturated. Small organisms may therefore be at a disadvantage in terms of average daily growth rate in environments that involve prolonged periods of darkness and intermittent nutrient limitation. We suggest this mechanism is a significant constraint on phytoplankton C : N variability and cell size distribution in different oceanic regimes. </jats:p

    Surface ocean carbon dioxide during the Atlantic Meridional Transect (1995–2013); evidence of ocean acidification

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    Here we present more than 21,000 observations of carbon dioxide fugacity in air and seawater (fCO2) along the Atlantic Meridional Transect (AMT) programme for the period 1995–2013. Our dataset consists of 11 southbound and 2 northbound cruises in boreal autumn and spring respectively. Our paper is primarily focused on change in the surface-ocean carbonate system during southbound cruises. We used observed fCO2 and total alkalinity (TA), derived from salinity and temperature, to estimate dissolved inorganic carbon (DIC) and pH (total scale). Using this approach, estimated pH was consistent with spectrophotometric measurements carried out on 3 of our cruises. The AMT cruises transect a range of biogeographic provinces where surface Chlorophyll-a spans two orders of magnitude (mesotrophic high latitudes to oligotrophic subtropical gyres). We found that surface Chlorophyll-a was negatively correlated with fCO2, but that the deep chlorophyll maximum was not a controlling variable for fCO2. Our data show clear evidence of ocean acidification across 100� of latitude in the Atlantic Ocean. Over the period 1995–2013 we estimated annual rates of change in: (a) sea surface temperature of 0.01 ± 0.05 �C, (b) seawater fCO2 of 1.44 ± 0.84 latm, (c) DIC of 0.87 ± 1.02 lmol per kg and (d) pH of �0.0013 ± 0.0009 units. Monte Carlo simulations propagating the respective analytical uncertainties showed that the latter were < 5% of the observed trends. Seawater fCO2 increased at the same rate as atmospheric CO2

    Impacts and environmental risks of oil spills on marine invertebrates, algae and seagrass: a global review from an Australian perspective

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    Marine invertebrates and macrophytes are sensitive to the toxic effects of oil. Depending on the intensity, duration and circumstances of the exposure, they can suffer high levels of initial mortality together with prolonged sublethal effects that can act at individual, population and community levels. Under some circumstances, recovery from these impacts can take years to decades. However, effects are variable because some taxa are less sensitive than others, and many factors can mitigate the degree of exposure, meaning that impacts are moderate in many cases, and recovery occurs within a few years. Exposure is affected by a myriad of factors including: Type and amount of oil, extent of weathering, persistence of exposure, application of dispersants or other clean-up measures, habitat type, temperature and depth, species present and their stage of development or maturity, and processes of recolonisation, particularly recruitment. Almost every oil spill is unique in terms of its impact because of differing levels of exposure and the type of habitats, communities and species assemblages in the receiving environment. Between 1970 and February 2017, there were 51 significant oil spills in Australia. Five occurred offshore with negligible likely or expected impacts. Of the others, only 24 of the spills were studied in detail, while 19 had only cursory or no assessment despite the potential for oil spills to impact the marine environment. The majority were limited to temperate waters, although 10 of the 14 spills since 2000 were in tropical coastal or offshore areas, seven were in north Queensland in areas close to the Great Barrier Reef. All four spills that have occurred from offshore petroleum industry infrastructure have occurred since 2009. In Australia, as elsewhere, a prespill need exists to assess the risk of a spill, establish environmental baselines, determine the likely exposure of the receiving environment, and test the toxicity of the oil against key animal and plant species in the area of potential impact. Subsequent to any spill, the baseline provides a reference for targeted impact monitoring

    A synthesis of the environmental response of the North and South Atlantic Sub-Tropical Gyres during two decades of AMT

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    This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Anthropogenically-induced global warming is expected to decrease primary productivity in the subtropical oceans by strengthening stratification of the water column and reducing the flux of nutrients from deep-waters to the sunlit surface layers. Identification of such changes is hindered by a paucity of long-term, spatially-resolved, biological time-series data at the basin scale. This paper exploits Atlantic Meridional Transect (AMT) data on physical and biogeochemical properties (1995–2014) in synergy with a wide range of remote-sensing (RS) observations from ocean colour, Sea Surface Temperature (SST), Sea Surface Salinity (SSS) and altimetry (surface currents), combined with different modelling approaches (both empirical and a coupled 1-D Ecosystem model), to produce a synthesis of the seasonal functioning of the North and South Atlantic Sub-Tropical Gyres (STGs), and assess their response to longer-term changes in climate. We explore definitive characteristics of the STGs using data of physical (SST, SSS and peripheral current systems) and biogeochemical variables (chlorophyll and nitrate), with inherent criteria (permanent thermal stratification and oligotrophy), and define the gyre boundary from a sharp gradient in these physical and biogeochemical properties. From RS data, the seasonal cycles for the period 1998–2012 show significant relationships between physical properties (SST and PAR) and gyre area. In contrast to expectations, the surface layer chlorophyll concentration from RS data (CHL) shows an upward trend for the mean values in both subtropical gyres. Furthermore, trends in physical properties (SST, PAR, gyre area) differ between the North and South STGs, suggesting the processes responsible for an upward trend in CHL may vary between gyres. There are significant anomalies in CHL and SST that are associated with El Niño events. These conclusions are drawn cautiously considering the short length of the time-series (1998–2012), emphasising the need to sustain spatially-extensive surveys such as AMT and integrate such observations with models, autonomous observations and RS data, to help address fundamental questions about how our planet is responding to climate change. A small number of dedicated AMT cruises in the keystone months of January and July would complement our understanding of seasonal cycles in the STGs.Natural Environment Research Council National CapabilityUK National Centre for Earth Observatio

    Inter-comparison of phytoplankton functional type phenology metrics derived from ocean color algorithms and Earth System Models

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    This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordOcean color remote sensing of chlorophyll concentration has revolutionized our understanding of the biology of the oceans. However, a comprehensive understanding of the structure and function of oceanic ecosystems requires the characterization of the spatio-temporal variability of various phytoplankton functional types (PFTs), which have differing biogeochemical roles. Thus, recent bio-optical algorithm developments have focused on retrieval of various PFTs. It is important to validate and inter-compare the existing PFT algorithms; however direct comparison of retrieved variables is non-trivial because in those algorithms PFTs are defined differently. Thus, it is more plausible and potentially more informative to focus on emergent properties of PFTs, such as phenology. Furthermore, ocean color satellite PFT data sets can play a pivotal role in informing and/or validating the biogeochemical routines of Earth System Models. Here, the phenological characteristics of 10 PFT satellite algorithms and 7 latest-generation climate models from the Coupled Model Inter-comparison Project (CMIP5) are inter-compared as part of the International Satellite PFT Algorithm Inter-comparison Project. The comparison is based on monthly satellite data (mostly SeaWiFS) for the 2003–2007 period. The phenological analysis is based on the fraction of microplankton or a similar variable for the satellite algorithms and on the carbon biomass due to diatoms for the climate models. The seasonal cycle is estimated on a per-pixel basis as a sum of sinusoidal harmonics, derived from the Discrete Fourier Transform of the variable time series. Peak analysis is then applied to the estimated seasonal signal and the following phenological parameters are quantified for each satellite algorithm and climate model: seasonal amplitude, percent seasonal variance, month of maximum, and bloom duration. Secondary/double blooms occur in many areas and are also quantified. The algorithms and the models are quantitatively compared based on these emergent phenological parameters. Results indicate that while algorithms agree to a first order on a global scale, large differences among them exist; differences are analyzed in detail for two Longhurst regions in the North Atlantic: North Atlantic Drift Region (NADR) and North Atlantic Subtropical Gyre West (NASW). Seasonal cycles explain the most variance in zonal bands in the seasonally-stratified subtropics at about 30° latitude in the satellite PFT data. The CMIP5 models do not reproduce this pattern, exhibiting higher seasonality in mid and high-latitudes and generally much more spatially homogeneous patterns in phenological indices compared to satellite data. Satellite data indicate a complex structure of double blooms in the Equatorial region and mid-latitudes, and single blooms on the poleward edges of the subtropical gyres. In contrast, the CMIP5 models show single annual blooms over most of the ocean except for the Equatorial band and Arabian Sea.NASAEuropean Space Agency (ESA

    Obtaining Phytoplankton Diversity from Ocean Color: A Scientific Roadmap for Future Development

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    To improve our understanding of the role of phytoplankton for marine ecosystems and global biogeochemical cycles, information on the global distribution of major phytoplankton groups is essential. Although algorithms have been developed to assess phytoplankton diversity from space for over two decades, so far the application of these data sets has been limited. This scientific roadmap identifies user needs, summarizes the current state of the art, and pinpoints major gaps in long-term objectives to deliver space-derived phytoplankton diversity data that meets the user requirements. These major gaps in using ocean color to estimate phytoplankton community structure were identified as: (a) the mismatch between satellite, in situ and model data on phytoplankton composition, (b) the lack of quantitative uncertainty estimates provided with satellite data, (c) the spectral limitation of current sensors to enable the full exploitation of backscattered sunlight, and (d) the very limited applicability of satellite algorithms determining phytoplankton composition for regional, especially coastal or inland, waters. Recommendation for actions include but are not limited to: (i) an increased communication and round-robin exercises among and within the related expert groups, (ii) the launching of higher spectrally and spatially resolved sensors, (iii) the development of algorithms that exploit hyperspectral information, and of (iv) techniques to merge and synergistically use the various streams of continuous information on phytoplankton diversity from various satellite sensors' and in situ data to ensure long-term monitoring of phytoplankton composition

    Obtaining phytoplankton diversity from ocean color: A scientific roadmap for future development

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    This is the final version. Available from Frontiers Media via the DOI in this record.To improve our understanding of the role of phytoplankton for marine ecosystems and global biogeochemical cycles, information on the global distribution of major phytoplankton groups is essential. Although algorithms have been developed to assess phytoplankton diversity from space for over two decades, so far the application of these data sets has been limited. This scientific roadmap identifies user needs, summarizes the current state of the art, and pinpoints major gaps in long-term objectives to deliver space-derived phytoplankton diversity data that meets the user requirements. These major gaps in using ocean color to estimate phytoplankton community structure were identified as: (a) the mismatch between satellite, in situ and model data on phytoplankton composition, (b) the lack of quantitative uncertainty estimates provided with satellite data, (c) the spectral limitation of current sensors to enable the full exploitation of backscattered sunlight, and (d) the very limited applicability of satellite algorithms determining phytoplankton composition for regional, especially coastal or inland, waters. Recommendation for actions include but are not limited to: (i) an increased communication and round-robin exercises among and within the related expert groups, (ii) the launching of higher spectrally and spatially resolved sensors, (iii) the development of algorithms that exploit hyperspectral information, and of (iv) techniques to merge and synergistically use the various streams of continuous information on phytoplankton diversity from various satellite sensors' and in situ data to ensure long-term monitoring of phytoplankton composition.ESA SEOM SY-4Sci Synergy projectNAS

    Reproductive constraints influence habitat accessibility, segregation, and preference of sympatric albatross species

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