Mighty small: Observing and modeling individual microbes becomes big science

Progress in microbiology has always been driven by technological advances, ever since Antonie van Leeuwenhoek discovered bacteria by making an improved compound microscope. However, until very recently we have not been able to identify microbes and record their mostly invisible activities, such as nutrient consumption or toxin production on the level of the single cell, not even in the laboratory. This is now changing with the rapid rise of exciting new technologies for single-cell microbiology (1, 2), which enable microbiologists to do what plant and animal ecologists have been doing for a long time: observe who does what, when, where, and next to whom. Single cells taken from the environment can be identified and even their genomes sequenced. Ex situ, their size, elemental, and biochemical composition, as well as other characteristics can be measured with high-throughput and cells sorted accordingly. Even better, individual microbes can be observed in situ with a range of novel microscopic and spectroscopic methods, enabling localization, identification, or functional characterization of cells in a natural sample, combined with detecting uptake of labeled compounds. Alternatively, they can be placed into fabricated microfluidic environments, where they can be positioned, exposed to stimuli, monitored, and their interactions controlled “in microfluido.” By introducing genetically engineered reporter cells into a fabricated landscape or a microcosm taken from nature, their reproductive success or activity can be followed, or their sensing of their local environment recorded.

Analysis of classification accuracy for pre-filtered multichannel remote sensing data

Noise is one of the main factors degrading the quality of original multichannel remote sensing data and its presence influences classification efficiency, object detection, etc. Thus, pre-filtering is often used to remove noise and improve the solving of final tasks of multichannel remote sensing. Recent studies indicate that a classical model of additive noise is not adequate enough for images formed by modern multichannel sensors operating in visible and infrared bands. However, this fact is often ignored by researchers designing noise removal methods and algorithms. Because of this, we focus on the classification of multichannel remote sensing images in the case of signal-dependent noise present in component images. Three approaches to filtering of multichannel images for the considered noise model are analysed, all based on discrete cosine transform in blocks. The study is carried out not only in terms of conventional efficiency metrics used in filtering (MSE) but also in terms of multichannel data classification accuracy (probability of correct classification, confusion matrix). The proposed classification system combines the pre-processing stage where a DCT-based filter processes the blocks of the multichannel remote sensing image and the classification stage. Two modern classifiers are employed, radial basis function neural network and support vector machines. Simulations are carried out for three-channel image of Landsat TM sensor. Different cases of learning are considered: using noise-free samples of the test multichannel image, the noisy multichannel image and the pre-filtered one. It is shown that the use of the pre-filtered image for training produces better classification in comparison to the case of learning for the noisy image. It is demonstrated that the best results for both groups of quantitative criteria are provided if a proposed 3D discrete cosine transform filter equipped by variance stabilizing transform is applied. The classification results obtained for data pre-filtered in different ways are in agreement for both considered classifiers. Comparison of classifier performance is carried out as well. The radial basis neural network classifier is less sensitive to noise in original images, but after pre-filtering the performance of both classifiers is approximately the same.

Transfer Across the Air-Sea Interface

The efficiency of transfer of gases and particles across the air-sea interface is controlled by several physical, biological and chemical processes in the atmosphere and water which are described here (including waves, large- and small-scale turbulence, bubbles, sea spray, rain and surface films). For a deeper understanding of relevant transport mechanisms, several models have been developed, ranging from conceptual models to numerical models. Most frequently the transfer is described by various functional dependencies of the wind speed, but more detailed descriptions need additional information. The study of gas transfer mechanisms uses a variety of experimental methods ranging from laboratory studies to carbon budgets, mass balance methods, micrometeorological techniques and thermographic techniques. Different methods resolve the transfer at different scales of time and space; this is important to take into account when comparing different results. Air-sea transfer is relevant in a wide range of applications, for example, local and regional fluxes, global models, remote sensing and computations of global inventories. The sensitivity of global models to the description of transfer velocity is limited; it is however likely that the formulations are more important when the resolution increases and other processes in models are improved. For global flux estimates using inventories or remote sensing products the accuracy of the transfer formulation as well as the accuracy of the wind field is crucial.

An intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensing

Satellite remote sensing of ocean colour is the only method currently available for synoptically measuring wide-area properties of ocean ecosystems, such as phytoplankton chlorophyll biomass. Recently, a variety of bio-optical and ecological methods have been established that use satellite data to identify and differentiate between either phytoplankton functional types (PFTs) or phytoplankton size classes (PSCs). In this study, several of these techniques were evaluated against in situ observations to determine their ability to detect dominant phytoplankton size classes (micro-, nano- and picoplankton). The techniques are applied to a 10-year ocean-colour data series from the SeaWiFS satellite sensor and compared with in situ data (6504 samples) from a variety of locations in the global ocean. Results show that spectral-response, ecological and abundance-based approaches can all perform with similar accuracy. Detection of microplankton and picoplankton were generally better than detection of nanoplankton. Abundance-based approaches were shown to provide better spatial retrieval of PSCs. Individual model performance varied according to PSC, input satellite data sources and in situ validation data types. Uncertainty in the comparison procedure and data sources was considered. Improved availability of in situ observations would aid ongoing research in this field.

Recent Arctic Climate Change and Its Remote Forcing of Northwest Atlantic Shelf Ecosystems

During recent decades, historically unprecedented changes have been observed in the Arctic as climate warming has increased precipitation, river discharge, and glacial as well as sea-ice melting. Additionally, shifts in the Arctic's atmospheric pressure field have altered surface winds, ocean circulation, and freshwater storage in the Beaufort Gyre. These processes have resulted in variable patterns of freshwater export from the Arctic Ocean, including the emergence of great salinity anomalies propagating throughout the North Atlantic. Here, we link these variable patterns of freshwater export from the Arctic Ocean to the regime shifts observed in Northwest Atlantic shelf ecosystems. Specifically, we hypothesize that the corresponding salinity anomalies, both negative and positive, alter the timing and extent of water-column stratification, thereby impacting the production and seasonal cycles of phytoplankton, zooplankton, and higher-trophic-level consumers. Should this hypothesis hold up to critical evaluation, it has the potential to fundamentally alter our current understanding of the processes forcing the dynamics of Northwest Atlantic shelf ecosystems.

Macroscale factors affecting diatom abundance: a synergistic use of Continuous Plankton Recorder and satellite remote sensing data

Diatoms exist in almost every aquatic regime; they are responsible for 20% of global carbon fixation and 25% of global primary production, and are regarded as a key food for copepods, which are subsequently consumed by larger predators such as fish and marine mammals. A decreasing abundance and a vulnerability to climatic change in the North Atlantic Ocean have been reported in the literature. In the present work, a data matrix composed of concurrent satellite remote sensing and Continuous Plankton Recorder (CPR) in situ measurements was collated for the same spatial and temporal coverage in the Northeast Atlantic. Artificial neural networks (ANNs) were applied to recognize and learn the complex non-monotonic and non-linear relationships between diatom abundance and spatiotemporal environmental factors. Because of their ability to mimic non-linear systems, ANNs proved far more effective in modelling the diatom distribution in the marine ecosystem. The results of this study reveal that diatoms have a regular seasonal cycle, with their abundance most strongly influenced by sea surface temperature (SST) and light intensity. The models indicate that extreme positive SSTs decrease diatom abundances regardless of other climatic conditions. These results provide information on the ecology of diatoms that may advance our understanding of the potential response of diatoms to climatic change.

Enhancement of primary production in the North Atlantic outside of the spring bloom, identified by remote sensing of ocean colour and temperature

The heterogeneity in phytoplankton production in the North Atlantic after the spring bloom is poorly understood. We analysed merged microwave and infrared satellite sea surface temperature (SST) data and ocean colour phytoplankton size class biomass, primary production (PP) and new production (ExP) derived from SeaWiFS data, to assess the spatial and temporal frequency of surface thermal fronts and areas of enhanced PP and ExP. Strong and persistent surface thermal fronts occurred at the Reykjanes Ridge (RR) and sub-polar front (SPF), which sustain high PP and ExP and, outside of the spring bloom, account for 9% and 15% of the total production in the North Atlantic. When normalised by area, PP at the SPF is four times higher than the RR. Analysis of 13 years of satellite ocean colour data from SeaWiFS, and compared with MODIS-Aqua and MERIS, showed that there was no increase in Chla from 1998 to 2002, which then decreased in all areas from 2002 to 2007 and was most pronounced in the RR. These time series also illustrated that the SPF exhibited the highest PP and the lowest variation in Chla over the ocean colour record. This implies that the SPF provides a high and consistent supply of carbon to the benthos irrespective of fluctuations in the North Atlantic Oscillation.

Remote sensing of assimilation number for marine phytoplankton

Estimating primary production at large spatial scales is key to our understanding of the global carbon cycle. Algorithms to estimate primary production are well established and have been used in many studies with success. One of the key parameters in these algorithms is the chlorophyll-normalised production rate under light saturation (referred to as the light saturation parameter or the assimilation number). It is known to depend on temperature, light history and nutrient conditions, but assigning a magnitude to it at particular space-time points is difficult. In this paper, we explore two models to estimate the assimilation number at the global scale from remotely-sensed data that combine methods to estimate the carbon-to-chlorophyll ratio and the maximum growth rate of phytoplankton. The inputs to the algorithms are the surface concentration of chlorophyll, seasurface temperature, photosynthetically-active radiation af the surface of the sea, sea surface nutrient concentration and mixed-layer depth. A large database of in situ estimates of the assimilation number is used to develop the models and provide elements of validation. The comparisons with in situ observations are promising and global maps of assimilation number are produced.

Volcanic ash supply to the surface ocean – remote sensing of biological responses and their wider biogeochemical significance

Transient micronutrient enrichment of the surface ocean can enhance phytoplankton growth rates and alter microbial community structure with an ensuing spectrum of biogeochemical feedbacks. Strong phytoplankton responses to micronutrients supplied by volcanic ash have been reported recently. Here we: (i) synthesize findings from these recent studies; (ii) report the results of a new remote sensing study of ash fertilization; and (iii) calculate theoretical bounds of ash-fertilized carbon export. Our synthesis highlights that phytoplankton responses to ash do not always simply mimic that of iron amendment; the exact mechanisms for this are likely biogeochemically important but are not yet well understood. Inherent optical properties of ash-loaded seawater suggest rhyolitic ash biases routine satellite chlorophyll-a estimation upwards by more than an order of magnitude for waters with <0.1 mg chlorophyll-a m-3, and less than a factor of 2 for systems with >0.5 mg chlorophyll-a m-3. For this reason post-ash-deposition chlorophyll-a changes in oligotrophic waters detected via standard Case 1 (open ocean) algorithms should be interpreted with caution. Remote sensing analysis of historic events with a bias less than a factor of 2 provided limited stand-alone evidence for ash-fertilization. Confounding factors were poor coverage, incoherent ash dispersal, and ambiguity ascribing biomass changes to ash supply over other potential drivers. Using current estimates of iron release and carbon export efficiencies, uncertainty bounds of ash-fertilized carbon export for 3 events are presented. Patagonian iron supply to the Southern Ocean from volcanic eruptions is less than that of windblown dust on thousand year timescales but can dominate supply at shorter timescales. Reducing uncertainties in remote sensing of phytoplankton response and nutrient release from ash are avenues for enabling assessment of the oceanic response to large-scale transient nutrient enrichment.

The impact of ocean acidification and warming on the skeletal mechanical properties of the sea urchin Paracentrotus lividus from laboratory and field observations

Increased atmospheric CO2 concentration is leading to changes in the carbonate chemistry and the temperature of the ocean. The impact of these processes on marine organisms will depend on their ability to cope with those changes, particularly the maintenance of calcium carbonate structures. Both a laboratory experiment (long-term exposure to decreased pH and increased temperature) and collections of individuals from natural environments characterized by low pH levels (individuals from intertidal pools and around a CO2 seep) were here coupled to comprehensively study the impact of near-future conditions of pH and temperature on the mechanical properties of the skeleton of the euechinoid sea urchin Paracentrotus lividus. To assess skeletal mechanical properties, we characterized the fracture force, Young's modulus, second moment of area, material nanohardness, and specific Young's modulus of sea urchin test plates. None of these parameters were significantly affected by low pH and/or increased temperature in the laboratory experiment and by low pH only in the individuals chronically exposed to lowered pH from the CO2 seeps. In tidal pools, the fracture force was higher and the Young's modulus lower in ambital plates of individuals from the rock pool characterized by the largest pH variations but also a dominance of calcifying algae, which might explain some of the variation. Thus, decreases of pH to levels expected for 2100 did not directly alter the mechanical properties of the test of P. lividus. Since the maintenance of test integrity is a question of survival for sea urchins and since weakened tests would increase the sea urchins' risk of predation, our findings indicate that the decreasing seawater pH and increasing seawater temperature expected for the end of the century should not represent an immediate threat to sea urchins vulnerability.

20 Years of the Atlantic Meridional Transect — AMT

The AMT (www.amt-uk.org) is a multidisciplinary programme which undertakes biological, chemical, and physical oceanographic research during an annual voyage between the UK and a destination in the South Atlantic such as the Falkland Islands,South Africa, or Chile. This transect of >12,000 km crosses a range of ecosystems from subpolar to tropical, from euphotic shelf seas and upwelling systems, to oligotrophic mid-ocean gyres. The year 2015 has seen two milestones in the history of the AMT: the achievement of 20 years of this unique ocean going programme and the departure of the 25th cruise on the 15th of September. Both of these events were celebrated in June this year with an open science conference hosted by the Plymouth Marine Laboratory (PML) and will be further documented in a special issue of Progress in Oceanography which is planned for publication in 2016. Since 1995, the 25 research cruises have involved 242 sea-going scientists from 66 institutes representing 22 countries.

Ocean acidification has different effects on the production of DMS and DMSP measured in cultures of Emiliania huxleyi and a mesocosm study: a comparison of laboratory monocultures and community interactions

The human-induced rise in atmospheric carbon dioxide since the industrial revolution has led to increasing oceanic carbon uptake and changes in seawater carbonate chemistry, resulting in lowering of surface water pH. In this study we investigated the effect of increasing CO2 partial pressure (pCO2) on concentrations of volatile biogenic dimethylsulfide (DMS) and its precursor dimethylsulfoniopropionate (DMSP), through monoculture studies and community pCO2 perturbation. DMS is a climatically important gas produced by many marine algae: it transfers sulfur into the atmosphere and is a major influence on biogeochemical climate regulation through breakdown to sulfate and formation of subsequent cloud condensation nuclei (CCN). Overall, production of DMS and DMSP by the coccolithophore Emiliania huxleyi strain RCC1229 was unaffected by growth at 900 matm pCO2, but DMSP production normalised to cell volume was 12% lower at the higher pCO2 treatment. These cultures were compared with community DMS and DMSP production during an elevated pCO2 mesocosm experiment with the aim of studying E. huxleyi in the natural environment. Results contrasted with the culture experiments and showed reductions in community DMS and DMSP concentrations of up to 60 and 32% respectively at pCO2 up to 3000 matm, with changes attributed to poorer growth of DMSP-producing nanophytoplankton species, including E. huxleyi, and potentially increased microbial consumption of DMSand dissolvedDMSPat higher pCO2.DMSandDMSPproduction differences between culture and community likely arise from pH affecting the inter-species responses between microbial producers and consumers.

Uncertainty estimates of remote sensing reflectance derived from comparison of ocean color satellite data sets

Assigning uncertainty to ocean-color satellite products is a requirement to allow informed use of these data. Here, uncertainty estimates are derived using the comparison on a 12th-degree grid of coincident daily records of the remote-sensing reflectance RRS obtained with the same processing chain from three satellite missions, MERIS, MODIS and SeaWiFS. The approach is spatially resolved and produces σ, the part of the RRS uncertainty budget associated with random effects. The global average of σ decreases with wavelength from approximately 0.7– 0.9 10−3 sr−1 at 412 nm to 0.05–0.1 10−3 sr−1 at the red band, with uncertainties on σ evaluated as 20–30% between 412 and 555 nm, and 30–40% at 670 nm. The distribution of σ shows a restricted spatial variability and small variations with season, which makes the multi-annual global distribution of σ an estimate applicable to all retrievals of the considered missions. The comparison of σ with other uncertainty estimates derived from field data or with the support of algorithms provides a consistent picture. When translated in relative terms, and assuming a relatively low bias, the distribution of σ suggests that the objective of a 5% uncertainty is fulfilled between 412 and 490 nm for oligotrophic waters (chlorophyll-a concentration below 0.1 mg m−3). This study also provides comparison statistics. Spectrally, the mean absolute relative difference between RRS from different missions shows a characteristic U-shape with both ends at blue and red wavelengths inversely related to the amplitude of RRS. On average and for the considered data sets, SeaWiFS RRS tend to be slightly higher than MODIS RRS, which in turn appear higher than MERIS RRS. Biases between mission-specific RRS may exhibit a seasonal dependence, particularly in the subtropical belt.