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Despite the importance of Agulhas Bank (AB) marine productivity in supporting South African coastal fisheries and shelf ecosystems, there are relatively few regional-scale assessments of its spatial and temporal variability, and most productivity studies have been limited in scale. Here we use satellite-derived Net Primary Production (NPP) rates calculated using the Vertically Generalized Production Model (VGPM) to examine the spatial and temporal dynamics of NPP over the 21-year satellite record (1998–2018) on the AB. In calculating VGPM NPP we used the OCCI Chlorophyll-a product, SST from Operational-Sea-Surface-Temperature-and-Sea-Ice-Analysis (OSTIA) and PAR from GlobColour level-3 mapped products as these represent the longest datasets that fit our extended study period. We examine spatial trends between the eastern and central AB, as well as three areas of the bank (around Port Alfred, the Tsitsikamma coast, and the ‘cold ridge’) that have been previously identified as contributing significantly to the overall productivity of the AB. The AB shows only a moderate degree of seasonality in NPP calculated from the VGPM, with NPP being highest in austral summer (1.7–1.8 g C m−2 d−1) and lowest in winter (0.9–1.0 g C m−2 d−1), and remains relatively high (>1 g C m−2 d−1) throughout the year, contrasting sharply with other shelf systems. Considered annually, NPP on the bank was 516 g C m−2 yr−1 (38 Mt C yr−1 when scaled to the total shelf area) which is higher than many other shelf systems though lower than the neighbouring Benguela system and is indicative of a moderately productive shelf system fuelled by perennial NPP. Comparing different sections of the AB from east to central bank, and including the three upwelling areas, highlighted that spatial differences in NPP were relatively limited; that these three upwelling areas made similar contributions to their relative proportion of the total shelf area, and that average rates of NPP are spatially similar across th

The balance of physical and biological processes governing phytoplankton growth rates and the accumulation of biomass is widely debated in the literature, notably during the winter–spring transition. Here we show, in a temperate shelf sea that variability in the depth of the actively mixing surface layer is the leading order control. During a 2-week period preceding the peak of the spring bloom we observe two distinct regimes; first, growth within the euphotic zone during the day and re-distribution of new biomass to the seasonal pycnocline at night by convective mixing; then, more rapid biomass accumulation trapped within a shallower, wind-driven actively mixing layer that was decoupled from the pycnocline below. Our observations of the bloom in the Celtic Sea, Northwest European Shelf, were made using ocean gliders and include measurements of the dissipation of turbulent kinetic energy. A 1-D phytoplankton growth model driven by our measurements of dissipation and incident irradiance replicates the observed bloom and reinforces the conclusion that physical processes that mediate light availability were key. Day-to-day variability in cloud cover and the ability of phytoplankton to acclimate to their light environment were also important factors in determining growth rates, and the timing of the biomass peak. Our results emphasize the need for accurate turbulent mixing parameterizations in coupled hydrodynamic-ecosystem models. Our findings are applicable to any region where wind-driven mixing can modify nutrient and light availability, especially across subpolar shelves in the northern hemisphere where light rather than nutrients is typically the limiting factor on phytoplankton growth.

Phytoplankton blooms play an important role in the global carbon cycle and regulate marine ecosystems. The balance of physical and biological processes governing the onset of seasonal blooms is widely debated in the literature. Most studies focus on the open ocean, yet rates of carbon fixation are often greater over shallow shelves, which are dynamically and optically different environments. Here, we present ocean glider observations of a spring phytoplankton bloom during April 2015 in the Celtic Sea, Northwest European Shelf. We provide new insights into the drivers of phytoplankton growth in a tidally active temperate shelf sea. Uniquely, we have measurements of turbulent kinetic energy dissipation, which together with incident irradiance were used to drive a 1-D phytoplankton growth model. The greatest changes in phytoplankton biomass took place within the wind-driven active mixing layer, which was decoupled from the deeper, seasonal pycnocline. Maximum carbon production and biomass accumulation rates occurred following periods of reduced wind stress and shoaling, which trapped phytoplankton cells at shallower depths in the euphotic zone. Day-to-day variability in cloud cover subsequently determined the exact timing and magnitude of biomass peaks. We also observed tidally driven turbulent entrainment of phytoplankton from the base of the biomass maximum. This is a physical erosion process unique to shallow shelf systems leading to the loss of new biomass to deep waters. The importance that changes in the depth of the surface mixing layer play during the spring bloom emphasises the need for accurate turbulent mixing parameterisations in shelf sea models.

Biodiversity of phytoplankton is important for ecosystem stability and marine biogeochemistry. However, the large-scale patterns of diversity are not well understood and are often poorly characterized in terms of statistical relationships with factors such as latitude, temperature and productivity. Here we use ecological theory and a global trait-based ecosystem model to provide mechanistic understanding of patterns of phytoplankton diversity. Our study suggests that phytoplankton diversity across three dimensions of trait space (size, biogeochemical function and thermal tolerance) is controlled by disparate combinations of drivers: the supply rate of the limiting resource, the imbalance in different resource supplies relative to competing phytoplankton demands, size-selective grazing and transport by the moving ocean. Using sensitivity studies we show that each dimension of diversity is controlled by different drivers. Models including only one (or two) of the trait dimensions will have different patterns of diversity than one which incorporates another trait dimension. We use the results of our model exploration to infer the controls on the diversity patterns derived from field observations along meridional transects in the Atlantic and to explain why different taxa and size classes have differing patterns

Biodiversity of phytoplankton is important for ecosystem stability and marine biogeochemistry. However, the large-scale patterns of diversity are not well understood and are often poorly characterized in terms of statistical relationships with factors such as latitude, temperature and productivity. Here we use ecological theory and a global trait-based ecosystem model to provide mechanistic understanding of patterns of phytoplankton diversity. Our study suggests that phytoplankton diversity across three dimensions of trait space (size, biogeochemical function and thermal tolerance) is controlled by disparate combinations of drivers: the supply rate of the limiting resource, the imbalance in different resource supplies relative to competing phytoplankton demands, size-selective grazing and transport by the moving ocean. Using sensitivity studies we show that each dimension of diversity is controlled by different drivers. Models including only one (or two) of the trait dimensions will have different patterns of diversity than one which incorporates another trait dimension. We use the results of our model exploration to infer the controls on the diversity patterns derived from field observations along meridional transects in the Atlantic and to explain why different taxa and size classes have differing patterns., NASA (Grant NNX16AR47G)

This article provides a proof of concept for using a biogeochemical/ecosystem/optical model with a radiative transfer component as a laboratory to explore aspects of ocean colour. We focus here on the satellite ocean colour chlorophyll a (Chl a) product provided by the often-used blue/green reflectance ratio algorithm. The model produces output that can be compared directly to the real-world ocean colour remotely sensed reflectance. This model output can then be used to produce an ocean colour satellite-like Chl a product using an algorithm linking the blue versus green reflectance similar to that used for the real world. Given that the model includes complete knowledge of the (model) water constituents, optics and reflectance, we can explore uncertainties and their causes in this proxy for Chl a (called < q > derived Chl a < /q > in this paper). We compare the derived Chl a to the < q > actual < /q > model Chl a field. In the model we find that the mean absolute bias due to the algorithm is 22% between derived and actual Chl a. The real-world algorithm is found using concurrent in situ measurement of Chl a and radiometry. We ask whether increased in situ measurements to train the algorithm would improve the algorithm, and find a mixed result. There is a global overall improvement, but at the expense of some regions, especially in lower latitudes where the biases increase. Not surprisingly, we find that region-specific algorithms provide a significant improvement, at least in the annual mean . However, in the model, we find that no matter how the algorithm coefficients are found there can be a temporal mismatch between the derived Chl a and the actual Chl a. These mismatches stem from temporal decoupling between Chl a and other optically important water constituents (such as coloured dissolved organic matter and detrital matter). The degree of decoupling differs regionally and over time. For example, in many highly seasonal regions, the timing of initiation and peak, United States. National Aeronautics and Space Administration (Award NNX13AC34G), United States. National Aeronautics and Space Administration (Award NNX16AR47G)

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.

Observing changes in the oceans helps governments make informed decisions about issues such as fishing and the impact of climate change on ecosystems, coastal defence and weather. Some changes to the oceans occur over many decades and can only be detected if there have been many observations in the same area over a long time period. Such sustained observations require long term commitment from both the scientists that do the work and the funders that pay for the work. This theme issue reflects on the contribution that UK sustained observations of the ocean have made to science and society and presents a vision for their future. Contributions include observations of sea level, ocean circulation, biodiversity, ocean carbon and nutrient cycles, the sea and ice conditions in the Arctic and Antarctic and the importance of observations for climate predictions. The papers in this issue arose from a meeting hosted by the Challenger Society for Marine Science and the Scientific Committee on Oceanic Research at the Royal Society, London, in September 2013. The meeting and theme issue are part of a wider initiative of the Challenger Society to discuss marine science initiatives and future strategy in open forum.

We show that a breaking internal tide at a shelf edge is a fundamental control on the structural and functional properties of ecosystems. Contrasts in vertical mixing of nitrate between the shelf and the open ocean correspond with horizontal and vertical changes in phytoplankton communities, with largest cells found in surface waters at the shelf edge. Intense fishing activity is commonly seen at continental shelf edges, targeting spawning fish stocks. We suggest that the internal tide, a globally ubiquitous physical process at steep shelf edge bathymetry, supports shelf edge fisheries by providing large-celled phytoplankton for first-feeding fish larvae. The repeatability of the internal tide removes fish from the need to time spawning with a spring bloom. Also, with large phytoplankton cells dominating particulate organic carbon export, the internal tides could be an important influence on spatial and temporal variability in patterns of global carbon sequestration in deep water and sediments. Citation: Sharples, J., C. M. Moore, A. E. Hickman, P. M. Holligan, J. F. Tweddle, M. R. Palmer, and J. H. Simpson (2009), Internal tidal mixing as a control on continental margin ecosystems, Geophys. Res. Lett., 36, L23603, doi:10.1029/2009GL040683.