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An investigation of possible phytoplankton seeding in the Strait of Georgia from Nanoose Bay Ianson, Debby 1994

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AN INVESTIGATION OF POSSIBLE PHYTOPLANKTON SEEDING IN THESTRAIT OF GEORGIA FROM NANOOSE BAYByDebby lansonB.Sc.E. Physics, Queens University, 1991A THESIS SUBMITTED IN PARTIAL FULFILLMENT OFTHE REQUIREMENTS FOR THE DEGREE OFMASTER OF SCIENCEinTHE FACULTY OF GRADUATE STUDIESDEPARTMENT OF PHYSICSDEPARTMENT OF OCEANOGRAPHYWe accept this thesis as conformingto the required standardTHE UNIVERSITY OF BRITISH COLUMBIAJanuary 1994© Debby lanson, 1994In presenting this thesis in partial fulfilment of the requirements for an advanceddegree at the University of British Columbia, I agree that the Library shall make itfreely available for reference and study. I further agree that permission for extensivecopying of this thesis for scholarly purposes may be granted by the head of mydepartment or by his or her representatives, It is understood that copying orpublication of this thesis for financial gain shall not be allowed without my writtenpermission.(Signature)_________________Department of__________________The University of British ColumbiaVancouver, CanadaDate JOJV 3 9qLDE-6 (2188)AbstractThis thesis investigates the possibility of bays providing the seed population for thespring phytoplankton bloom to larger adjacent bodies of water via advective transport.The study area was Nanoose Bay, Vancouver Island and the adjacent region of the Straitof Georgia. In 1992 and 1993 data were collected 2-3 times weekly and a mooring withan array of 5 current meters was placed at the mouth of the bay during the 1992 study.Interannual variability was tremendous.In 1992 seeding from Nanoose Bay was not possible as the net transport was intothe bay at the surface and middle depths. The influence of the Fraser River seemed todominate as low density water with high silicate concentrations was present at the surfaceand density profiles were generally well stratified. Although nutrients were not limitingand light availability appeared high, phytoplankton concentrations were low until March5 when they began to increase and a bloom occurred. It is suggested that horizontaladvection and flushing of the bay were responsible for suppressing a bloom prior toMarch 5 in 1992.In 1993 phytoplankton concentrations were high inside the bay from the beginning ofFebruary onward. In the Strait no periods of high phytoplankton concentration occurredalthough there were two small increases which appear to be due to advective transport,although it is possible that the first was due to reduced wind mixing. It is suggestedthat seeding of the Strait from Nanoose Bay was possible in this year, although it is alsopossible that seeding occurred from other locations depending on time and conditions.The conservation equation for a scalar was used to investigate advective transport asbalanced by biological sources and sinks. With no current measurements available in111993, estimates were made from the above equation and compared to wind directionin the Strait and density changes at the mouth of the bay. In 1993 profiles were wellmixed with respect to 1992 and overall salinity was higher. It is suggested that light wasusually limiting to phytoplankton growth in the Strait due to vertical mixing throughoutthe study, while in the bay the depth of the water column limited vertical mixing thusallowing phytoplankton to bloom.To continue experiments of this type it is suggested that daily sampling be done astemporal changes can occur quickly. As evidenced from the 1993 data, spatial resolutionis also valuable. Current measurements are necessary and their absence in the 1993 dataset was unfortunate. It is suggested that drogues may be useful for measuring currents.They could be used to attempt to track phytoplankton when concentrations begin toincrease.111AbstractTable of Contents11List of TablesList of FiguresAcknowledgementsvi’vi”x1 Introduction1.1 Introduction1.1.1 Spring Bloom Dynamics .1.1.2 Seeding1.2 Thesis Objectives1.3 Sverdrup Critical Depth Theory .1.3.1 Critical Depth1.4 Stratification and Mixing1.4.1 Depthofthetoplayer .1.4.2 Mixing1.5 Advection and Diffusion1.5.1 Physical Forcing1.6 Phytoplankton Ecology1.6.1 Diatoms and Flagellates .1.6.2 Sources1111234557810111213iv1.6.3 Sinks. 132 The Experiment 152.1 Nanoose Bay 152.2 Design 162.2.1 Sampling Timing and Locations 162.2.2 Sampling 182.2.3 Current and Wind 203 Results and Analysis 233.1 Current and Wind 233.1.1 Processing 243.1.2 Wind correlations between lighthouses and the mouth of Nanoosebay 333.1.3 Relationship between wind and current residuals 353.1.4 Advective exchange between Nanoose bay and the Strait of Georgia 413.1.5 Flushing and stability 433.1.6 Density changes and current direction 463.2 Density profiles 493.2.1 Mixed Depth 503.2.2 Density Gradients and Velocity Shear 513.2.3 Temporal changes 543.3 Critical Depth 593.3.1 Radiation data 593.3.2 Secchi disc depth and critical depth 603.4 Chlorophyll a 663.5 Species Composition 66V3.6 Nutrients 754 Discussion 834.1 Limitations to phytoplankton growth during the onset of the spring bloom 834.1.1 1992 844.1.2 1993 884.2 Seeding by advection 924.2.1 1992 934.2.2 1993 934.3 Summary 1004.4 Suggestions for improving or continuing this experiment 101Appendix A Dominant genera in species composition 102Bibliography 105viList of Tables3.1 Tidal constituents used in the harmonic analysis .........., 293.2 Amplitudes (cm/s) of the stronger tidal constituents of the u current. 293.3 Maximum wind cross-correlations 353.4 Angles for principal axis rotations for 1992 current and wind data 383.5 Maximum wind and current cross-correlations 393.6 Velocity shear necessary for turbulence 544.1 Phytoplankton growth parameters determined from CTD profiles for NAN10 86A.1 Dominant genera with abundance for 1992 103A.2 Dominant genera with abundance for 1993 104viiList of Figures2.1 Nanoose bay and the Strait of Georgia with locations of all sampling stations 173.1 Processed u current time series at NAN 20, 1992 253.2 Processed v current time series at NAN 20, 1992 263.3 Processed t (kg/rn3)time series at NAN 20, 1992 273.4 Filtered residual u current time series at NAN 20, 1992 313.5 Filtered residual v current time series at NAN 20, 1992 323.6 Wind time series for Ballenas Island lighthouse and Nanoose bay mooring 343.7 Time series of the principal component of the wind for Ballenas Islandlighthouse and 2 m currents 403.8 Net transport plotted as a running integral with time 423.9 A phytoplankton flushing index,—1-— j u(t)dt, as a function of t1 for eachdepth 453.10 Filtered o (kg/rn3)time series shown with the flushing index at each depth. 473.11 t7 (kg/rn3), at NAN 20 from the mooring and CTD profiles 483.12 Representative density profiles at NAN 10 523.13 Density structure time series: for two favourable intervals 573.14 Density structure time series: for two unfavourable intervals 583.15 1 and PAR as functions of time 603.16 Secchi disc depth as a function of time for NAN 10, 20 and 30 in 1992. 613.17 Secchi disc depth as a function of time for inside stations in 1993 623.18 Secchi disc depth as a function of time for outside stations in 1993. . .. 63viii3.19 Critical depth as a function of time for NAN 10 and 30 653.20 Chiorophylla as a function of time in 1992 673.21 Chiorophylla as a function of time for the inside stations in 1993 683.22 Chiorophylla as a function of time for the outside stations in 1993 693.23 Skeletonema costatum, Chaetoceros spp. and Thalassiosira spp. counts for1992 703.24 Skeletonema costatum, Chaetoceros spp. and Thalassiosira spp. counts for1992 before the onset of the spring bloom 713.25 Chaetoceros debilis counts for 1993, inside stations 723.26 Chaetoceros debilis counts for 1993, outside stations 733.27 Skeletonema costatum and Chaetoceros debilis counts for 1993, NAN 10and 30 743.28 Time series of nitrate in 1992 for NAN 10, 20 and 30 773.29 Time series of silicate in 1992 for NAN 10, 20 and 30 783.30 Time series of nitrate concentrations in 1993, inside stations 793.31 Time series of nitrate concentrations in 1993, outside stations 803.32 Time series of phosphate concentrations in 1993, inside stations 813.33 Time series of phosphate concentrations in 1993, outside stations 824.1 1992 time series of phytoplankton concentration and factors possibly limiting its growth for stations NAN 10 and NAN 30 854.2 1993 time series of phytoplankton concentration and factors possibly limiting its growth for stations NAN 10 and NAN 30 90ixAcknowledgementsDr. Stephen Pond’s name should be emblazoned on this page in large bold letters.I acknowledge not only the experimental expertise and solid academic guidance, butespecially the enthusiasm and immense support that Dr. Pond has given me.I acknowledge Dr. Paul LeBlond and Dr. Tim Parsons for their support and guidance.Thank-you Dr. Parsons for the idea behind this experiment and for introducing me toan entirely new world outside of physics.I would like to thank Dr. Paul Harrison for the discussions of biological aspects duringthe preparation of this thesis.I am of course also grateful for the financial support from Dr. Pond’s NSERC grantand teaching assistantships in the Department of Physics.Thanks to the officers and the crew of the C.S.S. Vector for their assistance with themooring work.I would like to acknowledge the personnel at C.F.B. Nanoose Bay for their excellentsampling work and for welcoming me on their base.Thanks to Dr. Richard Thompson and I.O.S. for making the 1993 experiment possibleby providing a boat.I carry many fond memories of the field work. Thank-you Hugh MacLean, HeinzHeckl, Jonathan Nash and David Timothy for your excellent assistance and company.Special thanks to Heinz for teaching me how to properly tie knots.I do not know where to begin in thanking those in the department who have helpedme with all aspects of my work. I did manage to spread out and pester most labs in thedepartment during this experiment. I thank you all in random order, Catriona, Rowan,xVictor, John, Kedong, Peter, Scott, Roger, Renee, Denis, Roy, Joe, and David.I can not complete the acknowledgements without a very sentimental mention of mymom and my dad who seem implicitly involved. Relaxing did make it all possible.xiChapter 1Introduction1.1 Introduction1.1.1 Spring Bloom DynamicsPrimary productivity is defined as the change in phytoplankton biomass per time (Parsons, Takahashi and Hargrave [22]). A large net increase in primary productivity constitutes a phytoplankton bloom.Phytoplankton require light and nutrients to survive. The depth over which theyare vertically mixed depends on the stratification of the water column and the forcing.During the winter, mixing is at a maximum due to strong winds and low fresh water input.Light is at a minimum. As a result phytoplankton travel deeper than the range wherethey receive enough light so that, on average, their respiration demands are exceeded bytheir photosynthetic production. At this time nutrients that have been mixed upwardare abundant and not limiting to phytoplankton growth. Light availability increasesand mixing decreases as spring approaches. When phytoplankton receive enough lightaveraged over their vertical journey in the water column they are able to utilize the richnutrient supply. At this time the spring bloom occurs.1.1.2 SeedingThere are two main ways in which a phytoplankton bloom can be seeded. It can be seededin situ by phytoplankton present at that location or advectively by phytoplankton carried1Chapter 1. Introduction 2from elsewhere. Advective transport occurs through wind-driven currents, tidal currentsand density driven circulation. These influences also control mixing.In a coastal situation some interesting possibilities exist. The depth of the watercolumn can limit the depth to which phytoplankton are mixed. If an area is mixed tothe bottom and the critical depth of light penetration (defined below) reaches this deptha bloom can occur simply because the water column is shallow enough. In deeper areasthe vertical mixing may be greater (i.e. below the critical depth) and a bloom would notoccur.Some areas may also be more sheltered by topography or more stratified due toterrigenous fresh water input. Both cases would serve to reduce vertical mixing andtherefore allow a bloom to occur earlier.Thus both, mixing to a shallow bottom or limited mixing, should provide potentialseeding areas for offshore waters. It is however also possible that flushing of a potentialseeding area could prevent a bloom from occurring there even when nutrients and lightare not limiting. If the time for a full volume exchange to occur is less than the generationtime for phytoplankton growth, a bloom will not occur. Phytoplankton will be flushedout before they have a chance to multiply.1.2 Thesis ObjectivesThe intention of this work was to investigate the possibility of a spring bloom in largeropen bodies of water being seeded advectively by adjacent areas. Of specific interest wasa seeding area that is shallow enough to be mixed to the bottom. For this reason anincrease in primary productivity could occur earlier there, once the critical depth reachedthe bottom. The study area chosen was Nanoose Bay and the adjacent waters of the Straitof Georgia. Nanoose Bay is large and shallow making it an excellent potential seedingChapter 1. Introduction 3area. The bay is also sheltered with respect to the Strait. In low wind conditions, whenthe bay is not mixed to the bottom, the mixed layer would be expected to be shallowerthan in the Strait. In this case the spring bloom would occur first in the bay, still makingit a good potential seeding area. What follows is a list of data collected in the field,and what was intended to be done with each data set in order to address the proposedquestion.1. Currents at 5 different depths and wind at the mouth of the bay were measured toprovide information about advection.2. Time series of chlorophyll a were measured at all stations to represent phytoplankton biomass.3. Time series of nutrients were measured at all stations mainly to ensure that phytoplankton growth was not nutrient limited.4. Time series of density profiles were taken at all stations to estimate the extent ofvertical mixing and provide information about circulation.5. The Secchi disc depth was measured at each station and daily total solar radiationmeasurements were made to calculate the critical depth as a time series.6. Phytoplankton species composition were examined for all stations as a time series for a quantitative measure of phytoplankton concentration and a qualitativedescription and comparison of phytoplankton communities.1.3 Sverdrup Critical Depth TheorySverdrup [28] proposed a theory using light and stratification as the limiting conditionsto determine when a spring bloom would occur: A net increase in primary productionChapter 1. Introduction 4can happen once phytoplankton are not being mixed deeper than the critical depth oflight penetration.1.3.1 Critical DepthThe critical depth (Do) is defined as the depth above which respiration demands aremore than met by photosynthetic production of phytoplankton (Parsons, Takahashi andHargrave [22]). It is dependent on the absorption and scattering of light by water and thetotal amount of photosynthetically available solar radiation (PAR) received at the surfaceof the ocean, which is a fraction of the total incoming solar radiation at the surface (Ia).The former is parameterized by k, the extinction coefficient of light in water. The criticaldepth is calculated from:D=— e_k) (1.1)where k is estimated from the measured Secchi disc depth, D3, as 1.7/D3 [22]. I isthe compensation light intensity inherent to the definition of the critical depth. It isthe average amount of radiation available integrated from the surface to D and is setdepending on the ability of phytoplankton to photosynthesize at a minimum light level.The accepted range for I is 0.12 to 0.54 langley/hr [22]. Radiation in the 400-700nm band is considered photosynthetically available. PAR is obtained from J, using thefactor F. The accepted value for F is 0.5 [22]. Reflectance of radiation by the sea surfaceparticularly when the sun is at low angles is also considered to be accounted for by F. At500 N the percentage of total PAR reflected varies from about 10% in February to 5% inApril (Campbell and Aarup [2]).Chapter 1. Introduction 51.4 Stratification and MixingThe ocean is often considered as a two-layer system. It is defined in terms of densitystructure. Both layers have constant t; ( = p - 1000, where p is the density of waterat the in situ temperature and salinity and at the reference pressure of 1 atmosphere).The bottom is more dense than the top with a strong density gradient, the pycnocline,between. In coastal waters fresh water input often plays a major role in the stratificationof the water column. Density structure is often much more complex than this simple twolayer idealization. What is of interest in this problem is the depth to which plankton ismixed. It is often assumed to be the depth of the top layer.1.4.1 Depth of the top layerIt is possible to calculate an equivalent thickness of the top layer from density profiles asdescribed by Freeland and Farmer [9]. In this method two relevant physical quantitiesare conserved, the potential energy of the water column and the baroclinic first modeinternal wave speed. These quantities are calculated from continuous density profilesand then set equal to the theoretical values for the two layer system. In this way theexperimental density profile can be fit to a two layer structure. From this fit the depthof the upper layer and t of the lower layer are estimated.Potential EnergyWork is required to mix water of different densities. The potential energy of a watercolumn is increased when denser water is mixed upwards. The potential energy parameterx is defined by Freeland and Farmer [9] as:=1JH (1.2)Chapter 1. Introduction 6where H is the total height of the water column, z is the depth (which is zero at thesurface and increases downward) and ut(z) is the density profile. This equation is easilyintegrated for the ideal case to obtain:x = (j1h2 +2(H —h2))/H (1.3)where the subscripts 1 and 2 denote the upper and lower layer respectively and h is thedepth of the top layer. Freeland and Farmer [9] assume that o is the experimental o at2 m.First Mode Internal Wave SpeedA stratified system provides the physical environment for many modes of internal oscillations. The barotropic mode is the basic one that would occur without the densitystructure simply due to the restoring force of gravity. The next highest mode is the oneconsidered. Its restoring force includes the buoyancy forces associated with the variation of density with depth. To estimate the internal wave speed the partial differentialequation for vertical oscillations is solved for its eigenvalues:d2W+W(z)N2(z— 1 4dz2 c (.)where W(z) are amplitude distributions for the n eigenfunctions with phase speeds c.N(z) is the Brunt Vaisala frequency:N2(z) = (1.5)N is the natural frequency of the water column giving an upper limit to vertical oscillations. A rigid lid boundary condition is implied at the surface. The solution to thisproblem is presented in LeBlond and Mysak [18]. In the ideal two layer case the internalwave speed is:g h(H—h)c12= —(o2 — ai) H (1.6)Chapter 1. Introduction 7Using the two equations 1.6 and 1.3 and equating each to the respective values c1 andas estimated directly from the density profiles, h and •2 can be calculated.1.4.2 MixingTurbulent mixing may occur due to vertical shear of the horizontal velocity (f). Strongstratification inhibits turbulence through buoyancy forces. More energy and thus agreater velocity shear is required to move heavier parcels of water upwards. Richardson defined a non-dimensional index to quantify this effect:(Q!)2 (1.7)Note that N is the Brunt Vaisala frequency, as defined above, and is a measure of verticalstability in the water column. Theoretically if R > 1/4 everywhere in the fluid there isno turbulence, as shown by LeBlond and Mysak [18].It is easily possible that the top layer, although it is called the mixed layer, may notbe actively mixing. Velocity shear and even weak stratification within layers should alsobe considered. In most cases fitting the density profiles in and around Nanoose Bay tothe two layer model was not appropriate. For example, the density structure was oftensuch that there was a nearly constant small density gradient from the surface to thebottom. The question arises as to whether this is a well mixed situation. Where werephytoplankton in the water column? To attempt to answer this question a Richardsonnumber of 1/4 can be used along with N, estimated from the density profiles, to calculatea velocity shear in the vertical necessary for turbulence. The velocity shear can becompared to current data at the mouth of the bay to estimate whether or not activemixing is occurring.Chapter 1. Introduction 81.5 Advection and DiffusionTo determine whether or not a bloom is seeded other than in situ an understanding ofadvection and diffusion is necessary. The general conservation equation for the rate ofchange of a scalar in a fluid is:= —V• uC + V2C + (Sources + Sinks) (1.8)C is a scalar quantity of interest, u is the vector current velocity and i is the moleculardiffusivity. This equation describes changes in C at a fixed location. It simply statesthat the change in C with time is due to the net amount of C that is advected, or isdiffused, to or from that location and the sum of any sources and sinks present. C willbe considered generally at this point as either concentration of phytoplankton biomassor as number of cells per volume.The sources and sinks come from biological influences and are discussed in the lastsection of this chapter.Molecular diffusion is driven by gradients of a scalar and is proportional to the diffusivity , of that scalar. In general molecular diffusion is negligible compared to the otherterms. Often the diffusivity i is replaced by a much larger value using the Reynolds approach as in Pond and Pickard [23]. It is called the eddy diffusivity K. Doing so can makediffusive effects appreciable. The dispersion of phytoplankton has been fit to equationsusing a similar method by J. Cloern [4].To understand the Reynolds approach both C and u are split into mean and fluctuating parts. The fluctuating parts,u’ and C’, are turbulence terms. C and u are substitutedinto equation 1.8, each as a sum of the the two parts and the equation is time averaged.(1.9)where <> indicates a time average. The Reynolds fluxes <u’C’ > are replaced byChapter 1. Introduction 9assuming that they are directly related to the spatial gradients of the mean C as in Pondand Pickard [23].(1.10)The proportionality constant is the eddy diffusivity. Thus fluctuating terms lead toturbulent diffusion. Note that the turbulent and molecular diffusive terms differ only bythe factors K and i respectively, K being much larger. The molecular diffusive fluxes aretherefore negligible compared to the turbulent fluxes.The difference between eddy and molecular diffusivity other than scales is that K isnot isotropic as .c is. Eddy diffusivity is much smaller in the vertical as the length scalein this direction is much smaller than in the horizontal. It is assumed that the verticalregion over which phytoplankton were sampled (the top 3 m) was uniform, thus makingthe vertical gradient in C zero. For this reason the vertical Reynolds flux term wasneglected. It is recognized however that it may be important. Vertical eddy diffusion hasbeen related to increases in phytoplankton concentration by Cloern [3] in San FranciscoBay. It is noted however that tidal currents are much stronger in San Francisco bay thanin Nanoose bay. Also, vertical chlorophyll a gradients often exist (Harrison et. al. [13])and can be related to many different processes, as in Cullen [6]. Such gradients howeverare often associated with a well stratified water column where phytoplankton with theability to move dominate. During the sampling time diatoms were the dominant typeof phytoplankton. Diatoms have no means of locomotion. It is therefore hoped that,at least in the upper part of the water column which was sampled, the approximationof zero vertical C gradient is reasonable in the sense that any associated error is muchsmaller than the horizontal advective effects.For this work both turbulent and molecular diffusion will be assumed negligible compared to advective transport in equation 1.8. Advection usually dominates turbulentChapter 1. Introduction 10diffusion in coastal situations (Hansen and Rattray [11]), with the exception of areaswhere strong tidal currents and thus intense mixing exist. Tidal currents at Nanoose bayare not strong. It is therefore assumed that turbulent diffusion is negligible compared toadvection. Equation 1.8 then becomes:-- —V. uC + E(Sources + Sinks) (1.11)where C and u are now mean quantities.1.5.1 Physical ForcingMaterial transport, or advection, can be driven by three main forces, wind, tides andhorizontal density gradients.In the case of tides, the forcing in the open ocean is due to the gravitational pull ofthe moon and the sun. Boundary conditions are produced by the progressive elevationchanges at the entrances (Juan du Fuca and Johnstone Straits) to the Strait of Georgiathat are responsible for the tides there. The result is mixed, but mainly semidiurnal tides,with a mean tidal range of 3m (Thompson [29]). The amplitudes of the tidal currents atthe mouth of Nanoose bay are a few cm/sec.Wind blowing at the surface of the ocean produces a stress which causes motion. Thewind stress is a function of the square of wind speed, density of air and a non-linear dragcoefficient. This stress is transferred downwards as a function of vertical eddy viscosityand vertical velocity shear, (Pond and Pickard [23]). Winds at the mouth of Nanoosebay typically range from 2 to 8 m/s. Surface currents driven by such wind speeds areexpected to be within the range of a few to 10 cm/s or so. The currents measured werein this range and it was expected that wind would be mainly responsible for non-tidalcurrents.Density driven circulation occurs due to pressure gradients created by horizoiltalChapter 1. Introduction 11variation in density. The force due to density gradients is proportional to the f dz andin the opposite direction to . Local fresh water input is an effective means of creatingstrong horizontal variation in stratification and is essentially responsible for estuarinecirculation. In estuarine circulation there is a surface flow away from a fresh water source.The addition of fresh water causes an increased surface elevation which has a horizontalgradient thus driving the surface layer away from the source. The stratification set upin such a system generally varies spatially such that the fresher surface layer becomesprogressively more saline away from the source through entrainment. The density changecan create horizontal density gradients which more than compensate for the forcing dueto elevation changes. The net result at depth is for a density driven current to flowtowards the fresh water source.The fresh water input from the Fraser river influences stratification throughout theStrait of Georgia (Thompson [29]). It is the dominant feature especially in the summerduring freshet. It was expected that it would have little influence on Nanoose duringthe winter-spring season given that the distance between Nanoose and the mouth ofthe Fraser is approximately 70 km (see figure 2.1) and they are on the opposite sidesof the Strait. The residual circulation of the entire Strait is very complicated (Stacey,Pond, LeBlond, Freeland and Farmer [25]) however and certainly influenced currents atNanoose Bay.1.6 Phytoplankton EcologyPhytoplankton ecology will be considered in terms of providing source and sink termsin equation 1.8. Specifically the Z(Sources + Sinks) term will be replaced by biologicalparameters.Chapter 1. Introduction 121.6.1 Diatoms and FlagellatesThe main types of phytoplankton found in and around Nanoose Bay are diatoms, dinoflagellates and nanoflagellates, (which include cryptomonads, haptophytes and chioromonads). Each has different strategies for survival which tend to make it dominant underdifferent environmental conditions. Dinoflagellates and nanoflagellates have flagella andtherefore some means of locomotion. Diatoms are truly free-floating. Their strategy formovement in the water column involves cellular processes that change their density withrespect to the surrounding sea water. Ability to take up nutrients from the water alsodiffers amongst classes (Harrison and Turpin [14]). Diatoms tend to dominate in highnutrient conditions where they are able to take up nutrients very quickly. In general theflagellates are more flexible in their ability to use nutrients.During spring bloom conditions nutrient availability is high as nutrients have beenmixed up during the winter and not used. As primary productivity increases, nutrientsget depleted. Nutrient depletion is often coincident with increased stratification, as thereis generally less wind and greater fresh water input and therefore less mixing during thespring and summer months than in the winter. Diatoms therefore usually dominate earlyin the year and make up the majority of phytoplankton biomass during the spring bloom.Conditions are perfect for them in terms of high nutrient availability and stronger mixingproviding them with a means of locomotion. Flagellates dominate later when nutrientsare depleted in the upper layer and waters are more stratified. In these conditionsflagellates may be able to swim down to the nutricline (the nutrient gradient usually justbelow the nutrient deplete upper region) where they can utilize available nutrients or atleast move through the water and enhance their intake of nutrients.Diatoms made up the majority of the phytoplankton population in Nanoose bayduring the sampling period with very few flagellates as expected. Samples tended to beChapter 1. Introduction 13low in species diversity and typical of spring boom conditions in the Strait of Georgia(Harrison, Fulton, Taylor and Parsons [13]).1.6.2 SourcesThe most obvious source of phytoplankton comes from growth and cell division. Infavourable conditions the generation time for cell division is temperature dependent. Inthe Strait of Georgia during the study period a reasonable doubling time would be 2 days(Parsons, Takahashi and Hargrave [22]).A second possible source is over-wintering cysts. Many genera of phytoplanktonare able to form dormant resting spores. They sink to the sediments and excyst whenconditions, for example a rise in temperature and light, become favourable. A situationin which the water column is mixed to the bottom could provide an excellent means ofintroducing the excysted phytoplankton back into the euphotic zone.1.6.3 SinksSinks for phytoplankton are due mainly to being eaten and sinking out of the watercolumn. Two types of grazing were considered, grazing by zooplankton and by benthos.Zooplankton have a threshold in concentration of phytoplankton for grazing (Parsons andLeBrasseur [19]). If very little food is present they would expend more energy huntingfor food than they would consume. Typical grazing rates for zooplankton in the Straitof Georgia for the study period were used. In Nanoose Bay however benthic grazingappears to play a much more important role. The bay is an oyster bed and if it is wellmixed the filter feeding bivalves are being continually supplied with food. The flushingtime for Nanoose bay was compared with the filtering time by bivalves.Phytoplankton will sink passively to the sediments if they are not buoyant enough.Chapter 1. Introduction 14Dead plankton can sink over 10 times faster than live (Parsons, Takahashi and Hargrave [22]). Two of the factors affecting buoyancy are nutrient enrichment and light.Putting the sources and sinks together yields:YZ(Sources + Sinks) = C(t)(1u— b — z — s) (1.12)where i is the specific growth rate of phytoplankton, b is the feeding rate of bivalves, zis the grazing rate of zooplankton and s is the sinking rate.Rewriting equation 1.8 in its final form with all substitutions yields:= —V. uC + C(t)( — b — z—s) (1.13)Note also that, since water is an essentially incompressible fluid, V uC can also bewritten as u VC, which is the form that will be used in Chapter 4.Chapter 2The Experiment2.1 Nanoose BayThe study area chosen to investigate the seeding of a spring bloom from shallow areaswas Nanoose Bay, on the east coast of Vancouver Island. It seemed an ideal location dueto its bathymetry and geography. The bay itself is quite large, about 2 square kilometres,is shallow, generally 25 metres deep, and is directly connected to the Strait of Georgiavia a narrow (approximately 0.5 km) opening. There are extensive mud flats at theend of the bay and several small creeks that input a little fresh water mainly near themouth. The bay itself is shallow enough to be mixed to the bottom during strong windconditions typical of winter and early spring. In the case of calm weather, the bay issheltered and becomes quite stratified, with a brackish layer on top and a shallow mixedlayer. Regardless of wind conditions therefore, the extent of vertical mixing outside thebay is generally greater, allowing for an increase in primary productivity to occur first inthe bay. Advective exchange between the bay and the adjacent Strait occurs through thenarrows at the mouth of the bay. Currents here appear to be density driven, wind drivenand tidal and are not strong. The tides are typical of the Strait of Georgia, mainlysemidiurnal with the M2 and the K1 constituents dominating (Thompson [29]). Themean tidal range is just over 3m.15Chapter 2. The Experiment 162.2 Design2.2.1 Sampling Timing and LocationsData collection was started near the end of January to ensure that any early increasein phytoplankton biomass was recognized, as well as to observe the phytoplankton community surviving in the water column through the winter. Once the spring bloom wasclearly in full force the experiment ended. Originally the main criterion for samplinglocations was to choose stations representative of both the inside and outside of the bay.The criteria evolved to include spatial resolution and thus more stations between insideand outside.1992 was the first year that data were collected. Data collection began on January 27(Julian day 27). The sampling scheme was very simple. Stations were: NAN 10 insidethe bay, NAN 20 at the mouth, NAN 30 in the Strait, just west of the Winchelsea Islands(figure 2.1). The location of NAN 30 was chosen as it was convenient for the military crewat Nanoose to sample. It was thought to be a reasonable location to sample receivingwaters of the bay during the winter as the prevailing winds at this time are typicallyfrom the south east, creating wind driven north westerly currents. I was fortunate tohave personnel from Nanoose sample twice weekly during their own maneuvers. Samplingwas done by myself once weekly in the UBC departmental boat, the Tintannic. Weeklysampling ended March 21 (Julian day 81), 1992 when there was a strong phytoplanktonbloom in the Strait. At this time the Secchi disc depth at all stations was limited to 5mby the high numbers of phytoplankton. The mooring was recovered on April 9 (Julianday 100) at which time an additional water sample (chlorophyll, nutrients and speciescomposition) was drawn at each station.In 1993 the experiment was significantly altered. More spatial resolution was desired,especially at the mouth of the bay, so four new stations were added. Two stations wereChapter 2. The Experiment 17.5 I..I..• zzi)Figure 2.1: Nanoose bay and the Strait of Georgia with locations of all sampling stationsChapter 2. The Experiment 18added between NAN 10 and 20 to create a line of stations at the mouth of the bayand two were added on the outside between NAN 20 and 30. It was hoped that horizontal chlorophyll a gradients could be estimated from this configuration. All stationsare shown in figure 2.1. Chlorophyll measurements were taken in triplicate to make therecord less noisy. On one occasion in 1992 triplicates were taken to give a measure oferror in the sampling and it was found that chlorophylla varied by over an order of magnitude between replicates at the same station. Clearly biological patchiness is a majorconsideration when taking discrete water samples from any location. An eighth stationwas added (NAN 5) in a shallow (several metres deep) cove in the bay. It was hopedthat overwintering cysts could possibly be observed here as well as any early increasesin primary productivity. Sampling was done twice weekly at all stations, weather permitting, in the Whaler 3 provided by the Institute of Ocean Sciences, Sidney, B.C. ofFisheries and Oceans, Canada. Three extra days of sampling at the original stationswere done by the crew at Nanoose; they were unable to sample weekly. Sampling beganon February 4 (Julian day 35) and ended on April 13 (Julian day 103). Strong southeasterly winds during the first part of April suppressed a strong bloom in the Strait andcaused sampling to continue later in the season than in 1992.2.2.2 SamplingAt each station nutrients, chlorophyll and species composition were sampled. Densityprofiles and Secchi disc depth were also measured.Water samples were drawn using a 3m integrated pipe sampler (see Sutherland [27]).The 3m water column was thoroughly mixed as it was emptied into a bucket. From thisbucket, 100 ml were forced through a precombusted 2.5 cm diameter Whatman OF/Fglass filter. The filtrate was collected in 30 ml polypropylene bottles for nutrient analysis.The filter and filtrate were put on ice and frozen as soon as possible to avoid bacterialChapter 2. The Experiment 19activity and enzymatic breakdown in the samples. Note that in 1993 three pipes weredrawn at each station for chlorophyll triplicates although only one nutrient sample wastaken. For species composition analysis a 60 ml glass jar was filled from the bucket andfixed with Lugol’s iodine solution.The chlorophyll analysis was done using the method described in Parsons, Maita andLalli [20]. The filters were placed in 10 ml of 90% acetone solution and put in a sonification bath for 20 minutes to extract pigments and then stored for 24 hrs at 5 deg C. Thechlorophyll a and phaeopigment concentrations were then measured fluorometrically using a Turner designs Model 10TM fluorometer. Fluorescence is converted to concentrationusing equations in Parsons, Maita and Lalli [20].Nutrient analysis was done using a Technicon AutoanalyzerTMwith a baseline of 3 pptseawater. Nitrate, phosphate, ammonium and silicate were measured for the 1992 data.Only nitrate and phosphate were analyzed for the 1993 data as data from the previousyear indicate that nutrients were high everywhere until phytoplankton concentrationsincreased and they were not at any time limiting to phytoplankton growth. Ammoniumand silicate data were not directly used. Also ammonium concentrations were largeenough to suspect contamination. Silicate concentrations are often used as a fresh watertracer and CTD data could be used for that.Species composition analysis was done using an inverted microscope. Samples weresettled for 24 hours in 10 ml and 25 ml Leitz settling chambers, the volume depending onabundance of phytoplankton. Identification was done to the genus level as it was sufficientin comparing phytoplankton communities. For reference and identification of diatomsCupp [7] was used. All genera were noted for their presence and the most abundantwas counted under 100X or 400X magnification depending on the size of phytoplankton.The percentage of the total number that the most abundant made up was also notedto provide an estimate of the relative composition ot the different species present. InChapter 2. The Experiment 20addition three genera were always counted regardless of their abundance: Chaetocerosspp., Thalassiosira spp. and Skeletonema costatum. The presence of zooplankton, larvaeor any other plankton was also noted.Density profiles were taken using an S4 current meter as a CTD. The S4 meter thatwas used has an inductive conductivity sensor. For temperature measurements it has aplatinum resistance thermometer which has the fast response time necessary for takingprofiles. For depth measurements a strain gauge pressure sensor is used. Based onlaboratory calibration checks the accuracy is tO.02 for temperature, t0.05 for salinity,and i0.05 for ot. After the correction for zero offset the depths should be accurate to0.5 m or better. All casts were done to 20 m, which is nearly to the bottom at stations10 through 15, and then to 40 m in 1993 at station 30 on the outside to observe thestructure in the deeper water of the Strait. The S4 was set to sample continuously at 5sec intervals before going out to sample and left running. All of the data were read offof the S4 afterwards and the useful segments, (i.e. when the S4 was in the water) wereextracted from the record.To measure the turbidity of the water, and thus calculate the extinction coefficientk, the Secchi disc depth was measured at each station. Solar radiation was measuredusing a pyranometer placed on a piling in Nanoose bay. The pyranometer was connectedto a data logger inside a weather proof case. The data logger recorded 24 hr values ofintegrated solar radiation.2.2.3 Current and WindOn January 27 1992 a mooring was placed near the mouth of Nanoose bay at stationNAN2O to measure the advective exchange in and out of the bay. It was equipped with5 interocean S4 current meters and an Aanderra meteorological station. The locationof the mooring was chosen to be just outside of the bay. The reason for its placementChapter 2. The Experiment 21was mainly to avoid possible difficulties with boat traffic entering the bay, especially logbooms during storms. Advantages of its placement include measuring wind componentsthat are blowing in the Strait as well as into the bay.The S4 current meters were placed at 2, 4, 7, 12 and 20 m below the surface. Itwas expected that most variation in the currents would appear near the top of the watercolumn as was found for wind driven responses in Peter Baker’s work in Knight Inlet [1].The current meters were therefore packed more closely near the surface. The S4s wereset to record conductivity, temperature and a one minute vector averaged velocity every10 minutes.By laboratory calibration the accuracy is i0.02 for temperature aild generally f 0.2for S and o. Conductivity is measured by conductive sensors and because of the longimmersion time some fouling is possible. Examination of the records suggests that theprecision for the set of measurements is i0.1 for S and cit.Currents are generally small at the mouth of Nanoose bay, typically a few cm/s andtherefore difficult to measure. Mechanical devices, such as Aanderra current meters areprone to errors through friction, rotor pumping and alignment to surface wave trails, (seeKollstad and Hansen [16]). S4 current meters use magnetic induction to measure motionin the water. A magnetic field is set up and the motion of conductive seawater throughit induces a voltage which is measured and recorded by the S4, (see Lawson et al. [17]).The S4 is capable of measuring smaller currents than mechanical current meters. Thevelocity is vector averaged so the results are unaffected by surface wave trains.The wind data were taken by an Aanderra system on the Ceodyne buoy of the mooring. Unfortunately it failed to record data for the first 40 days that it was deployed,which happened to be the portion of the record with stronger winds. To obtain a complete wind record lighthouse data were used from both Ballenas and Entrance Islands,on either side of Nanoose bay (figure 2.1). Correlations between both lighthouse recordsChapter 2. The Experiment 22and the Geodyne record were high and the Ballenas record was therefore used.The meteorological station was equipped with an anemometer 4m above the water,a compass, and a thermometer to measure ambient temperature. Wind speed, direction and air temperature were recorded at 10 mm. intervals. The reported ambienttemperature was a suspicious 16 deg C throughout the entire experiment.It was hoped that the non-tidal part of the currents could be correlated with the windfor the 1992 record and this correlation could be used to extrapolate 1993 currents fromthe the 1993 wind data. This approach proved to be more difficult than anticipated andthe comparison is discussed in the next chapter.Chapter 3Results and Analysis3.1 Current and WindAll current data are from the mooring set at NAN 20 for the 1992 season. There is a 73day record of current speed and direction as well as density for depths of 2, 4, 7, 12 and20 m. Wind data came from three sources, the geodyne anemometer and Ballenas andEntrance Island lighthouses. All data were run through a sequence of processing whichis described in the next section.The current data were taken to measure the advective transport in and out of the bayas a function of time, and thus determine whether phytoplankton were traveling fromthe bay to the outside and possibly providing a seed population. Because current datawere only taken in 1992, it was hoped to gain knowledge from these data to allow 1993currents to be estimated. To do so, cross-correlations between the current and wind weredone to estimate the contribution of the wind to the current. As wind data are readilyavailable a relationship between wind and current would have allowed the extrapolationof current in 1993. It was however not possible to find such a relationship as is shown insection 3.1.3.The time scales of interest are related to phytoplankton growth. To consider advectionimportant to phytoplankton, fluctuations with periods less than their generation timewere removed. The generation time during this experiment is assumed to be about 2days (Parsons, Takahashi and Hargrave [22]), thus it was desired to remove energy with23Chapter 3. Results and Analysis 24frequencies greater than 1/2 cpd from the current record. Harmonic analysis was usedto take the energy at tidal frequencies out of the record. The main tidal constituentsare semidiurnal and diurnal and thus of time scales less than phytoplankton growth. Toremove remaining high frequency energy 25 hour averaging was done.3.1.1 ProcessingCurrentsRaw data (velocity components, conductivity, and temperature) came directly from theS4 current meters. Velocity data were rotated to correct for the magnetic declinationwhich is 22 degrees at Nanoose Bay. Possible spikes were then removed from the rotatedfiles and averaging was done to make hourly values from the 10 minute samples, and thusremove high frequency noise. This processing was done using a window based averagecentred on the hour. In this case the highest and lowest values in each window werediscarded and the remaining 5 values were averaged. Salinity and at were calculatedusing the practical salinity scale and the international equation of state as in Pond andPickard, [23]. After the binning and calculations, the S4 data were split into two files,one with Julian day, u and v and the other with Julian day, temperature, salinity andt• Results are shown in figures 3.1 and 3.2 of the east-west (u) and north-south (v)current components, respectively. The t series is shown in figure 3.3. Note that thedensity range shown at each depth is identical with the exception of the 2 m series whichis shown over a larger range.Chapter 3. Results and Analysis 25Processed u Current Time Series40 60 80 100Julian dayFigure 3.1: Processed u current time series at NAN 20, 1992.Chapter 3. Results and Analysis0c’J0Co00cJ0c’J0Eo00c10c.J00,EoC)00C..J0Eo00cJ00Eo00Processed v Current Time Series2640 60 80 100Julian dayFigure 3.2: Processed v current time series at NAN 20, 1992.Chapter 3. Results and Analysis 27CMC)CMCMCMCM0CMC,)CMCMCMProcessed SigmaT Time SeriesJulian dayCMCM0CMC’)CMCMCMCM0CMCMCMCM40 60 80 100Figure 3.3: Processed o (kg/rn3)time series at NAN 20, 1992.Chapter 3. Results and Analysis 28Harmonic AnalysisFourier spectral analysis gives a frequency spectrum from a time series. The spectrallevel at a given frequency is a measure of the energy present in the record at that frequency. For the current data the frequency spectra are expected to have high amplitudesat the astronomical forcing frequencies responsible for tides. Therefore, amplitudes atthe known forcing frequencies were calculated from these data and subtracted at eachdepth without doing a full spectral analysis. The calculation of the amplitudes of expected frequencies is known as harmonic analysis. Linear matrices were used to do thecomputation as the tidal constituents are orthogonal. The matrices are:[A][T] = [D] (3.1)[D] is the matrix of observed data and [A] is the matrix of amplitudes to be solved for.[T] is the matrix of known tidal constituents. It was expanded in terms of sin and cosfunctions with a first order polynomial added to represent the mean and the trend. Thetidal constituents that were used in the analysis are shown in table 3.1 along with theirrespective periods. The matrix [A] was found using standard matrix techniques as inGodin [10]. The method of singular value matrix decomposition used was that of Presset.al. [24]. The larger amplitudes in the u current direction determined in the analysisare shown in table 3.2 for all depths.After [A] was found, the tidal contribution was subtracted from the record at eachdepth, with the exception of the mean, the trend and the MSf and Mm constituents.The resulting currents were used for all of the following analyses. They are referred toas residual currents.Chapter 3. Results and Analysis 29Tide Description Period, (hours)Mm Lunar Monthly 661.3MSf Lunar solar fortnightly 354.4O Principal lunar diurnal 25.82K1 Luni-solar diurnal 23.93N2 Large lunar elliptic 12.66M2 Principal lunar 12.42S2 Principal solar 12.00MK3 Lunar solar tridiurnal 8.18M4 Quaditirnal 6.12Table 3.1: Tidal constituents used in the harmonic analysis.Tidal constituentDepth MS1 01 K1 M2 S22 1.02 0.97 1.04 2.17 1.454 0.89 0.73 2.01 3.43 1.377 1.31 0.79 2.18 2.51 0.5212 0.40 0.92 2.08 1.83 0.3620 0.78 0.88 1.44 2.69 1.02Table 3.2: Amplitudes (cm/s) of the stronger tidal constituents of the u current.Chapter 3. Results and Analysis 30SmoothingHarmonic analysis assumes that the amplitudes are independent of time and effectivelycalculates an average amplitude for each frequency. Amplitudes often vary with timehowever. As a result, high frequency energy may still be present after the estimated tidalconstituents are subtracted. Also there may be noise still present in the record.The residual current record was low-pass filtered to remove any such remaining highfrequency energy. A moving 25 hour average was used. Current data were now smoothed,non-tidal, averaged hourly values. The results are shown in figures 3.4 and 3.5 for uand v respectively. Records were later gridded to 3 hourly values for cross-correlationswith lighthouse winds.WindWind data were run through a similar processing sequence to the current data. A certainamount of formatting was first necessary to make all wind records compatible with currentdata and its software. Raw data were converted to standard units using calibrationconstants for the meteorological station. Wind direction was calculated from the mooringcompass and the anemometer wind vane. This record was then formatted and time wasadded. The lighthouse data came from Environment Canada with wind speeds in knots,time in GMT and with the meteorological direction convention. Directions and timewere adjusted and split into two files, one for each location. All times were in terms ofdecimal Julian day.The next step for the anemometer data involved a process similar to the averagingdone with the current records. The anemometer data was first hand edited to removespikes that persisted over more than an hour (such as a two hour sudden wind of 140m/s). Hourly values were then computed from the 10 minute record by discarding theChapter 3. Results and Analysis0U)CoC)00U)CoC)00U)CoC)00U)F00U)COC)0Filtered Residual u Current Time SeriesJulian day31Figure 3.4: Filtered residual u current time series at NAN 20, 1992.40 60 80 100Chapter 3. Results and AnalysisU)00U)U)0U)0c)U)0U)0U;>U)00U)00Filtered Residual v Current Time SeriesJulian day32Figure 3.5: Filtered residual v current time series at NAN 20, 1992.40 60 80 100Chapter 3. Results and Analysis 33two highest and two lowest values in each window and averaging the remaining three.Two values were removed on either side instead of one as in the case of the current databecause the anemometer record had much more high frequency noise. Unlike the S4data, the velocities were not vector averaged. Wind speed was averaged while directionwas taken as a spot reading. The 10 minute values were determined by averaging theresolved components of two consecutive readings on either side of the interval.vn.u = ---(sznO + szn6_i) (3.2)vnv = --(cosO + cosO_i) (3.3)The angle 8 is the true direction recorded as a spot reading and V is the average speed.The subscript n dellotes the sample number. The determined east-west and north-southvelocity components are u and v respectively.The lighthouse data were manually recorded. The record had 3 hourly values withoccasional missing blocks of data, as much as 36 hours. Where only one datum wasmissing it was added by linear interpolation. Where a large block was missing, it wasreplaced with zeros so that uniform time steps were maintained throughout the record.A complete time series was needed to do cross-correlations. Note, when records witha block of zeros were correlated with others, zeros were placed in the second record tomatch and thus not affect the correlation.All of the wind records were gridded and filtered. A 25 hour running average wasused for the hourly winds and similarly, the 3 hourly lighthouse data were averaged over24 hours. All files were then gridded to 3 hourly values.3.1.2 Wind correlations between lighthouses and the mouth of Nanoose bayAs mentioned, the anemometer only functioned for the last 30 days that it was deployed,from day 70 to day 100. Unfortunately during the missing part of the record the windsWind time series for NAN 20 and Ballenas lighthouse, 1992Julian dayFigure 3.6: Wind time series for Ballenas Island lighthouse and Nanoose bay mooring.and currents were the strongest. To replace the missing portion, wind data from Ballenasand Entrance lighthouses were examined. Lighthouse records also had the advantage ofbeing available for the 1993 season; therefore any comparisons made with wind datawould be uniform for both years.Both Entrance and Ballenas islands displayed fairly high positive correlations withthe anemometer data. Lagged cross-correlations were done using Splus software [26].A 3 hour time step was used. The time series for both u and v components as wellas the magnitude of the wind velocity between lighthouse and anemometer data wereChapter 3. Results and Analysis 34u direction0S0S00CDE0S0SE0L NAN 20 IBallenas0- 70 75 80 85 90 95 100I I I0Sv direction75 80— NAN2OBaflenas-_J_70 85 90 95 100Chapter 3. Results and Analysis 35First data set Correlation Time lag (hrs) Second data setBallenas u 0.86 0 Entrance uBallenas v 0.79 0 Entrance vBallenas u 0.74 0 NAN 20 uBallenas v 0.54 0 NAN 20 vEntrance u 0.69 0 NAN 20 uEntrance v 0.62 0 NAN 20 vTable 3.3: Maximum wind cross-correlations.compared. The data were not rotated, thus u and v were east-west and north-southcomponents respectively. Nanoose bay is oriented in an east-west direction, thus theu direction is of primary interest as it is in and out of the bay. In this direction thwind correlation was the highest with the Ballenas Island data. Ballenas wind data weretherefore used throughout the rest of the analysis. Figure 3.6 shows the filtered BallenasIsland wind data with the filtered anemometer data over the 30 day time period for bothu and v. Correlation values are shown in table 3.3. Note that the time periods are notuniform for all correlations. Ballenas and Entrance lighthouse records were correlatedover days 27 to 100 to match the current record. Correlations with NAN 20 were overdays 70 through 100, the length of the NAN 20 record. A positive time lag correspondsto the first data set leading the second.3.1.3 Relationship between wind and current residualsOnce high frequency and tidal energy had been removed from the records a certainamount of low frequency energy remained. Much of the remaining energy was originallyexpected to be due to wind. If this were the case a correlation matrix would have beencalculated so that 1993 currents could be extrapolated from 1993 wind data. The extrapolation would have been used to provide advective information for the 1993 analysis.Cross-correlations of wind and current at different depths however did not yield strongChapter 3. Results and Analysis 36maxima at any time lag between the two records. As above Splus software [26] was usedfor all cross and auto-correlations. The records used in the analysis had gone through anidentical sequence in processing with the exception of harmonic analysis.First relationships between the Ballenas wind and currents at all depths separatelyfor east-west and then north-south directions were investigated. The cross-correlationswere low. Maxima in the u direction occurred for time lags between the two on theorder of 10’s of hours with negative and positive correlation values of less than 0.4. Thetime lags associated with these maxima were negative however, implying that the windwas lagging the current. In the v direction results were a little more as expected. Thecorrelations were all positive and had maxima at time lags of 0 to +3 hours, with theexception of the 20 m current. The correlation values were not high however. The largestvalue was 0.32 at 4 m.A correlation between the magnitude of the velocity at 2 m, where the influence ofwind was expected to be the greatest, and the magnitude of the wind at Ballenas wasequally poor. It had a very flat time lagged cross-correlation series with the maximumat 0 time lag. This poor correlation showed that when the wind was strong the currentwas not necessarily strong in any direction.Although it appeared that wind and current were poorly related, the data were rotatedto see if the correlations would improve. Contributions to the current by the wind neednot be in the same direction as the wind. Also wind and current at the mouth of the bay(inside NAN 20) may not be in the same direction as at NAN 20. Wind in the Strait ofGeorgia obviously tends to blow northwest or southeast. Thus east-west and north-southcomponents have roughly the same variance. Topographic effects could be funneling thewind and affecting its direction in and out of the bay. Observations in the field duringthe experiment support this idea. A wind from the southeast appeared to blow forciblystraight into the bay (westward) at the mouth. In a wind from the northwest the bayChapter 3. Results and Analysis 37was much more sheltered. Bathymetry could affect currents in the same manner. Thelocation of the mooring at NAN 20 was also a consideration. Measured currents wereprobably affected by currents flowing up and down the Strait as NAN 20 is just beyondthe mouth of the bay. To consider these possibilities principal axis rotations were done.Principal axis rotationsA principal axis rotation rotates vector data such that the variance in the data is ata maximum along one axis, the principal axis, and a minimum along the other. Theequation relating the variance in one coordinate system to the new one under a rotationof 0 is:= iUcos20—— )sin20 (3.4)The primes denote the rotated components and the overbars averages. To minimize thevariance in one direction (and thus maximize the variance perpendicular to that) ?? isset equal to zero yielding:1 2iiY0 = —arctan(_—) (3.5)2Here 0 is the angle of rotation to put u, v data into its principal coordinate system.Angles were calculated and subsequent rotations done for all data. Results are shown intable 3.4. The ratio of the variance along the principal axis to the variance perpendicularto it after the rotation (equation 3.6) is also presented in the table.Variance ratio= (=) (3.6)v,The ratio indicates how isotropic the record is. For a completely isotropic situation thevariance ratio would be one.As expected wind data from Ballenas had a strong principal axis in the northwest,southeast direction. Current data however were more isotropic with almost as muchChapter 3. Results and Analysis 38Location Angle Variance ratioBallenas -39deg 8.12 m current 8ldeg 1.84 m current -32deg 1.37 m current -26deg 2.212 m current -43deg 3.320 m current -7deg 5.9Table 3.4: Angles for principal axis rotations for 1992 current and wind data.variance along the calculated principal axis as along the perpendicular axis, with theexception of the 20 m data. The maximum currents at 20 m were in and out of the bayas expected within the channel due to bathymetry. Note that although the angles ofrotation vary greatly amongst depths in the current data, they have little meaning dueto the isotropic nature of the currents.To fully investigate possible wind effects, cross-correlations were done between allpossible combinations of the principal component of wind at Ballenas and current dataat all depths. Also rotations were done of 2 m currents in 10 degree steps over 180degrees and the resulting u was compared to the principal wind. In this way all possiblerotations were considered. Note that the rotation is not sensitive to small changes in 0as the derivative of the cos function with respect to 9 is very small for small dO, thus 10degree steps provided sufficient resolution.The results confirmed the lack of correlation between wind and current at the mouth ofNanoose bay. The highest correlation values were found between the principal componentof the wind and the north-south current components. The values were around 0.5 withno time lag (table 3.5). This correlation corresponds to a wind blowing to the north westcausing a northerly flow. In the u direction however the maximum correlations occurredwith negative time lags indicating that the current was leading the wind at those maxima.Values were around 0.4 as they were before the winds were rotated (table 3.5). WithChapter 3. Results and Analysis 39First data set Correlation Time lag (hrs) Second data setBallenas u -0.27 -15 2 m uBallenas v 0.31 3 2 m vBallenas wind speed 0.39 -3 2 m current speedPrincipal Ballenas 0.28 -9 2 m uPrincipal Ballenas 0.52 0 2 m vPrincipal Ballenas 0.41 -9 4 m uPrincipal Ballenas 0.55 0 4 m vPrincipal Ballenas 0.42 -6 7 m uPrincipal Ballenas 0.52 0 7 m vPrincipal Ballenas -0.40 -30 12 m uPrincipal Ballenas 0.53 0 12 m vPrincipal Ballenas -0.23 -21 20 m uPrincipal Ballenas -0.32 -33 20 m vTable 3.5: Maximum wind and current cross-correlations.the exception of the 12 and 20 m correlations, values were positive. Here the positivesign indicates that a wind blowing from the northwest is related to a current travelingwestward into the bay. This result seems to indicate that there is no strong relationshipbetween current and wind that can be found with cross-correlations. The time series ofthe principal component of the Ballenas wind with both components of the 2 m currentare shown in figure 3.7.The time-lagged auto-correlations of the north-south current components were veryflat showing little periodicity with the exception of the current at 20 m. This currentshowed some periodicity in auto-correlations at roughly 2 and 4 days, although the amplitudes were low. These periods are often associated with weather fronts.Cross-correlations are done in the time domain. It is recognized that a comparisonbetween records in the frequency domain (coherence analysis) can provide a more complete relationship as destructive interference between signals that are not in phase mayoccur in the time domain. At this point a coherence analysis was not done as it appearedthat it would not improve results sufficiently to provide a predictive relationship betweenChapter 3. Results and Analysis 40Principal wind time series for Ballenas lighthouse with 2m currents, 19920LC)— 0 .vdirechon- •1 00I I I I40 60 80 100Julian dayFigure 3.7: Time series of the principal component of the wind for Ballenas Island lighthouse and 2 m currents.Chapter 3. Results and Analysis 41residual current and wind.The conclusion of this investigation was that the near surface residual circulation inthe Strait of Georgia is complicated. It could not be described only in terms local windforcing. As a result an extrapolation of current data from wind data for the 1993 seasonwas not possible.For all following considerations involving current, the east-west component, essentiallyin and out of the bay, was used.3.1.4 Advective exchange between Nanoose bay and the Strait of GeorgiaThe purpose of having an array of current meters at the mouth of Nanoose bay was toestimate advective exchange between the bay and the Strait. This estimate was done todetermine if phytoplankton could be carried out of the bay and possibly seed the Strait.Thus the velocity in the advective term in equation 1.13 was provided. Also a flushingtime for the bay was estimated to determine its potential for phytoplankton growth.To get an overall picture of the net transport during the study period a runningintegral, f u(t)dt was calculated for the entire record at each depth. Here u is theresidual velocity and dt is 1 hour.Nettransport(t) = ju(t)dt (3.7)This running integral was then plotted against time and is shown in figure 3.8. It wasalso hoped that the net transport would yield information about the residual circulation.The integral plotted against time is cumulative. It has units of length, shown as km infigure 3.8. This measure represents a volume flux when multiplied by the cross sectionalarea perpendicular to the current direction spanning the mouth of the bay.The most notable feature in figure 3.8 is that the net transport at 4, 7 and 12 m isinto the bay. At 2 and 20 m fluctuations add over time to yield a net transport nearChapter 3. Results and Analysis 42Net Transport Time Series40 60 80 100Julian dayFigure 3.8: Net transport plotted as a running integral with time. The positive directionis eastward (out of the bay) and the negative direction is westward.Chapter 3. Results and Analysis 43zero, although at different times during the record there was appreciable transport inboth directions. Note the much smaller length scales on the y axis at 2 and 20 m. At2 m it seems that wind and other effects cause fluctuations that cancel one another. At4, 7 and 12 m however it appears that the residual circulation was generally into thebay. The density time series suggests that water flowing inwards tends to be less saline.The possible relationship between current direction and density changes with time isinvestigated in section 3.1.6.When net transport at all depths was added together mass continuity was not obeyedas the data show net inward transport. The array of current meters obviously did notmeasure all transport in and out ot the bay, probably because the array was not deepenough. There must be transport out and it is assumed to be at depth, although it isgenerally not seen at 20 m. There were however several periods of strong inflow at themiddle depths where outflow was seen at 20 m, for example around day 56 and againaround day 68. This outlow at 20 m can best be seen in fig 3.9 which is discussed in thenext section. The depth of the shallowest part of the mouth of the bay is 20 m, howeverthe mooring was located in 50 m of water. To account for water coming out of the bayit is suggested that deeper water in the bay is often more dense than water outside atthe same depth. The dense water moves over the 20 m sill and then sinks down as itflows out because it is more dense than the surrounding water and thus is not detected atthe mooring. Secondly, it is possible that there is cross-channel variation in the current.This variation may also account for some of the outflow that is not observed in the massbalance at the mooring location.3.1.5 Flushing and stabilityThe running integral j u(t)dt vs. time shows that transport in one direction is oftenmaintained over a time period long enough for several or more km to pass consecutively.Chapter 3. Results and Analysis 44Using the length of the bay and scaling by a width factor (Wth) to account for strongerflow through the narrows, a distance of 5 km was determined to be a reasonable for onecomplete flushing. For each depth in figure 3.8 a L J u(t)dt of 5 km or more thereforerepresents a flushing of the layer at that depth.Using this distance as a limit, an index was determined. If the bay is flushed ina time scale faster than the generation time of phytoplankton, an increase in primaryproductivity will not occur in the bay. The index also shows the direction of advection,in or out of the bay, in each layer during the flushing event.This index was calculated by using a running integral as in the case of the net transport. The integral starts at t1 and continues adding u(t)dt until 12, when the distance of5 km is reached or just exceeded. The index was then calculated by dividing the integral(5 km or greater) by the time interval that it was calculated over as follows.1 pt2Flushing Index= J u(t)dt (3.8)t2—tl tlIt was calculated as a function of t1. Once the sum of u(t)dt added to 5 km andan index was calculated, the integral was set back to zero and restarted from t + dt.Therefore for each time in the record there is a corresponding index. Note that the indexis associated with the beginning of the time interval, thus it indicates flushing for thetime period immediately following it.A large flushing index corresponds to a complete exchange in a short time intervaland an unfavourable period for phytoplankton growth. A small index indicates a longtime interval for exchange and thus a favourable period for phytoplankton growth. Anegative flushing index corresponds to inflow so that seeding of the outside waters fromthe bay is not possible. Such trapping of phytoplankton could allow a bloom in the baywhich could be a source for seeding sometime later.Chapter 3. Results and Analysis 45Flushing Index Time SeriesiH80 100ZEJ.E0. 40 80 10012 mJulian dayFigure 3.9: A phytoplankton flushing index,---f u(t)dt, as a function of t1 for eachdepth.Chapter 3. Results and Analysis 46Figure 3.9 shows the flushing index as a function of time for each depth. The indexhas units of velocity and was calculated in km/day. Considering the doubling time ofphytoplankton to be around 2 days, a flushing index with the magnitude of 2.5 km/dayprovides a ceiling for phytoplankton growth. This ceiling is shown in figure 3.9. Althoughat depths of 4 and 7 m there was generally an appreciable constant inflow, at 2 m, whichis where plankton was sampled, there were four periods which appear to be favourablefor phytoplankton growth. The periods are; days 38 through 43, days 45 through 56,days 57 through 64 and days 68 through 89. Note that during two of the four timeintervals (the first and the last) defined by the 2 m index, transport was out of thebay. During the middle two intervals transport is into the bay and these periods aresubsequently terminated by high negative flushing indices. Note that the 4 m flushingindex indicates a favourable period over days 45 through 55 and relatively favourableover days 68 through 89 (although during the latter period the index creeps below the-2.5 km/day ceiling on two occasions and is of the opposite sign of the 2 m index).The index quickly indicates ranges of flushing times. The integral is only assignedto a time when enough water has passed at that depth to cause one complete exchange.Therefore each (t2 — t1) is a flushing time. The plots in figure 3.9 show that under thisanalysis the bay can be flushed in a time scale of the order of days. Near the beginningof the record the index reaches its maximum at 2 m suggesting that a volume exchangecan occur in as little as one day in the upper layer. During the period beginning at day70 however (t2 — t1) becomes several weeks.3.1.6 Density changes and current directionThe predominant inflow in the middle layers at the mooring prompted an examination ofthe density of the incoming water. The assumption was that it was lower density brackishwater, which is ultimately from the Fraser River, that was flowing in. The density time0c’Jc’J0c’J00c’J0c’Jc’J0c.J00c’JU,c’Jc’J0U,CUqCUCUC”0C.)CUU,U’o.0Figure 3.10: Filtered a (kg/rn3)time series shown with the flushing index at each depth.series at the mooring confirmed this assumption.Filtered at at each depth is shown in figure 3.10 with the flushing index to indicatethe direction of appreciable volume transport. During periods of strong inflow the changein density with time often was negative. After an appreciable inflow the water at a givendepth was less dense. Examples are seen around days 36, 56 and 69 particularly at 4 and7 m. Likewise, during outflows the density change with time was often positive, althoughpositive changes in at also occurred during periods of little or no outflow, (for exampleChapter 3. Results and AnalysisFiltered SigmaT Time Series470o00100>,0 .400CUCU0CU20 m80 10040 60 80 100Julian day:10the large increase in t around day 42).Figure 3.11: at7 (kg/rn3), at NAN 20 from the mooring and CTD profiles.As no current data were measured in 1993 and no relationship between current andwind was found to allow an extrapolation for 1993 currents, it was desired to find a meansof indicating at least the probable current direction with no direct measurement. To doso, the density time series at 7 m was chosen. Its signal was strong while having lesshigh frequency noise than the 2 and 4 m time series. The signal to noise ratio becameimportant as in 1993 only spot t7 values were available via CTD casts, instead of acomparatively continuous record as in 1992.A comparison between t7 at the mooring and the flushing index (see figure 3.10)showed that during the 1992 season large volume transports into the bay were correlatedwith decreasing ot7.In 1993 therefore, although density profiles are much different than in 1992, thechange in O7 with time was used to suggest current direction. Figure 3.11 shows o as afunction of time for both 1992 and 1993 with the continuous density time series from themooring. Note that the CTD spot measurements are indicated by points (which weresimply joined by a straight line). The 1992 CTD data follow the 7 m mooring recordChapter 3. Results and Analysis7 m SigmaT at NAN 2048c’.JC.,C”C”C”C”0C”1993CTD—...• .•— 1992 mooring1992CTD40 60 80 100Julian dayChapter 3. Results and Analysis 49well. CTD measurements such as on day 35, which do not lie on the mooring curve aredue to the fact that the mooring data has been smoothed by 25 hour averaging. It isrecognized however that the information between CTD measurements is unknown. Notethe period between day 59 and 64 in 1992. The CTD data do not show the drop in o’that the mooring does. In 1993 however the sampling interval was half of that of 1992so there is higher temporal resolution. Figure 3.11 also shows the large difference in tbetween years. Fluctuations appear to be much smaller in 1993 and overall o higher.3.2 Density profilesVertical density profiles were sampled using an S4 current meter as a CTD. These profilesprovided snapshots in time of density structure for each day that sampling was done ateach station.Estimating the extent of vertical mixing in the water column is essential in evaluatinggrowth conditions and understanding why a bloom may occur in some places and notin others. Different locations can be compared in terms of their growth potential. Onecan also determine whether or not the depth of the bay limits the vertical mixing ofphytoplankton and thus allows a bloom to occur earlier at that location.Initially the mixed depth was estimated from each profile to represent the extent ofvertical mixing for phytoplankton. The mixed depth approach proved inadequate giventhe data set. Instead some parameters were developed from the time series of densityprofiles to indicate the degree of mixing of the water column and thus potential increasesin phytoplankton concentration. The different methods used in this analysis, successfuland not, are presented in the following sections.Chapter 3. Results and Analysis 503.2.1 Mixed DepthOriginally the intention of measuring density structure was to allow estimation of themixed layer depth. Given this estimate along with the critical depth, the Sverdrupcriterion for a spring bloom could be considered.In viewing the density profiles on different days it was realized that the mixed depthwas not always obvious. Profiles were usually much more complex than two fairly homogeneous water masses with a large density gradient separating them. Density structurediffered radically depending on day and location. An objective means of determiningthe mixed depth for all profiles was desired, which led to the use of the Freeland andFarmer approach [9] as described in Chapter 1. Density profiles were integrated anddifferentiated to provide measures of both the potential energy and the buoyancy frequency as in equations 1.3 and 1.5 respectively. Buoyancy frequency profiles were thenused to solve for the eigenvalues in equation 1.4 through a series of iterative integration(deYoung [30]) and thus obtain the first mode internal wave speed. Both up and downcasts were used and the results of each were averaged. Although the approach provideda uniform method to look at all types of profiles, it failed in addressing the pertinentquestion: where were phytoplankton in the water column?For many profiles the two-layer fit was inappropriate to the given density structure.Where a solution was possible, internal wave speeds were in the range of 10 to 20 cm/sand potential energy parameter (x) was around 10 to 12 kg/rn3. Three very differentrepresentative profiles are presented in figure 3.12 with the results of the mixed depthcalculation and a discussion as to why or why not they may represent the depth to whichphytoplankton are mixed. All are from NAN 10, the station inside the bay.Results were reasonable for the April 6, 1993 profile shown in figure 3.12. The approach predicts a mixed depth of 9.5 m, which is a bit larger than an intuitive evaluationChapter 3. Results and Analysis 51of about 8 m. This type of profile was the exception within the entire data set. Thefollowing two structures are representative of those that occur more often.The second example was taken on February 11, 1992. The surface layer in this caseis quite stratified. Mixing would be inhibited and if this profile were to persist overtime, phytoplankton could be confined near the surface. The model fits the profile to astructure such that the top layer is 1.8 m and a2 is 22.0 kg/rn3 when a1 is from 1.5 minstead of from 2 m. Note that a1 was changed so that the equations could be solved andthe profile fit to the model. The estimated mixed depth is consistent with phytoplanktonbeing kept near the surface.A third profile from March 4, 1993 indicates a uniformly stratified situation. Thetwo-layer model fails in this case yielding a non-real value for h, the thickness of theupper layer. The failure could be interpreted as mixed to the bottom in a single layer.This interpretation would imply that phytoplankton were mixed at least to the bottomof the cast, which may be the case. There is still a small uniform density gradienthowever which could be enough to prevent turbulent mixing. The vertical shear of thehorizontal velocity necessary for turbulence was considered to determine whether or notphytoplankton were being mixed throughout. This consideration is the topic of the nextsection.3.2.2 Density Gradients and Velocity ShearIn determining the depth to which phytoplankton are mixed, results of the two layermodel may be questionable or ambiguous. Density gradients still exist within the regionthat is assumed to be well mixed. The Richardson number, as defined in equation 1.7,was used to estimate the velocity shear necessary for turbulent mixing to occur giventhe density gradient from the experimental profile. R greater than 1/4 is requiredeverywhere in the fluid to ensure laminar flow. The velocity shear calculated using thisChapter 3. Results and Analysis 5222 22.90 23.00 23.10 23.20SigmaT10. Note that both the up and the05I10512Apria 6, 1993NAN 10I I IFeb, 111992NAN 10I I0-March 4, 1993NAN 105.——2 -I I I I I I22.4 22.6 22.8 23.0SigmaT23.2 20 21SigmaTFigure 3.12: Representative density profiles at NANdown casts are shown.Chapter 3. Results and Analysis 53number therefore represents a lower limit necessary to ensure that phytoplankton are notbeing mixed over the region in question. Since occurs as a square in the Richardsonnumber, only the magnitude will be considered. If the true velocity shear is greater thanthat calculated, then turbulent mixing is occurring.An upper limit for the true velocity shear was set by comparing the raw hourly velocitymeasurements from the mooring data at 2 and 4 m. During the first two weeks of therecord where the variance was higher, ranged from 0-7 cm/s/m, but was less than orequal to 1 cm/s/m approximately 70% of the time. In the latter part of the record (day70 onward) J- ranged from 0-3 cm/s/m, and was less than or equal to 1 cm/s/rn over80% of the time. Velocity shear between 4 and 7 m was generally smaller by a factorof two. The limit in velocity shear determined to be reasonable in the study area atthis time was set at 1 cm/s/rn. Thus it will be assumed that any structure associatedwith a necessary for turbulence that is greater than 1cm/s/rn is not being mixed.Note that this limit is only used where the uncertainty in the estimation of the densitygradient allows. The uncertainty was determined by simply estimating the maximumand minimum gradient from the data subjectively. This estimate was made by using anyscatter or noise in the cast as well as differences due to reproducibility between the upand down casts.The resulting velocity shears (necessary for R, = 1/4) for different profiles are shownin table 3.6. Note that the presented in the table was calculated over the estimatedmixed layer depth which is also shown in the table. Profiles that were apparently mixedto the bottom of the cast are listed in the table with B for the mixed depth. All castsexcept at NAN 30 in 1993 were done to about 20 m, depending on line angle. On someoccasions casts are 1 or 2 m shallower where it was difficult to maintain position. In 1993NAN 30 casts were done to 40 m. Where weather did not permit sampling, dashed linesare shown in the table. Only the results for the NAN 10 profiles that are presented inChapter 3. Results and Analysis 54this chapter along with the results for stations 20 and 30 on the corresponding days forcomparison are shown. These results represent the overall range.NAN 10 NAN 20 NAN 30J day h (m) (cm/s/rn) h (m) (cm/s/rn) h (m) (cm/s/rn)1992Feb 4 35 3.4 335 4.0 285 — —Feb 11 42 1.6 12f3 4.1 4.00.5 4.3 12j4Feb 18 49 2.3 204 3.8 10t2 7.1 4t1Feb 25 56 <1 30j5 4.3 224 11 7t21993Feb 22 53 B 2t2 B 21 B 11Feb 25 56 B <ltO.5 B <lj:0.5 B 1j1March 1 60 B 2jl B 2j1 —March 4 63 B 2jl 12 21 B 1j1April 6 96 9.7 1.0j0.5 6.7 <1.00.5 19.8 21Table 3.6: Values of dU/dz are calculated from the Richardson number (R=1/4) usingexperimental density profiles to determine the Brunt Vaisala frequency.3.2.3 Temporal changesThe full approach considering the density structure in terms of necessary velocity shearwas still inadequate in predicting favourable enough situations for the occurrence of aspring bloom. For example, in the 1992 data set each density profile was stratifiedenough to suggest that a bloom should occur throughout the study period under theabove analysis. Nutrients were certainly not limiting, and given the vertical structure,light was not limiting either. In 1993 profiles often had small density gradients that wereconstant to the bottom of the cast (see table 3.6). Velocity shears required for turbulentmixing were generally as low as the 1 cm/s/m limit within uncertainty and thus assumedto be well mixed. In 1992 phytoplankton concentrations were low however, and in 1993they were high in the bay throughout the study.Chapter 3. Results and Analysis 55The profiles are spot measurements. Nothing is known about the temporal variability.Time scales necessary for phytoplankton to reproduce must be considered. To includethis variability the time series of the profiles at a given location were examined. Twogeneral parameters were used to do so. First the change in the mean density gradientover the entire profile with respect to time was calculated.p1 = /Tt) (39)Note that as z is depth positive downward, the more stratified the water column becomesthe more positive () is. Second the change in t at 20m (the lower limit of mostcasts) with respect to time was considered.= (cTt2o) (3.10)The change in density gradient showed whether a structure was becoming more orless stable through change in overall stratification. A non-negative value of () wastherefore considered a necessary stability criterion for non-mixing conditions.The density at 20 m was used to indicate whether or not the same water mass waspresent. A large change in t2O would indicate new water and thus unfavourable growthconditions. The magnitude of (Ut2O) was required to be less than an upper limit for abloom to be possible. The upper limit was set at 0.05 kg/m3/day using the 1992 results.This limit was determined using profiles from NAN 20, the location of the mooring, sothat direct comparison with the mooring record would be possible. Profiles were chosenover a time period in which stratification increased and also when a large increase inphytoplankton concentration was observed. The time period used was day 70 through75. The change in ot20 is thought to correspond to an increase in stratification as opposedto a new water mass. The change could also be due to a slow exchange of water. Notethat the sign of (Ut2O) was positive, while water at the surface became slightly lessChapter 3. Results and Analysis 56dense (see figure 3.10). The current data show that volume transport at this time wasvery low (less than 10% of the bay’s volume per day) and the o time series show littlevariation.Both of these parameters were required to indicate conditions necessary for a bloomto occur. Profiles from two favourable growth periods under this analysis are shown infigure 3.13. They are representative of the respective years that they were taken. In1992 vertical structure in the bay was generally stratified while in 1993 profiles tended tobe mixed and more saline throughout. Both situations in figure 3.13 however were stablewith time. The 1992 example shows profiles spanning 7 days starting on February 18(day 49). The net stratification increases during the period with the addition of brackishwater at the surface while there is little change in structure below 4m. The secondplot however indicates a very different situation that is favourable considering temporalvariability of the two parameters defined above. The structure appears to be well mixedthroughout the period spanning 4 days beginning on February 25 (day 56), 1993. Therewas a slight positive change in net stratification with time and (Ut2O) was essentiallyzero.Figure 3.14 shows two very different poor growth periods inside the bay under thiscriterion. The first period suggests mixing while the second suggests flushing. The 1992profiles are separated in time by one week. The earlier profile from February 4, (day35) is well stratified with a large . One week later the density structure changedconsiderably. It is mixed with respect to the first and there is a large change in thedensity of the water at the bottom of the cast. It is much less dense. The secondexample from 1993 is also from the inside of the bay. Here the time between casts isonly 3 days beginning on February 22 (day 53), 1993. In this case the change in netstratification is small but still negative. There is a change in Ut20 however as the waterin the bay becomes more dense throughout the water column.Chapter 3. Results and Analysis10Favourable5719 20 21 22SigmaT SigmaTFavourable05-NAN 1015 -0—NAN 105—15-Feb25,1993— Marchl,199320- -I I I IFeb18 1992Feb25, 199220 -I I I22.6 22.8 23.0 23.2Figure 3.13: Density structure time series: for two favourable intervals.Chapter 3. Results and Analysis 58Unfavourable Unfavourable0..... 05- 5-NAN 10 NAN 1010- 10—ci’ :.U ..... U15- 15—Feb4,1992 Feb22,1993— Febll,1992 Feb25, 199320- 20—I I I I I I I I I12 14 16 18 20 22 22.6 22.8 23.0 23.2SigmaT SigmaTFigure 3.14: Density structure time series: for two unfavourable intervals.Chapter 3. Results and Analysis 59The flushing index defined by the volume exchange as measured by current meterssupports this method and agreement between the two is discussed in the next chapter.Although nothing is known about variation during the time between profiles, these parameters successfully form a minimum requirement for phytoplankton growth. The 1992data are easily supported using the current data at the mooring when profiles were onlytaken once weekly. In 1993, when there are no current data, profiles were done twiceweekly yielding a temporal resolution that is of the same order as the generation timefor phytoplankton. The use of the two parameters therefore seems reasonable.Using these criteria blooms within Nanoose bay were predicted, which is the subjectof much of the following chapter.3.3 Critical DepthCritical depths, as described in chapter one, were estimated to measure light limitation tophytoplankton growth. Two sets of data were used; Secchi disc depth and solar radiation.3.3.1 Radiation dataIn 1992 there were some difficulties with condensation developing inside the bulb of thepyranometer. Condensation affected measurements by scattering some of the incominglight so that it was not detected. As a result there was a two week section in thestudy period in which a second pyranometer was also used. To scale the measurementsand make them compatible over the entire record two calibrations were done betweeninstruments, one in which both functioned with dry bulbs and one in which only one hadcondensation. It was found that condensation caused roughly 10% of the light not to bedetected. In 1993 the use of dry desicant in the pyranometers was perfected and no suchproblems occurred.Chapter 3. Results and Analysis 60Solar Radiation0c’J1992It)—••.• • •/\, /\,•_•• • • • •• • •\.• • • • • •••‘I•I• • •I• •: /‘ ...•f \/\\ /v\ /‘• \‘ .1! \\ /\/1.0- / • S./ ••o I I I I I I50 60 70 80 90 100Julian dayFigure 3.15: Jo and PAR as functions of time.Radiation was directly measured in mV and converted to standard units of langley/hrusing the instrument calibration. The time series of 10, which are 24 hr integrated values,is shown in figure 3.15 for both the 1992 and 1993 data.3.3.2 Secchi disc depth and critical depthSecchi disc depths were measured at all stations. The 1992 results are shown in figure 3.16and the 1993 results in figures 3.17 and 3.18. Decreases in Secchi depth generally coincidewith either an increase in phytoplankton concentration or a period of rainfall in whichterrigenous runoff is present. Both phytoplankton and terrigenous particles absorb andscatter light decreasing visibility.Secchi disc depths and radiation measurements were combined to calculate the criticalChapter 3. Results and Analysis 61Secchi disc depth vs.Time0c’Ja •.a) •./o /o •.—.——-.a, /cn - / NAN1O.0- I I40 60 60 70 800c’Jaa)- . •\ z N / \.,• •• •o /oa,ci - NAN2O0- I60 800 -C’)aa,• V . \ V• ••\/0 /LO NAN 300- I I40 50 60 70 80Julian dayFigure 3.16: Secchi disc depth as a function of time for NAN 10, 20 and 30 in 1992.Chapter 3. Results and Analysis 62Secchi disc depth vs.Time.—.----...V • .• NAN 10 ••.—.U)o I I40 60 80 100.—.—-0• NAN 12 —. ._0) .—..Cl)o • I I•_—•... 60 80 100— . — .• NAN 151) . — .U)o• I40 60 80 100• •_•___•\ ..•0•. . — .8° • NAN2O0) .Cl)o• I I I40 60 80 100Julian dayFigure 3.17: Secchi disc depth as a function of time for inside stations in 1993.Chapter 3. Results and Analysis 63Secchi disc depth vs.Time0a— .a)•V • ._______. — .C) •__•_.• NAN2OCoo Io 40 60 80 100•.U)•— • •a-a)• • — • •NAN25Coo • I I•• 60 80 100a- ••• — • •a) •• •0• NAN27Cl)o• I I•0. 40 / N\ 60 80 100•a- N —•\a)t,o• ••z•0NAN3OCo0’40 60 80 100Julian dayFigure 3.18: Secchi disc depth as a function of time for outside stations in 1993.Chapter 3. Results and Analysis 64depth using equation 1.1. Critical depths were calculated at two day intervals, the timescale chosen to match that of phytoplankton growth. A running two day average of I,was computed from the daily values. To determine 2 day Secchi disc depths a cubic splinewas calculated from the Secchi time series. A spline was used because the data were notuniformly spaced. Results of the critical depth calculation are shown in figure 3.19. Onlystations 10 and 30 are presented for each year. They will be used to represent criticaldepths inside and outside of the bay respectively.A minimum critical depth was estimated. Thus the value for I which was usedto calculate D was the upper limit, 0.54 langley/hr, of its range. Also the extinctioncoefficient (k) as determined from the Secchi disc depth was increased by a factor of2 as suggested by Dr. T. Parsons (pers. comm.). The defined extinction coefficientcorresponds to blue light (.X = 450 nm). Photosynthetically available radiation is madeup of the 400-700 nm band and has a much higher k as radiation with longer wavelengthsis absorbed in much shorter distances in water. Increasing k by a factor of 2 decreases Dby a factor of 2. The minimum critical depths were still large and generally suggest thatlight was not limiting given estimates of vertical mixing. The choice of I was probablytoo large. The range of I for different types of phytoplankton has been investigatedby Falkowksi [8]. He found that I varied by over four orders of magnitude for differenttypes of phytoplankton in a laboratory experiment. The most efficient users of light(and thus those with corresponding minimum I values) were diatoms. He used twodiatoms, Skeletonema costatum and Ditylum brightwelli, both of which were observed inand around Nanoose bay. These results suggest that the I used here was definitely toolarge.Although it was not possible to determine an absolute D with certainty, the minimumcritical depth shown here should provide a true relative measure.Chapter 3. Results and Analysis 65Critical depth vs. Time0Co— NAN1Oi. —. NAN3OS•-‘:/ \. .. —. So- \1992o- I I I I0CO• :0•••• •• • •. •— NAN 10 • •..• •/•• • .•• •NAN:/ \:Z.Z/ 13Julian dayFigure 3.19: Critical depth as a function of time for NAN 10 and 30.Chapter 3. Results and Analysis 663.4 Chlorophyll aIn 1992 chlorophyll a was measured on each sampling day and location and is shownin figure 3.20. Results are noisy mainly due to biological patchiness. Note at NAN 30on day 81 measurements were done in triplicate and results varied by over an order ofmagnitude. When a large increase in chlorophyll a concentration around day 75 wasobserved, it was not possible to determine whether it happened at one location anyearlier than the others. These data are too noisy and do not have high enough temporalresolution to be useful in this problem.In 1993, triplicate chlorophyll a measurements were taken at each station to improvethe signal to noise ratio. The three samples were averaged to produce the plots shownin figures 3.21 and 3.22. The standard error was calculated for each point and suggeststhat all values have a fractional uncertainty of about 40%.3.5 Species CompositionSpecies composition analysis was done to the genus level for each sampling date andlocation. Originally this analysis was done to back up the chlorophyll a data as a measureof primary production and also to ensure that the same types of phytoplankton werepresent at each location. Species within the seed population must bloom in the areasthat they seed.Counts of phytoplankton were found to have a higher signal to noise ratio than chlorophyll a data in 1992, where only one chlorophyll sample was drawn per location andtime. The small increase in phytoplankton over days 45 through 56 at NAN 10, seenmost strongly in Thalas.siosira spp., is not seen at all in the chlorophyll data. For thisreason phytoplankton cell counts were used in 1992 to represent C in equation 1.13.A table listing the dominant genera (species where possible) with its concentrationChapter 3. Results and AnalysisChlorophyll 1992 Time Series670c’JL)LC)00c’JLt)00c’JU)U)040 60 80Julian dayFigure 3.20: Chiorophylla as a function of time in 1992.100NAN 10• • — • I• . — . • — • — • — • r—NAN 20./\• ._._.__r••___.__..•_•___._.__•i_•___.___•._.NAN 30••/- .—•_•____•••___•__•._•_______•___•__•__•___•‘•__•Chapter 3. Results and AnalysisChlorophyll 1993 Time Series68CDC..J0CD(0c’J0CDCD(‘10CDCD(.‘J0NAN 15NAN 10/\I.. /\I — • VI. . — I. .NAN12 II I/\ A / /\•. •____I •.. I / .\/N.--.I./\—./—...NAN2OII.7 \ .—.• • I/ I•/ — I.____ II•._I•40 60 80 100Julian dayFigure 3.21: Chiorophylla as a function of time for the inside stations in 1993.Chapter 3. Results and Analysis 69Chlorophyll 1993 Time SeriesNAN 20(0/‘/•— ••. • .•.——‘ ••I I(0NAN 25N —./\•__________o •_,_•_• • I(0NAN 27(0/•\— • •— •—•— •.____-. \o •_____•7_._.___• •—•-—--•————-. s._..• •__.____r____.(0CD NAN3O•(N• / • \ • — • •o •__1.__.—40 60 80 100Julian dayFigure 3.22: Chiorophylla as a function of time for the outside stations in 1993.Chapter 3. Results and Analysis 700____/\— NAN 10 Skeletonema .E0 NAN20:8 —.— NAN3O //. ....o I • I —.40 60 100—NAN1O IlNAN2O/.— -— NAN 30 Chaetoceros / ...,I a a $I a a—40 60 80 100/NNAN1O / Nz. Thalassiosira / N NN/ \.. N: .0•NJulian dayFigure 3.23: Skeletonema costatum, Chaetoceros spp. and Thalassiosira spp. counts for1992.for each sample counted is presented in the Appendix.The 1992 full time series of Skeletonema costatum, Chaetoceros spp. and Thalassiosiraspp. counts are shown in figure 3.23. A plot is done for each genus and stations 10 20and 30 are shown together on each plot. The concentrations of each genus behaved ina similar manner at each station. Numbers were low, (0-10/ml) until around day 70when they began to climb steeply. There was however a slight increase around day 50inside the bay and at the mouth (NAN 10 and 20). Figure 3.24 shows this increase bycontracting the axes to look at only day 35 through 70, the time period before the fullChapter 3. Results and AnalysisNAN1ONAN2ONAN3Ooc’J04071Figure 3.24: Skeletonema costatum, Chaetoceros spp. and Thalas.siosira spp. counts for1992 before the onset of the spring bloom.00050 60 70Julian dayChapter 3. Results and Analysis 72Ii0000.NAN 10 /\\•/N/\40 60 80 100NAN 1240 60 80 100NAN15/—.. — — ••\. •40 60 80 100NAN2O/••_•\/\• /N/ . \ V040 60 80 100Julian dayFigure 3.25: Chaetoceros debilis counts for 1993, inside stations.spring bloom.In 1993 samples the dominance of one species was overwhelming. The species wasChaetoceros debilis and a time series of its concentration is shown for each station. Figure 3.25 shows the series for stations from the inside to just outside the mouth of the bay(NAN 10 through 20). The results for the outside stations are shown starting at NAN20 and progressing further from the bay to NAN 30 in figure 3.26.At the inside stations Chaetoceros debilis was present and dominant from the firstsampling date onwards. Concentrations rose between days 35 and 39 and subsequentlyChapter 3. Results and Analysis 73NAN2O/1 • —— \ / \ / N .\\• .o i40 60 80 100o NAN25E___/•_ ____. / .—- —.-—----.o •1— I40 60 80 100o NAN27z..o • • — . — — — . I40 60 80 100NAN 30p/•\__.._ .—— .••.—.— .I • . I40 60 80 100Julian dayFigure 3.26: Chaetoceros debilis counts for 1993, outside stations.Chapter 3. Results and Analysis 74.0 - . 0— Skeletonema . .. 80 Chaetoceros :U,.______...: ,.... -Eo •.. . .- NAN1O-.Oo .• .. . ...8 (U0 - • • 0-— Sk&etonema 8Chaetoceros 0E(U 8cE. co2aC00CsJo - 040 50 60 70 80Julian dayFigure 3.27: Skeletonerna costatum and Chaetoceros debilis counts for 1993, NAN 10 and30.peaked several times broken up by intervals where numbers dropped.On the outside, concentrations of Chaetoceros debilis were lower. Note that the samescale for vertical axes was used in both figures 3.25 and 3.26 so that a direct comparisonis possible between all time series. Day 39 was the first day that that the furthest outsidestation (NAN 30) was sampled. At this time no Chaetoceros debilis was found in thesample. By day 42 however Chaetoceros debilis appeared at all outside stations in muchlower concentrations than on the inside and was present throughout the rest of the studyperiod. A notable increase did not begin at NAN 27 and NAN 30 until day 89 and wassuppressed within the week probably by strong southeasterly winds in the Strait.Skeletonema costatum was present usually at very low numbers (0-10/ml) until day96 when counts increased at the inside stations to concentrations > 1000/ml and on theNAN 30Chapter 3. Results and Analysis 75outside to > 500/mi. A time series of Skeletonema costatum and Chaetoceros debilisbefore the large increase in concentration is shown in figure 3.27. Concentrations of bothspecies are shown on the same scales for each station. There were some higher countsof S. costatum on the outside compared to the inside, particularly at NAN 30, whereconcentrations were 40-60 cells/mi on days 46, 56 and 74 through 77. It is noted thatSkeletortema costatum makes up a much larger portion of the total number of cells onthe outside. On the inside concentrations of all other plankton are negligible comparedto Chaetoceros debilis.Thalassiosira spp. behaved much like Skeletonema costatum. Numbers did not increase above 10 cells/mi until the end of March and they reached the highest value of200-500/mi at all stations on the last sampling date. Again there were some slightlyhigher counts at the outside stations during the same time periods.3.6 NutrientsNutrients were sampled on each sampling day at each station. In 1992 nitrate, phosphate,ammonium and silicate analyses were done, while in 1993 only the first two concentrationswere analyzed.The main reason for sampling nutrients was to ensure that they were not limiting tophytoplankton before the spring bloom. Also a comparison was made between stationsto consider the motion of different water masses by using nutrients as tracers. The latterproved unreasonable as nutrients were generally very high everywhere until phytoplankton began to bloom and then dropped quickly, with the exception of phosphate.Nitrate concentrations from both years were high and typical for the Strait of Georgiaduring the winter and early spring (Harrison et al. [12]). Silicate concentrations werehigher than expected in 1992, although the time series is consistent. Concentrations ofChapter 3. Results and Analysis 76up to 60 M are not uncommom in the Fraser River, which is high in silicate. Withinthe Strait around Nanoose bay however this concentration is expected to be more dilutearound 20-30 tM, [12]. Phosphate concentrations were expected to be within the 2-3 iMrange, [12]. These data had intermittent spikes of up to 5 M however which suggeststhat some of the samples were possibly contaminated. Ammonium samples also appearto have been contaminated, as concentrations far exceed the expected range for surfacevalues (and ammonium is generally difficult to measure).Nutrient data are summarized in figures 3.28 through 3.33. The 1992 phosphateand ammonium time series are excluded due to apparent contamination. 1993 phosphatevalues are shown although several suspiciously high concentrations are present in someof the series as well.It is considered that nitrate becomes limiting at concentrations of 1 1iM, while phosphate concentrations are limiting at 1/16 of that, given the Redfield ratio (Parsons,Takahashi and Hargrave [22]). Using these limits, nutrients were not limiting at anytime throughout the experiment with the exception of nitrate at the inside stations atthe very end of the 1993 record. Phytoplankton growth was therefore limited initiallyby light and the stability of the water column throughout the study period during bothyears. Also sinking rates in equation 1.13 will be assumed constant and unaffected bynutrient concentrations.Chapter 3. Results and Analysis 77Nitrate 1992 Time Series0/\..I_•U) \ / : — NAN 10\IU)o I I I40 60 80 100U)cs INAN 20I .-.Zr\U) ..o I I I0. 40 60 80 100• .—..-.-o . ._..— —U). I NAN3OZr• .—.--.----.U).0•40 60 80 100Julian dayFigure 3.28: Time series of nitrate in 1992 for NAN 10, 20 and 30.Chapter 3. Results and Analysis 78Silicate 1992 Time Series./\0• •. ..— \ • \ —• — .NAN 100• •\./.—.——\.o I IS. • •—.—.----%0Lt)/\/‘N.\..0C%Jo I I I0CD • ••• / \ ___.—_____••S.___/N/o • • • \ ,•• \ , \• •_.., NAN 300(‘JI—.o I l•40 60 80 100Julian dayFigure 3.29: Time series of silicate in 1992 for NAN 10, 20 and 30.Chapter 3. Results and Analysis 79Nitrate 1993 Time Series0c).. — .oc’JNAN1O\/\ /\__.— ..—.o I I60 80 100•0csJ —S. •_—•NAN12—U) N____o I • •0 60 80 100••0c’J Nz NAN 15 /——. .—•ss.__%_%•U) • • •o• 60 80 100•.—. • — •o“-..NAN 20 \ •! \ • •\ —.U) \• • V \••o40 60 80 100Julian dayFigure 3.30: Time series of nitrate concentrations in 1993, inside stations.Chapter 3. Results and Analysis 80Nitrate 1993 Time Series•— ..o .—.——.csJNAN2O \•_.•\\ /\•__o I60 80 100• •N • • •_____• •/• •\0.C%JNAN 25LOo I0C”•-—._ 60 80 100•\_____• •—.—.-—— •S.— •• NAN 27 • —__ —• N•L)o• • 60 100—/• •\ /•\ z___•0C’J •NAN3OU,0 I I40 60 80 100Julian dayFigure 3.31: Time series of nitrate concentrations in 1993, outside stations.Chapter 3. Results and Analysis 81Phosphate 1993 Time SeriesCoNAN 10.• .• \ • • • /• . . ..— I—____ •—— • -.o I I I40 60 80 100CoNAN 12•.— ..— ..— • — ._••— ._.— I••o I I I40 60 80 100CDNAN 15I•cJo I I I40 60 80 100CDNAN 20•— — —•—————NI • — • I • • —.-———--•o I I40 60 80 100Julian dayFigure 3.32: Time series of phosphate concentrations in 1993, inside stations.Chapter 3. Results and Analysis 82Phosphate 1993 Time SeriesCD.NAN 20—.•___•••%__.. ___.•.—.— .o I I I.40 60 80CDNAN 25__ __/\100...._..____ ____•______.___•.o I I I40 60 80 100CDNAN 27D•.—.— ..___________•___—.• .— .— .— .— ._______•.o I I40 60 80 100CoNAN 30•• — •— • — • ••••.z• $ ••o I I I I40 60 80 100Julian dayFigure 3.33: Time series of phosphate concentrations in 1993, outside stations.Chapter 4DiscussionThe differences in the data between years made this experiment very interesting. Density structure, phytoplankton concentration and dominant species had little in commonbetween years. Factors affecting phytoplankton growth are discussed as well as the possibility of seeding with reference to both the 1992 and 1993 situations. Terms in equation 1.13 are estimated where appropriate. Finally suggestions as to how to continue andimprove experiments such as this one are made.4.1 Limitations to phytoplankton growth during the onset of the springbloomThe Sverdrup criterion as stated in chapter 1 is not suitable in balancing factors limitingphytoplankton growth to predict a spring bloom given these data. The mixed depthappears to have little meaning in the coastal environment. The critical depth, definedin equation 1.1 was calculated for these data as a minimum (see section 3.3.2). Theestimated D still indicated that light was generally not limiting to phytoplankton growththroughout the study periods (at least when compared to vertical mixing). The followingis a discussion of measured factors limiting phytoplankton growth in reference to the timeswhen phytoplankton bloomed in each of 1992 and 1993, inside and outside of the bay.83Chapter 4. Discussion 844.1.1 1992In 1992 light was not limiting at any time or location. D appears to be roughly thesame for all stations. From day 45 onward the critical depth ranged from 20 to 40 m.D did not begin to drop until approximately one week after the bloom began whenhigh concentrations of phytoplankton began to limit light penetration. During the entireperiod the density structure at all locations was reasonably well stratified. Mixed depthsas calculated in section 3.2.1 were less than 12 m everywhere and often there was strongstratification at the surface as in the first example of figure 3.13. The velocity shear overthis depth, , necessary for turbulent mixing was large. Thus profiles indicated verylimited vertical mixing of phytoplankton. Time variability in density structure appearsto be a necessary consideration at least within the bay.Figure 4.1 shows a time series of phytoplankton concentration at NAN 10 and NAN30 with possible limiting factors. The critical depth and nitrate concentration are shownfor both stations along with the flushing index as well as the principal component ofthe Ballenas wind. Concentrations of Skeletonema costatum are shown as S. costatumwas present in the highest numbers during 1992 and was representative of all genera (seefigures 3.23 and 3.24). This time series begins just before phytoplankton concentrationsshow a small increase and is truncated just after the apparent onset of the spring bloom.Note that at NAN 30 the concentrations of S. costatum after day 80 rise to 3900/ml, welloutside the range shown on the plot.The flushing index at 2 m indicates four periods of potentially favourable conditionsfor phytoplankton growth inside the bay. Between these intervals the top layer of thebay was flushed in a shorter time than that of phytoplankton generation. Note that boththe 2 and 4 m flushing indices are shown as phytoplankton was sampled in the top 3 m.Also, the index was often very different at 4 m than at 2 m.Chapter 4. Discussion 85_..tzte• -NAN3O0zoEo0Ui0(I)oU)c’J0C’Ja.0U)0‘0000000U)I:— NAN1O•.. .•... *.Z. . . .: ::::Critical depth— NAN1ONAN3OSkeletonema-. 4m .. .... Flushing Index40 50 60 70 80Julian dayFigure 4.1: 1992 time series of phytoplankton concentration and factors possibly limitingits growth for stations NAN 10 and NAN 30. The dashed line at 25m on the criticaldepth plot is the maximum depth of the bay below datum.Chapter 4. Discussion 86NAN 10Time interval (a)(Julian day) (kg/m4/day) (kg/m3/day)199227-35 +0.71 -0.0335-42 -1.5 -0.1442-49 +0.03 +0.1149-56 +0.30 056-65 -0.18 -0.0365-70 -0.16 -0.0370-75 0 +0.0575-81 -0.05 +0.07199335-39 +0.40 039-46 -0.29 +0.00446-49 +0.01 -0.00749-53 -0.03 -0.0553-56 -0.01 +0.0356-60 +0.01 +0.00860-63 +0.02 -0.0163-67 0 +0.0867-70 +0.07 -0.1370-74 +0.02 +0.0374-77 +0.28 +0.0377-82 +0.90 +0.0482-85 -1.6 -0.0385-89 +0.03 -0.0589-92 +0.01 -0.0392-96 -0.09 096-103 +0.19 -0.01Table 4.1: Phytoplankton growth parameters determined from CTD profiles for NAN10, as described in section 3.2.3. For favourable growth conditions it is suggested thatover the interval Lt, both () must be positive and I(t2o) < 0.05. Favourableparameters are listed in bold. Parameters are shown for NAN 10 only as they do notseem applicable to the outside stations. Changes in density structure were small on theoutside, thus parameters were small indicating potentially good growth conditions bythese criteria.Chapter 4. Discussion 87During the first period, days 38 through 43, there was no increase in phytoplanktonconcentration. Note that at 4 m there was an inflow >2.5 km/day during this time. Theparameters determined from density profiles (see table 4.1) were unfavourable, ()is negative and large suggesting that mixing has occurred during this period. Figure 3.14shows the profiles near the beginning and end of this interval (days 35 and 42).During the second period, day 45 through 55, there was a corresponding, but small,increase in phytoplankton concentration inside the bay. In this case the 4 m flushingindex was also favourable for phytoplankton growth, as were the two parameters shownin table 4.1. Profiles taken during and just after this period are shown in figure 3.13 (day49 and 56).The third period was from day 57 through 64, during which a very small increase in S.costatum counts occurred. At this time the flushing index at 4 m showed an inflow >2.5km/day for 2 days. The change in net stratification as measured from density profileswas also negative (although it was small), thus unfavourable to phytoplankton growth.During the fourth period, days 68 through 89, the phytoplankton concentrationseverywhere reached their highest values.Note that the increase in S. costatum at NAN 10 around day 64 does not agree witheither the flushing index or with the parameters in table 4.1. Concentrations began toincrease at both NAN 10 and 30 around day 65, however within the bay the bloom seemedto be suppressed and then fully began after day 70. Any time lag between favourableconditions and an increase in phytoplankton concentration would be expected to be ofthe order of 2-3 days. In this case however the third favourable period defined by the 2m flushing index leads the increase in phytoplankton concentration by almost a week. Itis possible however that the decrease in S. costatum was in response to the inflow thatoccurred beginning on day 64.In the Strait of Georgia conditions appear to be excellent for phytoplankton growthChapter 4. Discussion 88throughout the study. From the beginning small numbers of phytoplankton were seenin the 25 ml samples, particularly Skeletonema costatum, thus a seed was present. Thephytoplankton growth parameters determined from CTD profiles show favourable conditions at NAN 30 in 1992 with the exception of days 35 through 49. Changes in t2Owere small after day 42, with magnitudes less than the upper limit of 0.05 kg/rn3 setin section 3.2.3. Likewise there were no large negative changes in net stratification. Asnoted D calculated as a minimum was large (over 20 m) and nutrient concentrationswere high. Phytoplankton however did not begin to bloom until day 65. What limitedphytoplankton growth earlier is unknown, perhaps a similar type of horizontal advection,that was flushing the bay and suppressing a bloom there, was responsible for horizontaltransport in the Strait that also suppressed a bloom. The CTD profiles do not show largechanges of density that would be indicative of advection. However if the density field ishorizontally fairly homogeneous, advection can be occurring without causing appreciabledensity changes. The flushing index does show that after day 68, there was little exchangebetween the bay and the Strait. Perhaps the decreased exchange indicates less transportwithin the Strait as well and thus more favourable growth conditions. Examination ofthe principal component of the Ballenas wind record shows that, although winds were notparticularly strong before day 65, after that they were weaker and the direction switchedto predominantly from the northwest (figure 4.1).4.1.2 1993In 1993 the situation was very different. Density was less stratified than in 1992. Insidethe bay phytoplankton concentrations were higher throughout the experiment, generallyby at least an order of magnitude. In the Strait no large increase in phytoplanktonoccurred as it did in 1992. Concentrations were generally steady and moderately largecompared to the early part of the 1992 record. Figure 4.2 shows nitrate concentrations,Chapter 4. Discussion 89critical depths, C.debilis concentrations (all at NAN 10 and 30), the principal componentof the Ballenas wind and at7 at NAN 20 in place of the 1992 flushing indices. Recall thatduring the 1993 season Chaetoceros debilis dominated the phytoplankton community.Inside the bay phytoplankton bloomed throughout the season. The bay was wellmixed, generally to the bottom throughout the study period. Occasional decreases inconcentration could be due to light limitation. Note periods in figure 4.2 where D dropsbelow 25 m (the depth of the bay), which is shown on the plot, seem to correlate withsubsequent decreases in C. debilis concentration. The parameters in table 4.1 indicatefavourable conditions with the exception of days 39 through 46, days 49-53-56, days63-67-70, days 82-85 and possibly days 92 through 96. During all of these intervalsC. debilis counts decreased with the exception of days 53 through 56 where there wasa small increase and days 82-85 where there was a strong increase. Note that theseparameters were generally much smaller than in 1992 showing that changes in overalldensity structure tended to be small. All waters seemed to be much more homogeneousin 1993. Note that after day 96, although the parameters defined by the density profilesseem favourable, phytoplankton concentrations still continue to drop. It is suggestedthat nitrate became limiting at this point, as concentrations dropped below 1 zM to 0.4pM on day 96 and then to 0.02 pM on the last sampling date.A comparison between nitrate and C. debilis concentrations at NAN 10 is interesting.They seem related although it is difficult to tell if one signal leads the other. Earlier in therecord it would appear that nitrate dropped in response to an increase in phytoplanktonconcentration. For example, the decrease in nitrate beginning on day 56 following theincrease in C. debilis. Later however increasing nitrate may lead increasing C. debilisconcentration. Note that after nitrate concentrations increased from days 82 and 89C. debilis concentration rose until day 92 after which it decreased and nitrate becamelimiting.Chapter 4. Discussion 90(‘4C’4Julian dayFigure 4.2: 1993 time series of phytoplankton concentration and factors possibly limitingits growth for stations NAN 10 and NAN 30. The dashed line at 25m on the criticaldepth plot is the maximum depth of the bay below datum.a-0c’1zaaa(0000C,c’JE°40 50 60 70 80 90 100Chapter 4, Discussion 91In summary, conditions were favourable inside the bay during the 1993 season. Itis not possible to determine what caused decreases in C. debilis concentration. It issuggested that a combination of mixing, flushing, light availability and towards the endnitrate limitation were responsible.The outside stations during 1993 have comparatively low phytoplankton concentrations, although some phytoplankton was always present in the 25 ml samples which werecounted. Nutrient concentrations were high and critical depths generally large, althoughthe deeper CTD cast at NAN 30 indicated that the extent of vertical mixing in the Straitwas often greater than 40 m (the depth of the cast). The small increases in phytoplankton concentration which occurred at NAN 30 around day 56 and then later on day 92are difficult to explain. Note that only the latter increase was observed at NAN 27 (seefigure 3.26). Conditions seem constant around day 56. Profiles were well mixed and thevelocity shear necessary for turbulent mixing was low. The critical depth on day 57 wasactually decreasing on the outside and was around 30 m. Profiles did not begin to showany noticeable structure until day 70. At this time the estimated mixed depths fluctuated from 20 m occasionally up to 6 m, until day 96 when profiles were mixed evenlyto 40 m again. Changes in ot20 were also small. Wind conditions were low before day56 and may have allowed this small increase to occur. Stronger winds to the northwestfollowing this time may have mixed the plankton downward. On day 92 however windswere moderately strong from the southeast.In comparing the conditions at the inside and outside stations related to the largedifference in phytoplallkton concentrations, temperature was considered. It was suggestedthat perhaps higher temperatures in the bay led to excystment of phytoplankton andfaster generation times than in the Strait. In general however temperature within thetop 3 m were within 0.2 deg C of one another on the same days at all stations.In summary phytoplankton concentrations inside the bay were much higher thanChapter 4. Discussion 92outside in 1993. Thus it appears that growth conditions in the Strait were poor althoughthey were excellent in Nanoose bay. It is suggested that light was usually limiting on theoutside due to vertical mixing, while on the inside, the depth of the bay limited mixingand as a result light was not limiting there. Outside concentrations were low and did notpersist over any length of time. The source for the two small increases may have beenadvective transport rather than in situ growth.Plankton communities differed between inside and outside stations. The proportionof S. costatum and Thalassiosira spp. to Chaetoceros spp. was higher on the outside(see figure 3.27). It is suggested that perhaps S. costatum and Thalassiosira spp. areable to use light more efficiently and thus did better than Chaetoceros spp. in the Straitwhere light may have been limiting. In the bay however where light was not limiting,Chaetoceros spp. dominated. Also filter feeders do not feed as well on Chaetoceros spp.due to their cetae (Jorgenson [15]). Another possibility as to why proportions of S.costatum and Thalassiosira spp. were low in the bay may therefore be because filterfeeding bivalves are able to feed on them and not Chaetoceros spp.C. debilis often dominates blooms in the Strait during the early summer (Harrison,Fulton, Taylor and Parsons [13]). It seems unusual that it bloomed in early Februarybeginning the spring bloom. As Chaetoceros spp. frequently form resting spores [13] inthe Strait of Georgia it is suggested that perhaps Nanoose bay had a high concentrationof of C. debilis cysts in 1993 and conditions for excystment became favourable yieldinga strong C. debilis bloom.4.2 Seeding by advectionTo investigate possible seeding, the conservation equation of a scalar (equation 1.13) wasused. Changes in phytoplankton concentration with respect to time were calculated andChapter 4. Discussion 93accounted for by advection and/or the sources and sinks at that location. For seeding,advection from the potential seeding area was required.4.2.1 1992In 1992 (figure 4.1) there was really only one possible time interval, day 45 through 55, inwhich seeding could have occurred. During this interval the phytoplankton concentrationincreased inside the bay. This increase was the only appreciable one before a strong bloomin the Strait occurred. The current data showed that during this time there was a weakinflow, with the exception of a one day interval around day 48 at 2 m (at 4 m there was netinflow, throughout). This event was terminated by a negative flushing index indicatingthat net transport was into the bay at the surface. It is suggested that phytoplanktonwere grazed by oysters and flushed out of the bay at depth and did not provide the seedpopulation for the bloom that occurred later outside.The large increase in phytoplankton concentration at NAN 30 began on day 65 andwas much stronger than in Nanoose bay. In the bay concentrations did not begin to riseuntil after day 65; an increase was found on day 69 (the next sampling date). Up to day67 the flow at 2 and 4 m was into the bay. Thus in 1992 the bay did not seed the Strait.If any seeding occurred given the net transport, it is more likely that the Strait providedthe seed for the bay.4.2.2 1993In 1993 the situation was very different. There were many intervals in which to investigatepossible seeding. There was sufficient spatial resolution to calculate gradients, howeverno current data were available.Chapter 4. Discussion 94Use of the conservation equationEquation 1.13 was evaluated by considering one dimension only, with derivatives calculated as averages over a single time interval. Thus equation 1.13 becomes:dC dC-a-- = —u.--+G(t)(—z—b—s) (4.1)Terms in equation 4.1 were evaluated as follows.ac C21 42(öC) 1( G1 — C(_i)i + 0i2 — C(j_l)2+C(+1)— Cjl + C(t+l)2 — Cr2) (4.3)4 —— xiC(t) = + Cii (44)The concentration of Chaetoceros debilis was used to represent the quantity C. It waschosen as it was the dominant species at all locations and its numbers were very high.The indices i and j are used to denote location and time respectively. For locations,i was considered increasing in the positive x-direction. For example if NAN 12 werebeing considered then (i + 1) would be NAN 15 and (i — 1) NAN 10. As derivativeswere calculated centred on one time interval j was 1 or 2, the beginning and end ofthat interval respectively. At end stations, such as NAN 10, the spatial gradient at theboundary was simply assumed to be zero.Station 25 was used as an end point for calculations involving both inside and outsidestations, For stations 10 through 25 the x-direction was east-west (positive moving outof the bay). For the outside stations 25 through 30, the x-direction was essentiallynorthwest-southeast, increasing in the northwest direction. Note that at NAN 25 x andy terms could have been used, however it seemed that there were already a sufficientnumber of variables.Chapter 4. Discussion 95A range for the sum of the rates in the source and sink term (j — b — z— s) waschosen using reasonable estimates for each rate. Afterwards, the corresponding range ofvelocities required to satisfy equation 1.13 was calculated. Where possible, combinationsof (p — b — z — s) and the velocity u were chosen to agree between stations. For example,the velocities at stations 12 and 15 were assumed to be equal because the stations werejust less than 1 km apart and both were situated in a channel which is only 0.5 kmwide. This assumption put another restriction on the equations. Likewise at the outsidestations 27 and 30, where conditions for phytoplankton growth appeared to be similar(density profiles and Secchi disc depths agreed between the two and nutrients were high),a constant value for (p — b — z — .s) was chosen.Choice of biological ratesA reasonable range for generation times during the 1993 season was taken as (0.5-1.5)days1 (Parsons, Takahashi and Hargrave [22]).For zooplankton grazing an upper limit for z was chosen using a maximum concentration of copepods and a maximum filtering rate for each animal of 200m1/day fromParsons, Takahashi and Hargrave [22]. The concentration used was 2/i as determined byLeBrasseur et al. [21] of the dominant copepod Neocalanus piumchrus during the springin the Strait of Georgia. The calculated maximum rate (considering the time for 2 cope-pods to filter 1/e 1) was 1 days’. A lower limit for z was assumed to be zero as for lowphytoplankton concentrations zooplankton do not graze (Parsons [19]). Thus the rangefor zwas (0-1)days’.To determine b, the oyster concentration in the bay was assumed to be 30/rn2 forthe entire area of the bay. The value was chosen by observation of the shoreline and theshallows, and is hoped to represent an upper limit when used for all depths of the bay.This estimate suggests that there are 83 million oysters in Nanoose bay. Their filteringChapter 4. Discussion 96rates were taken to be the same as that of mussels in 8.5 deg C water in Friday Harbour,(from Kine [5]). Oysters and mussels are classified in the same habitat group and havefiltering rates which are of the same order of magnitude, [5]. The result was a rangein b of (O.2-O.5)days’ within Nanoose bay. Note that the equation 1.13 requires thatthe oysters are being continually supplied with new water, and thus fresh phytoplankton.Given the density profiles in 1993 and the current data in 1992, this assumption seemsreasonable. The upper limit of this rate suggests that the 83 million oysters in the baycould filter the entire volume of the bay in just under one week, which is within theestimated range of flushing times.The sinking rate s was determined using Parsons, Takahashi and Hargrave [22], tobe about O.ldays’. Given the size of the other rates s was assumed to be zero for livephytoplankton. Where conditions were poor and phytoplankton were probably dying it islikely that s was larger, as dead phytoplankton sink an order of magnitude more quicklythan live ones. Thus s was considered nonzero, ranging from (O-O.1)days’, outside thebay (where conditions for phytoplankton growth seemed to be poor) and inside towardsthe end of the study when nitrate became limiting.Once a range of velocities was estimated for each location in a given interval, theywere compared to those at adjacent stations, expecting them to be of the same orderand direction. If the magnitude of the velocity was reasonable (also considering the timeperiod over which it was maintained) its direction was considered. Two indicators fordirection were used. For the inside station t7 at NAN 20 was used as described at theend of section 3.1. t7 were decreasing with time (see figure 4.2) currents were expectedto be into the bay. A constant or increasing Ut7 put no restriction on current direction.For the outside stations wind data were used. Note that the correlation between theprincipal component of the Ballenas wind and the v current velocity was 0.5 at 2 and 4m. This is not a strong correlation, however it was used only to indicate direction.Chapter 4. Discussion 97The time series were investigated concentrating on times when numbers of Chaetocerosdebilis at the outside stations increased. Because conditions for phytoplankton growthappear poor for in situ growth, as discussed in the previous section, advection is assumedto be responsible for the increases in phytoplankton concentrations seen there. For theinside stations special attention was paid to intervals with weak phytoplankton gradientsand also to periods in which the change in C with time was close to zero. Where gradientswere weak, current velocity became unimportant as the advective term was small and adirect estimate of (p — b — z — s) could be made. Similarly where C was constant in time,one term was eliminated and advection was balanced by sources and sinks.Application of the equationA chronological summary of the results follows. All rates have units of days’ andvelocities are in km/day, (1 km/day = 1.16 cm/s).Chaetoceros debilis was present inside the bay from the beginning of the experimentonward. The first time interval investigated was day 35-39, where information was available on both days only for the inside stations. It was found from stations 12 and 15 thata current of 0.6 km/day into the bay and total rates, (p — b — z — s), of +0.3 days1 atall stations provided a reasonable solution to the conservation equation 4.1. Assuminga growth rate p of 0.7 days1, the sum of the sinks would be 0.4 days1, which seemsreasonable expecting b to dominate and z and s to be small.Note that NAN 30 was first sampled on day 39 and no Chaetoceros debilis was foundin the 25 ml sample that was counted, although C. debilis was seen at NAN 27. On day42 Chaetoceros debilis appeared at NAN 30 as well as NAN 27. For advective transportfrom NAN 25 a northwest current of approximately 1 km/day was necessary over the3 day period to balance the increase in C. debilis. This current seems very reasonableas the wind was blowing predominantly from the southeast during this time. The totalChapter 4. Discussion 98rate ( — b — z — s) was assumed to be zero in this case. Growth conditions wereapparently poor and benthic grazing was not considered important in the Strait. Alsophytoplankton concentrations were low so if zooplankton were present they were assumednot to be grazing. Note that there are no data from NAN 25 and 27 (only NAN 20 and30) on day 42 so no comparison can be made.The peak at NAN 25 on day 49 was investigated. The rate ( — z — s) was assumedto be zero at this station as well. Using data from the inside stations a transport of 2km/day out of the bay was necessary to balance this increase in phytoplankton giventhe gradient of C at the mouth of the bay. Over this time period however t7 becamesmaller suggesting that transport was into the bay. Using an optimistic positive growthrate of 0.5 still requires a small transport out of the bay. It appears in this case that thephytoplankton came from elsewhere, perhaps even the shallows on the south shore justoutside the mouth of the bay.The period from day 53 to 56 has small spatial gradients at the mouth of the bay.Rates were calculated from these data as they were not sensitive to changes in velocity.It appears that at stations 10 through 20 rates decreased to about (0.1-0.2) days’. Itis suggested that increased grazing by zooplankton at this time may be responsible.The outside stations during the same interval and on to day 57 were investigated. Onday 57 concentrations of C. debilis reached 670/mi. Assuming the source and sink termto be zero again, a transport rate of 0.3 km/day NW for both NAN 27 and NAN 30 wasrequired from day 53 to 56. To account for the further increase in C at NAN 30 on day57 a transport of 3-4 km/day would be required over one day. The later current is notexcessive considering the 1992 current observations and that during the entire period thewind was blowing from the southeast. It is possible that the plankton was carried fromstation 25 up the Strait, although plankton at that location could easily have originatedfrom the shallows outside Nanoose bay or elsewhere.Chapter 4. Discussion 99Later in the record total rates seemed to decrease at the inside stations. Using theinterval from day 77 through 82, where again gradients were small, the total rate at NAN10 was determined to be -0.4 days’ and -0.2 days’ at NAN 12 and 15. These valuesmay be due to an increase in zooplankton and thus more intense grazing as well as anonzero value of s as nutrients may be becoming more scarce.Investigating the last increase in C. debilis observed at all of the outside stationssuggests that NAN 25 was not the source of C. debilis in that case. Neglecting sourcesand sinks, a transport of- 3 km/day at both NAN 27 and NAN 30 was required, whichis from the opposite direction to NAN 25. For transport to occur from NAN 25 a growthrate of at least 0.6 days1 would be required, which seems unlikely at this time. Likewiseit appears that changes in C at NAN 25 over this period were balanced by currents goingrnto Nanoose bay (u -0.1 km/day) as estimated from gradients at the mouth.In summary it appears that it is possible for Nanoose bay to provide the seed phytoplankton population for the adjacent area of the Strait of Georgia at times. It is alsopossible that other areas may provide the seed and it is suggested that a combinationis likely and seeding areas are different at different times. Terms in the conservationequation were difficult to evaluate, even with all of the assumptions, as there were manyunknown variables. Also terms tend to be of the same order. Nonetheless the approximations seemed to yield reasonable values which agreed between adjacent stations, especiallyat the mouth of the bay where the spatial resolution was the highest. The first time C.debilis appeared at NAN 30 it could easily have originated from Nanoose bay, assumingthat growth conditions at this time were poor in the Strait and advection was responsible.Chapter 4. Discussion 1004.3 SummaryThe two seasons that were investigated were very different. In 1992 density structure wasstratified with respect to 1993 with more brackish water, assumed to be the influence ofthe Fraser River. Net transport in 1992 was into the bay at upper and middle depthsand it appears that the bay was flushed too rapidly to allow phytoplankton to bloomearlier in the season. Nutrients and light were not limiting at any time or location. In1992 a strong phytoplankton bloom occurred in the bay and the Strait simultaneouslybeginning around day 65-70. Seeding was not possible in this year as transport was intothe bay at the surface and middle depths and the bloom did not occur earlier in the baythan in the Strait.In 1993 phytoplankton concentrations were appreciable in Nanoose bay from the firstsampling day onward suggesting that growth conditions were good there. It appearsthat the bay was generally mixed to the bottom. It is suggested that phytoplanktonconcentrations were comparatively low in the Strait because light was limiting due tovertical mixing deeper than the critical depth. It is suggested that growth conditionsat the inside stations were limited at different times by a combination of light, mixing,flushing and nitrate limitation toward the end of the study. Seeding from the bay duringthis season was possible although it is likely that different areas provided the seed atdifferent times and in the absence of current measurements it is certainly not possible tobe conclusive.The differences in nature of phytoplankton growth (timing, concentrations, and speciesdominance at all locations) between both years suggests that while coastal environmentsare complicated they provide many different possibilities for phytoplankton blooms leading to biological diversity from year to year. In 1992 the bloom began later (day 65-70)than in 1993 apparently when phytoplankton growth conditions became favourable at allChapter 4. Discussion 101sampling locations. During this year circulation was such that the bay was flushed in ashorter time than that of phytoplankton generation. In 1993 phytoplankton concentrations and growth conditions varied between the outside and inside stations. Phytoplankton bloomed in the bay much earlier than in 1992 (day 35 onward) and concentrationswere higher in the Strait than they were proceeding the bloom in 1992. It is likely thatin situ growth conditions were poor on the outside and higher counts of phytoplanktonwere due to advection from areas such as Nanoose bay where concentrations were veryhigh. Also the dominant species at all locations in 1993 was Chaetoceros debilis, whichhas the ability to form resting spores (Harrison et al. [13]). It appears that excystmentof C. debilis in the bay led to a strong bloom which subsequently influenced species composition in the Strait. Thus in 1993 it was possible that the bay and other potentialseeding areas had a major influence on phytoplankton concentration and composition inthe Strait while in 1992 there was no influence from one area on the other.4.4 Suggestions for improving or continuing this experimentIf this experiment were to continue there are several additions and changes that mayimprove results. Daily sampling is necessary as horizontal advection can play a majorrole. For example, the 1992 current record suggests that the bay can be flushed in lessthan one day. Note that the 1993 data showed a peak in Chaetoceros debilis on day 57at NAN 30 while missing a possible increase at NAN 27 as it was not sampled on thatday. Also, generation times may be as short as 18 hours during the spring bloom andphytoplankton disappear rapidly under adverse conditions.Spatial resolution is necessary. Although there was much more energy spent analyzing the 1993 results due to the increased number of stations, the spatial resolution atChapter 4. Discussion 102the mouth of the bay proved very useful in estimates made using the conservation equation 1.13. Ranges for parameters within the equations were narrowed significantly. Forthe outside stations estimates were vague and more difficult. If the total rate (IL—b—z—s)had not been ignored the calculations would have become even more ambiguous.Also in this experiment only phytoplankton and chlorophyll a concentrations weremeasured. The rates in the sum of biological sources and sinks (equation 1.13) weredifficult to distinguish between as the measured C was the result of all influences (growthand grazing etc. as well as advection). Primary productivity rate measurements providea measure of the true standing stock and thus it could be separated from the sink termsin the sum of all of the rates. Although primary productivity rate measurements aredifficult to make in the field (Parsons, Maita and Lalli [20]) they would be very useful inan experiment of this type.Replicates in biological data can also improve results significantly, for example thechlorophyll a data.Vertical turbulent diffusion has been neglected in this problem. It is recognized thatit may be important. It is suggested that vertical profiles of biological parameters betaken, especially for nutrients and species composition.The absence of current data in the 1993 data set is unfortunate. Without themnothing can be conclusively stated from this experiment. Current measurements areexpensive and time consuming. It is suggested that since Lagrangian motion is of interestin this problem, drogues would be more appropriate than current meters. One couldsample daily and when the first increase in phytoplankton concentration was observed,place a drogue at that location and track its motion. Sampling could be done followingthe drogue as well as at the other regular locations.Appendix ADominant genera in species composition1992J day NAN 10 NAN 20 NAN 3027 Melosjra sp. 0.5 S. costatum 0.3 S. costatum 0.537 Thalassiosira sp. 0.8 Thalassionema sp. 0.2 S. costatum 0.742 S. costatum 5 S. costatum 7 S. costatum 645 5. costatum 16 S. costatum 12 S. costatum 248 5. costatum 39 S. costatum 22 S. costatum 249 S. costatum 48 S. costatum 34 S. co.statum 351 S. costatum 36 S. costatum 25 Corethron sp. 256 Thalassiosira sp. 2 S. costatum 8 Thalassiosira sp. 0.559 Thalassiosira sp. 5 S. costatum 2 S. costatum 562 S. costaturn 24 5. costatum 12 S. costatum 765 Chaetoceros sp. 0.5 5. costatum 1.2 S. costaturn 1765 5. costatum 1.1 5. costatum 2 5. costatum 1069 5. costatum 190 5. costatum 258 5. costatum 14070 5. costatum 18 5. costatum 76 5. costatum 18075 5. costatum 350 5. costatum 325 5. costatum 17079 Thalassiosira sp. 750 S. costatum 900 S. costatum 300081 Thaiassiosira sp. 360 5. costatum 670 S. costatum 3900100 Schrooderella sp. 610 Chaetoceros sp. 330 Chaetoceros sp. 15Table A.1: Dominant genera with abundance for 1992. All numbers have units of cells/ml.Note that on day 65 samples were drawn by the Nanoose personnel as well as myself.Both samples are included for comparison.103Appendix A Dominant genera 1041993NANJulian day 5 10 12 15 20 25 27 3035 600 450 60039 340 2800 1000 660 80 40 30 <0.542 2000 700 34046 60 500 650 350 300 130 170 15049 160 3800 1600 1100 2300 2400 40 10050 1400 200053 270 2100 2300 2300 2200 1200 20 3556 65 3300 3400 2500 2400 550 300 36057 4800 1200 67060 60 5600 4100 2000 150063 <0.5 3100 3200 1500 440 25 1 3067 330 800 3400 2300 1500 46070 1 300 340 850 300 300 300 14074 500 1300 1700 1600 1300 30 60 7077 <0.5 2800 3500 2500 2800 2000 80 23082 <0.5 8 140 1000 900 650 30 15086 830 1400 2500 1500 1700 12 6 1489 230 2200 2600 3000 1800 300 200 40092 300 5300 4400 4200 2700 800 1100 180096 85 2800 4700 3600 2400 300 400 100103** 12 3000 2400 2200 1800 540Table A.2: Dominant genera with abundance for 1993. Numbers are of Chaetocerosdebilis cells/ml with the exception of day 103. Note that C. debilis was the dominantspecies throughout the experiment until day 103, when Skeleton ema costatum becamedominant (** S. costatum cells/ml). Missing counts correspond to stations that were notsampled on that day.Bibliography[1] Baker, P. 1992. Low frequency residual circulation in Knight Inlet, a fjord of coastalBritish Columbia., Masters Thesis, The University of British Columbia. 184 pages.[2] Campbell J. and Aarup T. 1989. Photosynthetically available radiation at high latitudes. Limnology and Oceanography, 34 1490—1499.[3] Cloern, J. E. 1991. Tidal stirring and phytoplankton bloom dynamics in an estuary.Journal of Marine Research, 49, 203—22 1.[4] Cloern, J. E. 1982. Does Benthos Control Phytoplankton Biomass in South SanFrancisco Bay? Marine Ecology Prog. Series, 9 191—202.[5] Conover, R. J. 1978. Transformation of organic matter. Vol 4 in Marine Ecology:A Comprehensive, Integrated Treatise on Life in Oceans and Coastal Waters. (ed.Otto Kine). John Wiley and Sons, New York. 277—288.[6] Cullen, J. J. 1982. The deep Chlorophyll Maximum: Comparing Vertical Profiles ofChlorophyll a. Can. J. Fish. Aquat. Sci., 39 791—802.[7] Cupp, E. E. 1943. Marine Plankton Diatoms of the West Coast of North America.University of California Press, Berkeley, California. 221 pages.[8] Falkowski, P. G. and Owens, T.G., 1978. Effects of Light Intensity on Photosynthesisand Dark Respiration in 6 species of Marine Phytoplankton. Marine Biology, 45,289—295.[9] Freeland, H. J. and Farmer, D. M., 1980. Circulation and Energetics of a Deep,Strongly Stratified Inlet Can. J. Fish. Aquat. Sci., 37 1398—1410.[10] Godin, G. 1972. The Analysis of Tides. University of Toronto Press, Toronto,Canada. 264 pages.[11] Hansen, D. V. and Rattray, M. Jr. 1966. New dimensions in estuary classification.Limnology and Oceanography, 11 319—326.[12] Harrison, P. J., Clifford, P. J., Cochlan, W.P., Yin K., St John, M.A., Thompson,P.A., Sibbald and Albright, L. J. 1991. Nutrient and plankton dynamics in the FraserRiver Plume, Strait of Georgia, British Columbia. Marine Ecology Progress Series,70 291—304.105Bibliography 106[13] Harrison P. J., Fulton J. D., Taylor F. J. R. and Parsons T.R. 1983. Review of thebiological oceanography of the Strait of Georgia: pelagic environment. Can. J. Fish.Aquat. Sci., 40 1064—1094.[14] Harrison, P. J. and Turpin D. H. 1979. Limiting nutrient patchiness and its role inphytoplankton ecology. J. exp. mar. Biol. Ecol., 39 151—166.[15] Jorgenson, C. B. 1966. Biology of Suspension Feeding. International Series of Monographs in Pure and Applied Biology, Zoology Division. Volume 27. Pergamon Press,Oxford, U.K. 357 pages.[16] Kollstad, T. F. and Hansen, S. E. 1985. An Investigation of the Performance of 4Different Current Meters When Applied in the Wave Zone. In: Advances in Underwater Technology and Offshore Engineering Vol. 4:Evaluation, Comparison andCalibration of Oceanographic Instruments. Proceedings of an International Conference (Ocean Data). Society for Underwater Technology, London, England. 223—245.[17] Lawson, K. D. et a!. 1983. The Development of a Spherical, Electromagnetic Current Meter. In: Proceedings of Oceans 1983, Vol. 1 Technical Papers. Institute ofElectrical and Electronics Engineers, Piscataway, New Jersey. 187—193.[18] LeBlond, P. H. and Mysak, L. A. 1978. Waves in the Ocean. Elsevier Science Publishers B. V., Amsterdam, The Netherlands. 602 pages.[19] Parsons, T. R. and LeBrasseur R. J. 1970. The availability of food to different trophiclevels in the marine food chain, in Marine Food Chains. (ed. J. H. Steele). Oliverand Boyd, Edinburgh, U. K. 325—343.[20] Parsons, T. R., Maita, Y. and Lalli, C. M. 1984. A Manual of Chemical and BiologicalMethods for Seawater Analysis. Pergamon Press, Oxford, U.K. 173 pages.[21] Parsons, T. R., Stephens K. and LeBrasseur R. J. 1969. Production studies in theStrait of Georgia. Part 1. Primary production under the Fraser River plume, February to May, 1967. J. exp. mar. Biol. Ecol., 3 51—61.[22] Parsons, T. R., Takahashi, M. and Hargrave B. 1973. Biological Oceanographic Processes. Pergamon Press, Oxford, U.K. 332 pages.[23] Pond, S. and Pickard, G. L. 1983. Introductory Dynamical Oceanography, 2nd edition. Pergamon Press, Oxford, U.K. 329 pages.[24] Press, W. H., Flanners, B. P., Teukolsky, S. A. and Vetterling, V. T. 1988. NumericalRecipes in C, The Art of Scientific Computing. Cambridge University Press. 735pages.Bibliography107[25] Stacey, M. W., Pond, S., LeBlond, P. H., Freeland, H. J. and Farmer D. M. 1987.An Analysis of the Low-Frequency Current Fluctuations in the Strait of Georgia,from June 1984 until January 1985. Journal of Physical Oceanography. 17, No. 3,326—342.[26] Statistical Sciences, Inc. S-PLUS User’s Manual, Version 3.1 Supplement, Seattle:Statistical Sciences, Inc., 1992.[27] Sutherland, T.and C. Leonard, 1992. A segmented pipe sampler for integrated profiling of the upper water column. J. Plankton Res., (in press).[28] Sverdrup, H. U., 1953. On conditions for the vernal blooming of phytoplankton. J.Cons. Explor. Mer, 18, 287—295.[29] Thompson, R. 1981. Oceanography of the British Columbia Coast. Canadian SpecialPublication of Fisheries and Aquatic Sciences 56, Ottawa. 139—185.[30] de Young, B. 1986. The circulation and internal tide of Indian Arm, B. C. PhDThesis, University of British Columbia. 175 pages.


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