Fluorescence Switching for Temperature Sensing in Water.

A water-soluble thermochromic molecular switch with spectrally resolved fluorescence in its two interconvertible states can be assembled in three synthetic steps by integrating a fluorescent coumarin chromophore, a hydrophilic oligo(ethylene glycol) chain, and a switchable oxazole heterocycle in the same covalent skeleton. Measurements of its two emissions in separate detection channels of a fluorescence microscope permit the noninvasive and ratiometric sensing of temperature at the micrometer level with millisecond response in aqueous solutions and within hydrogel matrices. The ratiometric optical output of this fluorescent molecular switch overcomes the limitations of single-wavelength fluorescent probes and enables noninvasive temperature mapping at length scales that are not accessible to conventional thermometers based on physical contact.

Long-term evaluation of three satellite ocean color algorithms for identifying harmful algal blooms (Karenia brevis) along the west coast of Florida: A matchup assessment.

We present a simple algorithm to identify Karenia brevis blooms in the Gulf of Mexico along the west coast of Florida in satellite imagery. It is based on an empirical analysis of collocated matchups of satellite and in situ measurements. The results of this Empirical Approach is compared to those of a Bio-optical Technique - taken from the published literature - and the Operational Method currently implemented by the NOAA Harmful Algal Bloom Forecasting System for K. brevis blooms. These three algorithms are evaluated using a multi-year MODIS data set (from July, 2002 to October, 2006) and a long-term in situ database. Matchup pairs, consisting of remotely-sensed ocean color parameters and near-coincident field measurements of K. brevis concentration, are used to assess the accuracy of the algorithms. Fair evaluation of the algorithms was only possible in the central west Florida shelf (i.e. between 25.75°N and 28.25°N) during the boreal Summer and Fall months (i.e. July to December) due to the availability of valid cloud-free matchups. Even though the predictive values of the three algorithms are similar, the statistical measure of success in red tide identification (defined as cell counts in excess of 1.5 × 10(4) cells L(-1)) varied considerably (sensitivity-Empirical: 86%; Bio-optical: 77%; Operational: 26%), as did their effectiveness in identifying non-bloom cases (specificity-Empirical: 53%; Bio-optical: 65%; Operational: 84%). As the Operational Method had an elevated frequency of false-negative cases (i.e. presented low accuracy in detecting known red tides), and because of the considerable overlap between the optical characteristics of the red tide and non-bloom population, only the other two algorithms underwent a procedure for further inspecting possible detection improvements. Both optimized versions of the Empirical and Bio-optical algorithms performed similarly, being equally specific and sensitive (~70% for both) and showing low levels of uncertainties (i.e. few cases of false-negatives and false-positives: ~30%)-improved positive predictive values (~60%) were also observed along with good negative predictive values (~80%).

Satellite remote sensing of harmful algal blooms: A new multi-algorithm method for detecting the Florida Red Tide (Karenia brevis).

In a continuing effort to develop suitable methods for the surveillance of Harmful Algal Blooms (HABs) of Karenia brevis using satellite radiometers, a new multi-algorithm method was developed to explore whether improvements in the remote sensing detection of the Florida Red Tide was possible. A Hybrid Scheme was introduced that sequentially applies the optimized versions of two pre-existing satellite-based algorithms: an Empirical Approach (using water-leaving radiance as a function of chlorophyll concentration) and a Bio-optical Technique (using particulate backscatter along with chlorophyll concentration). The long-term evaluation of the new multi-algorithm method was performed using a multi-year MODIS dataset (2002 to 2006; during the boreal Summer-Fall periods - July to December) along the Central West Florida Shelf between 25.75°N and 28.25°N. Algorithm validation was done with in situ measurements of the abundances of K. brevis; cell counts ≥1.5×10(4) cells l(-1) defined a detectable HAB. Encouraging statistical results were derived when either or both algorithms correctly flagged known samples. The majority of the valid match-ups were correctly identified (~80% of both HABs and non-blooming conditions) and few false negatives or false positives were produced (~20% of each). Additionally, most of the HAB-positive identifications in the satellite data were indeed HAB samples (positive predictive value: ~70%) and those classified as HAB-negative were almost all non-bloom cases (negative predictive value: ~86%). These results demonstrate an excellent detection capability, on average ~10% more accurate than the individual algorithms used separately. Thus, the new Hybrid Scheme could become a powerful tool for environmental monitoring of K. brevis blooms, with valuable consequences including leading to the more rapid and efficient use of ships to make in situ measurements of HABs.

Net community production and dark community respiration in a Karenia brevis (Davis) bloom in West Florida coastal waters, USA.

Oxygen-based productivity and respiration rates were determined in West Florida coastal waters to evaluate the proportion of community respiration demands met by autotrophic production within a harmful algal bloom dominated by Karenia brevis. The field program was adaptive in that sampling during the 2006 bloom occurred where surveys by the Florida Wildlife Research Institute indicated locations with high cell abundances. Net community production (NCP) rates from light-dark bottle incubations during the bloom ranged from 10 to 42 µmole O2 L-1 day-1 with highest rates in bloom waters where abundances exceeded 105 cells L-1. Community dark respiration (R) rates in dark bottles ranged from <10 to 70 µmole O2 L-1 day-1 over 24 h. Gross primary production derived from the sum of NCP and R varied from ca. 20 to 120 µmole O2 L-1 day-1. The proportion of GPP attributed to NCP varied with the magnitude of R during day and night periods. Most surface communities exhibited net autotrophic production (NCP > R) over 24 h, although heterotrophy (NCP < R) characterized the densest sample where K. brevis cell densities exceed 106 cells L-1.

Environmental controls, oceanography and population dynamics of pathogens and harmful algal blooms: connecting sources to human exposure.

Coupled physical-biological models are capable of linking the complex interactions between environmental factors and physical hydrodynamics to simulate the growth, toxicity and transport of infectious pathogens and harmful algal blooms (HABs). Such simulations can be used to assess and predict the impact of pathogens and HABs on human health. Given the widespread and increasing reliance of coastal communities on aquatic systems for drinking water, seafood and recreation, such predictions are critical for making informed resource management decisions. Here we identify three challenges to making this connection between pathogens/HABs and human health: predicting concentrations and toxicity; identifying the spatial and temporal scales of population and ecosystem interactions; and applying the understanding of population dynamics of pathogens/HABs to management strategies. We elaborate on the need to meet each of these challenges, describe how modeling approaches can be used and discuss strategies for moving forward in addressing these challenges.

Emissivity and reflection model for calculating unpolarized isotropic water surface-leaving radiance in the infrared. 2: validation using Fourier transform spectrometers.

The surface-leaving radiance model developed in Part I [Appl. Opt.47,3701 (2008)] is validated against an exhaustive set of Fourier transform spectrometer field observations acquired at sea. Unlike prior limited studies, these data include varying all-sky atmospheric conditions (clear, cloudy, and dusty), with regional samples from the tropics, mid-latitudes, and high latitudes. Our analyses show the model to have reduced bias over standard models at emission angles > or = 45 degrees.

Emissivity and reflection model for calculating unpolarized isotropic water surface-leaving radiance in the infrared. I: Theoretical development and calculations.

Although published sea surface infrared (IR) emissivity models have gained widespread acceptance for remote sensing applications, discrepancies have been identified against field observations obtained from IR Fourier transform spectrometers at view angles approximately > 40 degrees. We therefore propose, in this two-part paper, an alternative approach for calculating surface-leaving IR radiance that treats both emissivity and atmospheric reflection in a systematic yet practical manner. This first part presents the theoretical basis, development, and computations of the proposed model.

Measurements of the infrared emissivity of a wind-roughened sea surface.

Spectral statistical-analysis techniques were developed and applied to high-spectral-resolution infrared measurements of the sea surface. The effective incidence angle of a ship-borne instrument in typical at-sea conditions was found to introduce errors of up to 0.7 K in sea-surface temperature retrievals at a 55 degrees view angle. The sea-surface emissivity was determined over the 8-12-microm window at view angles of 40 degrees and 55 degrees and at wind speeds up to 13 ms(-1). The emissivity was found to increase in magnitude with increasing wind speed, rather than decrease, as predicted by widely used parameterizations. Use of these parameterizations can cause significant bias in remote sensing of sea-surface temperature in noncalm conditions.