Estimation of phytoplankton production from space: current status and future potential of satellite remote sensing

A new generation of ocean colour satellites is now operational, with frequent observation of the global ocean. This paper reviews the potential to estimate marine primary production from satellite images. The procedures involved in retrieving estimates of phytoplankton biomass, as pigment concentrations, are discussed. Algorithms are applied to SeaWiFS ocean colour data to indicate seasonal variations in phytoplankton biomass in the Celtic Sea, on the continental shelf to the south west of the UK. Algorithms to estimate primary production rates from chlorophyll concentration are compared and the advantages and disadvantage discussed. The simplest algorithms utilise correlations between chlorophyll concentration and production rate and one equation is used to estimate daily primary production rates for the western English Channel and Celtic Sea; these estimates compare favourably with published values. Primary production for the central Celtic Sea in the period April to September inclusive is estimated from SeaWiFS data to be 102 gC m⁻² in 1998 and 93 gC m⁻² in 1999; published estimates, based on in situ incubations, are ca. 80 gC m⁻². The satellite data demonstrate large variations in primary production between 1998 and 1999, with a significant increase in late summer in 1998 which did not occur in 1999. Errors are quantified for the estimation of primary production from simple algorithms based on satellite-derived chlorophyll concentration. These data show the potential to obtain better estimates of marine primary production than are possible with ship-based methods, with the ability to detect short-lived phytoplankton blooms. In addition, the potential to estimate new production from satellite data is discussed.     

Validation of the MERIS products on large European lakes: Peipsi,Vänern and Vättern

The Medium Resolution Imaging Spectrometer (MERIS/Envisat) was launched in March 2002 for coastal zone monitoring. Preliminary data from MERIS show that its imagery of large lakes is superior to that of other common ocean colour sensors. The main objective of the present study is to evaluate the MERIS data on large European lakes, Vänern and Vättern in Sweden and Peipsi in Estonia/Russia. In these lakes, coloured dissolved organic matter (CDOM) can be a major contributor to the optical properties of the water. Another characteristic of the waters under investigation is the large temporal and spatial variability in the concentrations of chlorophyll (C _Chl) and suspended sediments (C _TSS). Potentially toxic cyanobacterial blooms occur in Lake Peipsi in late summer. We have compared the MERIS products from the latest reprocessing (finished in March 2006) with available in situ data. There is a reasonably good correlation between the MERIS algal_2 product and the measured C _chl over all three lakes, but no correlation was found for other optically active substances. A significant portion of the pixels (up to 90%) are flagged as invalid results after atmospheric correction.     

Suspended Particulate Matter detection in the North Sea by hyper spectral airborne remote sensing

A spectral model is developed describing the relation between optical spectral reflectance and sampled suspended particulate matter concentration. This reflectance model is based on inherent optical properties of North Sea colouring water constituents. Hyper spectral airborne observations by a CASI scanner are carried out in the Dutch coastal zone and interpreted making use of the reflectance model. A non linear relation between reflectance and suspended particulate matter concentration is found. Variability of sampled suspended matter concentration is high, in contrast to this the variability of interpreted spectral measurements is much lower. Abbreviations: IOP – inherent optical properties; CASI – compact airborne spectral imager; SPM – suspended particulate matter; CHL – chlorophyll; FWHM – full width half maximum; r.m.s – root mean square.     

A review on substances and processes relevant for optical remote sensing of extremely turbid marine areas, with a focus on the Wadden Sea

The interpretation of optical remote sensing data of estuaries and tidal flat areas is hampered by optical complexity and often extreme turbidity. Extremely high concentrations of suspended matter, chlorophyll and dissolved organic matter, local differences, seasonal and tidal variations and resuspension are important factors influencing the optical properties in such areas. This review gives an overview of the processes in estuaries and tidal flat areas and the implications of these for remote sensing in such areas, using the Wadden Sea as a case study area. Results show that remote sensing research in extremely turbid estuaries and tidal areas is possible. However, this requires sensors with a large ground resolution, algorithms tuned for high concentrations of various substances and the local specific optical properties of these substances, a simultaneous detection of water colour and land–water boundaries, a very short time lag between acquisition of remote sensing and in situ data used for validation and sufficient geophysical and ecological knowledge of the area.     

Applications of Satellite Ocean Color Sensors for Monitoring and Predicting Harmful Algal Blooms

The new satellite ocean color sensors offer a means of detecting and monitoring algal blooms in the ocean and coastal zone. Beginning with SeaWiFS (Sea Wide Field-of-view Sensor) in September 1997, these sensors provide coverage every 1 to 2 days with 1-km pixel view at nadir. Atmospheric correction algorithms designed for the coastal zone combined with regional chlorophyll algorithms can provide good and reproducible estimates of chlorophyll, providing the means of monitoring various algal blooms. Harmful algal blooms (HABs) caused by Karenia brevis in the Gulf of Mexico are particularly amenable to remote observation. The Gulf of Mexico has relatively clear water and K. brevis, in bloom conditions, tends to produce a major portion of the phytoplankton biomass. A monitoring program has begun in the Gulf of Mexico that integrates field data from state monitoring programs with satellite imagery, providing an improved capability for the monitoring of K. brevis blooms.     

Use of SeaWiFS ocean color data to estimate neritic sediment mass transport from carbonate platforms for two hurricane-forced events

Plumes of neritic sediment caused by the passage of Hurricane Gert near Bermuda in 1999, and by the passage of Hurricane Michelle over Cubas Gulf of Batabano in 2001, were observed by the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). The mass of sediments in each of these plumes, which consist largely of neritic carbonate particles, was estimated using an algorithm for the calculation of suspended sediment concentrations. The Bermuda and Batabano plumes transported 0.22 and 1.2–1.35 million kg of sediment, respectively. The algorithm results were compared with the results from two other sediment mass algorithms and proved to be consistent. These results indicate the potential use of remote sensing to estimate carbonate flux from coral reefs and banks and atolls as an augmentation to in situ studies. In addition, the use of remote sensing data may improve estimates of the annual global carbonate sediment flux, a quantity important to models of global carbonate production and the global carbon cycle.James G. Acker and Denis Nadeau are employed by Science Systems and Applications, Inc.     

Satellite detection of harmful algal bloom occurrences in Korean waters

Cochlodinium polykrikoides (p) is a planktonic dinoflagellate known to produce red tides responsible for massive fish kills and thereby serious economic loss in Korean coastal waters, particularly during summer and fall seasons. The present study involved analyzing chlorophyll-a (Chl-a) from SeaWiFS ocean color imagery collected over the period 1998–2002 to understand the spatial and temporal aspects of C. polykrikoides blooms that occurred in the enclosed and semi-enclosed bays of the Korean Southeast Sea. NOAA-AVHRR data were used to derive Sea Surface Temperature (SST) to elucidate physical factors affecting the spatial distribution and abundance of C. polykrikoides blooms. The time series of SeaWiFS-derived Chl-a gave an impression that recent red tide events with higher concentrations appeared to span more than 8 weeks during summer and fall seasons and were widespread in most of the Korean Southeast Sea coastal bays and neighboring oceanic waters. Coupled eutrophication and certain oceanic processes were thought to give rise to the formation of massive C. polykrikoides blooms with cell abundances ranging from 1000 to 30,000 cells ml⁻¹, causing heavy mortalities of aquaculture fish and other marine organisms in these areas. Our analysis indicated that Chl-a estimates from SeaWiFS ocean color imagery appeared to be useful in demarcating the locality, spatial extent and distribution of these blooms, but unique identification of C. polykrikoides from non-bloom and sediment dominated waters remains unsuccessful with this data alone. Thus, the classical spectral enhancement and classification techniques such as Forward Principal Component Analysis (FPCA) and Minimum Spectral Distance (MSD) to uniquely identify and better understand C. polykrikoides blooms characteristics from other optical water types were attempted on both low spatial resolution SeaWiFS ocean color imagery and high spatial resolution Landsat-7 ETM+ imagery. Application of these techniques could capture intricate and striking patterns of C. polykrikoides blooms from surrounding non-bloom and sediment dominated waters, providing improved capability of detecting, predicting and monitoring C. polykrikoides bloom in such optically complex waters. The result obtained from MSD classification showed that retrieval of C. polykrikoides bloom from the mixed phase of this bloom with turbid waters was not feasible with the SeaWiFS ocean color imagery, but feasible with Landsat-7 ETM+ imagery that provided more accurate and comparable spatial C. polykrikoides patterns consistent with in situ observations. The dense phase of the bloom estimated from these imageries occupied an area of more than 25 km² around the coastal bays and the mixed phase extended over several hundreds kilometers towards the Southeast Sea offshore due to exchange of water masses caused by coastal and oceanic processes. Sea surface temperature analyzed from AVHRR infrared data captured the northeastward flow of Tsushima Warm Current (TWC) waters that provided favorable environmental conditions for the rapid growth and subsequent southward initiation of C. polykrikoides blooms in hydrodynamically active regions in the Korean Southeast Sea offshore.     

Sources,concentrations and characteristics of organic matter in softwater lakes and streams of the Swedish forest region

18 Swedish forest lakes covering a wide range of dystrophy were studied in order to quantify and characterize the organic matter in the water with respect to origin (allochthonous or autochthonous), physical state (particulate or dissolved) and phosphorus content. Samples were collected repeatedly during a two-year period with unusually variable hydrological conditions. Water from three different depths and from tributaries was analysed with standard monitoring methods, including water colour, Secchi disk transparency, total organic carbon (TOC), COD_Cr, COD_Mn, total phosphorus and molybdate reactive phosphorus. Interrelationships were used to compare different methods and to assess the concentration and composition of organic matter. It is estimated that in remote softwater lakes of the Swedish forest region, autochthonous carbon is typically < 5 g m⁻³. Most lakes in this region receive significant amounts of humic matter originating from coniferous forest soils or peatland in the catchment area. In most humic lakes with a water colour of ≥ 50 g Pt m⁻³, more than half of the organic carbon in the surface water is of allochthonous origin, and in polyhumic lakes (> 200 g Pt m⁻³) the proportion can exceed 90%. Secchi depth readings were related similarly to organic matter from both sources and provided good estimates of TOC with a single optical measurement. Water colour was used to distinguish allochthonous and autochthonous matter. High concentrations of phosphorus were found in humic waters, most of it being molybdate reactive, and probably associated with humic matter rather than as dissolved free inorganic forms. COD_Mn yielded only 25–60% of TOC and appears to include mainly truly dissolved substances of low molecular weight.     

Analysing spectral data: comparison and application of two techniques

This study compares two different methods of condensing complex spectral data into interpretable indices or metrics of colour. Colour spectra were measured on standardized Munsell colour paint chips and estimates of the three fundamental components of colour (brightness, chroma and hue) were generated using principal component analysis (PCA) and segment classification (SC). We tested the accuracy of these techniques for generating colour component estimates from spectral data in four different 'colour classes' (red/orange, yellow/ green, green/blue, and blue/purple) and in an aggregate data set containing all measured spectra. We conclude that both analysis techniques will generally provide more information than more conventional colour assessment techniques. Neither technique was superior under all conditions; appropriateness of each technique depends on the system under study. Efficacy of both techniques depends on the variability present in the data set; greater variance in colour tends to reduce overall resolution. An application of tfiese techniques is also presented in which we characterize sex-specific differences in colour between different populations of the poecilliid fish, Limia perugia.     

Natural selection in a postglacial range expansion: the case of the colour cline in the European barn owl

Gradients of variation—or clines—have always intrigued biologists. Classically, they have been interpreted as the outcomes of antagonistic interactions between selection and gene flow. Alternatively, clines may also establish neutrally with isolation by distance (IBD) or secondary contact between previously isolated populations. The relative importance of natural selection and these two neutral processes in the establishment of clinal variation can be tested by comparing genetic differentiation at neutral genetic markers and at the studied trait. A third neutral process, surfing of a newly arisen mutation during the colonization of a new habitat, is more difficult to test. Here, we designed a spatially explicit approximate Bayesian computation (ABC) simulation framework to evaluate whether the strong cline in the genetically based reddish coloration observed in the European barn owl (Tyto alba) arose as a by‐product of a range expansion or whether selection has to be invoked to explain this colour cline, for which we have previously ruled out the actions of IBD or secondary contact. Using ABC simulations and genetic data on 390 individuals from 20 locations genotyped at 22 microsatellites loci, we first determined how barn owls colonized Europe after the last glaciation. Using these results in new simulations on the evolution of the colour phenotype, and assuming various genetic architectures for the colour trait, we demonstrate that the observed colour cline cannot be due to the surfing of a neutral mutation. Taking advantage of spatially explicit ABC, which proved to be a powerful method to disentangle the respective roles of selection and drift in range expansions, we conclude that the formation of the colour cline observed in the barn owl must be due to natural selection.     

Specific attenuation coefficients of optically active substances and their contribution to the underwater ultraviolet and visible light climate in shallow lakes and ponds

Sunlight penetration through the water column is controlled by the amount and kind of materials dissolved and suspended in the water. Understanding UV penetration in its complexity is essential for the prediction of the impact of UV radiation on aquatic ecosystems. However, only limited data are available on the penetration of UVR into shallow waters rich in inorganic suspended solids and chromophoric dissolved organic matter (CDOM). The same is true for the specific attenuation coefficients of light-absorbing components at the UV waveband. This study analyses the role of CDOM, algal-free suspended solids and algae in the formation of underwater UVR and PAR climate in 30 water bodies from clear gravel pit lakes trough the shallow Lake Balaton to turbid soda pans. Irradiance-depth profiles were obtained at 305, 313, 320 nm (UV-B), 340, 380, 395 nm (UV-A) and 400–700 nm (PAR) with a Biospherical PUV-2500 radiometer. Vertical attenuation coefficients (K _d) were calculated. Water samples were taken for the laboratory measurement of the concentration of light-absorbing components: algae as chlorophyll a (CHL), chromophoric dissolved organic matter as colour (CDOM), and algal-free suspended solids (TSS-Alg) parallel with the in situ light measurements. Specific attenuation coefficient values were calculated by multiple regression analysis (n = 140). The obtained specific UV attenuation coefficient values of CHL, CDOM and TSS-Alg made it possible to establish light attenuation at different wavelengths based on the knowledge of the concentration of these light-absorbing components.     

A meta-analysis of pigmentary characteristics,sun sensitivity,freckling and melanocytic nevi and risk of basal cell carcinoma of the skin

ObjectiveTo calculate pooled risk estimates of the association between pigmentary characteristics and basal cell carcinoma (BCC) of the skin.MethodsWe searched three electronic databases and reviewed the reference lists of the retrieved articles until July 2012 to identify eligible epidemiologic studies. Eligible studies were those published in between 1965 and July 2012 that permitted quantitative assessment of the association between histologically-confirmed BCC and any of the following characteristics: hair colour, eye colour, skin colour, skin phototype, tanning and burning ability, and presence of freckling or melanocytic nevi. We included 29 studies from 2236 initially identified. We calculated summary odds ratios (ORs) using weighted averages of the log OR, using random effects models.ResultsWe found strongest associations with red hair (OR 2.02; 95% CI: 1.68, 2.44), fair skin colour (OR 2.11; 95% CI: 1.56, 2.86), and having skin that burns and never tans (OR 2.03; 95% CI: 1.73, 2.38). All other factors had weaker but positive associations with BCC, with the exception of freckling of the face in adulthood which showed no association.ConclusionsAlthough most studies report risk estimates that are in the same direction, there is significant heterogeneity in the size of the estimates. The associations were quite modest and remarkably similar, with ORs between about 1.5 and 2.5 for the highest risk level for each factor. Given the public health impact of BCC, this meta-analysis will make a valuable contribution to our understanding of BCC.     

Using digital photography to study animal coloration

In understanding how visual signals function, quantifying the components of those patterns is vital. With the ever-increasing power and availability of digital photography, many studies are utilizing this technique to study the content of animal colour signals. Digital photography has many advantages over other techniques, such as spectrometry, for measuring chromatic information, particularly in terms of the speed of data acquisition and its relatively cheap cost. Not only do digital photographs provide a method of quantifying the chromatic and achromatic content of spatially complex markings, but also they can be incorporated into powerful models of animal vision. Unfortunately, many studies utilizing digital photography appear to be unaware of several crucial issues involved in the acquisition of images, notably the nonlinearity of many cameras' responses to light intensity, and biases in a camera's processing of the images towards particular wavebands. In the present study, we set out step-by-step guidelines for the use of digital photography to obtain accurate data, either independent of any particular visual system (such as reflection values), or for particular models of nonhuman visual processing (such as that of a passerine bird). These guidelines include how to: (1) linearize the camera's response to changes in light intensity; (2) equalize the different colour channels to obtain reflectance information; and (3) produce a mapping from camera colour space to that of another colour space (such as photon catches for the cone types of a specific animal species).  © 2007 The Linnean Society of London, Biological Journal of the Linnean Society , 2007, 90 , 211–237.     

From silk to satellite: half a century of ocean colour anomalies in the Northeast Atlantic

Changes in phytoplankton dynamics influence marine biogeochemical cycles, climate processes, and food webs, with substantial social and economic consequences. Large‐scale estimation of phytoplankton biomass was possible via ocean colour measurements from two remote sensing satellites – the Coastal Zone Colour Scanner (CZCS, 1979–1986) and the Sea‐viewing Wide Field‐of‐view Sensor (SeaWiFS, 1998–2010). Due to the large gap between the two satellite eras and differences in sensor characteristics, comparison of the absolute values retrieved from the two instruments remains challenging. Using a unique in situ ocean colour dataset that spans more than half a century, the two satellite‐derived chlorophyll‐a (Chl‐a) eras are linked to assess concurrent changes in phytoplankton variability and bloom timing over the Northeast Atlantic Ocean and North Sea. Results from this unique re‐analysis reflect a clear increasing pattern of Chl‐a, a merging of the two seasonal phytoplankton blooms producing a longer growing season and higher seasonal biomass, since the mid‐1980s. The broader climate plays a key role in Chl‐a variability as the ocean colour anomalies parallel the oscillations of the Northern Hemisphere Temperature (NHT) since 1948.     

Satellite discrimination of Karenia mikimotoi and Phaeocystis harmful algal blooms in European coastal waters: Merged classification of ocean colour data

The detection of dense harmful algal blooms (HABs) by satellite remote sensing is usually based on analysis of chlorophyll-a as a proxy. However, this approach does not provide information about the potential harm of bloom, nor can it identify the dominant species. The developed HAB risk classification method employs a fully automatic data-driven approach to identify key characteristics of water leaving radiances and derived quantities, and to classify pixels into “harmful”, “non-harmful” and “no bloom” categories using Linear Discriminant Analysis (LDA). Discrimination accuracy is increased through the use of spectral ratios of water leaving radiances, absorption and backscattering. To reduce the false alarm rate the data that cannot be reliably classified are automatically labelled as “unknown”. This method can be trained on different HAB species or extended to new sensors and then applied to generate independent HAB risk maps; these can be fused with other sensors to fill gaps or improve spatial or temporal resolution. The HAB discrimination technique has obtained accurate results on MODIS and MERIS data, correctly identifying 89% of Phaeocystis globosa HABs in the southern North Sea and 88% of Karenia mikimotoi blooms in the Western English Channel. A linear transformation of the ocean colour discriminants is used to estimate harmful cell counts, demonstrating greater accuracy than if based on chlorophyll-a; this will facilitate its integration into a HAB early warning system operating in the southern North Sea.     

Coupling satellite data with in situ measurements and numerical modeling to study fine suspended-sediment transport: a study for the lagoon of New Caledonia

This paper investigates the potential of remotely sensed data to map turbidity in a coral reef lagoon and to calibrate a numerical model of fine suspended-sediment transport. Simultaneous measurements of turbidity depth-profile and above-water spectral reflectance integrated according Landsat 7 ETM+ band 2 spectral sensitivity provide a linear regression relationship for the southwest lagoon of New Caledonia (r²=0.95, n=40). This relationship is applied to an empirically atmospherically corrected Landsat ETM+ image of the lagoon acquired on October 23, 2002. A comparison between Landsat estimates of turbidity and concurrent measurements at 14 stations indicates that the mean standard error in the satellite-estimated turbidity is 17.5%. The numerical model introduced in Douillet et al. (2001) is used to simulate the transport of fine suspended sediments in the lagoon in October 2002. A calibration of the erosion rate coefficient required by the model is proposed using in situ turbidity profiles and the remotely sensed turbidity field. In situ data are used to tune locally the erosion rate coefficient, while satellite data are used to determine its spatial zonation. We discuss necessary improvements in coupled studies of fine-sediment transport in coastal zones, namely relationships between turbidity and sediment concentration, integration of wave influence in the model, and correction of bottom reflection in satellite data processing.     

Wind-Mediated Spread of Low-Pathogenic Avian Influenza Virus into the Environment during Outbreaks at Commercial Poultry Farms

Avian influenza virus-infected poultry can release a large amount of virus-contaminated droppings that serve as sources of infection for susceptible birds. Much research so far has focused on virus spread within flocks. However, as fecal material or manure is a major constituent of airborne poultry dust, virus-contaminated particulate matter from infected flocks may be dispersed into the environment. We collected samples of suspended particulate matter, or the inhalable dust fraction, inside, upwind and downwind of buildings holding poultry infected with low-pathogenic avian influenza virus, and tested them for the presence of endotoxins and influenza virus to characterize the potential impact of airborne influenza virus transmission during outbreaks at commercial poultry farms. Influenza viruses were detected by RT-PCR in filter-rinse fluids collected up to 60 meters downwind from the barns, but virus isolation did not yield any isolates. Viral loads in the air samples were low and beyond the limit of RT-PCR quantification except for one in-barn measurement showing a virus concentration of 8.48x10⁴ genome copies/m³. Air samples taken outside poultry barns had endotoxin concentrations of ~50 EU/m³ that declined with increasing distance from the barn. Atmospheric dispersion modeling of particulate matter, using location-specific meteorological data for the sampling days, demonstrated a positive correlation between endotoxin measurements and modeled particulate matter concentrations, with an R² varying from 0.59 to 0.88. Our data suggest that areas at high risk for human or animal exposure to airborne influenza viruses can be modeled during an outbreak to allow directed interventions following targeted surveillance.     

Effect of a waveband shift on chlorophyll retrieval from MERIS imagery of inland and coastal waters

A chlorophyll-retrieval algorithm for use with imagery fromthe Medium Resolution Imaging Spectrometer (MERIS) aboard ENVISATrelying on wavebands centred at 665, 705 and 775 nm was describedin a previous paper (Gons et al. 2002, J. Plankton Res., 24,947–951). The present study reexamined the performancefor the current nominal setting to 708.75 nm of the previouslyenvisaged 705 nm band. Validation of the algorithm with revisedcoefficients gave the same standard error of estimate for theinland and coastal waters as in the original work. The algorithmhas been transcribed for direct application with the MERIS level-2standard product ‘water-leaving reflectance’. Bythis correction, chlorophyll estimation will generally improve,especially for high concentrations.     

Maintenance of clinal variation for shell colour phenotype in the flat periwinkle Littorina obtusata

Clines can signal spatially varying selection and therefore have long been used to investigate the role of environmental heterogeneity in maintaining genetic variation. However, clinal patterns alone are not sufficient to reject neutrality or to establish the mechanism of selection. Indirect, inferential methods can be used to address neutrality and mechanism, but fully understanding the adaptive significance of clinal variation ultimately requires a direct approach. Ecological model systems such as the rocky intertidal provide a useful context for direct experimentation and can serve as a complement to studies in more traditional genetic model systems. In this study, we use indirect and direct approaches to investigate the role of environmental heterogeneity in the maintenance of shell colour polymorphism in the flat periwinkle snail, Littorina obtusata. We document replicated clines in shell colour morph frequencies over thermal gradients at two spatial scales, contrasting with patterns at previously reported microsatellite loci. In addition, experimental results demonstrate that that shell colour has predictable effects on shell temperature and that these differences in temperature, in turn, coincide with patterns of survivorship under episodic thermal stress. Direct manipulation of shell colour revealed that shell colour, and not a correlated character, was the target of selection. Our study provides evidence that spatially varying selection via thermal regime contributes to the maintenance of shell colour phenotype variation in L. obtusata in the sampled areas of the Gulf of Maine.