Ocean Sciences [OS]

OS16B HCC:HALL 3 Monday

Assessing the Productivity of Large Marine Ecosystems Posters

Presiding:M S Berman, National Marine Fisheries Service; B Mueller-Karulis, Institute of Aquatic Ecology, University of Latvia; M O'Toole, Benguela Current Large Marine Ecosystem Programme

OS16B-01

Measuring the Productivity of Large Marine Ecosystems, an Introduction

* Berman, M S (mark.berman@noaa.gov) , National Marine Fisheries Service, 28 Tarzwell Drive, Narragansett, RI 02882 United States

The 64 Large Marine Ecosystems defined by the IOC are areas of the world's oceans adjacent to continental shelves, characterized by distinct bathymetry, hydrography and ecology. LMEs generally encompass areas greater than 200,000 square kilometers, and together account for up to 95% of the world's annual marine fisheries catches. They have been designated as areas for the introduction of ecosystem-based assessment and management practices. NOAA has developed a 5 module strategy for the assessment and management of LMEs including indicator suites for pollution and ecosystem health, fish and fisheries, governance, socioeconomic factors, and ecosystem productivity. The productivity module focuses of the lower trophic levels of the ecosystem, and, because of the large spatial areas involved, presents special challenges. Traditional methods of assessing plankton and primary productivity, are too time consuming and expensive to be used efficiently in LMEs. Narragansett Bay, Rhode Island, has been the site of the development of a prototype system for assessing the productivity of LME's. The system relies on a series of transects made with an undulating oceanographic recorder fitted with CTD-Fluorometer, Optical Plankton Counter, Autonomous Plankton Recorder, Dissolved Oxygen Electrode, and Fast Repetition Rate Fluorometer. Data from these transects is combined with that from ocean observing satellites or continuously monitoring buoys for a detailed view of the productivity of the system. We believe that this prototype can be scaled up and adapted to fit the needs of LME's around the world.

OS16B-02

Gross Oxygen Production Measurements For Satellite Productivity

* Vedula, V (sarma@hyarc.nagoya-u.ac.jp) , Hydrospheric Atmospheric Research Center, Nagoya University, Furo-Cho, Chikusa-ku, Nagoya, 4648601 Japan
Abe, O (osamu.abe@nagoya-u.jp) , Graduate School of Environmental Studies, Nagoya University, Furo-Cho, Chikusa-ku, Nagoya, 4648601 Japan
Hinuma, A (s030116d@mbox.nagoya-u.ac.jp) , Hydrospheric Atmospheric Research Center, Nagoya University, Furo-Cho, Chikusa-ku, Nagoya, 4648601 Japan
Saino, T (tsaino@hyarc.nagoya-u.ac.jp) , Hydrospheric Atmospheric Research Center, Nagoya University, Furo-Cho, Chikusa-ku, Nagoya, 4648601 Japan

Gross oxygen production (GOP) is a fundamental but poorly known characteristic of planktonic marine ecosystem especially with reference to climate change. The application of remote sensing ocean color improved our understanding on net primary production, however its application mainly depend on the sea truth data, which is hard to obtain and suffer from several problems such as bottle effect, tracer recycling etc. Estimation of in situ GOP by flurometric techniques are found to be promising tool in the biological oceanography, which not only gives GOP but also physiological parameters such as photosystem II (PSII), Fv/Fm ratios etc. In an effort to understand short-term to seasonal variations in GOP in the photic zone, the high resolution vertical profiles of GOP were measured at 2 h intervals using Fast Repetition Rate Flurometer (FRRF) at the time-series station S3 in the Sagami Bay, northwestern Pacific during summer 2003 and 2004. Simultaneously we have also measured GOP using 17$\Delta$ anomaly of dissolved O2, which represents the average O2 produced in the mixed layer over a residence time of oxygen. Therefore, occurrence of short-term blooms due to local physical forcing can be deciphered by this method. Since this method involves no incubation, the effects of bottle, heterogeneity of sample, incubation time, and tracer recycling can be avoided. In addition to this, both FRRF and 17$\Delta$ anomaly methods measure O2 produced at the PSII, these two methods are comparable and the accuracy of the GOP measured by the FRRF can be evaluated. Daily integrated production by 17$\Delta$ anomaly, and FRRF showed good agreement during entire study period within $\<$$\pm$10$%$. This suggests that accurate GOP profiles at higher temporal and vertical resolutions can be obtained using FRRF technique that enable us to construct new generation productivity algorithm and can be calibrated using 17$\Delta$ anomaly technique. Based on O2/Ar ratios, in combination with 17$\Delta$ anomaly, in the mixed layer, it is possible to calculate net oxygen production and, respiration rates. Therefore, major metabolic processes can be modeled using both FRRF and 17$\Delta$ anomaly measurements.

OS16B-03

Separating Aggregates/Fragile Particles From Zooplankton Using Transparency Measurements From Camera Imaging and Optical Plankton Counters.

* Herman, A W (hermana@mar.dfo-mpo.gc.ca) , Bedford Institute of Oceanography, 1 Challenger Dr., Dartmouth, NS B2Y 4A2 Canada
Checkley, D (dcheckley@ucsd.edu) , Scripps Institution of Oceanography, 9500 Gilman Dr, La Jolla, CA 92093 United States
Powell, J (jpowell@ucsd.edu) , Scripps Institution of Oceanography, 9500 Gilman Dr, La Jolla, CA 92093 United States
Jackson, G (gjackson@tamu.edu) , Texas A&M University, Dept. Of Oceanography, College Station, TX 77843 United States

Both taxonomic-based and size-based studies of plankton are dependent on our metrics or sampling methodology. With newer sampling technologies, our ability to distinguish aggregates and other `fragile particles' (FPs) has become crucial. Production studies require the characterization of zooplankton separately while inputs to studies of biomass balance, grazing, and recycling, can require both zooplankton and aggregates/FPs. Plankton nets cause disintegration of most aggregates or FPs while optical measurements can sample both classes. We report here on a study in California coastal waters (CalCOFI region) containing high aggregate/FP concentrations and compare data from digital camera images and from a Laser-Optical Plankton Counter (LOPC) taken simultaneously. Both camera and LOPC data were analyzed using size-based spectra, ie. normalized biomass size spectra - NBSS, representing a broad size range of the plankton community while measured particle transparencies were used to calculate the NBSS from camera & LOPC. By combining transparency measurements with optical cross-sectional areas, we can recalculate the `effective or conserved' particle esd (equivalent-spherical diameter). Such analytical methods can provide us with the ability to separate and taxonomically categorize FPs and zooplankton measured by the LOPC and can also provide us with rapid assessment capability within the context of monitoring programs.

OS16B-04

Functional Relationships Between Physical Environment, Macroalgal Assemblages, Primary Productivity and Macroinvertebrate Grazing in the Northern Baltic Sea

* Kotta, J (jonne@sea.ee) , Estonian Marine Institute, University of Tartu, M\"{a}ealuse 10a, Tallinn, 12618 Estonia
Paalme, T (tiina.paalme@ut.ee) , Estonian Marine Institute, University of Tartu, M\"{a}ealuse 10a, Tallinn, 12618 Estonia
Orav-Kotta, H (helen.orav@sea.ee) , Estonian Marine Institute, University of Tartu, M\"{a}ealuse 10a, Tallinn, 12618 Estonia
Moller, T (tiia.moller@ut.ee) , Estonian Marine Institute, University of Tartu, M\"{a}ealuse 10a, Tallinn, 12618 Estonia
Martin, G (gerog.martin@sea.ee) , Estonian Marine Institute, University of Tartu, M\"{a}ealuse 10a, Tallinn, 12618 Estonia

The structure of phytobenthic assemblages and invertebrate grazing pressure were related to the number of abiotic (temperature, salinity, nutrient concentration) and biotic variables (algal productivity, invertebrate feeding guilds) in different basins of the northern Baltic Sea. In general the studied coastal areas had dense macrophyte beds. The structure of phytobenthic assemblages was explained by sediment characteristics and concentration of nutrients in seawater. The biomass of annual algae rose with increasing concentration of nutrients. The relationships between different feeding guilds of macroinvertebrates and macroalgae were diverse and function specific. In some cases the annual algae supported the diverse community of herbivores while in other instances the relationship was opposite. The macroalgae accounted for the majority of total primary production in the studied basins. The net diurnal primary production of macroalgae increased with light intensity and leveled out at high light levels. Compared to perennial species the net productivity of annual algae was significantly higher. The grazing on perennial algae depended on the availability of annual algae. Annual algae were preferred over perennial algae. Low photosynthetic activity of algae coincided with high invertebrate grazing. Thus, unlike in many other coastal seas, bottom-up effects primarily control the macroalgal productivity and benthic grazing pressure is negligible in the northern Baltic Sea. As young and photosynthetically active algae are avoided by grazers then the majority of macrophyte production is not consumed and channeled into the detritus food chain. This may explain why the Baltic Sea ecosystem is very sensitive to eutrophication induced macroalgal blooms.

OS16B-05

Population Structure and Dynamics of {\it Neomysis Integer} in the Gulf of Riga, Northeastern Baltic Sea

* Kotta, I (ilmar.kotta@sea.ee) , Estonian Marine Institute, University of Tartu, M\"{a}ealuse 10a, Tallinn, 12618 Estonia
Kotta, J (jonne@sea.ee) , Estonian Marine Institute, University of Tartu, M\"{a}ealuse 10a, Tallinn, 12618 Estonia

Knowledge about the life history of key species is the first step towards reliable estimates of secondary production and understanding the functioning of the aquatic ecosystem in general. Life history characteristics of a species can vary considerably between different sites; hence, knowledge of the local population structure and life cycle is a prerequisite for experimental work and ecosystem modeling. {\it Neomysis integer} is the keystone mysid species in the Baltic Sea area. Based on the multiannual surveys in the Gulf of Riga, the density of overwintering generations of {\it N. integer} was low in winter and spring. The increase in the biomass of the cohorts was due to the growth in length. {\it N. integer} bred continuously through the summer and had two recruitment peaks. The mortality of the species abruptly increased since September due to fish predation. Zooplankton abundance and biomass, and severity of winter were the best predictors of mysids' abundance and biomass. The population dynamics of mysids showed low and relatively stable abundances from the early 1970s to the late 1980s and high and fluctuating abundances onwards. Since 1991 the density of mysids declined with concurrent invasion of a predatory cladoceran {\it Cercopagis pengoi}. Strong predation pressure of {\it C. pengoi} on other zooplankton taxa has partly released phytoplankton from the zooplankton grazing and resulted in the food limitation of mysids.

OS16B-06

Assessing the Zooplankton Productivity in a Practical and Cost Effective Way

* Postel, L (lutz.postel@io-warnemuende.de)

All the recommended methods of zooplankton production measurements have their special restrictions. There are time consuming incubations for determining the physiological balance for example between assimilation and respiration rates, the temporal change of body mass, the rate of egg production, the generation times, etc. Every method includes a certain amount of artefacts. Additionally, some are restricted to special organism groups, like copepods. Biochemical methods determine the relative utilisation of substrate, apply substrate saturated conditions or/and are limited to chitinous organisms. Zooplankton production G primarily (exponentially) rely on body mass W and secondarily (linearly) on food concentration and temperature as described by G = a W(exp)b. This predominance of body mass seems to allow using allometric models which are valid over a certain temperature range and scarcely dependent on food concentration during the vegetation period in shelf sea areas, in Large Marine Ecosystems. This approach needs the average body size to be determined by biomass concentration and abundance of size fractionated samples only which is a practical and cost effective way. Examples for the Baltic Sea, a Norwegian Fjord and the Benguela region will be presented.

OS16B-07

Assessment of Narragansett Bay Phytoplankton by Fast Repetition Rate Fluorescence

* Melrose, D C (melrose@gso.uri.edu) , University of Rhode Island, South Ferry Rd, Narragansett, RI 02882 United States
Berman, M S (mberman@mola.na.nmfs.gov) , NOAA, 28 Tarzwell Drive, Narragansett, RI 02882 United States
O'Reilly, J E (Jay.O'Reilly@noaa.gov) , NOAA, 28 Tarzwell Drive, Narragansett, RI 02882 United States

Phytoplankton photosynthesis in Narragansett Bay was studied using fast repetition rate fluorescence (FRRF) between 1998 and 2004. The FRRF-method provides a tool for quickly assessing the health and photosynthetic capacity of phytoplankton in situ. During this study, an FRRF instrument was deployed in a towed, undulating oceanographic sampling platform. The coupling of the FRRF-method with a towed sampler permits the assessment of photosynthesis over large spatial areas more quickly, and with finer spatial resolution than could be accomplished using traditional techniques such as radiocarbon uptake, making it an excellent tool for studying large marine ecosystems. The estimated maximum quantum yield (Fv/Fm ratio), and light absorption cross-section of photosystem II were both observed in Narragansett Bay using the FRRF-method. Typically, the variation in these parameters between regions of Narragansett Bay and between seasons was relatively small. The maximum quantum yield remained high at most times (Fv/Fm ratio near or above 0.5), indicating the phytoplankton in Narragansett Bay are usually not growth-stressed even during periods when biomass is low. This lack of stress indicates that the cells were not experiencing nutrient limitation in most cases and suggests that primary productivity in Narragansett Bay is limited by factors other than nutrients at most times. This is not surprising as Narragansett Bay receives a steady supply of nutrients from wastewater treatment facilities and runoff. There were some exceptions where the estimated maximum quantum yield indicated growth-stress in small sections of the Bay and so instances of localized nutrient stress cannot be ruled out. These were uncommon events and were not observed in the majority of cruises.

OS16B-08

Phytoplankton biomass and productivity in the Baltic Sea derived from the ocean color data record

* Melin, F (frederic.melin@jrc.it) , Joint Research Centre E.C. - IES, TP 272 - via Fermi, ISPRA, VA 21020 Italy

The temporal variability of phytoplankton biomass and primary production is studied using an 8-year time series derived from remote sensing. Phytoplankton biomass is represented by the concentration of chlorophyll a obtained from SeaWiFS and MODIS imagery from September 1997 to August 2005. Primary production is computed with a depth- and wavelength-resolved photosynthesis model. In practice, the field of spectral direct and diffuse irradiance is propagated down the water column using a bio-optical model and the carbon fixation at each depth level is calculated on the basis of light-photosynthesis curves. The photosynthetic parameters, that are chlorophyll normalized initial slope and photosynthetic rate at light saturation, are fixed according to values published for the basin. The average surface concentration of chlorophyll a from the satellite record is approximately 4 mg.m-3. In its standard version, the primary production model yields an average productivity of 0.8 gC.m-2.d-1, peaking in July at approximately 2 gC.m-2.d-1, at the time of highest solar irradiance (40 E.m-2.d-1). The most productive summers are found in 1999, 2001 and 2002; however, the interannual variations are not pronounced. The fraction of carbon fixation taking place in the upper layer, defined by the 10% light level, is high and 85% on average. Moreover, a photon budget performed on the euphotic zone indicates that the fraction of light absorbed by phytoplankton in the water column is 30% of total absorption; this fraction, very high with respect to other basins, is likely affected by the assumptions underlying the bio-optical model. A sensitivity analysis with respect to the phytoplankton vertical structure and the bio-optical model parameters is presented. The results are described for the different regions of the basin and compared with available in situ estimates.

OS16B-09

Phytoplankton Dynamics in the Baltic Sea: Ship of Opportunity Approach

* Seppala, J (jukka.seppala@fimr.fi) , Finnish Institute of Marine Research, Erik Palmenin aukio 1, P.O Box 2, Helsinki, 00561 Finland
Kaitala, S (seppo.kaitala@fimr.fi) , Finnish Institute of Marine Research, Erik Palmenin aukio 1, P.O Box 2, Helsinki, 00561 Finland
Raateoja, M (mika.raateoja@fimr.fi) , Finnish Institute of Marine Research, Erik Palmenin aukio 1, P.O Box 2, Helsinki, 00561 Finland
Ylostalo, P (pasi.ylostalo@fimr.fi) , Finnish Institute of Marine Research, Erik Palmenin aukio 1, P.O Box 2, Helsinki, 00561 Finland
Maunula, P (petri.maunula@fimr.fi) , Finnish Institute of Marine Research, Erik Palmenin aukio 1, P.O Box 2, Helsinki, 00561 Finland

The Alg@line project, automated sampling of pelagic waters of the Baltic Sea using ship-of-opportunity approach, started in 1993. Nowadays Alg@line is a joint multinational project including several research institutes and shipping companies. Automated online analyzers and sampling devises are onboard nine ships, either merchant vessels or the ships of the Finnish coastal guard. These provide annually approx. 2 million flow through observations of in vivo chlorophyll a, salinity and temperature. Recently we have tested new sensors for online monitoring of the Baltic Sea. Currently, online measurements of turbidity and sampling for coloured dissolved organic matter analyses are carried out. Operational detection of phycocyanin fluorescence started in 2005. This pigment is specific for filamentous cyanobacteria, and was used to reveal the extent of summer bloom of these species. Phytoplankton photophysiology during spring bloom was studied using Fast Repetition Rate fluorometry. Here these methods are critically examined, as based on detailed field and laboratory studies. Finally, we show that these methods, combined with ecosystem modelling and remote sensing, provide more comprehensive information to assess the state of the phytoplankton in the Baltic Sea.

http://www.balticseaportal.fi

OS16B-10

Instantaneous Estimates of Copepod Community Growth and Development Rates via Measurements of Chitobiase Decay Rates

* Sastri, A R (asastri@uvic.ca) , University of Victoria, Biology Department, Victoria, BC V8W 3N5 Canada
Dower, J F (dower@uvic.ca) , University of Victoria, Biology Department, Victoria, BC V8W 3N5 Canada

Biological oceanographers have long sought a method for routinely estimating development and growth rates of marine copepods. Due to the logistical constraints of conventional methodologies, however, our understanding of how naupliar and copepodite production rates vary remain limited to a very few species single species and environments. In order to examine spatiotemporal variation of growth and development rates at the community level we have developed a field application of an instantaneous estimate of molting rate based on the rate of production of the crustacean molting enzyme, chitobiase. This approach is attractive because it is rapid, simple, and can be applied shipboard at high spatial and temporal resolution. Critical to this approach is a single body size descriptor of chitobiase that can be applied across species. Application of this relationship to single size frequency distributions and estimates of the rate of chitobiase decay in the water column yield mean community molting rates that are in good agreement with both conventional and literature based estimates. Here we address spatio-temporal variation in community wide growth and development rates from the Strait of Georgia and along onshore-offshore transects from the west coast of Vancouver Island and the Gulf of Alaska.

OS16B-11

Use of Ferrybox Measurements for the Baltic Sea Environment Assessment

* Lips, I (inga@sea.ee) , Marine Systems Institute, Tallinn Technical University, Akadeemia tee 21b, Tallinn, 12618 Estonia
Lips, U (urmas.lips@emara.ee) , Estonian Maritime Academy, Mustakivi 25, Tallinn, 13912 Estonia
Fleming, V (vivi.fleming@fimr.fi) , Finnish Institute of Marine Research, PO Box 2, Helsinki, FI-00561 Finland
Kaitala, S (seppo.kaitala@fimr.fi) , Finnish Institute of Marine Research, PO Box 2, Helsinki, FI-00561 Finland

The spatially heterogeneous character of aquatic life and rapid changes in pelagic communities make it difficult to assess the status of the marine environment using traditional monitoring methods. In order to distinguish between human induced and natural changes in the ecosystem the environmental parameters and the factors affecting them need to be monitored at a wide range of temporal and spatial scales. The capacity of any single monitoring method or strategy should not be overestimated. Instead, different methods complement each other. In the Baltic Sea high frequency recordings of phytoplankton biomass and related environmental parameters (temperature, salinity, nutrients, chlorophyll a) in the near surface layer (4-5m) have been conducted with unattended water sampling onboard several commercial ferries over the last 12 years. An index for estimating the annual phytoplankton spring bloom intensity in the Baltic Sea based on automated fluorescence measurements and chlorophyll a analyses has been developed. The Ferrybox measurements allow us to observe the rapid changes in the ecosystem from meso- to basin-wide scale with high temporal and spatial frequency at relatively low cost. The combination of high frequency automated sampling onboard merchant ships with satellite imagery, traditional sampling and meteorological information has increased the understanding of ecological processes in the Baltic Sea.