Book contents
- Frontmatter
- Contents
- Contributors
- Preface
- Acknowledgements
- Abbreviations and symbols
- Part I Chlorophylls and carotenoids
- Part II Methodology guidance
- Part III Water-soluble ‘pigments’
- Part IV Selected pigment applications in oceanography
- 11 Pigments and photoacclimation processes
- 12 Pigment-based measurements of phytoplankton rates
- 13 In vivo bio-optical properties of phytoplankton pigments
- 14 Optical monitoring of phytoplankton bloom pigment signatures
- Part V Future perspectives
- Part VI Aids for practical laboratory work
- Part VII Data sheets aiding identification of phytoplankton carotenoids and chlorophylls
- Index
- Plate Section
- References
14 - Optical monitoring of phytoplankton bloom pigment signatures
Published online by Cambridge University Press: 05 March 2012
Book contents
- Frontmatter
- Contents
- Contributors
- Preface
- Acknowledgements
- Abbreviations and symbols
- Part I Chlorophylls and carotenoids
- Part II Methodology guidance
- Part III Water-soluble ‘pigments’
- Part IV Selected pigment applications in oceanography
- 11 Pigments and photoacclimation processes
- 12 Pigment-based measurements of phytoplankton rates
- 13 In vivo bio-optical properties of phytoplankton pigments
- 14 Optical monitoring of phytoplankton bloom pigment signatures
- Part V Future perspectives
- Part VI Aids for practical laboratory work
- Part VII Data sheets aiding identification of phytoplankton carotenoids and chlorophylls
- Index
- Plate Section
- References
Summary
Introduction
The absorption of light by algal pigments determines the cellular absorption of phytoplankton and thus contributes to the in situ optical signatures of coastal and offshore waters. This is the basis of a range of bio-optical approaches used for monitoring phytoplankton distribution (taxa and biomass) and is the focus of this chapter. Details regarding bio-optical signatures of phytoplankton and their spectral absorption, scattering and fluorescence characteristics are covered in Chapter 13, this volume. Details of how phytoplankton adjust their pigments in response to variation in light climate are reviewed in Chapter 11, this volume.
Phytoplankton blooms cover spatial scales that vary from patches of 1 m2 to large blooms covering more than 1 × 106 km2 (Franks, 1997; Smyth et al., 2004; Schofield et al., 2008). Related to the spatial scale is the temporal variability of these blooms (from minutes to years), depending on the physical and biological processes at a given location. The development of techniques for monitoring phytoplankton blooms at different geographical and temporal scales has evolved rapidly in recent years (Kahru and Brown, 1997; Schofield et al., 1999; Babin et al., 2008). Because of the wide range in scale, different methods and approaches (different sensors and corresponding platforms) are needed for monitoring water masses and associated phytoplankton blooms as a function of environmental change (i.e. temperature, salinity, circulation and light regime), biogeochemical cycling, eutrophication, ocean acidification and pollution. Globally, monitoring of phytoplankton bloom dynamics is important to estimate changes in primary productivity affecting carbon and nutrient cycling in the world oceans.
- Type
- Chapter
- Information
- Phytoplankton PigmentsCharacterization, Chemotaxonomy and Applications in Oceanography, pp. 538 - 606Publisher: Cambridge University PressPrint publication year: 2011
References
2005 Remote sensing of phytoplankton groups in case 1 waters from global SeaWiFS imageryDeep-Sea Res. I 52 1989CrossRefGoogle Scholar
2003 Airborne hyperspectral detection of microbial mat pigmentation in Rangiroa Atoll (French Polynesia)Limnol. Oceanogr 48 426CrossRefGoogle Scholar
2008 Assessment of uncertainty in the ocean reflectance determined by three satellite ocean color sensors (MERIS, SeaWiFS, and MODIS-A) at an offshore site in the Mediterranean Sea (BOUSSOLE project)J. Geophys. Res 113 C07013CrossRefGoogle Scholar
2005 New approaches and technologies for observing harmful algal bloomsOceanography 18 210CrossRefGoogle Scholar
2008 Real-Time Coastal Observing Systems for Ecosystem Dynamics and Harmful Algal Blooms: Theory, Instrumentation and ModellingParisUNESCO Publishing
1991 Biological and optical properties of mesoscale coccolithophoride blooms in the Gulf of MaineLimnol. Oceanogr 36 629CrossRefGoogle Scholar
2009 Diel vertical migration of Arctic zooplankton during the polar nightBiol. Lett 5 69CrossRefGoogle ScholarPubMed
2004 From meters to kilometers: A look at ocean-color scales of variability, spatial coherence, and the need for fine-scale remote sensing in coastal ocean opticsOceanography 15 33Google Scholar
1979 Pigmentation and morphology of a marine (Dinophyceae) with a major carotenoid different from peridinin and fucoxanthinJ. Phycol 15 457CrossRefGoogle Scholar
1988 sp. clone 677-3 –a tropical marine planktonic prymnesiophyte with fucoxanthin and 19′-acyloxyfucoxanthins as chemosystematic carotenoid markersBiochem. Syst. Ecol 16 445CrossRefGoogle Scholar
2003 Carotenoids of the Florida red tide dinoflagellate Biochem. Syst. Ecol 31 1147CrossRefGoogle Scholar
2008 Three years of ocean data from a bio-optical profiling floatEOS, Trans. AGU 89 209CrossRefGoogle Scholar
2004 Natural variability of phytoplankton absorption in oceanic waters: Influence of size structure of algal populationsJ. Geophys. Res 109 C11010CrossRefGoogle Scholar
2007 Coastal aquatic remote sensing applications for environmental monitoring and management. Special issues editorialJ. Appl. Remote Sens 1 1Google Scholar
2004 Mapping coastal optical and biogeochemical variability using an Autonomous Underwater Vehicle (AUV) and a new bio-optical inversion algorithmLimnol. Oceanogr. Methods 2 262CrossRefGoogle Scholar
1995 Optical Properties and Remote Sensing of Inland and Coastal WatersBoca RatonCRC PressGoogle Scholar
2001 Comparative studies on mycosporine-like amino acids, paralytic shellfish toxins and pigment profiles of the toxic dinoflagellates , and Mar. Ecol. Prog. Ser 223 49CrossRefGoogle Scholar
2008 Advanced laser fluorometry of natural aquatic environmentsLimnol. Oceanogr. Methods 6 591CrossRefGoogle Scholar
2006 Retrievals of a size parameter for phytoplankton and spectral light absorption by colored detrital matter from water-leaving radiances at SeaWiFS channels in a continental shelf region off BrazilLimnol. Oceanogr. Methods 4 237CrossRefGoogle Scholar
1997 Sources of variability in the column photosynthetic cross section for Antarctic coastal watersJ. Geophys. Res 102 25047CrossRefGoogle Scholar
2004 An intercomparison of HPLC phytoplankton pigment methods using in situ samples: application to remote sensing and database activitiesMar. Chem 85 41CrossRefGoogle Scholar
2006 Use of hyperspectral remote sensing reflectance for detection and assessment of the harmful algaKarenia brevis. Appl. Optics 45 5415Google ScholarPubMed
2008 Observation and prediction of harmful algal bloomsReal-Time Coastal Observing Systems for Ecosystem Dynamics and Harmful Algal Blooms: Theory, Instrumentation and ModellingParisUNESCO Publishing1Google Scholar
1995 Biological processes and optical measurements near the sea surface: Some issues relevant to remote sensingJ. Geophys. Res 100 13255CrossRefGoogle Scholar
2003 gen. nov. (Gymnodiniales, Dinophyceae), a new genus of unarmored dinoflagellates with sigmoid apical grooves, including the description of two new speciesJ. Phycol 39 1233CrossRefGoogle Scholar
2007 In situ and remote monitoring of water quality in Puget Sound: the ORCA time-seriesEnviron. Res. Eng. Manag 1 19Google Scholar
2008 Limnology and Oceanography special issue on Autonomous and Lagrangian Platforms and Sensors (ALPS)Limnol. Oceanogr 53 2057CrossRef
2000 Bio-optical properties and remote sensing ocean color algorithms for Antarctic Peninsula watersJ. Geophys. Res 105 26301CrossRefGoogle Scholar
1994 Concentrations of chlorophyll, suspended matter and gelbstoff in case II waters derived from satellite coastal zone color scanner data with inverse modelling methodsJ. Geophys. Res 99 7457CrossRefGoogle Scholar
1994 Iteration/regularization method of solution to nonlinear inverse problems and its application to interpreting water leaving radiance spectraProc. Russian Academy of Sciences: Ocean and Atmospheric Physics 30 106Google Scholar
2009 Formation of thin phytoplankton layers disruption of vertical motility by shear triggersScience 323 1067CrossRefGoogle ScholarPubMed
2007 gen. et sp. nov. (Dictyochophyceae, Heterokonta) – a bloom forming ichthyotoxic flagellate from the Skagerrak, NorwayJ. Phycol 43 1054CrossRefGoogle Scholar
2003 Phytoplankton and their role in primary, new, and export productionOcean Biogeochemistry: The Role of the Ocean Carbon Cycle in Global ChangeBerlinSpringer99CrossRefGoogle Scholar
2006 Real-time monitoring of harmful algal blooms in the southern BenguelaAfr. J. Mar. Sci 28 257CrossRefGoogle Scholar
2007 Inter-comparison of ocean colour data products during algal blooms in the SkagerrakInt. J. Rem. Sens 28 569CrossRefGoogle Scholar
2000 Atmospheric correction algorithm for hyperspectral remote sensing of ocean color from spaceAppl. Optics 39 887CrossRefGoogle ScholarPubMed
2006 Characterization of NW Mediterranean spp. (Dinophyceae) strains using morphological, molecular, chemical and physiological methodologiesJ. Phycol 42 1096CrossRefGoogle Scholar
1994 Variability in near-surface particulate absorption spectra: What can a satellite ocean color imager see?Limnol. Oceanogr 39 1349CrossRefGoogle Scholar
2003 Observing the oceans from the COOL room: our history, experience, and opinionsOceanography 16 37CrossRefGoogle Scholar
1997 Atmospheric correction of ocean color imagery in the Earth Observing System eraJ. Geophys. Res 102 17081CrossRefGoogle Scholar
2004 On the potential of MODIS and MERIS for imaging chlorophyll fluorescence from spaceInt. J. Rem. Sens 25 1459CrossRefGoogle Scholar
2008 Glider and autonomous underwater vehicle observing systemsReal-Time Coastal Observing Systems for Ecosystem Dynamics and Harmful Algal Blooms: Theory, Instrumentation and ModellingParisUNESCO Publishing495Google Scholar
2000 Comparative study of and , comb. nov. (= ) based on morphology, pigment composition, and molecular dataJ. Phycol 36 394CrossRefGoogle Scholar
2008 An absorption model to determine phytoplankton size classes from satellite ocean colourRemote Sens. Environ 112 3153CrossRefGoogle Scholar
2005 New algorithms for MODIS sun-induced chlorophyll fluorescence and a comparison with present data productsLimnol. Oceanogr. Methods 3 108CrossRefGoogle Scholar
2007 Retrieval of phytoplankton biomass from simultaneous inversion of reflectance, the diffuse attenuation coefficient, and sun-induced fluorescence in coastal watersJ. Geophys. Res 112 C06013CrossRefGoogle Scholar
2000 Remote sensing of ocean colour in coastal, and other optically complex watersDartmouthIOCCGGoogle Scholar
2006 Remote Sensing of Inherent Optical Properties: Fundamentals, Tests of Algorithms, and ApplicationsDartmouthIOCCGGoogle Scholar
1997 Introduction to marine phytoplankton and their pigment signaturesPhytoplankton Pigments in Oceanography: Guidelines to Modern MethodsParisUNESCO Publishing37Google Scholar
2006 Photosynthetic pigments in marine microalgae: Insights from cultures and the seaAlgal Cultures, Analogues of Blooms and ApplicationsEnfieldScience Publishers33Google Scholar
1997 Phytoplankton Pigments in Oceanography: Guidelines to Modern MethodsParisUNESCO Publishing
1993 Bio-optical characteristics and photoadaptive responses in the toxic and bloom-forming dinoflagellates , , and two strains of J. Phycol 29 627CrossRefGoogle Scholar
2007 Bio-optical characteristics of PSII and PSI in 33 species (13 pigment groups) of marine phytoplankton, and the relevance for pulse-amplitude-modulated and fast-repetition-rate fluorometryJ. Phycol 43 1236CrossRefGoogle Scholar
1994 absorption characteristics in 10 classes of phytoplankton: Taxonomic characteristics and responses to photoadaptation by means of discriminant and HPLC analysisMar. Ecol. Progr. Ser 105 149CrossRefGoogle Scholar
1997 Time series of harmful and benign phytoplankton blooms in northwest European waters using the Seawatch buoy systemMonitoring Algal Blooms: New Techniques for Detecting Large-Scale Environmental ChangeNew YorkSpringer115Google Scholar
1998 Bio-optical classification of potential harmful chlorophyll 3-containing prymnesiophyte blooms in Scandinavian watersHarmful MicroalgaeSantiago de CompostelaXunta de Galicia and Intergovernmental Oceanographic Commission of UNESCO300Google Scholar
2009 Remote sensing in the Barents SeaEcosystem Barents SeaTrondheimTapir Academic Press151Google Scholar
2009 Observing biogeochemical cycles at global scales with profiling floats and gliders: prospects for a global arrayOceanography 22 216CrossRefGoogle Scholar
1997 Monitoring Algal Blooms: New Techniques for Detecting Large-Scale Environmental ChangeNew YorkSpringer
1994 Light and Photosynthesis in Aquatic EcosystemsCambridgeCambridge University PressCrossRefGoogle Scholar
2000 Optical discrimination of a phytoplankton species in natural mixed populationsLimnol. Oceanogr 45 467CrossRefGoogle Scholar
2004 Literature review of Florida red tide: implications for human health effectsHarmful Algae 3 99CrossRefGoogle ScholarPubMed
2008 Phytoplankton community composition observed by autonomous underwater vehicleProceedings of the XIIth International Conference on Harmful AlgaeParisISSHA and IOC of UNESCO83Google Scholar
2007 Retrieving key benthic cover types and bathymetry from hyperspectral imageryJ. Appl. Remote Sens 1CrossRefGoogle Scholar
1994 Application of remote sensing in the visible for hydrodynamic studies in lakesWater Pollut. Res. J. Canada 29 385Google Scholar
1993 Chromatic regulation of quantum yields values for photosystem II charge separation, oxygen evolution and carbon fixation in (Pyrrophyta)J. Phycol 29 453CrossRefGoogle Scholar
2007 Development of finer spatial resolution optical properties from MODISProc. SPIE 6680 13Google Scholar
2004 Absorption spectrum of phytoplankton pigments derived from hyperspectral remote-sensing reflectanceRemote Sens. Environ 89 361CrossRefGoogle Scholar
1994 Model for the interpretation of hyperspectral remote-sensing reflectanceAppl. Optics 33 5721CrossRefGoogle ScholarPubMed
2002 Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep watersAppl. Optics 41 5755CrossRefGoogle ScholarPubMed
2007 Determination of primary spectral bands for remote sensing of aquatic environmentsSensors 7 3428CrossRefGoogle ScholarPubMed
2005 Ecosystem dynamics based on plankton functional types for global ocean biogeochemistry modelsGlobal Change Biol 11 2016Google Scholar
2010 Taxonomic discrimination of phytoplankton by spectral fluorescenceChlorophyll a Fluorescence in Aquatic Sciences: Methods and ApplicationsDordrechtSpringerGoogle Scholar
2004 Methods for reducing biofouling of moored optical sensorsJ. Atmos. Ocean. Tech 21 9582.0.CO;2>CrossRefGoogle Scholar
2009 A decade of satellite ocean color observationsAnnu. Rev. Mar. Sci 1 19CrossRefGoogle ScholarPubMed
1993 Microalgal pigment assessments of high-performance liquid chromatography: a synopsis of organismal and ecological applicationsCan. J. Fish. Aquat. Sci 50 2513CrossRefGoogle Scholar
1995 Relating photosynthetic pigments and optical density spectra to irradiance for the Florida red-tide dinoflagellate Mar. Ecol. Prog. Ser 120 65CrossRefGoogle Scholar
1997 Detection of harmful algal blooms using photopigments and absorption signatures: A case study of the Florida red tide dinoflagellate, Limnol. Oceanogr 42 1240CrossRefGoogle Scholar
1998 Photoadaptive response during the development of a coastal Antarctic diatom bloom and relationship to water column stabilityLimnol. Oceanogr 43 146CrossRefGoogle Scholar
2004 Variability in spectral backscatter estimated from satellites and its relation to in situ measurements in optically complex coastal watersInt. J. Remote Sens 25 1465CrossRefGoogle Scholar
2004 Episodic physical forcing and the structure of phytoplankton communities in the coastal waters of New JerseyJ. Geophys. Res 109CrossRefGoogle Scholar
2004 Alteration of the food web along the Antarctic Peninsula in response to a regional warming trendGlobal Change Biol 10 1973CrossRefGoogle Scholar
2005 Remote environmental monitoring units: an autonomous vehicle for characterizing coastal environmentsJ. Atmos. Ocean. Technol 22 1798CrossRefGoogle Scholar
2009 Bioluminescence to reveal structure and interaction of coastal planktonic communitiesDeep-Sea Res. II 56 232CrossRefGoogle Scholar
2008 Introduction to optical properties in the sea: theoretical aspectsReal-Time Coastal Observing Systems for Ecosystem Dynamics and Harmful Algal Blooms: Theory, Instrumentation and ModellingParisUNESCO Publishing109Google Scholar
2002 Normalized water-leaving radiance and remote sensing reflectance: bidirectional reflectance and other factorsOcean Optics Protocols for Satellite Ocean Color Sensor Validation 2 NASA/Technical Memorandum2002183Google Scholar
2008 Remote sensing of phytoplankton functional typesRemote Sens. Environ 112 3366CrossRefGoogle Scholar
2004 Deriving phytoplankton absorption for bio-optical productivity models in turbid watersJ. Geophys. Res 109CrossRefGoogle Scholar
2003 Quantification of the relative abundance of the toxic dinoflagellate, (Dinophyta), using unique photopigmentsJ. Phycol 39 449CrossRefGoogle Scholar
2008 Assessment of an underwater light attenuation model using bio-optical data collected in Monterey, CAEOS Trans. AGU 89Google Scholar
2008 Seaglider observations of blooms and subsurface chlorophyll maxima off the Washington coastLimnol. Oceanogr 53 2169CrossRefGoogle Scholar
1998 Annual cycles of phytoplankton community-structure and bloom dynamics in the Neuse River Estuary, North CarolinaMar. Biol 131 371CrossRefGoogle Scholar
1999 Responses of the phytoplankton community growth rate to nutrient pulses in variable estuarine environmentsJ. Phycol 35 1455CrossRefGoogle Scholar
2005 An advanced algorithm for operational retrieval of water quality parameters from satellite data in the visibleInt. J. Remote Sens 26 2669CrossRefGoogle Scholar
1976 Hydrologic Optics. Vol. I. IntroductionHonoluluUS Department of Commerce National Oceanic and Atmospheric Administration, Environment Research LaboratoryGoogle Scholar
1987 The photosynthetic physiology of dinoflagellatesThe Biology of Dinoflagellates. I. DinoflagellataOxfordBlackwell Scientific174Google Scholar
1986 Molecular bases of cell absorption and fluorescence in phytoplankton: potential applications to studies in optical oceanographyProgress in Phycological ResearchBristolBiopress Limited349Google Scholar
2008 Spatial variability of phytoplankton pigment distributions in the Subtropical South Pacific Ocean: comparison between and predicted dataBiogeosciences 5 353CrossRefGoogle Scholar
1987 Spatial and temporal patterns of marine blooms in the Northeastern Atlantic and North Sea from the Continuous Plankton Recorder SurveyRapp. Pv. Reun. Cons. Int. Explor. Mer 187 27Google Scholar
1997 Remote sensing of algal bloom dynamics: New research fuses remote sensing of aquatic ecosystems with algal assessory pigment analysisBioScience 46 492CrossRefGoogle Scholar
1999 Identification and classification of mixed phytoplankton assemblages using AVIRIS image-derived spectraSummaries of the Eighth JPL Airborne Earth Science WorkshopPasadenaCalifornia (JPL Publication 99–17)339Google Scholar
2004 Monitoring of the toxic dinoflagellate using gyroxanthin-based detection methodsJ. Appl. Phycol 16 315CrossRefGoogle Scholar
2010 Spectral fluorometric characterization of phytoplankton community composition using the Algae Online AnalyserWater Res 44 2461CrossRefGoogle ScholarPubMed
2006 Improved monitoring of HABs using autonomous underwater vehicles (AUV)Harmful Algae 5 749CrossRefGoogle Scholar
2003 Phytoplankton and pigment distributions in an anticyclonic slope water oceanic eddy (SWODDY) in the southern Bay of BiscayMar. Biol 143 995CrossRefGoogle Scholar
2006 Photoacclimation in phytoplankton: implications for biomass estimates, pigment functionality and chemotaxonomyMar. Biol 148 963CrossRefGoogle Scholar
2008 In situ measurement of inherent optical properties and potential for harmful algal detection and coastal ecosystem observationsReal-Time Coastal Observing Systems for Ecosystem Dynamics and Harmful Algal Blooms: Theory, Instrumentation and ModellingParisUNESCO Publishing153Google Scholar
2008 Overview of ocean colour: theoretical background, sensors and applicability to detection and monitoring of harmful algal blooms (capabilities and limitations)Real-Time Coastal Observing Systems for Ecosystem Dynamics and Harmful Algal Blooms: Theory, Instrumentation and ModellingParisUNESCO Publishing331Google Scholar
2004 Discrimination of diatoms from other phytoplankton using ocean-colour dataMar. Ecol. Prog. Ser 272 59CrossRefGoogle Scholar
1999 Neural network for emulation of an inverse model – operational derivation of Case II water properties from MERIS dataInt. J. Remote Sens 20 1735CrossRefGoogle Scholar
1991 Variability in spectral and nonspectral measurements of photosynthetic light utilization efficienciesMar. Ecol. Prog. Ser 78 253CrossRefGoogle Scholar
1999 Optical monitoring and forecasting systems for harmful algal blooms: Possibility or pipe dream?J. Phycol 35 1477CrossRefGoogle Scholar
2002 The long-term ecosystem observatory: an integrated coastal observatory. J. Oceanic Eng 27 146CrossRefGoogle Scholar
2004 Inversion of spectral absorption in the optically complex coastal waters of the Mid-Atlantic BightJ. Geophys. Res 109CrossRefGoogle Scholar
2008 Bio-optics in integrated ocean observing networks: potential for studying harmful algal bloomsReal-Time Coastal Observing Systems for Ecosystem Dynamics and Harmful Algal Blooms: Theory, Instrumentation and ModellingParisUNESCO Publishing85Google Scholar
2008 Prospects for developing automated systems for detection of harmful algae and their toxinsReal-Time Coastal Observing Systems for Ecosystem Dynamics and Harmful Algal Blooms: Theory, Instrumentation and ModellingParisUNESCO Publishing413Google Scholar
1998 An imaging-in-flow system for automated analysis of marine microplanktonMar. Ecol. Prog. Ser 168 285CrossRefGoogle Scholar
2004 Time series of coccolithophore activity in the Barents Sea, from twenty years of satellite imageryGeophys. Res. Lett 31 L11302CrossRefGoogle Scholar
2008 Characterizing seawater constituents from optical propertiesReal-Time Coastal Observing Systems for Ecosystem Dynamics and Harmful Algal Blooms: Theory, Instrumentation and ModellingParisUNESCO Publishing281Google Scholar
1995 Bio-optical variability associated with phytoplankton dynamics in the North Atlantic Ocean during spring and summer of 1991J. Geophys. Res 100 6621CrossRefGoogle Scholar
2005 Remote sensing of harmful algal bloomsRemote Sensing of Coastal Aquatic Environments: Technologies, Techniques and ApplicationsDordrechtSpringer277CrossRefGoogle Scholar
1999 Bio-optical properties of the marine diazotrophic cyanobacteria spp. II. A reflectance model for remote sensingLimnol. Oceanogr 44 618CrossRefGoogle Scholar
2009 Interpretation of fast repetition rate (FRR) fluorescence: signatures of phytoplankton community structure versus physiological stateMar. Ecol. Prog. Ser 376 1CrossRefGoogle Scholar
2010 Chlorophyll a Fluorescence in Aquatic Sciences: Methods and ApplicationsDordrechtSpringerCrossRef
1992 Characteristics of photosynthetic pigment composition of Miyake et Kominami ex OdaJ. Oceanogr 48 367CrossRefGoogle Scholar
2007 Proposal of gen. nov., comb. nov. (Dictyochophyceae) for a former raphidophycean alga , based on 18S rDNA phylogeny and ultrastructural characteristicsPhycol. Res 55 185CrossRefGoogle Scholar
2005 Inherent optical properties of the Irish Sea and their effect on satellite primary production algorithmsJ. Plankton Res 27 1127CrossRefGoogle Scholar
2008 Relating phytoplankton photophysiological properties to community structure on large scalesLimnol. Oceanogr 53 614Google Scholar
2008 HYDROPT: A fast and flexible method to retrieve chlorophyll-a from multispectral satellite observations of optically complex coastal watersRemote Sens. Environ 112 1795CrossRefGoogle Scholar
2007 Kelp forest mapping by use of airborne hyperspectral imagerJ. Appl. Remote Sens 1Google Scholar
2009 Microscopic hyperspectral imaging used as a bio-optical taxonomic tool for micro- and macroalgaeAppl. Optics 48 4170CrossRefGoogle ScholarPubMed
2005 Uncertainties of inherent optical properties obtained from semi-analytical inversions of ocean colorAppl. Optics 44 4074CrossRefGoogle Scholar
2006 Spatial and temporal distribution of blooms in the world's oceansGlobal Biogeochem. Cycles 20CrossRefGoogle Scholar
2005 An improved bio-optical model for the remote sensing of spp. bloomsJ. Geophys. Res 110 C06012CrossRefGoogle Scholar
1995 A theoretical derivation of the dependence of the remotely sensed reflectance on the inherent optical propertiesJ. Geophys Res 100 13135CrossRefGoogle Scholar
2005 Recent advances in pigment analysis as applied to picophytoplanktonVie et Milieu 55 233Google Scholar
2006 Comparison of SeaWiFS, MODIS and MERIS radiometric products at a coastal siteGeophys. Res. Lett 33 L06617CrossRefGoogle Scholar
- 8
- Cited by