For Observing Harmful Algal Blooms

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For Observing Harmful Algal Blooms HARMFUL ALGAL BLOOMS BY MARCEL BABIN, JOHN J. CULLEN, COLLIN S. ROESLER, PERCY L. DONAGHAY, GREGORY J. DOUCETTE, MATI KAHRU, MARLON R. LEWIS, CHRISTOPHER A. SCHOLIN, New MICHAEL E. SIERACKI, AND HEIDI M. SOSIK Approaches and Technologies for Observing Harmful Algal Blooms Th is article has been published in Oceanography, Volume 18, Number 2, a quarterly journal of Th e Oceanography Society. Copyright 2005 by Th e Oceanography Society. All rights reserved. Reproduction of any portion of this article by photo- 210 Oceanography Vol.18, No.2, June 2005 copy machine, reposting, or other means without prior authorization of Th e Oceanography Society is strictly prohibited. Send all correspondence to: [email protected] or Th e Oceanography Society, PO Box 1931, Rockville, MD 20849-1931, USA. Harmful algal blooms (HABs) represent a diverse of phytoplankton. Also, in situ analysis of nutri- range of phenomena that universally share only two ent concentrations is now a reality, complementing Hcharacteristics: they produce effects on ecosystems established methods for measuring temperature, or food resources that humans perceive as harmful, salinity, and oxygen concentrations with submers- and their progression is fundamentally a process ible sensors. of population dynamics under oceanographic con- Many of the new approaches and technologies trol. Because of the complexity, scales, and transient are unfamiliar to potential users, therefore, they are nature of HABs, their monitoring and prediction not immediately useful to them. Hence, we orga- requires rapid, intensive, extensive, and sustained nized a “Workshop on Real-Time Coastal Observ- observations at sea. These requirements cannot ing Systems for Ecosystem Dynamics and Harmful be met with traditional approaches that depend Algal Blooms” in Villefranche-sur-Mer (France), on ships for sampling and laboratories for chemi- held 11-21 June 2003, to review the new technolo- cal or biological analyses. Fortunately, new sensing gies and platforms appropriate for autonomous technologies that operate autonomously in situ will and in situ observation of HABs. We provided the allow, in the near future, the development of com- participants with both the theory relevant to un- prehensive observation strategies for timely detec- derstanding the basic principles of real-time ob- tion of HABs. In turn, developments in modeling servation and modeling tools, and tutorials to ex- will support prediction of these phenomena, based plain the use of these tools. The proceedings of this directly on real-time measurements. workshop (“Habwatch”) appear in two forms. First, Enabling ocean-observation technologies that all invited lectures and contributed talks, and most have emerged during the last decade refl ect advanc- posters, are available on the workshop web site es in optical imaging, molecular biology, chemistry, (www.obs-vlfr.fr/habwatch); oral talks are available acoustics, phytoplankton physiology, and marine as slide shows with voice. Second, chapters based on optics. Now, sensors are increasingly deployed from invited lectures will be published in a peer-reviewed various platforms such as in situ profi lers, autono- volume of the UNESCO series Monographs on mous underwater vehicles (AUVs), and moorings Oceanographic Methodology (Babin et al., in press). to derive a broad range of quantitative and qualita- Here, we present an overview of the major ob- tive information about the pelagic environment. servational technologies described during the For example, optical sensing, used for decades to Habwatch workshop, referring the reader to de- measure photosynthetically available radiation and tailed reviews on specifi c topics, which form the to estimate concentrations of suspended particles chapters of the Habwatch proceedings. We con- from turbidity or phytoplankton from chlorophyll clude by suggesting some priorities for the devel- fl uorescence, has been greatly enhanced to provide opment of observational tools within the frame- much better measures of the light fi eld and sea- work of the Global Ecology and Oceanography of water constituents, plus indicators of the species Harmful Algal Blooms (GEOHAB) program (see composition, cell size, and physiological properties www.geohab.info/). Oceanography Vol.18, No.2, June 2005 211 AVAILABLE AND EMERGING 1998). This instrument measures light among HAB species. Thus, unique ge- OBSERVATIONAL TECHNOLOGIES scattering, and fl uorescence from chlo- netic signatures (DNA, RNA) targeted by Many technologies show promise for rophyll and phycoerythrin, on individual molecular probes have been increasingly real-time observation of HABs and the particles larger than 5 µm. Its CCD cam- used for detection of microorganisms at oceanographic processes that in large era is triggered by, for instance, the chlo- the species level, including the discrimi- part determine their dynamics. Some rophyll a fl uorescence signal; digital sil- nation of potentially toxic from non- enhance existing capabilities while others houette images are stored on disk. Data toxic species of a genus (e.g., Pseudo- can provide information in situ that until analysis allows enumeration of targeted nitzschia spp.). However, simply the pres- recently could be obtained only through morphotypes with semi-automatic shape ence of a toxigenic species provides no hands-on analysis of samples. recognition. This particle analyzer is es- information on the associated toxicity, as pecially good in the microplankton size toxin levels can vary widely as a function Detection of Phytoplankton at the range (20 to 200+µm) where morpholo- of environmental effects on the organ- Group or Species Level gy is an important identifi cation feature. ism’s physiology. Ideally, the potential im- The harmful effects of HABs are general- Benchtop, portable, and submersible pacts of a toxic HAB should be assessed ly attributable to single species. It is thus versions are available. Jaffe (in press) re- necessary to discriminate phytoplankton views other optical imagers that could be Marcel Babin ([email protected]) is at the group or species level for the de- used in HAB research and monitoring. Research Scientist, Laboratoire d’Océan- tection, early warning, and oceanograph- Sensitive to cells smaller than Flow- ographie de Villefranche, CNRS/UPMC, ic characterization of HABs. This is tra- CAM’s limit, fl ow cytometers can be Villefranche-sur-Mer Cedex, France. John J. ditionally done by microscopic examina- used to discriminate phytoplankton Cullen is Professor, Department of Ocean- tion or analysis for toxins, both of which groups based on pigment fl uorescence ography, Dalhousie University, Halifax, are laborious and generally performed in and light scattering as an index of size. Nova Scotia, Canada. Collin S. Roesler is the laboratory; these approaches are not Automated submersible fl ow cytometers Research Scientist, Bigelow Laboratory for suitable for real-time observation. There have been developed and deployed suc- Ocean Sciences, West Boothbay Harbor, are, however, new and emerging tech- cessfully to obtain signifi cant results on ME, USA. Percy L. Donaghay is Research nologies derived from those traditional phytoplankton population dynamics Scientist, Graduate School of Oceanogra- methods that allow autonomous and/or (Figure 2). With sample preparation, phy, University of Rhode Island, Narra- gansett, RI, USA. Gregory J. Doucette is Research Scientist, NOAA/National Ocean Service, Charleston, SC, USA. Mati Kahru Many technologies show promise for is Research Scientist, Scripps Institution of real-time observation of HABs and the Oceanography, UCSD, La Jolla, CA, USA. oceanographic processes that in large Marlon R. Lewis is Professor, Department of Oceanography, Dalhousie University, part determine their dynamics. Halifax, Nova Scotia, Canada. Christopher A. Scholin is Associate Scientist, Monterey Bay Aquarium Research Institute, Moss near real-time detection of phytoplank- fl ow cytometers can identify cells labeled Landing, CA, USA. Michael E. Sieracki is ton at the species and group levels. One with specifi c markers (e.g., for proteins, Research Scientist, Bigelow Laboratory for such commercial technology is Flow- bulk DNA, or gene probes). Ocean Sciences, West Boothbay Harbor, ME, CAM, a particle analyzer and imager In many cases, phenotypic attributes USA. Heidi M. Sosik is Associate Scientist, that combines aspects of microscopy and of cells (e.g., morphology, pigment com- Biology Department, Woods Hole Oceano- fl ow cytometry (Figure 1) (Sieracki et al., position) are insuffi cient to discriminate graphic Institution, Woods Hole, MA, USA. 212 Oceanography Vol.18, No.2, June 2005 A B C Figure 1. Schematic diagrams and results from the FlowCAM imaging-in-fl ow system (Fluid Imaging Technologies, USA; www.fl uidimaging.com). Sample fl uid is pulled through the fl ow cell at rates up to 4 mL/min. (A) When a cell enters the fi eld of view, fl uorescence is excited by a fan of laser light. Epifl uorescence optics are used that em- ploy dichroic mirrors (DM) to split the light signals. Diff erent objectives (OBJ) can be used for diff erent magnifi cations (e.g., 4X to 20X). Th e fl uorescence signal is detected by photomultiplier tubes (PMT) and triggers a light emitting diode (LED) to fl ash and backlight the fl ow cell. Th e camera image is digitized by the frame grabber. Th e cell is located within the image and measured, and a subimage is stored on disk in real time. Particles can also be detected by light scatter (detector not shown for simplicity). (B) Details of the fi eld of view of the fl ow cell. (C) Th ese images are linked to the size and fl uorescence values and results can be browsed using the interactive scattergram. Th e dot plot shows fl uorescence versus size and populations can be investigated by se- lecting points and the corresponding images are displayed. Oceanography Vol.18, No.2, June 2005 213 x 105 106 6 Synechococcus C A B -1 Picoeukaryotes CryptophytesCryptophytes 4 Synechococcus 4 2 10 Cells ml 0 x 105 Nano- 3 D 2 Nano- Nanoeukaryotes 10 -1 eukaryotes 2 Cryptophytes (x 50) Red Flourescence eukaryotes 1 Picoeukaryotes Cells ml 100 0 100 102 104 106 01 Aug 15 Aug 01 Sep 15 Sep Side Scattering Figure 2.
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