Sequential variations of phytoplankton growth and mortality in an NPZ model: a remote-sensing-based assessment

Radiometric data in the visible domain acquired by satellite remote sensing have proven to be powerful for monitoring the states of the ocean, both physical and biological. With the help of these data it is possible to understand certain variations in biological responses of marine phytoplankton on ecological time scales. Here, we implement a sequential data-assimilation technique to estimate from a conventional nutrient–phytoplankton–zooplankton (NPZ) model the time variations of observed and unobserved variables. In addition, we estimate the time evolution of two biological parameters, namely, the specific growth rate and specific mortality of phytoplankton. Our study demonstrates that: (i) the series of time-varying estimates of specific growth rate obtained by sequential data assimilation improves the fitting of the NPZ model to the satellite-derived time series: the model trajectories are closer to the observations than those obtained by implementing static values of the parameter; (ii) the estimates of unobserved variables, i.e., nutrient and zooplankton, obtained from an NPZ model by implementation of a pre-defined parameter evolution can be different from those obtained on applying the sequences of parameters estimated by assimilation; and (iii) the maximum estimated specific growth rate of phytoplankton in the study area is more sensitive to the sea-surface temperature than would be predicted by temperature-dependent functions reported previously. The overall results of the study are potentially useful for enhancing our understanding of the biological response of phytoplankton in a changing environment.

Modelling the time-evolution of phytoplankton size spectra from satellite remote sensing

A dynamic size-structured model is developed for phytoplankton and nutrients in the oceanic mixed layer and applied to extract phytoplankton biomass at discrete size fractions from remotely sensed, ocean-colour data. General relationships between cell size and biophysical processes (such as sinking, grazing, and primary production) of phytoplankton were included in the model through a bottom–up approach. Time-dependent, mixed-layer depth was used as a forcing variable, and a sequential data-assimilation scheme was implemented to derive model trajectories. From a given time-series, the method produces estimates of size-structured biomass at every observation, so estimates seasonal succession of individual phytoplankton size, derived here from remote sensing for the first time. From these estimates, normalized phytoplankton biomass size spectra over a period of 9 years were calculated for one location in the North Atlantic. Further analysis demonstrated that strong relationships exist between the seasonal trends of the estimated size spectra and the mixed-layer depth, nutrient biomass, and total chlorophyll. The results contain useful information on the time-dependent biomass flux in the pelagic ecosystem.

The phenology of phytoplankton blooms: ecosystems indicators from remote sensing

Remote sensing offers many advantages in the development of ecosystem indicators for the pelagic zone of the ocean. Particularly suitable in this context are the indicators arising from time series that can be constructed from remotely sensed data. For example, using ocean-colour radiometry, the phenology of phytoplankton blooms can be assessed. Metrics defined in this way show promise as informative indicators for the entire pelagic ecosystem. A simple phytoplankton–substrate model, with forcing dependent on latitude and day number is used to explore the qualitative features of bloom phenology for comparison with the results observed in a suite of 10-year time series of chlorophyll concentration, as assessed by remote sensing, from the Northwest Atlantic Ocean. The model reveals features of the dynamics that might otherwise have been overlooked in evaluation of the observational data.

Electrochemical sensing of 2D condensation in amyloid peptides

The interfacial behavior of the model amyloid peptide octamer YYKLVFFC (peptide 1) and two other amyloid peptides YEVHHQKLVFF (peptide 2) and KKLVFFA (peptide 3) at the metal|aqueous solution interface was studied by voltammetric and constant current chronopotentiometric stripping (CPS). All three peptides are adsorbed in a wide potential range and exhibit different interfacial organizations depending on the electrode potential. At the least negative potentials, chemisorption of peptide 1 occurs through the formation of a metal sulfur bond. This bond is broken close to −0.6 V. The peptide undergoes self-association at more negative potentials, leading to the formation of a “pit” characteristic of a 2D condensed film. Under the same conditions the other peptides do not produce such a pit. Formation of the 2D condensed layer in peptide 1 is supported by the time, potential and temperature dependences of the interfacial capacity and it is shown that presence of the 2D layer is reflected by the peptide CPS signals due to the catalytic hydrogen evolution. The ability of peptide 1 to form the potential-dependent 2D condensed layer has been reported neither for any other peptide nor for any protein molecule. This ability might be related to the well-known oligomerization and aggregation of Alzheimer amyloid peptides.

Comparison of the radiative properties and direct radiative effect of aerosols from a global aerosol model and remote sensing data over ocean

A global aerosol transport model (Oslo CTM2) with main aerosol components included is compared to five satellite retrievals of aerosol optical depth (AOD) and one data set of the satellite-derived radiative effect of aerosols. The model is driven with meteorological data for the period November 1996 to June 1997 which is the time period investigated in this study. The modelled AOD is within the range of the AOD from the various satellite retrievals over oceanic regions. The direct radiative effect of the aerosols as well as the atmospheric absorption by aerosols are in both cases found to be of the order of 20 Wm−2 in certain regions in both the satellite-derived and the modelled estimates as a mean over the period studied. Satellite and model data exhibit similar patterns of aerosol optical depth, radiative effect of aerosols, and atmospheric absorption of the aerosols. Recently published results show that global aerosol models have a tendency to underestimate the magnitude of the clear-sky direct radiative effect of aerosols over ocean compared to satellite-derived estimates. However, this is only to a small extent the case with the Oslo CTM2. The global mean direct radiative effect of aerosols over ocean is modelled with the Oslo CTM2 to be –5.5 Wm−2 and the atmospheric aerosol absorption 1.5 Wm−2.

In situ and remote-sensing measurements of the mean microphysical and optical properties of industrial pollution aerosol during ADRIEX

We present a summary of the principal physical and optical properties of aerosol particles using the FAAM BAE-146 instrumented aircraft during ADRIEX between 27 August and 6 September 2004, augmented by sunphotometer, lidar and satellite retrievals. Observations of anthropogenic aerosol, principally from industrial sources, were concentrated over the northern Adriatic Sea and over the Po Valley close to the aerosol sources. An additional flight was also carried out over the Black Sea to compare east and west European pollution. Measurements show the single-scattering albedo of dry aerosol particles to vary considerably between 0.89 and 0.97 at a wavelength of 0.55 μm, with a campaign mean within the polluted lower free troposphere of 0.92. Although aerosol concentrations varied significantly from day to day and during individual days, the shape of the aerosol size distribution was relatively consistent through the experiment, with no detectable change observed over land and over sea. There is evidence to suggest that the pollution aerosol within the marine boundary layer was younger than that in the elevated layer. Trends in the aerosol volume distribution show consistency with multiple-site AERONET radiometric observations. The aerosol optical depths derived from aircraft measurements show a consistent bias to lower values than both the AERONET and lidar ground-based radiometric observations, differences which can be explained by local variations in the aerosol column loading and by some aircraft instrumental artefacts. Retrievals of the aerosol optical depth and fine-mode (<0.5 μm radius) fraction contribution to the optical depth using MODIS data from the Terra and Aqua satellites show a reasonable level of agreement with the AERONET and aircraft measurements.

The integration of lipid-sensing and anti-inflammatory effects: how the PPARs play a role in metabolic balance

The peroxisomal proliferating-activated receptors (PPARs) are lipid-sensing transcription factors that have a role in embryonic development, but are primarily known for modulating energy metabolism, lipid storage, and transport, as well as inflammation and wound healing. Currently, there is no consensus as to the overall combined function of PPARs and why they evolved. We hypothesize that the PPARs had to evolve to integrate lipid storage and burning with the ability to reduce oxidative stress, as energy storage is essential for survival and resistance to injury/infection, but the latter increases oxidative stress and may reduce median survival (functional longevity). In a sense, PPARs may be an evolutionary solution to something we call the 'hypoxia-lipid' conundrum, where the ability to store and burn fat is essential for survival, but is a 'double-edged sword', as fats are potentially highly toxic. Ways in which PPARs may reduce oxidative stress involve modulation of mitochondrial uncoupling protein (UCP) expression (thus reducing reactive oxygen species, ROS), optimising forkhead box class O factor (FOXO) activity (by improving whole body insulin sensitivity) and suppressing NFkB (at the transcriptional level). In light of this, we therefore postulate that inflammation-induced PPAR downregulation engenders many of the signs and symptoms of the metabolic syndrome, which shares many features with the acute phase response (APR) and is the opposite of the phenotype associated with calorie restriction and high FOXO activity. In genetically susceptible individuals (displaying the naturally mildly insulin resistant 'thrifty genotype'), suboptimal PPAR activity may follow an exaggerated but natural adipose tissue-related inflammatory signal induced by excessive calories and reduced physical activity, which normally couples energy storage with the ability to mount an immune response. This is further worsened when pancreatic decompensation occurs, resulting in gluco-oxidative stress and lipotoxicity, increased inflammatory insulin resistance and oxidative stress. Reactivating PPARs may restore a metabolic balance and help to adapt the phenotype to a modern lifestyle.

Targeting Staphylococcus aureus quorum sensing with non-peptidic small molecule inhibitors

A series of 3-oxo-C12-HSL, tetramic acid and tetronic acid analogues was synthesized to gain insights into the structural requirements for quorum sensing inhibition in Staphylococcus aureus. Compounds active against agr were non-competitive inhibitors of the auto-inducing peptide (AIP)-activated AgrC receptor, by altering the activation efficacy of the cognate AIP-1. They appeared to act as negative allosteric modulators and are exemplified by 3-tetradecanoyltetronic acid 17 which reduced nasal cell colonization and arthritis in a murine infection model.

Voltage-gated sodium (NaV) channel blockade by plant cannabinoids does not confer anticonvulsant effects per se

Cannabidiol (CBD) is a non-psychoactive, well-tolerated, anticonvulsant plant cannabinoid, although its mechanism(s) of seizure suppression remains unknown. Here, we investigate the effect of CBD and the structurally similar cannabinoid, cannabigerol (CBG), on voltage-gated Na+ (NaV) channels, a common anti-epileptic drug target. CBG’s anticonvulsant potential was also assessed in vivo. CBD effects on NaV channels were investigated using patch-clamp recordings from rat CA1 hippocampal neurons in brain slices, human SH-SY5Y (neuroblastoma) cells and mouse cortical neurons in culture. CBG effects were also assessed in SH-SY5Y cells and mouse cortical neurons. CBD and CBG effects on veratridine-stimulated human recombinant NaV1.1, 1.2 or 1.5 channels were assessed using a membrane potential-sensitive fluorescent dye high-throughput assay. The effect of CBG on pentyleneterazole-induced (PTZ) seizures was assessed in rat. CBD (10M) blocked NaV currents in SH-SY5Y cells, mouse cortical neurons and recombinant cell lines, and affected spike parameters in rat CA1 neurons; CBD also significantly decreased membrane resistance. CBG blocked NaV to a similar degree to CBD in both SH-SY5Y and mouse recordings, but had no effect (50-200mg/kg) on PTZ-induced seizures in rat. CBD and CBG are NaV channel blockers at micromolar concentrations in human and murine neurons and recombinant cells. In contrast to previous reports investigating CBD, CBG had no effect upon PTZ-induced seizures in rat, indicating that NaV blockade per se does not correlate with anticonvulsant effects.

Control methodologies: Peak reduction algorithms for DNO owned storage devices on the Low Voltage network

The Distribution Network Operators (DNOs) role is becoming more difficult as electric vehicles and electric heating penetrate the network, increasing the demand. As a result it becomes harder for the distribution networks infrastructure to remain within its operating constraints. Energy storage is a potential alternative to conventional network reinforcement such as upgrading cables and transformers. The research presented here in this paper shows that due to the volatile nature of the LV network, the control approach used for energy storage has a significant impact on performance. This paper presents and compares control methodologies for energy storage where the objective is to get the greatest possible peak demand reduction across the day from a pre-specified storage device. The results presented show the benefits and detriments of specific types of control on a storage device connected to a single phase of an LV network, using aggregated demand profiles based on real smart meter data from individual homes. The research demonstrates an important relationship between how predictable an aggregation is and the best control methodology required to achieve the objective.

A peak reduction scheduling algorithm for storage devices on the low voltage network

Reinforcing the Low Voltage (LV) distribution network will become essential to ensure it remains within its operating constraints as demand on the network increases. The deployment of energy storage in the distribution network provides an alternative to conventional reinforcement. This paper presents a control methodology for energy storage to reduce peak demand in a distribution network based on day-ahead demand forecasts and historical demand data. The control methodology pre-processes the forecast data prior to a planning phase to build in resilience to the inevitable errors between the forecasted and actual demand. The algorithm uses no real time adjustment so has an economical advantage over traditional storage control algorithms. Results show that peak demand on a single phase of a feeder can be reduced even when there are differences between the forecasted and the actual demand. In particular, results are presented that demonstrate when the algorithm is applied to a large number of single phase demand aggregations that it is possible to identify which of these aggregations are the most suitable candidates for the control methodology.

Thermal remote sensing of sea surface temperature

Sea surface temperature has been an important application of remote sensing from space for three decades. This chapter first describes well-established methods that have delivered valuable routine observations of sea surface temperature for meteorology and oceanography. Increasingly demanding requirements, often related to climate science, have highlighted some limitations of these ap-proaches. Practitioners have had to revisit techniques of estimation, of characterising uncertainty, and of validating observations—and even to reconsider the meaning(s) of “sea surface temperature”. The current understanding of these issues is reviewed, drawing attention to ongoing questions. Lastly, the prospect for thermal remote sens-ing of sea surface temperature over coming years is discussed.

Sources, sinks, and transatlantic transport of North African dust aerosol: a multimodel analysis and comparison with remote sensing data

This study evaluates model-simulated dust aerosols over North Africa and the North Atlantic from five global models that participated in the Aerosol Comparison between Observations and Models phase II model experiments. The model results are compared with satellite aerosol optical depth (AOD) data from Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), and Sea-viewing Wide Field-of-view Sensor, dust optical depth (DOD) derived from MODIS and MISR, AOD and coarse-mode AOD (as a proxy of DOD) from ground-based Aerosol Robotic Network Sun photometer measurements, and dust vertical distributions/centroid height from Cloud Aerosol Lidar with Orthogonal Polarization and Atmospheric Infrared Sounder satellite AOD retrievals. We examine the following quantities of AOD and DOD: (1) the magnitudes over land and over ocean in our study domain, (2) the longitudinal gradient from the dust source region over North Africa to the western North Atlantic, (3) seasonal variations at different locations, and (4) the dust vertical profile shape and the AOD centroid height (altitude above or below which half of the AOD is located). The different satellite data show consistent features in most of these aspects; however, the models display large diversity in all of them, with significant differences among the models and between models and observations. By examining dust emission, removal, and mass extinction efficiency in the five models, we also find remarkable differences among the models that all contribute to the discrepancies of model-simulated dust amount and distribution. This study highlights the challenges in simulating the dust physical and optical processes, even in the best known dust environment, and stresses the need for observable quantities to constrain the model processes.

On the voltage and distance across the low latitude boundary layer

A pass of the AMPTE-UKS satellite through the low-latitude boundary layer (LLBL) at 8:30 MLT is studied in detail. The magnetosheath field is predominantly northward. It is shown that multiple transitions through part or all of the layer of antisunward flow lead to overestimation of both the voltage across this layer and its width. The voltage is estimated to be only about 3 kV and this implies that the full LLBL is about 1200 km thick, consistent with previous studies.

On flow reversal boundaries and transpolar voltage in average models of high-latitude convection

The implications of polar cap expansions, contractions and movements for empirical models of high-latitude plasma convection are examined. Some of these models have been generated by directly averaging flow measurements from large numbers of satellite passes or radar scans; others have employed more complex means to combine data taken at different times into large-scale patterns of flow. In all cases, the models have implicitly adopted the assumption that the polar cap is in steady state: they have all characterized the ionospheric flow in terms of the prevailing conditions (e.g. the interplanetary magnetic field and/or some index of terrestrial magnetic activity) without allowance for their history. On long enough time scales, the polar cap is indeed in steady state but on time scales shorter than a few hours it is not and can oscillate in size and position. As a result, the method used to combine the data can influence the nature of the convection reversal boundary and the transpolar voltage in the derived model. This paper discusses a variety of effects due to time-dependence in relation to some ionospheric convection models which are widely applied. The effects are shown to be varied and to depend upon the procedure adopted to compile the model.