93 research outputs found
The Fourth SeaWiFS HPLC Analysis Round-Robin Experiment (SeaHARRE-4)
Ten international laboratories specializing in the determination of marine pigment concentrations using high performance liquid chromatography (HPLC) were intercompared using in situ samples and a mixed pigment sample. Although prior Sea-viewing Wide Field-of-view Sensor (SeaWiFS) High Performance Liquid Chromatography (HPLC) Round-Robin Experiment (SeaHARRE) activities conducted in open-ocean waters covered a wide dynamic range in productivity, and some of the samples were collected in the coastal zone, none of the activities involved exclusively coastal samples. Consequently, SeaHARRE-4 was organized and executed as a strictly coastal activity and the field samples were collected from primarily eutrophic waters within the coastal zone of Denmark. The more restrictive perspective limited the dynamic range in chlorophyll concentration to approximately one and a half orders of magnitude (previous activities covered more than two orders of magnitude). The method intercomparisons were used for the following objectives: a) estimate the uncertainties in quantitating individual pigments and higher-order variables formed from sums and ratios; b) confirm if the chlorophyll a accuracy requirements for ocean color validation activities (approximately 25%, although 15% would allow for algorithm refinement) can be met in coastal waters; c) establish the reduction in uncertainties as a result of applying QA procedures; d) show the importance of establishing a properly defined referencing system in the computation of uncertainties; e) quantify the analytical benefits of performance metrics, and f) demonstrate the utility of a laboratory mix in understanding method performance. In addition, the remote sensing requirements for the in situ determination of total chlorophyll a were investigated to determine whether or not the average uncertainty for this measurement is being satisfied
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Investigation of the 2p3/2-3d5/2 line emission of Au53+ -- Au69+ for diagnosing high energy density plasmas
Measurements of the L-shell emission of highly charged gold ions were made under controlled laboratory conditions using the SuperEBIT electron beam ion trap, allowing detailed spectral observations of lines from ironlike Au{sup 53+} through neonlike Au{sup 69+}. Using atomic data from the Flexible Atomic Code, we have identified strong 3d{sub 5/2} {yields} 2p{sub 3/2} emission features that can be used to diagnose the charge state distribution in high energy density plasmas, such as those found in the laser entrance hole of hot hohlraum radiation sources. We provide collisional-radiative calculations of the average ion charge <Z> as a function of temperature and density, which can be used to relate charge state distributions inferred from 3d{sub 5/2} {yields} 2p{sub 3/2} emission features to plasma conditions, and investigate the effects of plasma density on calculated L-shell Au emission spectra
Effect of a Once in 100-Year Flood on a Subtropical Coastal Phytoplankton Community
© Copyright © 2021 Clementson, Richardson, Rochester, Oubelkheir, Liu, D’Sa, Gusmão, Ajani, Schroeder, Ford, Burford, Saeck and Steven. Subtropical systems experience occasional severe floods, dramatically altering the phytoplankton community structure, in response to changes in salinity, nutrients, and light. This study examined the effects of a 1:100 year summer flood on the phytoplankton community in an Australian subtropical bay – Moreton Bay – over 48 weeks, from January to December 2011. Immediately after maximum flood levels were reached on the rivers flowing into the bay, the lowest salinity, and highest turbidity values, in more than a decade, were measured in the Bay and the areal extent of the flood-related parameters was also far greater than previous flood events. Changes in these parameters together with changes in Colored Dissolved Organic Matter (CDOM) and sediment concentrations significantly reduced the light availability within the water column. Despite the reduced light availability, the phytoplankton community responded rapidly (1–2 weeks) to the nutrients from flood inputs, as measured using pigment concentrations and cell counts and observed in ocean color satellite imagery. Initially, the phytoplankton community was totally dominated by micro-phytoplankton, particularly diatoms; however, in the subsequent weeks (up to 48-weeks post flood) the community changed to one of nano- and pico-plankton in all areas of the Bay not usually affected by river flow. This trend is consistent with many other studies that show the ability of micro-phytoplankton to respond rapidly to increased nutrient availability, stimulating their growth rates. The results of this study suggest that one-off extreme floods have immediate, but short-lived effects, on phytoplankton species composition and biomass as a result of the interacting and dynamic effects of changes in nutrient and light availability
A blind detection of a large, complex, Sunyaev--Zel'dovich structure
We present an interesting Sunyaev-Zel'dovich (SZ) detection in the first of
the Arcminute Microkelvin Imager (AMI) 'blind', degree-square fields to have
been observed down to our target sensitivity of 100{\mu}Jy/beam. In follow-up
deep pointed observations the SZ effect is detected with a maximum peak
decrement greater than 8 \times the thermal noise. No corresponding emission is
visible in the ROSAT all-sky X-ray survey and no cluster is evident in the
Palomar all-sky optical survey. Compared with existing SZ images of distant
clusters, the extent is large (\approx 10') and complex; our analysis favours a
model containing two clusters rather than a single cluster. Our Bayesian
analysis is currently limited to modelling each cluster with an ellipsoidal or
spherical beta-model, which do not do justice to this decrement. Fitting an
ellipsoid to the deeper candidate we find the following. (a) Assuming that the
Evrard et al. (2002) approximation to Press & Schechter (1974) correctly gives
the number density of clusters as a function of mass and redshift, then, in the
search area, the formal Bayesian probability ratio of the AMI detection of this
cluster is 7.9 \times 10^4:1; alternatively assuming Jenkins et al. (2001) as
the true prior, the formal Bayesian probability ratio of detection is 2.1
\times 10^5:1. (b) The cluster mass is MT,200 = 5.5+1.2\times 10^14h-1M\odot.
(c) Abandoning a physical model with num- -1.3 70 ber density prior and instead
simply modelling the SZ decrement using a phenomenological {\beta}-model of
temperature decrement as a function of angular distance, we find a central SZ
temperature decrement of -295+36 {\mu}K - this allows for CMB primary
anisotropies, receiver -15 noise and radio sources. We are unsure if the
cluster system we observe is a merging system or two separate clusters.Comment: accepted MNRAS. 12 pages, 9 figure
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High-Resolution Spectroscopy of K-shell Praseodymium with a High-Energy Calorimeter
We present a measurement of the K-shell spectrum of He-like through Be-like praseodymium ions trapped in the Livermore SuperEBIT electron beam ion trap using a bismuth absorber pixel on the XRS/EBIT microcalorimeter. This measurement is the first of its kind where the n=2 to n=1 transitions of the various charge states are spectroscopically resolved. The measured transition energies are compared with theoretical calculations from several atomic codes
CoastColour Round Robin datasets: A data base to evaluate the performance of algorithms for the retrieval of water quality parameters in coastal waters
The use of in situ measurements is essential in the validation and evaluation of the algorithms that provide coastal water quality data products from ocean colour satellite remote sensing. Over the past decade, various types of ocean colour algorithms have been developed to deal with the optical complexity of coastal waters. Yet there is a lack of a comprehensive intercomparison due to the availability of quality checked in situ databases. The CoastColour Round Robin (CCRR) project, funded by the European Space Agency (ESA), was designed to bring together three reference data sets using these to test algorithms and to assess their accuracy for retrieving water quality parameters. This paper provides a detailed description of these reference data sets, which include the Medium Resolution Imaging Spectrometer (MERIS) level 2 match-ups, in situ reflectance measurements, and synthetic data generated by a radiative transfer model (HydroLight). These data sets, representing mainly coastal waters, are available from doi:10.1594/PANGAEA.841950.
The data sets mainly consist of 6484 marine reflectance (either multispectral or hyperspectral) associated with various geometrical (sensor viewing and solar angles) and sky conditions and water constituents: total suspended matter (TSM) and chlorophyll a (CHL) concentrations, and the absorption of coloured dissolved organic matter (CDOM). Inherent optical properties are also provided in the simulated data sets (5000 simulations) and from 3054 match-up locations. The distributions of reflectance at selected MERIS bands and band ratios, CHL and TSM as a function of reflectance, from the three data sets are compared. Match-up and in situ sites where deviations occur are identified. The distributions of the three reflectance data sets are also compared to the simulated and in situ reflectances used previously by the International Ocean Colour Coordinating Group (IOCCG, 2006) for algorithm testing, showing a clear extension of the CCRR data which covers more turbid waters.JRC.H.1-Water Resource
Phytoplankton functional types from Space.
The concept of phytoplankton functional types has emerged as a useful approach to
classifying phytoplankton. It finds many applications in addressing some serious
contemporary issues facing science and society. Its use is not without challenges,
however. As noted earlier, there is no universally-accepted set of functional types,
and the types used have to be carefully selected to suit the particular problem being
addressed. It is important that the sum total of all functional types matches all
phytoplankton under consideration. For example, if in a biogeochemical study,
we classify phytoplankton as silicifiers, calcifiers, DMS-producers and nitrogen fix-
ers, then there is danger that the study may neglect phytoplankton that do not
contribute in any significant way to those functions, but may nevertheless be a
significant contributor to, say primary production. Such considerations often lead
to the adoption of a category of “other phytoplankton” in models, with no clear
defining traits assigned them, but that are nevertheless necessary to close budgets
on phytoplankton processes. Since this group is a collection of all phytoplankton
that defy classification according to a set of traits, it is difficult to model their physi-
ological processes. Our understanding of the diverse functions of phytoplankton is
still growing, and as we recognize more functions, there will be a need to balance the
desire to incorporate the increasing number of functional types in models against
observational challenges of identifying and mapping them adequately. Modelling
approaches to dealing with increasing functional diversity have been proposed,
for example, using the complex adaptive systems theory and system of infinite
diversity, as in the work of Bruggemann and Kooijman (2007). But it is unlikely that
remote-sensing approaches might be able to deal with anything but a few prominent
functional types. As long as these challenges are explicitly addressed, the functional-
type concept should continue to fill a real need to capture, in an economic fashion,
the diversity in phytoplankton, and remote sensing should continue to be a useful
tool to map them.
Remote sensing of phytoplankton functional types is an emerging field, whose
potential is not fully realised, nor its limitations clearly established. In this report,
we provide an overview of progress to date, examine the advantages and limitations
of various methods, and outline suggestions for further development. The overview
provided in this chapter is intended to set the stage for detailed considerations of
remote-sensing applications in later chapters.
In the next chapter, we examine various in situ methods that exist for observing
phytoplankton functional types, and how they relate to remote-sensing techniques.
In the subsequent chapters, we review the theoretical and empirical bases for the
existing and emerging remote-sensing approaches; assess knowledge about the
limitations, assumptions, and likely accuracy or predictive skill of the approaches;
provide some preliminary comparative analyses; and look towards future prospects
with respect to algorithm development, validation studies, and new satellite mis-
sions
A large scale hearing loss screen reveals an extensive unexplored genetic landscape for auditory dysfunction
The developmental and physiological complexity of the auditory system is likely reflected in the underlying set of genes involved in auditory function. In humans, over 150 non-syndromic loci have been identified, and there are more than 400 human genetic syndromes with a hearing loss component. Over 100 non-syndromic hearing loss genes have been identified in mouse and human, but we remain ignorant of the full extent of the genetic landscape involved in auditory dysfunction. As part of the International Mouse Phenotyping Consortium, we undertook a hearing loss screen in a cohort of 3006 mouse knockout strains. In total, we identify 67 candidate hearing loss genes. We detect known hearing loss genes, but the vast majority, 52, of the candidate genes were novel. Our analysis reveals a large and unexplored genetic landscape involved with auditory function
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