Oct 2004: Data Summary  Image

Apr 2001: Full Proposal

Apr 2002: Fraser River Plume Image

Oct 2002: Poster Produced for EPOC and PICES meetings 2002

Oct 2002: The Great Flurometer Scaling mystery

Feb 2004: Ocean Sciences Poster: Revisiting the timing of the spring bloom in the SoG

Feb 2004: Ocean Sciences Poster: Assessing surface water properties and chlorophyll concentrations with ferry-based instruments

Summary Figure of Data to October 2004

Full Proposal:

The Strait of Georgia is a highly productive, semi-enclosed, marine ecosystem located between Vancouver Island and mainland British Columbia (Fig. 1). In recent years the Strait has undergone considerable changes, many of which are tied to the rapid population growth in the lower mainland of British Columbia (by nearly 13% between 1991-1996). These changes have included increased usage of the Strait for both commercial (e.g. fishing and shipping) and recreational purposes (e.g. boating and sport-fishing), reduced air-quality, as well as increases in sewage and other effluent from the greater Vancouver region. There have also been significant changes in the marine ecosystem of the Strait of Georgia. Surface water temperatures have warmed by about 1ºC since the 1960's [2]. Certain fish species (e.g. lingcod and certain rockfish) have been fished virtually to local extinction. Increased occurrences of red tides and high fecal coliform counts have led to more frequent shellfish harvesting closures and raised concerns in the aquaculture industry. Plankton dynamics have also changed, with key species now arriving at least a month earlier than they did historically. However, it was the highly visible collapse of the Strait of Georgia salmon stocks in the late 1990's, in what had been one of the most productive salmon nursery grounds in the NE Pacific, that finally served as the catalyst to raise public awareness of the "State of the Strait". In response, several scientific and community-based initiatives have been launched. The largest of these projects, the Georgia Basin Ecosystem Initiative, involves a partnership between several provincial and federal agencies to develop action plans to improve air quality, to reduce water pollution, to protect habitat and coastal biodiversity, and to support community-based environmental initiatives within the Georgia Basin. Fisheries and Oceans Canada (DFO) have also recently initiated a new program (led by Richard Thomson at IOS) that aims to determine how physical and biological processes in the SoG are linked to processes in the adjoining Strait of Juan de Fuca and the continental shelf on the west coast of Vancouver Island.

To date there has been little recognition of the role played by natural physical variability in regulating biological production in the Strait of Georgia (SoG hereafter). However, a growing body of evidence suggests that changes in the productivity and structure of this and other marine ecosystems are likely due to interannual variability in the linkages between physical and biological processes [1, 16, 17, 33, 34, 35]. Moreover, it appears that these linkages may have recently been altered by climate change. Climate affects the physical oceanography of the SoG through a number of processes. ENSO oscillations and the North Pacific Decadal oscillation can influence precipitation and air temperature (and therefore the Fraser River outflow and timing) [1], poleward and equatorward winds off the West Coast of Vancouver Island (and therefore the strength of upwelling and the density/nutrient of deep flow through Juan de Fuca [11]. Large scale climate oscillations also influence storm tracks and the number and strength of storms in a particular region [25]. The physical oceanography of the SoG affects the biology primarily through nutrient availability, light availability, temperature effects on physiological processes and temperature effects on predator migration. Light availability to the phytoplankton is determined by the amount of light reaching the surface of the water (determined by time of year and cloud amounts), the depth of the mixed layer and clarity of the water. Nutrient availability is determined by large scale nutrient fluxes into and out of the estuary and the mixing of nutrients from deeper waters into the mixed layer.

Biological-physical coupling has been the focus of several high profile national and international oceanographic projects (funded in part by NSERC) including OPEN, GLOBEC, JGOFS and the newly funded SOLAS. However, it remains unclear whether observed changes in ecosystem structure and productivity are driven primarily by top-down or bottom-up control. In this study we will couple an innovative field program with a series of models to determine the dominant physical mechanisms underlying ecosystem structure. We will use the SoG as our laboratory. In many respects the SoG is the ideal environment in which to test the importance of "bottom-up" effects. Effectively a semi-enclosed sea, the SoG has only limited exchange with the open ocean via its southern end (Fig. 1) which is connected to the Strait of Juan de Fuca (SJF hereafter). The net effect of this unique geographic setting is that advective effects in the SoG are easy to quantify, thereby making it much easier sample and model. Our request is also quite timely, for two reasons. First, the new DFO program mentioned was specifically designed to integrate and collaborate with our proposed research. (Letters of support attached). Second, there are signs that a major change in the SoG during 2000 (resulting in reduced mortality rates of young coho salmon) may have been caused by a particular combination of Fraser outflow and wind patterns which created ideal conditions for strong primary and secondary productivity (R.J. Beamish, DFO, pers. comm.) If, as some suggest, we are currently on the cusp of entering a new regime then we are in a unique position to follow this change as it develops.

THE PRODUCT: Our aim is to develop a mechanistic understanding of the key links between physics and biology in the SoG. This will enable us to generate a series of "heuristic rules" linking variable physical oceanographic conditions and biological oceanographic responses in the SoG. Our hope is that a rule-based system of the sort proposed here can then be used by DFO to evaluate the "oceanographic state" of the Strait for a given year. This level of mechanistic knowledge of the links between biology and physics is essential to implement an "ecosystem approach" to the management of our renewable marine resources. Currently, there is no set of such rules because no single environmental variable can explain the observed variability. We envison the rules we propose to develop being along the lines of: Strong winds, followed by a calm period and relatively strong outflow will enhance the early summer primary productivity due to diatoms, thereby producing a good "year". Similar rules will outline the conditions leading to "average" and "poor" years. To build these heuristic linkages we need to address four key issues: the physical nutrient sources and sinks, the timing and magnitude of the spring bloom, the summer primary productivity (and relative species composition), and the timing and productivity of Neocalanus plumchrus, the dominant copepod in the SoG. Each of these processes will be affected by tides, winds and Fraser River input. Interannual variation in the latter two will be partly determined by large scale climatic variations.

Physical Oceanography: The SoG is a semi-enclosed marine sea with significant fresh water input and strong stratification. Stratification is especially strong near the Fraser River in a brackish plume, mixed by both estuarine entrainment and surface wind mixing. The plume is advected by winds and tides and its size varies by season with the volume flux of the Fraser River. Freshet usually starts in April and peaks in late June or early July with an approximately tenfold increase in volume flux. There is considerable interannual variation [9,15]. Winds in the SoG are generally lighter than on the outer coast but strong storm winds do occur. As the strong winds are storm forced there is considerable interannual variability. Most exchange with the open ocean occurs via the SJF, and the overall flow can be considered a classical two-layer estuarine exchange. Both the outgoing upper brackish waters and the incoming deep ocean waters are significantly modified by tidal mixing, both in the SJF and the islands at its eastern end [15, 23] but layer transports are 5-20 times larger than Fraser input.
Nutrients and Primary Production: The primary source of nutrients in the SoG and SJF system is the deep estuarine inflow; anthropogenic influences are considered relatively minor in comparison [18]. The estuarine inflow traverses the continental shelf within the deep Juan de Fuca Canyon and hence has its source in oceanic waters well below the mixed layer. In consequence, observed nutrient concentrations are always relatively high, varying from approx 25 uM in winter to over 30 uM in summer [18]. Summer inflows are as high as 7000 tonnes N/day into SJF but much of this inflow is mixed upwards into outflowing surface waters and only a small fraction (perhaps 10-30%) actually enters the SoG [22]. Deep waters in the SoG are also high in nutrients. Surface waters, however, are often very low in nutrients during May-September [18].
Primary production in the SoG is believed to be limited by nitrogen [10]. The Strait is light-limited during winter due to low light levels and deeper mixed layers [10,17]. Winter SoG conditions are favourable to nanoflagellates [29]. The increased light and stability of the spring favour diatoms which usually bloom in succession (Thalassiosira spp. followed by Chaetoceros spp.). Comprehensive cruises in 1991 [32,33,34] showed qualitatively that wind events can delay the spring bloom. Stronger stratification in summer favours flagellates. However, wind events can cause mixing and nutrient injection into the surface layer. Summer blooms of various diatoms [27, 28] and dinoflagellate species [30] also occur.
Zooplankton: The mesozooplankton community of the SoG is similar to that of the oceanic NE Pacific and is dominated by the large calanoid copepod Neocalanus plumchrus (Neocalanus, hereafter) [7]. Other species (particularly E. bungii, Calanus marshellae, C. pacificus and Pseudocalanus minutus) may dominate to a lesser degree at other times [10]. Numerous other small copepod species also inhabit the surface waters over much of the year (e.g. Acartia spp., Centropages sp., Chiridus gracialis, Metridia spp., Microcalanus pusillus, Paracalanus parvus, Pseudocalanus spp.), however, the life history patterns of these species are not well known [10].

LOGISTICAL APPROACH: We will investigate the potential for bottom-up control in the SoG by combining: (1) a targeted field program, (2) retrospective analysis, and (3) coupled biological-physical modeling. Given the physical proximity of the lead PI's (Allen/Dower/Pawlowicz), all three will interact to attack each specific questions and the long term goal. Travel costs have been budgeted to enhance collaboration with Li and Denman.
Field Work (Dower, Pawlowicz, Harrison): Fieldwork will be used to (a) determine the nutrient flux into/out of the SoG, (b) monitor daily conditions within the SoG, and (c) obtain snapshots of key physical and biological parameters a different times of the year. In order to minimize costs for such an ambitious plan we propose a variety of innovative approaches. First, work in progress by Pawlowicz (NSERC-RG) should lead to a quantitative relationship between the estuarine circulation and the Fraser River flow. Continuous deep nutrient concentrations will be measured using a moored automated nitrate sampler, now available from several companies. A continuous record is desirable since deep inflows may "pulse'' with the spring/neap cycle. Near-surface samples of nitrates, silicates, and phosphates will be obtained during monthly surveys (see below). Second, daily monitoring of conditions over a large part of the SoG will be carried out using instrumented ferries (Fig. 1). In conjunction with J. Gower (IOS), T/S/ Fluorescence will be measured over all tracks, with nitrates measured over 1 path in the 2nd and 3rd years. Finally, we propose using the CCG Hovercraft Siyay (based in Vancouver) to sample at 8 stations throughout the SoG at roughly monthly intervals (for hydrography, phytoplankton, zooplankton and nutrients). Dower and Pawlowicz are already experimenting with this platform (NSERC-RG work). The Siyay is also logistically convenient with great flexibility in modifying sampling days as required for special occasions (or bad weather) and with a cruising speed of 80 km/h is able to cover the entire SoG.
Retrospective Analyses (Ingram, Pawlowicz, Allen): The SoG is at the doorstep of two oceanographic institutes and two major universities. Measurements have been made since the 1920 by various investigators for various regions. We will assemble the available historical physical and biological data and examine interannual variability to investigate the temporal links between climate, physics and biology in the SoG. Previous studies [24.5] have shown a positive (warmer) link between strong ENSO events and sea surface temperature along the B.C. coast. Extensive physical and chemical data, as well as sporadic biological data, are available at the DFO laboratories in British Columbia, UBC, UVIC, and the Marine Environmental Data Service. Station data for meteorological forcing and river discharge will also be obtained. Elsewhere [5.5], the importance of 10-15 year signals in atmospheric/ runoff forcing was found to alter the sea surface characteristics in the Gulf of St. Lawrence.
Modeling Approach (Allen, Dower, Denman, Walters): Several approaches currently are used to model biological/physical systems. A traditional approach (e.g. UB GLOBEC Georges Bank studies) is to couple a relatively simple NPZ-type biological model to a fully 3D physical model. Although this approach is attractive, in practice unknown or neglected factors make results difficult to interpret in anything other than general ways. Another approach is to design a relatively simple "box-model" to parameterize the physics (with a fair degree of tuning) which can be coupled to more detailed biological models [12, 16]. An approach often used in open-ocean studies, [eg 5], is to couple a simple biological model to a 1D mixed layer model. In this case it becomes computationally easier to examine seasonal and interannual changes, at the cost of tuning of the physical model to make it match available observations. Obviously, a desirable goal would be to develop a fully 3D physical model with complex biology. However, even were it possible to create such a model of the SoG at this time, it is clear that such models must be developed gradually, as the apex of a hierarchy of simple models from which fundamental understanding will flow. We will employ three complementary models. One will couple a vertical mixed layer model (KPP) to a six compartment lower tropic-layer model and a copepod life history model. The second will be a dynamic mass balance model (Ecosim) that will be used to explore the effects of bottom-up forcing on trophic interactions and population dynamics of fish species. The third model (developed by our DFO collaborator, M. Li) will use a full 3D physical model coupled to a simpler biological model.

THE RESEARCH TEAM: Understanding the biophysical coupling in the Strait of Georgia will require expertise in a number of disciplines. We have assembled a team with a broad and complementary skill set that brings together physicists and biologists, modelers and observationalists. Collaboration will be facilitated by our geographic proximity, as well as the fact that several of us have already worked together and/or have co-supervised students. Susan Allen (UBC) will have primary responsibility for the coupled 1D biophysical model. Allen is a physical oceanographer with experience in box-modeling coupled chemical-biological-physical processes [12]. She was a member of the Canada GLOBEC Steering Committee for 4 years and is one of Canada's representatives to PICES. John Dower (UBC) will have primary responsibility for the biological field measurements and the biology incorporated into the models. Dower has extensive experience in bio-physical coupling (including current-topography effects at seamounts, and turbulence effects on zooplankton and larval fish) and is involved in spatially-explicit modeling in coastal Newfoundland [24]. His group is currently studying diapause and vertical migratory behaviour of Neocalanus in the SoG. Rich Pawlowicz (UBC) will have primary responsibility for the physical and tracer measurements. He has led major research missions in Haro Strait and has focussed his recent research on the exchange and mixing processes in the Juan de Fuca, Haro Strait, Georgia Strait system. Currently he is completing fieldwork to determine the seasonal cycle of nutrient fluxes including source/sink terms in Juan de Fuca and Haro Strait. Grant Ingram, FRSC (UBC) is a physical oceanographer who has worked on field studies of river plumes, coastal circulation and mixing, and relationship between physical forcing and different components of the marine ecosystem in the St. Lawrence estuary, Gulf of St. Lawrence, and Hudson Bay. He was a principal investigator in the Canadian JGOFS program, the OPEN NCE program, and various NSERC strategic grants. Paul Harrison, FRSC (UBC) is an internationally recognized phytoplankton physiologist. He was a member of the Steering Committee for JGOFS Canada and is a lead-PI in SOLAS. Carl Walters, FRSC (UBC) is a world leader in the development of multi-species fisheries harvesting models and in fisheries conservation. He was recently named one of 10 "Guardians of the Oceans" by the Pew Charitable Trust. Ken Denman, FRSC (DFO/UVic) is an internationally recognized expert in coupled biological-physical models. He has systematically developed a 1D model for Ocean Station P including iron limitation. He played a key role in JGOFS Canada and GLOBEC Canada and was a member of the IGBP Global Climate Change Panel.

MANAGEMENT AND COLLABORATION: Overall management of the project will be shared by Allen, Dower and Pawlowicz with advice from Ingram. Pawlowicz and Dower will have responsibility for the field program. Allen and Denman will have primary direction of the modeling with input from Walters. Retrospective analysis will be directed by Ingram. Harrison will lead the analysis of nutrients and phytoplankton samples. Informal collaboration will be greatly facilitated by our geographical proximity and by our monthly cruises (travel money for visits to and from IOS is budgeted). In addition, to ensure collaboration occurs between the PI's, graduate students and the post-doc, we will hold a monthly informal seminar/meeting series at UBC. In December of each year, we will travel to IOS to give a scientific presentation followed by smaller group meetings to discuss and coordinate our projects.

Physical Nutrient Sources and Sinks: Conceptually, we envision the SoG as a bowl with only one major connection to the ocean (SJF). Work in progress investigating SJF using a tracer inverse technique [22, 23] will lead to estimates of transport and nutrient flux through SJF into the SoG in 2000, and produce source/sink terms for various parts of the SJF. Parameterizing transport as a function of river inflow, and measuring nutrient concentrations in this proposed work will allow us to (a) form budgets for the SoG (and hence estimate "new production'') (b) investigate interannual variability, and (c) provide advective flux terms necessary for the numerical modeling.
Spring Bloom Dynamics: The spring bloom timing is a function of stratification due to river input, mixing due to wind and grazing pressure due to Neocalanus [32]. What is the relative importance of these three factors? Given a certain combination, what will be the outcome? Ferry observations will give us the exact timing of the blooms and their distribution across SoG. In addition the surface salinity and temperature will give us an idea of stratification (location of the Fraser plume). Neocalanus timing will be based on observations (and preliminary analysis) from hovercraft observations. With 3 field seasons planned it is anticipated that various different situations will be observed using similar methodologies.
The 1D coupled model will be used to test the sensitivity to various wind, fresh water and Neocalanus timing scenarios. The model will be run Feb-Apr/May with initial conditions based on climatology for February. Five wind, five fresh water and five Neocalanus ontogenetic-timing scenarios will be combined to investigate the sensitivity on the entire parameter space. The computational simplicity of a 1D model will permit us to run the 125 scenarios multiple times, if necessary. Scenarios for our three observation years and 1988, 1992 and 1993 [35] will be compared to field observations.
There is sufficient data available to run the Ecosim model from 1950 to the present. When run in "hindcast mode" Ecosim can estimate the primary productivity that would have been required to produce the observed time-series of population dynamics at higher trophic levels. Since not all primary production is available to the food chain that leads to fish and other higher trophic levels, what this will really provide is an estimate of the "target" amount of diatom-based primary production that would have bee required in a given year. Thus, the Ecosim model will be used to test the "heuristic rules" that we generate using our 1D biological-physical coupled models. Given that we have access to historical data on Fraser outflow and winds, we should be able to see whether years that Ecosim suggests may have been "good" years are also years when physical conditions were such that our 1D biological-physical coupled model would have predicted high primary and secondary production.
Summer Productivity:
Summer productivity in the SoG is controlled by nutrient availability to the surface euphotic zone. Yin et al. (1997b) observed that summer productivity can be enhanced by wind mixing or increased Fraser River outflow. They also observed a shallow nutricline and postulated it was maintained by estuarine entrainment. Quantitatively how important is wind? What types of wind event are necessary to maintain production? Does the "windiness" of a summer determine the type (large diatom or small flagellates) of phytoplankton that dominates? Starting after the spring bloom (with a nutrient depleted mixed layer) we will use the 1D biological-physical model (without the full Neocalanus life history model) to investigate the sensitivity to rate parameters in the two phytoplankton classes. The biological model will have two phytoplankton classes; one representing phytoplankton >10um (diatoms) and one representing phytoplankton <10um. For reasonable physical and biological parameters we will determine if both summers with mainly diatom growth and summers dominated by smaller phytoplankton can exist. Because the actual time-dependence of the wind (i.e. storms, etc) is expected to be crucial, we will use actual wind data. Once again the ferry data will be important for comparison. Phytoplankton biomass (as Chla), nutrient concentrations and salinity/temperature (as proxy for stratification) will be used. Phytoplankton species will be identified from samples collected during the hovercraft surveys. We will use this data to constrain the biological parameters using optimization (the simplicity of the 1D model allows use of techniques like simulated annealing).
Neocalanus plumchrus Dynamics:
Although Neocalanus is a key food source for numerous fish species (notably several species of juvenile salmon), it remains unclear what factors control interannual variability in its biomass. The factors often cited as influencing copepod growth rates are temperature and food (either quality or quantity). However, given that Neocalanus is a strongly seasonal species (spending only about 100 days in the surface waters and the rest of the year at depth), it seems likely that its biomass during any given summer is determined largely by the conditions encountered by the population in the previous year.
The life history model that we will use was initially developed for the Neocalanus population in the open NE Pacific (OSP). However, Neocalanus behaviour in the SoG is different than at OSP; the overwintering period is longer in the SoG, the time spent in the surface layer is shorter, and the adults are larger than at OSP [21]. It has also been shown [2] that the ontogenetic timing of the Neocalanus population in the SoG has changed over the past 20 years (peak biomass now occurs one month earlier than the historical mean). Unfortunately the SoG Neocalanus population has received little attention in recent years, and so we will begin by initializing our life history model with historical data [7, 8]. We will update the model using the zooplankton data collected monthly from our the eight stations in our hovercraft surveys (using nets and an optical plankton counter), plus monthly data collected from a single site in the central SoG since 1999 by Dower. We will then use the life history model to explore to what extent changes in (i) spring temperature (ii) overwintering temperature and (iii) food quantity or quality in a given year affect the weight of overwintering females (which determines their fecundity). Dower's lab is currently modeling the effect of buoyancy on both the overwintering depth (of C5's) and the vertical ascent rates (of naupliar stages) of Neocalanus in the SoG.

The KPP Model: The KPP model [14] has been chosen as the mixed-layer model for the vertical 1D model. It is a non-local turbulent diffusion model consistent with Monin-Obukov similarity theory. The KPP model has been used in simulations of storms, diurnal cycles, and seasonal weather patterns at OSP [13, 14]. It compares favourably with observations and performs at least as well (in many cases better) than other boundary layer models. We have a version at UBC currently configured for Ocean Station P.
The Biological Model: This model will have six compartments (1) Phytoplankton <10um (2) Phytoplankton >10um (e.g. diatoms), (3) Microzooplankton (modeled after flagellates, aloricate ciliates, and dinoflagellates) (4) New nitrogen (nitrate and nitrite) (5) Regenerated nitrogen (ammonium and urea) and (6) Detritus (includes PON, DON and heterotrophic bacteria). The phytoplankton compartments will be partitioned so that the fraction of the biomass present as species >10 um in size will increase with increasing total biomass. Detritus maybe divided into several sub-compartments based on size and regeneration rate. All compartments in the model will be defined in units of nitrogen per cubic metre. Model fluxes will determine the flow of nitrogen between theses compartments and will be based on a suite of physiological processes: (1) Nutrient uptake (controlled by ambient concentrations and light) (2) Ingestion (by both micro and mesozooplankton) (3) Excretion (by both micro and mesozooplankton) (4) Egestion (by both micro and mesozooplankton) (5) Phytoplankton cell lysis (either auto- or viral lysis) (6) Zooplankton mortality (and grazing by mesozooplankton & unmodeled higher trophic predators) (7) Sinking losses and (8) Nutrient regeneration. We will use a similar model (developed by N. Jeffery and S. Allen at UBC for OSP, based on [5]) and adapt it to reflect conditions more characteristic of the SoG.
Copepod Life History Model:
A Neocalanus life cycle model has been developed at UBC. The model includes weight dependent growth and mortality, migration into and out of the upper ocean, molting between stages and a stage distributed population. The total population is divided into cohorts: cohorts share a common arrival time, maturity distribution and weight distribution. The maturity distribution is assumed Gaussian, and the mean and variance have prescribed evolutions based on field observations of stage durations, however temperature dependence will be included. For each day, maturity defines the fraction of each cohort in the mixed layer, in a given stage, and in diapause. Physiological processes, and thus stage biomass, molting weights, and grazing, depend on the mean weight of each cohort and other environmental cues such as predator and prey concentration and temperature. The model solves a first order coupled nonlinear differential equation for each mean cohort weight.
Ecosim Model:
Walters has begun developing an Ecosim model for the SoG. Ecosim is a dynamic simulation model which is an extension of Ecopath, a well-known dynamic mass balance model [31] used to examine trophic interactions and population dynamics due to either top-down (e.g. fishing or predator-prey interactions) or bottom-up effects (e.g. variability in primary production). The SoG Ecopath model contains 27 compartments, ranging from phytoplankton and detritus all the way up to apex predators such as large fish (e.g. salmon and hake) and marine mammals (e.g. seals and orcas). The Ecosim model is initialized using historical catch statistics, abundance indices and dietary studies, in combination with estimates of rate processes (e.g. growth and feeding rates) drawn from literature sources. The model can then be used to predict how higher trophic levels may be affected by changes in primary productivity or, as we propose here, to reconstruct the primary and secondary production necessary to have produced a given biomass configuration of higher trophic levels.

FIELD WORK DETAILS: The first component of our field work will make use of the Canadian Coast Guard's high-speed hovercraft, the Siyay, to conduct 2-day sampling trips monthly for the first two years of the project. Currently there is no regular program of oceanographic sampling in the SoG, and so these surveys will provide monthly snapshots of the vertical distribution of hydrographic, biological and chemical properties (Fig. 1). The second portion of our field work will involve instrumenting two of the BC Ferries that travel regularly between Tsawwassen and Nanaimo. Once established, it is envisioned that this automated sampling program will run over entire the life of this project, (and hopefully be continued in the future). Our ferry data will be supplemented by data from a similar instrument package already in use by Dr. Jim Gower (DFO) along the southern BC Ferries route through the Gulf Islands (Fig. 1). Whereas the hovercraft surveys will provide us with monthly snapshots of the 3D structure of the SoG, the ferry sampling program will provide high temporal resolution data about the near surface oceanographic conditions in the southern and central portions of the SoG. Parameters to be measured from the ferries will include temperature, salinity, nitrate and fluorescence.

REFERENCES: [1] Beamish et al. (1999) Can. J. Fish. Aquat. Sci. 56:506-515. [2] Bornhold (2000) M.Sc. Thesis, UBC. [5] Denman & Pena (1999) Deep-sea Res. II 46: 2877-2908. [5.5] Dery, F. (1992) M.Sc.Thesis, McGill Univ. [7] Fulton (1973) J. Fish. Res. Board Can. 30:811-815. [8] Gardner (1972) M.Sc. Thesis, Institute of Oceanography, UBC. [9]Griffin & LeBlond (1990) Est. Coastal Shelf Sci. 30: 275-297. [10] Harrison et al. (1983) Can. J. Fish. Aquat. Sci. 40: 1064-1094. [11] Hsieh et al (1995) Can. J. Fish. Aquat. Sci. 52: 325-334. [12] Ianson & Allen (submitted) Global. Biogeo. Cycles. [13] Large & Crawford (1995) J. Phys. Oceanogr. 25: 2831-2852. [14] Large et al. (1994) Rev. Geophys. 32: 363-403. [15] LeBlond (1983) Can. J. Fish. Aquat. Sci. 40: 1033-1063. [16] Li et al (1999) Atmos.-Ocean 37:1-19. [17] Li et al. (2000) Est. Coastal Shelf Sci. 50:467-488. [18] Mackas & Harrison (1997) Est. Coastal Shelf Sci. 44: 1-21. [21] Miller et al. (1984) Prog. Oceanog. 13:201-243. [22] Pawlowicz (in press) Est. Coastal Shelf. Sci. [23] Pawlowicz & Farmer (1998) J. Geophys. Res. 103: 30695-30711. [24] Pepin et al. (submitted) Fish. Oceanogr. [24.5] Robert, M. M.Sc. Thesis, McGill Univ. [25] Rogers (1997) J. Climate 10: 1635-1647. [27]Stockner et al. (1979) J. Fish. Res. Board Can. 36: 657-666. [28] Takahashi et al. (1977) Deep Sea Res. 24: 775-780. [29]] Takahashi et al. (1978) J. Exp. Mar. Biol. Ecol. 31: 283-301. [30] Taylor (1975) Environ. Lett. 9: 103-119. [31] Walters et al. (1997) Rev. Fish Biol. & Fisheries 7:139-172. [32] Yin et al. (1996) Mar. Ecol. Prog. Ser. 138: 255-263. [33]Yin et al. (1997a) Can. J. Fish. Aquat. Sci. 54: 1015-1024. [34] Yin et al. (1997b) Mar. Ecol. Prog. Ser. 161: 173-183. [35] Yin et al. (1997c) Can. J. Fish. Aquat. Sci. 54: 1985-1995.

SECTION 2 - TRAINING OF HIGHLY QUALIFIED PERSONNEL: We will train at least ten highly qualified personnel during the four years of this project (2 postdocs, 1 technician, and 7 grad students). Besides those students funded directly by this proposal, many other students in the Department of Earth and Ocean Sciences will benefit from interactions with the multidisciplinary team we are assembling. Five MSc students and two PhD students will be partially funded through this project. Initial plans suggest the following topics would be appropriate, but this may change depending on the students available :
(1) MSc: Interannual variability in Nutrient fluxes and the input into SoG (with Pawlowicz)
(2) PhD: 3D model of the Strait of Georgia (with Pawlowicz & Li)
(3) MSc: Short and long term variability of physical forcing in the Strait of Georgia and its relationship to primary production (with Ingram)
(4) MSc: Physical determination of size-structure of summer phytoplankton community (with Allen, Denman & Harrison)
(5) PhD: Sensitivity of Neocalanus plumchrus biomass and timing to interannual variability in temperature & food availability (with Dower & Allen)
(6) MSc: Impact of El-Nino events on surface temperature and salinity, and its relationship to primary productivity in SoG (Ingram & Dower)
(7) MSc: Linking top-down and bottom-up models in the Strait of Georgia (Dower & Walters)

Students will gain a thorough background in their main field of study (biological or physical oceanography) in addtion to developing a broadly based oceanographic skill set (e.g. field observations and interpretation or modeling and interpretation). Each will also gain a understanding of the other field and the other skill set. Belonging to a large project will enable the students to meet (and have on their supervisor committee) a cross-section of oceanographers. Our monthly meetings will also ensure that they learn about and collaborate with the other scientists and students. These students will be highly trained specialists and be conversant with the language and tools of a broad field; the emerging hot topic of biological-physical coupling.
Two postdoctoral fellows will (sequentially) oversee the modeling effort (i.e. two years each). These young scientists will be trained in the detailed science of the other field (they will likely be either physicists or biologists), in coordinating the efforts of a number of students, in mentoring and leadership, in choosing topics for scientific papers and focusing research towards "the big questions" and in grantsmanship. Our plan is that these scientists will leave our group ready to accept the challenges of an Assistant Professor or a Research Scientist position.
We will also partially fund one technical person to oversee and participate in the monthly hovercraft cruise program. This position will probably go to a recent Masters graduate, who will receive additional training in field techniques, field organization, leadership and mentoring (as they aid the students on the cruises), and scientific liaison.
Of course the other beneficiaries of a large multidisciplinary, multi-skill project of this sort will be the PI's. Given the breadth of the proposed research we look forward to learning from each other, and broadening our own knowledge and skill sets.

Our primary collaborator and partner is Fisheries and Oceans Canada, and in particular their Ocean Science and Productivity Division (Head: Robin Brown). Our proposal was designed in concert with their DFO Strategic Proposal: "Co-variability of Coastal Marine Ecosystems: Determining the Responses to Environmental Stress and Change within the Interconnected Basins of Southwestern British Columbia". They see our proposal as integral (Allen, Dower and Harrison are named as primary collaborators in their proposal). We will provide the research component into the biological-physical coupling in the Strait of Georgia. Their proposal was submitted in December 2000 and has been funded. Specifically we plan to collaborate with DFO scientists Angelica Pena, Diane Masson, Richard Thomson, David Mackas, Richard Beamish, Jim Gower and Ming Li. In addition to comparing model results (they are modeling the west cast of Vancouver Island while we are modeling the SoG) we have made plans to co-ordinate our SoG sampling plans to supplement each others work, but also to prevent unnecessary (and costly) duplication of effort. Our secondary collaborator is Parks Canada. Parks Canada is working toward the creation of a marine park in the Southern Gulf Islands. Understanding the state of the marine ecosystem in the SoG will be integral to monitoring the biological health of this Park. We will share our modeling results as well as our field data from the region with Tom Tomascik and Cliff Robinson, who will be our direct Parks Canada contacts (Letter of support attached).
Details of collaboration with Fisheries & Oceans Canada:

Angelica Pena
is assembling a bio-physical lower trophic level model for the La Perouse region of the West Coast of Vancouver Island (WCVI). We (Denman and Allen) plan to actively exchange ideas on the biological and physical components of our models. In Year 3, both groups will have determined the basic physical-biological coupling of there region. We will organize a workshop to analyze why the SoG and WCVI are out of phase.
Diane Masson and Richard Thomson
are leading the ship-board plankton and physical surveys component and the moored time series components, respectively, of the Co-variability project. Mooring data will be collected from the WCVI, SJF, Howe Sound, Jervis Inlet and the SoG. In the SoG, thermistor chains, three deep current meters and a bottom-mounted ADCP will measure deep and intermediate water renewal events. These detailed measurements of the deep/intermediate water complement the budget approach we will take. Richard Thomson will directly collaborate with us (Allen) to collect acoustic backscatter measurements of mesozooplankton (and fish) biomass. One WASP will be moored in the southern SoG.
David Mackas is collecting broad zooplankton samples from both the WCVI and inlets around the SoG. Dower and Mackas will coordinate their zooplankton sampling efforts in the SoG. Mackas will also provide access to the zooplankton database that his group has assembled at IOS. This data will be critical in initializing the Neocalanus life-history model. Richard Beamish has been collecting fisheries data in the SoG for over 20 years. Beamish has agreed to provide Dower with access to this data for use in testing the "heuristic rules" developed from our 1D biological-physical coupled model. He will also collaborate with us (Walters) in the construction/comparison of the Ecosim upper-trophic level model for the SoG. Jim Gower has already instrumented one of the three principal ferry tracks in the southern SoG. We plan to instrument the other two. By combining data from all three ferry tracks we will obtain excellent temporal and spatial coverage of the near surface water properties in the southern SoG. As satellite data is difficult to interpret in this region (silt from the water is hard to differentiate from phytoplankton), this ferry data will be invaluable.
Ming Li will develop a 3D physical model of the SoG/SJF estuarine system in collaboration with us (Pawlowicz). The model will be coupled to a simplified biological model. We (Allen, Dower, Denman) will have detailed exchanges on the choices for the this model based on our results from the 1D model with complicated biology. Similarly, Li's results from the 3D model will have direct impact on how spatially varying physical processes are parameterized in our 1D models (Allen, Pawlowicz). Li will use sigma-coordinate Princeton Ocean Model (POM) as the physical model and a three-compartment NPZ model as the biological model. This model is a natural extension of a coupled box model that Li et al.(2000) have developed for the Georgia-Fuca estuary. While the 1D vertical model will focus on the role of wind mixing in phytoplankton production, the 3D model will be used to investigate horizontal advection and spatial variability.

SECTION 4 - TRANSFER OF KNOWLEDGE & BENEFITS TO CANADA: Knowledge & Technology Transfer: We will develop the knowledge necessary to generate a series of rules that can be used to help determine "the state of the Strait". The main user of this information will be our primary partner, Fisheries & Oceans Canada, in addition to the international oceanographic and fisheries scientific communities. We will transfer this knowledge to these groups in a variety of ways.
On a local level, our monthly seminars at UBC will provide a means of communicating our results to colleagues within the oceanographic and fisheries community. UBC has a long history of conducting leading-edge marine science in Canada and we see these monthly meetings as an important means of getting real-time feedback on our progress from a wide ranging group of world class marine scientists.
Our closest ties to Fisheries and Oceans will be through their Strategic Science project "Co-variability of Coastal Marine Ecosystems", led by Richard Thomson. We will work directly with several DFO scientists from this program in both our field work (e.g. Thomson, Masson and Mackas and Gower) and in model development and testing (Li, Pena and Beamish). We have budgeted funds to enable members of our group to spend time working side-by-side with our collaborators at both the Institute of Ocean Sciences (Sidney) and the Pacific Biological Station (Nanaimo). In addition to those scientists in DFO's Co-variability project, we will communicate our progress and results to the wider DFO community by having our PI's give formal scientific seminars at IOS or PBS at least once a year.
UBC and DFO are both key players in Canada's delegation to PICES, the North Pacific Marine Science Organization. In recent years, three members of our team (Allen, Harrison and Denman) have each chaired special sessions at annual PICES meetings (held alternatively in Canada, the US, Russia, Korea, China and Japan). We will take advantage of these strong ties to the Pacific Rim marine science community by having members of our team chair a Special Session on Coastal Ecosystem Modeling (at a PICES Meeting in either Year 3 or 4 of our project) where we can highlight our findings. Additionally, our PI's, graduate students and postdocs will present results from our research at other international scientific meetings (e.g. Canadian Conference for Fisheries Research, Canadian Meteorological and Oceanographic Society, American Geophysical Union, American Society of Limnology & Oceanography, and the American Fisheries Society). In terms of publications, we will submit the results of our work to leading peer-reviewed scientific journals. As well, given the large field component in our project, we will compile annual technical data reports which we will archive with DFO. In Year 4 we will use one of our visits to DFO to organize a workshop where the results from our models in the SoG can be compared with DFO's modeling efforts on the west coast of Vancouver Island.

Benefits to Canada and Non-Academic Participating Organizations: This research will benefit Canada in two main ways. Most Canadians are aware that climate change is occurring and that its effects are already being felt in Canada. Given that Canada's economic well-being relies heavily on renewable resources (including marine resources), understanding how such resources may be affected by climate change in the future is one of the biggest challenges facing Canadians today. Of course, before we can accurately predict how these resources may change in the future, it is imperative that we first understand the factors that govern natural variability in our renewable marine resources today. By focusing on the processes and mechanisms linking physics and biology in our natural laboratory, the SoG, we will gain important insights into how and when marine ecosystems are sensitive to environmental change and thus help to build a more informed basis for predicting the effects of climate change in the future.
The results from this project will be used primarily by Fisheries & Oceans Canada. In the past, traditional approaches to management and stock assessment rarely incorporated environmental data, in part because it was assumed that environmental and ecological conditions do not change significantly over time. However, we now know that environments and ecosystems do change on both interannual and interdecadal time scales. Thus, it has become clear that fisheries stock assessment studies are not sufficient in themselves to provide an adequate basis for management decisions and to ensure sustainable fisheries. In recent years (particularly following the passing of the Oceans Act in 1997) DFO has moved toward newer strategies rooted in ideas of "ecosystem management" and "the precautionary approach". Not surprisingly, the implementation of these new approaches will also require the development of new tools and strategies. The heuristic rule-based system that we will develop here will provide a tool that Fisheries & Oceans can use to incorporate detailed environmental information into their management plans. Using this system managers will be able to evaluate the "state of the Strait" in any given year. By understanding the physical factors that determine the level of primary and secondary production, it will be possible to classify individual years as being "better than average", "average", or "less than average". Such rules will assist managers in making well-informed decisions about the possible consequences of different management options. For instance, by knowing that the environmental conditions in the SoG in a particular spring will most likely have created poor conditions for plankton production, managers might decide to be more cautious in their predictions of recruitment of various fish stocks in that year.
A second benefit will come from the novel approach we propose for building and testing our models. Far too often, ecosystem modeling is done in isolation, with only vague connections to real data. In contrast, we will employ at least three different models (1D coupled biological-physical models, Ecosim models, and Ming Li's 3D physical model) and an innovative field program to understand the links between physics and biology in the Strait. Moreover, we propose to use our top-down model (e.g. Ecosim) to help test the validity of the "rules" generated from the 1D coupled biological-physical model. We will supplement this with tests based on a time-series of fisheries data collected in the Strait of Georgia over the last 20 years (in collaboration with R. Beamish). This approach of combining top-down and bottom-up models (and combining oceanographic and fisheries data) from the same ecosystem at the same time has rarely, if ever, been attempted. Thus, Canada will benefit in that the scientists and student involved in our SoG project will be trained in this new approach, in the hope that it can applied to other marine ecosystems elsewhere in Canada.

Fraser River Plume: (Click on images to enlarge)

Suspended Particles 2000.08.30 from NOAA 14 Satellite Imagery SST 2000.08.30 from NOAA 14 Satellite Imagery

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