An Easy-to-Construct Automated Winkler Titration System

The instrument described in this report is an updated version of the high precision, automated Winkler titration system described by Friederich et al.(1984). The original instrument was based on the work of Bryan et al. (1976) who developed a colorimetric endpoint detector and on the work of Williams and Jenkinson (1982) who produced an automated system that used this detector. The goals of our updated version of the device described by Friederich et al. (1984) were as follows: 1) Move control of the system to the MS-DOS environment because HP-85 computers are no longer in production and because more user-friendly programs could be written using the IBM XT or AT computers that control the new device. 2) Use more "off the shelf" components and reduce the parts count in the new system so that it could be easily constructed and maintained. This report describes how to construct and use the new automated Winkler titration device. It also includes information on the chemistry of the Winkler titration, and detailed instructions on how to prepare reagents, collect samples, standardize and perform the titrations (Appendix I: Codispoti, L.A. 1991 On the determination of dissolved oxygen in sea water, 15pp.). A disk containing the program needed to operate the new device is also included. (pdf contains 33 pages)

System requirement report for ‘Level 2’: national management institutions, Fisheries Department in Cambodia

(51 p.)

MBARI procedures for automated nutrient analyses using a modified Alpkem Series 300 Rapid Flow Analyzer

This report documents the methods used at the Monterey Bay Aquarium Research Institute (MBARI) for analyzing seawater nutrient samples with an Alpkem Series 300 Rapid Flow Analyzer (RFA) system. The methods have been optimized for the particular requirements of this laboratory. The RFA system has been used to analyze approximately 20,000 samples during the past two years. The methods have been optimized to run nutrient analyses in a routine manner with a detection limit of better than -±1% and a within run precision of -±1% of the full scale concentration range. The normal concentration ranges are 0-200 ~M silicate, 0-5 ~M phosphate, 0-50 ~M nitrate, 0-3 ~M nitrite, and 0-10 ~M ammonium. The memorandum is designed to be used in a loose-leaf binder format. Each page is dated and as revisions are made, they should be inserted into the binder. The revisions should be added into the binder. Retain the old versions in order to maintain a historical record of the procedures. (88 pages)

Automated, objective texture segmentation of multibeam echosounder data - Seafloor survey and substrate maps from James Island to Ozette Lake, Washington Outer Coast

Without knowledge of basic seafloor characteristics, the ability to address any number of critical marine and/or coastal management issues is diminished. For example, management and conservation of essential fish habitat (EFH), a requirement mandated by federally guided fishery management plans (FMPs), requires among other things a description of habitats for federally managed species. Although the list of attributes important to habitat are numerous, the ability to efficiently and effectively describe many, and especially at the scales required, does not exist with the tools currently available. However, several characteristics of seafloor morphology are readily obtainable at multiple scales and can serve as useful descriptors of habitat. Recent advancements in acoustic technology, such as multibeam echosounding (MBES), can provide remote indication of surficial sediment properties such as texture, hardness, or roughness, and further permit highly detailed renderings of seafloor morphology. With acoustic-based surveys providing a relatively efficient method for data acquisition, there exists a need for efficient and reproducible automated segmentation routines to process the data. Using MBES data collected by the Olympic Coast National Marine Sanctuary (OCNMS), and through a contracted seafloor survey, we expanded on the techniques of Cutter et al. (2003) to describe an objective repeatable process that uses parameterized local Fourier histogram (LFH) texture features to automate segmentation of surficial sediments from acoustic imagery using a maximum likelihood decision rule. Sonar signatures and classification performance were evaluated using video imagery obtained from a towed camera sled. Segmented raster images were converted to polygon features and attributed using a hierarchical deep-water marine benthic classification scheme (Greene et al. 1999) for use in a geographical information system (GIS). (PDF contains 41 pages.)