In the IOCCG Report Series: 1. Minimum Requirements for an Operational Ocean-Colour Sensor for the Open Ocean (1998) 2. Status and Plans for Satellite Ocean-Colour Missions: Considerations for Com- plementary Missions (1999) 3. Remote Sensing of Ocean Colour in Coastal, and Other Optically-Complex, Waters (2000) 4. Guide to the Creation and Use of Ocean-Colour, Level-3, Binned Data Products (2004) 5. Remote Sensing of Inherent Optical Properties: Fundamentals, Tests of Algo- rithms, and Applications (2006) 6. Ocean-Colour Data Merging (2007) 7. Why Ocean Colour? The Societal Benefits of Ocean-Colour Technology (2008) 8. Remote Sensing in Fisheries and Aquaculture (2009) 9. Partition of the Ocean into Ecological Provinces: Role of Ocean-Colour Radiome- try (2009) 10. Atmospheric Correction for Remotely-Sensed Ocean-Colour Products (2010) 11. Bio-Optical Sensors on Argo Floats (2011) 12. Ocean-Colour Observations from a Geostationary Orbit (2012) 13. Mission Requirements for Future Ocean-Colour Sensors (2012) 14. In-flight Calibration of Satellite Ocean-Colour Sensors (2013) 15. Phytoplankton Functional Types from Space (this volume) Disclaimer: The opinions expressed here are those of the authors; in no way do they represent the policy of agencies that support or participate in the IOCCG. The printing of this report was sponsored and carried out by the National Oceanic and Atmospheric Administration (NOAA), USA, which is gratefully acknowledged. Reports and Monographs of the International Ocean-Colour Coordinating Group An Affiliated Program of the Scientific Committee on Oceanic Research (SCOR) An Associated Member of the (CEOS) IOCCG Report Number 15, 2014 Phytoplankton Functional Types from Space Edited by: Shubha Sathyendranath (Plymouth Marine Laboratory) Report of an IOCCG working group on Phytoplankton Functional Types, chaired by Shubha Sathyendranath and based on contributions from (in alphabetical order): Jim Aiken, Séverine Alvain, Ray Barlow, Heather Bouman, Astrid Bracher, Robert J. W. Brewin, Annick Bricaud, Christopher W. Brown, Aurea M. Ciotti, Lesley Clementson, Susanne E. Craig, Emmanuel Devred, Nick Hardman-Mountford, Takafumi Hirata, Chuanmin Hu, Tihomir S. Kostadinov, Samantha Lavender, Hubert Loisel, Tim S. Moore, Jesus Morales, Cyril Moulin, Colleen B. Mouw, Anitha Nair, Dionysios Raitsos, Collin Roesler, Shubha Sathyendranath, Jamie D. Shutler, Heidi M. Sosik, Inia Soto, Venetia Stuart, Ajit Subramaniam and Julia Uitz. Series Editor: Venetia Stuart Correct citation for this publication: IOCCG (2014). Phytoplankton Functional Types from Space. Sathyendranath, S. (ed.), Reports of the International Ocean-Colour Coordinating Group, No. 15, IOCCG, Dartmouth, Canada. The International Ocean-Colour Coordinating Group (IOCCG) is an international group of experts in the field of satellite ocean colour, acting as a liaison and communication channel between users, managers and agencies in the ocean-colour arena. The IOCCG is sponsored by Centre National d’Etudes Spatiales (CNES, France), Canadian Space Agency (CSA), Commonwealth Scientific and Industrial Research Or- ganisation (CSIRO, Australia), Department of Fisheries and Oceans (Bedford Institute of Oceanography, Canada), European Space Agency (ESA), European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), Helmholtz Center Geesthacht (Germany), National Institute for Space Research (INPE, Brazil), Indian Space Research Organisation (ISRO), Japan Aerospace Exploration Agency (JAXA), Joint Research Centre (JRC, EC), Korea Institute of Ocean Science and Technology (KIOST), National Aeronautics and Space Administration (NASA, USA), National Centre for Earth Observation (NCEO, UK), National Oceanic and Atmospheric Ad- ministration (NOAA, USA), Scientific Committee on Oceanic Research (SCOR), and Second Institute of Oceanography (SIO), China. http: //www.ioccg.org Published by the International Ocean-Colour Coordinating Group, P.O. Box 1006, Dartmouth, Nova Scotia, B2Y 4A2, Canada. ISSN: 1098-6030 ©IOCCG 2014 Printed by the National Oceanic and Atmospheric Administration (NOAA), USA Contents 1 General Introduction 1 1.1 Background . 1 1.2 What Do We Mean by a Functional Type? . 2 1.3 Distribution of Some Common Phytoplankton Groups . 7 1.4 Why Study Phytoplankton Functional Types? . 9 1.5 Why Study Phytoplankton Functional Types From Space? . 15 1.6 The Need for Complementary Approaches . 17 1.7 Concluding Remarks . 18 2 In situ Methods of Measuring Phytoplankton Functional Types 21 2.1 Introduction . 21 2.2 Microscopy . 21 2.3 Flow Cytometry . 23 2.4 HPLC Methods . 26 2.5 Molecular Methods . 30 2.6 Spectral Inherent Optical Properties of Phytoplankton . 32 2.7 Fluorescence Excitation and Emission Spectra of Phytoplankton . 34 2.8 Phytoplankton Size Structure through Successive Filtration . 36 2.9 Concluding Remarks . 36 3 Detection of Dominant Algal Blooms by Remote Sensing 39 3.1 Introduction . 39 3.2 Detection of Diatom Blooms . 40 3.2.1 Background . 40 3.2.2 Distribution . 40 3.2.3 Optical traits . 41 3.2.4 Remote-sensing algorithms for identification and mapping of diatoms . 41 3.3 Detection of Coccolithophore Blooms . 45 3.3.1 Background . 45 3.3.2 Detection using Earth observation . 47 3.4 Detection of Karenia brevis and K. mikimotoi Blooms . 51 3.4.1 Background . 51 3.4.2 K. brevis bloom detection . 52 3.4.3 K. mikimotoi bloom detection . 56 3.4.4 Summary . 57 i ii • Phytoplankton Functional Types from Space 3.5 Detection of Trichodesmium Blooms . 58 3.5.1 Background . 58 3.5.2 Bloom detection . 58 3.5.3 Other cyanobacterial blooms . 62 3.6 Detection of Ulva prolifera Blooms . 63 3.6.1 Background . 63 3.6.2 Bloom detection . 64 3.7 Detection of Sargassum spp. Blooms . 66 3.7.1 Background . 66 3.7.2 Bloom detection . 67 3.8 Summary and Discussion . 68 4 Detection of Phytoplankton Size Structure by Remote Sensing 71 4.1 Introduction . 71 4.2 Abundance-Based Approaches . 72 4.2.1 Size-classes based on discrete trophic classes . 72 4.2.2 Phytoplankton size classes based on a continuum of abundance measures . 74 4.2.3 Comparison of abundance-based methods . 78 4.3 Spectral-Based Approaches . 81 4.3.1 Absorption spectral-based approaches . 82 4.3.2 Backscattering approaches . 89 4.4 Discussion . 94 4.4.1 Spectral-based approaches: absorption or backscattering? . 94 4.4.2 Advantages and disadvantages of abundance-based and spectral- based approaches . 95 4.4.3 Novel and future methods . 98 4.5 Summary . 99 5 Remote Sensing Algorithms for Multiple Phytoplankton Types 101 5.1 Introduction . 101 5.2 Statistical Methods Based on Spectral Anomaly . 102 5.2.1 Establishing a global in situ dataset for satellite match-ups . 102 5.2.2 Removing the effect of chlorophyll concentration . 103 5.2.3 Reflectance anomalies and phytoplankton types . 104 5.2.4 Implementation of the method . 105 5.2.5 A theoretical explanation for PHYSAT . 107 5.3 Differential Absorption-Based Method . 108 5.4 Abundance-Based Methods . 113 5.5 Ecological Algorithms . 114 5.6 Methods Based on Non-Linear Inversion of Ocean-Colour Models . 118 5.7 Discussion and Conclusion . 121 CONTENTS • iii 6 General Discussion and Conclusion 125 6.1 Size and Community Structure . 126 6.2 Single-Variable and Multi-Variable Approaches . 126 6.3 Uncertainties in Products and Limits of Detection . 128 6.4 Need for an In Situ Database . 130 6.5 Harmful Algal Blooms . 130 6.6 Case-2 Waters . 131 6.7 Directions for Future Work . 131 6.8 Serving the User Community . 133 6.9 In Conclusion . 133 References 135 Acronyms and Abbreviations 155 iv • Phytoplankton Functional Types from Space Chapter 1 General Introduction Shubha Sathyendranath, Heidi M. Sosik, Jim Aiken, Séverine Alvain, Ray Barlow, Lesley Clementson, Cyril Moulin, Nick Hardman-Mountford, Takafumi Hirata, Jesus Morales, Anitha Nair, Colleen Mouw and Venetia Stuart 1.1 Background Satellite-based remote sensing of ocean colour provides unique observational capa- bility to biological oceanographers and other Earth observation scientists interested in processes that involve phytoplankton. No other observational strategy can pro- vide synoptic views of upper ocean optical properties with such high spatial and temporal resolution (∼1 km or better, daily or better) as well as high spatial and temporal extent (global scales, for years to decades). Since the proof-of-concept Coastal Zone Color Scanner (CZCS) mission, the principal focus of ocean-colour research has been on retrieval of information about the content of chlorophyll-a, the major phytoplankton pigment in the upper ocean (e.g., Gordon et al., 1983). Whereas this focus continues to the present (Morel and Antoine 2000; O’Reilly et al., 1998; 2000) with chlorophyll concentration being by far the most utilised product from ocean-colour satellites, an evolving interest in retrieving other properties, including information on the composition of the phytoplankton community, has emerged in recent years. Note that the community may be described on the basis of their size structure, their taxonomic composition, or their functions. This interest has paralleled the incorporation of the concept of phytoplankton functional types (PFTs) into studies of a range of ecological and biogeochemical problems, especially into modelling studies (Le Quéré et al., 2005; Hood et al., 2006). In this concept, each PFT represents a group of species aggregated according to distinct functional characteristics. Such approaches are receiving increasing attention because of the realization that capturing the role of phytoplankton