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Water-Sample Processing In addition to direct enumeration and morphological examination of organisms in Gulper water samples with light microscopy, a variety of molecular methods are used to identify the taxonomy and relative abundance of phyto- plankton, zooplankton and bacterioplankton. AUV samples are also commonly analyzed for nutrients (e.g., phosphate, silicate, nitrate), chlorophyll or other chemistries in shore- based laboratories for comparison with data collected by AUV and additional data. Organisms from multiple trophic levels present in indi- vidual water samples can be size fractionated and collected by serial filtration with decreasing porosity. Filters are then frozen or chemically preserved for subsequent molecular analysis. For example, comparatively large zooplankton (larger than 100 micrometers) can be separated from toxin- producing algal-bloom forming species of phytoplankton (0.65 to 100 micrometers) or marine bacteria (0.22 to 5 mi- crometers) present in a single sample. Subsequent molecular analysis of filter-collected organ- isms involves chemical lysis, followed by various methods at the researcher's discretion. Molecular probe-based tech- niques, such as the sandwich hybridization assay, assess the presence and relative abundance of target RNA from organ- isms of interest, while reverse transcriptase amplification of RNA transcripts, followed by quantitative polymerase chain reaction of bacterial functional genes, provides information regarding the regulation of ocean biochemical cycling. Several methods are frequently used together. A sand- wich hybridization assay can be used to assess harmful al- gal bloom species abundance and diversity, while replicate filters and liquid filtrate can quantify harmful algal bloom toxicity by high-performance liquid chromatography analy- sis of toxin concentrations. Zooplankton collected in these samples can also be analyzed to quantify the transfer of toxin to the next higher trophic level, which has detrimental consequences for humans and larger marine life. Conclusions Among myriad technologies available in the rapidly grow- ing field of ocean-observing networks, water sampling AUVs equipped with adaptive decision-making software based on intelligent processing of environmental signals offer novel opportunities to investigate plankton ecology. Recent signal- processing and software-engineering developments for AUVs have taken these already versatile platforms to a new level of autonomous, adaptive sampling of marine ecological nich- es, such as thin phytoplankton layers and upwelling fronts. These phenomena are often highly spatially and temporally variable, precluding precise sampling by traditional means and driving requirements for present and future engineering efforts. Thanks to AUV innovations, monumental advances in the study of plankton ecology are underway. Acknowledgments The David and Lucile Packard Foundation and MBARI provided funding and facilities for this research. The authors extend sincere thanks to their collaborators at MBARI and elsewhere. References For a list of references, contact Julio Harvey at jharvey@ mbari.org. n After receiving his Ph.D. at the University of California, Santa Cruz, in 2004, Dr. Julio Harvey worked with the University of Washington to develop molecular methods to detect ma- rine invasive species. Since 2008, his work at the Monterey Bay Aquarium Research Institute has integrated molecular genetic detection with robot-mediated adaptive sampling. Dr. Yanwu Zhang, a senior research specialist at the Mon- terey Bay Aquarium Research Institute, received a Ph.D. in oceanographic engineering from the Massachusetts Insti- tute of Technology-Woods Hole Oceanographic Institution joint program in 2000. He designs and field-tests adaptive sampling algorithms for AUVs and assists in developing the Tethys AUV. Dr. John Ryan received a Ph.D. in biological oceanography from the University of Rhode Island in 1998. He is a senior research specialist at the Monterey Bay Aquarium Research Institute, focusing on studies of coastal ocean processes us- ing observational and modeling approaches. 54 st / SEPTEMBER 2012 www.sea-technology.com