CMOP 2nd Annual Report May 1, 2008

II. RESEARCH

II.1. Introduction

II.1.a Overall Research Goals and Objectives NSF instructions: Describe the Center's overall research goals and/or objectives. If the Center’s overall research goals/objectives changed from the previous year, how did they change and why? [In section 2a below, please describe progress the Center has made toward reaching these goals/objectives.]

The CMOP research goals and supporting research objectives remain the same identified in the Strategic and Implementation Plan. There are four major goals: R1 Coastal Margin Observatories goal: Generate, disseminate and archive detailed quantitative

descriptions of river-to-ocean environments through coastal margin observatories (and, in particular, the pilot observatory SATURN), defined as configurable integrations of modeling systems, heterogeneous observation networks, and information delivery systems.

R2 Coastal Margin Science goal: Understand condition, variability and change in the context of grand challenges at the interface of coastal margins with large-scale processes (climate and plate tectonics) and human activities.

R3 Enabling Technologies goal: Develop and demonstrate enabling technologies (modeling, sensors and platforms, and information and visualization) in support of advanced functionality of river-to-ocean observatories.

R4 Education Enabling goal: Enable research-based education.

and 12 supporting research objectives: A SATURN modeling system: Organize heterogeneous physical and ecosystem models,

and external forcings to produce continuous forecasts, long-term databases, and process-oriented simulations across the PNW coastal margin.

Supports goal R1

B SATURN long-term time-series: Make integrated, real-time, vertically-resolved measurements of physical, chemical, and biological variables at 4 fixed SATURN stations located in the Columbia River, estuary, plume, and shelf.

Supports goal R1

C SATURN mobile-platform network: Expand the spatial and temporal extent of the fixed network, by creating infrastructure and protocols toward the vision of a river-to-ocean mobile-platform testbed - and moving towards long-term, continuous, adaptive, monitoring of estuary, plume and shelf gradients of physical, chemical and biological variables off the mouth of the Columbia River.

Supports goal R1

D SATURN information system: Develop a multi-dimensional flow of information among sensors, models, processing tools, and people that will handle: adaptive deployment of sensors and platforms; on-demand product generation; heterogeneity of networks, sensors, and data types; fault tolerance; event detection and triggering; and technology evolution.

Supports goal R1

E Ecosystem dynamics, climate, and water use: Advance the cross-scale quantitative understanding of multi-scale variability of events and high-gradient regions, ecosystem dynamics, biological productivity, and air-sea carbon fluxes in the PNW coastal margin, as a function of climate and water use.

Supports goal R2

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F Microbial communities in productive coastal margins: Advance the mechanistic, molecular-level understanding of microbial organisms and communities in coastal margins, including the structure, activity, and response to varying physical/chemical environmental stressors.

Supports goal R2

G Modeling and simulation: Advance modeling and simulation technologies for circulation, productivity, and carbon fluxes across river-to-ocean scales, and including: improved computational efficiency and operational robustness; improved data assimilation and objective skill assessment; model-based techniques for optimization of observational design; and increased range of biological parameters that can be modeled at ecosystem scales.

Supports goal R3

H OSSE: Develop observing system simulation experiments (OSSE) in the Columbia River estuary, plume and adjacent coastal waters, to guide optimization of SATURN fixed stations, to design tracks of ensembles of vessels, unmanned underwater vehicles and profilers, and, ultimately, with other SATURN assets, to enable deployable, real-time adaptive monitoring strategies.

Supports goal R3

I Smart platforms: In partnership with industry, address commonly encountered challenges (e.g., mobility, power generation, and communications) of smart platforms for sensor deployment.

Supports goal R3

J In situ sensors: In partnership with industry, develop sensors that are inexpensive, power-efficient, and small enough to mount on large numbers of moorings/mobile platforms - with early emphasis on broadening the range of parameters (in particular biological and chemical) and the spatial range of in situ sensors.

Supports goal R3

K Information and visualization: Develop the technologies and strategies for management, quality assurance, visualization, provenance control and delivery of heterogeneous – and, in some cases, massive – data, data producers and information products associated with coastal margin observatories.

Supports goal R3

L Broad impacts of research: Involve non-academic groups and a diverse set of K-G students and teachers in research activities and in the use of research products

Supports Goal E1

II.1.b Implementation metrics NSF instructions: Inform us of the performance and management indicators/metrics (click for definition) the Center has developed to assess progress in meeting its research goals/objectives, if changed from the previous reporting period.

We show below the CMOP research implementation metrics, which remain largely unchanged. A SATURN modeling system: Skill assessment and operational robustness of the SATURN

modeling system, as reported electronically (via CMOP web site) on a routine basis for forecasts and climate-scale simulation databases, and as reported in appropriate peer-reviewed publications for process-based simulations.

B SATURN long-term time-series: Quantity and quality of observational data collected at the SATURN fixed stations.

C SATURN mobile-platform network: Quantity and quality of data collected by mobile platforms, and adequacy of that data to address the driving scientific hypothesis

D SATURN information system: Customer satisfaction, evaluated through annual surveys across all Center participants and selected external constituencies.

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E Ecosystem dynamics, climate, and water use: Advancements in scientific understanding, as measured by peer reviewed papers, thesis, and conference presentations

F Microbial communities in productive coastal margins: Advancements in scientific understanding, as measured by peer reviewed papers, thesis, and conference presentations

G Modeling and simulation: Advancements in algorithmic developments, as measured by improvements in operational performance of SATURN and/or in the quality of process-oriented simulations

H OSSE: Evaluation of adequacy of recommended sampling strategies, as measured by success in obtaining the data necessary to test science-driven hypothesis

I Smart platforms: Operational performance of the platforms and supporting technologies, and – where applicable –scientific value of SATURN observations conducted in these platforms. Where applicable, number of patents.

J In situ sensors: Number of new variables and processes that can be observed, and quality of the observations. Where applicable, number of patents.

K Information and visualization: Degree to which new technologies are adopted by the SATURN information system, and, for the adopted technologies, customer satisfaction based on user surveys (see D)

L Broad impacts of research: List of participating non-academic groups, students, teachers and trainees

II.1.c Problems encountered NSF instructions: Discuss any problems you have encountered in making progress toward the Center’s research goals/objectives during the reporting period as well as any problems anticipated in the next period. Include your plans for addressing these problems.

We have encountered no unsolvable problems, but we have faced various challenges that require reflection and intervention. In particular:

• CMOP has a very large number of investigators, from many institutions and disciplines, many of whom did not know each other’s institutional and disciplinary cultures. Many research teams have gelled remarkably well across disciplinary and institutional boundaries in a fairly short time period. However, this is not universally true yet. Also, needed changes in the CMOP leadership at one of the partner institutions, with associated delays in funding, created trust issues that will take time to heal at the research collaboration level.

Addressing the challenge: Several activities and milestones (trust-building within the Senior Management Team, validation of CMOP’s direction though the first meeting of the External Advisory Board, a successful all-hands meeting in 2008, a highly participated cross-campus Seminar Series and the creation of the Research Incubation Team, RIG) are all contributing positively to a broader engagement in the intellectual and cultural environment of CMOP.

• As pointed out by the External Advisory Board, the number of participants in CMOP is large, leading to sub-critical funding of many investigators. Modest funding has been used very effectively by some investigators, who seeded exploratory research or leveraged the funding with an existing and synergistic broader context. However, in other cases, modest funding has truly meant sub-critical participation and contributions.

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Addressing the challenge: We have invited each partner institution to consider adjusting participant number/composition, funding distributions, and/or philosophy of participation of modestly funded investigators.

• Research cruises are placing a large burden on investigators across the center, and arguably detracting from using the “long-time time series” philosophy and assets of the center to full benefit.

Addressing the issue: We are re-thinking our cruise goals and strategies. It is conceivable that, as we shift from exploratory to hypothesis-driven cruises, we would be able reduce the need for annual ship days.

• The CMOP computing/IT staff is stretched thin. They must maintain the databases, web interfaces and tools for current data collections and services, monitor the day-to-day operation of those services, provide the data infrastructure for cruises and aid with the ingest and release of cruise data, while trying to support special needs of individual research projects and expand the SATURN infrastructure to meet the needs of new activities and data sources. That load leaves limited time for re-architecting and re-implementing CMOP infrastructure in ways that will be more flexible and maintainable in the future.

Addressing the challenge: We hired in 2008 a full-time web coordinator/multi-media specialist . We also hired an additional programmer (shared with the Northwest Association of Network Ocean Observing Systems). Finally, we are considering hiring a quarter-time project manager to coordinate the activities of the existing computing/IT team.

• The CMOP management staff was originally under-designed, with implications on research productivity through issues such as policy setting, center-wide communications, project management/tracking and procurement.

Addressing the challenge: We hired in April 2008 a Managing Director, with a complementary set of skills relative to the original management team. Currently with part-time dedication, she will become full-time in Fall 2008.

II.2. Research Thrusts

II.2.a Progress and Accomplishments NSF instructions: Briefly describe the research thrust areas at the Center. Please provide basic information for each thrust area and details of significant accomplishments during the reporting period, including any research partnerships and their contributions to the Center (do not include publications, presentations, etc., that are reported in Section VIII, Center-wide Outputs and Issues). Include in the narrative a discussion of the goals, activities, and outcomes and/or impacts in the current reporting period, if changed from the previous reporting period. Be sure to discuss how the activities in the various research thrust areas enable the Center to meet its goals/objectives described above

We organize our research under three umbrella themes (coastal-margin science, coastal-margin observatories and enabling technologies–Fig. II-1,) with cross-theme interaction strongly encouraged. All themes are organized to contribute to a better characterization (and distinction between) variability and change in coastal margins. We think of cyclic variations as variability, and of shifting trends as change.

Substantial activity has occurred in and across all themes during the reporting period. Progress and accomplishments reported here necessarily reflect only a sub-set of such activity.

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II.2.a.1 Progress and accomplishments in Coastal Margin Observatories

We are developing an advanced observatory for the PNW coastal margin, as essential infrastructure for CMOP research, education, and knowledge transfer, including broad engagement of the scientific and regional communities. The observatory is an ambitious, configurable integration of heterogeneous modeling systems, observation networks and cyber-infrastructure, which will offer transformative opportunities to understand processes, variability and change.

Currently anchoring the CMOP infrastructure is CORIE, an early pioneer among coastal margin observatories, with which we have over a decade of semi-operational1 experience. An end-to-end observatory–with a modeling system, an observation network, and unifying cyber-infrastructure–CORIE offers an excellent platform for evolution towards a next-generation high-end collaborative observatory, SATURN2. While built upon CORIE as a foundation, SATURN is developing distinctive capabilities in critical areas. We anticipate that over the next five years CORIE will become one of several sub-systems of SATURN, which will progressively assume the umbrella identity.

There are four major projects under Theme II, each with multiple sub-projects (see Table II-1). Several of these efforts (marked with a P) leverage synergistic funding, often integral to our Knowledge Transfer initiatives.

II.2.a.1.1 Modeling System (goal R1, objective A)

Team: Joseph Zhang (CMOP investigator, OHSU), Paul Turner (CMOP staff, OHSU), Charles Seaton (CMOP staff and part-time PhD student, OHSU), Grant Law (CMOP post-doctoral fellow, OHSU), Antonio Baptista (CMOP director, OHSU), plus, as noted, Yvette Spitz (CMOP investigator, OSU), David Rivas (CMOP post-doctoral fellow, OSU) and Roger Samelson (CMOP investigator, OSU).

Description: We envision the SATURN modeling system as an integrated ensemble of inter-disciplinary models, external forcings, observational data (for quality control and/or assimilation), and skill metrics, able to produce (a) near real-time forecasts; (b) multi-year (“climate scale”) simulation databases; and (c) scenario/process-oriented simulations.

The CORIE modeling system (http://www.stccmop.org/corie), which preceded CMOP, offers a powerful–if embryonic–implementation of that vision. CORIE offers extensive modeling capabilities for 3D baroclinic circulation, in particular for the estuary and plume (with quality degrading along the continental shelf, away from the Columbia River). CORIE will anchor the SATURN modeling system, as it evolves into a more interdisciplinary set of capabilities and a broader regional coverage.

During the reporting period, we (in part through funding from regional knowledge transfer projects): 1 The word “semi-operational” implies a system that is operated and maintained on a continued basis, with at least some anchor products generated (but not necessarily maintained) on a regular 24-7 schedule. By contrast, a system would be “operational” if both generation and maintenance are ensured 24-7. 2 Consistent with then-OOI terminology, we named our testbed after a planet. The acronym SATURN (Science And Technology University Research Network) was chosen because the extensive satellite system of Saturn evokes the distributed nature envisioned for coastal margin observatories.

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• Extended in time and characterized in skill the ensemble of CORIE circulation simulation databases. There are currently three useful multi-year (to 1999-2006/07) simulation databases (DB11 and DB14 for the river-to-ocean system; and DB16 for just the estuary), each with different skill; differences in skill result from different choices of code (ELCIRC versus SELFE), domain/grid, parameterization and external forcing. Comparisons with a fourth and a fifth database (DB17 and DB18, estuary only, one year only) were conducted in Y3, to explore recent algorithmic improvements in SELFE. The contrasting skills (e.g., Fig. II-2) of the various simulation databases were mined to understand and mitigate error sources–in ways rendered unique by the length and detail of the simulation databases. A new multi-year simulation database, incorporating lessons learned, is in preparation.

• Continued adding data assimilation as a semi-operational capability of the CORIE modeling system. The fast, model-independent data assimilation techniques described later have now been successfully applied to improve representation of hard-to-model physical processes (e.g., salinity intrusion length) and one of the daily forecasts of circulation (estuary-only) uses data assimilation to improve initial (nowcast) conditions.

• Maintained multiple day-ahead daily circulation forecasts for the Columbia River estuary or estuary/plume system, with various degrees of skill. We also maintain a seven days-ahead forecast, a timeframe that more effectively supports oceanographic cruises.

• Began the development of a year-long (2004) scenario simulation of the Columbia River circulation, after bathymetric changes associated with a large Cascadia Subduction Zone (CSZ) earthquake. The reference earthquake is a magnitude 9, created for tsunami inundation studies. This earthquake leads to a substantial subsidence at the mouth of the Columbia River, and is based on best-available geological and seismic evidence. Contrast against contemporary conditions shows dramatic change in salinity intrusion–the Columbia River will, in fact, be a different ecosystem.

• Created, maintain and are progressively improving the quality of circulation forecasts (and, eventually, simulation databases) for a range of Pacific Northwest estuaries. The contrast of these and other PNW estuaries with the Columbia River, will allow a robust analysis of impacts of large-scale processes such as tectonic deformations and climate. Current forecasts are for: Fraser River; Grays Harbor; Willapa Bay; Tillamook, Nahalem and Netarts Bays; Yaquina and Alsea Bays; Humboldt Bay; Siletz and Depoe Bay; and Coos Bay.

• Began preparing PNW basin-scale forcing to drive analysis of impact of climate change on the Columbia River (Roger Samelson, David Rivas).

• Began developing under Enabling Technologies the ecological modeling tools that we anticipate incorporating in SATURN in later years (Yvette Spitz).

Knowledge Transfer: All the Columbia River simulation databases, scenarios and forecasts are integral to active collaborations with NOAA’s Northwest Fisheries Science Center (with NOAA and Bonneville Power Administration support) regarding salmon survival and recovery, and to emerging collaborations with CRITFC (planning stage) regarding estuary and near-shore ecosystem changes under large scale external forcing and human activities. Daily forecasts of other PNW estuaries represent shared development with the Northwest Association of Networked Ocean Observing Systems (NANOOS.) CSZ deformations were obtained from a joint project with the Oregon Department of Geology and Mineral Industries, Canadian Geological Survey and Oregon State University.

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II.2.a.1.2 Progress and accomplishments in Coastal Margin Observatories: Long-term Time Series (goal R1, objective B)

We envision the generation of sustainable long-term time series of physical, chemical and/or biological variables through a heterogeneous network of stations with fixed latitude and longitude, concentrated in the estuary but extending to the plume. The network is built on top of multiple (~18) historical CORIE stations, which number and spatial configuration we seek to modify using new Enabling Technologies for network optimization. Note that there are several changes of the concept of the SATURN observation network, relative to the original design, and consistent with an increased focus of our research on river-to-ocean gradients.

SATURN-01 and SATURN-03 (Fig. II-3), recently deployed, are the first of several anticipated multi-disciplinary stations. They will form with SATURN-02 (to be deployed in the plume) and SATURN-04 (to be deployed in Cathlamet Bay, in primarily freshwater conditions), the backbone of measurements of river-to-ocean biogeochemical gradients. SATURN-04 will use LOBO technology, and will join a national network of LOBO stations.

SATURN-01 is also our first station with vertical mobility. It will anchor a field laboratory in the North Channel of the estuary designed to help characterize estuarine processes with unprecedented spatial detail; of particular interest are processes such as vertical mixing, estuarine turbidity maxima, estuarine fronts, and topography-generated internal waves. Besides SATURN-01 and two existing CORIE stations, the laboratory will include radar-based measurements of surface currents (SATURN-20, roughly co-located with SATURN-01) and four bottom-mounted stations with underwater acoustic telemetry (SATURN-05/08, specific locations to be determined through network optimization studies). Each of the bottom-mounted stations will include (besides more conventional instrumentation) sigma profilers developed as an Enabling Technology to characterize aspects of vertical density structure.

Plume/shelf coverage will be accomplished initially through SATURN-02 and one historical CORIE station (OGI01), aided by historical CODAR coverage of surfaces velocities in the near plume. Envisioned multi-disciplinary and with vertical mobility, we anticipate deploying SATURN-02 in the historical location of the far less able OGI02 (physical variables only, at fixed levels). Additional coverage of the plume and near-shelf will be considered to support the CMOP modeling and scientific goals. Part of that coverage will be come from mobile platforms (see next section), but we will also use newly developed Enabling Technologies for network optimization to explore high-priority locations for potential additional stations. To support studies of network optimization in the plume, we plan to resort to short-term deployments of a simple buoy with surface conductivity and temperature sensors (SATURN-09) in combination with a glider set in vertical motion at nearly fixed latitude and longitude.

An ORCOOS shelf station in Newport (NH-10) was partially supported by CMOP in Y2, with funding transitioning to NANOOS in Y3. CMOP will continue to provide vessel support for deployment and recovery. NH-10 provides historical continuity in a region of the shelf substantially less affected by freshwater than the SATURN domain.

Further details of selected sub-elements of SATURN and ancillary observation systems are described below.

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II.2.a.1.2.1 SATURN-01

Team: Michael Wilkin (CMOP staff, OHSU) and CORIE filed team, Joe Needoba (CMOP investigator, OHSU)

Description: SATURN-01 was deployed in March 2008, as the first of several anticipated multi-disciplinary stations of the SATURN observatory and the first station with vertical mobility.

SATURN-01 is located at Astoria Meglar Bridge pier 11 (Fig. II-3). This station can actively profile the water column with a suite of instruments. The winch speed is ~10cm/s, and the sampling rate: ~5Hz. Early testing was with a simple CTD (Fig. II-4), but current instrumentation also includes an ISUS and a FLNTU. Profiling provides more meaningful data than a single point at the seabed, and is cheaper than multiple instruments spread through the water column. However maintaining a mechanical system of this nature introduces its own problems, which we are addressing as they occur. As a side benefit the return of the instruments to the surface provides an easy route to cleaning and amelioration of biofouling.

Plan for the next funding period: (a) Maintain and improve station based on accumulated experience. (b) Add additional sensors as they become available, from core CMOP funding or externally. (c) Assess data quality, including bridge influence. (d) Evaluate feasibility/value to replicate the design in other stations, in particular SATURN-03. (e) Evaluate whether the more costly original designed is required.

II.2.a.1.2.2 SATURN-02

Team: Michael Wilkin (CMOP staff, OHSU) and CORIE filed team, Joe Needoba (CMOP investigator, OHSU)

Description: SATURN-02 will be located at the current location of CORIE’s OGI02 (Fig. II-3), in the near field plume. Deployment of SATURN-02 is anticipated in stages, starting 2009. Ultimately the station will have both multi-disciplinary sensors and profiling capability.

Plan for the next funding period: (a) Design profiling system. (b) Begin phased deployment.

II.2.a.1.2.3 SATURN-03

Team: Michael Wilkin (CMOP staff, OHSU) and CORIE filed team, Joe Needoba (CMOP investigator, OHSU)

Description: SATURN-03 is located at Pt Adams Packing Pier (Fig. II-3). This station too has a CTD, a FLNTU and an ISUS as a part of its instrumentation package. The Covered pier and availability of utility power is allowing us to begin experimenting pumping seawater from the sampling point to an instrument on top of the pier. This along with land access should allow us to keep the conductivity sensor in calibration and free from biofouling without resorting to diving and retrieving the instrument package periodically.

Plan for the next funding period: (a) Maintain and improve station based on accumulated experience. (b) Add additional sensors as they become available, from core CMOP funding or externally. (c) Assess data quality, including bridge influence. (d) Evaluate feasibility/value to replicate the design in other stations, in particular SATURN-03. (e) Evaluate whether the more costly original designed is required.

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II.2.a.1.2.4 SATURN-04

Team: Andrew Barnard (CMOP investigator, WETLabs) and Joe Needoba (CMOP investigator, OHSU) This new project (to start outside the reporting period) aims to develop new capabilities for the current state-of-the-art coastal biogeochemical LOBO moorings that are commercially available from Satlantic. Specifically, WETlabs will (in collaboration with Needoba) develop and install a geo-fouling resistant LOBO mooring in the Columbia River estuary, in primarily freshwater (near the CORIE station Mott Basin). We anticipate that the first data stream will be available mid-Summer 2008.

II.2.a.1.2.5 SATURN-09

Team: Michael Wilkin (CMOP staff, OHSU) and CORIE filed team, Sergey Frolov (CMOP post-doctoral felow, OHSU)

Description: To support studies of network optimization in the plume, we plan to resort to short-term deployments of a simple buoy with surface conductivity and temperature sensors (SATURN-09).

Plan for the next funding period: Temporarily deploy in Summer 2008. Deployment will be off Grays Harbor, at a location determined by studies of network optimization. We will be testing the hypothesis that the selected location substantially adds to data assimilated plume circulation simulations, in both upwelling and downwelling regimes.

II.2.a.1.2.6 Newport station

Team: Murray Levine (CMOP co-director, OSU)

Description: The year 2 effort began with the recovery of the surface mooring deployed at water depth of 80m at station NH-10 (Newport hydrographic line, 10 nmiles off Newport, Oregon) in April 2007 during the first CMOP cruise on the R/V Wecoma (W0704A). This buoy system was funded by NOAA / OrCOOS (Oregon Coastal Ocean Observing System) using instrumentation borrowed from other projects. The CMOP funding was used to refurbish the buoy and instrumentation and to redeploy the mooring 10 days later during a cruise funded by a different NSF project.

The mooring consisted of a surface buoy, jacketed wire rope, chain and anchor. The surface buoy supported a suite of meteorological sensors, a system controller, battery pack, Argos satellite location beacon, flashing light and radar reflector. Oceanographic sensors were distributed in the buoy bridle and along the wire rope. Temperature and conductivity were measured at 14 and 5 depths, respectively. Fluorometers and backscatter sensors were deployed near the top and bottom of the mooring. A dissolved oxygen sensor was placed about 10 meters above the bottom. An acoustic Doppler velocity profiler measured current at 2 meter intervals over most of the water column. All the instruments recorded data internally every 2 minutes. A subset of these data were transferred daily using a cell phone modem, including meteorological observations, current profiles, temperature / conductivity at two depths, and dissolved oxygen near the bottom.

After 3 months the wire rope was apparently cut by trawling activity. The mooring was recovered from the 50’ R/V Elakha, although there was some instrument damage and loss. After

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refurbishing the mooring was redeployed in August 2007. In November 2007 the mooring was recovered and redeployed with refurbished instruments and a new improved surface buoy. Unfortunately about one month after deployment a strong storm with surface waves exceeding 40 feet broke the mooring chain. Fortunately we were able to recover most of the mooring components. Data reports and documentation are being written and most of the data has gone through a quality control procedure.

This mooring, located in the continental shelf in the far field of the Columbia River, allows us to explore time scales spanning processes from internal waves to tides and from storm events to seasonal changes. The NH line is one of the most sampled regions off the Oregon coast with observations dating back to the 1960’s. Maintaining observations along this line is important to help our understanding of long-term oceanic changes and allow new observations to be put into context. After December 2007, CMOP funding to support this mooring was discontinued with the anticipation that NOAA will continue to fund the mooring as part of NANOOS.

Plan for the next funding period: The mooring at NH-10 will be maintained by NANOOS to the extent that funding permits. Ship time from CMOP will be used to accomplish the deployments and recoveries. In addition to the data acquired, the mooring platform will be available for investigators to attach their sensors for testing or data collection.

II.2.a.1.2.7 Underwater acoustic network (expected to become SATURN 05-08)

Team: Bruce Howe (CMOP investigator, UW)

The goal of this work is to sample the Columbia River estuary and plume by means of a network of fixed bottom instrumentation acoustically linked to one another and a surface gateway. The instrumentation includes CTD, ADCP, conductivity sounder, chemical, bio-optical, and other sensors supplied by other STC participants; the ADCP and conductivity sounder “probe” the water column from the bottom. The use of the acoustic network enables the necessary spatial distribution of sensors, real-time data return, and two-way communication for adaptive sampling and fault diagnosis. While this particular portion of CMOP is addressing the fixed nodes, other portions are addressing AUVs, the provision of energy, and sensors. At this stage, the emphasis is on developing the sensor network technology, which then can be expanded upon and used in Phase 2.

In year 1 planning began to define the acoustically linked bottom nodes. These will have instruments connected to them, and they will acoustically communicate data to a surface gateway buoy. They will serve as navigation/acoustic communications nodes for the autonomous undersea vehicle (AUV). A major step was the hiring of Matt Grund, a software engineer, to assist on the acoustic portions of this work. Grund comes from the WHOI acoustic modem group at WHOI. We will use the WHOI micromodems for this purpose. See Fig. II-5, the original concept figure from the proposal.

In year 2 the design of the bottom nodes continued and testing of acoustic communications began. This work is being done in concert with similar complementary work being done as part of four other grants here at APL-UW: 1) an ONR grant involving acoustic Seagliders with modems talking to each other and other platforms, including bottom nodes and gateway buoys; 2) an NSF grant for a cabled, profiler mooring (ALOHA-MARS Mooring (AMM) system, http://alohamooring.apl.washington.edu) intended for the Ocean Observatories Initiative; 3) a NASA grant which will ultimately have gliders flying around the mooring system (all with

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modems), with data being assimilated into a model with real-time adaptive control; and 4) the NSF HOT Profiler project, a high power battery powered autonomous mooring with real-time RF and acoustic data communications. Fig. II-6 shows a combination of a schematic and actual hardware of the NASA concept. These three projects and CMOP are working together to achieve common and complementary goals.

During the past year there has been much work in testing acoustic communications between gliders and between gliders other platforms, both fixed and mobile, at the surface, in the water column, and on the bottom. In one such test in Port Susan, Puget Sound, a glider (Fig. II-7 shows a fleet)sat on the bottom and communicated with a glider moving out in range (Fig. II-8). Frequency shift-key (FSK) signal coding at 80 bits per second was used, with reliable results to 4 km and less reliable results to 7 km. In another test, an acoustic modem was installed on a bottom node at 30 m water depth as part of the AMM testing at the Seahurst Observatory in Puget Sound (just west of Sea-Tac airport). Using a boat deployed transducer and deck box, ranges to 2.5 km were obtained (Figs. II-9 and II-10); the lower ranges than in Port Susan were likely a result of the much shallower bottom. In more recent testing in March 2008, phase-shift-key (PSK) signal coding (coherent vice the incoherent FSK) was used. In this case 240 b/s and 5200 b/s were obtained between a glider and a surface gateway buoy with a modem suspended beneath; this modem has a 4-element hydrophone-receiving array. Further, an abort command was sent to the glider to demonstrate real-time vehicle control via the acoustic communications channel. In all cases, one-way travel times were obtained from which range is obtained. In summary, these test results have given us confidence that this type of modem system will perform well for the CMOP application.

Fig. II-11 shows a schematic block diagram for the CMOP work. A surface gateway buoy (provided by OHSU) will host an acoustic modem system. The latter will have a 4-element receive array and the modem will be synchronized to GPS time. The radio communications link provided on the buoy will enable real time communications to subsea autonomous assets. The latter can include both mobile and fixed platforms. In the former class are gliders of various flavors and powered vehicles, such as the APL CMOP REMUS recently purchased (it will have modem). While not in the current CMOP plans, there is no reason gliders with modems could not also fit into the system, though taking consideration of the local flows and bathymetry.

As shown in Fig. II-11, the seafloor nodes (ultimately) will be able to host multiple, in principle arbitrary, sensors (a sample of the possible sensors are shown in the figure). There will a controlling computer (likely a Verdex made by Gumstix, being used on the HOT Profiler Mooring) that will serve as the intermediary between the sensors and the modem, controlling both and exchanging data and commands. There are still several unanswered questions that further discussions with CMOP investigators will address, namely specifications on the range and characteristics of possible sensors, and whether power is to be centrally controlled and distributed, or whether each sensor has its own supply. In the coming months, use case scenarios will be determined. Related to these questions is how we expect possible energy harvesting systems (under development by Tom Sanford as part of CMOP) to interface to these nodes.

Towards the end of year 2, two bottom nodes will be constructed along with a simple gateway buoy (suitable for use and testing purposes in Puget Sound). These initial nodes will make use of equipment bought on the ONR grant, for testing, to be sure they are suitable for the CMOP application. The bottom nodes will have CTDs (borrowed from our pool to begin with), interfaced simply with the current modem Gumstix computer. These units will be tested with

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point-to-point protocols in Port Susan. When testing is complete, two modem units and CTD units will be purchased for CMOP.

Plans moving forward: In year 3 the two (crude) bottom nodes will be modified to include the controlling computer, power distribution, recovery system, and frame. After testing these, then parts for the second two acoustic nodes and an ADCP will be purchased and assembled for test in Puget Sound. It is expected that two nodes with a gateway buoy will be deployed in the North Channel of Columbia River estuary in spring 2009 for testing. In year 4, we will interface other sensors (provided by other participants), as well as interface Energy Harvesters to a node in Puget Sound. Four nodes (1 powered) with gateway buoy will be deployed in the Columbia River estuary in spring 2010. Finally in year 5, operational experience will be acquired and repair/refurbish/upgrading of the systems will continue.

II.2.a.1.3 Progress and accomplishments in Coastal Margin Observatories: Mobile-Platform network (goal R1, objective C)

Mobile platforms are essential components of the vision for SATURN. Two advanced types of platforms are planned: gliders and unmanned underwater vehicles. The 50ft M/V Forerunner, operated by the Clatsop Community College (CCC) will be used as a third mobile platform, both ad hoc during CCC classes, and during targeted scientific cruises.

II.2.a.1.3.1.1 Unmanned underwater vehicles (UUV)

Team: Russ Light (CMOP investigator, UW)

Status: After convening the CMOP UUV Workshop in Feb 2007 (see Y1 report), a final Request for Quote (RFQ) that included a set of specific requirements was issued to three selected UUV vendors (Hydroid, Hafmynd-Gavia, BlueFin) in May 2007. Quotes were received and evaluated over the next several months. A final recommendation report was prepared and sent to the CMOP director in July 2007 which called for the acquisition of (2) Hydroid REMUS 100 systems with primary scientific sensors Seabird SBE-49 CTD and up/down looking ADCP. This system was selected after many discussions, meetings, vendor information review, CMOP UUV workshop, budgetary constraints, operational constraints, reliability, etc. OHSU placed the order with Hydroid in Jan 2008. Expected delivery is May-June 2008. Plans for next funding period:

• Delivery of the REMUS systems is expected in May-June 2008.

• An UUV lab will be setup at APL and outfitted with tools, fixtures, and computer systems

• Hydroid will send a training person to Seattle for a one week REMUS training course in June-July 2008 after delivery of the REMUS systems. APL staff that will participate in the training are two field engineers, Trina Litchendorf and Troy Swanson (both Seaglider experts) and Russ Light, Craig McNeil. Training will tale place at APL in Seattle with on the water operations using APL’s vessel R/V Miller on Puget Sound or Lake Washington. After training is complete, local water tests will be conducted for gaining more familiarization with system operations. On-going will be further discussions of potential deployment sites and missions fur CMOP. Similar missions will be practiced in local water testing using the same vehicle behavior and systems.

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• After completion of local water testing the budget will be analyzed for feasible deployments during the remaining FY. At a minimum it is expected that at least one, (1) week experiment will be conducted in late summer/fall 2008 in the Columbia River estuary.

II.2.a.1.3.1.2 Glider

Team: CORIE field team, with assistance from the group of Jack Barth (CMOP investigator, OSU)

Status: A Sloccum glider was acquired, and training of the CORIE field team at Webb Research is scheduled for June 2008. The first glider deployment is anticipated for June 2008.

Plan for next funding period: (a) Establish routine of operation. (b) Use in conjunction with SATURN-09 to test optimization network strategies–e.g., by emulating a horizontally fixed profiling station. (c) Create policies and tools to support customized requests for glider routes from the CMOP community, defined broadly to include the educational mission. (d) Determine when to acquire a second glider (a competing alternative would be to acquire a second LOBO station, for flexible deployment in the broader SATURN domain.)

II.2.a.1.3.1.3 Coastal radar network

Team: Mike Kosro (CMOP investigator, OSU)

Description: During Y2, we: • operated 11 HF surface current mapping sites throughout the PNW, including two focused on

the Columbia River near and far fields. collected data in near real-time to central hubs, then combined to produce daily maps of surface flow in 3 regions: (i) over the shelf near Newport, Oregon (ii) over the shelf and slope to 150 km offshore between Crescent City, CA and southern Washington, at lower resolution than (i), and (iii) at the mouth of the Columbia River. We collected data during winter 2007-2008 for the first time in region (iii).

• repaired HF infrastructure at Loomis Lake, Fort Stevens and Manhattan Beach, which were damaged during the severe storm of Dec 3-4, 2007.

• maintained web delivery of ASCII preliminary data associated with each new map • web products available through http://bragg.coas.oregonstate.edu • daily maps of ocean currents delivered for use by CMOP cruises • implemented real-time correction in test mode for high-horizontal-shear regions, such as the

Columbia River outflow, to avoid under-estimation bias identified by our group. This identification and solution have proven useful to groups operating in the Gulf Stream as well.

• acquired manufacturer-designed upgrades for two of the older HF surface current mappers, enabling them to use modern USB communication, and therefore use the latest and most stable data acquisition software and Macintosh operating system, extending their useful life.

• upgraded two additional older HF surface current mappers as above, with a grant from the OSU Research Equipment Reserve Fund.

• Installed new wireless communications at HF sites WLD and YHS to improve control and data retrieval.

Analysis of the data:

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• We examined the anomalous conditions surrounding the onset of upwelling during spring 2005. Found that, while physical upwelling was late by O(50 days) compared with climatology, upwelled waters were prevented from surfacing for an additional 50 days due to isolation of surface waters by the Columbia River outflow. This resulted in a very late appearance of biological bloom, which had serious consequences across trophic levels.

• We identified a confined region of strong apparent M2 tidal currents (hot spot) over northern half of Columbia River mouth.

II.2.a.1.3.1.4 M/V Forerunner and SWAP2

Team: Michael Wilkin (CMOP staff, OHSU) and CORIE field team; faculty/vessel operators from Clatsop Community College

Description: Clatsop Community Colleges training vessel Forerunner has for some years been outfitted by OHSU with a suite of oceanographic instrumentation that automatically operates when the vessel is away from the dock without human intervention. The data is returned to OHSU using SWAP2, a telemetry system compatible with the UNOLS vessels. The instrumentation suite on Forerunner was upgraded to include a DO sensor.

Forerunner will be used as a third vessel during selected CMOP cruises involving UNOLS vessels, and will continue to be used throughout the year for routine data collection (e.g., in coordination with research on microbial communities) and as platform of occasion while fulfilling its primary role as a seamanship training vessel for the Community College.

Note that, through a joint effort by OSU marine technical staff and OHSU computer staff, SWAP2 is now deployed around both the Columbia River and Yaquina estuaries. This vastly improved wireless network has allowed far greater internet availability to UNOLS and other vessels visiting Newport and Astoria, provides telemetry for the new SATURN stations in the Columbia River and telemetry links for CODAR coastal radar in Newport.

II.2.a.1.4 Progress and Accomplishments in Coastal Margin Observatories: Information System (goal R1, objective D)

Team: Paul Turner (CMOP staff, OHSU), Charles Seaton (CMOP staff, OHSU), Bill Howe (post-doctoral fellow, OHSU), Antonio Baptista (CMOP director, OHSU), David maier (PSU)

Description: We seek to lift scientific cyber-infrastructure to an active participant in the scientific process, acting autonomously to provide the data, products, and context users need, right when needed. To encapsulate this vision, we use the term RoboCMOP. We see RoboCMOP as providing a shared “exploration space” for teams of researchers to use during collaborative activities, accommodating and eventually promoting remote interaction.

While RoboCMOP is being developed as an Enabling Technology, we have managed data from sensors, models and platforms through a combination of slightly modified historical CORIE capabilities (http://www.stccmop.org/corie) and new capabilities. Among new capabilities are: • Cruise mapper (http://www.stccmop.org/corie/cruise_support): a Open GIS web tool

designed to support cruise planning and analysis. • DataMart (http://www.stccmop.org/datamart): a data management system that offers flexible

data access (in contrast with the CORIE canned, pre-generated images), extensive coverage (online access to the entire CMOP observation archive, not just current observations) and

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specificity (access just what you need, just when you need it, without the need for bulk downloads.) DataMart relies heavily on the Product Factory, an Enabling Technology.

• Ocean appliance: a pre-configured open-source “server-in-a-box” for ingest, processing, and fusion of observation streams and model results. Data and products can be configured and accessed locally through the on-board web server and database server, and are optionally shipped to other ocean appliances for simplified multi-site integration. Currently, we use this model for providing data and computing capabilities on cruises.

II.2.a.2 Progress and Accomplishments in Coastal Margin Science

Much of our science effort has been placed in exploratory analysis of microbial communities in the Columbia River river-estuary-plume-shelf system. Cruises conducted with guidance from circulation models and contextual physical/ecological observations have led to a wealth of samples, that are being processed with multiple RNA and DNa-based techniques. Results are providing exciting insights into community composition and activity across the river-to-ocean continuum, including recognizable patterns of bacterioplankton biogeography and bacterial productivity.

We are also conducting a steady effort of characterization of physical variability in the Columbia River estuary and plume, and ramping up research on physical-biological scales of variability–both activities poised to provide increasingly formal context for the microbial studies. Exploratory work is being conducted in contamination pathways, an area of likely growth for the activities of the center.

Progress has started in the definition of circulation-based sentinels of variability and change. As a simple example, salinity intrusion length has been used both to describe modern variability in the Columbia River estuary and to anticipate dramatic changes in the Columbia River ecosystem in the event of a Cascadia Subduction Zone eathrquake. We see circulation-based sentinels as a precursor to the more inter-disciplinary and robust environmental sentinels required to fulfill our vision of anticipatory oceanography. Defining these sentinels relative to large-scale processes such as climate change would benefit from examining gradients across West coast estuaries, an opportunity that we plan to explore by integrating data from SATURN and other modern observation assets (such as LOBO stations).

II.2.a.2.1 Microbial Communities in Productive Coastal Margins (goal R2, objective F)

The characterization of microbial communities in the Columbia River and coastal waters has a focal area of CMOP research during Y2, in particular driving the design and implementation of various single- and multi-vessel cruises. Four microbial labs are involved in the research. Although the report from each lab is presented in separate, below, the labs are operating collaboratively, as illustrated by the overlap of team members in each report.

II.2.a.2.1.1 Exploring Microbial Populations and their Activities in the Columbia River System: 1. Zuber Lab

Team: Holly Simon, CMOP Investigator; Byron Crump CMOP Investigator; Michiko M. Nakano, CMOP Investigator; Ricardo Letelier, CMOP Investigator; Fred Prahl, CMOP Investigator; Joseph Needoba, CMOP Investigator; Tawnya Peterson, CMOP Invesigator; Lydie Herfort, Post-Doctoral Fellow; Mariya Smit, Senior Research Associate; Dan Murphy, Graduate

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Student; Suzanne DeLorenzo, Graduate Student; Caroline Fortunato, Graduate Student (UMCES); Johanna Green, Research associate (UMCES); Peter Kahn, Undergraduate (Willamette University), Mikaela Selby, Technician Assistant, and Peter Zuber.

Activities Collection of environmental samples and conducting chemical analysis to determine

nutritional composition of each sampling site. Processing samples to optimize protocols for microbial transcriptomic analysis

(rRNA/mRNA for cDNA library construction) Determination of microbial population structure by DGGE (Denaturant Gradient Gel

Electrophoresis) and SSCP (Single-Strand Conformation Polymorphism) analysis of DNA encoding bacterial and archaeal rRNA.

Sequence analysis of 16S and 18S cDNA libraries to identify taxa inhabiting the selected sampling sites that reside across the salinity gradients of the Columbia River, its estuary, and plume in the coastal ocean.

Sample collection: Research Cruises, Aug. and Nov. 2007. Three major research cruises were conducted on the UNOLS vessels Wecoma (August and November) and Barnes (August only). The Wecoma was used for sampling at established sampling lines of the Oregon and Washington coastlines across gradients in the pelagic environment. The Wecoma also was used to obtain samples in the Columbia River plume and estuary (Fig. II-12A and II-12B). The Barnes was used for sampling the Columbia River up to the confluence of the Willamette River (and within the Willamette River), and for obtaining samples from the estuary. Important gradient features that were targeted included the areas of hypoxia in the coastal zones, the Columbia plume, the salinity gradient over a set of sampling sites extending from the Columbia River (zero salinity) to a point on the Columbia river line extending beyond the Plume (>30 psu salinity). Additionally a samples series was collected from neap and spring tides in the estuary, and from the estuary turbidity maximum, which has been shown to be an area of high microbial productivity. Finally, a red tide bloom (Myrionecta rubra) in the estuary was sampled extensively during the August cruise on the Barnes. Shorter cruises on the Forerunner were conducted in June and in July as part of an exercise for CMOP undergraduate interns employed for the summer months in 2007. Another important feature of the estuary that was sampled extensively is the estuary turbidity maximum that is an area of high bacterial productivity.

Samples from the April 2007 cruise (Fig. II-12C) of year 1 were also analyzed during year 2 of the CMOP project. Data presented here are only from the CR (Columbia River Line). The data analysis of samples collected from the Wecoma cruise will be reported by Byron Crump. The focus of this report will be the Columbia River Line, consisting of sampling sites from the Columbia River, the estuary, the plume and beyond the plume.

In addition to the research cruises of year 2, samples have been collected in on a monthly basis from Nov. 2006 until Aug. 2007 using the Clatsop Community College’s M/V Forerunner. Samples for the following analyses have been collected: DNA microbial community profiles, 18S rRNA and 16S rRNA sequence analyses, microbial mRNA by sequence analysis of cDNA libraries of environmental RNA, microbial cell counts (by CARD-FISH), concentrations of chlorophyll a, nutrients (ammonium, nitrate & nitrite, phosphorous), particulate organic carbon and nitrogen, suspended particulate matter (Table II-2). At each sites, physical parameters (e.g. temperature, salinity, depth, optical back scattering) are also obtained.

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Chemical and Biological Analysis of Samples Collected from the Columbia River Line: The April and August data uncovers regions of high primary productivity in the plume surface, evident from high chlorophyll and oxygen concentrations, with a layer of high ammonium concentration in the salinity gradient below the chlorophyll/oxygen maximum. Ammonium is a preferred nitrogen source for many prokaryotic species and could be fueling the high bacterial production detected near the plume surface. In contrast, the elevated phaeophytin and silicate concentrations of the estuary and river suggest an area of high algal growth and turnover, which could potentially sustain heterotrophic activity within the estuary. The 18S sequence analysis presented below supports these conclusions. The spring/neap tidal cycles appear to profoundly influence the levels of nutrients at the surface of the plume, with the spring tide injecting high concentrations of nitrate, another readily metabolized nitrogen source, into the plume surface. A more detailed discussion, below, focus on: a) Seasonal variation in nutrient concentrations b) Chlorophyll/phaeophytin concentration in the Columbia River and Plume c) Influence of neap/spring tide cycle on nutrient concentrations d) identification of chlorophyll maximum in plume and silicate maximum in the river. .

a) Seasonal variation in nutrient concentrations: Salinity values of surface water collected on the Columbia River line in April, August and November 2007, showed the extent of the river-water influence on ocean surface water, with salinity values below 28 PSU (reflecting a ‘fresh’ plume) found at all times near the mouth of the Columbia (CR4 & CR7) and values of 31 PSU (reflecting an ‘aged’ plume) measured in different seasons at different sites along the Columbia River line.

Inorganic phosphorous concentrations (Fig. II-14B) in surface water over a river-to-ocean gradient in April, August and November 2007 showed no strong river-to-ocean concentration differences or seasonal variations, although a distinct Neap/Spring tide difference is observed (see below). Note, 15 PSU was the only sample collected in mid-water column (10 m). Dissolved silicate concentrations (Fig. II-14C) in surface water over a river-to-ocean gradient in, showed high concentrations of silicate in river water (0 psu) and low concentration in ocean water, during all seasons. The high silicate concentration in Columbia River corresponds to a region with high diatom 18S rDNA from nucleic acid sequencing data (see below). Nitrate concentration (Fig. II-14E) was quite variable, especially in the plume. A large standard deviation found in the surface plume samples illustrates the large variation in nitrate concentrations, which reflects the mixing of plume water with different water masses as well as the influence of the neap and spring tide cycle (see below). Nitrite concentrations (Fig. II-14F) in surface water over a river-to-ocean gradient showed low nitrite concentrations in plume and coastal water in August 2007 compared with April and November. A clear river-to-ocean concentration gradient was observed in August but not in November. In river and plume water, higher nitrite concentrations were measured in November than August, but this was not the case for coastal water (CR-15, CR-25/30, CR40). Equivalent nitrite concentrations were measured in April and November in plume and coastal waters. Ammonium concentrations (Fig. II-14G) showed seasonal variation. A large standard deviation is observed in the total surface plume samples, which reflects large variations due to the mixing of plume water with coastal water masses. On the coast, higher ammonium values were measured in August than April. In summary, aside from the Spring tide effect (see below), the levels of nutrients are low in the Columbia River plume (CR4/7), as shown by the low silicate, ammonium, nitrite, and nitrate levels. The depletion of the nutrients coincides with a high concentration of chlorophyll and

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elevated bacterial production (Fig. II-14D), and could reflect accelerated, microbial mediated nutrient uptake and utilization.

b) Chlorophyll /phaeophytin concentration in the Columbia River and Plume: Chlorophyll and phaeophytin concentration was measured, for samples collected from the Columbia River Line (Fig. II-15A), using a Turner AU10 Fluorometer (data is shown in Figs. II-14D and II-15). High chlorophyll a concentration was observed in the stations within the plume (Fig. II-15B), within an area of high bacterial productivity (Fig. II-14D). In contrast, higher concentrations of phaeophytin, a degradation product of chlorophyll, are observed in the river and estuary (0 psu, 15 psu, Fig. II-15C). The ratio of phaeophytin to chlorophyll approaches 0.9 (Fig. II-15D), suggestive of a decay in algal populations within the river and estuary. The phaeophytin concentration in the river and estuary surface water is especially pronounced in August. At this time, chlorophyll data awaits more rigorous HPLC analysis, which will resolve chlorophyll a, b, and c pigments, as the latter two can affect fluorescence-based measurements. The region of high chlorophyll at CR4/7 is a site potentially inhabited by marine diatoms of the genus Thalassiosira according to 18S rDNA sequence data (see below). The region of high phaeophytin is also near an area of high silicate at the 0 psu site in the Columbia River. This site contains 18S rDNA of freshwater diatoms Diatoma and Aulocoseira according to 18S nucleic acid sequence data presented below.

c) Influence of neap/spring tide cycle on nutrient concentrations: Surface ‘fresh’ plume salinity values collected in August 2007 showed salinity was not affected by the neap and spring tidal cycle. ‘Fresh’ plume is here defined as having a salinity value below 28 PSU. Inorganic phosphorus concentrations of surface ‘fresh’ plume water collected in August 2007 showed that phosphorous concentrations are affected by the neap and spring tidal cycle, with low values measured during neap tide. The same was true with Nitrate concentrations of surface ‘fresh’ plume water collected in August 2007. Again, concentrations were affected by the neap and spring tidal cycle, with low values measured during neap tide. The Nitrate/phosphorus ratio in the spring tide approaches 16, which is conducive to primary production. The results suggest that the spring tide creates greater opportunities for primary production by delivering an important nitrogen source, nitrate, to the plume waters.

d) Identification of chlorophyll maximum in plume and silicate maximum in the river: Concentration contour maps of nutrient/chemical distribution were created using the nutrient measurements of sample from the April 2007 cruise and the Ocean Data View software (performed by Dr. Joseph Needoba). The samples and data described above were primarily from surface water, aside from the mid-depth sample at 15 psu. The maps of Figs. II-17 and II-18 in this section were generated using data from samples collected at several depths within the plume and river. Salinity measurements uncovered the plume over the surface (Fig. II-17), and a chlorophyll maximum in the low salinity layer at the surface. This is also a site of high oxygen by low nitrate and silicate. A layer of high ammonium concentration is located near the salinity gradient of the plume and below the chlorophyll maximum. The 18S sequence data (see below) suggest that the high chlorophyll and oxygen area is inhabited predominantly by diatoms of the genus Thalassiosira. It is also an area of high bacterial productivity (Fig. II-14D).

Concentration contour maps of the Columbia River and estuary highlight the low salinity of the upper river, where a high concentration of silicate is observed. This site is also an area of high phaeophytin, elevated phaeophytin/chlorophyll a ratio and inhabited by freshwater diatoms (Diatoma and Aulocoseira) as indicated by 18S clone DNA sequence analysis.

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The estuary also shows high silicate and phaeophytin/chlorophyll a ratio. Sequence analysis of 18S rDNA clones suggests that heterotrophic ciliates of the genus Katablepharis are abundant in the estuary and is being sustained by decaying algal populations.

Investigation of microbial activity. RNA analysis, protocol optimization and preliminary results: Four lines of investigation are underway in the analysis of nucleotide sequences obtained from samples collected throughout the Columbia River Line. Two involve the sequence analysis of 16S rRNA from bacteria and Archaea. This involves obtaining population profiles using DGGE (denaturant gradient gel electrophoresis) and SSCP (single-strand conformational polymorphism), which indicate the number of different taxa at each sampling site. This is accompanied by sequence analysis of clone libraries of DNA sequences encoding 16S rRNA amplified from total environmental DNA. Byron Crump and Holly Simon have included the description of these investigations in the reports for their respective labs, and will only be presented here in brief.

A third project involves a similar approach to uncover the eukaryotic microbial population (phytoplankton, zooplankton, protists, etc.). This involves cloning and sequencing the DNA encoding the 18S rRNA from amplified environmental DNA samples. This was carried out be undergraduate, Peter Kahn, under the supervision of Lydie Herfort, and with the assistance of Mikaela Selby. Tawnya Peterson and Joseph Needoba have participated in the analysis of the data and will be actively engaged in the project in year 3.

The fourth project involves transcriptomic analysis of environmental gene expression at selected sampling sites. This is being carried out by Lydie Herfort and Mikaela Selby, and in collaboration with Mariya Smit and Holly Simon. The approach is to obtain total environmental RNA, free of DNA, followed by removal of stable RNA by subtractive hybridization. The remaining RNA is then amplified by sequential treatments with reverse transcriptase and Taq polymerase to create a collection of cDNAs derived from mRNA sequences. These are then inserted into a TOPO-TA vector followed by E. coli transformation for library construction.

In addition to these projects, Mariya Smit is engaged in a bioinformatic approach to identify candidate genes from databases of sequenced bacterial genomes for construction of probes that will be used to outfit a microarray/hybridization device (such as the ESP) employed for in situ bacterial taxa identification. This is described under Enabling Technologies.

In each of these projects, sequencing is carried out at the Genome Sequencing Center, Washington University, St. Louis, MO (Contact: William Courtney, Lucinda Fulton).

a) Transcriptomic analysis: Our protocol for transcriptomic analysis is based on that of Poretsky et al. 2005 Appl. Env. Microbiol. 71: 4121-4126, but in contrast to their study, water is not pre-filtered. This is done in order to collect both free-living and particle-attached microbial assemblages. Water is thus directly filtered onto a 0.2 �m Sterivex filter. Extraction procedure has been optimized using samples that were collected in the Columbia River at St Helen (Oregon) at different seasons. We have compared several extraction procedures for microbial mRNA included those presented below. We determined that there is a strong seasonal variation in the RNA content of river samples, suggesting that most of the DNA signal observed in winter might be an in-situ community with low RNA content or DNA from biofilm matrices associated with particles that originate from up-river, soil run-off.

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Following subtractive hybridization of 16S & 23S rDNA, mRNA isolated from these samples was used for cDNA synthesis by reverse transcription (RT). The resulting cDNA was amplified by polymerase chain reaction (PCR). Sequencing of samples collected in the Columbia River water collected at St Helen in November 2006 returned many sequences affiliated to the 28S rDNA of phytoplankton, so that an additional subtractive hybridization step for 18S & 28S rDNA was added for the subsequent samples.

The BLAST analysis from the cDNA clone collection from the Febuary 2007 sample collected from the upriver site at St. Helens, OR is shown in Table II-3.

The upriver site is an area of low productivity in February and is likely nutrient limited. Sequences specifying ammonium and sulfonate transporters indicate activities that are normally induced when preferred nitrogen and sulfur sources are depleted.

Difficulties encountered in obtaining transcriptomic data included high concentrations of stable RNA in samples from sites of high productivity. Also the recurrence of certain sequences, such as a clone of acetyl-CoA carboxylase, indicate problems with primer hybridization bias during amplification or a very limited set of mRNA sequences that can be reverse transcribed. Improvements in RNA extraction are being implemented by Mariya Smit (Holly Simon, Year 2 report).

b) Analysis of 18S clone libraries uncover profiles of the Eukaryotic microbial population: In this section, I will summarize work initiated by an undergraduate student, Peter Kahn, who served as a CMOP undergraduate intern during the summer of 2007, and has continued his work here in the spring of 2008. The goal of the project was to obtain profiles of the eukaryotic microbial population of the areas covered by the Columbia River sampling line, focusing on the salinity gradient that extends across the lower river and estuary. These studies mark the first time eukaryotic microbial assemblages within the Columbia River, Estuary and Plume have been examined by employing sequence analysis of environmental 18S rRNA. In addition to the sampling sites across the salinity gradient of the estuary and plume, the August cruise encountered a large red tide (Myrionecta rubra) bloom (Fig. II-21), which as extensively sampled.

For sampling sites in the salinity gradient, a freshwater (0 psu) site, an intermediate salinity site (15 psu), and a higher salinity site (28 psu) were chosen (Figs. II-22 and II-23).

The 18S clone libraries were constructed by amplification of total environmental DNA with primers EukA (1,AACCTGGTTGATCCTGCCAGT,21) and EukB (1766, TGATCCTTC TGCAGGTTCACCTAC, 1743). The PCR fragments were inserted into TOPO-TA vector and transformation of competent E. coli strain Top10 by electroporation was carried to generated libraries of 18S DNA sequences. The collections (192 clones/per site) were sent to the GSC at Washington University for sequencing. BLAST analysis was undertaken by Chris Oehman of Pacific Northwest National Laboratories.

The first sets of clones were constructed from DNA extracted from samples that were collected during the April 2007 cruise. Sequences of 18S rRNA were obtained from species of several phylogenetic levels. The collection of cloned sequences is presented in Figs. II-22 to II-24, and in Table II-4. Differences in the composition of the eukaryotic microbial assemblages can be discerned when the three sites of the salinity gradient are examined. Phytoplankton was the predominant group of eukaryotic microbe in the river and in the plume. However the major

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group in the mid-salinity site within the estuary was the protist (Fig. II-22). A closer inspection of he BLAST results yields the data of Fig. II-23, which show that the phytoplankton of the river and plume areas are predominantly Diatoms, while protists and dinoflagellates are abundant in the mid-salinity area of the estuary. Unlike the 16S sequence data, only a few genera are represented among the 18S sequences of the predominant eukaryotic groups found at each site. The diatoms at the 0 psu site are mostly Diatoma and Aulacoseira, while the diatoms in the plume area at 28 psu were nearly all Thalassiosira (Fig. II-24, Table II-4). In the estuary at the mid-salinity site, the predominant protist is of the genus Katablepharis, Katablepharids are heterotrophic, single-celled eukaryotes with two flagella. They are grazers that feed on algae, and are found abundantly in the estuary where there is a high concentration of phaeophytin, which as mentioned in the previous sections, is indicative of algal decay, or perhaps predation. Interestingly, some Katablepharids have been known to contain single plastids high-jacked from algae. It is not known if the Katablepharids that are likely to inhabit the estuary in April possess this capability.

Several samples were collected from the North channel during the red tide bloom in August (Fig. II-21). The five samples included two in the red tide, one at the fluorescence peak, one from a lower fluorescence site, and two non-red tide, one of which was collected 1 m below the high fluorescence layer at the surface.

Thus far the 18S sequences that have been collected and sequenced are of the those of Myrionecta rubra species, a ciliate that carries a chloroplast obtained from a cryptophyte. The species carries on karyoklepty, in which it appropriates nuclei and chloroplasts from algal species. A goal of this part of the 18S project is to characterize the 18S and 16S sequences of the nucleic acid extracted from the red tide samples to uncover the products of karyoklepty likely resulting from resident Myrionecta activity.

c) Other Investigations of microbial assemblages in the Columbia River and Coastal Ocean

c1) The Estuary Turbidity Maximum: As mentioned above, the estuary turbidity maximum of the Columbia River estuary is a site of high bacterial productivity. Turbidity measurements during the August cruise detected the ETM event (Fig. II-26).The ETM is a site of active manganese redox turnover, which is believed to be microbially mediated. Mn is an abundant and important nutrient of the Columbia River and estuary system. Mn oxidation and reduction are under study by Suzanna Braür and Kira Kranzler (Evergreen State University) in the laboratory of Brad Tebo. Extensive sampling of the ETM was carried out for future 16S, 18S, and transcriptomic analysis. A number of bacterial isolates were collected from the ETM and cultured in the laboratory by Michiko Nakano (see M. M. Nakano year 2 report). The RNA from the laboratory stocks of ETM bacteria will be used to test probes for the design of microarray probes used in gene expression studies.

c2) Nitrogen cycling within the hypoxic zone: A Ph.D. student, Suzanne DeLorenzo in Brad Tebo’s lab is engaged in a project to uncover the bacteria of the hypoxic environment off the coast of Oregon. These organisms participate in nitrogen cycling pathways that fuel biological productivity. Of particular interest is the process of ammonium oxidation leading to nitrogen and nitrate production in the oxic/suboxic boundary and within the oxygen minimum zone. Stable isotope probing (SIP) will be conducted and 16S rRNA sequence clone libraries of DNA extracted from samples collected in the suboxic area and at the oxic/suboxic boundary will be analyzed to determine which taxa might participate in ammonium oxidation.

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c3) Archaeal diversity in the Columbia River and its tributaries: Our aim is to find out if pelagic archaeal diversity changes seasonally in river water and if so, determine if those changes are comparable and occur simultaneously in four neighbour rivers that are subject to the same climatic forcings. Eventually our goal is to establish if environmental parameters can predict archaeal community structure in river water.Monthly sampling of surface water was carried out since November 2006 to November 2007 at the same sites in the following four rivers: Columbia River at Port Westward, Lewis & Clack River at Ford Clatsop National Memorial, Youngs River at the Waterfalls and Deep River at the bridge on Hwy 4. The samples for the following analysis were collected: nucleic acid, microbial cell counts (by CARD-FISH), concentrations of chlorophyll a, nutrients (ammonium, nitrate & nitrite, phosphorous, silicate), particulate organic carbon and nitrogen, suspended particulate matter, temperature and salinity.

For each site, Sterivex filters (0.2 um) were extracted by adding small pieces of filter in tube containing 2 ml of Phenol/Chloroform/Isoamylalcohol (PCI) (25:24:1), 2 ml of extraction buffer (LETS: 100 mM LiCl, 10 mM EDTA, 10 mM Tris (pH 7.8), 1% SDS) and Zirconia beads; bead-beating twice for 2 min; cleaning with PCI, running the extraction through a Ribopure Bacteria column. The specificity of archaeal denaturing gradient gel electrophoresis (DGGE) was first tested for a sample collected in the Columbia River in 21 January 2007. DGGE partial archaeal 16S rRNA genes (420 bp) were amplified using the general archaeal PCR primers Parch 519f (50-CAGCCGCCGCGGTAA-30) and Arch915r (50-GTGCTCCCCCGCCAATTCCT-30). To increase sensitivity to Archaea a two step PCR was used: without CG-clamp for first PCR (annealing temperature: touchdown PCR 68-64 oC for 9 cycles and 64 oC for 31 cycles) and with GC-clamp on the reverse primer in the second PCR (annealing temperature: 64 oC for 13 cycles). Amplicons were separated according to the GC content and secondary structure by using a linear denaturing gradient of 30–60% for 6 h at 200V. Gels were stained for 20 min with SYBR gold and documented Typhoon Trio+. DGGE bands were excised and each one was eluted in sterile 10mM Tris-HCl (pH 8.0) at 4 1C for 24 h. Sequencing reactions were performed with Parch 519f.

DGGE bands 1-7 were re-amplified with Parch 519f and Arch915r and sequenced at OGI (primate center). Sequences were blast in NCBI and were all affiliated to Archaea, thus showing that the approach used works. Therefore all remaining samples are going to be analyzed in the coming weeks using this protocol.

Plans for next funding period: The further characterization of eukaryotic microbial communities using 18S sequence, nutrient and microscopic analysis will be continued in by P. Kahn, L. Herfort, T. Peterson, J. Needoba, and P Zuber. The goal will be to uncover the seasonal changes the microbial community undergoes and how tidal influences, particularly the neap spring tidal events that influence the nutritional environment of the estuary, affects microbial population structure.

As mentioned above, work will proceed on optimizing protocols for obtaining cDNA libraries of environmental messenger RNA as a means of uncovering the microbial activity ongoing at sampling sites.

Studies of nitrogen cycling in the anoxic areas of the coastal ocean will proceed as part of the thesisresearch of Suzanne DeLorenzo.

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A new project is being explored with Fred Prahl, T. Peterson, J. Needoba, and P. Zuber that involves the study of the microbial-mediated methane generation and utilization in the estuarine environment of the lower Columbia.

II.2.a.2.1.2 Exploring Microbial Populations and their Activities in the Columbia River System: 3. Crump Lab

Team: Byron Crump (CMOP investigator, UMCES), Lydie Herfort (CMOP post-doctoral fellow, OHSU), Caroline Fortunato (CMOP student, UMCES), Joanna Green (CMOP technician, UMCES)

Overview: The goal of the Crump lab in the first several years of this project is to collect and analyze nucleic acid samples from the Columbia River, its estuary and the adjacent coastal ocean in order to characterize bacterial, archaeal and eukaryotic phylogenetic diversity and identify how those communities change over time and across major physical and chemical gradients. Results from this project will be published, but will also be used to direct the efforts of a team of scientists who will be selecting samples for more intense genetic analyses, including cDNA libraries of mRNA, CARD-FISH enumeration of productive taxa using specific rRNA and mRNA sequence probes, and probe microarray design.

Progress on research in year 2 entailed preparing for and carrying out field sampling and laboratory analysis of chemical and biological samples. Dr. Crump and his team handled a broad range of environmental measurements for the CMOP cruises. Working with Dr. Lydie Herfort, they coordinated the post-cruise processing of samples for measurements of dissolved organic carbon, total dissolved nitrogen, total dissolved phosphorous, particulate organic carbon, particulate organic nitrogen, and total suspended solids. These measurements describe the dissolved and particulate organic matter pools throughout the Columbia River, estuary and coastal ocean. The Crump group also collected and processed measurements of heterotrophic bacterial production rates using 3H-leucine incorporation technique. This is the only measurement of biological production performed in the first year of this project. Bacterial production is a relatively easy rate to measure, and it tends to correlate with primary productivity, protist grazing rate, and other food web processes, and so will be useful as input for ecosystem modeling.

The Crump lab group is also processing DNA samples to measure the diversity of bacteria and other microorganisms. They plan to use chemical and biological measurements mentioned in the last paragraph to define the environments within which these microbial communities exist.

Results from Crump group research fall into two categories: Bacterial Biogeography and Bacterial Productivity, both of which make use of water samples collected during CMOP research cruises in 2007. These samples covered a broad range of salinity and temperature, nearly capturing the full range of estuarine conditions sampled during the CRETM-LMER project (1991-1998; Fig. II-29), and expanding this sample set to higher salinity waters in the plume and along the coast.

Bacterioplankton biogeography: This work is being done primarily by CMOP graduate student Caroline Fortunato. Bacterioplankton diversity was surveyed in 75 out of 121 samples extracted and 148 samples collected from the August cruise on the Wecoma using PCR-DGGE fingerprinting of 16S rRNA genes in DNA extracts. These samples included river, estuary, plume, surface ocean, and deep ocean samples. We identified great variability in

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bacterioplankton community composition (Fig. II-30a), but determined that communities clustered significantly into four major groups: 1) Estuary, 2) Surface/Chlorophyll maximum depth in plume and coastal ocean, 3) Bottom depths on the shelf (<150 m), and 4) Deep bottom depths off the shelf (>650m). Estuary and Deep communities were quite distinct, but Surface and Bottom communities on the shelf overlapped somewhat because of similarities between offshore chlorophyll maximum samples and nearshore bottom samples. Stepwise linear regression models using environmental data were able to explain 83% of the variability along the two axes of a multidimensional scaling diagram (p<0.001). This analysis identified temperature, silica, chlorophyll-a, and phaeophytin as potential drivers of community variability, but also identified a spatial component to community variability by identifying relationships with depth, longitude and latitude.

Within each of these major clusters of bacterioplankton community composition we identified some finer-scale variability (Fig. II-30b). In the Columbia River estuary, communities were fairly constant (average DGGE similarity value = 0.68), when compared to Coast Surface/Chlorophyll maximum and Coast Bottom clusters (0.40 and 0.38 respectively). However, these estuarine communities clustered by salinity, and varied with longitude, temperature and bacteria production. Graduate student Daniel Murphy is applying several molecular techniques to more fully describe variability in communities across the salinity gradient of the estuary.

Bacterioplankton communities in bottom water samples on the shelf were highly variable and clustered weakly by region (Fig. II-30b). Communities in bottom waters below the plume clustered with bottom water samples from coastal transects on the Columbia, Waquoit and LaPush lines. Two nearshore bottom samples from the Newport line clustered separately. Variability in these communities was weakly related to chlorophyll concentration. Graduate student Suzanne DeLorenzo will be applying several molecular techniques to more fully describe variability in communities in this environment, with special emphasis on oxygen gradients and hypoxic/anoxic waters.

Bacterioplankton communities in coastal surface waters clustered into several groups based on distance from shore and proximity to the plume (Fig. II-30b). Surface and chlorophyll maximum samples were rarely identical, but tended to cluster together except in offshore samples. Plume samples clustered together, except for one plume sample (WS#64 collected at P-16), which was collected just outside the plume front and contained a community similar to offshore coastal communities on the nearby Waquoit Bay and Columbia River lines. Community composition in these samples varied with longitude, bacterial production, salinity, temperature and chlorophyll-a. Graduate student Caroline Fortunato is designing a dissertation project centered on the Columbia River plume and will be applying several molecular techniques to more fully describe variability in communities in this region

Bacterial productivity: This work is being done primarily by CMOP research technician Joanna Green. Bacterial production was measured on all CMOP water samples from the August and November cruises using the Leucine Incorporation technique. Many of these samples have yet to be processed, but using the available data from the August cruise we applied stepwise multiple linear regression to model bacterial production based on a) CTD-based sensor data (Sal, T, O2, OBS, fluorescence, depth) and b) Sensor data plus chemistry measurements (NO3, NO2, NH4, PO4, Si, Chl-a, Phaeo, DOC, TDN, TDP). The goal of this comparison was to identify new sensors-based measurements to improve our ability to predict bacterial productivity. Bacterial

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production measurements were modeled together, and grouped by major regions (estuary, plume, coast) and by bacterial community composition (see DGGE results above). In all cases, inclusion of measurements not currently being collected with sensors improved these models (Table II-6). Many different measurements improved these models, but the ones that made the biggest difference were phosphate (overall, coast, and coast_surface/chlorophyll maximum), chlorophyll-a (coast, coast_surface/chlorophyll maximum, coast_bottom), DOC (plume), and dissolved silica (estuary).

Empirical models like those presented in Table II-6 can be used to predict bacterial production from the rich, higher resolution datasets provided by sensors. Fig. II-30c shows predicted bacterial productivity in surface waters and with depth along the Newport Hydroline based on the first empirical model in Table II-6. These maps of productivity fall short in many places, particularly in the plume region where bacterial productivity was higher than indicated. Moreover, these models failed to accurately predict bacterial production measurements from the CRETM-LMER program. So clearly our empirical model-based predictions cannot yet be used as predictive tools, but they may be used as tools for hypothesis generation and for visualizing potential variability across this large and complex system. We intend to use this approach to investigate spatial and temporal patterns in bacterial productivity and also to investigate the distribution and dynamics of bacterial populations and communities in the Columbia River, Estuary, Plume and Coastal Ocean.

Plans for next funding period: In years 3 and 4, Dr. Crump plans to continue to serve as one of the principal coordinators for CMOP field research activities, and to participate in the Research Incubation Group and Data Standards Working Group. Our research goals for years 3 and 4 build on our current research and are aimed at predicting the composition and productivity of bacterioplankton communities throughout the river to ocean system. We will continue to process samples collected in 2007 in order to complete our broad-scale picture of productivity and community composition. Results of this work will help identify environmental gradients that require finer-scale sampling (e.g., the plume front and plume bottom), and will provide information for modeling the distribution and dynamics of dominant bacterial populations. We also plan to expand on this work by: 1) identifying dominant bacteriopankton communities through DNA sequencing, 2) applying a second “community fingerprinting” technique better suited to very large sample sets (Automated Ribosomal Intergenic Spacer Analysis, ARISA), and 3) designing quantitative PCR primer-probe sets to quantify dominant bacterioplankton populations throughout the system. We will also continue to measure bacterial production, and hope to collaborate more closely with the ecosystem modeling team to efficiently gather the necessary data to construct and test a predictive model for ecosystem production. A detailed description of our plans for Years 2 and 3 will be submitted as a proposal in response to the forthcoming CMOP request for proposals.

II.2.a.2.1.3 Exploring Microbial Populations and their Activities in the Columbia River System: 3. Simon Lab

Team: Holly Simon, Mariya Smit, Dan Murphy, Isaac K’Owino, Holly Simon, Lydie Herfort, Mikaela Selby, Peter Zuber, Byron Crump Activities

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• Analysis of microbial communities of Columbia River and coastal ocean using phylogenetic and gene expression microarrays (reported under Enabling Technologies)

• Investigation of the microbial composition along salinity and temporal gradients using 16S rRNA gene analysis.

• Development of environmental biosensor (reported under Enabling Technologies)

Investigation of the microbial composition along salinity and temporal gradients using 16S rRNA gene analysis (Murphy, Simon, Zuber): A primary goal of CMOP is to relate the composition and activities of microbial assemblages to regional productivity and to biogeochemical cycles in the Pacific Northwest coastal margins. As a part of the microbiology component of CMOP, we have undertaken a study to understand the ecology of microbes within the Columbia River estuary. To characterize the dominant microorganisms, molecular analysis of small subunit (SSU) ribosomal RNA (rRNA) genes is being conducted within the Columbia River estuary, the Columbia River itself and the adjacent coastal ocean. Construction and analysis of clone libraries, together with PCR-Single Strand Conformation Polymorphism (SSCP) fingerprinting analysis has led to the identification of dominant microbial taxa and their relative populations sizes (Figs. II-31 and II-32, and Table II-7).

Clone libraries constructed from SSU rRNA genes collected from Columbia River ecosystem samples resulted in an initial assessment of the biogeography of microorganisms identified (Fig. II-31). At present, eight different bacterial SSU rRNA gene libraries in ninety-six well plates have been constructed. Two of these libraries were constructed from microbial DNA extracted from water samples collected on March 27, 2007 at the beaver army dock- a freshwater sampling site upriver of the Columbia River Estuary. Additionally, two libraries have been constructed from each of three samples that were taken across a salinity gradient within the estuary during the first week of April 2007. These six libraries were constructed with microbial DNA collected at salinities of O PSU, 15 PSU and 32 PSU. Additional clone libraries of archaeal SSU rRNA genes are also being constructed from the April samples, along with bacterial SSU rRNA gene libraries from samples collected during August 2007. The August samples were collected at similar salinities as those from April - 0 PSU, 15 PSU and 32 PSU.

The SSU rRNA gene sequences are being used to develop phylogenetic constructs, from which we will infer identities of the corresponding microorganisms. Preliminary analyses suggest that these data correspond well to studies done previously in the region by Byron Crump and colleagues. Further analysis will allow us to determine if observed differences are relevant. The microbial community information will also be analyzed within the context of concurrently collected measurements on chemical and physical parameters.

The characterization of microbial communities present within the Columbia River ecosystem has been conducted using Polymerase Chain Reaction - Single Strand Conformation Polymorphism (PCR-SSCP). Used widely today in biomedical research, PCR-SSCP was originally described as a technique to detect allelic polymorphisms in interspersed repetitive sequences of human chromosomal DNA. At low temperatures, single-stranded DNA molecules will adopt a three-dimensional conformation determined by the intramolecular interactions that influence their electrophoretic mobility in a non-denaturing polyacrylamide gel. PCR fragments of the same size, but with differing nucleotide sequences, are separated due to their differing electrophoretic mobility and detected using silver staining of DNA bands or fluorescently labeled primers and an automated DNA sequencer. At present, a working protocol for the identification of bacterial phylogenetic types (phylotypes) within the sample has been established. Profiles of the water

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samples that were used to construct the April clone libraries have been analyzed (Fig. II-32 and Table II-7). These data indicate that PCR-SSCP can be used to compare the microbial community composition across reasonably large numbers of samples at one time. Additional analysis will be done to determine whether the community profiles generated from different samples are significantly different.

The work described in this section builds and expands upon microbial research within the Columbia River ecosystem. Our expectation in the future is to connect microbial composition and population data to system-wide chemical and physical phenomena. More immediately, the current data set provides a foundation from which to characterize temporal and spatial relationships of estuarine microbial populations.

II.2.a.2.1.4 Exploring Microbial Populations and their Activities in the Columbia River System: 4. Nakano Lab

Team: Misty Scevola (HS teacher), Cole Zuber (HS student), Tai Huang [EBS MS student] and Michiko Nakano (CMOP investigator)

Activities

Isolation and Identification of Bacteria from Water Samples in the Columbia River estuary Isolation of Bacteria that Utilizes Dimethyl Sulfide (Nakano). Antibacterial Activity from Bacillus pumilus isolated from the Columbia River estuary

Isolation and Identification of Bacteria from Water Samples in the Columbia River estuary (Scevola, Zuber, Nakano): In this project we cultured and isolated bacteria from water samples collected from the Columbia River estuary turbidity maximum on June 14 by Lydie Herfort. The aims of this project are 1) for Ms. Scevola to learn basic concepts and techniques of environmental microbiology and molecular biology, which she can bring back to her classroom and adopt to her teaching. 2) to identify bacteria and their activities that could influence the coastal margin, which might yield useful data for the future monitoring of such activities in its natural environment.

We incubated the water samples by shaking at 28°C for 8 days and aliquots of diluted samples were plated on half-diluted artificial seawater agar (Halohandbook, http://www.microbiol.unimelb.edu.au/people/dyallsmith/) supplemented with 0.5% peptone and 0.1% yeast extract. The agar plates were incubated at room temperature and colonies with different morphologies were further purified to obtain single clone isolates. Chromosomal DNA prepared from each clone was used as a template for PCR amplification of 16S rRNA gene (nucleotides between 27 and 1492). The 16S rDNA sequences were used for BLAST search to identify each isolate. The results are summarized in Table II-8.

As expected and previously shown (Crump, BC et al., Appl. Environ. Microbiol. 65:3192-3204, 1999), bacteria likely originated from both the ocean and the fresh water habitat in the Columbia River estuary, although the results did not elucidate which bacteria are metabolically active and which genes are highly expressed. Multiple clones were classified into the same species, which indicates either that some of these clones could be sister cells or in some cases, these clones belong to different strains. The latter possibility is most likely in the case of Pseudoalteromonas sp., as some isolates produced different colored colonies from the others.

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Isolation of Bacteria that Utilizes Dimethyl Sulfide (Nakano): Dimethylsulfoniopropionate (DMSP), which is produced by marine phytoplankton and macroalgae, is converted to dimethyl sulfide (DMS) by bacteria. DMS, released from the sea to the atmosphere, is thought to affect global climate, although some conflicting views have surfaced. A great level of DMS is degraded or utilized by micoroorganisms in the sea, suggesting that bacterial utilization of DMS would have an impact on climate change. Therefore, bacterial genes involved in DMS utilization could be good candidates to use as a probe for the sensor and/or RNA analysis to detect changes in microbial activity. Therefore, I determined whether some of the bacteria isolated above have the capability of using DMS as a sole sulfur or carbon source. None of the isolates was able to grow with DMS as a sole carbon source, whereas some grew with NSYE base (Fuse et al., Appl. Environ. Microbiol. 66:5527-5532, 2000) supplemented with DMS as sulfur source. These bacteria are A1 (Limnobacter sp.), B28 (Marinobacter marinus), C4 (Marinobacterium geogiense), and C12 (Pseudoalteromonas arctica). In fact, C4 is closely related to Marionbacterium sp. strain DMS-SI that was shown to utilize DMS as a sulfur source in the presence of light by Omori’s group (Fuse et al., Appl. Environ. Microbiol. 66:5527-5532: Hirano, et al., Environ. Microbiol. 5:503-509). As a noticeable level of growth was detected in these strains when cultured in the absence of sulfur source, I will further examine in more detail whether DMS is indeed utilized in these bacteria. The GC-MS facility on site will be useful for looking at DMS consumption.

Antibacterial Activity from Bacillus pumilus isolated from the Columbia River estuary (Huang and Nakano): Natural environments serve as rich reservoirs of substances with antibacterial activities, which potentially can be developed as a drug for therapeutic use. Bacterial infectious disease is a worldwide threat for public health and the news is fresh in our memory that recent outbreaks of infections by methicillin-resistant Staphylococcus aureus (MRSA) caused 94,000 life-threatening infections and 18,650 deaths in the United States in 2005. We screened for anti-Staphylococcus activity among the bacteria isolated as a pure culture as described in A.1. Although CMOP does not contribute either budget or human resource for this research, the bacteria were isolated during a CMOP research activity. Hence, I will summarize the results.

Three bacterial isolates (C1, C2, C9) produced substances effective against S. aureus RN6390 (methicillin-sensitive S. aureus, or MSSA). Because Bacillus pumilus C9 showed the highest activity, we focused on the substance, which was subsequently named C9ASA (C9-produced anti- Staphylococcus activity). C9ASA is exclusively produced by B. pumilus isolated from the Columbia River estuary, but not in six strains of B. pumilus obtained from Bacillus Genetic Stock Center (Ohio State University) as shown by inhibitory zones on lawns of S. aureus (only 8A3, 8A4, 14A1 strains from the Stock Center are shown in Fig. II-33).

C9ASA is active against only but not all Gram-positive bacteria and it is particularly effective against S. aureus, Staphylococcus carnosus, and Sreptococcus pyogenes. Both hospital-associated MRSA (HA-MRSA) and community-acquired MRSA (CA-MRSA) are sensitive to C9ASA. S. aureus and S. pyogenes (Streptococcus group A) are among the NIAID list of re-emerging pathogens group II (http://www3.niaid.nih.gov/research/topics/ emerging/list.htm), indicating that C9ASA is effective against important pathogens.

We have partially purified C9ASA and characterized physico-chemical nature of the substance (data not shown). We are planning to identify the structure of C9ASA and identify genes involved in C9ASA production in B. pumilus.

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Plans for next funding period: We plan to further characterize DMS utilization by bacteria isolated from the Columbia River estuary.

1) We will determine whether A1 (Limnobacter sp.), B28 (Marinobacter marinus), C4 (Marinobacterium geogiense), and C12 (Pseudoalteromonas arctica) grow with DMS as a sole sulfur source, and whether the utilization is dependent on light.

2) Metabolites produced from DMS during growth of the above bacteria will be determined by gas chromatography-mass spectrometry (GC-MS) analysis.

3) Studies will be aimed at identifying genes involved in DMS utilization.

II.2.a.3 Progress and accomplishments in Coastal Margin Science: Ecosystem Dynamics, Climate and Water Use (goal R2, objective E)

As we evolve towards a broad interdisciplinary perspective, much of Y2 activity was still mostly exploratory in nature, rather than hypothesis-driven. A common thrust is the exploration of river-to-ocean gradients. Most of that work was conducted along Columbia River estuary and plume gradients, but we have started to also explore gradients across estuaries. The concept of environmental sentinels, representative of variability and change, is becoming a more prevalent topic–although we recognize that understanding of several scales and processes is still not amenable to the definition of such metrics. The arrival of Joseph Needoba and Tawnya Peterson has created a range of opportunities for collaboration, which are still emerging.

II.2.a.3.1.1 Physical characteristics of the Columbia River estuary and plume

Team: Antonio Baptista (CMOP director, OHSU); Charles Seaton (CMOP staff and part-time PhD student); Joseph Zhang (CMOP investigator)

Description: The 1999-2006 SATURN/CORIE simulation databases (DB11, DB14 and DB16, see http://www.ccalmr.ogi.edu/CORIE/hindcasts/database/base_frame.html) are being examined, in conjunction with historical SATURN/CORIE observation, to examine estuarine and plume processes and gradients. The objectives are multiple and synchronous: • Develop an authoritative description of Columbia River circulation and its climate- and

human-induced variability, aimed at serving as a peer-reviewed reference for the scientific community and for CMOP ecological and microbial research.

• Provide contextual guidance for the design of microbial cruises (e.g., characterization of patterns of salinity intrusion, estuarine turbidity maxima, and estuarine and near-plume fronts; for our purposes, characterization inherently includes the concept of variability.)

• Develop a process-based benchmark for numerical models of estuarine circulation. • Explore contrasts between the Columbia River and other PNW estuaries, in particular as they

relate to impact of climate systems and bottom deformation associated to Cascadia Subduction Zone earthquakes.

In Y2, activities included:

• Developing, calculating or using possible circulation-based “environmental sentinels”, such as a Columbia River upwelling index, plume metrics (volume, area, centroid, thickness) salinity intrusion lengths, and dimensionless estuary numbers.

• Using circulation-based environmental sentinels to characterize variability, both in the Columbia River estuary and plume and across PNW estuaries. Cross-estuary contrasts are still limited by the quality of simulations available for those estuaries.

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• Beginning to characterize change associated with large-scale processes (emphasis on the radical changes associated with Cascadia Subduction Zone earthquakes).

II.2.a.3.1.2 Linkages between physical forcing and expression of biological variability along steep gradients in the river-to-ocean system

Team: Tim Cowles (CMOP investigator, OSU; RIG co-chair); Ricardo Letelier (CMOP investigator, OSU)

Scope: Our component of the CMOP STC addresses the scales of variability in the spatial gradients observed within the Columbia River to coastal ocean system. We are particularly interested in assessing the links between physical forcing and the expression of biological variability along steep gradients in this river-to-ocean system. We use bio-optical instruments, deployed in situ, to evaluate changes in particulate and dissolved constituents along these spatial gradients. Interpretation of our results depends upon coordinated measurements of physical properties and processes by other CMOP investigators.

During Year 2 we have been involved in three primary areas within CMOP research: 1) analysis of discrete samples obtained during CMOP cruises, 2) direct collection, processing and distribution of NASA MODIS ocean data, and 2) research planning and coordination for CMOP, particularly for Year 3 and beyond. In the sections below we will provide details of these accomplishments and activities.

Analysis: Discrete samples for chlorophyll (fluorometry), pigments (HPLC), and flow cytometry were collected as part of the core measurements during each cruise. To date all chlorophyll samples have been processed, analyzed and sent to Lydie Herfort. The flow cytometry samples have also been processed but we still need to analyze the results to assess any potential errors before they are distributed. Finally, the HPLC samples are scheduled to be processed next April and should be ready for distribution by May.

Remote sensing: In collaboration with the Cooperative Institute for Ocean Satellite Studies (CIOSS) and NASA we have maintained our Direct Broadcast Station and processed daily images of MODIS Terra and Aqua sea surface temperature (SST) and ocean color products (see http://orca.coas.oregonstate.edu/MODIS/RTSI/index.shtml) . In addition, we have an online archive of these images as well as the time-series of chlorophyll and SST for the pixel region corresponding to NH10 (see: http://picasso.coas.oregonstate.edu/ORSOO/oregon/satellite/). These time-series can be extended, if needed to other regions of interest for CMOP researchers. Finally, we have started to explore the use of 250m MODIS products to assess environmental variability in bays and other coastal regions that are usually masked when 1km resolution data are used.

Research Planning and Coordination: One of us (Cowles) has served as Co-Chair of the CMOP Research Incubation Group (RIG) during Year 2. The RIG has been addressing many of the issues mentioned by the NSF Year 1 Annual Review, as well as the suggestions of the External Advisory Board. The focused discussions of the RIG regarding CMOP research objectives led to productive program-wide discussions at the CMOP All-Hands Meeting in February 2008. The RIG can provide valuable advice in the short-term and long-term aspects of research coordination with CMOP, and we strongly support the continued engagement of the RIG in the distillation of the overarching goals of CMOP.

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II.2.a.4 Progress and accomplishments in Coastal Margin Science: Contamination Pathways

We anticipate that an increasing number of CMOP projects will explore contamination pathways in coastal margins. In Y2, we conducted only one project in this area.

II.2.a.4.1 Transport of polycyclic aromatic hydrocarbons (PAHs)

Team: Tiffany Gregg (MS student; OSU), Fred Prahl (CMOP investigator, OSU)

Motivation and goal: This projects aims to gain a better understanding of the transport of polycyclic aromatic hydrocarbons (PAHs) via suspended particulate matter (SPM) from the Columbia River to its estuary. PAHs are ubiquitous, hydrophobic contaminants that have recently been detected at elevated levels in the stomach contents of juvenile salmon collected from sites within the Columbia River and its estuary (Johnson et al., 2007). This finding is environmentally concerning because studies of English sole have shown that PAHs can cause a variety of deleterious impacts, such as liver disease, reproductive dysfunction, DNA damage, and decreased growth (Johnson et al., 2002). One goal \is to identify and ultimately quantify the role of SPM as an exposure pathway for PAHs and other hydrophobic contaminants to organisms in the Columbia River-Estuary system.

Data collection: In August 2007, Tiffany participated with other CMOP personnel in a cruise aboard the RV Barnes to collect water samples from the Columbia River and its estuary. Sampling sites in the river extended from the port of Vancouver down to the USGS NASQAN (National Stream Quality Accounting Network) sampling site at Beaver Army Dock (River Mile 53) and in the estuary during neap and spring tide ETM (Estuarine Turbidity Maximum) events. These samples now provide the foundation for the present research.

Status: By the end of March 2007, Tiffany will have completed processing and analyzing all the samples collected from the Barnes. Results will include data on SPM concentration, particulate organic carbon and nitrogen content, phytoplankton pigment content and PAH composition and concentration (per L of water, per g sediment and per g organic carbon), at each sampling site. In addition, Tiffany has been working in cooperation with the USGS, Portland Water District to obtain bi-monthly samples from River Mile 53, a designated NASQAN site. This field work was completed in February, 2008. The latter data set will provide a quantitative sense of the seasonal fluctuations in the composition and concentration of SPM-associated PAH discharged by the Columbia River to its estuary.

Preliminary results: Preliminary results indicate that SPM in the Columbia River and estuary, regardless of sampling site, carries easily detectable quantities of PAH. The PAH composition measured throughout the study region is very similar and derived from at least two sources, one of which is not unexpected from high temperature combustion processes (LaFlamme and Hites, 1978). In comparison to the river, combustion-derived PAH concentrations (ng PAH/g sediment) during spring and neap ETM (Estuarine Turbidity Maximum) events appear to be somewhat more enriched and perylene, a PAH of natural but yet otherwise uncertain origin, is highly concentrated. The detected PAH concentrations were compared to EPA issued sediment quality guidelines for PAHs shown to cause adverse impacts in aquatic organisms. The upriver PAH concentrations fall below the guidelines, with the exception of phenanthrene and its mono-methyl homologues, compounds of potentially mixed high temperature combustion and fossil fuel origin (LaFlamme and Hites, 1978), and the estuary PAH concentrations are at the threshold

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of concern. Gregg is currently working with her thesis committee, Jennifer Morace from the USGS, and Lydie Hefort from CMOP, to further interpret the data.

II.2.a.5 Progress and accomplishments in Enabling Technologies: Numerical Modeling and Data Assimilation (goal R3, objective G)

Our goal is to develop, advance, and/or parameterize algorithms, protocols and codes that effectively support emerging coastal margin modeling systems and their enabled coastal margin science. Activities have been conducted in the following areas:

• Circulation models • Model-independent data assimilation • Ecosystem models • Ocean forcing for climate change scenarios

II.2.a.5.1 Circulation Models

Team: Joseph Zhang (CMOP investigator, OHSU), Antonio Baptista (CMOP director, OHSU).

Description: We developed a MPI version of SELFE, the primary circulation model used in the SATURN/CORIE modeling system. As all versions of SELFE and ELCIRC, MPI SELFE is available as a community model. A user group meeting takes place annually.

We have also developed SELFE interfaces to ecological models being developed at OSU and LNEC.

Plan for next period: We will continue low-level algorithmic development for SELFE, as needed to support robust modeling efforts in the Columbia River and other PNW estuaries. We will also continue to address issues at the interface between SELFE and ecological models. We will also continue to support the SELFE community, including hosting the annual user group meeting.

II.2.a.5.2 Model-independent Data Assimilation

Team: Sergey Frolov (PhD student, OHSU), Todd Leen (CMOP investigator, OHSU), Antonio Baptista (CMOP director, OHSU)

Description: Data assimilation (DA) plays a central role in emerging costal observatories. However, a wide application of many existing DA methods is hampered, among other things, by the limited computational resources available to coastal observatories. To address the need for fast, model-independent, non-linear data assimilation methods, we recently developed a non-linear extension to the reduced-dimension Kalman filter (KF). The computational efficiency of the new method comes, in part, from the use of neural network model surrogates that execute forward simulations three orders of magnitude faster than the traditional numerical circulation codes.

In Year 2, we tested our DA methods to:

• Improve characterization of estuarine processes (in particular salinity intrusion length). A publication was submitted on this topic.

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• Optimize the location of new SATURN/CORIE sensors. In particular, we formally showed that the location of SATURN-01 fills a significant gap in current physical measurements in the estuary. A publication was also submitted on the topiv of network optimization.

Plan for next period: As post-doctoral fellow Sergey Frolov leaves to accept a position at MBARI, we will transition the responsibility for data assimilation to Dr. Y. Joseph Zhang. Continued effort in Y3 will focus on network optimization and adaptive sampling..

II.2.a.5.3 Ecosystem Models

Team: Scott Durski (post-doctoral fellow, then staff; OSU), Yvette Spitz (CMOP investigator, OSU)

Our modeling research of year 2 included two parts. First, we addressed two of the three grand challenges proposed by CMOP, i.e. determination of the impact of climate on the physical and biological conditions and the variability of coastal margins, and identification of the role of coastal margins on global elemental cycle. Second, we focused on the coupling of unstructured grid circulation models with various ecological model, which is a necessary precursor to development of a coupled ecosystem/circulation model designed to understand natural variability of the dynamics of river-ocean ecosystem off Oregon.

Impact of climate and global elemental cycle: A five component ecosystem model developed for the Oregon Coast (Spitz et al., 2005) has been coupled to the ROMS circulation model to study the impact of wind forcing on the ecosystem on the shelf. This configuration does not yet include the Columbia River but will be added in year 3. To study the impact of wind forcing, we chose three summers that are characterized by upwelling favorable wind with different strength and periodicity. Two important time scales of 2- to 6-days (weather-band) and_20-days in the wind forcing are characteristic of 2000-2002 and 2001, respectively (Fig. II-34)

The ecosystem initial conditions are the same for all three years and are horizontally uniform with profiles for nitrate and phytoplankton obtained from the first day of the COAST summer cruise 2001 (Spitz et al, 2005). The initial profiles for the remaining variables are taken from one year, one dimensional run with small background diffusivity and without detrital sinking. The circulation model is started with zero velocity and horizontally uniform temperature and salinity profiles from climatological May values 25 miles off Newport. The coupled model is started on May 1 and the first 22 days are considered as spin-up period.

In the year 2000, the beginning of May experienced a weak upwelling favorable wind stress compared to the year 2001 and 2002. Upwelling/relaxation on time scales less than 10 days are dominant by mid June in 2000 and 2002, contrary to 2001 when periods of continuous upwelling are of roughly 20 days. As a consequence, the mean chlorophyll-a concentration (Fig. II-35) over the upwelling season (May 23 – August 2) shows slightly higher value inshore of the 50 m isobath in 2001 than in 2000-2002. Higher concentration is found on the shelf in 2001-2002 while it is wider spread in 2000. The succession of upwelling/relaxation on shorter time scale in 2000 than in 2002 allows for larger across-shore extension of biomass in 2000 than 2002. Similar effect is observed with upwelling/relaxation events on 20 day periodicity. The most striking differences among the three years are in the zooplankton mean biomass. The zooplankton concentration is much higher in 2001 than in 2000 and 2002. Year 2000 experienced the lowest mean biomass. The standard deviation (not shown) is also very low in 2000. The prolonged upwelling events during 2001 (20 days) allow zooplankton to grow and control phytoplankton

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biomass on the shelf. Less than 10 day upwelling events do not permit high zooplankton biomass but allow for wider spread of phytoplankton biomass on the shelf. In addition to wind forcing, topographic effects on the ecosystem is also observed. There is accumulation of zooplankton biomass where the shelf widens. The relative importance of the physical and biological forcing on the phytoplankton and zooplankton concentrations for the three years is currently being analysed.

For the comparison of three years with typical wind forcing off the Oregon Coast, we can conclude that climatic changes will have consequences on the balance between primary and secondary producers, which ultimately will be of importance for fisheries management.

Preliminary results show that nearshore oxygen concentration is higher in 2001 than in 2000 and 2002. However, the standard deviation of the oxygen concentration displays larger across-shore variability in 2000. This study will continues in year 3 of the project.

Coupling with unstructured grid circulation model: Unstructured grid circulation models allow very high resolution in the Columbia River and the river plume and lower resolution off the Oregon Coast where horizontal scales of variability are larger. Multiple efforts of ecosystem/circulation coupling are in progress with collaborators in Portugal, OHSU and NOAA, spanning a range of ecological codes and coastal regions. A shelf benchmark has been developed and is currently under investigation. Technical difficulties occurred with the coupling of the ecosystem and the SELFE circulation model in its serial configuration. The SELFE circulation model in its serial configuration requires high cpu time and high memory. The addition of the ecosystem model made it impossible to use this configuration other than for a limited region and limited time (few days) or as a 1D configuration similar to the coupling of ECOSYM by collaborators in Portugal. A new MPI version of SELFE was made available a few weeks ago. The ecosystem model has been embedded in this version and is been tested. We are confident that we can now proceed with the shelf benchmark and plan a river to ocean benchmark.

II.2.a.5.4 Ocean forcing for climate change scenarios

Team: David Rivas (post-doctoral fellow, OSU), Roger Samelson (CMOP investigator, OSU)

We have achieved the projected Jan 2008 milestones for: • SIP 1.7.A.1 (analysis of existing capabilities): Initial results on analysis of selected IPCC

simulations • SIP 1.7.A.2 (design and implementation): Demonstration of capability for regional process-

oriented modeling • SIP 1.7.A.4 (climate-scale databases): Collection of selected IPCC simulations • SIP 1.7.A.6 (system skill assessment): Initial results on selected IPCC simulations

A subset of IPCC simulations has been selected for analysis. Selection of the subset was based on evaluations of the model representations of PDO and ENSO variability. A regional primitive-equation model has been implemented for the relevant portion of the northeast Pacific. Currently, all of the associated numerical data resides on COAS computers. We are also maintaining an archive of regional atmospheric forcing fields from the NCEP Eta/NAM model. We have explored transferring this archive to OHSU but at this time it remains at COAS.

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II.2.a.6 Progress and Accomplishments in Enabling Technologies: Sensors (goal R3, objective J)

The goal of this thrust is to develop or render deployable innovative sensors to support the emerging SATURN monitoring network and the CMOP coastal margin science. Activities have been conducted in areas that include:

• Sigma profiler • Phylogenetic and gene expression microarrays for analysis of microbial communities Nucleic acid

hybridization array device using surface plasmon resonance technology • Airborne remote sensing • Nutrient sensors • Derivatizing agents

II.2.a.6.1 Sigma Profiler

Team: Thomas Sanford (CMOP investigator, UW)

Goals and approach: Point measurements of salinity via electrical conductivity are standard. By contrast, autonomous measuring of vertical profiles of salinity is not standard and represents a challenge. Mechanical solutions for profiling salinity and other variables are used in CMOP elsewhere. Here, we seek to measure conductivity over the entire water column from a fixed position in the water column. The approach will be based on using ambient EM signals or producing low-frequency EM waves while observing the attenuated, reflected or backscattered signals. The enabling principle is that EM waves travel with phase and group velocities and absorption that are inversely proportional to the square root of electrical conductivity. Salinity is a function of electrical conductivity. The inverse is true: electrical conductivity in the sea can be used to determine salinity. The absorption of EM signals in seawater is proportional to the square root of electrical

conductivity times frequency. Natural signals, such as ionospheric EM waves and Schumann resonances from global

lightning enter the ocean and decay at a rate proportional to the square root of frequency times electrical conductivity.

Expected usage and impacts of new technology: Within CMOP the use of multiple sigma profilers will permit more detailed budgets of fresh water and salt transport, position and strength of turbulent, high-gradient salt wedge fronts and observations for numerical model validations and assimilation.

Beyond CMOP, there are applications that would benefit from sigma profiling. For example, fresh water export from the Arctic through the Davis and other straits needs to be monitored for ocean climate studies. Strong flow and ice cover or icebergs make conventional measurements, such as from moorings or autonomous gliders, difficult and expensive with high probabilities for loss.

EM Fields in Electrically Conducting Media: Underlying concepts are: E-field has a simplified governing equation given by

∇2E = μσ∂E/∂t + με∂2E/∂t2 Without the 1st term on the RHS in 1, it is a wave equation. However, the 2nd term on the

RHS is small in seawater for frequencies below one MHz. Thus, the resulting equation is a

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diffusion equation and EM wave decays with distance. For a signal of exp –i(kx – ωt), diffusion solution must satisfy the dispersion relation, k2 = –

iωμσ. Thus, k = (1 – i)√(ωμσ/2). The real part is the wavenumber and the imaginary part is the attenuation rate, i.e.: The wavenumber k is (ωμσ/2)1/2, which is a wavelength of 2π/(ωμσ/2)1/2 that is about

1570 m at 1 Hz and 4 S/m. EM waves decay by e–1 in skin depth δ = (2/ωμσ)1/2, which is about 250 m at 1 Hz and 4

S/m. The phase speed is cp = ω/k = (2ω/μσ)1/2, which for the above values of ω and σ is 1570

m/s. Note that the wave is dispersive; group velocity cg = cp /√2.

Relationship Between σ and S in Columbia River: Electrical conductivity is highly correlated with salinity in this and all other records, as shown in Fig. II-36 for Desdemona Sands, near the mouth of the Columbia. The correlation is strong throughout the year (Figs. II-37 and II-38). Numerical Simulations: The concept was validated by solutions from a numerical model adapted from terrestrial geophysical surveying. Prof. Doug Oldenburg at the University of British Columbia provided a program to compute the EM fields from a grounded dipole source in the river with air above, sediments and rock below the sediments.

Many computations were conducted for the E, H and E/H signals at a receiver spaced away from the source. The domain consists of air, fresh water, saltwater, sediments and basement with electrical conductivities of 10–8, 10–2, 3, and 1 S/m, respectively. This forward model has been used to simulate the performance of the system for various combinations of source and receiver separations and model parameters. Fig. II-39 is an example of the simulations for the model at current source spacing similar to our observations in the Snohomish River. The E-field decays more rapidly in space for 10 kHz vs. 100 Hz. Relative to 100 Hz, the nearfield signals at 10 kHz are generally stronger, while its farfield signals are weaker. This is consistent with the skin depth differences.

Experimental Approach for Columbia River: Our approach is to inject known electric current at the riverbed into the water column. The electric field at some distance from the source electrodes is just

E = J/σ

where J is the electric current density (Am–2) that reaches the receiver along paths through the various layers of river water of differing electrical conductivities. In addition to the geometry of the paths, the electric field depends on the frequency of the source. The decay scale or skin depth is proportional to the inverse square root of ωσ. That is, the amplitude of the received electric field is a function of the conductivity along many paths and the frequency of the source.

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Electrical Conductivity Profiler Electronics and Power Supply: The instrumentation injects electric current at known amplitudes and frequencies at one point and measures the resulting electric field nearby. A block diagram of the electronics is presented in Fig. II-40.

The instrument is functionally and physically separated into two halves. Strict electrical isolation is maintained between the two sections to eliminate ground loops and minimize cross coupling of direct transmit signals into the receiver. One section provides the transmit function where drive signals are amplified and applied to drive electrodes. The other section contains a low noise transformer-isolated receiver amplifier and a low-power digitizer and data logger.

The transmitter section consists of a 22 W rms audio power amplifier derived from an Audiovox AXT-120 automobile stereo amplifier. The amplifier input was modified to provide additional capacitive coupling for isolation and better low-frequency response. The physical case was modified to fit within a 5” ID pressure case. A current sense transformer (Amveco Magnetics AC1005) was added to measure transmitter output current into the driven electrodes. This current-sense signal remains completely isolated from the transmitter. The amplified signal drive titanium mesh electrodes are coated with a mixed metal oxide (Telpro Inc. 1.25” x 48”). Power for the transmitter amplifier is provided by a Ni-MH battery pack rated 3.3 A-h @ 14.4V. The transmit section also contains another Ni-MH battery pack with the same rating that supplies a DC-DC converter providing a regulated +/-15V output to power the receiver preamplifier. External connections for turning the power on and charging the batteries are provided by underwater rated connectors. (Impulse Enterprise IE55 series)

The receive section processes signals presented from a pair of carbon-fiber electrodes (Polyamp AB model PA3001A). A low-noise transformer-coupled preamplifier of our own design amplifies the low-level signal from the electrodes. It utilizes a 5:1 step-up transformer on the input that is double-shielded and internally Faraday-screened to provide isolation, common-mode rejection and low noise. The output of the transformer is applied to an Analog Devices AD797 OPAMP where it is further amplified for a total gain of 100. The amplified signal is presented to a 16-bit A/D converter (Texas Instruments ADS8344) through an offset and clipping circuit which insures the signals will fall in the A/D converter’s range of 0 – 2.500 V. The ADC and its voltage reference reside on a “micro recipe card” from Persistor Inc. The data logging function is provided by custom firmware running on a Persistor CF-2 microcontroller. Data is buffered and written to compact flash. An OES USB-1 card, which shares an electrical bus with the CF-2 and micro recipe cards, provide a USB interface. The USB interface allows rapid (200 kB/s) offload of data from the compact flash card to an external PC. The power for the microcomputer system is provided by a Ni-MH battery pack rated for 1.60 A-h @ 9.6V. A modified B+K 3003 signal generator produces the sine wave signals at various frequencies used to drive the dipole source electrodes. The 3003 generator circuit board was removed from its housing and the thumbwheel switches that set the frequency were removed. Open-drain switches from a custom port-expander board interfaced to the CF-2 were substituted for the manual switches. This arrangement provided the CF-2 with the ability to set the generator frequency to any frequency between 10 Hz and 40 kHz in a 1-2-5 sequence. The sine wave signal is coupled across a barrier to the transmitter power amplifier via a coupling transformer that provides isolation between transmit and receive.

The firmware executed by the CF-2 provides the operator with the ability to set parameters that define the operation of the unit for a particular mission. Basically the unit sleeps for a period of time, wakes up and executes a series of measurements utilizing different frequencies, computes

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some statistics, writes the data to compact flash and goes back to sleep. The 9.6V battery pack provides enough power to operate the microcomputer system for 16 h of ON time and 100 h of OFF time. The maximum mission time possible will depend on the frequency of measurements and the amount of time spent ON calculating statistics. The 14.4V battery for the preamplifier provides for about 100 h of ON time for the +/–15V supply. The 14.4V battery for the transmitter power amplifier will provide full power operation of the power amplifier (25 W rms) for about 1 h. The mission parameters define how this 45 W-h of energy are used, i.e., fewer lengthy measurement periods or many short bursts for sampling.

Overall the electronics are housed in an all-plastic (Delrin) pressure case with o-ring seals and underwater connectors for all signals and battery charge functions. An RS-232 serial connection is also provided, which allows an operator with a PC to setup the instrument in the field with mission parameters and initiate the USB upload of data. Under normal operations there is no need to open the instrument housing as the unit can be re-charged and data uploaded through the end cap connectors.

The first implementation of the Sigma Profiler concept was a set of electrodes on a rectangular frame of polypropylene piping and fittings. The vertical dashed lines in Fig. II-40 denote the physical separation and electrical isolation between the Source Transmitter and the EM Receiver and Datalogger sections. The source was a pair of mixed metal oxide coated mesh titanium electrodes, spaced about 2.5-m apart on a narrow end of the rectangle. The receive electrodes are similarly spaced on the other end of the rectangle, about 6-m distant. The Ti-MMO source electrodes are specially prepared to provide high current density for many years. The electronics and pressure housing are shown in Fig. II-41. The receive electrodes are made with carbon fiber that are basically capacitive connections to the water. Fig. II-42a shows the Ti-MMO electrodes, and Fig.II-42b shows an example of the carbon fiber receive electrodes.

Field Observations: The Sigma Profiler was deployed in the Snohomish River in water about 6.5 m deep at high tide with a range of about 3 m. The planned observation site is shown in Fig. II-44. However, a brief depth survey discovered a deeper site to the south of the planned location. Not only was the chosen site deeper, but also it was south of the main tug and barge traffic.

The R/V Miller was anchored heading upstream and the frame was then lowered onto the riverbed. The Miller was moved forward on its anchor line as a tag line from the frame was let out. Once the frame was on the bottom, a clump of weights was deployed on the line after 30 m. About 150 m of line was trailed upstream where another weight was deployed attached to a surface float.

Soon after deployment, CTD casts were taken every 30 min with a Seabird SBE-19, and acoustic backscatter strength was monitored on the fathometer at 15 kHz or 200 kHz. All of the profiles of electrical conductivity are shown in Fig. II-45a. The water column was always river water at the surface, but initially the bottom half was seawater. Gradually the saltwater layer thinned until after about 6 h it was nearly fresh from top to bottom. There were numerous distinct layers seen on many of the CTD profiles. Most of the time these layers also showed up on the Miller’s fathometer (Fig. II-46). The accumulated data over the 6-h deployment were downloaded soon after the recovery of the frame and electronics (Fig. II-47).

The observations of received voltage difference normalized by the corresponding source current are plotted in Fig. II-48. The bottom layer of saltwater thinned starting after 1530 (Fig. II-45b), and the received electric field began to increase. The largest rate changes were after 1730,

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reaching a maximum at the end of our observations. All transmissions exhibited similar behavior but only the 1-kHz signal lacked harmonic distortion. The source current was too strong at 10 Hz and 100 Hz and saturated the current transformer core (vide Fig. II-40). The 10-kHz signal failed for an unknown reason. The form of Rx/Tx agrees with the numerical simulations.

As the well-mixed layer of seawater thinned, the electrical conductance of the water column decreased. The increased resistance of the water column caused the receiver voltage to increase for the same amount of source current. The pattern of the received electrical potential difference divided by the transmitter current, Rx/Tx, is almost the inverse of height of the seawater layer or the electrical conductance of the water column. This suggests that there is a useful relationship between the Rx/Tx and the conductance of the seawater.

The experimental results demonstrate a sensitivity of Rx/Tx to the conductivity profile of the river. A simple inversion scheme is based on an electrical circuit model, which shows that the conductance of the water column should be inversely related to Rx/Tx. Such a model is applied to the 1-kHz observations (Fig. II-49).

The inverse relation between Rx/Tx and thickness of the seawater is consistent with our expectation. The relation 0.9/(Rx/Tx - 1.6 mV/A) yields a time series of the height of the seawater layer. A single frequency provides a single height estimate. It is expected that a future experiment will demonstrate that other frequencies provide complementary height estimates, such as the heights of other conductance values. It is important to realize that the CTD data provided the calibration that led to this empirical fit. Other sites may have very different relationships between conductance and electric measurements. However, it is likely that CTD casts between high and low water will supply the calibration values at other sites. It is not known if the calibration is time dependent, e.g., seasonal.

Discussion: The first deployment of the Sigma Profiler was carried off smoothly and produced excellent results. Not all frequencies were useable because of saturation of the current transformer measuring the source current. The failure of the 10-kHz channel is not yet explained. However, the best signal, 1 kHz, demonstrates the ability of the Sigma Profiler to determine the conductance of the saltwater layer from the riverbed. Electrical conductance of the saltwater intrusion is the vertical integral of the electrical conductivity over this layer. The electrical measurements from the riverbed provided a remote measure of the saltwater conductance. This performance was achieved with 2.5-m separation of the source electrodes. In general, the region of the water column sampled by the grounded dipole is related to the electrode separation, with larger separations the current is distributed higher in the water column. In deep water, we probably need to increase the source electrode separation. However, the smoothness of the black curve in Fig. II-49 suggests that we have a low-noise measurement. It may be possible to work in the Columbia River with 2–4-m source electrode separation.

We will deploy the frame again, probably multiple times, in the Snohomish River before the start of the 3rd year. We plan to separate the source electronics with its high-level voltages and currents from the low-noise receiver electronics. Now they are housed in the same pressure vessel, and there is some crosstalk between the source and the receive portions.

The large frame provides support for many source and receiving electrode sites but is not optimum for the Columbia River and duplication elsewhere. Our intention is to experiment with a long, linear array, such as a cable with multiple source and receiver locations. This would

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make it easier to provide source and receiver separations that are at least twice the water depth and would be simple to deploy by streaming it behind a small boat.

Acknowledgments: The Sigma Profiler was developed and deployed with funding from the NSF’s Science and Technology Center for Coastal Margin Observation and Prediction under grant OCE-0424602. The instrument’s electronics and frame were designed and built by Jim Carlson. John Dunlap developed the software for the data logger. Both are Sr. Engineers at APL-UW. Jim Carlson, John Dunlap, Avery Snyder and Tom Sanford conducted the deployment in the Snohomish River. We were guided in our experiment planning by the numerical model provided by Doug Oldenburg of Earth and Ocean Sciences at UBC and members of his group, Roman Shekhtman and Rob Eso.

Planned Activities for Year 3:

Science and Technology Goals: The science goal of this project is to contribute to understanding and predicting better the character of physical and chemical variability at many time and space scales. The technology goals is to develop the Sigma Profiler into an inexpensive, easily deployed and long-lived instrument with near real-time data communication that will support the interdisciplinary science and real-time numerical models being conducted by CMOP investigators. Costs depend on what is included, but the EM system should cost less than $10K. The plan is that Years 3 and 4 complete the development so there is time to analyze data and document efforts in Year 5.

Objectives for Year 3: Our objectives for the next year are to simplify and improve the Sigma Profiler and deploy it repeatedly for long durations in multiple sites in the Columbia River. These tasks will be complemented by efforts to implementing in situ power, such as using microbial fuel cells, and near real-time data communications.

Plans for Year 3: Specific tasks to be undertaken in Year 3 include:

• Expand numerical modeling and data inversion studies for Sigma Profiler data. • Study tradeoffs among frequencies and source/sensor arrangements using numerical

model or from multiple arrangements in field observations. • Determine how best to exploit the observations to support the scientific studies and real-

time numerical models of CMOP investigators. • Construct new optimum sensor configuration and reduce power. • Evaluate options for using CR river structures, such as bridge piers or navigation pilings,

for more reliable, long duration observations and sites for downloading lander data for real-time data.

• Determine means to download data via EM (i.e., using the present current source to transmit data to shore) or acoustic signals sending real-time data; use spread spectrum RF link to CMOP HQ.

• Deploy new Sigma Profiler arrays and ancillary systems (CTD, ac. backscatter) and trial data link in the CR, make CTD casts or use observations from the moored CTD profiler on bridge pier.

• Observe simultaneous E- and B-field signals to compute the Poynting vector). • Collaborate with Clare Reimers and determine feasibility of microbial fuel cells for the

Sigma Profiler.

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Discussion: The most attractive sensor design is that with source and receiver electrodes all in a line (i.e., collinear) that can be deployed easily from a small boat. One concept is to use a fabric tube, much like the covering of a fire hose, in which the electrodes are strung. The lines of potential will pass easily into the tubing. Low power operations are necessary. This will be achieved by lowering the source power (the results of the field tests demonstrate high S/N. Also, the duty cycle can be reduced to a measurement every 10 to 30 min and still adequately observe the salt wedge.

It is important that we begin to develop a means to communicate the measurements to shore and on to CMOP investigators in near-real time, say with latency of one measurement cycle. The first link is between the Sigma Profiler and the shore. Obviously, the preferred method is to use a cable. This not only provides the data link but also the power. Such an arrangement might be possible at some sites and may be used initially for testing. A more useful solution is to communicate data from an autonomous installation, distant from cable connections. It would be nice if the data link used the same signals that are injected to measure the height of the seawater layer. Enough data can be encoded on the 10 kHz signal to convey the few observations per measurement cycle. The alternative is acoustic telemetry. An acoustic modem is too expensive – two would be needed for each path. We are currently using time delay telemetry for other projects, such as data from a bottom lander off Newport OR. The scheme is very simple. The values are sent as the time delays between reference and slave pings or bursts. It is a low-baud analog system that is accurate enough for this application and low power. With either the acoustic or EM approach, there must be a receiving station nearby. How far away depends on the transmit power, beam directionality, path loss, ambient noise and receiver sensitivity. There has been some work done with acoustic transponders and modems in shallow water, but it will be mostly a matter of designing the right gear and conducting evaluations in the Columbia River. We hope to benefit from our colleagues’ experience with spread spectrum RF data links from remote platforms to a central acquisition station (Baptista et al. 1999).

The most appropriate installation sites include N. Channel at Saturn 01, AM 169, Pt. Adams, N26 (if rebuilt), Elliot Pt., Jetty A, and Mott Basin. Several of these sites offer CTD observations, shore power and RF data links. Although our goal is to develop an autonomous instrument, relying on internal power and RF/acoustic data link, the early deployments benefit from nearby CTD point or profiler measurements, power and data link.

We expect to collaborate with CMOP investigators, especially modelers, to determine the best locations for the initial deployments of the Sigma Profilers. The number of units is not known at this time and is presently quite constrained by the small amount of Year 4 funding.

II.2.a.6.2 Phylogenetic and gene expression microarrays for analysis of microbial communities in the Columbia River and coastal ocean

Team: Mariya Smit (CMOP post-doctoral fellow, OHSU), Holly Simon (CMOP investigator, OHSU)

Scope: To progress towards phylogenetic and gene expression microarrays for analysis of microbial communities in the Columbia River and coastal ocean, we conducted the following activities: Optimization of a technique to obtain maximum yields of total RNA from environmental

water samples for subsequent nucleic acid analysis.

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Characterization of the abundance of active microorganisms in environmental samples using the amounts of total RNA isolated per liter of sampled water.

Design of an oligonucleotide microarray probe set for analysis of gene expression in environmental samples from Columbia River

Optimization of a technique to obtain maximum yields of total RNA from environmental water samples for subsequent nucleic acid analysis: A robust, high-yield, fast, and reproducible technique is required to obtain sufficient amounts of nucleic acid targets for subsequent analysis. Multiple protocols exist for total RNA isolation from laboratory samples. However, environmental samples present an additional challenge due to contamination with soil and sediment particles. In addition, our water samples are collected by filtering of 1.5 to 5 liters of water through Sterivex 0.22 �m filter units (Fisher Scientific). The filters are preserved in RNAlater reagent (Ambion) to prevent RNA degradation, and then frozen at -80oC. Thus, we needed a protocol adapted for total RNA isolation from a filter, and for removal of RNAlater solution prior to RNA extraction.

Several protocols for total RNA isolation and purification have been tested to select the one producing the highest yields of total RNA. The selected protocol is based on the one described in Griffiths et al. (Griffiths RI, Whiteley AS, O’Donnell AG. 2000. Rapid method for coextraction of DNA and RNA from natural environments for analysis of ribosomal DNA and rRNA-based microbial community composition. Applied and Environmental Microbiology, Vol. 66, No. 12, p. 5488–5491). The protocol has been modified for filter samples, and to further optimize the yield by increasing the number of extractions. As the result, we use three rounds of bead beating for full disruption of microbial cells on a filter. We also collect the particle residue from the RNAlater solution in the filter holder to extract nucleic acids and pool them with the extract obtained from the filter. The optimized protocol takes approximately 3 hours of hands-on work per 4 samples, and it allows one to obtain up to 100 �g of total RNA per filter. The quality of total RNA is estimated using agarose gel electrophoresis. In the future the QC process will be supplemented by capillary electrophoresis performed using a Bioanalyzer (Agilent).

Characterization of the abundance of active microorganisms in environmental samples using the amounts of total RNA isolated per liter of sampled water: Cellular RNA is known be degraded by intracellular RNases within minutes upon the cell death. Thus, the amount of total RNA that can be isolated from a filter sample should correlate with the abundance of live microorganisms prior to fixation of the filter in RNAlater. To estimate whether the amount of total RNA (normalized per liter of sampled water) can be used as proxy characteristics of microbe abundance, we used a set of environmental water samples collected in three cruises in April, August, and November of 2007.

Variability of total extracted RNA from several samples collected during the same day at the same location was evaluated using 4 fresh water samples from the Beaver Army Dock (November cruise). The estimated yield of total RNA was 3.17+0.19 �g/liter, and the coefficient of variation (StDev/Mean in percent) was approximately 12%.

Another sample set was used to characterize microbial populations along salinity gradients in the Columbia River estuary, plume, and the surrounding coastal ocean (Table II-9). Three series of 4 samples each were collected at the same sampling stations with 0, 15, 24-28 and 32 PSU salinity during April, August and November cruises. The resultant total RNA yields are shown in Fig. II-50.

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For all sample collections, RNA abundance was the highest in the Columbia River plume, at the salinities between 24 and 28 psu (Fig. II-50). The nearest sampling location in the estuary (15 PSU) also yielded high RNA amounts, however, they were at least 30% less abundant than in the plume. In April and November, the difference between the two estuary sampling locations (15 and 0 PSU) was below the 12% sample-to-sample variation observed at the same location. However, the difference between the estuary and the plume always exceeded the sample-to-sample variation by at least 3-fold. The difference between the plume and the coastal ocean was quite dramatic, from 3- to 36-fold; the latter observed for the August samples.

RNA data were also analyzed in relation to other environmental parameters that were measured at the same sampling locations during the August cruise. A good correlation (with the correlation coefficient of 0.976) was observed with chlorophyll A measurements (Fig. II-51). Thus, the total RNA amount may reflect the abundance of autotrophic phytoplankton in the samples.

RNA data were also compared to heterotrophic bacterioplankton production measurements, using the technique of 3H-labeled leucine incorporation (from Byron Crump for the two August samples, one from the coastal ocean, and another one – from the plume). The difference in bacterial production between the plume and the ocean (Fig. II-52, right panel) was 28-fold, and it was on the same order of magnitude as the 36-fold difference for total RNA observed between the plume and the ocean (Fig. II-52, left panel).

The chlorophyll measurements showed that the plume sample was rich in phytoplankton, and bacteria are known to be abundant in phytoplankton communities. Thus, high bacterial production rates can be expected at sampling locations with high chlorophyll content, as we observed in our samples. Our data show that the amount of total RNA correlates with the presence of both phytoplankton and bacterioplankton. Therefore, RNA may serve as a proxy for the abundance of active microorganisms. This hypothesis will be further evaluated using subsequent bacterial production data. It will also be tested in samples containing low chlorophyll A and high heterotrophic bacterial populations, in order to evaluate the influence of the bacterial community composition on RNA abundance.

Design of an oligonucleotide microarray probe set for analysis of gene expression in environmental samples from Columbia River: We plan to perform gene expression analysis using commercial oligonucleotide microarrays from CombiMatrix Corporation (www.combimatrix.com, Mukilteo, WA). This array format has been selected since it provides the following advantages: fully customizable probe content, bioinformatic support of probe design from user-defined

gene lists, checking of the designed probes for specificity against a user-defined set of background genomes;

microarray re-usability up to 4-5 times; two major microarray formats: 12K with 12,000 spots, and 4X2K with 4 independent sectors

of 2,240 spots each; availability of a novel electrochemical detection platform for hybridization signals to achieve

shipboard deployment.

The process of probe design for environmental samples from Columbia River is greatly hampered by paucity of sequence information on genes and genomes of interest. The limited information available at the moment has been obtained from two projects that are in progress at CMOP: (1) cloning of 16S rDNA sequences for identification of the corresponding taxonomic

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groups, and (2) cloning and sequencing of cDNA libraries prepared from mRNA transcripts. Sequences from a set of 576 16S rDNA clones from three different salinity conditions (0, 15 and 32 PSU) were obtained by Dan Murphy. The clone sequences were further analyzed using the Ribosomal Database Project II (http://rdp.cme.msu.edu/, the Classify tool) to assign the 16S rDNA sequences to a taxonomical hierarchy based on sequence identity scores. The results indicated that only 10 of these 576 clones could be identified to the genus or species level with an identity over 95%. Reduction of the threshold for identity score to 50% yielded 90 clones that can be assigned to known genera/species. Even if the sequence assignment is done to the relatively high taxonomic family level, 70% of all clones do not show identity over 50% to any known bacterial group. Thus, despite the close identity with a number of different microbial species among the sequenced 16S rDNA clones, only a few of these have been characterized, and only 6 have their genomes fully sequenced (shown in bold in Table II-10). These 6 genomes will be used directly to generate gene-specific probes for well-annotated genes with relevant biological roles.

Since the majority of bacterial species in the environmental samples are unknown, the gene-specific probes from 6 genomes are insufficient to get a comprehensive picture of gene expression in the bacterial community. An additional approach to generate some coverage for unknown species is to design group-specific oligonucleotide probes against evolutionarily conserved regions of characterized genes. As the first steps, we need to generate clusters of ortholog genes (COGs) from ssequences of environmental bacteria, and then select regions conserved in several orthologs. The existing web-based public COG databases are pre-computed to include all, rather than a subset of genomes, and they are not updated frequently enough to incorporate newly available sequences. Thus, we used CombiMatrix Genotyper software to generate COGs for a list of 11 sequenced genomes of relevant bacteria found in environmental water samples (Table II-10). This list includes the 6 species identified in the Columbia River samples based on 16S rDNA sequences (shown in bold in Table II-10). The Genotyper software has performed the following steps: extracted full list of individual annotated genes from each genome; for each gene, performed a rapid one-versus-all BLAST against the whole NCBI database of

completed microbial genomes; selected all orthologs of this gene from the NCBI database; calculated percent identity for each individual ortholog, and average percent identity for

orthologs in different taxonomic groups.

The detailed Genotyper output provided an Excel file in which a row is an individual query gene from the 11 submitted genomes, and each table cell shows percent identity between the query gene and its ortholog (if present) in one of the sequenced genomes from the NCBI microbial database (columns of the file). The output provided a tool for selection of common genes based on the total number of orthologs and degree of identity in taxonomic groups. The genes were selected if they had at least 2 (preferably more) orthologs with the identity above 40% in at least two different species from a taxonomic group. As expected, the numbers of selected common genes were large for well-characterized taxonomic groups with several fully sequenced and related species. The results of gene selection for the 11 genomes submitted to Genotyper are shown in the last column of Table II-10. The numbers of selected genes varied from 30 (in gammaproteobacteria) to over 1000 (in betaproteobacteria).

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The selected genes were further checked for specificity to a particular taxonomic group using the Cluster software (http://rana.lbl.gov/). To better visualize the clustering results and to reduce the huge number of columns, the Genotyper output was re-parsed to a higher hierarchical level of taxonomic groups and families rather than individual genomes. An example of clustering results done for a subset of Roseobacter denitrificans genes is shown in Fig. II-53. It shows that the genes selected as common using the Genotyper output were indeed present with relatively high degree of identity in several other groups of alphaproteobacteria, and even in the more distant beta and gammaproteobacteria. Finally the selected common genes have been submitted to the CombiMatrix Probe Weaver software. It will select the regions that are the most conserved among the COGs, and design the maximum number of oligonucleotide probes between 35 and 40-mer in length. The probes should be capable of detecting various orthologs from different, possibly unknown, bacterial species that might be present in the environmental samples.

The whole set of gene-specific and group-specific probes will be synthesized on a 12K microarray, and tested by hybridization with a pool of labeled nucleic acid targets prepared from samples collected from Columbia River and coastal ocean. The best performing probes will be selected and used to design a smaller set for the 4X2K microarray format. This approach would enable us to reduce costs of testing multiple individual samples. The microarray probe set will be re-designed regularly to incorporate new sequence information, with CombiMatrix providing technical support for this work on microarray development.

II.2.a.6.3 Detection of Functional Microbial Gene Expression Using Surface Plasmon

Team: Isaac K’Owino (CMOP postdoctoral fellow, OHSU) and Holly Simon (CMOP investigator, OHSU)

Resonance Imaging: Rapid changes in the environment’s physical and chemical factors have impacted significantly on the existence of microbes along the river /estuarine/coastal ocean margins. For instance, the chemical composition of this region is continually changed by industrial and agricultural pollution containing toxic heavy metals, organic compounds, hydroxyl ions and other inorganic compounds discharged into rivers and oceans. These often lead to the generation of reactive oxygen species (ROS) such as superoxides and hydrogen peroxide that are capable of damaging the cell membranes of microorganisms as well as their nucleic acids.1 They may also affect the availability of essential elements such as sulfur, nitrogen and carbon that play a significant role in the microbial food cycle.

Microbes respond to these deleterious conditions by using transcriptional regulators to activate genes that express proteins expressions whose functions help them survive under these conditions. Therefore, an attempt to detect the expression of these specialized genes in samples along the river /estuarine/coastal ocean margins samples could reveal the presence of both dormant and inactive bacterial genes in this environment. This will require, however, the development of appropriate assay methods and the use of sensitive diagnostic tools.

In view of the above, we have embarked on a series of investigations with the long-term goal of: • Developing label-free biosensors for detecting microbial gene expression along the Columbia

River estuary/coastal margin • Optimizing the SPR imaging technique as a selective tool for detecting gene expression

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Hybridization buffers of varying stringencies were used to monitor hybridization reactions between both DNA and RNA probes of trxA, trxB, spx and sodD genes with their corresponding chromosomal Bacillus subtilis (B. subtilis) DNA.

We are using the spx, trxA, trxB and sodD genes from B. subtilis to optimize hybridization conditions. Experiments will be carried out using either 25 or 16-gold spotted glass chip (Fig. II-55, 1) mounted on the SPRimager®II sample holder with the rRNA probe sequences (Fig. II-55, 2) immobilized as shown. Briefly, hybridization reactions between the probes and their target complementary ssDNA sequences from B. subtilis DNA (Fig. II-55, 2 and 3) results in the formation of RNA-DNA heteroduplex (Fig. II-55, 4). The ssDNA will be generated from genomic B. subtilis DNA by heating 500 µl of a hybridization solution containing 3xSSC buffer, 0.5% SDS, and 400 ng/µl of B. subtilis DNA at 95oC for 10 minutes, followed by cooling in ice. The ensuing changes in the surface coverage are reflected as percent reduction in reflectivity measured by SPRi.

Results from DNA-DNA hybridization experiments, en route toward DNA-RNA hybridization experiments: Fig. II-56 shows a representative difference image obtained following the hybridization of genomic B. subtilis DNA onto a DNA microarray containing a row of DNA probes corresponding to the trxB and the spx genes found in B. subtilis DNA. The rows containing avidin, single base pair mismatch in trxB (trxBm1) and a 17-base pair mismatch in trxB (trxB17) served as negative controls. As seen from the intensity profile, the trxB probe gave stronger signals than trxBm1 and trxBm17 suggesting that the SPR imaging approach is a viable approach for screening mismatches within gene sequences. However, there was no appreciable difference between the responses of the spx probe from those of the negative controls. We believe the signal may be improved by increasing assay stringency.

The DNA and RNA nucleotide sequences used for probes in these studies are shown in Table II-11. Further optimization of conditions required for sensitive and specific detection of target nucleic acids is required to determine if the SPRimager®II is a viable platform for microbial biosenser development.

II.2.a.6.4 Airborne Remote Sensing

Team: Andrew Jessup (CMOP investigator, UW) and William J. Plant (CMOP investigator, UW)

Description: The original goal in this theme area was to utilize miniaturized infrared and microwave sensors to demonstrate their utility for future deployment on Unmanned Airborne Vehicles (UAVs). As a step towards that goal, the APL aircraft observations for mapping the Columbia River Plume in Year 2 used an infrared radiometer (APLIS-APL Infrared System), a coherent real-aperture radar (CORAR), and a GPS receiver. APLIS was used to measure sea surface temperature and CORAR was used measure surface roughness.

Our objectives for the Year 2 effort were to: 1. Combine infrared and microwave measurements on the same aircraft 2. Use the IR sea surface temperature (IRSST) to map the plume location 3. Use the surface roughness from the radar to detect the plume edge

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Three flights using a Kenmore Air Beaver floatplane based in Seattle were planned for 21-23 August 2007 to overlap with the ship cruise. Although the aircraft took off from Seattle on 21 August, the flight for that day was aborted due to fog. Flights on 22 and 23 August were made successfully. On August 22, the IR showed a large warm region in the plume area and the microwave images detected the evolution of the southwest edge of the plume. On August 23, neither the IR nor the microwaves showed many features of the plume. Figs. II-57 and II-58 show maps of IR skin temperature and mean radar cross section measured on the two flight days.

The measurements of skin temperature can be compared with the CORIE predictions of salinity shown in Fig. II-59. In the measurements, the plume is less visible in the IR measurements on August 23 (Fig. II-58) than on August 22 (Fig. II-57). This is not seen in the predictions (Fig. II-59). As evidenced by the radar cross sections, the wind was much weaker on August 22 than on August 23. This is also shown by nearby NOAA measurements shown in Fig. II-60, where the tidal phases are also shown. Tidal phases are nearly the same on the two days. So the wind speed was the obvious difference between the two days. It should not affect the IR measurement of skin temperature, though, assuming that the bulk temperature was also elevated by the plume. Therefore, the reason for the difference in the measurements is unclear at this time.

The Doppler radar (CORAR) was also able to produce images of cross sections as it flew. These showed the location of the southern boundary of the plume on August 22 and showed its progression toward the south during the flights. Fig. II-61 shows these images shrunken to show their locations.

Since the IR and microwave instruments were flown on the same plane, we can compare the microwave images of the front with the IR observation of the transition to the warmer water of the front as shown in Fig. II-62. Care must be taken in the interpretation of these comparisons since the IR radiometer looked straight down while CORAR looked off to the right side of the plane at distances shown in the figure.

Even allowing for the fact that the IR radiometer looked straight down (at 0 m on the images), it is rather clear that the microwave frontal features are not at the same location as the IR transitions. We will try to investigate this phenomenon further on future flights by collocating the IR and microwave measurements.

The main concern that came out of the Year 2 flights was the complication of transit time and the additional cost of using a Seattle-based aircraft. A Seattle-based aircraft was necessary because of the substantial cost of the installation of the microwave system, which had been done previously under a different project. Another concern was establishing a procedure for determining the optimum flight area to cover on a given day. We used a combination of CORIE model runs and available satellite data. Greater familiarity with using the CORIE model will help facilitate the process in the future.

Plans for the future: We anticipate shifting the focus of this component of the project to the deployment of a fixed remote sensing platform for deployment in the Astoria-Megler bridge, in the North Channel of the Columbia River. The target variable will be surface velocities. That platform will become an integral part of SATURN/CORIE observatory, adding long-term time series capabilities to a part of the estuary that is becoming uniquely instrumented to analyze estuarine processes.

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II.2.a.6.5 Nutrient sensors for application to coastal margins [Check title[

Team: Jim Nurmi (post-doctoral fellow, OHSU), Paul Tratnyek (CMOP investigator, OHSU)

Description:We developed an electrochemically based nitrate/nitrite sensor and a hydrogen peroxide sensor for applications in-situ. These novel sensors can be used for either large spatial resolution studies as well as at fine spatial resolution scales (i.e. every millimeter vertically in sediment cores). The other sensor is a new type of hydrogen peroxide sensor that uses biogenic manganese dioxide for the electrode material. The biogenic MnO2 offers more sensitivity to H2O2 due to the lower overpotential needed to reduce H2O2.

II.2.a.6.6 Derivatizing agents

Team: Jim Nurmi (post-doctoral fellow, OHSU), Paul Tratnyek (CMOP investigator, OHSU)

Description: Our activities are best organized along our classification scheme for sensor development (Type I—Commercial and routine; Type II—Proven but not routinely applied; and Type III—Innovative and exploratory). Given the progression of Type I-III sensors, we have progressed from using and deploying Type I sensors and doing background work on Type II/III sensors (last year) to fabricating and demonstrating the use of Type II sensors and doing background work on the Type III sensors.

Type I: (i) Continued to provide some support for those responsible for equipping SATURN stations regarding the types of analytes for which Type I sensors are available, options for making innovative uses of Type I sensor technologies, etc. (ii) We continued to make theses electrodes available. A new development that has just come to light is the ability to couple these electrodes (mainly O2) to cell cultures to measure the disappeance kinetics of oxygen. This is currently taking place in B. Tebo’s lab and will shortly be done in conjunction with Holly Simon’s group.

Type II: (i) From last year’s literature search, we concluded that the “LIX” type of sensors for key nutrients is the preferred method of fabrication. Using this technology, we designed and fabricated a micron sized electrochemical based nitrate/nitrite sensor that can be used under various configurations. Paul Lim (undergraduate) spent much of his summer perfecting the fabrication of this sensor. When he left, we had a functional nitrate/nitrite sensor that we used to take profiles of a Rock Creek sediment core. Paul Lim was offered early acceptance to Cornell where he will be entering the Chemistry department.

Type III: Two major leaps have made in defining what needs to be done in regards to these Type III sensors. (i) From literature, we have determined that, with respect to reactive oxygen species (ROS)), Individual ROS species such as H2O2 etc. have been studied but the overall ROS activity in coastal margins have not been quantified. In the biomolecular fields, it is necessary for the investigator to determine which ROS species is involved in the oxidation processes, and because of this, most ocean chemists use similar techniques to study individual ROS species concentrations. We plan on using general ROS probes (from Molecular Probes, such as dichlorodihydrofluorescein di-acetate (D-399)) to obtain overall concentrations of ROS species and then compare that data to others biological data (cell counts, nutrient concentration etc.) across the river-ocean gradient. (ii) In a similar sense, we have determined that the use of our 2-Chloroacetophenone probe for abiotic versus biotic activity could be very insightfull in conjuction with other measured parameters such as gene expression, gene activity, nutrient concentration, cell counts, etc.. We have not seen much literature discussing the possibility of

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abiotic versus biotic reduction reactions in the ocean. Given we have expertise with this probe in fresh water and sediment samples, we see this as an exciting new development with large payback possibilities.

II.2.a.7 Progress and accomplishments in Enabling Technologies: Information Management and Scientific Visualization (goal R3, objective K)

The goal of this thrust is to develop software and protocols that effectively support ocean observatories and the observatory-based coastal margin science. Activities have been conducted in the following areas:

• Scientific Visualization • Information management: towards RoboCMOP

II.2.a.8 Scientific Visualization

Team: Claudio Silva (CMOP investigator, Utah), Juliana Freire (CMOP investigator, Utah), Huy T. Vo (PhD student, Utah), Carlos Scheidegger (PhD student, Utah), Emanuele Santos (PhD student, Utah), Bill Howe (post-doctoral fellow, OHSU)

Description: Our primary focus has been on the development of a visualization and provenance management system for ocean observatories. In the context of NSF award IIS-0513692, ``Managing Complex Visualizations'' we built VisTrails (see http://www.vistrails.org), an open-source system that manages both the processes and metadata associated with visualizations. With VisTrails, we aim to give scientists a dramatically improved and simplified process to analyze and visualize large ensembles of simulations and observed phenomena. The beta-version of VisTrails was first made available as open source (under the GPL v2 license) in January 2007. Since then, it has been downloaded over 3000 times. In October 2008, we had the first official release of the system, VisTrails 1.0. We are leveraging the VisTrails system to build a platform to streamline the process CMOP scientists have to go through to analyze and visualize large data ensembles.

This year, we have made major advances in VisTrails and its applications to the CMOP vision. We now have a GridFields package that makes it substantially easier to access CMOP data and consequently to create visualizations. With this infrastructure, we have built a number of 3-D visualizations that have been shown to be useful for domain scientists. For instance, we created a number of 3-D visualizations for Dr. Peter Lawson from NOAA, which coupled CMOP models with NOAA proprietary databases.

We have also made a number of fundamental contributions to workflow provenance that were implemented in VisTrails and are being made available first to CMOP researchers. In particular, our work on “Querying and Creating Visualizations by Analogy” presented at the IEEE Visualization 2007 conference won the Best Paper Award. In our work, we show how to exploit provenance metadata collected during the creation of analysis and visualization workflows. We introduce the idea of query-by-example in the context of an ensemble of visualizations, and the use of analogies as first-class operations in a system to guide scalable interactions.

II.2.a.9 Information management: towards RoboCMOP

Team: Bill Howe (post-doctoral fellow, OHSU), David Maier

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Focus to date: Our primary focus has been on the development of concepts, semantics, and software enabling a transition from CORIE (functionally powerful, but requiring significant expertise to operate, maintain, and extend) to SATURN (characterized by accessibility, adaptability, scalability, and interoperability with external applications). Selected examples include (with primary developer(s) noted):

a) Data models for gridded datasets. Dr. Howe’s thesis focused on a model and algebra for gridded datasets, with particular attention to the unstructured grids arising in hydrodynamic simulations and the manipulations of simulation output used to create human-usable data products. We had an initial meeting with Dr. Roger Barga (Microsoft) about use of GridFields in the Trident workflow system he is involved with for Neptune.

b) Meta-data management: Dr. Howe is the chief developer of the Quarry meta-data harvesting and querying system, which is aimed at individual-product-level meta-data to support detailed query for relevant data products. Quarry allows for simple scripts to harvest meta-data information as (resource, property, value) triples, and synthesizes relational database schemes to support efficient query by analyzing the implicit structure in the data. Quarry currently collects meta-data over hindcast runs of CMOP models. We have been working with James Rucker, a PSU undergraduate, to improve Quarry both in execution efficiency and in the set of data-exploration operations it support, and trying to get meta-data on more CMOP resources into the Quarry Instance. (James is supported by DARPA funds through PSU.) We have had a paper accepted to the 2008 IIMAS workshop that discusses Quarry (and other topics).

c) DataMart: Bill Howe and others have been working at getting DataMart up and running for various CMOP data sources. There was a demonstration of some of the DataMart portals at the February 2008 All-Hands Meeting. DataMart has emphasized several principles in its constructions:

• On-demand construction of data products, so users are not limited to a pre-computed set. • It is always possible to download the data behind any product instance. • A “portal” page within the DataMart is easily configurable as to navigation, data

selection, products and product parameters.

d) Cruise Dashboard: Bill Howe, Antonio Baptista and I worked with a summer REU student, Nick Hagerty, during Summer 2007, to produce a “Cruise Dashboard” that gives on-line access to data being collected on a cruise, along with other data that is useful for cruise operations (such as tide predictions and model output). The Dashboard was used on multiple cruises in the remainder of 2007. This work was accepted for poster presentation the Undergraduate Research Experiences segment of the ASLO Ocean Sciences conference, to be held in March 2008. Part of the development of the Dashboard involved the creation of a framework for “pluggable” data-product components (plus creation of actual components for the framework) that can be easily added to the Dashboard, and for which the set of parameters that the user may select is configurable. This framework (and some of the components) has been reused in the DataMart.

Ocean Appliance: We have been developing the Ocean Appliance, a pre-configured open-source “server-in-a-box” for ingest, processing, and fusion of observation streams and model results. Data and products can be configured and accessed locally through the on-board web server and database server, and are optionally shipped to other ocean appliances for simplified multi-site integration. Currently, we use this model for providing data and computing capabilities on cruises.

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Plan moving forward: We are trying to coalesce future CMOP Cyber-Infrastructure (C-I) activities around the concept of RoboCMOP.

RoboCMOP Vision: Lift scientific C-I to an active participant in the scientific process, acting autonomously to provide the data, products, and context you need, right when needed.

We see RoboCMOP providing a shared “exploration space” for teams of researchers to use during collaborative activities, accommodating and eventually promoting remote interaction. We see its capabilities growing over the next several years: • Initially, it will help locate existing products, both from CMOP and elsewhere, based on

detecting cues in the “conversation” among human collaborators. (We are not proposing speech recognition here, but rather monitoring the tools, data sets and other products being accessed during a session.)

• The next step is to instantiate existing product types on demand (or perceived utility). This capability requires a means to model “product lines” and the ways in which they can be customized.

• Ultimately, we would like RoboCMOP to be able to devise new product variants to meet particular needs. This capability might exploit the initial VisTrails work on creating workflows by analogy.

• In some cases, the desired product can be identified, but cannot be realized because of lack of observations or model output. We would like RoboCMOP to aid in tasking observatory systems to collect or generate relevant data, either through explicit direction of assets, or recognizing opportunities for serendipitous gap-filling.

Getting RoboCMOP to this level will provide a basis for research in how to imbue it with scientific interpretation and analysis expertise, but we see that work probably being in the second five years of CMOP.

Realizing RoboCMOP will require much more funding than CMOP can supply directly. Thus we need to find additional sources of support. Until we have an initial RoboCMOP baseline capability, I think it will be difficult to secure significant funding from federal research sponsors. Thus, we are exploring whether there might be industry sources who would support initial development. Our current strategy is to try to interest Microsoft: Microsoft has a growing interest in supporting the scientific enterprise. They seem to use

both the names "Technical Computing" and "eScience" for it. Their main page is: http://www.microsoft.com/mscorp/tc/default.mspx. They do have an external funding program called the "Technical Computing Initiative" (TCI). Bill Howe and I have both met with Roger Barga (OGI PhD) who involved in TC and has a project called “Trident” that is looking at workflow support for Neptune oceanographers. The VisTrails group has also spoken with Roger. The Trident folks have been looking at incorporating some of Howe's GridField library to deal with irregular grids. We would like to be in position in a year or two where we can compete for serious funding from them to augment what CMOP has available for CI research. They have interest in oceanography, workflows and provenance, so we don’t have to change our focus greatly (if at all) to build ties with them.

Bill Howe has secured funding from MS under the "Jim Gray seed" program, to start building something we term an "eScience Appliance". Similarly to the Ocean Appliance, it would be a complete machine pre-configured to let domain scientists analyze data without worrying about how to install programs or access data. (We are actively discussing whether

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the machine is physical or virtual.) It will have capabilities such as VisTrails, Gridfields, and Quarry on it, plus model and observation data (or an easy way to attach to it). Presumably it will have tools from others, and there would be pre-built workflows as a starting point for use by domain scientists. It could be used for training, and could be cloned or remoted to broaden access. We are waiting to hear from the eScience program if they will be contributing resources to this project beyond the seed funding.

The “Workflow Medleys” work from the VisTrails group should fit in here, too. They have defined a language for manipulating collections of workflows that allows, for example, the synchronization of parameters (and abstraction) across workflows and workflow composition. They e are building a user interface based on this language targeted to end users without programming expertise. One can think of such an interface as a replacement for canned form interfaces that are commonplace in science portals: It is simple and yet gives user greater flexibility for exploration. (Medleys also have potential as a tool that allows IT personnel to more easily create canned interfaces.)

Getting a system set along the lines of the eScience appliance that scientists are actually using would be the right foundation to start building RoboCMOP capabilities on. We would need to make sure it was set up for multi-user sessions (with remote participants). To this end, there is an initial prototype of VisTrails that allows multiple users to collaborate from different locations in a synchronous manner. At that point, we would have some possibility of tracking the activity underway, and could use that to direct the suggestion of existing products, existing trails, formulating new trails, searching for additional data sources, etc.

Possibly related to this line work is construction of a Web site where people could share their workflows, similar to Yahoo! Pipes.

Nirupama Bulusu is interest in exploring “participatory sensing” as part of RoboCMOP.

II.2.b Meeting indicators and metrics NSF instructions: Describe how the Center is doing with respect to the indicators/metrics listed above. Include any data that have been collected on the indicators/metrics.

A SATURN modeling system: Skill assessment and operational robustness of the SATURN modeling system, as reported electronically (via the CMOP web site) on a routine basis for forecasts and climate-scale simulation databases, and as reported in appropriate peer-reviewed publications for process-based simulations.

Skill assessment metrics have been developed, and are being implemented in SATURN/CORIE with appropriate automatic harvesting tools.

B SATURN long-term time-series: Quantity and quality of observational data collected at the SATURN fixed stations

Metrics and query protocols are being implemented, in coordination with NANOOS standardization efforts

C SATURN mobile-platform network: Quantity and quality of data collected by mobile platforms, and adequacy of that data to address the driving scientific hypothesis

Metrics and query protocols are being implemented, in coordination with NANOOS standardization efforts

D SATURN information system: Customer satisfaction, evaluated through annual surveys across all Center participants and selected external constituencies

A customer satisfaction survey will be conducted in June 2008

E Ecosystem dynamics, climate, and water use: Advancements in scientific understanding, as measured by peer reviewed papers, thesis, and conference presentations

Specific criteria to define eligible publications have not yet been developed.

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F Microbial communities in productive coastal margins: Advancements in scientific understanding, as measured by peer reviewed papers, thesis, and conference presentations

Specific criteria to define eligible publications have not yet been developed.

G Modeling and simulation: Advancements in algorithmic developments, as measured by improvements in operational performance of SATURN and/or in the quality of process-oriented simulations

Will result naturally from A.

H OSSE: Evaluation of adequacy of recommended sampling strategies, as measured by success in obtaining the data necessary to test science-driven hypothesis

Specific criteria to define success have not yet been developed.

I Smart platforms: Operational performance of the platforms and supporting technologies, and – where applicable –scientific value of SATURN observations conducted in these platforms. Where applicable, number of patents

To be determined, once we acquire experience with using smart platforms.

J In situ sensors: Number of new variables and processes that can be observed, and quality of the observations. Where applicable, number of patents.

Will result naturally from B and C.

K Information and visualization: Degree to which new technologies are adopted by the SATURN information system, and, for the adopted technologies, customer satisfaction based on user surveys (see D)

Will be a part of the survey in D.

L Broad impacts of research: List of participating non-academic groups, students, teachers and trainees

See Educational section.

II.2.c Research plans NSF instructions: Describe your research plans for the next reporting period with attention to any major upcoming changes in research direction or level of activity. Also, list plans for developing new research partnerships, if any, for the next reporting period.

In the next reporting period we anticipate a continuation of the efforts described above, with particular attention to (and the benefits of):

• Continued integration across disciplines: We believe that conditions now exist (both through RIG-fostered collaborations; and technically, through substantially increased SATURN data streams) to place advances in understanding of microbial communities in a much more formal context of physical and ecological variability.

• CMOP cruises: We expect to change the emphasis of UNOLS-based cruises from exploratory to hypothesis driven, as we seek to understand and characterize the role of physical, ecological and microbial river-to-ocean gradients (progressively more formally expressed as “environmental sentinels”). This change might imply a re-alignment of the times of the cruises, and perhaps a smaller overall duration of the cruises.

• Environmental sentinels: We expect to develop an evolving set of multi-disciplinary sentinels, able to characterize variability and change in ecosystem condition and health. These sentinels will progressively become a cornerstone of our research, as they are essential for the vision of anticipatory oceanography.

• SATURN observations: We are moving aggressively towards an observation network with characteristics (from multi-disciplinary and increasingly profiling stations to UUVs and gliders) highly conducive to address the CMOP grand challenges.

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• Modeling: We will continue and expand the emerging integration of modeling efforts across the OHSU and OSU campuses.

• Contamination and public health pathways: A number of investigators are increasingly interested in investigating important contamination and public health pathways in coastal margins, an area that ties to our ultimate vision of the environmental as an integral part of global health issues. A sizeable increase in activity in this area is, however, not expected until Y4 or even Y5.

• Research-enabled education: We anticipate the sustained growth of the number of CMOP investigators involved in the CMOP education mission.

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